diff options
| author | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-06-03 20:07:58 +0000 |
|---|---|---|
| committer | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-06-03 20:07:58 +0000 |
| commit | fc2b129d31cbb474bbebfa0baa8537238f6332ed (patch) | |
| tree | 5c6055c1be787787ae2d13b144f280740e235f79 /docs/search.js | |
| parent | Adding upstream version 24.0.0. (diff) | |
| download | sqlglot-fc2b129d31cbb474bbebfa0baa8537238f6332ed.tar.xz sqlglot-fc2b129d31cbb474bbebfa0baa8537238f6332ed.zip | |
Adding upstream version 24.1.0.upstream/24.1.0
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
Diffstat (limited to 'docs/search.js')
| -rw-r--r-- | docs/search.js | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/docs/search.js b/docs/search.js index c5428b9..864463b 100644 --- a/docs/search.js +++ b/docs/search.js @@ -1,6 +1,6 @@ window.pdocSearch = (function(){ /** elasticlunr - http://weixsong.github.io * Copyright (C) 2017 Oliver Nightingale * Copyright (C) 2017 Wei Song * MIT Licensed */!function(){function e(e){if(null===e||"object"!=typeof e)return e;var t=e.constructor();for(var n in e)e.hasOwnProperty(n)&&(t[n]=e[n]);return t}var t=function(e){var n=new t.Index;return n.pipeline.add(t.trimmer,t.stopWordFilter,t.stemmer),e&&e.call(n,n),n};t.version="0.9.5",lunr=t,t.utils={},t.utils.warn=function(e){return function(t){e.console&&console.warn&&console.warn(t)}}(this),t.utils.toString=function(e){return void 0===e||null===e?"":e.toString()},t.EventEmitter=function(){this.events={}},t.EventEmitter.prototype.addListener=function(){var e=Array.prototype.slice.call(arguments),t=e.pop(),n=e;if("function"!=typeof t)throw new TypeError("last argument must be a function");n.forEach(function(e){this.hasHandler(e)||(this.events[e]=[]),this.events[e].push(t)},this)},t.EventEmitter.prototype.removeListener=function(e,t){if(this.hasHandler(e)){var n=this.events[e].indexOf(t);-1!==n&&(this.events[e].splice(n,1),0==this.events[e].length&&delete this.events[e])}},t.EventEmitter.prototype.emit=function(e){if(this.hasHandler(e)){var t=Array.prototype.slice.call(arguments,1);this.events[e].forEach(function(e){e.apply(void 0,t)},this)}},t.EventEmitter.prototype.hasHandler=function(e){return e in this.events},t.tokenizer=function(e){if(!arguments.length||null===e||void 0===e)return[];if(Array.isArray(e)){var n=e.filter(function(e){return null===e||void 0===e?!1:!0});n=n.map(function(e){return t.utils.toString(e).toLowerCase()});var i=[];return n.forEach(function(e){var n=e.split(t.tokenizer.seperator);i=i.concat(n)},this),i}return e.toString().trim().toLowerCase().split(t.tokenizer.seperator)},t.tokenizer.defaultSeperator=/[\s\-]+/,t.tokenizer.seperator=t.tokenizer.defaultSeperator,t.tokenizer.setSeperator=function(e){null!==e&&void 0!==e&&"object"==typeof e&&(t.tokenizer.seperator=e)},t.tokenizer.resetSeperator=function(){t.tokenizer.seperator=t.tokenizer.defaultSeperator},t.tokenizer.getSeperator=function(){return t.tokenizer.seperator},t.Pipeline=function(){this._queue=[]},t.Pipeline.registeredFunctions={},t.Pipeline.registerFunction=function(e,n){n in t.Pipeline.registeredFunctions&&t.utils.warn("Overwriting existing registered function: "+n),e.label=n,t.Pipeline.registeredFunctions[n]=e},t.Pipeline.getRegisteredFunction=function(e){return e in t.Pipeline.registeredFunctions!=!0?null:t.Pipeline.registeredFunctions[e]},t.Pipeline.warnIfFunctionNotRegistered=function(e){var n=e.label&&e.label in this.registeredFunctions;n||t.utils.warn("Function is not registered with pipeline. This may cause problems when serialising the index.\n",e)},t.Pipeline.load=function(e){var n=new t.Pipeline;return e.forEach(function(e){var i=t.Pipeline.getRegisteredFunction(e);if(!i)throw new Error("Cannot load un-registered function: "+e);n.add(i)}),n},t.Pipeline.prototype.add=function(){var e=Array.prototype.slice.call(arguments);e.forEach(function(e){t.Pipeline.warnIfFunctionNotRegistered(e),this._queue.push(e)},this)},t.Pipeline.prototype.after=function(e,n){t.Pipeline.warnIfFunctionNotRegistered(n);var i=this._queue.indexOf(e);if(-1===i)throw new Error("Cannot find existingFn");this._queue.splice(i+1,0,n)},t.Pipeline.prototype.before=function(e,n){t.Pipeline.warnIfFunctionNotRegistered(n);var i=this._queue.indexOf(e);if(-1===i)throw new Error("Cannot find existingFn");this._queue.splice(i,0,n)},t.Pipeline.prototype.remove=function(e){var t=this._queue.indexOf(e);-1!==t&&this._queue.splice(t,1)},t.Pipeline.prototype.run=function(e){for(var t=[],n=e.length,i=this._queue.length,o=0;n>o;o++){for(var r=e[o],s=0;i>s&&(r=this._queue[s](r,o,e),void 0!==r&&null!==r);s++);void 0!==r&&null!==r&&t.push(r)}return t},t.Pipeline.prototype.reset=function(){this._queue=[]},t.Pipeline.prototype.get=function(){return this._queue},t.Pipeline.prototype.toJSON=function(){return this._queue.map(function(e){return t.Pipeline.warnIfFunctionNotRegistered(e),e.label})},t.Index=function(){this._fields=[],this._ref="id",this.pipeline=new t.Pipeline,this.documentStore=new t.DocumentStore,this.index={},this.eventEmitter=new t.EventEmitter,this._idfCache={},this.on("add","remove","update",function(){this._idfCache={}}.bind(this))},t.Index.prototype.on=function(){var e=Array.prototype.slice.call(arguments);return this.eventEmitter.addListener.apply(this.eventEmitter,e)},t.Index.prototype.off=function(e,t){return this.eventEmitter.removeListener(e,t)},t.Index.load=function(e){e.version!==t.version&&t.utils.warn("version mismatch: current "+t.version+" importing "+e.version);var n=new this;n._fields=e.fields,n._ref=e.ref,n.documentStore=t.DocumentStore.load(e.documentStore),n.pipeline=t.Pipeline.load(e.pipeline),n.index={};for(var i in e.index)n.index[i]=t.InvertedIndex.load(e.index[i]);return n},t.Index.prototype.addField=function(e){return this._fields.push(e),this.index[e]=new t.InvertedIndex,this},t.Index.prototype.setRef=function(e){return this._ref=e,this},t.Index.prototype.saveDocument=function(e){return this.documentStore=new t.DocumentStore(e),this},t.Index.prototype.addDoc=function(e,n){if(e){var n=void 0===n?!0:n,i=e[this._ref];this.documentStore.addDoc(i,e),this._fields.forEach(function(n){var o=this.pipeline.run(t.tokenizer(e[n]));this.documentStore.addFieldLength(i,n,o.length);var r={};o.forEach(function(e){e in r?r[e]+=1:r[e]=1},this);for(var s in r){var u=r[s];u=Math.sqrt(u),this.index[n].addToken(s,{ref:i,tf:u})}},this),n&&this.eventEmitter.emit("add",e,this)}},t.Index.prototype.removeDocByRef=function(e){if(e&&this.documentStore.isDocStored()!==!1&&this.documentStore.hasDoc(e)){var t=this.documentStore.getDoc(e);this.removeDoc(t,!1)}},t.Index.prototype.removeDoc=function(e,n){if(e){var n=void 0===n?!0:n,i=e[this._ref];this.documentStore.hasDoc(i)&&(this.documentStore.removeDoc(i),this._fields.forEach(function(n){var o=this.pipeline.run(t.tokenizer(e[n]));o.forEach(function(e){this.index[n].removeToken(e,i)},this)},this),n&&this.eventEmitter.emit("remove",e,this))}},t.Index.prototype.updateDoc=function(e,t){var t=void 0===t?!0:t;this.removeDocByRef(e[this._ref],!1),this.addDoc(e,!1),t&&this.eventEmitter.emit("update",e,this)},t.Index.prototype.idf=function(e,t){var n="@"+t+"/"+e;if(Object.prototype.hasOwnProperty.call(this._idfCache,n))return this._idfCache[n];var i=this.index[t].getDocFreq(e),o=1+Math.log(this.documentStore.length/(i+1));return this._idfCache[n]=o,o},t.Index.prototype.getFields=function(){return this._fields.slice()},t.Index.prototype.search=function(e,n){if(!e)return[];e="string"==typeof e?{any:e}:JSON.parse(JSON.stringify(e));var i=null;null!=n&&(i=JSON.stringify(n));for(var o=new t.Configuration(i,this.getFields()).get(),r={},s=Object.keys(e),u=0;u<s.length;u++){var a=s[u];r[a]=this.pipeline.run(t.tokenizer(e[a]))}var l={};for(var c in o){var d=r[c]||r.any;if(d){var f=this.fieldSearch(d,c,o),h=o[c].boost;for(var p in f)f[p]=f[p]*h;for(var p in f)p in l?l[p]+=f[p]:l[p]=f[p]}}var v,g=[];for(var p in l)v={ref:p,score:l[p]},this.documentStore.hasDoc(p)&&(v.doc=this.documentStore.getDoc(p)),g.push(v);return g.sort(function(e,t){return t.score-e.score}),g},t.Index.prototype.fieldSearch=function(e,t,n){var i=n[t].bool,o=n[t].expand,r=n[t].boost,s=null,u={};return 0!==r?(e.forEach(function(e){var n=[e];1==o&&(n=this.index[t].expandToken(e));var r={};n.forEach(function(n){var o=this.index[t].getDocs(n),a=this.idf(n,t);if(s&&"AND"==i){var l={};for(var c in s)c in o&&(l[c]=o[c]);o=l}n==e&&this.fieldSearchStats(u,n,o);for(var c in o){var d=this.index[t].getTermFrequency(n,c),f=this.documentStore.getFieldLength(c,t),h=1;0!=f&&(h=1/Math.sqrt(f));var p=1;n!=e&&(p=.15*(1-(n.length-e.length)/n.length));var v=d*a*h*p;c in r?r[c]+=v:r[c]=v}},this),s=this.mergeScores(s,r,i)},this),s=this.coordNorm(s,u,e.length)):void 0},t.Index.prototype.mergeScores=function(e,t,n){if(!e)return t;if("AND"==n){var i={};for(var o in t)o in e&&(i[o]=e[o]+t[o]);return i}for(var o in t)o in e?e[o]+=t[o]:e[o]=t[o];return e},t.Index.prototype.fieldSearchStats=function(e,t,n){for(var i in n)i in e?e[i].push(t):e[i]=[t]},t.Index.prototype.coordNorm=function(e,t,n){for(var i in e)if(i in t){var o=t[i].length;e[i]=e[i]*o/n}return e},t.Index.prototype.toJSON=function(){var e={};return this._fields.forEach(function(t){e[t]=this.index[t].toJSON()},this),{version:t.version,fields:this._fields,ref:this._ref,documentStore:this.documentStore.toJSON(),index:e,pipeline:this.pipeline.toJSON()}},t.Index.prototype.use=function(e){var t=Array.prototype.slice.call(arguments,1);t.unshift(this),e.apply(this,t)},t.DocumentStore=function(e){this._save=null===e||void 0===e?!0:e,this.docs={},this.docInfo={},this.length=0},t.DocumentStore.load=function(e){var t=new this;return t.length=e.length,t.docs=e.docs,t.docInfo=e.docInfo,t._save=e.save,t},t.DocumentStore.prototype.isDocStored=function(){return this._save},t.DocumentStore.prototype.addDoc=function(t,n){this.hasDoc(t)||this.length++,this.docs[t]=this._save===!0?e(n):null},t.DocumentStore.prototype.getDoc=function(e){return this.hasDoc(e)===!1?null:this.docs[e]},t.DocumentStore.prototype.hasDoc=function(e){return e in this.docs},t.DocumentStore.prototype.removeDoc=function(e){this.hasDoc(e)&&(delete this.docs[e],delete this.docInfo[e],this.length--)},t.DocumentStore.prototype.addFieldLength=function(e,t,n){null!==e&&void 0!==e&&0!=this.hasDoc(e)&&(this.docInfo[e]||(this.docInfo[e]={}),this.docInfo[e][t]=n)},t.DocumentStore.prototype.updateFieldLength=function(e,t,n){null!==e&&void 0!==e&&0!=this.hasDoc(e)&&this.addFieldLength(e,t,n)},t.DocumentStore.prototype.getFieldLength=function(e,t){return null===e||void 0===e?0:e in this.docs&&t in this.docInfo[e]?this.docInfo[e][t]:0},t.DocumentStore.prototype.toJSON=function(){return{docs:this.docs,docInfo:this.docInfo,length:this.length,save:this._save}},t.stemmer=function(){var e={ational:"ate",tional:"tion",enci:"ence",anci:"ance",izer:"ize",bli:"ble",alli:"al",entli:"ent",eli:"e",ousli:"ous",ization:"ize",ation:"ate",ator:"ate",alism:"al",iveness:"ive",fulness:"ful",ousness:"ous",aliti:"al",iviti:"ive",biliti:"ble",logi:"log"},t={icate:"ic",ative:"",alize:"al",iciti:"ic",ical:"ic",ful:"",ness:""},n="[^aeiou]",i="[aeiouy]",o=n+"[^aeiouy]*",r=i+"[aeiou]*",s="^("+o+")?"+r+o,u="^("+o+")?"+r+o+"("+r+")?$",a="^("+o+")?"+r+o+r+o,l="^("+o+")?"+i,c=new RegExp(s),d=new RegExp(a),f=new RegExp(u),h=new RegExp(l),p=/^(.+?)(ss|i)es$/,v=/^(.+?)([^s])s$/,g=/^(.+?)eed$/,m=/^(.+?)(ed|ing)$/,y=/.$/,S=/(at|bl|iz)$/,x=new RegExp("([^aeiouylsz])\\1$"),w=new RegExp("^"+o+i+"[^aeiouwxy]$"),I=/^(.+?[^aeiou])y$/,b=/^(.+?)(ational|tional|enci|anci|izer|bli|alli|entli|eli|ousli|ization|ation|ator|alism|iveness|fulness|ousness|aliti|iviti|biliti|logi)$/,E=/^(.+?)(icate|ative|alize|iciti|ical|ful|ness)$/,D=/^(.+?)(al|ance|ence|er|ic|able|ible|ant|ement|ment|ent|ou|ism|ate|iti|ous|ive|ize)$/,F=/^(.+?)(s|t)(ion)$/,_=/^(.+?)e$/,P=/ll$/,k=new RegExp("^"+o+i+"[^aeiouwxy]$"),z=function(n){var i,o,r,s,u,a,l;if(n.length<3)return n;if(r=n.substr(0,1),"y"==r&&(n=r.toUpperCase()+n.substr(1)),s=p,u=v,s.test(n)?n=n.replace(s,"$1$2"):u.test(n)&&(n=n.replace(u,"$1$2")),s=g,u=m,s.test(n)){var z=s.exec(n);s=c,s.test(z[1])&&(s=y,n=n.replace(s,""))}else if(u.test(n)){var z=u.exec(n);i=z[1],u=h,u.test(i)&&(n=i,u=S,a=x,l=w,u.test(n)?n+="e":a.test(n)?(s=y,n=n.replace(s,"")):l.test(n)&&(n+="e"))}if(s=I,s.test(n)){var z=s.exec(n);i=z[1],n=i+"i"}if(s=b,s.test(n)){var z=s.exec(n);i=z[1],o=z[2],s=c,s.test(i)&&(n=i+e[o])}if(s=E,s.test(n)){var z=s.exec(n);i=z[1],o=z[2],s=c,s.test(i)&&(n=i+t[o])}if(s=D,u=F,s.test(n)){var z=s.exec(n);i=z[1],s=d,s.test(i)&&(n=i)}else if(u.test(n)){var z=u.exec(n);i=z[1]+z[2],u=d,u.test(i)&&(n=i)}if(s=_,s.test(n)){var z=s.exec(n);i=z[1],s=d,u=f,a=k,(s.test(i)||u.test(i)&&!a.test(i))&&(n=i)}return s=P,u=d,s.test(n)&&u.test(n)&&(s=y,n=n.replace(s,"")),"y"==r&&(n=r.toLowerCase()+n.substr(1)),n};return z}(),t.Pipeline.registerFunction(t.stemmer,"stemmer"),t.stopWordFilter=function(e){return e&&t.stopWordFilter.stopWords[e]!==!0?e:void 0},t.clearStopWords=function(){t.stopWordFilter.stopWords={}},t.addStopWords=function(e){null!=e&&Array.isArray(e)!==!1&&e.forEach(function(e){t.stopWordFilter.stopWords[e]=!0},this)},t.resetStopWords=function(){t.stopWordFilter.stopWords=t.defaultStopWords},t.defaultStopWords={"":!0,a:!0,able:!0,about:!0,across:!0,after:!0,all:!0,almost:!0,also:!0,am:!0,among:!0,an:!0,and:!0,any:!0,are:!0,as:!0,at:!0,be:!0,because:!0,been:!0,but:!0,by:!0,can:!0,cannot:!0,could:!0,dear:!0,did:!0,"do":!0,does:!0,either:!0,"else":!0,ever:!0,every:!0,"for":!0,from:!0,get:!0,got:!0,had:!0,has:!0,have:!0,he:!0,her:!0,hers:!0,him:!0,his:!0,how:!0,however:!0,i:!0,"if":!0,"in":!0,into:!0,is:!0,it:!0,its:!0,just:!0,least:!0,let:!0,like:!0,likely:!0,may:!0,me:!0,might:!0,most:!0,must:!0,my:!0,neither:!0,no:!0,nor:!0,not:!0,of:!0,off:!0,often:!0,on:!0,only:!0,or:!0,other:!0,our:!0,own:!0,rather:!0,said:!0,say:!0,says:!0,she:!0,should:!0,since:!0,so:!0,some:!0,than:!0,that:!0,the:!0,their:!0,them:!0,then:!0,there:!0,these:!0,they:!0,"this":!0,tis:!0,to:!0,too:!0,twas:!0,us:!0,wants:!0,was:!0,we:!0,were:!0,what:!0,when:!0,where:!0,which:!0,"while":!0,who:!0,whom:!0,why:!0,will:!0,"with":!0,would:!0,yet:!0,you:!0,your:!0},t.stopWordFilter.stopWords=t.defaultStopWords,t.Pipeline.registerFunction(t.stopWordFilter,"stopWordFilter"),t.trimmer=function(e){if(null===e||void 0===e)throw new Error("token should not be undefined");return e.replace(/^\W+/,"").replace(/\W+$/,"")},t.Pipeline.registerFunction(t.trimmer,"trimmer"),t.InvertedIndex=function(){this.root={docs:{},df:0}},t.InvertedIndex.load=function(e){var t=new this;return t.root=e.root,t},t.InvertedIndex.prototype.addToken=function(e,t,n){for(var n=n||this.root,i=0;i<=e.length-1;){var o=e[i];o in n||(n[o]={docs:{},df:0}),i+=1,n=n[o]}var r=t.ref;n.docs[r]?n.docs[r]={tf:t.tf}:(n.docs[r]={tf:t.tf},n.df+=1)},t.InvertedIndex.prototype.hasToken=function(e){if(!e)return!1;for(var t=this.root,n=0;n<e.length;n++){if(!t[e[n]])return!1;t=t[e[n]]}return!0},t.InvertedIndex.prototype.getNode=function(e){if(!e)return null;for(var t=this.root,n=0;n<e.length;n++){if(!t[e[n]])return null;t=t[e[n]]}return t},t.InvertedIndex.prototype.getDocs=function(e){var t=this.getNode(e);return null==t?{}:t.docs},t.InvertedIndex.prototype.getTermFrequency=function(e,t){var n=this.getNode(e);return null==n?0:t in n.docs?n.docs[t].tf:0},t.InvertedIndex.prototype.getDocFreq=function(e){var t=this.getNode(e);return null==t?0:t.df},t.InvertedIndex.prototype.removeToken=function(e,t){if(e){var n=this.getNode(e);null!=n&&t in n.docs&&(delete n.docs[t],n.df-=1)}},t.InvertedIndex.prototype.expandToken=function(e,t,n){if(null==e||""==e)return[];var t=t||[];if(void 0==n&&(n=this.getNode(e),null==n))return t;n.df>0&&t.push(e);for(var i in n)"docs"!==i&&"df"!==i&&this.expandToken(e+i,t,n[i]);return t},t.InvertedIndex.prototype.toJSON=function(){return{root:this.root}},t.Configuration=function(e,n){var e=e||"";if(void 0==n||null==n)throw new Error("fields should not be null");this.config={};var i;try{i=JSON.parse(e),this.buildUserConfig(i,n)}catch(o){t.utils.warn("user configuration parse failed, will use default configuration"),this.buildDefaultConfig(n)}},t.Configuration.prototype.buildDefaultConfig=function(e){this.reset(),e.forEach(function(e){this.config[e]={boost:1,bool:"OR",expand:!1}},this)},t.Configuration.prototype.buildUserConfig=function(e,n){var i="OR",o=!1;if(this.reset(),"bool"in e&&(i=e.bool||i),"expand"in e&&(o=e.expand||o),"fields"in e)for(var r in e.fields)if(n.indexOf(r)>-1){var s=e.fields[r],u=o;void 0!=s.expand&&(u=s.expand),this.config[r]={boost:s.boost||0===s.boost?s.boost:1,bool:s.bool||i,expand:u}}else t.utils.warn("field name in user configuration not found in index instance fields");else this.addAllFields2UserConfig(i,o,n)},t.Configuration.prototype.addAllFields2UserConfig=function(e,t,n){n.forEach(function(n){this.config[n]={boost:1,bool:e,expand:t}},this)},t.Configuration.prototype.get=function(){return this.config},t.Configuration.prototype.reset=function(){this.config={}},lunr.SortedSet=function(){this.length=0,this.elements=[]},lunr.SortedSet.load=function(e){var t=new this;return t.elements=e,t.length=e.length,t},lunr.SortedSet.prototype.add=function(){var e,t;for(e=0;e<arguments.length;e++)t=arguments[e],~this.indexOf(t)||this.elements.splice(this.locationFor(t),0,t);this.length=this.elements.length},lunr.SortedSet.prototype.toArray=function(){return this.elements.slice()},lunr.SortedSet.prototype.map=function(e,t){return this.elements.map(e,t)},lunr.SortedSet.prototype.forEach=function(e,t){return this.elements.forEach(e,t)},lunr.SortedSet.prototype.indexOf=function(e){for(var t=0,n=this.elements.length,i=n-t,o=t+Math.floor(i/2),r=this.elements[o];i>1;){if(r===e)return o;e>r&&(t=o),r>e&&(n=o),i=n-t,o=t+Math.floor(i/2),r=this.elements[o]}return r===e?o:-1},lunr.SortedSet.prototype.locationFor=function(e){for(var t=0,n=this.elements.length,i=n-t,o=t+Math.floor(i/2),r=this.elements[o];i>1;)e>r&&(t=o),r>e&&(n=o),i=n-t,o=t+Math.floor(i/2),r=this.elements[o];return r>e?o:e>r?o+1:void 0},lunr.SortedSet.prototype.intersect=function(e){for(var t=new lunr.SortedSet,n=0,i=0,o=this.length,r=e.length,s=this.elements,u=e.elements;;){if(n>o-1||i>r-1)break;s[n]!==u[i]?s[n]<u[i]?n++:s[n]>u[i]&&i++:(t.add(s[n]),n++,i++)}return t},lunr.SortedSet.prototype.clone=function(){var e=new lunr.SortedSet;return e.elements=this.toArray(),e.length=e.elements.length,e},lunr.SortedSet.prototype.union=function(e){var t,n,i;this.length>=e.length?(t=this,n=e):(t=e,n=this),i=t.clone();for(var o=0,r=n.toArray();o<r.length;o++)i.add(r[o]);return i},lunr.SortedSet.prototype.toJSON=function(){return this.toArray()},function(e,t){"function"==typeof define&&define.amd?define(t):"object"==typeof exports?module.exports=t():e.elasticlunr=t()}(this,function(){return t})}(); - /** pdoc search index */const docs = {"version": "0.9.5", "fields": ["qualname", "fullname", "annotation", "default_value", "signature", "bases", "doc"], "ref": "fullname", "documentStore": {"docs": {"sqlglot": {"fullname": "sqlglot", "modulename": "sqlglot", "kind": "module", "doc": "<p><img 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\" alt=\"SQLGlot logo\" /></p>\n\n<p>SQLGlot is a no-dependency SQL parser, transpiler, optimizer, and engine. It can be used to format SQL or translate between <a href=\"https://github.com/tobymao/sqlglot/blob/main/sqlglot/dialects/__init__.py\">21 different dialects</a> like <a href=\"https://duckdb.org/\">DuckDB</a>, <a href=\"https://prestodb.io/\">Presto</a> / <a href=\"https://trino.io/\">Trino</a>, <a href=\"https://spark.apache.org/\">Spark</a> / <a href=\"https://www.databricks.com/\">Databricks</a>, <a href=\"https://www.snowflake.com/en/\">Snowflake</a>, and <a href=\"https://cloud.google.com/bigquery/\">BigQuery</a>. It aims to read a wide variety of SQL inputs and output syntactically and semantically correct SQL in the targeted dialects.</p>\n\n<p>It is a very comprehensive generic SQL parser with a robust <a href=\"https://github.com/tobymao/sqlglot/blob/main/tests/\">test suite</a>. It is also quite <a href=\"#benchmarks\">performant</a>, while being written purely in Python.</p>\n\n<p>You can easily <a href=\"#custom-dialects\">customize</a> the parser, <a href=\"#metadata\">analyze</a> queries, traverse expression trees, and programmatically <a href=\"#build-and-modify-sql\">build</a> SQL.</p>\n\n<p>Syntax <a href=\"#parser-errors\">errors</a> are highlighted and dialect incompatibilities can warn or raise depending on configurations. However, SQLGlot does not aim to be a SQL validator, so it may fail to detect certain syntax errors.</p>\n\n<p>Learn more about SQLGlot in the API <a href=\"https://sqlglot.com/\">documentation</a> and the expression tree <a href=\"https://github.com/tobymao/sqlglot/blob/main/posts/ast_primer.md\">primer</a>.</p>\n\n<p>Contributions are very welcome in SQLGlot; read the <a href=\"https://github.com/tobymao/sqlglot/blob/main/CONTRIBUTING.md\">contribution guide</a> to get started!</p>\n\n<h2 id=\"table-of-contents\">Table of Contents</h2>\n\n<ul>\n<li><a href=\"#install\">Install</a></li>\n<li><a href=\"#versioning\">Versioning</a></li>\n<li><a href=\"#get-in-touch\">Get in Touch</a></li>\n<li><a href=\"#faq\">FAQ</a></li>\n<li><a href=\"#examples\">Examples</a>\n<ul>\n<li><a href=\"#formatting-and-transpiling\">Formatting and Transpiling</a></li>\n<li><a href=\"#metadata\">Metadata</a></li>\n<li><a href=\"#parser-errors\">Parser Errors</a></li>\n<li><a href=\"#unsupported-errors\">Unsupported Errors</a></li>\n<li><a href=\"#build-and-modify-sql\">Build and Modify SQL</a></li>\n<li><a href=\"#sql-optimizer\">SQL Optimizer</a></li>\n<li><a href=\"#ast-introspection\">AST Introspection</a></li>\n<li><a href=\"#ast-diff\">AST Diff</a></li>\n<li><a href=\"#custom-dialects\">Custom Dialects</a></li>\n<li><a href=\"#sql-execution\">SQL Execution</a></li>\n</ul></li>\n<li><a href=\"#used-by\">Used By</a></li>\n<li><a href=\"#documentation\">Documentation</a></li>\n<li><a href=\"#run-tests-and-lint\">Run Tests and Lint</a></li>\n<li><a href=\"#benchmarks\">Benchmarks</a></li>\n<li><a href=\"#optional-dependencies\">Optional Dependencies</a></li>\n</ul>\n\n<h2 id=\"install\">Install</h2>\n\n<p>From PyPI:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code>pip3<span class=\"w\"> </span>install<span class=\"w\"> </span><span class=\"s2\">"sqlglot[rs]"</span>\n\n<span class=\"c1\"># Without Rust tokenizer (slower):</span>\n<span class=\"c1\"># pip3 install sqlglot</span>\n</code></pre>\n</div>\n\n<p>Or with a local checkout:</p>\n\n<pre><code>make install\n</code></pre>\n\n<p>Requirements for development (optional):</p>\n\n<pre><code>make install-dev\n</code></pre>\n\n<h2 id=\"versioning\">Versioning</h2>\n\n<p>Given a version number <code>MAJOR</code>.<code>MINOR</code>.<code>PATCH</code>, SQLGlot uses the following versioning strategy:</p>\n\n<ul>\n<li>The <code>PATCH</code> version is incremented when there are backwards-compatible fixes or feature additions.</li>\n<li>The <code>MINOR</code> version is incremented when there are backwards-incompatible fixes or feature additions.</li>\n<li>The <code>MAJOR</code> version is incremented when there are significant backwards-incompatible fixes or feature additions.</li>\n</ul>\n\n<h2 id=\"get-in-touch\">Get in Touch</h2>\n\n<p>We'd love to hear from you. Join our community <a href=\"https://tobikodata.com/slack\">Slack channel</a>!</p>\n\n<h2 id=\"faq\">FAQ</h2>\n\n<p>I tried to parse SQL that should be valid but it failed, why did that happen?</p>\n\n<ul>\n<li>Most of the time, issues like this occur because the \"source\" dialect is omitted during parsing. For example, this is how to correctly parse a SQL query written in Spark SQL: <code>parse_one(sql, dialect=\"spark\")</code> (alternatively: <code>read=\"spark\"</code>). If no dialect is specified, <code>parse_one</code> will attempt to parse the query according to the \"SQLGlot dialect\", which is designed to be a superset of all supported dialects. If you tried specifying the dialect and it still doesn't work, please file an issue.</li>\n</ul>\n\n<p>I tried to output SQL but it's not in the correct dialect!</p>\n\n<ul>\n<li>Like parsing, generating SQL also requires the target dialect to be specified, otherwise the SQLGlot dialect will be used by default. For example, to transpile a query from Spark SQL to DuckDB, do <code>parse_one(sql, dialect=\"spark\").sql(dialect=\"duckdb\")</code> (alternatively: <code>transpile(sql, read=\"spark\", write=\"duckdb\")</code>).</li>\n</ul>\n\n<p>I tried to parse invalid SQL and it worked, even though it should raise an error! Why didn't it validate my SQL?</p>\n\n<ul>\n<li>SQLGlot does not aim to be a SQL validator - it is designed to be very forgiving. This makes the codebase more comprehensive and also gives more flexibility to its users, e.g. by allowing them to include trailing commas in their projection lists.</li>\n</ul>\n\n<h2 id=\"examples\">Examples</h2>\n\n<h3 id=\"formatting-and-transpiling\">Formatting and Transpiling</h3>\n\n<p>Easily translate from one dialect to another. For example, date/time functions vary between dialects and can be hard to deal with:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">transpile</span><span class=\"p\">(</span><span class=\"s2\">"SELECT EPOCH_MS(1618088028295)"</span><span class=\"p\">,</span> <span class=\"n\">read</span><span class=\"o\">=</span><span class=\"s2\">"duckdb"</span><span class=\"p\">,</span> <span class=\"n\">write</span><span class=\"o\">=</span><span class=\"s2\">"hive"</span><span class=\"p\">)[</span><span class=\"mi\">0</span><span class=\"p\">]</span>\n</code></pre>\n</div>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"s1\">'SELECT FROM_UNIXTIME(1618088028295 / POW(10, 3))'</span>\n</code></pre>\n</div>\n\n<p>SQLGlot can even translate custom time formats:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">transpile</span><span class=\"p\">(</span><span class=\"s2\">"SELECT STRFTIME(x, '%y-%-m-%S')"</span><span class=\"p\">,</span> <span class=\"n\">read</span><span class=\"o\">=</span><span class=\"s2\">"duckdb"</span><span class=\"p\">,</span> <span class=\"n\">write</span><span class=\"o\">=</span><span class=\"s2\">"hive"</span><span class=\"p\">)[</span><span class=\"mi\">0</span><span class=\"p\">]</span>\n</code></pre>\n</div>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"ss\">"SELECT DATE_FORMAT(x, 'yy-M-ss')"</span>\n</code></pre>\n</div>\n\n<p>Identifier delimiters and data types can be translated as well:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n\n<span class=\"c1\"># Spark SQL requires backticks (`) for delimited identifiers and uses `FLOAT` over `REAL`</span>\n<span class=\"n\">sql</span> <span class=\"o\">=</span> <span class=\"s2\">"""WITH baz AS (SELECT a, c FROM foo WHERE a = 1) SELECT f.a, b.b, baz.c, CAST("b"."a" AS REAL) d FROM foo f JOIN bar b ON f.a = b.a LEFT JOIN baz ON f.a = baz.a"""</span>\n\n<span class=\"c1\"># Translates the query into Spark SQL, formats it, and delimits all of its identifiers</span>\n<span class=\"nb\">print</span><span class=\"p\">(</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">transpile</span><span class=\"p\">(</span><span class=\"n\">sql</span><span class=\"p\">,</span> <span class=\"n\">write</span><span class=\"o\">=</span><span class=\"s2\">"spark"</span><span class=\"p\">,</span> <span class=\"n\">identify</span><span class=\"o\">=</span><span class=\"kc\">True</span><span class=\"p\">,</span> <span class=\"n\">pretty</span><span class=\"o\">=</span><span class=\"kc\">True</span><span class=\"p\">)[</span><span class=\"mi\">0</span><span class=\"p\">])</span>\n</code></pre>\n</div>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"k\">WITH</span><span class=\"w\"> </span><span class=\"o\">`</span><span class=\"n\">baz</span><span class=\"o\">`</span><span class=\"w\"> </span><span class=\"k\">AS</span><span class=\"w\"> </span><span class=\"p\">(</span>\n<span class=\"w\"> </span><span class=\"k\">SELECT</span>\n<span class=\"w\"> </span><span class=\"o\">`</span><span class=\"n\">a</span><span class=\"o\">`</span><span class=\"p\">,</span>\n<span class=\"w\"> </span><span class=\"o\">`</span><span class=\"k\">c</span><span class=\"o\">`</span>\n<span class=\"w\"> </span><span class=\"k\">FROM</span><span class=\"w\"> </span><span class=\"o\">`</span><span class=\"n\">foo</span><span class=\"o\">`</span>\n<span class=\"w\"> </span><span class=\"k\">WHERE</span>\n<span class=\"w\"> </span><span class=\"o\">`</span><span class=\"n\">a</span><span class=\"o\">`</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"mi\">1</span>\n<span class=\"p\">)</span>\n<span class=\"k\">SELECT</span>\n<span class=\"w\"> </span><span class=\"o\">`</span><span class=\"n\">f</span><span class=\"o\">`</span><span class=\"p\">.</span><span class=\"o\">`</span><span class=\"n\">a</span><span class=\"o\">`</span><span class=\"p\">,</span>\n<span class=\"w\"> </span><span class=\"o\">`</span><span class=\"n\">b</span><span class=\"o\">`</span><span class=\"p\">.</span><span class=\"o\">`</span><span class=\"n\">b</span><span class=\"o\">`</span><span class=\"p\">,</span>\n<span class=\"w\"> </span><span class=\"o\">`</span><span class=\"n\">baz</span><span class=\"o\">`</span><span class=\"p\">.</span><span class=\"o\">`</span><span class=\"k\">c</span><span class=\"o\">`</span><span class=\"p\">,</span>\n<span class=\"w\"> </span><span class=\"k\">CAST</span><span class=\"p\">(</span><span class=\"o\">`</span><span class=\"n\">b</span><span class=\"o\">`</span><span class=\"p\">.</span><span class=\"o\">`</span><span class=\"n\">a</span><span class=\"o\">`</span><span class=\"w\"> </span><span class=\"k\">AS</span><span class=\"w\"> </span><span class=\"nb\">FLOAT</span><span class=\"p\">)</span><span class=\"w\"> </span><span class=\"k\">AS</span><span class=\"w\"> </span><span class=\"o\">`</span><span class=\"n\">d</span><span class=\"o\">`</span>\n<span class=\"k\">FROM</span><span class=\"w\"> </span><span class=\"o\">`</span><span class=\"n\">foo</span><span class=\"o\">`</span><span class=\"w\"> </span><span class=\"k\">AS</span><span class=\"w\"> </span><span class=\"o\">`</span><span class=\"n\">f</span><span class=\"o\">`</span>\n<span class=\"k\">JOIN</span><span class=\"w\"> </span><span class=\"o\">`</span><span class=\"n\">bar</span><span class=\"o\">`</span><span class=\"w\"> </span><span class=\"k\">AS</span><span class=\"w\"> </span><span class=\"o\">`</span><span class=\"n\">b</span><span class=\"o\">`</span>\n<span class=\"w\"> </span><span class=\"k\">ON</span><span class=\"w\"> </span><span class=\"o\">`</span><span class=\"n\">f</span><span class=\"o\">`</span><span class=\"p\">.</span><span class=\"o\">`</span><span class=\"n\">a</span><span class=\"o\">`</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"o\">`</span><span class=\"n\">b</span><span class=\"o\">`</span><span class=\"p\">.</span><span class=\"o\">`</span><span class=\"n\">a</span><span class=\"o\">`</span>\n<span class=\"k\">LEFT</span><span class=\"w\"> </span><span class=\"k\">JOIN</span><span class=\"w\"> </span><span class=\"o\">`</span><span class=\"n\">baz</span><span class=\"o\">`</span>\n<span class=\"w\"> </span><span class=\"k\">ON</span><span class=\"w\"> </span><span class=\"o\">`</span><span class=\"n\">f</span><span class=\"o\">`</span><span class=\"p\">.</span><span class=\"o\">`</span><span class=\"n\">a</span><span class=\"o\">`</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"o\">`</span><span class=\"n\">baz</span><span class=\"o\">`</span><span class=\"p\">.</span><span class=\"o\">`</span><span class=\"n\">a</span><span class=\"o\">`</span>\n</code></pre>\n</div>\n\n<p>Comments are also preserved on a best-effort basis:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"n\">sql</span> <span class=\"o\">=</span> <span class=\"s2\">"""</span>\n<span class=\"s2\">/* multi</span>\n<span class=\"s2\"> line</span>\n<span class=\"s2\"> comment</span>\n<span class=\"s2\">*/</span>\n<span class=\"s2\">SELECT</span>\n<span class=\"s2\"> tbl.cola /* comment 1 */ + tbl.colb /* comment 2 */,</span>\n<span class=\"s2\"> CAST(x AS SIGNED), # comment 3</span>\n<span class=\"s2\"> y -- comment 4</span>\n<span class=\"s2\">FROM</span>\n<span class=\"s2\"> bar /* comment 5 */,</span>\n<span class=\"s2\"> tbl # comment 6</span>\n<span class=\"s2\">"""</span>\n\n<span class=\"c1\"># Note: MySQL-specific comments (`#`) are converted into standard syntax</span>\n<span class=\"nb\">print</span><span class=\"p\">(</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">transpile</span><span class=\"p\">(</span><span class=\"n\">sql</span><span class=\"p\">,</span> <span class=\"n\">read</span><span class=\"o\">=</span><span class=\"s1\">'mysql'</span><span class=\"p\">,</span> <span class=\"n\">pretty</span><span class=\"o\">=</span><span class=\"kc\">True</span><span class=\"p\">)[</span><span class=\"mi\">0</span><span class=\"p\">])</span>\n</code></pre>\n</div>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"cm\">/* multi</span>\n<span class=\"cm\"> line</span>\n<span class=\"cm\"> comment</span>\n<span class=\"cm\">*/</span>\n<span class=\"k\">SELECT</span>\n<span class=\"w\"> </span><span class=\"n\">tbl</span><span class=\"p\">.</span><span class=\"n\">cola</span><span class=\"w\"> </span><span class=\"cm\">/* comment 1 */</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"n\">tbl</span><span class=\"p\">.</span><span class=\"n\">colb</span><span class=\"w\"> </span><span class=\"cm\">/* comment 2 */</span><span class=\"p\">,</span>\n<span class=\"w\"> </span><span class=\"k\">CAST</span><span class=\"p\">(</span><span class=\"n\">x</span><span class=\"w\"> </span><span class=\"k\">AS</span><span class=\"w\"> </span><span class=\"nb\">INT</span><span class=\"p\">),</span><span class=\"w\"> </span><span class=\"cm\">/* comment 3 */</span>\n<span class=\"w\"> </span><span class=\"n\">y</span><span class=\"w\"> </span><span class=\"cm\">/* comment 4 */</span>\n<span class=\"k\">FROM</span><span class=\"w\"> </span><span class=\"n\">bar</span><span class=\"w\"> </span><span class=\"cm\">/* comment 5 */</span><span class=\"p\">,</span><span class=\"w\"> </span><span class=\"n\">tbl</span><span class=\"w\"> </span><span class=\"cm\">/* comment 6 */</span>\n</code></pre>\n</div>\n\n<h3 id=\"metadata\">Metadata</h3>\n\n<p>You can explore SQL with expression helpers to do things like find columns and tables in a query:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">parse_one</span><span class=\"p\">,</span> <span class=\"n\">exp</span>\n\n<span class=\"c1\"># print all column references (a and b)</span>\n<span class=\"k\">for</span> <span class=\"n\">column</span> <span class=\"ow\">in</span> <span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT a, b + 1 AS c FROM d"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">find_all</span><span class=\"p\">(</span><span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">Column</span><span class=\"p\">):</span>\n <span class=\"nb\">print</span><span class=\"p\">(</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">alias_or_name</span><span class=\"p\">)</span>\n\n<span class=\"c1\"># find all projections in select statements (a and c)</span>\n<span class=\"k\">for</span> <span class=\"n\">select</span> <span class=\"ow\">in</span> <span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT a, b + 1 AS c FROM d"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">find_all</span><span class=\"p\">(</span><span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">Select</span><span class=\"p\">):</span>\n <span class=\"k\">for</span> <span class=\"n\">projection</span> <span class=\"ow\">in</span> <span class=\"n\">select</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">:</span>\n <span class=\"nb\">print</span><span class=\"p\">(</span><span class=\"n\">projection</span><span class=\"o\">.</span><span class=\"n\">alias_or_name</span><span class=\"p\">)</span>\n\n<span class=\"c1\"># find all tables (x, y, z)</span>\n<span class=\"k\">for</span> <span class=\"n\">table</span> <span class=\"ow\">in</span> <span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT * FROM x JOIN y JOIN z"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">find_all</span><span class=\"p\">(</span><span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">Table</span><span class=\"p\">):</span>\n <span class=\"nb\">print</span><span class=\"p\">(</span><span class=\"n\">table</span><span class=\"o\">.</span><span class=\"n\">name</span><span class=\"p\">)</span>\n</code></pre>\n</div>\n\n<p>Read the <a href=\"https://github.com/tobymao/sqlglot/blob/main/posts/ast_primer.md\">ast primer</a> to learn more about SQLGlot's internals.</p>\n\n<h3 id=\"parser-errors\">Parser Errors</h3>\n\n<p>When the parser detects an error in the syntax, it raises a <code>ParseError</code>:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">transpile</span><span class=\"p\">(</span><span class=\"s2\">"SELECT foo FROM (SELECT baz FROM t"</span><span class=\"p\">)</span>\n</code></pre>\n</div>\n\n<pre><code>sqlglot.errors.ParseError: Expecting ). Line 1, Col: 34.\n SELECT foo FROM (SELECT baz FROM t\n ~\n</code></pre>\n\n<p>Structured syntax errors are accessible for programmatic use:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"k\">try</span><span class=\"p\">:</span>\n <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">transpile</span><span class=\"p\">(</span><span class=\"s2\">"SELECT foo FROM (SELECT baz FROM t"</span><span class=\"p\">)</span>\n<span class=\"k\">except</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">errors</span><span class=\"o\">.</span><span class=\"n\">ParseError</span> <span class=\"k\">as</span> <span class=\"n\">e</span><span class=\"p\">:</span>\n <span class=\"nb\">print</span><span class=\"p\">(</span><span class=\"n\">e</span><span class=\"o\">.</span><span class=\"n\">errors</span><span class=\"p\">)</span>\n</code></pre>\n</div>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"p\">[{</span>\n <span class=\"s1\">'description'</span><span class=\"p\">:</span> <span class=\"s1\">'Expecting )'</span><span class=\"p\">,</span>\n <span class=\"s1\">'line'</span><span class=\"p\">:</span> <span class=\"mi\">1</span><span class=\"p\">,</span>\n <span class=\"s1\">'col'</span><span class=\"p\">:</span> <span class=\"mi\">34</span><span class=\"p\">,</span>\n <span class=\"s1\">'start_context'</span><span class=\"p\">:</span> <span class=\"s1\">'SELECT foo FROM (SELECT baz FROM '</span><span class=\"p\">,</span>\n <span class=\"s1\">'highlight'</span><span class=\"p\">:</span> <span class=\"s1\">'t'</span><span class=\"p\">,</span>\n <span class=\"s1\">'end_context'</span><span class=\"p\">:</span> <span class=\"s1\">''</span><span class=\"p\">,</span>\n <span class=\"s1\">'into_expression'</span><span class=\"p\">:</span> <span class=\"kc\">None</span>\n<span class=\"p\">}]</span>\n</code></pre>\n</div>\n\n<h3 id=\"unsupported-errors\">Unsupported Errors</h3>\n\n<p>It may not be possible to translate some queries between certain dialects. For these cases, SQLGlot may emit a warning and will proceed to do a best-effort translation by default:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">transpile</span><span class=\"p\">(</span><span class=\"s2\">"SELECT APPROX_DISTINCT(a, 0.1) FROM foo"</span><span class=\"p\">,</span> <span class=\"n\">read</span><span class=\"o\">=</span><span class=\"s2\">"presto"</span><span class=\"p\">,</span> <span class=\"n\">write</span><span class=\"o\">=</span><span class=\"s2\">"hive"</span><span class=\"p\">)</span>\n</code></pre>\n</div>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"n\">APPROX_COUNT_DISTINCT</span><span class=\"w\"> </span><span class=\"n\">does</span><span class=\"w\"> </span><span class=\"k\">not</span><span class=\"w\"> </span><span class=\"n\">support</span><span class=\"w\"> </span><span class=\"n\">accuracy</span>\n<span class=\"s1\">'SELECT APPROX_COUNT_DISTINCT(a) FROM foo'</span>\n</code></pre>\n</div>\n\n<p>This behavior can be changed by setting the <a href=\"https://github.com/tobymao/sqlglot/blob/b0e8dc96ba179edb1776647b5bde4e704238b44d/sqlglot/errors.py#L9\"><code>unsupported_level</code></a> attribute. For example, we can set it to either <code>RAISE</code> or <code>IMMEDIATE</code> to ensure an exception is raised instead:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">transpile</span><span class=\"p\">(</span><span class=\"s2\">"SELECT APPROX_DISTINCT(a, 0.1) FROM foo"</span><span class=\"p\">,</span> <span class=\"n\">read</span><span class=\"o\">=</span><span class=\"s2\">"presto"</span><span class=\"p\">,</span> <span class=\"n\">write</span><span class=\"o\">=</span><span class=\"s2\">"hive"</span><span class=\"p\">,</span> <span class=\"n\">unsupported_level</span><span class=\"o\">=</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">ErrorLevel</span><span class=\"o\">.</span><span class=\"n\">RAISE</span><span class=\"p\">)</span>\n</code></pre>\n</div>\n\n<pre><code>sqlglot.errors.UnsupportedError: APPROX_COUNT_DISTINCT does not support accuracy\n</code></pre>\n\n<p>There are queries that require additional information to be accurately transpiled, such as the schemas of the tables referenced in them. This is because certain transformations are type-sensitive, meaning that type inference is needed in order to understand their semantics. Even though the <code>qualify</code> and <code>annotate_types</code> optimizer <a href=\"https://github.com/tobymao/sqlglot/tree/main/sqlglot/optimizer\">rules</a> can help with this, they are not used by default because they add significant overhead and complexity.</p>\n\n<p>Transpilation is generally a hard problem, so SQLGlot employs an \"incremental\" approach to solving it. This means that there may be dialect pairs that currently lack support for some inputs, but this is expected to improve over time. We highly appreciate well-documented and tested issues or PRs, so feel free to <a href=\"#get-in-touch\">reach out</a> if you need guidance!</p>\n\n<h3 id=\"build-and-modify-sql\">Build and Modify SQL</h3>\n\n<p>SQLGlot supports incrementally building SQL expressions:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">select</span><span class=\"p\">,</span> <span class=\"n\">condition</span>\n\n<span class=\"n\">where</span> <span class=\"o\">=</span> <span class=\"n\">condition</span><span class=\"p\">(</span><span class=\"s2\">"x=1"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">and_</span><span class=\"p\">(</span><span class=\"s2\">"y=1"</span><span class=\"p\">)</span>\n<span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"*"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">from_</span><span class=\"p\">(</span><span class=\"s2\">"y"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">where</span><span class=\"p\">(</span><span class=\"n\">where</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n</code></pre>\n</div>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"s1\">'SELECT * FROM y WHERE x = 1 AND y = 1'</span>\n</code></pre>\n</div>\n\n<p>It's possible to modify a parsed tree:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">parse_one</span>\n<span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT x FROM y"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">from_</span><span class=\"p\">(</span><span class=\"s2\">"z"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n</code></pre>\n</div>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"s1\">'SELECT x FROM z'</span>\n</code></pre>\n</div>\n\n<p>Parsed expressions can also be transformed recursively by applying a mapping function to each node in the tree:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">exp</span><span class=\"p\">,</span> <span class=\"n\">parse_one</span>\n\n<span class=\"n\">expression_tree</span> <span class=\"o\">=</span> <span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT a FROM x"</span><span class=\"p\">)</span>\n\n<span class=\"k\">def</span> <span class=\"nf\">transformer</span><span class=\"p\">(</span><span class=\"n\">node</span><span class=\"p\">):</span>\n <span class=\"k\">if</span> <span class=\"nb\">isinstance</span><span class=\"p\">(</span><span class=\"n\">node</span><span class=\"p\">,</span> <span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">Column</span><span class=\"p\">)</span> <span class=\"ow\">and</span> <span class=\"n\">node</span><span class=\"o\">.</span><span class=\"n\">name</span> <span class=\"o\">==</span> <span class=\"s2\">"a"</span><span class=\"p\">:</span>\n <span class=\"k\">return</span> <span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"FUN(a)"</span><span class=\"p\">)</span>\n <span class=\"k\">return</span> <span class=\"n\">node</span>\n\n<span class=\"n\">transformed_tree</span> <span class=\"o\">=</span> <span class=\"n\">expression_tree</span><span class=\"o\">.</span><span class=\"n\">transform</span><span class=\"p\">(</span><span class=\"n\">transformer</span><span class=\"p\">)</span>\n<span class=\"n\">transformed_tree</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n</code></pre>\n</div>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"s1\">'SELECT FUN(a) FROM x'</span>\n</code></pre>\n</div>\n\n<h3 id=\"sql-optimizer\">SQL Optimizer</h3>\n\n<p>SQLGlot can rewrite queries into an \"optimized\" form. It performs a variety of <a href=\"https://github.com/tobymao/sqlglot/blob/main/sqlglot/optimizer/optimizer.py\">techniques</a> to create a new canonical AST. This AST can be used to standardize queries or provide the foundations for implementing an actual engine. For example:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"kn\">from</span> <span class=\"nn\">sqlglot.optimizer</span> <span class=\"kn\">import</span> <span class=\"n\">optimize</span>\n\n<span class=\"nb\">print</span><span class=\"p\">(</span>\n <span class=\"n\">optimize</span><span class=\"p\">(</span>\n <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"""</span>\n<span class=\"s2\"> SELECT A OR (B OR (C AND D))</span>\n<span class=\"s2\"> FROM x</span>\n<span class=\"s2\"> WHERE Z = date '2021-01-01' + INTERVAL '1' month OR 1 = 0</span>\n<span class=\"s2\"> """</span><span class=\"p\">),</span>\n <span class=\"n\">schema</span><span class=\"o\">=</span><span class=\"p\">{</span><span class=\"s2\">"x"</span><span class=\"p\">:</span> <span class=\"p\">{</span><span class=\"s2\">"A"</span><span class=\"p\">:</span> <span class=\"s2\">"INT"</span><span class=\"p\">,</span> <span class=\"s2\">"B"</span><span class=\"p\">:</span> <span class=\"s2\">"INT"</span><span class=\"p\">,</span> <span class=\"s2\">"C"</span><span class=\"p\">:</span> <span class=\"s2\">"INT"</span><span class=\"p\">,</span> <span class=\"s2\">"D"</span><span class=\"p\">:</span> <span class=\"s2\">"INT"</span><span class=\"p\">,</span> <span class=\"s2\">"Z"</span><span class=\"p\">:</span> <span class=\"s2\">"STRING"</span><span class=\"p\">}}</span>\n <span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">(</span><span class=\"n\">pretty</span><span class=\"o\">=</span><span class=\"kc\">True</span><span class=\"p\">)</span>\n<span class=\"p\">)</span>\n</code></pre>\n</div>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"k\">SELECT</span>\n<span class=\"w\"> </span><span class=\"p\">(</span>\n<span class=\"w\"> </span><span class=\"ss\">"x"</span><span class=\"p\">.</span><span class=\"ss\">"a"</span><span class=\"w\"> </span><span class=\"o\"><></span><span class=\"w\"> </span><span class=\"mi\">0</span><span class=\"w\"> </span><span class=\"k\">OR</span><span class=\"w\"> </span><span class=\"ss\">"x"</span><span class=\"p\">.</span><span class=\"ss\">"b"</span><span class=\"w\"> </span><span class=\"o\"><></span><span class=\"w\"> </span><span class=\"mi\">0</span><span class=\"w\"> </span><span class=\"k\">OR</span><span class=\"w\"> </span><span class=\"ss\">"x"</span><span class=\"p\">.</span><span class=\"ss\">"c"</span><span class=\"w\"> </span><span class=\"o\"><></span><span class=\"w\"> </span><span class=\"mi\">0</span>\n<span class=\"w\"> </span><span class=\"p\">)</span>\n<span class=\"w\"> </span><span class=\"k\">AND</span><span class=\"w\"> </span><span class=\"p\">(</span>\n<span class=\"w\"> </span><span class=\"ss\">"x"</span><span class=\"p\">.</span><span class=\"ss\">"a"</span><span class=\"w\"> </span><span class=\"o\"><></span><span class=\"w\"> </span><span class=\"mi\">0</span><span class=\"w\"> </span><span class=\"k\">OR</span><span class=\"w\"> </span><span class=\"ss\">"x"</span><span class=\"p\">.</span><span class=\"ss\">"b"</span><span class=\"w\"> </span><span class=\"o\"><></span><span class=\"w\"> </span><span class=\"mi\">0</span><span class=\"w\"> </span><span class=\"k\">OR</span><span class=\"w\"> </span><span class=\"ss\">"x"</span><span class=\"p\">.</span><span class=\"ss\">"d"</span><span class=\"w\"> </span><span class=\"o\"><></span><span class=\"w\"> </span><span class=\"mi\">0</span>\n<span class=\"w\"> </span><span class=\"p\">)</span><span class=\"w\"> </span><span class=\"k\">AS</span><span class=\"w\"> </span><span class=\"ss\">"_col_0"</span>\n<span class=\"k\">FROM</span><span class=\"w\"> </span><span class=\"ss\">"x"</span><span class=\"w\"> </span><span class=\"k\">AS</span><span class=\"w\"> </span><span class=\"ss\">"x"</span>\n<span class=\"k\">WHERE</span>\n<span class=\"w\"> </span><span class=\"k\">CAST</span><span class=\"p\">(</span><span class=\"ss\">"x"</span><span class=\"p\">.</span><span class=\"ss\">"z"</span><span class=\"w\"> </span><span class=\"k\">AS</span><span class=\"w\"> </span><span class=\"nb\">DATE</span><span class=\"p\">)</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"k\">CAST</span><span class=\"p\">(</span><span class=\"s1\">'2021-02-01'</span><span class=\"w\"> </span><span class=\"k\">AS</span><span class=\"w\"> </span><span class=\"nb\">DATE</span><span class=\"p\">)</span>\n</code></pre>\n</div>\n\n<h3 id=\"ast-introspection\">AST Introspection</h3>\n\n<p>You can see the AST version of the parsed SQL by calling <code>repr</code>:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">parse_one</span>\n<span class=\"nb\">print</span><span class=\"p\">(</span><span class=\"nb\">repr</span><span class=\"p\">(</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT a + 1 AS z"</span><span class=\"p\">)))</span>\n</code></pre>\n</div>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"n\">Select</span><span class=\"p\">(</span>\n <span class=\"n\">expressions</span><span class=\"o\">=</span><span class=\"p\">[</span>\n <span class=\"n\">Alias</span><span class=\"p\">(</span>\n <span class=\"n\">this</span><span class=\"o\">=</span><span class=\"n\">Add</span><span class=\"p\">(</span>\n <span class=\"n\">this</span><span class=\"o\">=</span><span class=\"n\">Column</span><span class=\"p\">(</span>\n <span class=\"n\">this</span><span class=\"o\">=</span><span class=\"n\">Identifier</span><span class=\"p\">(</span><span class=\"n\">this</span><span class=\"o\">=</span><span class=\"n\">a</span><span class=\"p\">,</span> <span class=\"n\">quoted</span><span class=\"o\">=</span><span class=\"kc\">False</span><span class=\"p\">)),</span>\n <span class=\"n\">expression</span><span class=\"o\">=</span><span class=\"n\">Literal</span><span class=\"p\">(</span><span class=\"n\">this</span><span class=\"o\">=</span><span class=\"mi\">1</span><span class=\"p\">,</span> <span class=\"n\">is_string</span><span class=\"o\">=</span><span class=\"kc\">False</span><span class=\"p\">)),</span>\n <span class=\"n\">alias</span><span class=\"o\">=</span><span class=\"n\">Identifier</span><span class=\"p\">(</span><span class=\"n\">this</span><span class=\"o\">=</span><span class=\"n\">z</span><span class=\"p\">,</span> <span class=\"n\">quoted</span><span class=\"o\">=</span><span class=\"kc\">False</span><span class=\"p\">))])</span>\n</code></pre>\n</div>\n\n<h3 id=\"ast-diff\">AST Diff</h3>\n\n<p>SQLGlot can calculate the semantic difference between two expressions and output changes in a form of a sequence of actions needed to transform a source expression into a target one:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">diff</span><span class=\"p\">,</span> <span class=\"n\">parse_one</span>\n<span class=\"n\">diff</span><span class=\"p\">(</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT a + b, c, d"</span><span class=\"p\">),</span> <span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT c, a - b, d"</span><span class=\"p\">))</span>\n</code></pre>\n</div>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"p\">[</span>\n <span class=\"n\">Remove</span><span class=\"p\">(</span><span class=\"n\">expression</span><span class=\"o\">=</span><span class=\"n\">Add</span><span class=\"p\">(</span>\n <span class=\"n\">this</span><span class=\"o\">=</span><span class=\"n\">Column</span><span class=\"p\">(</span>\n <span class=\"n\">this</span><span class=\"o\">=</span><span class=\"n\">Identifier</span><span class=\"p\">(</span><span class=\"n\">this</span><span class=\"o\">=</span><span class=\"n\">a</span><span class=\"p\">,</span> <span class=\"n\">quoted</span><span class=\"o\">=</span><span class=\"kc\">False</span><span class=\"p\">)),</span>\n <span class=\"n\">expression</span><span class=\"o\">=</span><span class=\"n\">Column</span><span class=\"p\">(</span>\n <span class=\"n\">this</span><span class=\"o\">=</span><span class=\"n\">Identifier</span><span class=\"p\">(</span><span class=\"n\">this</span><span class=\"o\">=</span><span class=\"n\">b</span><span class=\"p\">,</span> <span class=\"n\">quoted</span><span class=\"o\">=</span><span class=\"kc\">False</span><span class=\"p\">)))),</span>\n <span class=\"n\">Insert</span><span class=\"p\">(</span><span class=\"n\">expression</span><span class=\"o\">=</span><span class=\"n\">Sub</span><span class=\"p\">(</span>\n <span class=\"n\">this</span><span class=\"o\">=</span><span class=\"n\">Column</span><span class=\"p\">(</span>\n <span class=\"n\">this</span><span class=\"o\">=</span><span class=\"n\">Identifier</span><span class=\"p\">(</span><span class=\"n\">this</span><span class=\"o\">=</span><span class=\"n\">a</span><span class=\"p\">,</span> <span class=\"n\">quoted</span><span class=\"o\">=</span><span class=\"kc\">False</span><span class=\"p\">)),</span>\n <span class=\"n\">expression</span><span class=\"o\">=</span><span class=\"n\">Column</span><span class=\"p\">(</span>\n <span class=\"n\">this</span><span class=\"o\">=</span><span class=\"n\">Identifier</span><span class=\"p\">(</span><span class=\"n\">this</span><span class=\"o\">=</span><span class=\"n\">b</span><span class=\"p\">,</span> <span class=\"n\">quoted</span><span class=\"o\">=</span><span class=\"kc\">False</span><span class=\"p\">)))),</span>\n <span class=\"n\">Keep</span><span class=\"p\">(</span>\n <span class=\"n\">source</span><span class=\"o\">=</span><span class=\"n\">Column</span><span class=\"p\">(</span><span class=\"n\">this</span><span class=\"o\">=</span><span class=\"n\">Identifier</span><span class=\"p\">(</span><span class=\"n\">this</span><span class=\"o\">=</span><span class=\"n\">a</span><span class=\"p\">,</span> <span class=\"n\">quoted</span><span class=\"o\">=</span><span class=\"kc\">False</span><span class=\"p\">)),</span>\n <span class=\"n\">target</span><span class=\"o\">=</span><span class=\"n\">Column</span><span class=\"p\">(</span><span class=\"n\">this</span><span class=\"o\">=</span><span class=\"n\">Identifier</span><span class=\"p\">(</span><span class=\"n\">this</span><span class=\"o\">=</span><span class=\"n\">a</span><span class=\"p\">,</span> <span class=\"n\">quoted</span><span class=\"o\">=</span><span class=\"kc\">False</span><span class=\"p\">))),</span>\n <span class=\"o\">...</span>\n<span class=\"p\">]</span>\n</code></pre>\n</div>\n\n<p>See also: <a href=\"https://github.com/tobymao/sqlglot/blob/main/posts/sql_diff.md\">Semantic Diff for SQL</a>.</p>\n\n<h3 id=\"custom-dialects\">Custom Dialects</h3>\n\n<p><a href=\"https://github.com/tobymao/sqlglot/tree/main/sqlglot/dialects\">Dialects</a> can be added by subclassing <code>Dialect</code>:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">exp</span>\n<span class=\"kn\">from</span> <span class=\"nn\">sqlglot.dialects.dialect</span> <span class=\"kn\">import</span> <span class=\"n\">Dialect</span>\n<span class=\"kn\">from</span> <span class=\"nn\">sqlglot.generator</span> <span class=\"kn\">import</span> <span class=\"n\">Generator</span>\n<span class=\"kn\">from</span> <span class=\"nn\">sqlglot.tokens</span> <span class=\"kn\">import</span> <span class=\"n\">Tokenizer</span><span class=\"p\">,</span> <span class=\"n\">TokenType</span>\n\n\n<span class=\"k\">class</span> <span class=\"nc\">Custom</span><span class=\"p\">(</span><span class=\"n\">Dialect</span><span class=\"p\">):</span>\n <span class=\"k\">class</span> <span class=\"nc\">Tokenizer</span><span class=\"p\">(</span><span class=\"n\">Tokenizer</span><span class=\"p\">):</span>\n <span class=\"n\">QUOTES</span> <span class=\"o\">=</span> <span class=\"p\">[</span><span class=\"s2\">"'"</span><span class=\"p\">,</span> <span class=\"s1\">'"'</span><span class=\"p\">]</span>\n <span class=\"n\">IDENTIFIERS</span> <span class=\"o\">=</span> <span class=\"p\">[</span><span class=\"s2\">"`"</span><span class=\"p\">]</span>\n\n <span class=\"n\">KEYWORDS</span> <span class=\"o\">=</span> <span class=\"p\">{</span>\n <span class=\"o\">**</span><span class=\"n\">Tokenizer</span><span class=\"o\">.</span><span class=\"n\">KEYWORDS</span><span class=\"p\">,</span>\n <span class=\"s2\">"INT64"</span><span class=\"p\">:</span> <span class=\"n\">TokenType</span><span class=\"o\">.</span><span class=\"n\">BIGINT</span><span class=\"p\">,</span>\n <span class=\"s2\">"FLOAT64"</span><span class=\"p\">:</span> <span class=\"n\">TokenType</span><span class=\"o\">.</span><span class=\"n\">DOUBLE</span><span class=\"p\">,</span>\n <span class=\"p\">}</span>\n\n <span class=\"k\">class</span> <span class=\"nc\">Generator</span><span class=\"p\">(</span><span class=\"n\">Generator</span><span class=\"p\">):</span>\n <span class=\"n\">TRANSFORMS</span> <span class=\"o\">=</span> <span class=\"p\">{</span><span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">Array</span><span class=\"p\">:</span> <span class=\"k\">lambda</span> <span class=\"bp\">self</span><span class=\"p\">,</span> <span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"sa\">f</span><span class=\"s2\">"[</span><span class=\"si\">{</span><span class=\"bp\">self</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">(</span><span class=\"n\">e</span><span class=\"p\">)</span><span class=\"si\">}</span><span class=\"s2\">]"</span><span class=\"p\">}</span>\n\n <span class=\"n\">TYPE_MAPPING</span> <span class=\"o\">=</span> <span class=\"p\">{</span>\n <span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"o\">.</span><span class=\"n\">TINYINT</span><span class=\"p\">:</span> <span class=\"s2\">"INT64"</span><span class=\"p\">,</span>\n <span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"o\">.</span><span class=\"n\">SMALLINT</span><span class=\"p\">:</span> <span class=\"s2\">"INT64"</span><span class=\"p\">,</span>\n <span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"o\">.</span><span class=\"n\">INT</span><span class=\"p\">:</span> <span class=\"s2\">"INT64"</span><span class=\"p\">,</span>\n <span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"o\">.</span><span class=\"n\">BIGINT</span><span class=\"p\">:</span> <span class=\"s2\">"INT64"</span><span class=\"p\">,</span>\n <span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"o\">.</span><span class=\"n\">DECIMAL</span><span class=\"p\">:</span> <span class=\"s2\">"NUMERIC"</span><span class=\"p\">,</span>\n <span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"o\">.</span><span class=\"n\">FLOAT</span><span class=\"p\">:</span> <span class=\"s2\">"FLOAT64"</span><span class=\"p\">,</span>\n <span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"o\">.</span><span class=\"n\">DOUBLE</span><span class=\"p\">:</span> <span class=\"s2\">"FLOAT64"</span><span class=\"p\">,</span>\n <span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"o\">.</span><span class=\"n\">BOOLEAN</span><span class=\"p\">:</span> <span class=\"s2\">"BOOL"</span><span class=\"p\">,</span>\n <span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"o\">.</span><span class=\"n\">TEXT</span><span class=\"p\">:</span> <span class=\"s2\">"STRING"</span><span class=\"p\">,</span>\n <span class=\"p\">}</span>\n\n<span class=\"nb\">print</span><span class=\"p\">(</span><span class=\"n\">Dialect</span><span class=\"p\">[</span><span class=\"s2\">"custom"</span><span class=\"p\">])</span>\n</code></pre>\n</div>\n\n<pre><code><class '__main__.Custom'>\n</code></pre>\n\n<h3 id=\"sql-execution\">SQL Execution</h3>\n\n<p>SQLGlot is able to interpret SQL queries, where the tables are represented as Python dictionaries. The engine is not supposed to be fast, but it can be useful for unit testing and running SQL natively across Python objects. Additionally, the foundation can be easily integrated with fast compute kernels, such as <a href=\"https://arrow.apache.org/docs/index.html\">Arrow</a> and <a href=\"https://pandas.pydata.org/\">Pandas</a>.</p>\n\n<p>The example below showcases the execution of a query that involves aggregations and joins:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"kn\">from</span> <span class=\"nn\">sqlglot.executor</span> <span class=\"kn\">import</span> <span class=\"n\">execute</span>\n\n<span class=\"n\">tables</span> <span class=\"o\">=</span> <span class=\"p\">{</span>\n <span class=\"s2\">"sushi"</span><span class=\"p\">:</span> <span class=\"p\">[</span>\n <span class=\"p\">{</span><span class=\"s2\">"id"</span><span class=\"p\">:</span> <span class=\"mi\">1</span><span class=\"p\">,</span> <span class=\"s2\">"price"</span><span class=\"p\">:</span> <span class=\"mf\">1.0</span><span class=\"p\">},</span>\n <span class=\"p\">{</span><span class=\"s2\">"id"</span><span class=\"p\">:</span> <span class=\"mi\">2</span><span class=\"p\">,</span> <span class=\"s2\">"price"</span><span class=\"p\">:</span> <span class=\"mf\">2.0</span><span class=\"p\">},</span>\n <span class=\"p\">{</span><span class=\"s2\">"id"</span><span class=\"p\">:</span> <span class=\"mi\">3</span><span class=\"p\">,</span> <span class=\"s2\">"price"</span><span class=\"p\">:</span> <span class=\"mf\">3.0</span><span class=\"p\">},</span>\n <span class=\"p\">],</span>\n <span class=\"s2\">"order_items"</span><span class=\"p\">:</span> <span class=\"p\">[</span>\n <span class=\"p\">{</span><span class=\"s2\">"sushi_id"</span><span class=\"p\">:</span> <span class=\"mi\">1</span><span class=\"p\">,</span> <span class=\"s2\">"order_id"</span><span class=\"p\">:</span> <span class=\"mi\">1</span><span class=\"p\">},</span>\n <span class=\"p\">{</span><span class=\"s2\">"sushi_id"</span><span class=\"p\">:</span> <span class=\"mi\">1</span><span class=\"p\">,</span> <span class=\"s2\">"order_id"</span><span class=\"p\">:</span> <span class=\"mi\">1</span><span class=\"p\">},</span>\n <span class=\"p\">{</span><span class=\"s2\">"sushi_id"</span><span class=\"p\">:</span> <span class=\"mi\">2</span><span class=\"p\">,</span> <span class=\"s2\">"order_id"</span><span class=\"p\">:</span> <span class=\"mi\">1</span><span class=\"p\">},</span>\n <span class=\"p\">{</span><span class=\"s2\">"sushi_id"</span><span class=\"p\">:</span> <span class=\"mi\">3</span><span class=\"p\">,</span> <span class=\"s2\">"order_id"</span><span class=\"p\">:</span> <span class=\"mi\">2</span><span class=\"p\">},</span>\n <span class=\"p\">],</span>\n <span class=\"s2\">"orders"</span><span class=\"p\">:</span> <span class=\"p\">[</span>\n <span class=\"p\">{</span><span class=\"s2\">"id"</span><span class=\"p\">:</span> <span class=\"mi\">1</span><span class=\"p\">,</span> <span class=\"s2\">"user_id"</span><span class=\"p\">:</span> <span class=\"mi\">1</span><span class=\"p\">},</span>\n <span class=\"p\">{</span><span class=\"s2\">"id"</span><span class=\"p\">:</span> <span class=\"mi\">2</span><span class=\"p\">,</span> <span class=\"s2\">"user_id"</span><span class=\"p\">:</span> <span class=\"mi\">2</span><span class=\"p\">},</span>\n <span class=\"p\">],</span>\n<span class=\"p\">}</span>\n\n<span class=\"n\">execute</span><span class=\"p\">(</span>\n<span class=\"w\"> </span><span class=\"sd\">"""</span>\n<span class=\"sd\"> SELECT</span>\n<span class=\"sd\"> o.user_id,</span>\n<span class=\"sd\"> SUM(s.price) AS price</span>\n<span class=\"sd\"> FROM orders o</span>\n<span class=\"sd\"> JOIN order_items i</span>\n<span class=\"sd\"> ON o.id = i.order_id</span>\n<span class=\"sd\"> JOIN sushi s</span>\n<span class=\"sd\"> ON i.sushi_id = s.id</span>\n<span class=\"sd\"> GROUP BY o.user_id</span>\n<span class=\"sd\"> """</span><span class=\"p\">,</span>\n <span class=\"n\">tables</span><span class=\"o\">=</span><span class=\"n\">tables</span>\n<span class=\"p\">)</span>\n</code></pre>\n</div>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"n\">user_id</span> <span class=\"n\">price</span>\n <span class=\"mi\">1</span> <span class=\"mf\">4.0</span>\n <span class=\"mi\">2</span> <span class=\"mf\">3.0</span>\n</code></pre>\n</div>\n\n<p>See also: <a href=\"https://github.com/tobymao/sqlglot/blob/main/posts/python_sql_engine.md\">Writing a Python SQL engine from scratch</a>.</p>\n\n<h2 id=\"used-by\">Used By</h2>\n\n<ul>\n<li><a href=\"https://github.com/TobikoData/sqlmesh\">SQLMesh</a></li>\n<li><a href=\"https://github.com/apache/superset\">Apache Superset</a></li>\n<li><a href=\"https://github.com/dagster-io/dagster\">Dagster</a></li>\n<li><a href=\"https://github.com/fugue-project/fugue\">Fugue</a></li>\n<li><a href=\"https://github.com/ibis-project/ibis\">ibis</a></li>\n<li><a href=\"https://github.com/kelsin/mysql-mimic\">mysql-mimic</a></li>\n<li><a href=\"https://github.com/pinterest/querybook\">Querybook</a></li>\n<li><a href=\"https://github.com/marsupialtail/quokka\">Quokka</a></li>\n<li><a href=\"https://github.com/moj-analytical-services/splink\">Splink</a></li>\n</ul>\n\n<h2 id=\"documentation\">Documentation</h2>\n\n<p>SQLGlot uses <a href=\"https://pdoc.dev/\">pdoc</a> to serve its API documentation.</p>\n\n<p>A hosted version is on the <a href=\"https://sqlglot.com/\">SQLGlot website</a>, or you can build locally with:</p>\n\n<pre><code>make docs-serve\n</code></pre>\n\n<h2 id=\"run-tests-and-lint\">Run Tests and Lint</h2>\n\n<pre><code>make style # Only linter checks\nmake unit # Only unit tests (or unit-rs, to use the Rust tokenizer)\nmake test # Unit and integration tests (or test-rs, to use the Rust tokenizer)\nmake check # Full test suite & linter checks\n</code></pre>\n\n<h2 id=\"benchmarks\">Benchmarks</h2>\n\n<p><a href=\"https://github.com/tobymao/sqlglot/blob/main/benchmarks/bench.py\">Benchmarks</a> run on Python 3.10.12 in seconds.</p>\n\n<table>\n<thead>\n<tr>\n <th>Query</th>\n <th>sqlglot</th>\n <th>sqlglotrs</th>\n <th>sqlfluff</th>\n <th>sqltree</th>\n <th>sqlparse</th>\n <th>moz_sql_parser</th>\n <th>sqloxide</th>\n</tr>\n</thead>\n<tbody>\n<tr>\n <td>tpch</td>\n <td>0.00944 (1.0)</td>\n <td>0.00590 (0.625)</td>\n <td>0.32116 (33.98)</td>\n <td>0.00693 (0.734)</td>\n <td>0.02858 (3.025)</td>\n <td>0.03337 (3.532)</td>\n <td>0.00073 (0.077)</td>\n</tr>\n<tr>\n <td>short</td>\n <td>0.00065 (1.0)</td>\n <td>0.00044 (0.687)</td>\n <td>0.03511 (53.82)</td>\n <td>0.00049 (0.759)</td>\n <td>0.00163 (2.506)</td>\n <td>0.00234 (3.601)</td>\n <td>0.00005 (0.073)</td>\n</tr>\n<tr>\n <td>long</td>\n <td>0.00889 (1.0)</td>\n <td>0.00572 (0.643)</td>\n <td>0.36982 (41.56)</td>\n <td>0.00614 (0.690)</td>\n <td>0.02530 (2.844)</td>\n <td>0.02931 (3.294)</td>\n <td>0.00059 (0.066)</td>\n</tr>\n<tr>\n <td>crazy</td>\n <td>0.02918 (1.0)</td>\n <td>0.01991 (0.682)</td>\n <td>1.88695 (64.66)</td>\n <td>0.02003 (0.686)</td>\n <td>7.46894 (255.9)</td>\n <td>0.64994 (22.27)</td>\n <td>0.00327 (0.112)</td>\n</tr>\n</tbody>\n</table>\n\n<h2 id=\"optional-dependencies\">Optional Dependencies</h2>\n\n<p>SQLGlot uses <a href=\"https://github.com/dateutil/dateutil\">dateutil</a> to simplify literal timedelta expressions. The optimizer will not simplify expressions like the following if the module cannot be found:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"n\">x</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"nb\">interval</span><span class=\"w\"> </span><span class=\"s1\">'1'</span><span class=\"w\"> </span><span class=\"k\">month</span>\n</code></pre>\n</div>\n\n<hr />\n"}, "sqlglot.logger": {"fullname": "sqlglot.logger", "modulename": "sqlglot", "qualname": "logger", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Logger sqlglot (WARNING)>"}, "sqlglot.pretty": {"fullname": "sqlglot.pretty", "modulename": "sqlglot", "qualname": "pretty", "kind": "variable", "doc": "<p>Whether to format generated SQL by default.</p>\n", "default_value": "False"}, "sqlglot.schema": {"fullname": "sqlglot.schema", "modulename": "sqlglot.schema", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.tokenize": {"fullname": "sqlglot.tokenize", "modulename": "sqlglot", "qualname": "tokenize", "kind": "function", "doc": "<p>Tokenizes the given SQL string.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>sql:</strong> the SQL code string to tokenize.</li>\n<li><strong>read:</strong> the SQL dialect to apply during tokenizing (eg. \"spark\", \"hive\", \"presto\", \"mysql\").</li>\n<li><strong>dialect:</strong> the SQL dialect (alias for read).</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The resulting list of tokens.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">sql</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">read</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">tokens</span><span class=\"o\">.</span><span class=\"n\">Token</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.parse": {"fullname": "sqlglot.parse", "modulename": "sqlglot", "qualname": "parse", "kind": "function", "doc": "<p>Parses the given SQL string into a collection of syntax trees, one per parsed SQL statement.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>sql:</strong> the SQL code string to parse.</li>\n<li><strong>read:</strong> the SQL dialect to apply during parsing (eg. \"spark\", \"hive\", \"presto\", \"mysql\").</li>\n<li><strong>dialect:</strong> the SQL dialect (alias for read).</li>\n<li><strong>**opts:</strong> other <code>sqlglot.parser.Parser</code> options.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The resulting syntax tree collection.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">sql</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">read</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]]</span>:</span></span>", "funcdef": "def"}, "sqlglot.parse_one": {"fullname": "sqlglot.parse_one", "modulename": "sqlglot", "qualname": "parse_one", "kind": "function", "doc": "<p>Parses the given SQL string and returns a syntax tree for the first parsed SQL statement.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>sql:</strong> the SQL code string to parse.</li>\n<li><strong>read:</strong> the SQL dialect to apply during parsing (eg. \"spark\", \"hive\", \"presto\", \"mysql\").</li>\n<li><strong>dialect:</strong> the SQL dialect (alias for read)</li>\n<li><strong>into:</strong> the SQLGlot Expression to parse into.</li>\n<li><strong>**opts:</strong> other <code>sqlglot.parser.Parser</code> options.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The syntax tree for the first parsed statement.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">sql</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">read</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">into</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">],</span> <span class=\"n\">Collection</span><span class=\"p\">[</span><span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]]],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.transpile": {"fullname": "sqlglot.transpile", "modulename": "sqlglot", "qualname": "transpile", "kind": "function", "doc": "<p>Parses the given SQL string in accordance with the source dialect and returns a list of SQL strings transformed\nto conform to the target dialect. Each string in the returned list represents a single transformed SQL statement.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>sql:</strong> the SQL code string to transpile.</li>\n<li><strong>read:</strong> the source dialect used to parse the input string (eg. \"spark\", \"hive\", \"presto\", \"mysql\").</li>\n<li><strong>write:</strong> the target dialect into which the input should be transformed (eg. \"spark\", \"hive\", \"presto\", \"mysql\").</li>\n<li><strong>identity:</strong> if set to <code>True</code> and if the target dialect is not specified the source dialect will be used as both:\nthe source and the target dialect.</li>\n<li><strong>error_level:</strong> the desired error level of the parser.</li>\n<li><strong>**opts:</strong> other <code>sqlglot.generator.Generator</code> options.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The list of transpiled SQL statements.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">sql</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">read</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">write</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">identity</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">error_level</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">errors</span><span class=\"o\">.</span><span class=\"n\">ErrorLevel</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe": {"fullname": "sqlglot.dataframe", "modulename": "sqlglot.dataframe", "kind": "module", "doc": "<h1 id=\"pyspark-dataframe-sql-generator\">PySpark DataFrame SQL Generator</h1>\n\n<p>This is a drop-in replacement for the PySpark DataFrame API that will generate SQL instead of executing DataFrame operations directly. This, when combined with the transpiling support in SQLGlot, allows one to write PySpark DataFrame code and execute it on other engines like <a href=\"https://duckdb.org/\">DuckDB</a>, <a href=\"https://prestodb.io/\">Presto</a>, <a href=\"https://spark.apache.org/\">Spark</a>, <a href=\"https://www.snowflake.com/en/\">Snowflake</a>, and <a href=\"https://cloud.google.com/bigquery/\">BigQuery</a>. </p>\n\n<p>Currently many of the common operations are covered and more functionality will be added over time. Please <a href=\"https://github.com/tobymao/sqlglot/issues\">open an issue</a> or <a href=\"https://github.com/tobymao/sqlglot/pulls\">PR</a> with your feedback or contribution to help influence what should be prioritized next and make sure your use case is properly supported.</p>\n\n<h1 id=\"how-to-use\">How to use</h1>\n\n<h2 id=\"instructions\">Instructions</h2>\n\n<ul>\n<li><a href=\"https://github.com/tobymao/sqlglot/blob/main/README.md#install\">Install SQLGlot</a> and that is all that is required to just generate SQL. <a href=\"#examples\">The examples</a> show generating SQL and then executing that SQL on a specific engine and that will require that engine's client library.</li>\n<li>Find/replace all <code>from pyspark.sql</code> with <code>from sqlglot.dataframe</code>.</li>\n<li>Prior to any <code>spark.read.table</code> or <code>spark.table</code> run <code>sqlglot.schema.add_table('<table_name>', <column_structure>, dialect=\"spark\")</code>.\n<ul>\n<li>The column structure can be defined the following ways:\n<ul>\n<li>Dictionary where the keys are column names and values are string of the Spark SQL type name.\n<ul>\n<li>Ex: <code>{'cola': 'string', 'colb': 'int'}</code></li>\n</ul></li>\n<li>PySpark DataFrame <code>StructType</code> similar to when using <code>createDataFrame</code>.\n<ul>\n<li>Ex: <code>StructType([StructField('cola', StringType()), StructField('colb', IntegerType())])</code></li>\n</ul></li>\n<li>A string of names and types similar to what is supported in <code>createDataFrame</code>.\n<ul>\n<li>Ex: <code>cola: STRING, colb: INT</code></li>\n</ul></li>\n<li>[Not Recommended] A list of string column names without type.\n<ul>\n<li>Ex: <code>['cola', 'colb']</code></li>\n<li>The lack of types may limit functionality in future releases.</li>\n</ul></li>\n</ul></li>\n<li>See <a href=\"#registering-custom-schema-class\">Registering Custom Schema</a> for information on how to skip this step if the information is stored externally.</li>\n</ul></li>\n<li>If your output SQL dialect is not Spark, then configure the SparkSession to use that dialect\n<ul>\n<li>Ex: <code>SparkSession().builder.config(\"sqlframe.dialect\", \"bigquery\").getOrCreate()</code></li>\n<li>See <a href=\"https://github.com/tobymao/sqlglot/tree/main/sqlglot/dialects\">dialects</a> for a full list of dialects.</li>\n</ul></li>\n<li>Add <code>.sql(pretty=True)</code> to your final DataFrame command to return a list of sql statements to run that command.\n<ul>\n<li>In most cases a single SQL statement is returned. Currently the only exception is when caching DataFrames which isn't supported in other dialects.</li>\n<li>Ex: <code>.sql(pretty=True)</code></li>\n</ul></li>\n</ul>\n\n<h2 id=\"examples\">Examples</h2>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"kn\">from</span> <span class=\"nn\">sqlglot.dataframe.sql.session</span> <span class=\"kn\">import</span> <span class=\"n\">SparkSession</span>\n<span class=\"kn\">from</span> <span class=\"nn\">sqlglot.dataframe.sql</span> <span class=\"kn\">import</span> <span class=\"n\">functions</span> <span class=\"k\">as</span> <span class=\"n\">F</span>\n\n<span class=\"n\">dialect</span> <span class=\"o\">=</span> <span class=\"s2\">"spark"</span>\n\n<span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">schema</span><span class=\"o\">.</span><span class=\"n\">add_table</span><span class=\"p\">(</span>\n <span class=\"s1\">'employee'</span><span class=\"p\">,</span>\n <span class=\"p\">{</span>\n <span class=\"s1\">'employee_id'</span><span class=\"p\">:</span> <span class=\"s1\">'INT'</span><span class=\"p\">,</span>\n <span class=\"s1\">'fname'</span><span class=\"p\">:</span> <span class=\"s1\">'STRING'</span><span class=\"p\">,</span>\n <span class=\"s1\">'lname'</span><span class=\"p\">:</span> <span class=\"s1\">'STRING'</span><span class=\"p\">,</span>\n <span class=\"s1\">'age'</span><span class=\"p\">:</span> <span class=\"s1\">'INT'</span><span class=\"p\">,</span>\n <span class=\"p\">},</span>\n <span class=\"n\">dialect</span><span class=\"o\">=</span><span class=\"n\">dialect</span><span class=\"p\">,</span>\n<span class=\"p\">)</span> <span class=\"c1\"># Register the table structure prior to reading from the table</span>\n\n<span class=\"n\">spark</span> <span class=\"o\">=</span> <span class=\"n\">SparkSession</span><span class=\"o\">.</span><span class=\"n\">builder</span><span class=\"o\">.</span><span class=\"n\">config</span><span class=\"p\">(</span><span class=\"s2\">"sqlframe.dialect"</span><span class=\"p\">,</span> <span class=\"n\">dialect</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">getOrCreate</span><span class=\"p\">()</span>\n\n<span class=\"n\">df</span> <span class=\"o\">=</span> <span class=\"p\">(</span>\n <span class=\"n\">spark</span>\n <span class=\"o\">.</span><span class=\"n\">table</span><span class=\"p\">(</span><span class=\"s1\">'employee'</span><span class=\"p\">)</span>\n <span class=\"o\">.</span><span class=\"n\">groupBy</span><span class=\"p\">(</span><span class=\"n\">F</span><span class=\"o\">.</span><span class=\"n\">col</span><span class=\"p\">(</span><span class=\"s2\">"age"</span><span class=\"p\">))</span>\n <span class=\"o\">.</span><span class=\"n\">agg</span><span class=\"p\">(</span><span class=\"n\">F</span><span class=\"o\">.</span><span class=\"n\">countDistinct</span><span class=\"p\">(</span><span class=\"n\">F</span><span class=\"o\">.</span><span class=\"n\">col</span><span class=\"p\">(</span><span class=\"s2\">"employee_id"</span><span class=\"p\">))</span><span class=\"o\">.</span><span class=\"n\">alias</span><span class=\"p\">(</span><span class=\"s2\">"num_employees"</span><span class=\"p\">))</span> \n<span class=\"p\">)</span>\n\n<span class=\"nb\">print</span><span class=\"p\">(</span><span class=\"n\">df</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">(</span><span class=\"n\">pretty</span><span class=\"o\">=</span><span class=\"kc\">True</span><span class=\"p\">))</span>\n</code></pre>\n</div>\n\n<pre><code>SELECT\n `employee`.`age` AS `age`,\n COUNT(DISTINCT `employee`.`employee_id`) AS `num_employees`\nFROM `employee` AS `employee`\nGROUP BY\n `employee`.`age`\n</code></pre>\n\n<h2 id=\"registering-custom-schema-class\">Registering Custom Schema Class</h2>\n\n<p>The step of adding <code>sqlglot.schema.add_table</code> can be skipped if you have the column structure stored externally like in a file or from an external metadata table. This can be done by writing a class that implements the <code>sqlglot.schema.Schema</code> abstract class and then assigning that class to <code>sqlglot.schema</code>. </p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"kn\">from</span> <span class=\"nn\">sqlglot.dataframe.sql.session</span> <span class=\"kn\">import</span> <span class=\"n\">SparkSession</span>\n<span class=\"kn\">from</span> <span class=\"nn\">sqlglot.dataframe.sql</span> <span class=\"kn\">import</span> <span class=\"n\">functions</span> <span class=\"k\">as</span> <span class=\"n\">F</span>\n<span class=\"kn\">from</span> <span class=\"nn\">sqlglot.schema</span> <span class=\"kn\">import</span> <span class=\"n\">Schema</span>\n\n\n<span class=\"k\">class</span> <span class=\"nc\">ExternalSchema</span><span class=\"p\">(</span><span class=\"n\">Schema</span><span class=\"p\">):</span>\n <span class=\"o\">...</span>\n\n<span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">schema</span> <span class=\"o\">=</span> <span class=\"n\">ExternalSchema</span><span class=\"p\">()</span>\n\n<span class=\"n\">spark</span> <span class=\"o\">=</span> <span class=\"n\">SparkSession</span><span class=\"p\">()</span> <span class=\"c1\"># Spark will be used by default is not specific in SparkSession config</span>\n\n<span class=\"n\">df</span> <span class=\"o\">=</span> <span class=\"p\">(</span>\n <span class=\"n\">spark</span>\n <span class=\"o\">.</span><span class=\"n\">table</span><span class=\"p\">(</span><span class=\"s1\">'employee'</span><span class=\"p\">)</span>\n <span class=\"o\">.</span><span class=\"n\">groupBy</span><span class=\"p\">(</span><span class=\"n\">F</span><span class=\"o\">.</span><span class=\"n\">col</span><span class=\"p\">(</span><span class=\"s2\">"age"</span><span class=\"p\">))</span>\n <span class=\"o\">.</span><span class=\"n\">agg</span><span class=\"p\">(</span><span class=\"n\">F</span><span class=\"o\">.</span><span class=\"n\">countDistinct</span><span class=\"p\">(</span><span class=\"n\">F</span><span class=\"o\">.</span><span class=\"n\">col</span><span class=\"p\">(</span><span class=\"s2\">"employee_id"</span><span class=\"p\">))</span><span class=\"o\">.</span><span class=\"n\">alias</span><span class=\"p\">(</span><span class=\"s2\">"num_employees"</span><span class=\"p\">))</span> \n<span class=\"p\">)</span>\n\n<span class=\"nb\">print</span><span class=\"p\">(</span><span class=\"n\">df</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">(</span><span class=\"n\">pretty</span><span class=\"o\">=</span><span class=\"kc\">True</span><span class=\"p\">))</span>\n</code></pre>\n</div>\n\n<h2 id=\"example-implementations\">Example Implementations</h2>\n\n<h3 id=\"bigquery\">Bigquery</h3>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"kn\">from</span> <span class=\"nn\">google.cloud</span> <span class=\"kn\">import</span> <span class=\"n\">bigquery</span>\n<span class=\"kn\">from</span> <span class=\"nn\">sqlglot.dataframe.sql.session</span> <span class=\"kn\">import</span> <span class=\"n\">SparkSession</span>\n<span class=\"kn\">from</span> <span class=\"nn\">sqlglot.dataframe.sql</span> <span class=\"kn\">import</span> <span class=\"n\">types</span>\n<span class=\"kn\">from</span> <span class=\"nn\">sqlglot.dataframe.sql</span> <span class=\"kn\">import</span> <span class=\"n\">functions</span> <span class=\"k\">as</span> <span class=\"n\">F</span>\n\n<span class=\"n\">client</span> <span class=\"o\">=</span> <span class=\"n\">bigquery</span><span class=\"o\">.</span><span class=\"n\">Client</span><span class=\"p\">()</span>\n\n<span class=\"n\">data</span> <span class=\"o\">=</span> <span class=\"p\">[</span>\n <span class=\"p\">(</span><span class=\"mi\">1</span><span class=\"p\">,</span> <span class=\"s2\">"Jack"</span><span class=\"p\">,</span> <span class=\"s2\">"Shephard"</span><span class=\"p\">,</span> <span class=\"mi\">34</span><span class=\"p\">),</span>\n <span class=\"p\">(</span><span class=\"mi\">2</span><span class=\"p\">,</span> <span class=\"s2\">"John"</span><span class=\"p\">,</span> <span class=\"s2\">"Locke"</span><span class=\"p\">,</span> <span class=\"mi\">48</span><span class=\"p\">),</span>\n <span class=\"p\">(</span><span class=\"mi\">3</span><span class=\"p\">,</span> <span class=\"s2\">"Kate"</span><span class=\"p\">,</span> <span class=\"s2\">"Austen"</span><span class=\"p\">,</span> <span class=\"mi\">34</span><span class=\"p\">),</span>\n <span class=\"p\">(</span><span class=\"mi\">4</span><span class=\"p\">,</span> <span class=\"s2\">"Claire"</span><span class=\"p\">,</span> <span class=\"s2\">"Littleton"</span><span class=\"p\">,</span> <span class=\"mi\">22</span><span class=\"p\">),</span>\n <span class=\"p\">(</span><span class=\"mi\">5</span><span class=\"p\">,</span> <span class=\"s2\">"Hugo"</span><span class=\"p\">,</span> <span class=\"s2\">"Reyes"</span><span class=\"p\">,</span> <span class=\"mi\">26</span><span class=\"p\">),</span>\n<span class=\"p\">]</span>\n<span class=\"n\">schema</span> <span class=\"o\">=</span> <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">StructType</span><span class=\"p\">([</span>\n <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">StructField</span><span class=\"p\">(</span><span class=\"s1\">'employee_id'</span><span class=\"p\">,</span> <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">IntegerType</span><span class=\"p\">(),</span> <span class=\"kc\">False</span><span class=\"p\">),</span>\n <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">StructField</span><span class=\"p\">(</span><span class=\"s1\">'fname'</span><span class=\"p\">,</span> <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">StringType</span><span class=\"p\">(),</span> <span class=\"kc\">False</span><span class=\"p\">),</span>\n <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">StructField</span><span class=\"p\">(</span><span class=\"s1\">'lname'</span><span class=\"p\">,</span> <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">StringType</span><span class=\"p\">(),</span> <span class=\"kc\">False</span><span class=\"p\">),</span>\n <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">StructField</span><span class=\"p\">(</span><span class=\"s1\">'age'</span><span class=\"p\">,</span> <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">IntegerType</span><span class=\"p\">(),</span> <span class=\"kc\">False</span><span class=\"p\">),</span>\n<span class=\"p\">])</span>\n\n<span class=\"n\">sql_statements</span> <span class=\"o\">=</span> <span class=\"p\">(</span>\n <span class=\"n\">SparkSession</span>\n <span class=\"o\">.</span><span class=\"n\">builder</span>\n <span class=\"o\">.</span><span class=\"n\">config</span><span class=\"p\">(</span><span class=\"s2\">"sqlframe.dialect"</span><span class=\"p\">,</span> <span class=\"s2\">"bigquery"</span><span class=\"p\">)</span>\n <span class=\"o\">.</span><span class=\"n\">getOrCreate</span><span class=\"p\">()</span>\n <span class=\"o\">.</span><span class=\"n\">createDataFrame</span><span class=\"p\">(</span><span class=\"n\">data</span><span class=\"p\">,</span> <span class=\"n\">schema</span><span class=\"p\">)</span>\n <span class=\"o\">.</span><span class=\"n\">groupBy</span><span class=\"p\">(</span><span class=\"n\">F</span><span class=\"o\">.</span><span class=\"n\">col</span><span class=\"p\">(</span><span class=\"s2\">"age"</span><span class=\"p\">))</span>\n <span class=\"o\">.</span><span class=\"n\">agg</span><span class=\"p\">(</span><span class=\"n\">F</span><span class=\"o\">.</span><span class=\"n\">countDistinct</span><span class=\"p\">(</span><span class=\"n\">F</span><span class=\"o\">.</span><span class=\"n\">col</span><span class=\"p\">(</span><span class=\"s2\">"employee_id"</span><span class=\"p\">))</span><span class=\"o\">.</span><span class=\"n\">alias</span><span class=\"p\">(</span><span class=\"s2\">"num_employees"</span><span class=\"p\">))</span>\n <span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"p\">)</span>\n\n<span class=\"n\">result</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>\n<span class=\"k\">for</span> <span class=\"n\">sql</span> <span class=\"ow\">in</span> <span class=\"n\">sql_statements</span><span class=\"p\">:</span>\n <span class=\"n\">result</span> <span class=\"o\">=</span> <span class=\"n\">client</span><span class=\"o\">.</span><span class=\"n\">query</span><span class=\"p\">(</span><span class=\"n\">sql</span><span class=\"p\">)</span>\n\n<span class=\"k\">assert</span> <span class=\"n\">result</span> <span class=\"ow\">is</span> <span class=\"ow\">not</span> <span class=\"kc\">None</span>\n<span class=\"k\">for</span> <span class=\"n\">row</span> <span class=\"ow\">in</span> <span class=\"n\">client</span><span class=\"o\">.</span><span class=\"n\">query</span><span class=\"p\">(</span><span class=\"n\">result</span><span class=\"p\">):</span>\n <span class=\"nb\">print</span><span class=\"p\">(</span><span class=\"sa\">f</span><span class=\"s2\">"Age: </span><span class=\"si\">{</span><span class=\"n\">row</span><span class=\"p\">[</span><span class=\"s1\">'age'</span><span class=\"p\">]</span><span class=\"si\">}</span><span class=\"s2\">, Num Employees: </span><span class=\"si\">{</span><span class=\"n\">row</span><span class=\"p\">[</span><span class=\"s1\">'num_employees'</span><span class=\"p\">]</span><span class=\"si\">}</span><span class=\"s2\">"</span><span class=\"p\">)</span>\n</code></pre>\n</div>\n\n<h3 id=\"snowflake\">Snowflake</h3>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"kn\">import</span> <span class=\"nn\">os</span>\n\n<span class=\"kn\">import</span> <span class=\"nn\">snowflake.connector</span>\n<span class=\"kn\">from</span> <span class=\"nn\">sqlglot.dataframe.session</span> <span class=\"kn\">import</span> <span class=\"n\">SparkSession</span>\n<span class=\"kn\">from</span> <span class=\"nn\">sqlglot.dataframe</span> <span class=\"kn\">import</span> <span class=\"n\">types</span>\n<span class=\"kn\">from</span> <span class=\"nn\">sqlglot.dataframe</span> <span class=\"kn\">import</span> <span class=\"n\">functions</span> <span class=\"k\">as</span> <span class=\"n\">F</span>\n\n<span class=\"n\">ctx</span> <span class=\"o\">=</span> <span class=\"n\">snowflake</span><span class=\"o\">.</span><span class=\"n\">connector</span><span class=\"o\">.</span><span class=\"n\">connect</span><span class=\"p\">(</span>\n <span class=\"n\">user</span><span class=\"o\">=</span><span class=\"n\">os</span><span class=\"o\">.</span><span class=\"n\">environ</span><span class=\"p\">[</span><span class=\"s2\">"SNOWFLAKE_USER"</span><span class=\"p\">],</span>\n <span class=\"n\">password</span><span class=\"o\">=</span><span class=\"n\">os</span><span class=\"o\">.</span><span class=\"n\">environ</span><span class=\"p\">[</span><span class=\"s2\">"SNOWFLAKE_PASS"</span><span class=\"p\">],</span>\n <span class=\"n\">account</span><span class=\"o\">=</span><span class=\"n\">os</span><span class=\"o\">.</span><span class=\"n\">environ</span><span class=\"p\">[</span><span class=\"s2\">"SNOWFLAKE_ACCOUNT"</span><span class=\"p\">]</span>\n<span class=\"p\">)</span>\n<span class=\"n\">cs</span> <span class=\"o\">=</span> <span class=\"n\">ctx</span><span class=\"o\">.</span><span class=\"n\">cursor</span><span class=\"p\">()</span>\n\n<span class=\"n\">data</span> <span class=\"o\">=</span> <span class=\"p\">[</span>\n <span class=\"p\">(</span><span class=\"mi\">1</span><span class=\"p\">,</span> <span class=\"s2\">"Jack"</span><span class=\"p\">,</span> <span class=\"s2\">"Shephard"</span><span class=\"p\">,</span> <span class=\"mi\">34</span><span class=\"p\">),</span>\n <span class=\"p\">(</span><span class=\"mi\">2</span><span class=\"p\">,</span> <span class=\"s2\">"John"</span><span class=\"p\">,</span> <span class=\"s2\">"Locke"</span><span class=\"p\">,</span> <span class=\"mi\">48</span><span class=\"p\">),</span>\n <span class=\"p\">(</span><span class=\"mi\">3</span><span class=\"p\">,</span> <span class=\"s2\">"Kate"</span><span class=\"p\">,</span> <span class=\"s2\">"Austen"</span><span class=\"p\">,</span> <span class=\"mi\">34</span><span class=\"p\">),</span>\n <span class=\"p\">(</span><span class=\"mi\">4</span><span class=\"p\">,</span> <span class=\"s2\">"Claire"</span><span class=\"p\">,</span> <span class=\"s2\">"Littleton"</span><span class=\"p\">,</span> <span class=\"mi\">22</span><span class=\"p\">),</span>\n <span class=\"p\">(</span><span class=\"mi\">5</span><span class=\"p\">,</span> <span class=\"s2\">"Hugo"</span><span class=\"p\">,</span> <span class=\"s2\">"Reyes"</span><span class=\"p\">,</span> <span class=\"mi\">26</span><span class=\"p\">),</span>\n<span class=\"p\">]</span>\n<span class=\"n\">schema</span> <span class=\"o\">=</span> <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">StructType</span><span class=\"p\">([</span>\n <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">StructField</span><span class=\"p\">(</span><span class=\"s1\">'employee_id'</span><span class=\"p\">,</span> <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">IntegerType</span><span class=\"p\">(),</span> <span class=\"kc\">False</span><span class=\"p\">),</span>\n <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">StructField</span><span class=\"p\">(</span><span class=\"s1\">'fname'</span><span class=\"p\">,</span> <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">StringType</span><span class=\"p\">(),</span> <span class=\"kc\">False</span><span class=\"p\">),</span>\n <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">StructField</span><span class=\"p\">(</span><span class=\"s1\">'lname'</span><span class=\"p\">,</span> <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">StringType</span><span class=\"p\">(),</span> <span class=\"kc\">False</span><span class=\"p\">),</span>\n <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">StructField</span><span class=\"p\">(</span><span class=\"s1\">'age'</span><span class=\"p\">,</span> <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">IntegerType</span><span class=\"p\">(),</span> <span class=\"kc\">False</span><span class=\"p\">),</span>\n<span class=\"p\">])</span>\n\n<span class=\"n\">sql_statements</span> <span class=\"o\">=</span> <span class=\"p\">(</span>\n <span class=\"n\">SparkSession</span>\n <span class=\"o\">.</span><span class=\"n\">builder</span>\n <span class=\"o\">.</span><span class=\"n\">config</span><span class=\"p\">(</span><span class=\"s2\">"sqlframe.dialect"</span><span class=\"p\">,</span> <span class=\"s2\">"snowflake"</span><span class=\"p\">)</span>\n <span class=\"o\">.</span><span class=\"n\">getOrCreate</span><span class=\"p\">()</span>\n <span class=\"o\">.</span><span class=\"n\">createDataFrame</span><span class=\"p\">(</span><span class=\"n\">data</span><span class=\"p\">,</span> <span class=\"n\">schema</span><span class=\"p\">)</span>\n <span class=\"o\">.</span><span class=\"n\">groupBy</span><span class=\"p\">(</span><span class=\"n\">F</span><span class=\"o\">.</span><span class=\"n\">col</span><span class=\"p\">(</span><span class=\"s2\">"age"</span><span class=\"p\">))</span>\n <span class=\"o\">.</span><span class=\"n\">agg</span><span class=\"p\">(</span><span class=\"n\">F</span><span class=\"o\">.</span><span class=\"n\">countDistinct</span><span class=\"p\">(</span><span class=\"n\">F</span><span class=\"o\">.</span><span class=\"n\">col</span><span class=\"p\">(</span><span class=\"s2\">"lname"</span><span class=\"p\">))</span><span class=\"o\">.</span><span class=\"n\">alias</span><span class=\"p\">(</span><span class=\"s2\">"num_employees"</span><span class=\"p\">))</span>\n <span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"p\">)</span>\n\n<span class=\"k\">try</span><span class=\"p\">:</span>\n <span class=\"k\">for</span> <span class=\"n\">sql</span> <span class=\"ow\">in</span> <span class=\"n\">sql_statements</span><span class=\"p\">:</span>\n <span class=\"n\">cs</span><span class=\"o\">.</span><span class=\"n\">execute</span><span class=\"p\">(</span><span class=\"n\">sql</span><span class=\"p\">)</span>\n <span class=\"n\">results</span> <span class=\"o\">=</span> <span class=\"n\">cs</span><span class=\"o\">.</span><span class=\"n\">fetchall</span><span class=\"p\">()</span>\n <span class=\"k\">for</span> <span class=\"n\">row</span> <span class=\"ow\">in</span> <span class=\"n\">results</span><span class=\"p\">:</span>\n <span class=\"nb\">print</span><span class=\"p\">(</span><span class=\"sa\">f</span><span class=\"s2\">"Age: </span><span class=\"si\">{</span><span class=\"n\">row</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"si\">}</span><span class=\"s2\">, Num Employees: </span><span class=\"si\">{</span><span class=\"n\">row</span><span class=\"p\">[</span><span class=\"mi\">1</span><span class=\"p\">]</span><span class=\"si\">}</span><span class=\"s2\">"</span><span class=\"p\">)</span>\n<span class=\"k\">finally</span><span class=\"p\">:</span>\n <span class=\"n\">cs</span><span class=\"o\">.</span><span class=\"n\">close</span><span class=\"p\">()</span>\n<span class=\"n\">ctx</span><span class=\"o\">.</span><span class=\"n\">close</span><span class=\"p\">()</span>\n</code></pre>\n</div>\n\n<h3 id=\"spark\">Spark</h3>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"kn\">from</span> <span class=\"nn\">pyspark.sql.session</span> <span class=\"kn\">import</span> <span class=\"n\">SparkSession</span> <span class=\"k\">as</span> <span class=\"n\">PySparkSession</span>\n<span class=\"kn\">from</span> <span class=\"nn\">sqlglot.dataframe.sql.session</span> <span class=\"kn\">import</span> <span class=\"n\">SparkSession</span>\n<span class=\"kn\">from</span> <span class=\"nn\">sqlglot.dataframe.sql</span> <span class=\"kn\">import</span> <span class=\"n\">types</span>\n<span class=\"kn\">from</span> <span class=\"nn\">sqlglot.dataframe.sql</span> <span class=\"kn\">import</span> <span class=\"n\">functions</span> <span class=\"k\">as</span> <span class=\"n\">F</span>\n\n<span class=\"n\">data</span> <span class=\"o\">=</span> <span class=\"p\">[</span>\n <span class=\"p\">(</span><span class=\"mi\">1</span><span class=\"p\">,</span> <span class=\"s2\">"Jack"</span><span class=\"p\">,</span> <span class=\"s2\">"Shephard"</span><span class=\"p\">,</span> <span class=\"mi\">34</span><span class=\"p\">),</span>\n <span class=\"p\">(</span><span class=\"mi\">2</span><span class=\"p\">,</span> <span class=\"s2\">"John"</span><span class=\"p\">,</span> <span class=\"s2\">"Locke"</span><span class=\"p\">,</span> <span class=\"mi\">48</span><span class=\"p\">),</span>\n <span class=\"p\">(</span><span class=\"mi\">3</span><span class=\"p\">,</span> <span class=\"s2\">"Kate"</span><span class=\"p\">,</span> <span class=\"s2\">"Austen"</span><span class=\"p\">,</span> <span class=\"mi\">34</span><span class=\"p\">),</span>\n <span class=\"p\">(</span><span class=\"mi\">4</span><span class=\"p\">,</span> <span class=\"s2\">"Claire"</span><span class=\"p\">,</span> <span class=\"s2\">"Littleton"</span><span class=\"p\">,</span> <span class=\"mi\">22</span><span class=\"p\">),</span>\n <span class=\"p\">(</span><span class=\"mi\">5</span><span class=\"p\">,</span> <span class=\"s2\">"Hugo"</span><span class=\"p\">,</span> <span class=\"s2\">"Reyes"</span><span class=\"p\">,</span> <span class=\"mi\">26</span><span class=\"p\">),</span>\n<span class=\"p\">]</span>\n<span class=\"n\">schema</span> <span class=\"o\">=</span> <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">StructType</span><span class=\"p\">([</span>\n <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">StructField</span><span class=\"p\">(</span><span class=\"s1\">'employee_id'</span><span class=\"p\">,</span> <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">IntegerType</span><span class=\"p\">(),</span> <span class=\"kc\">False</span><span class=\"p\">),</span>\n <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">StructField</span><span class=\"p\">(</span><span class=\"s1\">'fname'</span><span class=\"p\">,</span> <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">StringType</span><span class=\"p\">(),</span> <span class=\"kc\">False</span><span class=\"p\">),</span>\n <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">StructField</span><span class=\"p\">(</span><span class=\"s1\">'lname'</span><span class=\"p\">,</span> <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">StringType</span><span class=\"p\">(),</span> <span class=\"kc\">False</span><span class=\"p\">),</span>\n <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">StructField</span><span class=\"p\">(</span><span class=\"s1\">'age'</span><span class=\"p\">,</span> <span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">IntegerType</span><span class=\"p\">(),</span> <span class=\"kc\">False</span><span class=\"p\">),</span>\n<span class=\"p\">])</span>\n\n<span class=\"n\">sql_statements</span> <span class=\"o\">=</span> <span class=\"p\">(</span>\n <span class=\"n\">SparkSession</span><span class=\"p\">()</span>\n <span class=\"o\">.</span><span class=\"n\">createDataFrame</span><span class=\"p\">(</span><span class=\"n\">data</span><span class=\"p\">,</span> <span class=\"n\">schema</span><span class=\"p\">)</span>\n <span class=\"o\">.</span><span class=\"n\">groupBy</span><span class=\"p\">(</span><span class=\"n\">F</span><span class=\"o\">.</span><span class=\"n\">col</span><span class=\"p\">(</span><span class=\"s2\">"age"</span><span class=\"p\">))</span>\n <span class=\"o\">.</span><span class=\"n\">agg</span><span class=\"p\">(</span><span class=\"n\">F</span><span class=\"o\">.</span><span class=\"n\">countDistinct</span><span class=\"p\">(</span><span class=\"n\">F</span><span class=\"o\">.</span><span class=\"n\">col</span><span class=\"p\">(</span><span class=\"s2\">"employee_id"</span><span class=\"p\">))</span><span class=\"o\">.</span><span class=\"n\">alias</span><span class=\"p\">(</span><span class=\"s2\">"num_employees"</span><span class=\"p\">))</span>\n <span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"p\">)</span>\n\n<span class=\"n\">pyspark</span> <span class=\"o\">=</span> <span class=\"n\">PySparkSession</span><span class=\"o\">.</span><span class=\"n\">builder</span><span class=\"o\">.</span><span class=\"n\">master</span><span class=\"p\">(</span><span class=\"s2\">"local[*]"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">getOrCreate</span><span class=\"p\">()</span>\n\n<span class=\"n\">df</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>\n<span class=\"k\">for</span> <span class=\"n\">sql</span> <span class=\"ow\">in</span> <span class=\"n\">sql_statements</span><span class=\"p\">:</span>\n <span class=\"n\">df</span> <span class=\"o\">=</span> <span class=\"n\">pyspark</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">(</span><span class=\"n\">sql</span><span class=\"p\">)</span>\n\n<span class=\"k\">assert</span> <span class=\"n\">df</span> <span class=\"ow\">is</span> <span class=\"ow\">not</span> <span class=\"kc\">None</span>\n<span class=\"n\">df</span><span class=\"o\">.</span><span class=\"n\">show</span><span class=\"p\">()</span>\n</code></pre>\n</div>\n\n<h1 id=\"unsupportable-operations\">Unsupportable Operations</h1>\n\n<p>Any operation that lacks a way to represent it in SQL cannot be supported by this tool. An example of this would be rdd operations. Since the DataFrame API though is mostly modeled around SQL concepts most operations can be supported.</p>\n"}, "sqlglot.dataframe.sql": {"fullname": "sqlglot.dataframe.sql", "modulename": "sqlglot.dataframe.sql", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.SparkSession": {"fullname": "sqlglot.dataframe.sql.SparkSession", "modulename": "sqlglot.dataframe.sql", "qualname": "SparkSession", "kind": "class", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.SparkSession.DEFAULT_DIALECT": {"fullname": "sqlglot.dataframe.sql.SparkSession.DEFAULT_DIALECT", "modulename": "sqlglot.dataframe.sql", "qualname": "SparkSession.DEFAULT_DIALECT", "kind": "variable", "doc": "<p></p>\n", "default_value": "'spark'"}, "sqlglot.dataframe.sql.SparkSession.read": {"fullname": "sqlglot.dataframe.sql.SparkSession.read", "modulename": "sqlglot.dataframe.sql", "qualname": "SparkSession.read", "kind": "variable", "doc": "<p></p>\n", "annotation": ": sqlglot.dataframe.sql.readwriter.DataFrameReader"}, "sqlglot.dataframe.sql.SparkSession.table": {"fullname": "sqlglot.dataframe.sql.SparkSession.table", "modulename": "sqlglot.dataframe.sql", "qualname": "SparkSession.table", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">tableName</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.SparkSession.createDataFrame": {"fullname": "sqlglot.dataframe.sql.SparkSession.createDataFrame", "modulename": "sqlglot.dataframe.sql", "qualname": "SparkSession.createDataFrame", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">data</span><span class=\"p\">:</span> <span class=\"n\">Sequence</span><span class=\"p\">[</span><span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666179102480'</span><span class=\"o\">></span><span class=\"p\">],</span> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666179102480'</span><span class=\"o\">></span><span class=\"p\">],</span> <span class=\"n\">Tuple</span><span class=\"p\">]]</span>,</span><span class=\"param\">\t<span class=\"n\">schema</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666180910912'</span><span class=\"o\">></span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">samplingRatio</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">float</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">verifySchema</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.SparkSession.sql": {"fullname": "sqlglot.dataframe.sql.SparkSession.sql", "modulename": "sqlglot.dataframe.sql", "qualname": "SparkSession.sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">sqlQuery</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.SparkSession.Builder": {"fullname": "sqlglot.dataframe.sql.SparkSession.Builder", "modulename": "sqlglot.dataframe.sql", "qualname": "SparkSession.Builder", "kind": "class", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.SparkSession.Builder.SQLFRAME_DIALECT_KEY": {"fullname": "sqlglot.dataframe.sql.SparkSession.Builder.SQLFRAME_DIALECT_KEY", "modulename": "sqlglot.dataframe.sql", "qualname": "SparkSession.Builder.SQLFRAME_DIALECT_KEY", "kind": "variable", "doc": "<p></p>\n", "default_value": "'sqlframe.dialect'"}, "sqlglot.dataframe.sql.SparkSession.Builder.dialect": {"fullname": "sqlglot.dataframe.sql.SparkSession.Builder.dialect", "modulename": "sqlglot.dataframe.sql", "qualname": "SparkSession.Builder.dialect", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.SparkSession.Builder.config": {"fullname": "sqlglot.dataframe.sql.SparkSession.Builder.config", "modulename": "sqlglot.dataframe.sql", "qualname": "SparkSession.Builder.config", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">key</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">value</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Any</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"o\">*</span>,</span><span class=\"param\">\t<span class=\"nb\">map</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">Any</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">kwargs</span><span class=\"p\">:</span> <span class=\"n\">Any</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">session</span><span class=\"o\">.</span><span class=\"n\">SparkSession</span><span class=\"o\">.</span><span class=\"n\">Builder</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.SparkSession.Builder.getOrCreate": {"fullname": "sqlglot.dataframe.sql.SparkSession.Builder.getOrCreate", "modulename": "sqlglot.dataframe.sql", "qualname": "SparkSession.Builder.getOrCreate", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">session</span><span class=\"o\">.</span><span class=\"n\">SparkSession</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.SparkSession.builder": {"fullname": "sqlglot.dataframe.sql.SparkSession.builder", "modulename": "sqlglot.dataframe.sql", "qualname": "SparkSession.builder", "kind": "variable", "doc": "<p></p>\n", "annotation": ": sqlglot.dataframe.sql.session.SparkSession.Builder"}, "sqlglot.dataframe.sql.DataFrame": {"fullname": "sqlglot.dataframe.sql.DataFrame", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame", "kind": "class", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.DataFrame.__init__": {"fullname": "sqlglot.dataframe.sql.DataFrame.__init__", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">spark</span><span class=\"p\">:</span> <span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666183911504'</span><span class=\"o\">></span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Select</span>,</span><span class=\"param\">\t<span class=\"n\">branch_id</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">sequence_id</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">last_op</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">operations</span><span class=\"o\">.</span><span class=\"n\">Operation</span> <span class=\"o\">=</span> <span class=\"o\"><</span><span class=\"n\">Operation</span><span class=\"o\">.</span><span class=\"n\">INIT</span><span class=\"p\">:</span> <span class=\"o\">-</span><span class=\"mi\">1</span><span class=\"o\">></span>,</span><span class=\"param\">\t<span class=\"n\">pending_hints</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">output_expression_container</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666193925152'</span><span class=\"o\">></span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">kwargs</span></span>)</span>"}, "sqlglot.dataframe.sql.DataFrame.spark": {"fullname": "sqlglot.dataframe.sql.DataFrame.spark", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.spark", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.DataFrame.expression": {"fullname": "sqlglot.dataframe.sql.DataFrame.expression", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.expression", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.DataFrame.branch_id": {"fullname": "sqlglot.dataframe.sql.DataFrame.branch_id", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.branch_id", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.DataFrame.sequence_id": {"fullname": "sqlglot.dataframe.sql.DataFrame.sequence_id", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.sequence_id", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.DataFrame.last_op": {"fullname": "sqlglot.dataframe.sql.DataFrame.last_op", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.last_op", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.DataFrame.pending_hints": {"fullname": "sqlglot.dataframe.sql.DataFrame.pending_hints", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.pending_hints", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.DataFrame.output_expression_container": {"fullname": "sqlglot.dataframe.sql.DataFrame.output_expression_container", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.output_expression_container", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.DataFrame.sparkSession": {"fullname": "sqlglot.dataframe.sql.DataFrame.sparkSession", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.sparkSession", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.DataFrame.write": {"fullname": "sqlglot.dataframe.sql.DataFrame.write", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.write", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.DataFrame.latest_cte_name": {"fullname": "sqlglot.dataframe.sql.DataFrame.latest_cte_name", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.latest_cte_name", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.dataframe.sql.DataFrame.pending_join_hints": {"fullname": "sqlglot.dataframe.sql.DataFrame.pending_join_hints", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.pending_join_hints", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.DataFrame.pending_partition_hints": {"fullname": "sqlglot.dataframe.sql.DataFrame.pending_partition_hints", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.pending_partition_hints", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.DataFrame.columns": {"fullname": "sqlglot.dataframe.sql.DataFrame.columns", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.columns", "kind": "variable", "doc": "<p></p>\n", "annotation": ": List[str]"}, "sqlglot.dataframe.sql.DataFrame.na": {"fullname": "sqlglot.dataframe.sql.DataFrame.na", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.na", "kind": "variable", "doc": "<p></p>\n", "annotation": ": sqlglot.dataframe.sql.dataframe.DataFrameNaFunctions"}, "sqlglot.dataframe.sql.DataFrame.sql": {"fullname": "sqlglot.dataframe.sql.DataFrame.sql", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666179831456'</span><span class=\"o\">></span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">optimize</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.copy": {"fullname": "sqlglot.dataframe.sql.DataFrame.copy", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.copy", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.select": {"fullname": "sqlglot.dataframe.sql.DataFrame.select", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.select", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">*</span><span class=\"n\">cols</span>, </span><span class=\"param\"><span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.alias": {"fullname": "sqlglot.dataframe.sql.DataFrame.alias", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.alias", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">name</span><span class=\"p\">:</span> <span class=\"nb\">str</span>, </span><span class=\"param\"><span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.where": {"fullname": "sqlglot.dataframe.sql.DataFrame.where", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.where", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">column</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span><span class=\"p\">,</span> <span class=\"nb\">bool</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.filter": {"fullname": "sqlglot.dataframe.sql.DataFrame.filter", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.filter", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">column</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span><span class=\"p\">,</span> <span class=\"nb\">bool</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.groupBy": {"fullname": "sqlglot.dataframe.sql.DataFrame.groupBy", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.groupBy", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">*</span><span class=\"n\">cols</span>, </span><span class=\"param\"><span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">group</span><span class=\"o\">.</span><span class=\"n\">GroupedData</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.agg": {"fullname": "sqlglot.dataframe.sql.DataFrame.agg", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.agg", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">*</span><span class=\"n\">exprs</span>, </span><span class=\"param\"><span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.join": {"fullname": "sqlglot.dataframe.sql.DataFrame.join", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.join", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">other_df</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>,</span><span class=\"param\">\t<span class=\"n\">on</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">],</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span><span class=\"p\">,</span> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span><span class=\"p\">]]</span>,</span><span class=\"param\">\t<span class=\"n\">how</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">'inner'</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.orderBy": {"fullname": "sqlglot.dataframe.sql.DataFrame.orderBy", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.orderBy", "kind": "function", "doc": "<p>This implementation lets any ordered columns take priority over whatever is provided in <code>ascending</code>. Spark\nhas irregular behavior and can result in runtime errors. Users shouldn't be mixing the two anyways so this\nis unlikely to come up.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">cols</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">ascending</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">Any</span><span class=\"p\">,</span> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">Any</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.sort": {"fullname": "sqlglot.dataframe.sql.DataFrame.sort", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.sort", "kind": "function", "doc": "<p>This implementation lets any ordered columns take priority over whatever is provided in <code>ascending</code>. Spark\nhas irregular behavior and can result in runtime errors. Users shouldn't be mixing the two anyways so this\nis unlikely to come up.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">cols</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">ascending</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">Any</span><span class=\"p\">,</span> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">Any</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.union": {"fullname": "sqlglot.dataframe.sql.DataFrame.union", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.union", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">other</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.unionAll": {"fullname": "sqlglot.dataframe.sql.DataFrame.unionAll", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.unionAll", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">other</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.unionByName": {"fullname": "sqlglot.dataframe.sql.DataFrame.unionByName", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.unionByName", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">other</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>,</span><span class=\"param\">\t<span class=\"n\">allowMissingColumns</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.intersect": {"fullname": "sqlglot.dataframe.sql.DataFrame.intersect", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.intersect", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">other</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.intersectAll": {"fullname": "sqlglot.dataframe.sql.DataFrame.intersectAll", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.intersectAll", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">other</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.exceptAll": {"fullname": "sqlglot.dataframe.sql.DataFrame.exceptAll", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.exceptAll", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">other</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.distinct": {"fullname": "sqlglot.dataframe.sql.DataFrame.distinct", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.distinct", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.dropDuplicates": {"fullname": "sqlglot.dataframe.sql.DataFrame.dropDuplicates", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.dropDuplicates", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">subset</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.dropna": {"fullname": "sqlglot.dataframe.sql.DataFrame.dropna", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.dropna", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">how</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">'any'</span>,</span><span class=\"param\">\t<span class=\"n\">thresh</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">int</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">subset</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">Tuple</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"o\">...</span><span class=\"p\">],</span> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.fillna": {"fullname": "sqlglot.dataframe.sql.DataFrame.fillna", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.fillna", "kind": "function", "doc": "<p>Functionality Difference: If you provide a value to replace a null and that type conflicts\nwith the type of the column then PySpark will just ignore your replacement.\nThis will try to cast them to be the same in some cases. So they won't always match.\nBest to not mix types so make sure replacement is the same type as the column</p>\n\n<p>Possibility for improvement: Use <code>typeof</code> function to get the type of the column\nand check if it matches the type of the value provided. If not then make it null.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">value</span><span class=\"p\">:</span> <span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666179446304'</span><span class=\"o\">></span>,</span><span class=\"param\">\t<span class=\"n\">subset</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">Tuple</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"o\">...</span><span class=\"p\">],</span> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.replace": {"fullname": "sqlglot.dataframe.sql.DataFrame.replace", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.replace", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">to_replace</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">bool</span><span class=\"p\">,</span> <span class=\"nb\">int</span><span class=\"p\">,</span> <span class=\"nb\">float</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">List</span><span class=\"p\">,</span> <span class=\"n\">Dict</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">value</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">bool</span><span class=\"p\">,</span> <span class=\"nb\">int</span><span class=\"p\">,</span> <span class=\"nb\">float</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">List</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">subset</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">Collection</span><span class=\"p\">[</span><span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666180055296'</span><span class=\"o\">></span><span class=\"p\">],</span> <span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666180055296'</span><span class=\"o\">></span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.withColumn": {"fullname": "sqlglot.dataframe.sql.DataFrame.withColumn", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.withColumn", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">colName</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">col</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.withColumnRenamed": {"fullname": "sqlglot.dataframe.sql.DataFrame.withColumnRenamed", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.withColumnRenamed", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">existing</span><span class=\"p\">:</span> <span class=\"nb\">str</span>, </span><span class=\"param\"><span class=\"n\">new</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.drop": {"fullname": "sqlglot.dataframe.sql.DataFrame.drop", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.drop", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">cols</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.limit": {"fullname": "sqlglot.dataframe.sql.DataFrame.limit", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.limit", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">num</span><span class=\"p\">:</span> <span class=\"nb\">int</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.hint": {"fullname": "sqlglot.dataframe.sql.DataFrame.hint", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.hint", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">name</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">parameters</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"nb\">int</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.repartition": {"fullname": "sqlglot.dataframe.sql.DataFrame.repartition", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.repartition", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">numPartitions</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">int</span><span class=\"p\">,</span> <span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666180055296'</span><span class=\"o\">></span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">cols</span><span class=\"p\">:</span> <span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666180055296'</span><span class=\"o\">></span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.coalesce": {"fullname": "sqlglot.dataframe.sql.DataFrame.coalesce", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.coalesce", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">numPartitions</span><span class=\"p\">:</span> <span class=\"nb\">int</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.cache": {"fullname": "sqlglot.dataframe.sql.DataFrame.cache", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.cache", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrame.persist": {"fullname": "sqlglot.dataframe.sql.DataFrame.persist", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrame.persist", "kind": "function", "doc": "<p>Storage Level Options: <a href=\"https://spark.apache.org/docs/3.0.0-preview/sql-ref-syntax-aux-cache-cache-table.html\">https://spark.apache.org/docs/3.0.0-preview/sql-ref-syntax-aux-cache-cache-table.html</a></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">storageLevel</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">'MEMORY_AND_DISK_SER'</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.GroupedData": {"fullname": "sqlglot.dataframe.sql.GroupedData", "modulename": "sqlglot.dataframe.sql", "qualname": "GroupedData", "kind": "class", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.GroupedData.__init__": {"fullname": "sqlglot.dataframe.sql.GroupedData.__init__", "modulename": "sqlglot.dataframe.sql", "qualname": "GroupedData.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">df</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>,</span><span class=\"param\">\t<span class=\"n\">group_by_cols</span><span class=\"p\">:</span> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">last_op</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">operations</span><span class=\"o\">.</span><span class=\"n\">Operation</span></span>)</span>"}, "sqlglot.dataframe.sql.GroupedData.spark": {"fullname": "sqlglot.dataframe.sql.GroupedData.spark", "modulename": "sqlglot.dataframe.sql", "qualname": "GroupedData.spark", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.GroupedData.last_op": {"fullname": "sqlglot.dataframe.sql.GroupedData.last_op", "modulename": "sqlglot.dataframe.sql", "qualname": "GroupedData.last_op", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.GroupedData.group_by_cols": {"fullname": "sqlglot.dataframe.sql.GroupedData.group_by_cols", "modulename": "sqlglot.dataframe.sql", "qualname": "GroupedData.group_by_cols", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.GroupedData.agg": {"fullname": "sqlglot.dataframe.sql.GroupedData.agg", "modulename": "sqlglot.dataframe.sql", "qualname": "GroupedData.agg", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">exprs</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span><span class=\"p\">,</span> <span class=\"n\">Dict</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">]]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.GroupedData.count": {"fullname": "sqlglot.dataframe.sql.GroupedData.count", "modulename": "sqlglot.dataframe.sql", "qualname": "GroupedData.count", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.GroupedData.mean": {"fullname": "sqlglot.dataframe.sql.GroupedData.mean", "modulename": "sqlglot.dataframe.sql", "qualname": "GroupedData.mean", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">*</span><span class=\"n\">cols</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.GroupedData.avg": {"fullname": "sqlglot.dataframe.sql.GroupedData.avg", "modulename": "sqlglot.dataframe.sql", "qualname": "GroupedData.avg", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">*</span><span class=\"n\">cols</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.GroupedData.max": {"fullname": "sqlglot.dataframe.sql.GroupedData.max", "modulename": "sqlglot.dataframe.sql", "qualname": "GroupedData.max", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">*</span><span class=\"n\">cols</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.GroupedData.min": {"fullname": "sqlglot.dataframe.sql.GroupedData.min", "modulename": "sqlglot.dataframe.sql", "qualname": "GroupedData.min", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">*</span><span class=\"n\">cols</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.GroupedData.sum": {"fullname": "sqlglot.dataframe.sql.GroupedData.sum", "modulename": "sqlglot.dataframe.sql", "qualname": "GroupedData.sum", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">*</span><span class=\"n\">cols</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.GroupedData.pivot": {"fullname": "sqlglot.dataframe.sql.GroupedData.pivot", "modulename": "sqlglot.dataframe.sql", "qualname": "GroupedData.pivot", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">*</span><span class=\"n\">cols</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column": {"fullname": "sqlglot.dataframe.sql.Column", "modulename": "sqlglot.dataframe.sql", "qualname": "Column", "kind": "class", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.Column.__init__": {"fullname": "sqlglot.dataframe.sql.Column.__init__", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666181935232'</span><span class=\"o\">></span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span></span>)</span>"}, "sqlglot.dataframe.sql.Column.expression": {"fullname": "sqlglot.dataframe.sql.Column.expression", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.expression", "kind": "variable", "doc": "<p></p>\n", "annotation": ": sqlglot.expressions.Expression"}, "sqlglot.dataframe.sql.Column.ensure_col": {"fullname": "sqlglot.dataframe.sql.Column.ensure_col", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.ensure_col", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">cls</span>,</span><span class=\"param\">\t<span class=\"n\">value</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666181935232'</span><span class=\"o\">></span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.ensure_cols": {"fullname": "sqlglot.dataframe.sql.Column.ensure_cols", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.ensure_cols", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">cls</span>,</span><span class=\"param\">\t<span class=\"n\">args</span><span class=\"p\">:</span> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666181935232'</span><span class=\"o\">></span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.invoke_anonymous_function": {"fullname": "sqlglot.dataframe.sql.Column.invoke_anonymous_function", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.invoke_anonymous_function", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">cls</span>,</span><span class=\"param\">\t<span class=\"n\">column</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666181935232'</span><span class=\"o\">></span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">func_name</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">args</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666181935232'</span><span class=\"o\">></span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.invoke_expression_over_column": {"fullname": "sqlglot.dataframe.sql.Column.invoke_expression_over_column", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.invoke_expression_over_column", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">cls</span>,</span><span class=\"param\">\t<span class=\"n\">column</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666181935232'</span><span class=\"o\">></span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">callable_expression</span><span class=\"p\">:</span> <span class=\"n\">Callable</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.binary_op": {"fullname": "sqlglot.dataframe.sql.Column.binary_op", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.binary_op", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">klass</span><span class=\"p\">:</span> <span class=\"n\">Callable</span>,</span><span class=\"param\">\t<span class=\"n\">other</span><span class=\"p\">:</span> <span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666181935232'</span><span class=\"o\">></span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.inverse_binary_op": {"fullname": "sqlglot.dataframe.sql.Column.inverse_binary_op", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.inverse_binary_op", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">klass</span><span class=\"p\">:</span> <span class=\"n\">Callable</span>,</span><span class=\"param\">\t<span class=\"n\">other</span><span class=\"p\">:</span> <span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666181935232'</span><span class=\"o\">></span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.unary_op": {"fullname": "sqlglot.dataframe.sql.Column.unary_op", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.unary_op", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">klass</span><span class=\"p\">:</span> <span class=\"n\">Callable</span>, </span><span class=\"param\"><span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.is_alias": {"fullname": "sqlglot.dataframe.sql.Column.is_alias", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.is_alias", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.Column.is_column": {"fullname": "sqlglot.dataframe.sql.Column.is_column", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.is_column", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.Column.column_expression": {"fullname": "sqlglot.dataframe.sql.Column.column_expression", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.column_expression", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Union[sqlglot.expressions.Column, sqlglot.expressions.Literal]"}, "sqlglot.dataframe.sql.Column.alias_or_name": {"fullname": "sqlglot.dataframe.sql.Column.alias_or_name", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.alias_or_name", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.dataframe.sql.Column.ensure_literal": {"fullname": "sqlglot.dataframe.sql.Column.ensure_literal", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.ensure_literal", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">cls</span>, </span><span class=\"param\"><span class=\"n\">value</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.copy": {"fullname": "sqlglot.dataframe.sql.Column.copy", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.copy", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.set_table_name": {"fullname": "sqlglot.dataframe.sql.Column.set_table_name", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.set_table_name", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">table_name</span><span class=\"p\">:</span> <span class=\"nb\">str</span>, </span><span class=\"param\"><span class=\"n\">copy</span><span class=\"o\">=</span><span class=\"kc\">False</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.sql": {"fullname": "sqlglot.dataframe.sql.Column.sql", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.alias": {"fullname": "sqlglot.dataframe.sql.Column.alias", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.alias", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">name</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.asc": {"fullname": "sqlglot.dataframe.sql.Column.asc", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.asc", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.desc": {"fullname": "sqlglot.dataframe.sql.Column.desc", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.desc", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.asc_nulls_first": {"fullname": "sqlglot.dataframe.sql.Column.asc_nulls_first", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.asc_nulls_first", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.asc_nulls_last": {"fullname": "sqlglot.dataframe.sql.Column.asc_nulls_last", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.asc_nulls_last", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.desc_nulls_first": {"fullname": "sqlglot.dataframe.sql.Column.desc_nulls_first", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.desc_nulls_first", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.desc_nulls_last": {"fullname": "sqlglot.dataframe.sql.Column.desc_nulls_last", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.desc_nulls_last", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.when": {"fullname": "sqlglot.dataframe.sql.Column.when", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.when", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">condition</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>,</span><span class=\"param\">\t<span class=\"n\">value</span><span class=\"p\">:</span> <span class=\"n\">Any</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.otherwise": {"fullname": "sqlglot.dataframe.sql.Column.otherwise", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.otherwise", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">value</span><span class=\"p\">:</span> <span class=\"n\">Any</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.isNull": {"fullname": "sqlglot.dataframe.sql.Column.isNull", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.isNull", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.isNotNull": {"fullname": "sqlglot.dataframe.sql.Column.isNotNull", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.isNotNull", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.cast": {"fullname": "sqlglot.dataframe.sql.Column.cast", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.cast", "kind": "function", "doc": "<p>Functionality Difference: PySpark cast accepts a datatype instance of the datatype class\nSqlglot doesn't currently replicate this class so it only accepts a string</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">dataType</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.startswith": {"fullname": "sqlglot.dataframe.sql.Column.startswith", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.startswith", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">value</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.endswith": {"fullname": "sqlglot.dataframe.sql.Column.endswith", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.endswith", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">value</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.rlike": {"fullname": "sqlglot.dataframe.sql.Column.rlike", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.rlike", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">regexp</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.like": {"fullname": "sqlglot.dataframe.sql.Column.like", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.like", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">other</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.ilike": {"fullname": "sqlglot.dataframe.sql.Column.ilike", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.ilike", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">other</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.substr": {"fullname": "sqlglot.dataframe.sql.Column.substr", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.substr", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">startPos</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">int</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">length</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">int</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.isin": {"fullname": "sqlglot.dataframe.sql.Column.isin", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.isin", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">cols</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666181935232'</span><span class=\"o\">></span><span class=\"p\">,</span> <span class=\"n\">Iterable</span><span class=\"p\">[</span><span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666181935232'</span><span class=\"o\">></span><span class=\"p\">]]</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.between": {"fullname": "sqlglot.dataframe.sql.Column.between", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.between", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">lowerBound</span><span class=\"p\">:</span> <span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666181935232'</span><span class=\"o\">></span>,</span><span class=\"param\">\t<span class=\"n\">upperBound</span><span class=\"p\">:</span> <span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666181935232'</span><span class=\"o\">></span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Column.over": {"fullname": "sqlglot.dataframe.sql.Column.over", "modulename": "sqlglot.dataframe.sql", "qualname": "Column.over", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">window</span><span class=\"p\">:</span> <span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666178523520'</span><span class=\"o\">></span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">column</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrameNaFunctions": {"fullname": "sqlglot.dataframe.sql.DataFrameNaFunctions", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrameNaFunctions", "kind": "class", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.DataFrameNaFunctions.__init__": {"fullname": "sqlglot.dataframe.sql.DataFrameNaFunctions.__init__", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrameNaFunctions.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">df</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span></span>)</span>"}, "sqlglot.dataframe.sql.DataFrameNaFunctions.df": {"fullname": "sqlglot.dataframe.sql.DataFrameNaFunctions.df", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrameNaFunctions.df", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.DataFrameNaFunctions.drop": {"fullname": "sqlglot.dataframe.sql.DataFrameNaFunctions.drop", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrameNaFunctions.drop", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">how</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">'any'</span>,</span><span class=\"param\">\t<span class=\"n\">thresh</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">int</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">subset</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">Tuple</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"o\">...</span><span class=\"p\">],</span> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrameNaFunctions.fill": {"fullname": "sqlglot.dataframe.sql.DataFrameNaFunctions.fill", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrameNaFunctions.fill", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">value</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">int</span><span class=\"p\">,</span> <span class=\"nb\">bool</span><span class=\"p\">,</span> <span class=\"nb\">float</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">Dict</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">Any</span><span class=\"p\">]]</span>,</span><span class=\"param\">\t<span class=\"n\">subset</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">Tuple</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"o\">...</span><span class=\"p\">],</span> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrameNaFunctions.replace": {"fullname": "sqlglot.dataframe.sql.DataFrameNaFunctions.replace", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrameNaFunctions.replace", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">to_replace</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">bool</span><span class=\"p\">,</span> <span class=\"nb\">int</span><span class=\"p\">,</span> <span class=\"nb\">float</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">List</span><span class=\"p\">,</span> <span class=\"n\">Dict</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">value</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">bool</span><span class=\"p\">,</span> <span class=\"nb\">int</span><span class=\"p\">,</span> <span class=\"nb\">float</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">List</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">subset</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Window": {"fullname": "sqlglot.dataframe.sql.Window", "modulename": "sqlglot.dataframe.sql", "qualname": "Window", "kind": "class", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.Window.unboundedPreceding": {"fullname": "sqlglot.dataframe.sql.Window.unboundedPreceding", "modulename": "sqlglot.dataframe.sql", "qualname": "Window.unboundedPreceding", "kind": "variable", "doc": "<p></p>\n", "annotation": ": int", "default_value": "-9223372036854775808"}, "sqlglot.dataframe.sql.Window.unboundedFollowing": {"fullname": "sqlglot.dataframe.sql.Window.unboundedFollowing", "modulename": "sqlglot.dataframe.sql", "qualname": "Window.unboundedFollowing", "kind": "variable", "doc": "<p></p>\n", "annotation": ": int", "default_value": "9223372036854775807"}, "sqlglot.dataframe.sql.Window.currentRow": {"fullname": "sqlglot.dataframe.sql.Window.currentRow", "modulename": "sqlglot.dataframe.sql", "qualname": "Window.currentRow", "kind": "variable", "doc": "<p></p>\n", "annotation": ": int", "default_value": "0"}, "sqlglot.dataframe.sql.Window.partitionBy": {"fullname": "sqlglot.dataframe.sql.Window.partitionBy", "modulename": "sqlglot.dataframe.sql", "qualname": "Window.partitionBy", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">cls</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">cols</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666178965504'</span><span class=\"o\">></span><span class=\"p\">,</span> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666178965504'</span><span class=\"o\">></span><span class=\"p\">]]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">window</span><span class=\"o\">.</span><span class=\"n\">WindowSpec</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Window.orderBy": {"fullname": "sqlglot.dataframe.sql.Window.orderBy", "modulename": "sqlglot.dataframe.sql", "qualname": "Window.orderBy", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">cls</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">cols</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666178965504'</span><span class=\"o\">></span><span class=\"p\">,</span> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666178965504'</span><span class=\"o\">></span><span class=\"p\">]]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">window</span><span class=\"o\">.</span><span class=\"n\">WindowSpec</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Window.rowsBetween": {"fullname": "sqlglot.dataframe.sql.Window.rowsBetween", "modulename": "sqlglot.dataframe.sql", "qualname": "Window.rowsBetween", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">cls</span>, </span><span class=\"param\"><span class=\"n\">start</span><span class=\"p\">:</span> <span class=\"nb\">int</span>, </span><span class=\"param\"><span class=\"n\">end</span><span class=\"p\">:</span> <span class=\"nb\">int</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">window</span><span class=\"o\">.</span><span class=\"n\">WindowSpec</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.Window.rangeBetween": {"fullname": "sqlglot.dataframe.sql.Window.rangeBetween", "modulename": "sqlglot.dataframe.sql", "qualname": "Window.rangeBetween", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">cls</span>, </span><span class=\"param\"><span class=\"n\">start</span><span class=\"p\">:</span> <span class=\"nb\">int</span>, </span><span class=\"param\"><span class=\"n\">end</span><span class=\"p\">:</span> <span class=\"nb\">int</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">window</span><span class=\"o\">.</span><span class=\"n\">WindowSpec</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.WindowSpec": {"fullname": "sqlglot.dataframe.sql.WindowSpec", "modulename": "sqlglot.dataframe.sql", "qualname": "WindowSpec", "kind": "class", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.WindowSpec.__init__": {"fullname": "sqlglot.dataframe.sql.WindowSpec.__init__", "modulename": "sqlglot.dataframe.sql", "qualname": "WindowSpec.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span> <span class=\"o\">=</span> <span class=\"n\">Window</span><span class=\"p\">()</span></span>)</span>"}, "sqlglot.dataframe.sql.WindowSpec.expression": {"fullname": "sqlglot.dataframe.sql.WindowSpec.expression", "modulename": "sqlglot.dataframe.sql", "qualname": "WindowSpec.expression", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.WindowSpec.copy": {"fullname": "sqlglot.dataframe.sql.WindowSpec.copy", "modulename": "sqlglot.dataframe.sql", "qualname": "WindowSpec.copy", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.WindowSpec.sql": {"fullname": "sqlglot.dataframe.sql.WindowSpec.sql", "modulename": "sqlglot.dataframe.sql", "qualname": "WindowSpec.sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.WindowSpec.partitionBy": {"fullname": "sqlglot.dataframe.sql.WindowSpec.partitionBy", "modulename": "sqlglot.dataframe.sql", "qualname": "WindowSpec.partitionBy", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">cols</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666178965504'</span><span class=\"o\">></span><span class=\"p\">,</span> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666178965504'</span><span class=\"o\">></span><span class=\"p\">]]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">window</span><span class=\"o\">.</span><span class=\"n\">WindowSpec</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.WindowSpec.orderBy": {"fullname": "sqlglot.dataframe.sql.WindowSpec.orderBy", "modulename": "sqlglot.dataframe.sql", "qualname": "WindowSpec.orderBy", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">cols</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666178965504'</span><span class=\"o\">></span><span class=\"p\">,</span> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"o\"><</span><span class=\"n\">MagicMock</span> <span class=\"nb\">id</span><span class=\"o\">=</span><span class=\"s1\">'140666178965504'</span><span class=\"o\">></span><span class=\"p\">]]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">window</span><span class=\"o\">.</span><span class=\"n\">WindowSpec</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.WindowSpec.rowsBetween": {"fullname": "sqlglot.dataframe.sql.WindowSpec.rowsBetween", "modulename": "sqlglot.dataframe.sql", "qualname": "WindowSpec.rowsBetween", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">start</span><span class=\"p\">:</span> <span class=\"nb\">int</span>, </span><span class=\"param\"><span class=\"n\">end</span><span class=\"p\">:</span> <span class=\"nb\">int</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">window</span><span class=\"o\">.</span><span class=\"n\">WindowSpec</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.WindowSpec.rangeBetween": {"fullname": "sqlglot.dataframe.sql.WindowSpec.rangeBetween", "modulename": "sqlglot.dataframe.sql", "qualname": "WindowSpec.rangeBetween", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">start</span><span class=\"p\">:</span> <span class=\"nb\">int</span>, </span><span class=\"param\"><span class=\"n\">end</span><span class=\"p\">:</span> <span class=\"nb\">int</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">window</span><span class=\"o\">.</span><span class=\"n\">WindowSpec</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrameReader": {"fullname": "sqlglot.dataframe.sql.DataFrameReader", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrameReader", "kind": "class", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.DataFrameReader.__init__": {"fullname": "sqlglot.dataframe.sql.DataFrameReader.__init__", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrameReader.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">spark</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">session</span><span class=\"o\">.</span><span class=\"n\">SparkSession</span></span>)</span>"}, "sqlglot.dataframe.sql.DataFrameReader.spark": {"fullname": "sqlglot.dataframe.sql.DataFrameReader.spark", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrameReader.spark", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.DataFrameReader.table": {"fullname": "sqlglot.dataframe.sql.DataFrameReader.table", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrameReader.table", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">tableName</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrameWriter": {"fullname": "sqlglot.dataframe.sql.DataFrameWriter", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrameWriter", "kind": "class", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.DataFrameWriter.__init__": {"fullname": "sqlglot.dataframe.sql.DataFrameWriter.__init__", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrameWriter.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">df</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">DataFrame</span>,</span><span class=\"param\">\t<span class=\"n\">spark</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">session</span><span class=\"o\">.</span><span class=\"n\">SparkSession</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">mode</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">by_name</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span></span>)</span>"}, "sqlglot.dataframe.sql.DataFrameWriter.copy": {"fullname": "sqlglot.dataframe.sql.DataFrameWriter.copy", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrameWriter.copy", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">readwriter</span><span class=\"o\">.</span><span class=\"n\">DataFrameWriter</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrameWriter.sql": {"fullname": "sqlglot.dataframe.sql.DataFrameWriter.sql", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrameWriter.sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrameWriter.mode": {"fullname": "sqlglot.dataframe.sql.DataFrameWriter.mode", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrameWriter.mode", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">saveMode</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">readwriter</span><span class=\"o\">.</span><span class=\"n\">DataFrameWriter</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrameWriter.byName": {"fullname": "sqlglot.dataframe.sql.DataFrameWriter.byName", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrameWriter.byName", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.dataframe.sql.DataFrameWriter.insertInto": {"fullname": "sqlglot.dataframe.sql.DataFrameWriter.insertInto", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrameWriter.insertInto", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">tableName</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">overwrite</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">bool</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">readwriter</span><span class=\"o\">.</span><span class=\"n\">DataFrameWriter</span>:</span></span>", "funcdef": "def"}, "sqlglot.dataframe.sql.DataFrameWriter.saveAsTable": {"fullname": "sqlglot.dataframe.sql.DataFrameWriter.saveAsTable", "modulename": "sqlglot.dataframe.sql", "qualname": "DataFrameWriter.saveAsTable", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">name</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"nb\">format</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">mode</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.dialects": {"fullname": "sqlglot.dialects", "modulename": "sqlglot.dialects", "kind": "module", "doc": "<h2 id=\"dialects\">Dialects</h2>\n\n<p>While there is a SQL standard, most SQL engines support a variation of that standard. This makes it difficult\nto write portable SQL code. SQLGlot bridges all the different variations, called \"dialects\", with an extensible\nSQL transpilation framework.</p>\n\n<p>The base <code>sqlglot.dialects.dialect.Dialect</code> class implements a generic dialect that aims to be as universal as possible.</p>\n\n<p>Each SQL variation has its own <code>Dialect</code> subclass, extending the corresponding <code>Tokenizer</code>, <code>Parser</code> and <code>Generator</code>\nclasses as needed.</p>\n\n<h3 id=\"implementing-a-custom-dialect\">Implementing a custom Dialect</h3>\n\n<p>Creating a new SQL dialect may seem complicated at first, but it is actually quite simple in SQLGlot:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">exp</span>\n<span class=\"kn\">from</span> <span class=\"nn\">sqlglot.dialects.dialect</span> <span class=\"kn\">import</span> <span class=\"n\">Dialect</span>\n<span class=\"kn\">from</span> <span class=\"nn\">sqlglot.generator</span> <span class=\"kn\">import</span> <span class=\"n\">Generator</span>\n<span class=\"kn\">from</span> <span class=\"nn\">sqlglot.tokens</span> <span class=\"kn\">import</span> <span class=\"n\">Tokenizer</span><span class=\"p\">,</span> <span class=\"n\">TokenType</span>\n\n\n<span class=\"k\">class</span> <span class=\"nc\">Custom</span><span class=\"p\">(</span><span class=\"n\">Dialect</span><span class=\"p\">):</span>\n <span class=\"k\">class</span> <span class=\"nc\">Tokenizer</span><span class=\"p\">(</span><span class=\"n\">Tokenizer</span><span class=\"p\">):</span>\n <span class=\"n\">QUOTES</span> <span class=\"o\">=</span> <span class=\"p\">[</span><span class=\"s2\">"'"</span><span class=\"p\">,</span> <span class=\"s1\">'"'</span><span class=\"p\">]</span> <span class=\"c1\"># Strings can be delimited by either single or double quotes</span>\n <span class=\"n\">IDENTIFIERS</span> <span class=\"o\">=</span> <span class=\"p\">[</span><span class=\"s2\">"`"</span><span class=\"p\">]</span> <span class=\"c1\"># Identifiers can be delimited by backticks</span>\n\n <span class=\"c1\"># Associates certain meaningful words with tokens that capture their intent</span>\n <span class=\"n\">KEYWORDS</span> <span class=\"o\">=</span> <span class=\"p\">{</span>\n <span class=\"o\">**</span><span class=\"n\">Tokenizer</span><span class=\"o\">.</span><span class=\"n\">KEYWORDS</span><span class=\"p\">,</span>\n <span class=\"s2\">"INT64"</span><span class=\"p\">:</span> <span class=\"n\">TokenType</span><span class=\"o\">.</span><span class=\"n\">BIGINT</span><span class=\"p\">,</span>\n <span class=\"s2\">"FLOAT64"</span><span class=\"p\">:</span> <span class=\"n\">TokenType</span><span class=\"o\">.</span><span class=\"n\">DOUBLE</span><span class=\"p\">,</span>\n <span class=\"p\">}</span>\n\n <span class=\"k\">class</span> <span class=\"nc\">Generator</span><span class=\"p\">(</span><span class=\"n\">Generator</span><span class=\"p\">):</span>\n <span class=\"c1\"># Specifies how AST nodes, i.e. subclasses of exp.Expression, should be converted into SQL</span>\n <span class=\"n\">TRANSFORMS</span> <span class=\"o\">=</span> <span class=\"p\">{</span>\n <span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">Array</span><span class=\"p\">:</span> <span class=\"k\">lambda</span> <span class=\"bp\">self</span><span class=\"p\">,</span> <span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"sa\">f</span><span class=\"s2\">"[</span><span class=\"si\">{</span><span class=\"bp\">self</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">(</span><span class=\"n\">e</span><span class=\"p\">)</span><span class=\"si\">}</span><span class=\"s2\">]"</span><span class=\"p\">,</span>\n <span class=\"p\">}</span>\n\n <span class=\"c1\"># Specifies how AST nodes representing data types should be converted into SQL</span>\n <span class=\"n\">TYPE_MAPPING</span> <span class=\"o\">=</span> <span class=\"p\">{</span>\n <span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"o\">.</span><span class=\"n\">TINYINT</span><span class=\"p\">:</span> <span class=\"s2\">"INT64"</span><span class=\"p\">,</span>\n <span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"o\">.</span><span class=\"n\">SMALLINT</span><span class=\"p\">:</span> <span class=\"s2\">"INT64"</span><span class=\"p\">,</span>\n <span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"o\">.</span><span class=\"n\">INT</span><span class=\"p\">:</span> <span class=\"s2\">"INT64"</span><span class=\"p\">,</span>\n <span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"o\">.</span><span class=\"n\">BIGINT</span><span class=\"p\">:</span> <span class=\"s2\">"INT64"</span><span class=\"p\">,</span>\n <span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"o\">.</span><span class=\"n\">DECIMAL</span><span class=\"p\">:</span> <span class=\"s2\">"NUMERIC"</span><span class=\"p\">,</span>\n <span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"o\">.</span><span class=\"n\">FLOAT</span><span class=\"p\">:</span> <span class=\"s2\">"FLOAT64"</span><span class=\"p\">,</span>\n <span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"o\">.</span><span class=\"n\">DOUBLE</span><span class=\"p\">:</span> <span class=\"s2\">"FLOAT64"</span><span class=\"p\">,</span>\n <span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"o\">.</span><span class=\"n\">BOOLEAN</span><span class=\"p\">:</span> <span class=\"s2\">"BOOL"</span><span class=\"p\">,</span>\n <span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"o\">.</span><span class=\"n\">TEXT</span><span class=\"p\">:</span> <span class=\"s2\">"STRING"</span><span class=\"p\">,</span>\n <span class=\"p\">}</span>\n</code></pre>\n</div>\n\n<p>The above example demonstrates how certain parts of the base <code>Dialect</code> class can be overridden to match a different\nspecification. Even though it is a fairly realistic starting point, we strongly encourage the reader to study existing\ndialect implementations in order to understand how their various components can be modified, depending on the use-case.</p>\n\n<hr />\n"}, "sqlglot.dialects.athena": {"fullname": "sqlglot.dialects.athena", "modulename": "sqlglot.dialects.athena", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.dialects.athena.Athena": {"fullname": "sqlglot.dialects.athena.Athena", "modulename": "sqlglot.dialects.athena", "qualname": "Athena", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.trino.Trino"}, "sqlglot.dialects.athena.Athena.Parser": {"fullname": "sqlglot.dialects.athena.Athena.Parser", "modulename": "sqlglot.dialects.athena", "qualname": "Athena.Parser", "kind": "class", "doc": "<p>Parser consumes a list of tokens produced by the Tokenizer and produces a parsed syntax tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>error_level:</strong> The desired error level.\nDefault: ErrorLevel.IMMEDIATE</li>\n<li><strong>error_message_context:</strong> The amount of context to capture from a query string when displaying\nthe error message (in number of characters).\nDefault: 100</li>\n<li><strong>max_errors:</strong> Maximum number of error messages to include in a raised ParseError.\nThis is only relevant if error_level is ErrorLevel.RAISE.\nDefault: 3</li>\n</ul>\n", "bases": "sqlglot.dialects.trino.Trino.Parser"}, "sqlglot.dialects.athena.Athena.Parser.STATEMENT_PARSERS": {"fullname": "sqlglot.dialects.athena.Athena.Parser.STATEMENT_PARSERS", "modulename": "sqlglot.dialects.athena", "qualname": "Athena.Parser.STATEMENT_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.ALTER: 'ALTER'>: <function Parser.<lambda>>, <TokenType.BEGIN: 'BEGIN'>: <function Parser.<lambda>>, <TokenType.CACHE: 'CACHE'>: <function Parser.<lambda>>, <TokenType.COMMENT: 'COMMENT'>: <function Parser.<lambda>>, <TokenType.COMMIT: 'COMMIT'>: <function Parser.<lambda>>, <TokenType.COPY: 'COPY'>: <function Parser.<lambda>>, <TokenType.CREATE: 'CREATE'>: <function Parser.<lambda>>, <TokenType.DELETE: 'DELETE'>: <function Parser.<lambda>>, <TokenType.DESC: 'DESC'>: <function Parser.<lambda>>, <TokenType.DESCRIBE: 'DESCRIBE'>: <function Parser.<lambda>>, <TokenType.DROP: 'DROP'>: <function Parser.<lambda>>, <TokenType.INSERT: 'INSERT'>: <function Parser.<lambda>>, <TokenType.KILL: 'KILL'>: <function Parser.<lambda>>, <TokenType.LOAD: 'LOAD'>: <function Parser.<lambda>>, <TokenType.MERGE: 'MERGE'>: <function Parser.<lambda>>, <TokenType.PIVOT: 'PIVOT'>: <function Parser.<lambda>>, <TokenType.PRAGMA: 'PRAGMA'>: <function Parser.<lambda>>, <TokenType.REFRESH: 'REFRESH'>: <function Parser.<lambda>>, <TokenType.ROLLBACK: 'ROLLBACK'>: <function Parser.<lambda>>, <TokenType.SET: 'SET'>: <function Parser.<lambda>>, <TokenType.TRUNCATE: 'TRUNCATE'>: <function Parser.<lambda>>, <TokenType.UNCACHE: 'UNCACHE'>: <function Parser.<lambda>>, <TokenType.UPDATE: 'UPDATE'>: <function Parser.<lambda>>, <TokenType.USE: 'USE'>: <function Parser.<lambda>>, <TokenType.SEMICOLON: 'SEMICOLON'>: <function Parser.<lambda>>, <TokenType.USING: 'USING'>: <function Athena.Parser.<lambda>>}"}, "sqlglot.dialects.athena.Athena.Parser.TABLE_ALIAS_TOKENS": {"fullname": "sqlglot.dialects.athena.Athena.Parser.TABLE_ALIAS_TOKENS", "modulename": "sqlglot.dialects.athena", "qualname": "Athena.Parser.TABLE_ALIAS_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.KILL: 'KILL'>, <TokenType.MONEY: 'MONEY'>, <TokenType.COPY: 'COPY'>, <TokenType.PERCENT: 'PERCENT'>, <TokenType.TAG: 'TAG'>, <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, <TokenType.VOLATILE: 'VOLATILE'>, <TokenType.IDENTIFIER: 'IDENTIFIER'>, <TokenType.VARBINARY: 'VARBINARY'>, <TokenType.HSTORE: 'HSTORE'>, <TokenType.ASC: 'ASC'>, <TokenType.IPADDRESS: 'IPADDRESS'>, <TokenType.ISNULL: 'ISNULL'>, <TokenType.TEMPORARY: 'TEMPORARY'>, <TokenType.PROCEDURE: 'PROCEDURE'>, <TokenType.SCHEMA: 'SCHEMA'>, <TokenType.NUMRANGE: 'NUMRANGE'>, <TokenType.DATE32: 'DATE32'>, <TokenType.INT8RANGE: 'INT8RANGE'>, <TokenType.ANTI: 'ANTI'>, <TokenType.AGGREGATEFUNCTION: 'AGGREGATEFUNCTION'>, <TokenType.VIEW: 'VIEW'>, <TokenType.VARCHAR: 'VARCHAR'>, <TokenType.TIMETZ: 'TIMETZ'>, <TokenType.GEOMETRY: 'GEOMETRY'>, <TokenType.BEGIN: 'BEGIN'>, <TokenType.ENUM8: 'ENUM8'>, <TokenType.INDEX: 'INDEX'>, <TokenType.PARTITION: 'PARTITION'>, <TokenType.UINT256: 'UINT256'>, <TokenType.BIGINT: 'BIGINT'>, <TokenType.CACHE: 'CACHE'>, <TokenType.OPERATOR: 'OPERATOR'>, <TokenType.COLUMN: 'COLUMN'>, <TokenType.INT128: 'INT128'>, <TokenType.SMALLMONEY: 'SMALLMONEY'>, <TokenType.HLLSKETCH: 'HLLSKETCH'>, <TokenType.UNPIVOT: 'UNPIVOT'>, <TokenType.SMALLINT: 'SMALLINT'>, <TokenType.INT256: 'INT256'>, <TokenType.FLOAT: 'FLOAT'>, <TokenType.COMMIT: 'COMMIT'>, <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, <TokenType.EXISTS: 'EXISTS'>, <TokenType.NULL: 'NULL'>, <TokenType.RECURSIVE: 'RECURSIVE'>, <TokenType.SET: 'SET'>, <TokenType.NULLABLE: 'NULLABLE'>, <TokenType.REFRESH: 'REFRESH'>, <TokenType.TINYTEXT: 'TINYTEXT'>, <TokenType.SHOW: 'SHOW'>, <TokenType.DEFAULT: 'DEFAULT'>, <TokenType.DATE: 'DATE'>, <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <TokenType.MERGE: 'MERGE'>, <TokenType.FIRST: 'FIRST'>, <TokenType.BINARY: 'BINARY'>, <TokenType.ARRAY: 'ARRAY'>, <TokenType.SERIAL: 'SERIAL'>, <TokenType.EXECUTE: 'EXECUTE'>, <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, <TokenType.INTERVAL: 'INTERVAL'>, <TokenType.PRAGMA: 'PRAGMA'>, <TokenType.STORAGE_INTEGRATION: 'STORAGE_INTEGRATION'>, <TokenType.BPCHAR: 'BPCHAR'>, <TokenType.BIT: 'BIT'>, <TokenType.UINT: 'UINT'>, <TokenType.UUID: 'UUID'>, <TokenType.STRUCT: 'STRUCT'>, <TokenType.FALSE: 'FALSE'>, <TokenType.FUNCTION: 'FUNCTION'>, <TokenType.TOP: 'TOP'>, <TokenType.SUPER: 'SUPER'>, <TokenType.CASE: 'CASE'>, <TokenType.IMAGE: 'IMAGE'>, <TokenType.UBIGINT: 'UBIGINT'>, <TokenType.LONGBLOB: 'LONGBLOB'>, <TokenType.ROLLUP: 'ROLLUP'>, <TokenType.VAR: 'VAR'>, <TokenType.COMMAND: 'COMMAND'>, <TokenType.LOAD: 'LOAD'>, <TokenType.TRUNCATE: 'TRUNCATE'>, <TokenType.KEEP: 'KEEP'>, <TokenType.UMEDIUMINT: 'UMEDIUMINT'>, <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, <TokenType.UINT128: 'UINT128'>, <TokenType.END: 'END'>, <TokenType.MAP: 'MAP'>, <TokenType.IPV4: 'IPV4'>, <TokenType.USERDEFINED: 'USERDEFINED'>, <TokenType.REFERENCES: 'REFERENCES'>, <TokenType.REPLACE: 'REPLACE'>, <TokenType.RANGE: 'RANGE'>, <TokenType.NVARCHAR: 'NVARCHAR'>, <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, <TokenType.TRUE: 'TRUE'>, <TokenType.TIMESTAMP_MS: 'TIMESTAMP_MS'>, <TokenType.VARIANT: 'VARIANT'>, <TokenType.ENUM: 'ENUM'>, <TokenType.USE: 'USE'>, <TokenType.USMALLINT: 'USMALLINT'>, <TokenType.OVERLAPS: 'OVERLAPS'>, <TokenType.TIMESTAMP_S: 'TIMESTAMP_S'>, <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, <TokenType.UNIQUE: 'UNIQUE'>, <TokenType.ORDINALITY: 'ORDINALITY'>, <TokenType.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>, <TokenType.TEXT: 'TEXT'>, <TokenType.DATABASE: 'DATABASE'>, <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, <TokenType.PSEUDO_TYPE: 'PSEUDO_TYPE'>, <TokenType.FIXEDSTRING: 'FIXEDSTRING'>, <TokenType.NEXT: 'NEXT'>, <TokenType.INT: 'INT'>, <TokenType.BIGSERIAL: 'BIGSERIAL'>, <TokenType.BOOLEAN: 'BOOLEAN'>, <TokenType.IS: 'IS'>, <TokenType.CONSTRAINT: 'CONSTRAINT'>, <TokenType.FINAL: 'FINAL'>, <TokenType.UNKNOWN: 'UNKNOWN'>, <TokenType.SETTINGS: 'SETTINGS'>, <TokenType.ROWS: 'ROWS'>, <TokenType.TSTZRANGE: 'TSTZRANGE'>, <TokenType.DATETIME64: 'DATETIME64'>, <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, <TokenType.DATETIME: 'DATETIME'>, <TokenType.MEDIUMINT: 'MEDIUMINT'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>, <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, <TokenType.XML: 'XML'>, <TokenType.JSON: 'JSON'>, <TokenType.UTINYINT: 'UTINYINT'>, <TokenType.DELETE: 'DELETE'>, <TokenType.TIME: 'TIME'>, <TokenType.UDECIMAL: 'UDECIMAL'>, <TokenType.NESTED: 'NESTED'>, <TokenType.SEMI: 'SEMI'>, <TokenType.DESC: 'DESC'>, <TokenType.ROWVERSION: 'ROWVERSION'>, <TokenType.TIMESTAMP_NS: 'TIMESTAMP_NS'>, <TokenType.ANY: 'ANY'>, <TokenType.DIV: 'DIV'>, <TokenType.DICTIONARY: 'DICTIONARY'>, <TokenType.INET: 'INET'>, <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, <TokenType.COMMENT: 'COMMENT'>, <TokenType.CURRENT_USER: 'CURRENT_USER'>, <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>, <TokenType.ALL: 'ALL'>, <TokenType.NAME: 'NAME'>, <TokenType.SOME: 'SOME'>, <TokenType.ENUM16: 'ENUM16'>, <TokenType.YEAR: 'YEAR'>, <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, <TokenType.DOUBLE: 'DOUBLE'>, <TokenType.INT4RANGE: 'INT4RANGE'>, <TokenType.FORMAT: 'FORMAT'>, <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, <TokenType.IPPREFIX: 'IPPREFIX'>, <TokenType.OVERWRITE: 'OVERWRITE'>, <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>, <TokenType.COLLATE: 'COLLATE'>, <TokenType.FILTER: 'FILTER'>, <TokenType.JSONB: 'JSONB'>, <TokenType.TDIGEST: 'TDIGEST'>, <TokenType.CHAR: 'CHAR'>, <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.ROW: 'ROW'>, <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.TABLE: 'TABLE'>, <TokenType.DATERANGE: 'DATERANGE'>, <TokenType.TSRANGE: 'TSRANGE'>, <TokenType.ESCAPE: 'ESCAPE'>, <TokenType.PIVOT: 'PIVOT'>, <TokenType.DECIMAL: 'DECIMAL'>, <TokenType.NCHAR: 'NCHAR'>, <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, <TokenType.UPDATE: 'UPDATE'>, <TokenType.MODEL: 'MODEL'>, <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, <TokenType.SEQUENCE: 'SEQUENCE'>, <TokenType.LONGTEXT: 'LONGTEXT'>, <TokenType.DESCRIBE: 'DESCRIBE'>, <TokenType.IPV6: 'IPV6'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, <TokenType.TINYINT: 'TINYINT'>, <TokenType.TINYBLOB: 'TINYBLOB'>}"}, "sqlglot.dialects.athena.Athena.Parser.SHOW_TRIE": {"fullname": "sqlglot.dialects.athena.Athena.Parser.SHOW_TRIE", "modulename": "sqlglot.dialects.athena", "qualname": "Athena.Parser.SHOW_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.athena.Athena.Parser.SET_TRIE": {"fullname": "sqlglot.dialects.athena.Athena.Parser.SET_TRIE", "modulename": "sqlglot.dialects.athena", "qualname": "Athena.Parser.SET_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'GLOBAL': {0: True}, 'LOCAL': {0: True}, 'SESSION': {0: True}, 'TRANSACTION': {0: True}}"}, "sqlglot.dialects.athena.Athena.Generator": {"fullname": "sqlglot.dialects.athena.Athena.Generator", "modulename": "sqlglot.dialects.athena", "qualname": "Athena.Generator", "kind": "class", "doc": "<p>Generator converts a given syntax tree to the corresponding SQL string.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>pretty:</strong> Whether to format the produced SQL string.\nDefault: False.</li>\n<li><strong>identify:</strong> Determines when an identifier should be quoted. Possible values are:\nFalse (default): Never quote, except in cases where it's mandatory by the dialect.\nTrue or 'always': Always quote.\n'safe': Only quote identifiers that are case insensitive.</li>\n<li><strong>normalize:</strong> Whether to normalize identifiers to lowercase.\nDefault: False.</li>\n<li><strong>pad:</strong> The pad size in a formatted string. For example, this affects the indentation of\na projection in a query, relative to its nesting level.\nDefault: 2.</li>\n<li><strong>indent:</strong> The indentation size in a formatted string. For example, this affects the\nindentation of subqueries and filters under a <code>WHERE</code> clause.\nDefault: 2.</li>\n<li><strong>normalize_functions:</strong> How to normalize function names. Possible values are:\n\"upper\" or True (default): Convert names to uppercase.\n\"lower\": Convert names to lowercase.\nFalse: Disables function name normalization.</li>\n<li><strong>unsupported_level:</strong> Determines the generator's behavior when it encounters unsupported expressions.\nDefault ErrorLevel.WARN.</li>\n<li><strong>max_unsupported:</strong> Maximum number of unsupported messages to include in a raised UnsupportedError.\nThis is only relevant if unsupported_level is ErrorLevel.RAISE.\nDefault: 3</li>\n<li><strong>leading_comma:</strong> Whether the comma is leading or trailing in select expressions.\nThis is only relevant when generating in pretty mode.\nDefault: False</li>\n<li><strong>max_text_width:</strong> The max number of characters in a segment before creating new lines in pretty mode.\nThe default is on the smaller end because the length only represents a segment and not the true\nline length.\nDefault: 80</li>\n<li><strong>comments:</strong> Whether to preserve comments in the output SQL code.\nDefault: True</li>\n</ul>\n", "bases": "sqlglot.dialects.trino.Trino.Generator"}, "sqlglot.dialects.athena.Athena.Generator.WITH_PROPERTIES_PREFIX": {"fullname": "sqlglot.dialects.athena.Athena.Generator.WITH_PROPERTIES_PREFIX", "modulename": "sqlglot.dialects.athena", "qualname": "Athena.Generator.WITH_PROPERTIES_PREFIX", "kind": "variable", "doc": "<p></p>\n", "default_value": "'TBLPROPERTIES'"}, "sqlglot.dialects.athena.Athena.Generator.PROPERTIES_LOCATION": {"fullname": "sqlglot.dialects.athena.Athena.Generator.PROPERTIES_LOCATION", "modulename": "sqlglot.dialects.athena", "qualname": "Athena.Generator.PROPERTIES_LOCATION", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.AllowedValuesProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.AlgorithmProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.AutoIncrementProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.BackupProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.BlockCompressionProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.CharacterSetProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ChecksumProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.CollateProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Cluster'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ClusteredByProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DataBlocksizeProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.DataDeletionProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DefinerProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.DictRange'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DictProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DistKeyProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DistStyleProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.EngineProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ExternalProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.FallbackProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.FileFormatProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.FreespaceProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.GlobalProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.HeapProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.InheritsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.IcebergProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.InputModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.IsolatedLoadingProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.JournalProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.LanguageProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LikeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LocationProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LockProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LockingProperty'>: <Location.POST_ALIAS: 'POST_ALIAS'>, <class 'sqlglot.expressions.LogProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.MaterializedProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.MergeBlockRatioProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.OnProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.OnCommitProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.Order'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.OutputModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.PartitionedByProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.PartitionedOfProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.PrimaryKey'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Property'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ReturnsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatDelimitedProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatSerdeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SampleProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SchemaCommentProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SerdeProperties'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Set'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SettingsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SetProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.SetConfigProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SharingProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.SequenceProperties'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.SortKeyProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SqlReadWriteProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SqlSecurityProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.StabilityProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.StrictProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.TemporaryProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.ToTableProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.TransientProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.TransformModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.MergeTreeTTL'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.UnloggedProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.VolatileProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.WithDataProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.WithSystemVersioningProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>}"}, "sqlglot.dialects.athena.Athena.Generator.TYPE_MAPPING": {"fullname": "sqlglot.dialects.athena.Athena.Generator.TYPE_MAPPING", "modulename": "sqlglot.dialects.athena", "qualname": "Athena.Generator.TYPE_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": 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"sqlglot.dialects.athena.Athena.BIT_START", "modulename": "sqlglot.dialects.athena", "qualname": "Athena.BIT_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.athena.Athena.BIT_END": {"fullname": "sqlglot.dialects.athena.Athena.BIT_END", "modulename": "sqlglot.dialects.athena", "qualname": "Athena.BIT_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.athena.Athena.HEX_START": {"fullname": "sqlglot.dialects.athena.Athena.HEX_START", "modulename": "sqlglot.dialects.athena", "qualname": "Athena.HEX_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""X'""}, "sqlglot.dialects.athena.Athena.HEX_END": {"fullname": "sqlglot.dialects.athena.Athena.HEX_END", "modulename": "sqlglot.dialects.athena", "qualname": "Athena.HEX_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""'""}, "sqlglot.dialects.athena.Athena.BYTE_START": {"fullname": "sqlglot.dialects.athena.Athena.BYTE_START", "modulename": "sqlglot.dialects.athena", "qualname": "Athena.BYTE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.athena.Athena.BYTE_END": {"fullname": "sqlglot.dialects.athena.Athena.BYTE_END", "modulename": "sqlglot.dialects.athena", "qualname": "Athena.BYTE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.athena.Athena.UNICODE_START": {"fullname": "sqlglot.dialects.athena.Athena.UNICODE_START", "modulename": "sqlglot.dialects.athena", "qualname": "Athena.UNICODE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""U&'""}, "sqlglot.dialects.athena.Athena.UNICODE_END": {"fullname": "sqlglot.dialects.athena.Athena.UNICODE_END", "modulename": "sqlglot.dialects.athena", "qualname": "Athena.UNICODE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""'""}, "sqlglot.dialects.bigquery": {"fullname": "sqlglot.dialects.bigquery", "modulename": "sqlglot.dialects.bigquery", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.dialects.bigquery.logger": {"fullname": "sqlglot.dialects.bigquery.logger", "modulename": "sqlglot.dialects.bigquery", "qualname": "logger", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Logger sqlglot (WARNING)>"}, "sqlglot.dialects.bigquery.BigQuery": {"fullname": "sqlglot.dialects.bigquery.BigQuery", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.dialect.Dialect"}, "sqlglot.dialects.bigquery.BigQuery.WEEK_OFFSET": {"fullname": "sqlglot.dialects.bigquery.BigQuery.WEEK_OFFSET", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.WEEK_OFFSET", "kind": "variable", "doc": "<p>First day of the week in DATE_TRUNC(week). Defaults to 0 (Monday). -1 would be Sunday.</p>\n", "default_value": "-1"}, "sqlglot.dialects.bigquery.BigQuery.UNNEST_COLUMN_ONLY": {"fullname": "sqlglot.dialects.bigquery.BigQuery.UNNEST_COLUMN_ONLY", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.UNNEST_COLUMN_ONLY", "kind": "variable", "doc": "<p>Whether <code>UNNEST</code> table aliases are treated as column aliases.</p>\n", "default_value": "True"}, "sqlglot.dialects.bigquery.BigQuery.SUPPORTS_USER_DEFINED_TYPES": {"fullname": "sqlglot.dialects.bigquery.BigQuery.SUPPORTS_USER_DEFINED_TYPES", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.SUPPORTS_USER_DEFINED_TYPES", "kind": "variable", "doc": "<p>Whether user-defined data types are supported.</p>\n", "default_value": "False"}, "sqlglot.dialects.bigquery.BigQuery.SUPPORTS_SEMI_ANTI_JOIN": {"fullname": "sqlglot.dialects.bigquery.BigQuery.SUPPORTS_SEMI_ANTI_JOIN", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.SUPPORTS_SEMI_ANTI_JOIN", "kind": "variable", "doc": "<p>Whether <code>SEMI</code> or <code>ANTI</code> joins are supported.</p>\n", "default_value": "False"}, "sqlglot.dialects.bigquery.BigQuery.LOG_BASE_FIRST": {"fullname": "sqlglot.dialects.bigquery.BigQuery.LOG_BASE_FIRST", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.LOG_BASE_FIRST", "kind": "variable", "doc": "<p>Whether the base comes first in the <code>LOG</code> function.\nPossible values: <code>True</code>, <code>False</code>, <code>None</code> (two arguments are not supported by <code>LOG</code>)</p>\n", "annotation": ": Optional[bool]", "default_value": "False"}, "sqlglot.dialects.bigquery.BigQuery.HEX_LOWERCASE": {"fullname": "sqlglot.dialects.bigquery.BigQuery.HEX_LOWERCASE", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.HEX_LOWERCASE", "kind": "variable", "doc": "<p>Whether the <code>HEX</code> function returns a lowercase hexadecimal string.</p>\n", "default_value": "True"}, "sqlglot.dialects.bigquery.BigQuery.NORMALIZATION_STRATEGY": {"fullname": "sqlglot.dialects.bigquery.BigQuery.NORMALIZATION_STRATEGY", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.NORMALIZATION_STRATEGY", "kind": "variable", "doc": "<p>Specifies the strategy according to which identifiers should be normalized.</p>\n", "default_value": "<NormalizationStrategy.CASE_INSENSITIVE: 'CASE_INSENSITIVE'>"}, "sqlglot.dialects.bigquery.BigQuery.NORMALIZE_FUNCTIONS": {"fullname": "sqlglot.dialects.bigquery.BigQuery.NORMALIZE_FUNCTIONS", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.NORMALIZE_FUNCTIONS", "kind": "variable", "doc": "<p>Determines how function names are going to be normalized.</p>\n\n<h6 id=\"possible-values\">Possible values:</h6>\n\n<blockquote>\n <p>\"upper\" or True: Convert names to uppercase.\n \"lower\": Convert names to lowercase.\n False: Disables function name normalization.</p>\n</blockquote>\n", "annotation": ": bool | str", "default_value": "False"}, "sqlglot.dialects.bigquery.BigQuery.TIME_MAPPING": {"fullname": "sqlglot.dialects.bigquery.BigQuery.TIME_MAPPING", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.TIME_MAPPING", "kind": "variable", "doc": "<p>Associates this dialect's time formats with their equivalent Python <code>strftime</code> formats.</p>\n", "annotation": ": Dict[str, str]", "default_value": "{'%D': '%m/%d/%y', '%E6S': '%S.%f'}"}, "sqlglot.dialects.bigquery.BigQuery.FORMAT_MAPPING": {"fullname": "sqlglot.dialects.bigquery.BigQuery.FORMAT_MAPPING", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.FORMAT_MAPPING", "kind": "variable", "doc": "<p>Helper which is used for parsing the special syntax <code>CAST(x AS DATE FORMAT 'yyyy')</code>.\nIf empty, the corresponding trie will be constructed off of <code>TIME_MAPPING</code>.</p>\n", "annotation": ": Dict[str, str]", "default_value": "{'DD': '%d', 'MM': '%m', 'MON': '%b', 'MONTH': '%B', 'YYYY': '%Y', 'YY': '%y', 'HH': '%I', 'HH12': '%I', 'HH24': '%H', 'MI': '%M', 'SS': '%S', 'SSSSS': '%f', 'TZH': '%z'}"}, "sqlglot.dialects.bigquery.BigQuery.PSEUDOCOLUMNS": {"fullname": "sqlglot.dialects.bigquery.BigQuery.PSEUDOCOLUMNS", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.PSEUDOCOLUMNS", "kind": "variable", "doc": "<p>Columns that are auto-generated by the engine corresponding to this dialect.\nFor example, such columns may be excluded from <code>SELECT *</code> queries.</p>\n", "annotation": ": Set[str]", "default_value": "{'_PARTITIONDATE', '_PARTITIONTIME'}"}, "sqlglot.dialects.bigquery.BigQuery.normalize_identifier": {"fullname": "sqlglot.dialects.bigquery.BigQuery.normalize_identifier", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.normalize_identifier", "kind": "function", "doc": "<p>Transforms an identifier in a way that resembles how it'd be resolved by this dialect.</p>\n\n<p>For example, an identifier like <code>FoO</code> would be resolved as <code>foo</code> in Postgres, because it\nlowercases all unquoted identifiers. On the other hand, Snowflake uppercases them, so\nit would resolve it as <code>FOO</code>. If it was quoted, it'd need to be treated as case-sensitive,\nand so any normalization would be prohibited in order to avoid \"breaking\" the identifier.</p>\n\n<p>There are also dialects like Spark, which are case-insensitive even when quotes are\npresent, and dialects like MySQL, whose resolution rules match those employed by the\nunderlying operating system, for example they may always be case-sensitive in Linux.</p>\n\n<p>Finally, the normalization behavior of some engines can even be controlled through flags,\nlike in Redshift's case, where users can explicitly set enable_case_sensitive_identifier.</p>\n\n<p>SQLGlot aims to understand and handle all of these different behaviors gracefully, so\nthat it can analyze queries in the optimizer and successfully capture their semantics.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"o\">~</span><span class=\"n\">E</span></span><span class=\"return-annotation\">) -> <span class=\"o\">~</span><span class=\"n\">E</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.bigquery.BigQuery.Tokenizer": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Tokenizer", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Tokenizer", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.tokens.Tokenizer"}, "sqlglot.dialects.bigquery.BigQuery.Tokenizer.QUOTES": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Tokenizer.QUOTES", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Tokenizer.QUOTES", "kind": "variable", "doc": "<p></p>\n", "default_value": "["'", '"', '"""', "'''"]"}, "sqlglot.dialects.bigquery.BigQuery.Tokenizer.COMMENTS": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Tokenizer.COMMENTS", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Tokenizer.COMMENTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "['--', '#', ('/*', '*/')]"}, "sqlglot.dialects.bigquery.BigQuery.Tokenizer.IDENTIFIERS": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Tokenizer.IDENTIFIERS", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Tokenizer.IDENTIFIERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "['`']"}, "sqlglot.dialects.bigquery.BigQuery.Tokenizer.STRING_ESCAPES": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Tokenizer.STRING_ESCAPES", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Tokenizer.STRING_ESCAPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "['\\\\']"}, "sqlglot.dialects.bigquery.BigQuery.Tokenizer.HEX_STRINGS": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Tokenizer.HEX_STRINGS", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Tokenizer.HEX_STRINGS", "kind": "variable", "doc": "<p></p>\n", "default_value": "[('0x', ''), ('0X', '')]"}, "sqlglot.dialects.bigquery.BigQuery.Tokenizer.BYTE_STRINGS": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Tokenizer.BYTE_STRINGS", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Tokenizer.BYTE_STRINGS", "kind": "variable", "doc": "<p></p>\n", "default_value": "[("b'", "'"), ("B'", "'"), ('b"', '"'), ('B"', '"'), ('b"""', '"""'), ('B"""', '"""'), ("b'''", "'''"), ("B'''", "'''")]"}, "sqlglot.dialects.bigquery.BigQuery.Tokenizer.RAW_STRINGS": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Tokenizer.RAW_STRINGS", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Tokenizer.RAW_STRINGS", "kind": "variable", "doc": "<p></p>\n", "default_value": "[("r'", "'"), ("R'", "'"), ('r"', '"'), ('R"', '"'), ('r"""', '"""'), ('R"""', '"""'), ("r'''", "'''"), ("R'''", "'''")]"}, "sqlglot.dialects.bigquery.BigQuery.Tokenizer.KEYWORDS": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Tokenizer.KEYWORDS", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Tokenizer.KEYWORDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'{%': <TokenType.BLOCK_START: 'BLOCK_START'>, '{%+': <TokenType.BLOCK_START: 'BLOCK_START'>, '{%-': <TokenType.BLOCK_START: 'BLOCK_START'>, '%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '+%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '-%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '{{+': <TokenType.BLOCK_START: 'BLOCK_START'>, '{{-': <TokenType.BLOCK_START: 'BLOCK_START'>, '+}}': <TokenType.BLOCK_END: 'BLOCK_END'>, '-}}': <TokenType.BLOCK_END: 'BLOCK_END'>, '/*+': <TokenType.HINT: 'HINT'>, '==': <TokenType.EQ: 'EQ'>, '::': <TokenType.DCOLON: 'DCOLON'>, '||': <TokenType.DPIPE: 'DPIPE'>, '>=': <TokenType.GTE: 'GTE'>, '<=': <TokenType.LTE: 'LTE'>, '<>': <TokenType.NEQ: 'NEQ'>, '!=': <TokenType.NEQ: 'NEQ'>, ':=': <TokenType.COLON_EQ: 'COLON_EQ'>, '<=>': <TokenType.NULLSAFE_EQ: 'NULLSAFE_EQ'>, '->': <TokenType.ARROW: 'ARROW'>, '->>': <TokenType.DARROW: 'DARROW'>, '=>': <TokenType.FARROW: 'FARROW'>, '#>': <TokenType.HASH_ARROW: 'HASH_ARROW'>, '#>>': <TokenType.DHASH_ARROW: 'DHASH_ARROW'>, '<->': <TokenType.LR_ARROW: 'LR_ARROW'>, '&&': <TokenType.DAMP: 'DAMP'>, '??': <TokenType.DQMARK: 'DQMARK'>, 'ALL': <TokenType.ALL: 'ALL'>, 'ALWAYS': <TokenType.ALWAYS: 'ALWAYS'>, 'AND': <TokenType.AND: 'AND'>, 'ANTI': <TokenType.ANTI: 'ANTI'>, 'ANY': <TokenType.ANY: 'ANY'>, 'ASC': <TokenType.ASC: 'ASC'>, 'AS': <TokenType.ALIAS: 'ALIAS'>, 'ASOF': <TokenType.ASOF: 'ASOF'>, 'AUTOINCREMENT': <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, 'AUTO_INCREMENT': <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, 'BEGIN': <TokenType.COMMAND: 'COMMAND'>, 'BETWEEN': <TokenType.BETWEEN: 'BETWEEN'>, 'CACHE': <TokenType.CACHE: 'CACHE'>, 'UNCACHE': <TokenType.UNCACHE: 'UNCACHE'>, 'CASE': <TokenType.CASE: 'CASE'>, 'CHARACTER SET': <TokenType.CHARACTER_SET: 'CHARACTER_SET'>, 'CLUSTER BY': <TokenType.CLUSTER_BY: 'CLUSTER_BY'>, 'COLLATE': <TokenType.COLLATE: 'COLLATE'>, 'COLUMN': <TokenType.COLUMN: 'COLUMN'>, 'COMMIT': <TokenType.COMMIT: 'COMMIT'>, 'CONNECT BY': <TokenType.CONNECT_BY: 'CONNECT_BY'>, 'CONSTRAINT': <TokenType.CONSTRAINT: 'CONSTRAINT'>, 'COPY': <TokenType.COPY: 'COPY'>, 'CREATE': <TokenType.CREATE: 'CREATE'>, 'CROSS': <TokenType.CROSS: 'CROSS'>, 'CUBE': <TokenType.CUBE: 'CUBE'>, 'CURRENT_DATE': <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, 'CURRENT_TIME': <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, 'CURRENT_TIMESTAMP': <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, 'CURRENT_USER': <TokenType.CURRENT_USER: 'CURRENT_USER'>, 'DATABASE': <TokenType.DATABASE: 'DATABASE'>, 'DEFAULT': <TokenType.DEFAULT: 'DEFAULT'>, 'DELETE': <TokenType.DELETE: 'DELETE'>, 'DESC': <TokenType.DESC: 'DESC'>, 'DESCRIBE': <TokenType.DESCRIBE: 'DESCRIBE'>, 'DISTINCT': <TokenType.DISTINCT: 'DISTINCT'>, 'DISTRIBUTE BY': <TokenType.DISTRIBUTE_BY: 'DISTRIBUTE_BY'>, 'DROP': <TokenType.DROP: 'DROP'>, 'ELSE': <TokenType.ELSE: 'ELSE'>, 'END': <TokenType.END: 'END'>, 'ENUM': <TokenType.ENUM: 'ENUM'>, 'ESCAPE': <TokenType.ESCAPE: 'ESCAPE'>, 'EXCEPT': <TokenType.EXCEPT: 'EXCEPT'>, 'EXECUTE': <TokenType.EXECUTE: 'EXECUTE'>, 'EXISTS': <TokenType.EXISTS: 'EXISTS'>, 'FALSE': <TokenType.FALSE: 'FALSE'>, 'FETCH': <TokenType.FETCH: 'FETCH'>, 'FILTER': <TokenType.FILTER: 'FILTER'>, 'FIRST': <TokenType.FIRST: 'FIRST'>, 'FULL': <TokenType.FULL: 'FULL'>, 'FUNCTION': <TokenType.FUNCTION: 'FUNCTION'>, 'FOR': <TokenType.FOR: 'FOR'>, 'FOREIGN KEY': <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, 'FORMAT': <TokenType.FORMAT: 'FORMAT'>, 'FROM': <TokenType.FROM: 'FROM'>, 'GEOGRAPHY': <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, 'GEOMETRY': <TokenType.GEOMETRY: 'GEOMETRY'>, 'GLOB': <TokenType.GLOB: 'GLOB'>, 'GROUP BY': <TokenType.GROUP_BY: 'GROUP_BY'>, 'GROUPING SETS': <TokenType.GROUPING_SETS: 'GROUPING_SETS'>, 'HAVING': <TokenType.HAVING: 'HAVING'>, 'ILIKE': <TokenType.ILIKE: 'ILIKE'>, 'IN': <TokenType.IN: 'IN'>, 'INDEX': <TokenType.INDEX: 'INDEX'>, 'INET': <TokenType.INET: 'INET'>, 'INNER': <TokenType.INNER: 'INNER'>, 'INSERT': <TokenType.INSERT: 'INSERT'>, 'INTERVAL': <TokenType.INTERVAL: 'INTERVAL'>, 'INTERSECT': <TokenType.INTERSECT: 'INTERSECT'>, 'INTO': <TokenType.INTO: 'INTO'>, 'IS': <TokenType.IS: 'IS'>, 'ISNULL': <TokenType.ISNULL: 'ISNULL'>, 'JOIN': <TokenType.JOIN: 'JOIN'>, 'KEEP': <TokenType.KEEP: 'KEEP'>, 'KILL': <TokenType.KILL: 'KILL'>, 'LATERAL': <TokenType.LATERAL: 'LATERAL'>, 'LEFT': <TokenType.LEFT: 'LEFT'>, 'LIKE': <TokenType.LIKE: 'LIKE'>, 'LIMIT': <TokenType.LIMIT: 'LIMIT'>, 'LOAD': <TokenType.LOAD: 'LOAD'>, 'LOCK': <TokenType.LOCK: 'LOCK'>, 'MERGE': <TokenType.MERGE: 'MERGE'>, 'NATURAL': <TokenType.NATURAL: 'NATURAL'>, 'NEXT': <TokenType.NEXT: 'NEXT'>, 'NOT': <TokenType.NOT: 'NOT'>, 'NOTNULL': <TokenType.NOTNULL: 'NOTNULL'>, 'NULL': <TokenType.NULL: 'NULL'>, 'OBJECT': <TokenType.OBJECT: 'OBJECT'>, 'OFFSET': <TokenType.OFFSET: 'OFFSET'>, 'ON': <TokenType.ON: 'ON'>, 'OR': <TokenType.OR: 'OR'>, 'XOR': <TokenType.XOR: 'XOR'>, 'ORDER BY': <TokenType.ORDER_BY: 'ORDER_BY'>, 'ORDINALITY': <TokenType.ORDINALITY: 'ORDINALITY'>, 'OUTER': <TokenType.OUTER: 'OUTER'>, 'OVER': <TokenType.OVER: 'OVER'>, 'OVERLAPS': <TokenType.OVERLAPS: 'OVERLAPS'>, 'OVERWRITE': <TokenType.OVERWRITE: 'OVERWRITE'>, 'PARTITION': <TokenType.PARTITION: 'PARTITION'>, 'PARTITION BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PARTITIONED BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PARTITIONED_BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PERCENT': <TokenType.PERCENT: 'PERCENT'>, 'PIVOT': <TokenType.PIVOT: 'PIVOT'>, 'PRAGMA': <TokenType.PRAGMA: 'PRAGMA'>, 'PRIMARY KEY': <TokenType.PRIMARY_KEY: 'PRIMARY_KEY'>, 'PROCEDURE': <TokenType.PROCEDURE: 'PROCEDURE'>, 'QUALIFY': <TokenType.QUALIFY: 'QUALIFY'>, 'RANGE': <TokenType.RANGE: 'RANGE'>, 'RECURSIVE': <TokenType.RECURSIVE: 'RECURSIVE'>, 'REGEXP': <TokenType.RLIKE: 'RLIKE'>, 'REPLACE': <TokenType.REPLACE: 'REPLACE'>, 'RETURNING': <TokenType.RETURNING: 'RETURNING'>, 'REFERENCES': <TokenType.REFERENCES: 'REFERENCES'>, 'RIGHT': <TokenType.RIGHT: 'RIGHT'>, 'RLIKE': <TokenType.RLIKE: 'RLIKE'>, 'ROLLBACK': <TokenType.ROLLBACK: 'ROLLBACK'>, 'ROLLUP': <TokenType.ROLLUP: 'ROLLUP'>, 'ROW': <TokenType.ROW: 'ROW'>, 'ROWS': <TokenType.ROWS: 'ROWS'>, 'SCHEMA': <TokenType.SCHEMA: 'SCHEMA'>, 'SELECT': <TokenType.SELECT: 'SELECT'>, 'SEMI': <TokenType.SEMI: 'SEMI'>, 'SET': <TokenType.SET: 'SET'>, 'SETTINGS': <TokenType.SETTINGS: 'SETTINGS'>, 'SHOW': <TokenType.SHOW: 'SHOW'>, 'SIMILAR TO': <TokenType.SIMILAR_TO: 'SIMILAR_TO'>, 'SOME': <TokenType.SOME: 'SOME'>, 'SORT BY': <TokenType.SORT_BY: 'SORT_BY'>, 'START WITH': <TokenType.START_WITH: 'START_WITH'>, 'TABLE': <TokenType.TABLE: 'TABLE'>, 'TABLESAMPLE': <TokenType.TABLE_SAMPLE: 'TABLE_SAMPLE'>, 'TEMP': <TokenType.TEMPORARY: 'TEMPORARY'>, 'TEMPORARY': <TokenType.TEMPORARY: 'TEMPORARY'>, 'THEN': <TokenType.THEN: 'THEN'>, 'TRUE': <TokenType.TRUE: 'TRUE'>, 'TRUNCATE': <TokenType.TRUNCATE: 'TRUNCATE'>, 'UNION': <TokenType.UNION: 'UNION'>, 'UNKNOWN': <TokenType.UNKNOWN: 'UNKNOWN'>, 'UNNEST': <TokenType.UNNEST: 'UNNEST'>, 'UNPIVOT': <TokenType.UNPIVOT: 'UNPIVOT'>, 'UPDATE': <TokenType.UPDATE: 'UPDATE'>, 'USE': <TokenType.USE: 'USE'>, 'USING': <TokenType.USING: 'USING'>, 'UUID': <TokenType.UUID: 'UUID'>, 'VIEW': <TokenType.VIEW: 'VIEW'>, 'VOLATILE': <TokenType.VOLATILE: 'VOLATILE'>, 'WHEN': <TokenType.WHEN: 'WHEN'>, 'WHERE': <TokenType.WHERE: 'WHERE'>, 'WINDOW': <TokenType.WINDOW: 'WINDOW'>, 'WITH': <TokenType.WITH: 'WITH'>, 'APPLY': <TokenType.APPLY: 'APPLY'>, 'ARRAY': <TokenType.ARRAY: 'ARRAY'>, 'BIT': <TokenType.BIT: 'BIT'>, 'BOOL': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BOOLEAN': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BYTE': <TokenType.TINYINT: 'TINYINT'>, 'MEDIUMINT': <TokenType.MEDIUMINT: 'MEDIUMINT'>, 'INT1': <TokenType.TINYINT: 'TINYINT'>, 'TINYINT': <TokenType.TINYINT: 'TINYINT'>, 'INT16': <TokenType.SMALLINT: 'SMALLINT'>, 'SHORT': <TokenType.SMALLINT: 'SMALLINT'>, 'SMALLINT': <TokenType.SMALLINT: 'SMALLINT'>, 'INT128': <TokenType.INT128: 'INT128'>, 'HUGEINT': <TokenType.INT128: 'INT128'>, 'INT2': <TokenType.SMALLINT: 'SMALLINT'>, 'INTEGER': <TokenType.INT: 'INT'>, 'INT': <TokenType.INT: 'INT'>, 'INT4': <TokenType.INT: 'INT'>, 'INT32': <TokenType.INT: 'INT'>, 'INT64': <TokenType.BIGINT: 'BIGINT'>, 'LONG': <TokenType.BIGINT: 'BIGINT'>, 'BIGINT': <TokenType.BIGINT: 'BIGINT'>, 'INT8': <TokenType.TINYINT: 'TINYINT'>, 'UINT': <TokenType.UINT: 'UINT'>, 'DEC': <TokenType.DECIMAL: 'DECIMAL'>, 'DECIMAL': <TokenType.DECIMAL: 'DECIMAL'>, 'BIGDECIMAL': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'BIGNUMERIC': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'MAP': <TokenType.MAP: 'MAP'>, 'NULLABLE': <TokenType.NULLABLE: 'NULLABLE'>, 'NUMBER': <TokenType.DECIMAL: 'DECIMAL'>, 'NUMERIC': <TokenType.DECIMAL: 'DECIMAL'>, 'FIXED': <TokenType.DECIMAL: 'DECIMAL'>, 'REAL': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT4': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT8': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE PRECISION': <TokenType.DOUBLE: 'DOUBLE'>, 'JSON': <TokenType.JSON: 'JSON'>, 'CHAR': <TokenType.CHAR: 'CHAR'>, 'CHARACTER': <TokenType.CHAR: 'CHAR'>, 'NCHAR': <TokenType.NCHAR: 'NCHAR'>, 'VARCHAR': <TokenType.VARCHAR: 'VARCHAR'>, 'VARCHAR2': <TokenType.VARCHAR: 'VARCHAR'>, 'NVARCHAR': <TokenType.NVARCHAR: 'NVARCHAR'>, 'NVARCHAR2': <TokenType.NVARCHAR: 'NVARCHAR'>, 'BPCHAR': <TokenType.BPCHAR: 'BPCHAR'>, 'STR': <TokenType.TEXT: 'TEXT'>, 'STRING': <TokenType.TEXT: 'TEXT'>, 'TEXT': <TokenType.TEXT: 'TEXT'>, 'LONGTEXT': <TokenType.LONGTEXT: 'LONGTEXT'>, 'MEDIUMTEXT': <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, 'TINYTEXT': <TokenType.TINYTEXT: 'TINYTEXT'>, 'CLOB': <TokenType.TEXT: 'TEXT'>, 'LONGVARCHAR': <TokenType.TEXT: 'TEXT'>, 'BINARY': <TokenType.BINARY: 'BINARY'>, 'BLOB': <TokenType.VARBINARY: 'VARBINARY'>, 'LONGBLOB': <TokenType.LONGBLOB: 'LONGBLOB'>, 'MEDIUMBLOB': <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, 'TINYBLOB': <TokenType.TINYBLOB: 'TINYBLOB'>, 'BYTEA': <TokenType.VARBINARY: 'VARBINARY'>, 'VARBINARY': <TokenType.VARBINARY: 'VARBINARY'>, 'TIME': <TokenType.TIME: 'TIME'>, 'TIMETZ': <TokenType.TIMETZ: 'TIMETZ'>, 'TIMESTAMP': <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, 'TIMESTAMPTZ': <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, 'TIMESTAMPLTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMP_LTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMPNTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'TIMESTAMP_NTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'DATE': <TokenType.DATE: 'DATE'>, 'DATETIME': <TokenType.TIMESTAMP: 'TIMESTAMP'>, 'INT4RANGE': <TokenType.INT4RANGE: 'INT4RANGE'>, 'INT4MULTIRANGE': <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, 'INT8RANGE': <TokenType.INT8RANGE: 'INT8RANGE'>, 'INT8MULTIRANGE': <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, 'NUMRANGE': <TokenType.NUMRANGE: 'NUMRANGE'>, 'NUMMULTIRANGE': <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, 'TSRANGE': <TokenType.TSRANGE: 'TSRANGE'>, 'TSMULTIRANGE': <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, 'TSTZRANGE': <TokenType.TSTZRANGE: 'TSTZRANGE'>, 'TSTZMULTIRANGE': <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, 'DATERANGE': <TokenType.DATERANGE: 'DATERANGE'>, 'DATEMULTIRANGE': <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, 'UNIQUE': <TokenType.UNIQUE: 'UNIQUE'>, 'STRUCT': <TokenType.STRUCT: 'STRUCT'>, 'SEQUENCE': <TokenType.SEQUENCE: 'SEQUENCE'>, 'VARIANT': <TokenType.VARIANT: 'VARIANT'>, 'ALTER': <TokenType.ALTER: 'ALTER'>, 'ANALYZE': <TokenType.COMMAND: 'COMMAND'>, 'CALL': <TokenType.COMMAND: 'COMMAND'>, 'COMMENT': <TokenType.COMMENT: 'COMMENT'>, 'EXPLAIN': <TokenType.COMMAND: 'COMMAND'>, 'GRANT': <TokenType.COMMAND: 'COMMAND'>, 'OPTIMIZE': <TokenType.COMMAND: 'COMMAND'>, 'PREPARE': <TokenType.COMMAND: 'COMMAND'>, 'VACUUM': <TokenType.COMMAND: 'COMMAND'>, 'USER-DEFINED': <TokenType.USERDEFINED: 'USERDEFINED'>, 'FOR VERSION': <TokenType.VERSION_SNAPSHOT: 'VERSION_SNAPSHOT'>, 'FOR TIMESTAMP': <TokenType.TIMESTAMP_SNAPSHOT: 'TIMESTAMP_SNAPSHOT'>, 'ANY TYPE': <TokenType.VARIANT: 'VARIANT'>, 'BEGIN TRANSACTION': <TokenType.BEGIN: 'BEGIN'>, 'BYTES': <TokenType.BINARY: 'BINARY'>, 'CURRENT_DATETIME': <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>, 'DECLARE': <TokenType.COMMAND: 'COMMAND'>, 'ELSEIF': <TokenType.COMMAND: 'COMMAND'>, 'EXCEPTION': <TokenType.COMMAND: 'COMMAND'>, 'FLOAT64': <TokenType.DOUBLE: 'DOUBLE'>, 'FOR SYSTEM_TIME': <TokenType.TIMESTAMP_SNAPSHOT: 'TIMESTAMP_SNAPSHOT'>, 'MODEL': <TokenType.MODEL: 'MODEL'>, 'NOT DETERMINISTIC': <TokenType.VOLATILE: 'VOLATILE'>, 'RECORD': <TokenType.STRUCT: 'STRUCT'>}"}, "sqlglot.dialects.bigquery.BigQuery.Parser": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Parser", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Parser", "kind": "class", "doc": "<p>Parser consumes a list of tokens produced by the Tokenizer and produces a parsed syntax tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>error_level:</strong> The desired error level.\nDefault: ErrorLevel.IMMEDIATE</li>\n<li><strong>error_message_context:</strong> The amount of context to capture from a query string when displaying\nthe error message (in number of characters).\nDefault: 100</li>\n<li><strong>max_errors:</strong> Maximum number of error messages to include in a raised ParseError.\nThis is only relevant if error_level is ErrorLevel.RAISE.\nDefault: 3</li>\n</ul>\n", "bases": "sqlglot.parser.Parser"}, "sqlglot.dialects.bigquery.BigQuery.Parser.PREFIXED_PIVOT_COLUMNS": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Parser.PREFIXED_PIVOT_COLUMNS", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Parser.PREFIXED_PIVOT_COLUMNS", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.bigquery.BigQuery.Parser.LOG_DEFAULTS_TO_LN": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Parser.LOG_DEFAULTS_TO_LN", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Parser.LOG_DEFAULTS_TO_LN", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.bigquery.BigQuery.Parser.SUPPORTS_IMPLICIT_UNNEST": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Parser.SUPPORTS_IMPLICIT_UNNEST", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Parser.SUPPORTS_IMPLICIT_UNNEST", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.bigquery.BigQuery.Parser.FUNCTIONS": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Parser.FUNCTIONS", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Parser.FUNCTIONS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ABS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Abs'>>, 'ADD_MONTHS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AddMonths'>>, 'ANONYMOUS_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnonymousAggFunc'>>, 'ANY_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnyValue'>>, 'APPROX_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_COUNT_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'APPROX_TOP_K': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxTopK'>>, 'ARG_MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARGMAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'MAX_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARG_MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARGMIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'MIN_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Array'>>, 'ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAgg'>>, 'ARRAY_ALL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAll'>>, 'ARRAY_ANY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAny'>>, 'ARRAY_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CONSTRUCT_COMPACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConstructCompact'>>, 'ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayContains'>>, 'FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_OVERLAPS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayOverlaps'>>, 'ARRAY_SIZE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_SORT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySort'>>, 'ARRAY_SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySum'>>, 'ARRAY_TO_STRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_JOIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_UNION_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUnionAgg'>>, 'ARRAY_UNIQUE_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUniqueAgg'>>, 'AVG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Avg'>>, 'CASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Case'>>, 'CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cast'>>, 'CAST_TO_STR_TYPE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CastToStrType'>>, 'CBRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cbrt'>>, 'CEIL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CEILING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CHR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'COALESCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'IFNULL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'NVL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'COLLATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Collate'>>, 'COMBINED_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedAggFunc'>>, 'COMBINED_PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedParameterizedAgg'>>, 'CONCAT': <function Parser.<lambda>>, 'CONCAT_WS': <function Parser.<lambda>>, 'CONNECT_BY_ROOT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ConnectByRoot'>>, 'CONVERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Convert'>>, 'CORR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Corr'>>, 'COUNT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Count'>>, 'COUNT_IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COUNTIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COVAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarPop'>>, 'COVAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarSamp'>>, 'CURRENT_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDate'>>, 'CURRENT_DATETIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDatetime'>>, 'CURRENT_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTime'>>, 'CURRENT_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTimestamp'>>, 'CURRENT_USER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentUser'>>, 'DATE': <function _build_date>, 'DATE_ADD': <function build_date_delta_with_interval.<locals>._builder>, 'DATEDIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateDiff'>>, 'DATE_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateDiff'>>, 'DATE_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATE_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateStrToDate'>>, 'DATE_SUB': <function build_date_delta_with_interval.<locals>._builder>, 'DATE_TO_DATE_STR': <function Parser.<lambda>>, 'DATE_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateToDi'>>, 'DATE_TRUNC': <function BigQuery.Parser.<lambda>>, 'DATETIME_ADD': <function build_date_delta_with_interval.<locals>._builder>, 'DATETIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeDiff'>>, 'DATETIME_SUB': <function build_date_delta_with_interval.<locals>._builder>, 'DATETIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeTrunc'>>, 'DAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Day'>>, 'DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAYOFMONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAY_OF_WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAYOFWEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAY_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DAYOFYEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DECODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Decode'>>, 'DI_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DiToDate'>>, 'ENCODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Encode'>>, 'EXP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Exp'>>, 'EXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Explode'>>, 'EXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ExplodeOuter'>>, 'EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Extract'>>, 'FIRST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.First'>>, 'FIRST_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FirstValue'>>, 'FLATTEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Flatten'>>, 'FLOOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Floor'>>, 'FROM_BASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase'>>, 'FROM_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase64'>>, 'GENERATE_DATE_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GenerateDateArray'>>, 'GENERATE_SERIES': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GenerateSeries'>>, 'GREATEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Greatest'>>, 'GROUP_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GroupConcat'>>, 'HEX': <function build_hex>, 'HLL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Hll'>>, 'IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'IIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'INITCAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Initcap'>>, 'IS_INF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'ISINF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'IS_NAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'ISNAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'J_S_O_N_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArray'>>, 'J_S_O_N_ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArrayAgg'>>, 'JSON_ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArrayContains'>>, 'JSONB_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONBExtract'>>, 'JSONB_EXTRACT_SCALAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONBExtractScalar'>>, 'JSON_EXTRACT': <function build_extract_json_with_path.<locals>._builder>, 'JSON_EXTRACT_SCALAR': <function BigQuery.Parser.<lambda>>, 'JSON_FORMAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONFormat'>>, 'J_S_O_N_OBJECT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONObject'>>, 'J_S_O_N_OBJECT_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONObjectAgg'>>, 'J_S_O_N_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONTable'>>, 'LAG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lag'>>, 'LAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Last'>>, 'LAST_DAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastDay'>>, 'LAST_DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastDay'>>, 'LAST_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastValue'>>, 'LEAD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lead'>>, 'LEAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Least'>>, 'LEFT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Left'>>, 'LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Length'>>, 'LEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Length'>>, 'LEVENSHTEIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Levenshtein'>>, 'LN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ln'>>, 'LOG': <function build_logarithm>, 'LOGICAL_AND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'BOOL_AND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'BOOLAND_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'LOGICAL_OR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'BOOL_OR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'BOOLOR_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'LOWER': <function build_lower>, 'LCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lower'>>, 'LOWER_HEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LowerHex'>>, 'MD5': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MD5Digest'>>, 'MD5_DIGEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MD5Digest'>>, 'MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Map'>>, 'MAP_FROM_ENTRIES': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MapFromEntries'>>, 'MATCH_AGAINST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MatchAgainst'>>, 'MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Max'>>, 'MIN': <bound method Func.from_arg_list of 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"doc": "<p></p>\n", "default_value": "{<TokenType.CURRENT_DATE: 'CURRENT_DATE'>: <class 'sqlglot.expressions.CurrentDate'>, <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>: <class 'sqlglot.expressions.CurrentDatetime'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>: <class 'sqlglot.expressions.CurrentTime'>, <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>: <class 'sqlglot.expressions.CurrentTimestamp'>, <TokenType.CURRENT_USER: 'CURRENT_USER'>: <class 'sqlglot.expressions.CurrentUser'>}"}, "sqlglot.dialects.bigquery.BigQuery.Parser.NESTED_TYPE_TOKENS": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Parser.NESTED_TYPE_TOKENS", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Parser.NESTED_TYPE_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.NESTED: 'NESTED'>, <TokenType.ARRAY: 'ARRAY'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.NULLABLE: 'NULLABLE'>, <TokenType.STRUCT: 'STRUCT'>, <TokenType.MAP: 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"default_value": "{'AUTOINCREMENT': <function Parser.<lambda>>, 'AUTO_INCREMENT': <function Parser.<lambda>>, 'CASESPECIFIC': <function Parser.<lambda>>, 'CHARACTER SET': <function Parser.<lambda>>, 'CHECK': <function Parser.<lambda>>, 'COLLATE': <function Parser.<lambda>>, 'COMMENT': <function Parser.<lambda>>, 'COMPRESS': <function Parser.<lambda>>, 'CLUSTERED': <function Parser.<lambda>>, 'NONCLUSTERED': <function Parser.<lambda>>, 'DEFAULT': <function Parser.<lambda>>, 'ENCODE': <function Parser.<lambda>>, 'EPHEMERAL': <function Parser.<lambda>>, 'EXCLUDE': <function Parser.<lambda>>, 'FOREIGN KEY': <function Parser.<lambda>>, 'FORMAT': <function Parser.<lambda>>, 'GENERATED': <function Parser.<lambda>>, 'IDENTITY': <function Parser.<lambda>>, 'INLINE': <function Parser.<lambda>>, 'LIKE': <function Parser.<lambda>>, 'NOT': <function Parser.<lambda>>, 'NULL': <function Parser.<lambda>>, 'ON': <function Parser.<lambda>>, 'PATH': <function Parser.<lambda>>, 'PERIOD': <function Parser.<lambda>>, 'PRIMARY KEY': <function Parser.<lambda>>, 'REFERENCES': <function Parser.<lambda>>, 'TITLE': <function Parser.<lambda>>, 'TTL': <function Parser.<lambda>>, 'UNIQUE': <function Parser.<lambda>>, 'UPPERCASE': <function Parser.<lambda>>, 'WITH': <function Parser.<lambda>>, 'OPTIONS': <function BigQuery.Parser.<lambda>>}"}, "sqlglot.dialects.bigquery.BigQuery.Parser.RANGE_PARSERS": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Parser.RANGE_PARSERS", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Parser.RANGE_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.BETWEEN: 'BETWEEN'>: <function Parser.<lambda>>, <TokenType.GLOB: 'GLOB'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.ILIKE: 'ILIKE'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.IN: 'IN'>: <function Parser.<lambda>>, <TokenType.IRLIKE: 'IRLIKE'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.IS: 'IS'>: <function Parser.<lambda>>, <TokenType.LIKE: 'LIKE'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.RLIKE: 'RLIKE'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.SIMILAR_TO: 'SIMILAR_TO'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.FOR: 'FOR'>: <function Parser.<lambda>>}"}, "sqlglot.dialects.bigquery.BigQuery.Parser.NULL_TOKENS": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Parser.NULL_TOKENS", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Parser.NULL_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.UNKNOWN: 'UNKNOWN'>, <TokenType.NULL: 'NULL'>}"}, "sqlglot.dialects.bigquery.BigQuery.Parser.STATEMENT_PARSERS": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Parser.STATEMENT_PARSERS", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Parser.STATEMENT_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.ALTER: 'ALTER'>: <function Parser.<lambda>>, <TokenType.BEGIN: 'BEGIN'>: <function Parser.<lambda>>, <TokenType.CACHE: 'CACHE'>: <function Parser.<lambda>>, <TokenType.COMMENT: 'COMMENT'>: <function Parser.<lambda>>, <TokenType.COMMIT: 'COMMIT'>: <function Parser.<lambda>>, <TokenType.COPY: 'COPY'>: <function Parser.<lambda>>, <TokenType.CREATE: 'CREATE'>: <function Parser.<lambda>>, <TokenType.DELETE: 'DELETE'>: <function Parser.<lambda>>, <TokenType.DESC: 'DESC'>: <function Parser.<lambda>>, <TokenType.DESCRIBE: 'DESCRIBE'>: <function Parser.<lambda>>, <TokenType.DROP: 'DROP'>: <function Parser.<lambda>>, <TokenType.INSERT: 'INSERT'>: <function Parser.<lambda>>, <TokenType.KILL: 'KILL'>: <function Parser.<lambda>>, <TokenType.LOAD: 'LOAD'>: <function Parser.<lambda>>, <TokenType.MERGE: 'MERGE'>: <function Parser.<lambda>>, <TokenType.PIVOT: 'PIVOT'>: <function Parser.<lambda>>, <TokenType.PRAGMA: 'PRAGMA'>: <function Parser.<lambda>>, <TokenType.REFRESH: 'REFRESH'>: <function Parser.<lambda>>, <TokenType.ROLLBACK: 'ROLLBACK'>: <function Parser.<lambda>>, <TokenType.SET: 'SET'>: <function Parser.<lambda>>, <TokenType.TRUNCATE: 'TRUNCATE'>: <function Parser.<lambda>>, <TokenType.UNCACHE: 'UNCACHE'>: <function Parser.<lambda>>, <TokenType.UPDATE: 'UPDATE'>: <function Parser.<lambda>>, <TokenType.USE: 'USE'>: <function Parser.<lambda>>, <TokenType.SEMICOLON: 'SEMICOLON'>: <function Parser.<lambda>>, <TokenType.ELSE: 'ELSE'>: <function BigQuery.Parser.<lambda>>, <TokenType.END: 'END'>: <function BigQuery.Parser.<lambda>>, <TokenType.FOR: 'FOR'>: <function BigQuery.Parser.<lambda>>}"}, "sqlglot.dialects.bigquery.BigQuery.Parser.BRACKET_OFFSETS": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Parser.BRACKET_OFFSETS", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Parser.BRACKET_OFFSETS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'OFFSET': (0, False), 'ORDINAL': (1, False), 'SAFE_OFFSET': (0, True), 'SAFE_ORDINAL': (1, True)}"}, "sqlglot.dialects.bigquery.BigQuery.Parser.TABLE_ALIAS_TOKENS": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Parser.TABLE_ALIAS_TOKENS", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Parser.TABLE_ALIAS_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.KILL: 'KILL'>, <TokenType.MONEY: 'MONEY'>, <TokenType.COPY: 'COPY'>, <TokenType.PERCENT: 'PERCENT'>, <TokenType.TAG: 'TAG'>, <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, <TokenType.VOLATILE: 'VOLATILE'>, <TokenType.IDENTIFIER: 'IDENTIFIER'>, <TokenType.VARBINARY: 'VARBINARY'>, <TokenType.HSTORE: 'HSTORE'>, <TokenType.ASC: 'ASC'>, <TokenType.IPADDRESS: 'IPADDRESS'>, <TokenType.ISNULL: 'ISNULL'>, <TokenType.TEMPORARY: 'TEMPORARY'>, <TokenType.PROCEDURE: 'PROCEDURE'>, <TokenType.SCHEMA: 'SCHEMA'>, <TokenType.NUMRANGE: 'NUMRANGE'>, <TokenType.DATE32: 'DATE32'>, <TokenType.INT8RANGE: 'INT8RANGE'>, <TokenType.ANTI: 'ANTI'>, <TokenType.AGGREGATEFUNCTION: 'AGGREGATEFUNCTION'>, <TokenType.VIEW: 'VIEW'>, <TokenType.VARCHAR: 'VARCHAR'>, <TokenType.TIMETZ: 'TIMETZ'>, <TokenType.GEOMETRY: 'GEOMETRY'>, <TokenType.BEGIN: 'BEGIN'>, <TokenType.ENUM8: 'ENUM8'>, <TokenType.INDEX: 'INDEX'>, <TokenType.PARTITION: 'PARTITION'>, <TokenType.UINT256: 'UINT256'>, <TokenType.BIGINT: 'BIGINT'>, <TokenType.CACHE: 'CACHE'>, <TokenType.OPERATOR: 'OPERATOR'>, <TokenType.COLUMN: 'COLUMN'>, <TokenType.INT128: 'INT128'>, <TokenType.SMALLMONEY: 'SMALLMONEY'>, <TokenType.HLLSKETCH: 'HLLSKETCH'>, <TokenType.UNPIVOT: 'UNPIVOT'>, <TokenType.SMALLINT: 'SMALLINT'>, <TokenType.INT256: 'INT256'>, <TokenType.FLOAT: 'FLOAT'>, <TokenType.COMMIT: 'COMMIT'>, <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, <TokenType.EXISTS: 'EXISTS'>, <TokenType.NULL: 'NULL'>, <TokenType.RECURSIVE: 'RECURSIVE'>, <TokenType.SET: 'SET'>, <TokenType.NULLABLE: 'NULLABLE'>, <TokenType.REFRESH: 'REFRESH'>, <TokenType.TINYTEXT: 'TINYTEXT'>, <TokenType.SHOW: 'SHOW'>, <TokenType.DEFAULT: 'DEFAULT'>, <TokenType.DATE: 'DATE'>, <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <TokenType.MERGE: 'MERGE'>, <TokenType.FIRST: 'FIRST'>, <TokenType.BINARY: 'BINARY'>, <TokenType.ARRAY: 'ARRAY'>, <TokenType.SERIAL: 'SERIAL'>, <TokenType.EXECUTE: 'EXECUTE'>, <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, <TokenType.INTERVAL: 'INTERVAL'>, <TokenType.PRAGMA: 'PRAGMA'>, <TokenType.STORAGE_INTEGRATION: 'STORAGE_INTEGRATION'>, <TokenType.BPCHAR: 'BPCHAR'>, <TokenType.BIT: 'BIT'>, <TokenType.UINT: 'UINT'>, <TokenType.UUID: 'UUID'>, <TokenType.STRUCT: 'STRUCT'>, <TokenType.FALSE: 'FALSE'>, <TokenType.FUNCTION: 'FUNCTION'>, <TokenType.TOP: 'TOP'>, <TokenType.SUPER: 'SUPER'>, <TokenType.CASE: 'CASE'>, <TokenType.IMAGE: 'IMAGE'>, <TokenType.UBIGINT: 'UBIGINT'>, <TokenType.LONGBLOB: 'LONGBLOB'>, <TokenType.ROLLUP: 'ROLLUP'>, <TokenType.VAR: 'VAR'>, <TokenType.COMMAND: 'COMMAND'>, <TokenType.LOAD: 'LOAD'>, <TokenType.TRUNCATE: 'TRUNCATE'>, <TokenType.KEEP: 'KEEP'>, <TokenType.UMEDIUMINT: 'UMEDIUMINT'>, <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, <TokenType.UINT128: 'UINT128'>, <TokenType.END: 'END'>, <TokenType.MAP: 'MAP'>, <TokenType.IPV4: 'IPV4'>, <TokenType.USERDEFINED: 'USERDEFINED'>, <TokenType.REFERENCES: 'REFERENCES'>, <TokenType.REPLACE: 'REPLACE'>, <TokenType.RANGE: 'RANGE'>, <TokenType.NVARCHAR: 'NVARCHAR'>, <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, <TokenType.TRUE: 'TRUE'>, <TokenType.TIMESTAMP_MS: 'TIMESTAMP_MS'>, <TokenType.VARIANT: 'VARIANT'>, <TokenType.ENUM: 'ENUM'>, <TokenType.USE: 'USE'>, <TokenType.USMALLINT: 'USMALLINT'>, <TokenType.OVERLAPS: 'OVERLAPS'>, <TokenType.TIMESTAMP_S: 'TIMESTAMP_S'>, <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, <TokenType.UNIQUE: 'UNIQUE'>, <TokenType.ORDINALITY: 'ORDINALITY'>, <TokenType.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>, <TokenType.TEXT: 'TEXT'>, <TokenType.DATABASE: 'DATABASE'>, <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, <TokenType.PSEUDO_TYPE: 'PSEUDO_TYPE'>, <TokenType.FIXEDSTRING: 'FIXEDSTRING'>, <TokenType.NEXT: 'NEXT'>, <TokenType.INT: 'INT'>, <TokenType.BIGSERIAL: 'BIGSERIAL'>, <TokenType.BOOLEAN: 'BOOLEAN'>, <TokenType.IS: 'IS'>, <TokenType.CONSTRAINT: 'CONSTRAINT'>, <TokenType.FINAL: 'FINAL'>, <TokenType.UNKNOWN: 'UNKNOWN'>, <TokenType.SETTINGS: 'SETTINGS'>, <TokenType.ROWS: 'ROWS'>, <TokenType.TSTZRANGE: 'TSTZRANGE'>, <TokenType.DATETIME64: 'DATETIME64'>, <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, <TokenType.DATETIME: 'DATETIME'>, <TokenType.MEDIUMINT: 'MEDIUMINT'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>, <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, <TokenType.XML: 'XML'>, <TokenType.JSON: 'JSON'>, <TokenType.UTINYINT: 'UTINYINT'>, <TokenType.DELETE: 'DELETE'>, <TokenType.TIME: 'TIME'>, <TokenType.UDECIMAL: 'UDECIMAL'>, <TokenType.NESTED: 'NESTED'>, <TokenType.SEMI: 'SEMI'>, <TokenType.DESC: 'DESC'>, <TokenType.ROWVERSION: 'ROWVERSION'>, <TokenType.TIMESTAMP_NS: 'TIMESTAMP_NS'>, <TokenType.ANY: 'ANY'>, <TokenType.DIV: 'DIV'>, <TokenType.DICTIONARY: 'DICTIONARY'>, <TokenType.INET: 'INET'>, <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, <TokenType.COMMENT: 'COMMENT'>, <TokenType.CURRENT_USER: 'CURRENT_USER'>, <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>, <TokenType.ALL: 'ALL'>, <TokenType.NAME: 'NAME'>, <TokenType.SOME: 'SOME'>, <TokenType.ENUM16: 'ENUM16'>, <TokenType.YEAR: 'YEAR'>, <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, <TokenType.DOUBLE: 'DOUBLE'>, <TokenType.INT4RANGE: 'INT4RANGE'>, <TokenType.FORMAT: 'FORMAT'>, <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, <TokenType.IPPREFIX: 'IPPREFIX'>, <TokenType.OVERWRITE: 'OVERWRITE'>, <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>, <TokenType.COLLATE: 'COLLATE'>, <TokenType.FILTER: 'FILTER'>, <TokenType.JSONB: 'JSONB'>, <TokenType.TDIGEST: 'TDIGEST'>, <TokenType.CHAR: 'CHAR'>, <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.ROW: 'ROW'>, <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.TABLE: 'TABLE'>, <TokenType.DATERANGE: 'DATERANGE'>, <TokenType.TSRANGE: 'TSRANGE'>, <TokenType.ESCAPE: 'ESCAPE'>, <TokenType.PIVOT: 'PIVOT'>, <TokenType.DECIMAL: 'DECIMAL'>, <TokenType.NCHAR: 'NCHAR'>, <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, <TokenType.UPDATE: 'UPDATE'>, <TokenType.MODEL: 'MODEL'>, <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, <TokenType.SEQUENCE: 'SEQUENCE'>, <TokenType.LONGTEXT: 'LONGTEXT'>, <TokenType.DESCRIBE: 'DESCRIBE'>, <TokenType.IPV6: 'IPV6'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, <TokenType.TINYINT: 'TINYINT'>, <TokenType.TINYBLOB: 'TINYBLOB'>}"}, "sqlglot.dialects.bigquery.BigQuery.Parser.SHOW_TRIE": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Parser.SHOW_TRIE", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Parser.SHOW_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.bigquery.BigQuery.Parser.SET_TRIE": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Parser.SET_TRIE", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Parser.SET_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'GLOBAL': {0: True}, 'LOCAL': {0: True}, 'SESSION': {0: True}, 'TRANSACTION': {0: True}}"}, "sqlglot.dialects.bigquery.BigQuery.Generator": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator", "kind": "class", "doc": "<p>Generator converts a given syntax tree to the corresponding SQL string.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>pretty:</strong> Whether to format the produced SQL string.\nDefault: False.</li>\n<li><strong>identify:</strong> Determines when an identifier should be quoted. Possible values are:\nFalse (default): Never quote, except in cases where it's mandatory by the dialect.\nTrue or 'always': Always quote.\n'safe': Only quote identifiers that are case insensitive.</li>\n<li><strong>normalize:</strong> Whether to normalize identifiers to lowercase.\nDefault: False.</li>\n<li><strong>pad:</strong> The pad size in a formatted string. For example, this affects the indentation of\na projection in a query, relative to its nesting level.\nDefault: 2.</li>\n<li><strong>indent:</strong> The indentation size in a formatted string. For example, this affects the\nindentation of subqueries and filters under a <code>WHERE</code> clause.\nDefault: 2.</li>\n<li><strong>normalize_functions:</strong> How to normalize function names. Possible values are:\n\"upper\" or True (default): Convert names to uppercase.\n\"lower\": Convert names to lowercase.\nFalse: Disables function name normalization.</li>\n<li><strong>unsupported_level:</strong> Determines the generator's behavior when it encounters unsupported expressions.\nDefault ErrorLevel.WARN.</li>\n<li><strong>max_unsupported:</strong> Maximum number of unsupported messages to include in a raised UnsupportedError.\nThis is only relevant if unsupported_level is ErrorLevel.RAISE.\nDefault: 3</li>\n<li><strong>leading_comma:</strong> Whether the comma is leading or trailing in select expressions.\nThis is only relevant when generating in pretty mode.\nDefault: False</li>\n<li><strong>max_text_width:</strong> The max number of characters in a segment before creating new lines in pretty mode.\nThe default is on the smaller end because the length only represents a segment and not the true\nline length.\nDefault: 80</li>\n<li><strong>comments:</strong> Whether to preserve comments in the output SQL code.\nDefault: True</li>\n</ul>\n", "bases": "sqlglot.generator.Generator"}, "sqlglot.dialects.bigquery.BigQuery.Generator.EXPLICIT_UNION": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.EXPLICIT_UNION", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.EXPLICIT_UNION", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.bigquery.BigQuery.Generator.INTERVAL_ALLOWS_PLURAL_FORM": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.INTERVAL_ALLOWS_PLURAL_FORM", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.INTERVAL_ALLOWS_PLURAL_FORM", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.bigquery.BigQuery.Generator.JOIN_HINTS": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.JOIN_HINTS", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.JOIN_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.bigquery.BigQuery.Generator.QUERY_HINTS": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.QUERY_HINTS", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.QUERY_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.bigquery.BigQuery.Generator.TABLE_HINTS": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.TABLE_HINTS", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.TABLE_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.bigquery.BigQuery.Generator.LIMIT_FETCH": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.LIMIT_FETCH", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.LIMIT_FETCH", "kind": "variable", "doc": "<p></p>\n", "default_value": "'LIMIT'"}, "sqlglot.dialects.bigquery.BigQuery.Generator.RENAME_TABLE_WITH_DB": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.RENAME_TABLE_WITH_DB", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.RENAME_TABLE_WITH_DB", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.bigquery.BigQuery.Generator.NVL2_SUPPORTED": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.NVL2_SUPPORTED", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.NVL2_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.bigquery.BigQuery.Generator.UNNEST_WITH_ORDINALITY": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.UNNEST_WITH_ORDINALITY", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.UNNEST_WITH_ORDINALITY", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.bigquery.BigQuery.Generator.COLLATE_IS_FUNC": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.COLLATE_IS_FUNC", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.COLLATE_IS_FUNC", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.bigquery.BigQuery.Generator.LIMIT_ONLY_LITERALS": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.LIMIT_ONLY_LITERALS", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.LIMIT_ONLY_LITERALS", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.bigquery.BigQuery.Generator.SUPPORTS_TABLE_ALIAS_COLUMNS": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.SUPPORTS_TABLE_ALIAS_COLUMNS", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.SUPPORTS_TABLE_ALIAS_COLUMNS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.bigquery.BigQuery.Generator.UNPIVOT_ALIASES_ARE_IDENTIFIERS": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.UNPIVOT_ALIASES_ARE_IDENTIFIERS", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.UNPIVOT_ALIASES_ARE_IDENTIFIERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.bigquery.BigQuery.Generator.JSON_KEY_VALUE_PAIR_SEP": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.JSON_KEY_VALUE_PAIR_SEP", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.JSON_KEY_VALUE_PAIR_SEP", "kind": "variable", "doc": "<p></p>\n", "default_value": "','"}, "sqlglot.dialects.bigquery.BigQuery.Generator.NULL_ORDERING_SUPPORTED": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.NULL_ORDERING_SUPPORTED", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.NULL_ORDERING_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.bigquery.BigQuery.Generator.IGNORE_NULLS_IN_FUNC": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.IGNORE_NULLS_IN_FUNC", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.IGNORE_NULLS_IN_FUNC", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.bigquery.BigQuery.Generator.JSON_PATH_SINGLE_QUOTE_ESCAPE": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.JSON_PATH_SINGLE_QUOTE_ESCAPE", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.JSON_PATH_SINGLE_QUOTE_ESCAPE", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.bigquery.BigQuery.Generator.CAN_IMPLEMENT_ARRAY_ANY": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.CAN_IMPLEMENT_ARRAY_ANY", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.CAN_IMPLEMENT_ARRAY_ANY", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.bigquery.BigQuery.Generator.SUPPORTS_TO_NUMBER": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.SUPPORTS_TO_NUMBER", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.SUPPORTS_TO_NUMBER", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.bigquery.BigQuery.Generator.NAMED_PLACEHOLDER_TOKEN": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.NAMED_PLACEHOLDER_TOKEN", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.NAMED_PLACEHOLDER_TOKEN", "kind": "variable", "doc": "<p></p>\n", "default_value": "'@'"}, "sqlglot.dialects.bigquery.BigQuery.Generator.HEX_FUNC": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.HEX_FUNC", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.HEX_FUNC", "kind": "variable", "doc": "<p></p>\n", "default_value": "'TO_HEX'"}, "sqlglot.dialects.bigquery.BigQuery.Generator.WITH_PROPERTIES_PREFIX": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.WITH_PROPERTIES_PREFIX", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.WITH_PROPERTIES_PREFIX", "kind": "variable", "doc": "<p></p>\n", "default_value": "'OPTIONS'"}, "sqlglot.dialects.bigquery.BigQuery.Generator.TRANSFORMS": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.TRANSFORMS", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.JSONPathKey'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRoot'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSubscript'>: <function <lambda>>, <class 'sqlglot.expressions.AllowedValuesProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.BackupProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CaseSpecificColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CollateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CommentColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DateFormatColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DefaultColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EncodeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EphemeralColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExcludeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <function Generator.<lambda>>, <class 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'sqlglot.expressions.AlgorithmProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.AutoIncrementProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.BackupProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.BlockCompressionProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.CharacterSetProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ChecksumProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.CollateProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Cluster'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ClusteredByProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 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"sqlglot.dialects.bigquery.BigQuery.Generator.column_parts", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.column_parts", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Column</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.bigquery.BigQuery.Generator.table_parts": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.table_parts", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.table_parts", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Table</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.bigquery.BigQuery.Generator.timetostr_sql": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.timetostr_sql", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.timetostr_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TimeToStr</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.bigquery.BigQuery.Generator.eq_sql": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.eq_sql", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.eq_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">EQ</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.bigquery.BigQuery.Generator.attimezone_sql": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.attimezone_sql", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.attimezone_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">AtTimeZone</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.bigquery.BigQuery.Generator.trycast_sql": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.trycast_sql", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.trycast_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TryCast</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.bigquery.BigQuery.Generator.bracket_sql": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.bracket_sql", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.bracket_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Bracket</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.bigquery.BigQuery.Generator.in_unnest_op": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.in_unnest_op", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.in_unnest_op", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Unnest</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.bigquery.BigQuery.Generator.except_op": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.except_op", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.except_op", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Except</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.bigquery.BigQuery.Generator.intersect_op": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.intersect_op", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.intersect_op", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Intersect</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.bigquery.BigQuery.Generator.version_sql": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.version_sql", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.version_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Version</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.bigquery.BigQuery.Generator.TRY_SUPPORTED": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.TRY_SUPPORTED", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.TRY_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.bigquery.BigQuery.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS": {"fullname": "sqlglot.dialects.bigquery.BigQuery.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'qualify': <function Generator.<lambda>>, 'windows': <function Generator.<lambda>>}"}, "sqlglot.dialects.bigquery.BigQuery.UNESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.bigquery.BigQuery.UNESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.UNESCAPED_SEQUENCES", "kind": "variable", "doc": "<p>Mapping of an escaped sequence (<code>\\n</code>) to its unescaped version (<code>\n</code>).</p>\n", "annotation": ": Dict[str, str]", "default_value": "{'\\\\a': '\\x07', '\\\\b': '\\x08', '\\\\f': '\\x0c', '\\\\n': '\\n', '\\\\r': '\\r', '\\\\t': '\\t', '\\\\v': '\\x0b', '\\\\\\\\': '\\\\'}"}, "sqlglot.dialects.bigquery.BigQuery.tokenizer_class": {"fullname": "sqlglot.dialects.bigquery.BigQuery.tokenizer_class", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.tokenizer_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.bigquery.BigQuery.Tokenizer'>"}, "sqlglot.dialects.bigquery.BigQuery.parser_class": {"fullname": "sqlglot.dialects.bigquery.BigQuery.parser_class", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.parser_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.bigquery.BigQuery.Parser'>"}, "sqlglot.dialects.bigquery.BigQuery.generator_class": {"fullname": "sqlglot.dialects.bigquery.BigQuery.generator_class", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.generator_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.bigquery.BigQuery.Generator'>"}, "sqlglot.dialects.bigquery.BigQuery.TIME_TRIE": {"fullname": "sqlglot.dialects.bigquery.BigQuery.TIME_TRIE", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'%': {'D': {0: True}, 'E': {'6': {'S': {0: True}}}}}"}, "sqlglot.dialects.bigquery.BigQuery.FORMAT_TRIE": {"fullname": "sqlglot.dialects.bigquery.BigQuery.FORMAT_TRIE", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.FORMAT_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'D': {'D': {0: True}}, 'M': {'M': {0: True}, 'O': {'N': {0: True, 'T': {'H': {0: True}}}}, 'I': {0: True}}, 'Y': {'Y': {'Y': {'Y': {0: True}}, 0: True}}, 'H': {'H': {0: True, '1': {'2': {0: True}}, '2': {'4': {0: True}}}}, 'S': {'S': {0: True, 'S': {'S': {'S': {0: True}}}}}, 'T': {'Z': {'H': {0: True}}}}"}, "sqlglot.dialects.bigquery.BigQuery.INVERSE_TIME_MAPPING": {"fullname": "sqlglot.dialects.bigquery.BigQuery.INVERSE_TIME_MAPPING", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.INVERSE_TIME_MAPPING", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'%m/%d/%y': '%D', '%S.%f': '%E6S'}"}, "sqlglot.dialects.bigquery.BigQuery.INVERSE_TIME_TRIE": {"fullname": "sqlglot.dialects.bigquery.BigQuery.INVERSE_TIME_TRIE", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.INVERSE_TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'%': {'m': {'/': {'%': {'d': {'/': {'%': {'y': {0: True}}}}}}}, 'S': {'.': {'%': {'f': {0: True}}}}}}"}, "sqlglot.dialects.bigquery.BigQuery.ESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.bigquery.BigQuery.ESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.ESCAPED_SEQUENCES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'\\x07': '\\\\a', '\\x08': '\\\\b', '\\x0c': '\\\\f', '\\n': '\\\\n', '\\r': '\\\\r', '\\t': '\\\\t', '\\x0b': '\\\\v', '\\\\': '\\\\\\\\'}"}, "sqlglot.dialects.bigquery.BigQuery.QUOTE_START": {"fullname": "sqlglot.dialects.bigquery.BigQuery.QUOTE_START", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.QUOTE_START", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.bigquery.BigQuery.QUOTE_END": {"fullname": "sqlglot.dialects.bigquery.BigQuery.QUOTE_END", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.QUOTE_END", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.bigquery.BigQuery.IDENTIFIER_START": {"fullname": "sqlglot.dialects.bigquery.BigQuery.IDENTIFIER_START", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.IDENTIFIER_START", "kind": "variable", "doc": "<p></p>\n", "default_value": "'`'"}, "sqlglot.dialects.bigquery.BigQuery.IDENTIFIER_END": {"fullname": "sqlglot.dialects.bigquery.BigQuery.IDENTIFIER_END", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.IDENTIFIER_END", "kind": "variable", "doc": "<p></p>\n", "default_value": "'`'"}, "sqlglot.dialects.bigquery.BigQuery.BIT_START": {"fullname": "sqlglot.dialects.bigquery.BigQuery.BIT_START", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.BIT_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.bigquery.BigQuery.BIT_END": {"fullname": "sqlglot.dialects.bigquery.BigQuery.BIT_END", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.BIT_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.bigquery.BigQuery.HEX_START": {"fullname": "sqlglot.dialects.bigquery.BigQuery.HEX_START", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.HEX_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "'0x'"}, "sqlglot.dialects.bigquery.BigQuery.HEX_END": {"fullname": "sqlglot.dialects.bigquery.BigQuery.HEX_END", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.HEX_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "''"}, "sqlglot.dialects.bigquery.BigQuery.BYTE_START": {"fullname": "sqlglot.dialects.bigquery.BigQuery.BYTE_START", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.BYTE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""b'""}, "sqlglot.dialects.bigquery.BigQuery.BYTE_END": {"fullname": "sqlglot.dialects.bigquery.BigQuery.BYTE_END", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.BYTE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""'""}, "sqlglot.dialects.bigquery.BigQuery.UNICODE_START": {"fullname": "sqlglot.dialects.bigquery.BigQuery.UNICODE_START", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.UNICODE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.bigquery.BigQuery.UNICODE_END": {"fullname": "sqlglot.dialects.bigquery.BigQuery.UNICODE_END", "modulename": "sqlglot.dialects.bigquery", "qualname": "BigQuery.UNICODE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.clickhouse": {"fullname": "sqlglot.dialects.clickhouse", "modulename": "sqlglot.dialects.clickhouse", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.dialects.clickhouse.ClickHouse": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.dialect.Dialect"}, "sqlglot.dialects.clickhouse.ClickHouse.NORMALIZE_FUNCTIONS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.NORMALIZE_FUNCTIONS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.NORMALIZE_FUNCTIONS", "kind": "variable", "doc": "<p>Determines how function names are going to be normalized.</p>\n\n<h6 id=\"possible-values\">Possible values:</h6>\n\n<blockquote>\n <p>\"upper\" or True: Convert names to uppercase.\n \"lower\": Convert names to lowercase.\n False: Disables function name normalization.</p>\n</blockquote>\n", "annotation": ": bool | str", "default_value": "False"}, "sqlglot.dialects.clickhouse.ClickHouse.NULL_ORDERING": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.NULL_ORDERING", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.NULL_ORDERING", "kind": "variable", "doc": "<p>Default <code>NULL</code> ordering method to use if not explicitly set.\nPossible values: <code>\"nulls_are_small\"</code>, <code>\"nulls_are_large\"</code>, <code>\"nulls_are_last\"</code></p>\n", "default_value": "'nulls_are_last'"}, "sqlglot.dialects.clickhouse.ClickHouse.SUPPORTS_USER_DEFINED_TYPES": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.SUPPORTS_USER_DEFINED_TYPES", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.SUPPORTS_USER_DEFINED_TYPES", "kind": "variable", "doc": "<p>Whether user-defined data types are supported.</p>\n", "default_value": "False"}, "sqlglot.dialects.clickhouse.ClickHouse.SAFE_DIVISION": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.SAFE_DIVISION", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.SAFE_DIVISION", "kind": "variable", "doc": "<p>Whether division by zero throws an error (<code>False</code>) or returns NULL (<code>True</code>).</p>\n", "default_value": "True"}, "sqlglot.dialects.clickhouse.ClickHouse.LOG_BASE_FIRST": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.LOG_BASE_FIRST", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.LOG_BASE_FIRST", "kind": "variable", "doc": "<p>Whether the base comes first in the <code>LOG</code> function.\nPossible values: <code>True</code>, <code>False</code>, <code>None</code> (two arguments are not supported by <code>LOG</code>)</p>\n", "annotation": ": Optional[bool]", "default_value": "None"}, "sqlglot.dialects.clickhouse.ClickHouse.UNESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.UNESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.UNESCAPED_SEQUENCES", "kind": "variable", "doc": "<p>Mapping of an escaped sequence (<code>\\n</code>) to its unescaped version (<code>\n</code>).</p>\n", "default_value": "{'\\\\a': '\\x07', '\\\\b': '\\x08', '\\\\f': '\\x0c', '\\\\n': '\\n', '\\\\r': '\\r', '\\\\t': '\\t', '\\\\v': '\\x0b', '\\\\\\\\': '\\\\', '\\\\0': '\\x00'}"}, "sqlglot.dialects.clickhouse.ClickHouse.Tokenizer": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Tokenizer", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Tokenizer", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.tokens.Tokenizer"}, "sqlglot.dialects.clickhouse.ClickHouse.Tokenizer.COMMENTS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Tokenizer.COMMENTS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Tokenizer.COMMENTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "['--', '#', '#!', ('/*', '*/')]"}, "sqlglot.dialects.clickhouse.ClickHouse.Tokenizer.IDENTIFIERS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Tokenizer.IDENTIFIERS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Tokenizer.IDENTIFIERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "['"', '`']"}, "sqlglot.dialects.clickhouse.ClickHouse.Tokenizer.STRING_ESCAPES": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Tokenizer.STRING_ESCAPES", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Tokenizer.STRING_ESCAPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "["'", '\\\\']"}, "sqlglot.dialects.clickhouse.ClickHouse.Tokenizer.BIT_STRINGS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Tokenizer.BIT_STRINGS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Tokenizer.BIT_STRINGS", "kind": "variable", "doc": "<p></p>\n", "default_value": "[('0b', '')]"}, "sqlglot.dialects.clickhouse.ClickHouse.Tokenizer.HEX_STRINGS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Tokenizer.HEX_STRINGS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Tokenizer.HEX_STRINGS", "kind": "variable", "doc": "<p></p>\n", "default_value": "[('0x', ''), ('0X', '')]"}, "sqlglot.dialects.clickhouse.ClickHouse.Tokenizer.HEREDOC_STRINGS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Tokenizer.HEREDOC_STRINGS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Tokenizer.HEREDOC_STRINGS", "kind": "variable", "doc": "<p></p>\n", "default_value": "['$']"}, "sqlglot.dialects.clickhouse.ClickHouse.Tokenizer.KEYWORDS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Tokenizer.KEYWORDS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Tokenizer.KEYWORDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'{%': <TokenType.BLOCK_START: 'BLOCK_START'>, '{%+': <TokenType.BLOCK_START: 'BLOCK_START'>, '{%-': <TokenType.BLOCK_START: 'BLOCK_START'>, '%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '+%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '-%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '{{+': <TokenType.BLOCK_START: 'BLOCK_START'>, '{{-': <TokenType.BLOCK_START: 'BLOCK_START'>, '+}}': <TokenType.BLOCK_END: 'BLOCK_END'>, '-}}': <TokenType.BLOCK_END: 'BLOCK_END'>, '/*+': <TokenType.HINT: 'HINT'>, '==': <TokenType.EQ: 'EQ'>, '::': <TokenType.DCOLON: 'DCOLON'>, '||': <TokenType.DPIPE: 'DPIPE'>, '>=': <TokenType.GTE: 'GTE'>, '<=': <TokenType.LTE: 'LTE'>, '<>': <TokenType.NEQ: 'NEQ'>, '!=': <TokenType.NEQ: 'NEQ'>, ':=': <TokenType.COLON_EQ: 'COLON_EQ'>, '<=>': <TokenType.NULLSAFE_EQ: 'NULLSAFE_EQ'>, '->': <TokenType.ARROW: 'ARROW'>, '->>': <TokenType.DARROW: 'DARROW'>, '=>': <TokenType.FARROW: 'FARROW'>, '#>': <TokenType.HASH_ARROW: 'HASH_ARROW'>, '#>>': <TokenType.DHASH_ARROW: 'DHASH_ARROW'>, '<->': <TokenType.LR_ARROW: 'LR_ARROW'>, '&&': <TokenType.DAMP: 'DAMP'>, '??': <TokenType.DQMARK: 'DQMARK'>, 'ALL': <TokenType.ALL: 'ALL'>, 'ALWAYS': <TokenType.ALWAYS: 'ALWAYS'>, 'AND': <TokenType.AND: 'AND'>, 'ANTI': <TokenType.ANTI: 'ANTI'>, 'ANY': <TokenType.ANY: 'ANY'>, 'ASC': <TokenType.ASC: 'ASC'>, 'AS': <TokenType.ALIAS: 'ALIAS'>, 'ASOF': <TokenType.ASOF: 'ASOF'>, 'AUTOINCREMENT': <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, 'AUTO_INCREMENT': <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, 'BEGIN': <TokenType.BEGIN: 'BEGIN'>, 'BETWEEN': <TokenType.BETWEEN: 'BETWEEN'>, 'CACHE': <TokenType.CACHE: 'CACHE'>, 'UNCACHE': <TokenType.UNCACHE: 'UNCACHE'>, 'CASE': <TokenType.CASE: 'CASE'>, 'CHARACTER SET': <TokenType.CHARACTER_SET: 'CHARACTER_SET'>, 'CLUSTER BY': <TokenType.CLUSTER_BY: 'CLUSTER_BY'>, 'COLLATE': <TokenType.COLLATE: 'COLLATE'>, 'COLUMN': <TokenType.COLUMN: 'COLUMN'>, 'COMMIT': <TokenType.COMMIT: 'COMMIT'>, 'CONNECT BY': <TokenType.CONNECT_BY: 'CONNECT_BY'>, 'CONSTRAINT': <TokenType.CONSTRAINT: 'CONSTRAINT'>, 'COPY': <TokenType.COPY: 'COPY'>, 'CREATE': <TokenType.CREATE: 'CREATE'>, 'CROSS': <TokenType.CROSS: 'CROSS'>, 'CUBE': <TokenType.CUBE: 'CUBE'>, 'CURRENT_DATE': <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, 'CURRENT_TIME': <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, 'CURRENT_TIMESTAMP': <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, 'CURRENT_USER': <TokenType.CURRENT_USER: 'CURRENT_USER'>, 'DATABASE': <TokenType.DATABASE: 'DATABASE'>, 'DEFAULT': <TokenType.DEFAULT: 'DEFAULT'>, 'DELETE': <TokenType.DELETE: 'DELETE'>, 'DESC': <TokenType.DESC: 'DESC'>, 'DESCRIBE': <TokenType.DESCRIBE: 'DESCRIBE'>, 'DISTINCT': <TokenType.DISTINCT: 'DISTINCT'>, 'DISTRIBUTE BY': <TokenType.DISTRIBUTE_BY: 'DISTRIBUTE_BY'>, 'DIV': <TokenType.DIV: 'DIV'>, 'DROP': <TokenType.DROP: 'DROP'>, 'ELSE': <TokenType.ELSE: 'ELSE'>, 'END': <TokenType.END: 'END'>, 'ENUM': <TokenType.ENUM: 'ENUM'>, 'ESCAPE': <TokenType.ESCAPE: 'ESCAPE'>, 'EXCEPT': <TokenType.EXCEPT: 'EXCEPT'>, 'EXECUTE': <TokenType.EXECUTE: 'EXECUTE'>, 'EXISTS': <TokenType.EXISTS: 'EXISTS'>, 'FALSE': <TokenType.FALSE: 'FALSE'>, 'FETCH': <TokenType.FETCH: 'FETCH'>, 'FILTER': <TokenType.FILTER: 'FILTER'>, 'FIRST': <TokenType.FIRST: 'FIRST'>, 'FULL': <TokenType.FULL: 'FULL'>, 'FUNCTION': <TokenType.FUNCTION: 'FUNCTION'>, 'FOR': <TokenType.FOR: 'FOR'>, 'FOREIGN KEY': <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, 'FORMAT': <TokenType.FORMAT: 'FORMAT'>, 'FROM': <TokenType.FROM: 'FROM'>, 'GEOGRAPHY': <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, 'GEOMETRY': <TokenType.GEOMETRY: 'GEOMETRY'>, 'GLOB': <TokenType.GLOB: 'GLOB'>, 'GROUP BY': <TokenType.GROUP_BY: 'GROUP_BY'>, 'GROUPING SETS': <TokenType.GROUPING_SETS: 'GROUPING_SETS'>, 'HAVING': <TokenType.HAVING: 'HAVING'>, 'ILIKE': <TokenType.ILIKE: 'ILIKE'>, 'IN': <TokenType.IN: 'IN'>, 'INDEX': <TokenType.INDEX: 'INDEX'>, 'INET': <TokenType.INET: 'INET'>, 'INNER': <TokenType.INNER: 'INNER'>, 'INSERT': <TokenType.INSERT: 'INSERT'>, 'INTERVAL': <TokenType.INTERVAL: 'INTERVAL'>, 'INTERSECT': <TokenType.INTERSECT: 'INTERSECT'>, 'INTO': <TokenType.INTO: 'INTO'>, 'IS': <TokenType.IS: 'IS'>, 'ISNULL': <TokenType.ISNULL: 'ISNULL'>, 'JOIN': <TokenType.JOIN: 'JOIN'>, 'KEEP': <TokenType.KEEP: 'KEEP'>, 'KILL': <TokenType.KILL: 'KILL'>, 'LATERAL': <TokenType.LATERAL: 'LATERAL'>, 'LEFT': <TokenType.LEFT: 'LEFT'>, 'LIKE': <TokenType.LIKE: 'LIKE'>, 'LIMIT': <TokenType.LIMIT: 'LIMIT'>, 'LOAD': <TokenType.LOAD: 'LOAD'>, 'LOCK': <TokenType.LOCK: 'LOCK'>, 'MERGE': <TokenType.MERGE: 'MERGE'>, 'NATURAL': <TokenType.NATURAL: 'NATURAL'>, 'NEXT': <TokenType.NEXT: 'NEXT'>, 'NOT': <TokenType.NOT: 'NOT'>, 'NOTNULL': <TokenType.NOTNULL: 'NOTNULL'>, 'NULL': <TokenType.NULL: 'NULL'>, 'OBJECT': <TokenType.OBJECT: 'OBJECT'>, 'OFFSET': <TokenType.OFFSET: 'OFFSET'>, 'ON': <TokenType.ON: 'ON'>, 'OR': <TokenType.OR: 'OR'>, 'XOR': <TokenType.XOR: 'XOR'>, 'ORDER BY': <TokenType.ORDER_BY: 'ORDER_BY'>, 'ORDINALITY': <TokenType.ORDINALITY: 'ORDINALITY'>, 'OUTER': <TokenType.OUTER: 'OUTER'>, 'OVER': <TokenType.OVER: 'OVER'>, 'OVERLAPS': <TokenType.OVERLAPS: 'OVERLAPS'>, 'OVERWRITE': <TokenType.OVERWRITE: 'OVERWRITE'>, 'PARTITION': <TokenType.PARTITION: 'PARTITION'>, 'PARTITION BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PARTITIONED BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PARTITIONED_BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PERCENT': <TokenType.PERCENT: 'PERCENT'>, 'PIVOT': <TokenType.PIVOT: 'PIVOT'>, 'PRAGMA': <TokenType.PRAGMA: 'PRAGMA'>, 'PRIMARY KEY': <TokenType.PRIMARY_KEY: 'PRIMARY_KEY'>, 'PROCEDURE': <TokenType.PROCEDURE: 'PROCEDURE'>, 'QUALIFY': <TokenType.QUALIFY: 'QUALIFY'>, 'RANGE': <TokenType.RANGE: 'RANGE'>, 'RECURSIVE': <TokenType.RECURSIVE: 'RECURSIVE'>, 'REGEXP': <TokenType.RLIKE: 'RLIKE'>, 'REPLACE': <TokenType.REPLACE: 'REPLACE'>, 'RETURNING': <TokenType.RETURNING: 'RETURNING'>, 'REFERENCES': <TokenType.REFERENCES: 'REFERENCES'>, 'RIGHT': <TokenType.RIGHT: 'RIGHT'>, 'RLIKE': <TokenType.RLIKE: 'RLIKE'>, 'ROLLBACK': <TokenType.ROLLBACK: 'ROLLBACK'>, 'ROLLUP': <TokenType.ROLLUP: 'ROLLUP'>, 'ROW': <TokenType.ROW: 'ROW'>, 'ROWS': <TokenType.ROWS: 'ROWS'>, 'SCHEMA': <TokenType.SCHEMA: 'SCHEMA'>, 'SELECT': <TokenType.SELECT: 'SELECT'>, 'SEMI': <TokenType.SEMI: 'SEMI'>, 'SET': <TokenType.SET: 'SET'>, 'SETTINGS': <TokenType.SETTINGS: 'SETTINGS'>, 'SHOW': <TokenType.SHOW: 'SHOW'>, 'SIMILAR TO': <TokenType.SIMILAR_TO: 'SIMILAR_TO'>, 'SOME': <TokenType.SOME: 'SOME'>, 'SORT BY': <TokenType.SORT_BY: 'SORT_BY'>, 'START WITH': <TokenType.START_WITH: 'START_WITH'>, 'TABLE': <TokenType.TABLE: 'TABLE'>, 'TABLESAMPLE': <TokenType.TABLE_SAMPLE: 'TABLE_SAMPLE'>, 'TEMP': <TokenType.TEMPORARY: 'TEMPORARY'>, 'TEMPORARY': <TokenType.TEMPORARY: 'TEMPORARY'>, 'THEN': <TokenType.THEN: 'THEN'>, 'TRUE': <TokenType.TRUE: 'TRUE'>, 'TRUNCATE': <TokenType.TRUNCATE: 'TRUNCATE'>, 'UNION': <TokenType.UNION: 'UNION'>, 'UNKNOWN': <TokenType.UNKNOWN: 'UNKNOWN'>, 'UNNEST': <TokenType.UNNEST: 'UNNEST'>, 'UNPIVOT': <TokenType.UNPIVOT: 'UNPIVOT'>, 'UPDATE': <TokenType.UPDATE: 'UPDATE'>, 'USE': <TokenType.USE: 'USE'>, 'USING': <TokenType.USING: 'USING'>, 'UUID': <TokenType.UUID: 'UUID'>, 'VALUES': <TokenType.VALUES: 'VALUES'>, 'VIEW': <TokenType.VIEW: 'VIEW'>, 'VOLATILE': <TokenType.VOLATILE: 'VOLATILE'>, 'WHEN': <TokenType.WHEN: 'WHEN'>, 'WHERE': <TokenType.WHERE: 'WHERE'>, 'WINDOW': <TokenType.WINDOW: 'WINDOW'>, 'WITH': <TokenType.WITH: 'WITH'>, 'APPLY': <TokenType.APPLY: 'APPLY'>, 'ARRAY': <TokenType.ARRAY: 'ARRAY'>, 'BIT': <TokenType.BIT: 'BIT'>, 'BOOL': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BOOLEAN': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BYTE': <TokenType.TINYINT: 'TINYINT'>, 'MEDIUMINT': <TokenType.MEDIUMINT: 'MEDIUMINT'>, 'INT1': <TokenType.TINYINT: 'TINYINT'>, 'TINYINT': <TokenType.TINYINT: 'TINYINT'>, 'INT16': <TokenType.SMALLINT: 'SMALLINT'>, 'SHORT': <TokenType.SMALLINT: 'SMALLINT'>, 'SMALLINT': <TokenType.SMALLINT: 'SMALLINT'>, 'INT128': <TokenType.INT128: 'INT128'>, 'HUGEINT': <TokenType.INT128: 'INT128'>, 'INT2': <TokenType.SMALLINT: 'SMALLINT'>, 'INTEGER': <TokenType.INT: 'INT'>, 'INT': <TokenType.INT: 'INT'>, 'INT4': <TokenType.INT: 'INT'>, 'INT32': <TokenType.INT: 'INT'>, 'INT64': <TokenType.BIGINT: 'BIGINT'>, 'LONG': <TokenType.BIGINT: 'BIGINT'>, 'BIGINT': <TokenType.BIGINT: 'BIGINT'>, 'INT8': <TokenType.TINYINT: 'TINYINT'>, 'UINT': <TokenType.UINT: 'UINT'>, 'DEC': <TokenType.DECIMAL: 'DECIMAL'>, 'DECIMAL': <TokenType.DECIMAL: 'DECIMAL'>, 'BIGDECIMAL': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'BIGNUMERIC': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'MAP': <TokenType.MAP: 'MAP'>, 'NULLABLE': <TokenType.NULLABLE: 'NULLABLE'>, 'NUMBER': <TokenType.DECIMAL: 'DECIMAL'>, 'NUMERIC': <TokenType.DECIMAL: 'DECIMAL'>, 'FIXED': <TokenType.DECIMAL: 'DECIMAL'>, 'REAL': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT4': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT8': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE PRECISION': <TokenType.DOUBLE: 'DOUBLE'>, 'JSON': <TokenType.JSON: 'JSON'>, 'CHAR': <TokenType.CHAR: 'CHAR'>, 'CHARACTER': <TokenType.CHAR: 'CHAR'>, 'NCHAR': <TokenType.NCHAR: 'NCHAR'>, 'VARCHAR': <TokenType.VARCHAR: 'VARCHAR'>, 'VARCHAR2': <TokenType.VARCHAR: 'VARCHAR'>, 'NVARCHAR': <TokenType.NVARCHAR: 'NVARCHAR'>, 'NVARCHAR2': <TokenType.NVARCHAR: 'NVARCHAR'>, 'BPCHAR': <TokenType.BPCHAR: 'BPCHAR'>, 'STR': <TokenType.TEXT: 'TEXT'>, 'STRING': <TokenType.TEXT: 'TEXT'>, 'TEXT': <TokenType.TEXT: 'TEXT'>, 'LONGTEXT': <TokenType.LONGTEXT: 'LONGTEXT'>, 'MEDIUMTEXT': <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, 'TINYTEXT': <TokenType.TINYTEXT: 'TINYTEXT'>, 'CLOB': <TokenType.TEXT: 'TEXT'>, 'LONGVARCHAR': <TokenType.TEXT: 'TEXT'>, 'BINARY': <TokenType.BINARY: 'BINARY'>, 'BLOB': <TokenType.VARBINARY: 'VARBINARY'>, 'LONGBLOB': <TokenType.LONGBLOB: 'LONGBLOB'>, 'MEDIUMBLOB': <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, 'TINYBLOB': <TokenType.TINYBLOB: 'TINYBLOB'>, 'BYTEA': <TokenType.VARBINARY: 'VARBINARY'>, 'VARBINARY': <TokenType.VARBINARY: 'VARBINARY'>, 'TIME': <TokenType.TIME: 'TIME'>, 'TIMETZ': <TokenType.TIMETZ: 'TIMETZ'>, 'TIMESTAMP': <TokenType.TIMESTAMP: 'TIMESTAMP'>, 'TIMESTAMPTZ': <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, 'TIMESTAMPLTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMP_LTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMPNTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'TIMESTAMP_NTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'DATE': <TokenType.DATE: 'DATE'>, 'DATETIME': <TokenType.DATETIME: 'DATETIME'>, 'INT4RANGE': <TokenType.INT4RANGE: 'INT4RANGE'>, 'INT4MULTIRANGE': <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, 'INT8RANGE': <TokenType.INT8RANGE: 'INT8RANGE'>, 'INT8MULTIRANGE': <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, 'NUMRANGE': <TokenType.NUMRANGE: 'NUMRANGE'>, 'NUMMULTIRANGE': <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, 'TSRANGE': <TokenType.TSRANGE: 'TSRANGE'>, 'TSMULTIRANGE': <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, 'TSTZRANGE': <TokenType.TSTZRANGE: 'TSTZRANGE'>, 'TSTZMULTIRANGE': <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, 'DATERANGE': <TokenType.DATERANGE: 'DATERANGE'>, 'DATEMULTIRANGE': <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, 'UNIQUE': <TokenType.UNIQUE: 'UNIQUE'>, 'STRUCT': <TokenType.STRUCT: 'STRUCT'>, 'SEQUENCE': <TokenType.SEQUENCE: 'SEQUENCE'>, 'VARIANT': <TokenType.VARIANT: 'VARIANT'>, 'ALTER': <TokenType.ALTER: 'ALTER'>, 'ANALYZE': <TokenType.COMMAND: 'COMMAND'>, 'CALL': <TokenType.COMMAND: 'COMMAND'>, 'COMMENT': <TokenType.COMMENT: 'COMMENT'>, 'EXPLAIN': <TokenType.COMMAND: 'COMMAND'>, 'GRANT': <TokenType.COMMAND: 'COMMAND'>, 'OPTIMIZE': <TokenType.COMMAND: 'COMMAND'>, 'PREPARE': <TokenType.COMMAND: 'COMMAND'>, 'VACUUM': <TokenType.COMMAND: 'COMMAND'>, 'USER-DEFINED': <TokenType.USERDEFINED: 'USERDEFINED'>, 'FOR VERSION': <TokenType.VERSION_SNAPSHOT: 'VERSION_SNAPSHOT'>, 'FOR TIMESTAMP': <TokenType.TIMESTAMP_SNAPSHOT: 'TIMESTAMP_SNAPSHOT'>, 'ATTACH': <TokenType.COMMAND: 'COMMAND'>, 'DATE32': <TokenType.DATE32: 'DATE32'>, 'DATETIME64': <TokenType.DATETIME64: 'DATETIME64'>, 'DICTIONARY': <TokenType.DICTIONARY: 'DICTIONARY'>, 'ENUM8': <TokenType.ENUM8: 'ENUM8'>, 'ENUM16': <TokenType.ENUM16: 'ENUM16'>, 'FINAL': <TokenType.FINAL: 'FINAL'>, 'FIXEDSTRING': <TokenType.FIXEDSTRING: 'FIXEDSTRING'>, 'FLOAT32': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT64': <TokenType.DOUBLE: 'DOUBLE'>, 'GLOBAL': <TokenType.GLOBAL: 'GLOBAL'>, 'INT256': <TokenType.INT256: 'INT256'>, 'LOWCARDINALITY': <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, 'NESTED': <TokenType.NESTED: 'NESTED'>, 'SAMPLE': <TokenType.TABLE_SAMPLE: 'TABLE_SAMPLE'>, 'TUPLE': <TokenType.STRUCT: 'STRUCT'>, 'UINT128': <TokenType.UINT128: 'UINT128'>, 'UINT16': <TokenType.USMALLINT: 'USMALLINT'>, 'UINT256': <TokenType.UINT256: 'UINT256'>, 'UINT32': <TokenType.UINT: 'UINT'>, 'UINT64': <TokenType.UBIGINT: 'UBIGINT'>, 'UINT8': <TokenType.UTINYINT: 'UTINYINT'>, 'IPV4': <TokenType.IPV4: 'IPV4'>, 'IPV6': <TokenType.IPV6: 'IPV6'>, 'AGGREGATEFUNCTION': <TokenType.AGGREGATEFUNCTION: 'AGGREGATEFUNCTION'>, 'SIMPLEAGGREGATEFUNCTION': <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>, 'SYSTEM': <TokenType.COMMAND: 'COMMAND'>, 'PREWHERE': <TokenType.PREWHERE: 'PREWHERE'>}"}, "sqlglot.dialects.clickhouse.ClickHouse.Tokenizer.SINGLE_TOKENS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Tokenizer.SINGLE_TOKENS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Tokenizer.SINGLE_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'(': <TokenType.L_PAREN: 'L_PAREN'>, ')': <TokenType.R_PAREN: 'R_PAREN'>, '[': <TokenType.L_BRACKET: 'L_BRACKET'>, ']': <TokenType.R_BRACKET: 'R_BRACKET'>, '{': <TokenType.L_BRACE: 'L_BRACE'>, '}': <TokenType.R_BRACE: 'R_BRACE'>, '&': <TokenType.AMP: 'AMP'>, '^': <TokenType.CARET: 'CARET'>, ':': <TokenType.COLON: 'COLON'>, ',': <TokenType.COMMA: 'COMMA'>, '.': <TokenType.DOT: 'DOT'>, '-': <TokenType.DASH: 'DASH'>, '=': <TokenType.EQ: 'EQ'>, '>': <TokenType.GT: 'GT'>, '<': <TokenType.LT: 'LT'>, '%': <TokenType.MOD: 'MOD'>, '!': <TokenType.NOT: 'NOT'>, '|': <TokenType.PIPE: 'PIPE'>, '+': <TokenType.PLUS: 'PLUS'>, ';': <TokenType.SEMICOLON: 'SEMICOLON'>, '/': <TokenType.SLASH: 'SLASH'>, '\\\\': <TokenType.BACKSLASH: 'BACKSLASH'>, '*': <TokenType.STAR: 'STAR'>, '~': <TokenType.TILDA: 'TILDA'>, '?': <TokenType.PLACEHOLDER: 'PLACEHOLDER'>, '@': <TokenType.PARAMETER: 'PARAMETER'>, '#': <TokenType.HASH: 'HASH'>, "'": <TokenType.UNKNOWN: 'UNKNOWN'>, '`': <TokenType.UNKNOWN: 'UNKNOWN'>, '"': <TokenType.UNKNOWN: 'UNKNOWN'>, '$': <TokenType.HEREDOC_STRING: 'HEREDOC_STRING'>}"}, "sqlglot.dialects.clickhouse.ClickHouse.Parser": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Parser", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Parser", "kind": "class", "doc": "<p>Parser consumes a list of tokens produced by the Tokenizer and produces a parsed syntax tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>error_level:</strong> The desired error level.\nDefault: ErrorLevel.IMMEDIATE</li>\n<li><strong>error_message_context:</strong> The amount of context to capture from a query string when displaying\nthe error message (in number of characters).\nDefault: 100</li>\n<li><strong>max_errors:</strong> Maximum number of error messages to include in a raised ParseError.\nThis is only relevant if error_level is ErrorLevel.RAISE.\nDefault: 3</li>\n</ul>\n", "bases": "sqlglot.parser.Parser"}, "sqlglot.dialects.clickhouse.ClickHouse.Parser.MODIFIERS_ATTACHED_TO_UNION": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Parser.MODIFIERS_ATTACHED_TO_UNION", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Parser.MODIFIERS_ATTACHED_TO_UNION", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.clickhouse.ClickHouse.Parser.INTERVAL_SPANS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Parser.INTERVAL_SPANS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Parser.INTERVAL_SPANS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.clickhouse.ClickHouse.Parser.FUNCTIONS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Parser.FUNCTIONS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Parser.FUNCTIONS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ABS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Abs'>>, 'ADD_MONTHS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AddMonths'>>, 'ANONYMOUS_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnonymousAggFunc'>>, 'ANY_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnyValue'>>, 'APPROX_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_COUNT_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'APPROX_TOP_K': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxTopK'>>, 'ARG_MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARGMAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'MAX_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARG_MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARGMIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'MIN_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Array'>>, 'ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAgg'>>, 'ARRAY_ALL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAll'>>, 'ARRAY_ANY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAny'>>, 'ARRAY_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CONSTRUCT_COMPACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConstructCompact'>>, 'ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayContains'>>, 'FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_OVERLAPS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayOverlaps'>>, 'ARRAY_SIZE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_SORT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySort'>>, 'ARRAY_SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySum'>>, 'ARRAY_TO_STRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_JOIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_UNION_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUnionAgg'>>, 'ARRAY_UNIQUE_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUniqueAgg'>>, 'AVG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Avg'>>, 'CASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Case'>>, 'CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cast'>>, 'CAST_TO_STR_TYPE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CastToStrType'>>, 'CBRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cbrt'>>, 'CEIL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CEILING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CHR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'COALESCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'IFNULL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'NVL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'COLLATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Collate'>>, 'COMBINED_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedAggFunc'>>, 'COMBINED_PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedParameterizedAgg'>>, 'CONCAT': <function Parser.<lambda>>, 'CONCAT_WS': <function Parser.<lambda>>, 'CONNECT_BY_ROOT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ConnectByRoot'>>, 'CONVERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Convert'>>, 'CORR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Corr'>>, 'COUNT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Count'>>, 'COUNT_IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COUNTIF': <function _build_count_if>, 'COVAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarPop'>>, 'COVAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarSamp'>>, 'CURRENT_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDate'>>, 'CURRENT_DATETIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDatetime'>>, 'CURRENT_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTime'>>, 'CURRENT_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTimestamp'>>, 'CURRENT_USER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentUser'>>, 'DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Date'>>, 'DATE_ADD': <function ClickHouse.Parser.<lambda>>, 'DATEDIFF': <function ClickHouse.Parser.<lambda>>, 'DATE_DIFF': <function ClickHouse.Parser.<lambda>>, 'DATE_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATE_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateStrToDate'>>, 'DATE_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateSub'>>, 'DATE_TO_DATE_STR': <function Parser.<lambda>>, 'DATE_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateToDi'>>, 'DATE_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateTrunc'>>, 'DATETIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeAdd'>>, 'DATETIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeDiff'>>, 'DATETIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeSub'>>, 'DATETIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeTrunc'>>, 'DAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Day'>>, 'DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAYOFMONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAY_OF_WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAYOFWEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAY_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DAYOFYEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DECODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Decode'>>, 'DI_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DiToDate'>>, 'ENCODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Encode'>>, 'EXP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Exp'>>, 'EXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Explode'>>, 'EXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ExplodeOuter'>>, 'EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Extract'>>, 'FIRST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.First'>>, 'FIRST_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FirstValue'>>, 'FLATTEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Flatten'>>, 'FLOOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Floor'>>, 'FROM_BASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase'>>, 'FROM_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase64'>>, 'GENERATE_DATE_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GenerateDateArray'>>, 'GENERATE_SERIES': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GenerateSeries'>>, 'GREATEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Greatest'>>, 'GROUP_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GroupConcat'>>, 'HEX': <function build_hex>, 'HLL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Hll'>>, 'IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'IIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'INITCAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Initcap'>>, 'IS_INF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'ISINF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'IS_NAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'ISNAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'J_S_O_N_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArray'>>, 'J_S_O_N_ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArrayAgg'>>, 'JSON_ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArrayContains'>>, 'JSONB_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONBExtract'>>, 'JSONB_EXTRACT_SCALAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONBExtractScalar'>>, 'JSON_EXTRACT': <function build_extract_json_with_path.<locals>._builder>, 'JSON_EXTRACT_SCALAR': <function build_extract_json_with_path.<locals>._builder>, 'JSON_FORMAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONFormat'>>, 'J_S_O_N_OBJECT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONObject'>>, 'J_S_O_N_OBJECT_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONObjectAgg'>>, 'J_S_O_N_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONTable'>>, 'LAG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lag'>>, 'LAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Last'>>, 'LAST_DAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastDay'>>, 'LAST_DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastDay'>>, 'LAST_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastValue'>>, 'LEAD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lead'>>, 'LEAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Least'>>, 'LEFT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Left'>>, 'LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Length'>>, 'LEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Length'>>, 'LEVENSHTEIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Levenshtein'>>, 'LN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ln'>>, 'LOG': <function build_logarithm>, 'LOGICAL_AND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'BOOL_AND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'BOOLAND_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'LOGICAL_OR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'BOOL_OR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'BOOLOR_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'LOWER': <function build_lower>, 'LCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lower'>>, 'LOWER_HEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LowerHex'>>, 'MD5': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MD5Digest'>>, 'MD5_DIGEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MD5Digest'>>, 'MAP': <function build_var_map>, 'MAP_FROM_ENTRIES': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MapFromEntries'>>, 'MATCH_AGAINST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MatchAgainst'>>, 'MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Max'>>, 'MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Min'>>, 'MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Month'>>, 'MONTHS_BETWEEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MonthsBetween'>>, 'NEXT_VALUE_FOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NextValueFor'>>, 'NTH_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NthValue'>>, 'NULLIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Nullif'>>, 'NUMBER_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NumberToStr'>>, 'NVL2': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Nvl2'>>, 'OPEN_J_S_O_N': <bound method Func.from_arg_list of <class 'sqlglot.expressions.OpenJSON'>>, 'PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParameterizedAgg'>>, 'PARSE_JSON': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParseJSON'>>, 'JSON_PARSE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParseJSON'>>, 'PERCENTILE_CONT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PercentileCont'>>, 'PERCENTILE_DISC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PercentileDisc'>>, 'POSEXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Posexplode'>>, 'POSEXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PosexplodeOuter'>>, 'POWER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Pow'>>, 'POW': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Pow'>>, 'PREDICT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Predict'>>, 'QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quantile'>>, 'QUARTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quarter'>>, 'RAND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'RANDOM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'RANDN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Randn'>>, 'RANGE_N': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RangeN'>>, 'READ_CSV': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ReadCSV'>>, 'REDUCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Reduce'>>, 'REGEXP_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpExtract'>>, 'REGEXP_I_LIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpILike'>>, 'REGEXP_LIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpLike'>>, 'REGEXP_REPLACE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpReplace'>>, 'REGEXP_SPLIT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpSplit'>>, 'REPEAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Repeat'>>, 'RIGHT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Right'>>, 'ROUND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Round'>>, 'ROW_NUMBER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RowNumber'>>, 'SHA': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA'>>, 'SHA1': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA'>>, 'SHA2': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA2'>>, 'SAFE_DIVIDE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SafeDivide'>>, 'SIGN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sign'>>, 'SIGNUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sign'>>, 'SORT_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SortArray'>>, 'SPLIT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Split'>>, 'SQRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sqrt'>>, 'STANDARD_HASH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StandardHash'>>, 'STAR_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StarMap'>>, 'STARTS_WITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STARTSWITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STDDEV': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stddev'>>, 'STDDEV_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StddevPop'>>, 'STDDEV_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StddevSamp'>>, 'STR_POSITION': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrPosition'>>, 'STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToDate'>>, 'STR_TO_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToMap'>>, 'STR_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToTime'>>, 'STR_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToUnix'>>, 'STRUCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Struct'>>, 'STRUCT_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StructExtract'>>, 'STUFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stuff'>>, 'INSERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stuff'>>, 'SUBSTRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Substring'>>, 'SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sum'>>, 'TIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeAdd'>>, 'TIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeDiff'>>, 'TIME_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'TIMEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'TIME_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToDate'>>, 'TIME_STR_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToTime'>>, 'TIME_STR_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToUnix'>>, 'TIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeSub'>>, 'TIME_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeToStr'>>, 'TIME_TO_TIME_STR': <function Parser.<lambda>>, 'TIME_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeToUnix'>>, 'TIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeTrunc'>>, 'TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Timestamp'>>, 'TIMESTAMP_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampAdd'>>, 'TIMESTAMPDIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampDiff'>>, 'TIMESTAMP_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampDiff'>>, 'TIMESTAMP_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampFromParts'>>, 'TIMESTAMPFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampFromParts'>>, 'TIMESTAMP_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampSub'>>, 'TIMESTAMP_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampTrunc'>>, 'TO_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToArray'>>, 'TO_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToBase64'>>, 'TO_CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToChar'>>, 'TO_DAYS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToDays'>>, 'TO_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToMap'>>, 'TO_NUMBER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToNumber'>>, 'TRANSFORM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Transform'>>, 'TRIM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Trim'>>, 'TRY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Try'>>, 'TRY_CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TryCast'>>, 'TS_OR_DI_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDiToDi'>>, 'TS_OR_DS_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsAdd'>>, 'TS_OR_DS_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsDiff'>>, 'TS_OR_DS_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToDate'>>, 'TS_OR_DS_TO_DATE_STR': <function Parser.<lambda>>, 'TS_OR_DS_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTime'>>, 'TS_OR_DS_TO_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTimestamp'>>, 'UNHEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Unhex'>>, 'UNIX_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixDate'>>, 'UNIX_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToStr'>>, 'UNIX_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTime'>>, 'UNIX_TO_TIME_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTimeStr'>>, 'UPPER': <function build_upper>, 'UCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Upper'>>, 'VAR_MAP': <function build_var_map>, 'VARIANCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'VAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Week'>>, 'WEEK_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.WeekOfYear'>>, 'WEEKOFYEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.WeekOfYear'>>, 'WHEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.When'>>, 'X_M_L_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.XMLTable'>>, 'XOR': <function ClickHouse.Parser.<lambda>>, 'YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Year'>>, 'GLOB': <function Parser.<lambda>>, 'JSON_EXTRACT_PATH_TEXT': <function build_extract_json_with_path.<locals>._builder>, 'LIKE': <function build_like>, 'LOG2': <function Parser.<lambda>>, 'LOG10': <function Parser.<lambda>>, 'MOD': <function build_mod>, 'TO_HEX': <function build_hex>, 'ANY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnyValue'>>, 'ARRAYSUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySum'>>, 'DATEADD': <function ClickHouse.Parser.<lambda>>, 'DATE_FORMAT': <function _build_date_format>, 'FORMATDATETIME': <function _build_date_format>, 'JSONEXTRACTSTRING': <function build_json_extract_path.<locals>._builder>, 'MATCH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpLike'>>, 'RANDCANONICAL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'TUPLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Struct'>>, 'UNIQ': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'SHA256': <function ClickHouse.Parser.<lambda>>, 'SHA512': <function ClickHouse.Parser.<lambda>>}"}, "sqlglot.dialects.clickhouse.ClickHouse.Parser.AGG_FUNCTIONS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Parser.AGG_FUNCTIONS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Parser.AGG_FUNCTIONS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'groupBitAnd', 'quantileExact', 'stddevPop', 'groupBitmap', 'uniqTheta', 'windowFunnel', 'quantilesTiming', 'groupBitmapOr', 'quantilesExact', 'quantilesBFloat16', 'quantileBFloat16Weighted', 'stochasticLogisticRegression', 'groupArrayMovingSum', 'contingency', 'quantilesExactWeighted', 'quantilesInterpolatedWeighted', 'kurtSamp', 'deltaSumTimestamp', 'maxIntersectionsPosition', 'entropy', 'avg', 'cramersV', 'minMap', 'quantileExactWeighted', 'exponentialMovingAverage', 'categoricalInformationValue', 'corr', 'anyHeavy', 'median', 'quantileDeterministic', 'quantileBFloat16', 'meanZTest', 'quantileInterpolatedWeighted', 'sumCount', 'welchTTest', 'simpleLinearRegression', 'groupArrayInsertAt', 'quantilesDeterministic', 'any', 'boundingRatio', 'min', 'quantilesExactLow', 'kolmogorovSmirnovTest', 'groupBitmapAnd', 'uniqHLL12', 'stochasticLinearRegression', 'max', 'quantileGK', 'sequenceNextNode', 'quantilesBFloat16Weighted', 'count', 'maxIntersections', 'sumKahan', 'quantilesGK', 'exponentialTimeDecayedAvg', 'quantileExactHigh', 'varSamp', 'avgWeighted', 'uniqCombined64', 'groupUniqArray', 'quantileTDigest', 'uniqCombined', 'cramersVBiasCorrected', 'first_value', 'skewSamp', 'uniqUpTo', 'groupArraySample', 'groupArrayMovingAvg', 'skewPop', 'groupBitXor', 'quantileTimingWeighted', 'maxMap', 'uniqExact', 'sumWithOverflow', 'intervalLengthSum', 'quantileTDigestWeighted', 'argMax', 'deltaSum', 'quantilesExactHigh', 'theilsU', 'sum', 'uniq', 'quantileExactLow', 'topK', 'retention', 'quantilesTDigestWeighted', 'quantileTiming', 'sumMap', 'mannWhitneyUTest', 'rankCorr', 'stddevSamp', 'varPop', 'sequenceMatch', 'covarPop', 'sequenceCount', 'argMin', 'covarSamp', 'quantilesTDigest', 'groupBitOr', 'largestTriangleThreeBuckets', 'anyLast', 'histogram', 'groupBitmapXor', 'last_value', 'groupArrayLast', 'kurtPop', 'sparkBar', 'topKWeighted', 'quantiles', 'quantilesTimingWeighted', 'quantile', 'studentTTest', 'groupArray'}"}, "sqlglot.dialects.clickhouse.ClickHouse.Parser.AGG_FUNCTIONS_SUFFIXES": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Parser.AGG_FUNCTIONS_SUFFIXES", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Parser.AGG_FUNCTIONS_SUFFIXES", "kind": "variable", "doc": "<p></p>\n", "default_value": "['If', 'Array', 'ArrayIf', 'Map', 'SimpleState', 'State', 'Merge', 'MergeState', 'ForEach', 'Distinct', 'OrDefault', 'OrNull', 'Resample', 'ArgMin', 'ArgMax']"}, "sqlglot.dialects.clickhouse.ClickHouse.Parser.FUNC_TOKENS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Parser.FUNC_TOKENS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Parser.FUNC_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.MONEY: 'MONEY'>, <TokenType.PRIMARY_KEY: 'PRIMARY_KEY'>, <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, <TokenType.IDENTIFIER: 'IDENTIFIER'>, <TokenType.VARBINARY: 'VARBINARY'>, <TokenType.HSTORE: 'HSTORE'>, <TokenType.IPADDRESS: 'IPADDRESS'>, <TokenType.ISNULL: 'ISNULL'>, <TokenType.NUMRANGE: 'NUMRANGE'>, <TokenType.DATE32: 'DATE32'>, <TokenType.INT8RANGE: 'INT8RANGE'>, <TokenType.AGGREGATEFUNCTION: 'AGGREGATEFUNCTION'>, <TokenType.VARCHAR: 'VARCHAR'>, <TokenType.TIMETZ: 'TIMETZ'>, <TokenType.GEOMETRY: 'GEOMETRY'>, <TokenType.ENUM8: 'ENUM8'>, <TokenType.INDEX: 'INDEX'>, <TokenType.UINT256: 'UINT256'>, <TokenType.BIGINT: 'BIGINT'>, <TokenType.INT128: 'INT128'>, <TokenType.SMALLMONEY: 'SMALLMONEY'>, <TokenType.HLLSKETCH: 'HLLSKETCH'>, <TokenType.RLIKE: 'RLIKE'>, <TokenType.SMALLINT: 'SMALLINT'>, <TokenType.INT256: 'INT256'>, <TokenType.GLOB: 'GLOB'>, <TokenType.FLOAT: 'FLOAT'>, <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, <TokenType.UNNEST: 'UNNEST'>, <TokenType.EXISTS: 'EXISTS'>, <TokenType.NULL: 'NULL'>, <TokenType.SET: 'SET'>, <TokenType.XOR: 'XOR'>, <TokenType.NULLABLE: 'NULLABLE'>, <TokenType.TINYTEXT: 'TINYTEXT'>, <TokenType.DATE: 'DATE'>, <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <TokenType.MERGE: 'MERGE'>, <TokenType.FIRST: 'FIRST'>, <TokenType.BINARY: 'BINARY'>, <TokenType.ARRAY: 'ARRAY'>, <TokenType.SERIAL: 'SERIAL'>, <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, <TokenType.INTERVAL: 'INTERVAL'>, <TokenType.WINDOW: 'WINDOW'>, <TokenType.RIGHT: 'RIGHT'>, <TokenType.BPCHAR: 'BPCHAR'>, <TokenType.BIT: 'BIT'>, <TokenType.UINT: 'UINT'>, <TokenType.ILIKE: 'ILIKE'>, <TokenType.UUID: 'UUID'>, <TokenType.STRUCT: 'STRUCT'>, <TokenType.LEFT: 'LEFT'>, <TokenType.SUPER: 'SUPER'>, <TokenType.IMAGE: 'IMAGE'>, <TokenType.UBIGINT: 'UBIGINT'>, <TokenType.LONGBLOB: 'LONGBLOB'>, <TokenType.VAR: 'VAR'>, <TokenType.COMMAND: 'COMMAND'>, <TokenType.TRUNCATE: 'TRUNCATE'>, <TokenType.UMEDIUMINT: 'UMEDIUMINT'>, <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, <TokenType.UINT128: 'UINT128'>, <TokenType.MAP: 'MAP'>, <TokenType.IPV4: 'IPV4'>, <TokenType.USERDEFINED: 'USERDEFINED'>, <TokenType.REPLACE: 'REPLACE'>, <TokenType.RANGE: 'RANGE'>, <TokenType.NVARCHAR: 'NVARCHAR'>, <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, <TokenType.TIMESTAMP_MS: 'TIMESTAMP_MS'>, <TokenType.VARIANT: 'VARIANT'>, <TokenType.ENUM: 'ENUM'>, <TokenType.USMALLINT: 'USMALLINT'>, <TokenType.TIMESTAMP_S: 'TIMESTAMP_S'>, <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, <TokenType.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>, <TokenType.TEXT: 'TEXT'>, <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, <TokenType.PSEUDO_TYPE: 'PSEUDO_TYPE'>, <TokenType.FIXEDSTRING: 'FIXEDSTRING'>, <TokenType.INT: 'INT'>, <TokenType.BIGSERIAL: 'BIGSERIAL'>, <TokenType.BOOLEAN: 'BOOLEAN'>, <TokenType.UNKNOWN: 'UNKNOWN'>, <TokenType.TSTZRANGE: 'TSTZRANGE'>, <TokenType.DATETIME64: 'DATETIME64'>, <TokenType.DATETIME: 'DATETIME'>, <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, <TokenType.MEDIUMINT: 'MEDIUMINT'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>, <TokenType.LIKE: 'LIKE'>, <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, <TokenType.XML: 'XML'>, <TokenType.JSON: 'JSON'>, <TokenType.UTINYINT: 'UTINYINT'>, <TokenType.TIME: 'TIME'>, <TokenType.UDECIMAL: 'UDECIMAL'>, <TokenType.NESTED: 'NESTED'>, <TokenType.ROWVERSION: 'ROWVERSION'>, <TokenType.OFFSET: 'OFFSET'>, <TokenType.INSERT: 'INSERT'>, <TokenType.TIMESTAMP_NS: 'TIMESTAMP_NS'>, <TokenType.ANY: 'ANY'>, <TokenType.INET: 'INET'>, <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, <TokenType.CURRENT_USER: 'CURRENT_USER'>, <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>, <TokenType.ALL: 'ALL'>, <TokenType.NAME: 'NAME'>, <TokenType.SOME: 'SOME'>, <TokenType.ENUM16: 'ENUM16'>, <TokenType.YEAR: 'YEAR'>, <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, <TokenType.DOUBLE: 'DOUBLE'>, <TokenType.INT4RANGE: 'INT4RANGE'>, <TokenType.FORMAT: 'FORMAT'>, <TokenType.IPPREFIX: 'IPPREFIX'>, <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>, <TokenType.COLLATE: 'COLLATE'>, <TokenType.FILTER: 'FILTER'>, <TokenType.JSONB: 'JSONB'>, <TokenType.TDIGEST: 'TDIGEST'>, <TokenType.CHAR: 'CHAR'>, <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.ROW: 'ROW'>, <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.TABLE: 'TABLE'>, <TokenType.DATERANGE: 'DATERANGE'>, <TokenType.TSRANGE: 'TSRANGE'>, <TokenType.DECIMAL: 'DECIMAL'>, <TokenType.NCHAR: 'NCHAR'>, <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, <TokenType.SEQUENCE: 'SEQUENCE'>, <TokenType.LONGTEXT: 'LONGTEXT'>, <TokenType.IPV6: 'IPV6'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, <TokenType.TINYINT: 'TINYINT'>, <TokenType.TINYBLOB: 'TINYBLOB'>}"}, "sqlglot.dialects.clickhouse.ClickHouse.Parser.AGG_FUNC_MAPPING": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Parser.AGG_FUNC_MAPPING", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Parser.AGG_FUNC_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'groupBitAndIf': ('groupBitAnd', 'If'), 'quantileExactIf': ('quantileExact', 'If'), 'stddevPopIf': ('stddevPop', 'If'), 'groupBitmapIf': ('groupBitmap', 'If'), 'uniqThetaIf': ('uniqTheta', 'If'), 'windowFunnelIf': ('windowFunnel', 'If'), 'quantilesTimingIf': ('quantilesTiming', 'If'), 'groupBitmapOrIf': ('groupBitmapOr', 'If'), 'quantilesExactIf': ('quantilesExact', 'If'), 'quantilesBFloat16If': ('quantilesBFloat16', 'If'), 'quantileBFloat16WeightedIf': ('quantileBFloat16Weighted', 'If'), 'stochasticLogisticRegressionIf': ('stochasticLogisticRegression', 'If'), 'groupArrayMovingSumIf': ('groupArrayMovingSum', 'If'), 'contingencyIf': ('contingency', 'If'), 'quantilesExactWeightedIf': ('quantilesExactWeighted', 'If'), 'quantilesInterpolatedWeightedIf': ('quantilesInterpolatedWeighted', 'If'), 'kurtSampIf': ('kurtSamp', 'If'), 'deltaSumTimestampIf': ('deltaSumTimestamp', 'If'), 'maxIntersectionsPositionIf': ('maxIntersectionsPosition', 'If'), 'entropyIf': ('entropy', 'If'), 'avgIf': ('avg', 'If'), 'cramersVIf': ('cramersV', 'If'), 'minMapIf': ('minMap', 'If'), 'quantileExactWeightedIf': ('quantileExactWeighted', 'If'), 'exponentialMovingAverageIf': ('exponentialMovingAverage', 'If'), 'categoricalInformationValueIf': ('categoricalInformationValue', 'If'), 'corrIf': ('corr', 'If'), 'anyHeavyIf': ('anyHeavy', 'If'), 'medianIf': ('median', 'If'), 'quantileDeterministicIf': ('quantileDeterministic', 'If'), 'quantileBFloat16If': ('quantileBFloat16', 'If'), 'meanZTestIf': ('meanZTest', 'If'), 'quantileInterpolatedWeightedIf': ('quantileInterpolatedWeighted', 'If'), 'sumCountIf': ('sumCount', 'If'), 'welchTTestIf': ('welchTTest', 'If'), 'simpleLinearRegressionIf': ('simpleLinearRegression', 'If'), 'groupArrayInsertAtIf': ('groupArrayInsertAt', 'If'), 'quantilesDeterministicIf': ('quantilesDeterministic', 'If'), 'anyIf': ('any', 'If'), 'boundingRatioIf': ('boundingRatio', 'If'), 'minIf': ('min', 'If'), 'quantilesExactLowIf': ('quantilesExactLow', 'If'), 'kolmogorovSmirnovTestIf': ('kolmogorovSmirnovTest', 'If'), 'groupBitmapAndIf': ('groupBitmapAnd', 'If'), 'uniqHLL12If': ('uniqHLL12', 'If'), 'stochasticLinearRegressionIf': ('stochasticLinearRegression', 'If'), 'maxIf': ('max', 'If'), 'quantileGKIf': ('quantileGK', 'If'), 'sequenceNextNodeIf': ('sequenceNextNode', 'If'), 'quantilesBFloat16WeightedIf': ('quantilesBFloat16Weighted', 'If'), 'countIf': ('count', 'If'), 'maxIntersectionsIf': ('maxIntersections', 'If'), 'sumKahanIf': ('sumKahan', 'If'), 'quantilesGKIf': ('quantilesGK', 'If'), 'exponentialTimeDecayedAvgIf': ('exponentialTimeDecayedAvg', 'If'), 'quantileExactHighIf': ('quantileExactHigh', 'If'), 'varSampIf': ('varSamp', 'If'), 'avgWeightedIf': ('avgWeighted', 'If'), 'uniqCombined64If': ('uniqCombined64', 'If'), 'groupUniqArrayIf': ('groupUniqArray', 'If'), 'quantileTDigestIf': ('quantileTDigest', 'If'), 'uniqCombinedIf': ('uniqCombined', 'If'), 'cramersVBiasCorrectedIf': ('cramersVBiasCorrected', 'If'), 'first_valueIf': ('first_value', 'If'), 'skewSampIf': ('skewSamp', 'If'), 'uniqUpToIf': ('uniqUpTo', 'If'), 'groupArraySampleIf': ('groupArraySample', 'If'), 'groupArrayMovingAvgIf': ('groupArrayMovingAvg', 'If'), 'skewPopIf': ('skewPop', 'If'), 'groupBitXorIf': ('groupBitXor', 'If'), 'quantileTimingWeightedIf': ('quantileTimingWeighted', 'If'), 'maxMapIf': ('maxMap', 'If'), 'uniqExactIf': ('uniqExact', 'If'), 'sumWithOverflowIf': ('sumWithOverflow', 'If'), 'intervalLengthSumIf': ('intervalLengthSum', 'If'), 'quantileTDigestWeightedIf': ('quantileTDigestWeighted', 'If'), 'argMaxIf': ('argMax', 'If'), 'deltaSumIf': ('deltaSum', 'If'), 'quantilesExactHighIf': ('quantilesExactHigh', 'If'), 'theilsUIf': ('theilsU', 'If'), 'sumIf': ('sum', 'If'), 'uniqIf': ('uniq', 'If'), 'quantileExactLowIf': ('quantileExactLow', 'If'), 'topKIf': ('topK', 'If'), 'retentionIf': ('retention', 'If'), 'quantilesTDigestWeightedIf': ('quantilesTDigestWeighted', 'If'), 'quantileTimingIf': ('quantileTiming', 'If'), 'sumMapIf': ('sumMap', 'If'), 'mannWhitneyUTestIf': ('mannWhitneyUTest', 'If'), 'rankCorrIf': ('rankCorr', 'If'), 'stddevSampIf': ('stddevSamp', 'If'), 'varPopIf': ('varPop', 'If'), 'sequenceMatchIf': ('sequenceMatch', 'If'), 'covarPopIf': ('covarPop', 'If'), 'sequenceCountIf': ('sequenceCount', 'If'), 'argMinIf': ('argMin', 'If'), 'covarSampIf': ('covarSamp', 'If'), 'quantilesTDigestIf': ('quantilesTDigest', 'If'), 'groupBitOrIf': ('groupBitOr', 'If'), 'largestTriangleThreeBucketsIf': ('largestTriangleThreeBuckets', 'If'), 'anyLastIf': ('anyLast', 'If'), 'histogramIf': ('histogram', 'If'), 'groupBitmapXorIf': ('groupBitmapXor', 'If'), 'last_valueIf': ('last_value', 'If'), 'groupArrayLastIf': ('groupArrayLast', 'If'), 'kurtPopIf': ('kurtPop', 'If'), 'sparkBarIf': ('sparkBar', 'If'), 'topKWeightedIf': ('topKWeighted', 'If'), 'quantilesIf': ('quantiles', 'If'), 'quantilesTimingWeightedIf': ('quantilesTimingWeighted', 'If'), 'quantileIf': ('quantile', 'If'), 'studentTTestIf': ('studentTTest', 'If'), 'groupArrayIf': ('groupArray', 'If'), 'groupBitAndArray': ('groupBitAnd', 'Array'), 'quantileExactArray': ('quantileExact', 'Array'), 'stddevPopArray': ('stddevPop', 'Array'), 'groupBitmapArray': ('groupBitmap', 'Array'), 'uniqThetaArray': ('uniqTheta', 'Array'), 'windowFunnelArray': ('windowFunnel', 'Array'), 'quantilesTimingArray': ('quantilesTiming', 'Array'), 'groupBitmapOrArray': ('groupBitmapOr', 'Array'), 'quantilesExactArray': ('quantilesExact', 'Array'), 'quantilesBFloat16Array': ('quantilesBFloat16', 'Array'), 'quantileBFloat16WeightedArray': ('quantileBFloat16Weighted', 'Array'), 'stochasticLogisticRegressionArray': ('stochasticLogisticRegression', 'Array'), 'groupArrayMovingSumArray': ('groupArrayMovingSum', 'Array'), 'contingencyArray': ('contingency', 'Array'), 'quantilesExactWeightedArray': ('quantilesExactWeighted', 'Array'), 'quantilesInterpolatedWeightedArray': ('quantilesInterpolatedWeighted', 'Array'), 'kurtSampArray': ('kurtSamp', 'Array'), 'deltaSumTimestampArray': ('deltaSumTimestamp', 'Array'), 'maxIntersectionsPositionArray': ('maxIntersectionsPosition', 'Array'), 'entropyArray': ('entropy', 'Array'), 'avgArray': ('avg', 'Array'), 'cramersVArray': ('cramersV', 'Array'), 'minMapArray': ('minMap', 'Array'), 'quantileExactWeightedArray': ('quantileExactWeighted', 'Array'), 'exponentialMovingAverageArray': ('exponentialMovingAverage', 'Array'), 'categoricalInformationValueArray': ('categoricalInformationValue', 'Array'), 'corrArray': ('corr', 'Array'), 'anyHeavyArray': ('anyHeavy', 'Array'), 'medianArray': ('median', 'Array'), 'quantileDeterministicArray': ('quantileDeterministic', 'Array'), 'quantileBFloat16Array': ('quantileBFloat16', 'Array'), 'meanZTestArray': ('meanZTest', 'Array'), 'quantileInterpolatedWeightedArray': ('quantileInterpolatedWeighted', 'Array'), 'sumCountArray': ('sumCount', 'Array'), 'welchTTestArray': ('welchTTest', 'Array'), 'simpleLinearRegressionArray': ('simpleLinearRegression', 'Array'), 'groupArrayInsertAtArray': ('groupArrayInsertAt', 'Array'), 'quantilesDeterministicArray': ('quantilesDeterministic', 'Array'), 'anyArray': ('any', 'Array'), 'boundingRatioArray': ('boundingRatio', 'Array'), 'minArray': ('min', 'Array'), 'quantilesExactLowArray': ('quantilesExactLow', 'Array'), 'kolmogorovSmirnovTestArray': ('kolmogorovSmirnovTest', 'Array'), 'groupBitmapAndArray': ('groupBitmapAnd', 'Array'), 'uniqHLL12Array': ('uniqHLL12', 'Array'), 'stochasticLinearRegressionArray': ('stochasticLinearRegression', 'Array'), 'maxArray': ('max', 'Array'), 'quantileGKArray': ('quantileGK', 'Array'), 'sequenceNextNodeArray': ('sequenceNextNode', 'Array'), 'quantilesBFloat16WeightedArray': ('quantilesBFloat16Weighted', 'Array'), 'countArray': ('count', 'Array'), 'maxIntersectionsArray': ('maxIntersections', 'Array'), 'sumKahanArray': ('sumKahan', 'Array'), 'quantilesGKArray': ('quantilesGK', 'Array'), 'exponentialTimeDecayedAvgArray': ('exponentialTimeDecayedAvg', 'Array'), 'quantileExactHighArray': ('quantileExactHigh', 'Array'), 'varSampArray': ('varSamp', 'Array'), 'avgWeightedArray': ('avgWeighted', 'Array'), 'uniqCombined64Array': ('uniqCombined64', 'Array'), 'groupUniqArrayArray': ('groupUniqArray', 'Array'), 'quantileTDigestArray': ('quantileTDigest', 'Array'), 'uniqCombinedArray': ('uniqCombined', 'Array'), 'cramersVBiasCorrectedArray': ('cramersVBiasCorrected', 'Array'), 'first_valueArray': ('first_value', 'Array'), 'skewSampArray': ('skewSamp', 'Array'), 'uniqUpToArray': ('uniqUpTo', 'Array'), 'groupArraySampleArray': ('groupArraySample', 'Array'), 'groupArrayMovingAvgArray': ('groupArrayMovingAvg', 'Array'), 'skewPopArray': ('skewPop', 'Array'), 'groupBitXorArray': ('groupBitXor', 'Array'), 'quantileTimingWeightedArray': ('quantileTimingWeighted', 'Array'), 'maxMapArray': ('maxMap', 'Array'), 'uniqExactArray': ('uniqExact', 'Array'), 'sumWithOverflowArray': ('sumWithOverflow', 'Array'), 'intervalLengthSumArray': ('intervalLengthSum', 'Array'), 'quantileTDigestWeightedArray': ('quantileTDigestWeighted', 'Array'), 'argMaxArray': ('argMax', 'Array'), 'deltaSumArray': ('deltaSum', 'Array'), 'quantilesExactHighArray': ('quantilesExactHigh', 'Array'), 'theilsUArray': ('theilsU', 'Array'), 'sumArray': ('sum', 'Array'), 'uniqArray': ('uniq', 'Array'), 'quantileExactLowArray': ('quantileExactLow', 'Array'), 'topKArray': ('topK', 'Array'), 'retentionArray': ('retention', 'Array'), 'quantilesTDigestWeightedArray': ('quantilesTDigestWeighted', 'Array'), 'quantileTimingArray': ('quantileTiming', 'Array'), 'sumMapArray': ('sumMap', 'Array'), 'mannWhitneyUTestArray': ('mannWhitneyUTest', 'Array'), 'rankCorrArray': ('rankCorr', 'Array'), 'stddevSampArray': ('stddevSamp', 'Array'), 'varPopArray': ('varPop', 'Array'), 'sequenceMatchArray': ('sequenceMatch', 'Array'), 'covarPopArray': ('covarPop', 'Array'), 'sequenceCountArray': ('sequenceCount', 'Array'), 'argMinArray': ('argMin', 'Array'), 'covarSampArray': ('covarSamp', 'Array'), 'quantilesTDigestArray': ('quantilesTDigest', 'Array'), 'groupBitOrArray': ('groupBitOr', 'Array'), 'largestTriangleThreeBucketsArray': ('largestTriangleThreeBuckets', 'Array'), 'anyLastArray': ('anyLast', 'Array'), 'histogramArray': ('histogram', 'Array'), 'groupBitmapXorArray': ('groupBitmapXor', 'Array'), 'last_valueArray': ('last_value', 'Array'), 'groupArrayLastArray': ('groupArrayLast', 'Array'), 'kurtPopArray': ('kurtPop', 'Array'), 'sparkBarArray': ('sparkBar', 'Array'), 'topKWeightedArray': ('topKWeighted', 'Array'), 'quantilesArray': ('quantiles', 'Array'), 'quantilesTimingWeightedArray': ('quantilesTimingWeighted', 'Array'), 'quantileArray': ('quantile', 'Array'), 'studentTTestArray': ('studentTTest', 'Array'), 'groupArrayArray': ('groupArray', 'Array'), 'groupBitAndArrayIf': ('groupBitAnd', 'ArrayIf'), 'quantileExactArrayIf': ('quantileExact', 'ArrayIf'), 'stddevPopArrayIf': ('stddevPop', 'ArrayIf'), 'groupBitmapArrayIf': ('groupBitmap', 'ArrayIf'), 'uniqThetaArrayIf': ('uniqTheta', 'ArrayIf'), 'windowFunnelArrayIf': ('windowFunnel', 'ArrayIf'), 'quantilesTimingArrayIf': ('quantilesTiming', 'ArrayIf'), 'groupBitmapOrArrayIf': ('groupBitmapOr', 'ArrayIf'), 'quantilesExactArrayIf': ('quantilesExact', 'ArrayIf'), 'quantilesBFloat16ArrayIf': ('quantilesBFloat16', 'ArrayIf'), 'quantileBFloat16WeightedArrayIf': ('quantileBFloat16Weighted', 'ArrayIf'), 'stochasticLogisticRegressionArrayIf': ('stochasticLogisticRegression', 'ArrayIf'), 'groupArrayMovingSumArrayIf': ('groupArrayMovingSum', 'ArrayIf'), 'contingencyArrayIf': ('contingency', 'ArrayIf'), 'quantilesExactWeightedArrayIf': ('quantilesExactWeighted', 'ArrayIf'), 'quantilesInterpolatedWeightedArrayIf': ('quantilesInterpolatedWeighted', 'ArrayIf'), 'kurtSampArrayIf': ('kurtSamp', 'ArrayIf'), 'deltaSumTimestampArrayIf': ('deltaSumTimestamp', 'ArrayIf'), 'maxIntersectionsPositionArrayIf': ('maxIntersectionsPosition', 'ArrayIf'), 'entropyArrayIf': ('entropy', 'ArrayIf'), 'avgArrayIf': ('avg', 'ArrayIf'), 'cramersVArrayIf': ('cramersV', 'ArrayIf'), 'minMapArrayIf': ('minMap', 'ArrayIf'), 'quantileExactWeightedArrayIf': ('quantileExactWeighted', 'ArrayIf'), 'exponentialMovingAverageArrayIf': ('exponentialMovingAverage', 'ArrayIf'), 'categoricalInformationValueArrayIf': ('categoricalInformationValue', 'ArrayIf'), 'corrArrayIf': ('corr', 'ArrayIf'), 'anyHeavyArrayIf': ('anyHeavy', 'ArrayIf'), 'medianArrayIf': ('median', 'ArrayIf'), 'quantileDeterministicArrayIf': ('quantileDeterministic', 'ArrayIf'), 'quantileBFloat16ArrayIf': ('quantileBFloat16', 'ArrayIf'), 'meanZTestArrayIf': ('meanZTest', 'ArrayIf'), 'quantileInterpolatedWeightedArrayIf': ('quantileInterpolatedWeighted', 'ArrayIf'), 'sumCountArrayIf': ('sumCount', 'ArrayIf'), 'welchTTestArrayIf': ('welchTTest', 'ArrayIf'), 'simpleLinearRegressionArrayIf': ('simpleLinearRegression', 'ArrayIf'), 'groupArrayInsertAtArrayIf': ('groupArrayInsertAt', 'ArrayIf'), 'quantilesDeterministicArrayIf': ('quantilesDeterministic', 'ArrayIf'), 'anyArrayIf': ('any', 'ArrayIf'), 'boundingRatioArrayIf': ('boundingRatio', 'ArrayIf'), 'minArrayIf': ('min', 'ArrayIf'), 'quantilesExactLowArrayIf': ('quantilesExactLow', 'ArrayIf'), 'kolmogorovSmirnovTestArrayIf': ('kolmogorovSmirnovTest', 'ArrayIf'), 'groupBitmapAndArrayIf': ('groupBitmapAnd', 'ArrayIf'), 'uniqHLL12ArrayIf': ('uniqHLL12', 'ArrayIf'), 'stochasticLinearRegressionArrayIf': ('stochasticLinearRegression', 'ArrayIf'), 'maxArrayIf': ('max', 'ArrayIf'), 'quantileGKArrayIf': ('quantileGK', 'ArrayIf'), 'sequenceNextNodeArrayIf': ('sequenceNextNode', 'ArrayIf'), 'quantilesBFloat16WeightedArrayIf': ('quantilesBFloat16Weighted', 'ArrayIf'), 'countArrayIf': ('count', 'ArrayIf'), 'maxIntersectionsArrayIf': ('maxIntersections', 'ArrayIf'), 'sumKahanArrayIf': ('sumKahan', 'ArrayIf'), 'quantilesGKArrayIf': ('quantilesGK', 'ArrayIf'), 'exponentialTimeDecayedAvgArrayIf': ('exponentialTimeDecayedAvg', 'ArrayIf'), 'quantileExactHighArrayIf': ('quantileExactHigh', 'ArrayIf'), 'varSampArrayIf': ('varSamp', 'ArrayIf'), 'avgWeightedArrayIf': ('avgWeighted', 'ArrayIf'), 'uniqCombined64ArrayIf': ('uniqCombined64', 'ArrayIf'), 'groupUniqArrayArrayIf': ('groupUniqArray', 'ArrayIf'), 'quantileTDigestArrayIf': ('quantileTDigest', 'ArrayIf'), 'uniqCombinedArrayIf': ('uniqCombined', 'ArrayIf'), 'cramersVBiasCorrectedArrayIf': ('cramersVBiasCorrected', 'ArrayIf'), 'first_valueArrayIf': ('first_value', 'ArrayIf'), 'skewSampArrayIf': ('skewSamp', 'ArrayIf'), 'uniqUpToArrayIf': ('uniqUpTo', 'ArrayIf'), 'groupArraySampleArrayIf': ('groupArraySample', 'ArrayIf'), 'groupArrayMovingAvgArrayIf': ('groupArrayMovingAvg', 'ArrayIf'), 'skewPopArrayIf': ('skewPop', 'ArrayIf'), 'groupBitXorArrayIf': ('groupBitXor', 'ArrayIf'), 'quantileTimingWeightedArrayIf': ('quantileTimingWeighted', 'ArrayIf'), 'maxMapArrayIf': ('maxMap', 'ArrayIf'), 'uniqExactArrayIf': ('uniqExact', 'ArrayIf'), 'sumWithOverflowArrayIf': ('sumWithOverflow', 'ArrayIf'), 'intervalLengthSumArrayIf': ('intervalLengthSum', 'ArrayIf'), 'quantileTDigestWeightedArrayIf': ('quantileTDigestWeighted', 'ArrayIf'), 'argMaxArrayIf': ('argMax', 'ArrayIf'), 'deltaSumArrayIf': ('deltaSum', 'ArrayIf'), 'quantilesExactHighArrayIf': ('quantilesExactHigh', 'ArrayIf'), 'theilsUArrayIf': ('theilsU', 'ArrayIf'), 'sumArrayIf': ('sum', 'ArrayIf'), 'uniqArrayIf': ('uniq', 'ArrayIf'), 'quantileExactLowArrayIf': ('quantileExactLow', 'ArrayIf'), 'topKArrayIf': ('topK', 'ArrayIf'), 'retentionArrayIf': ('retention', 'ArrayIf'), 'quantilesTDigestWeightedArrayIf': ('quantilesTDigestWeighted', 'ArrayIf'), 'quantileTimingArrayIf': ('quantileTiming', 'ArrayIf'), 'sumMapArrayIf': ('sumMap', 'ArrayIf'), 'mannWhitneyUTestArrayIf': ('mannWhitneyUTest', 'ArrayIf'), 'rankCorrArrayIf': ('rankCorr', 'ArrayIf'), 'stddevSampArrayIf': ('stddevSamp', 'ArrayIf'), 'varPopArrayIf': ('varPop', 'ArrayIf'), 'sequenceMatchArrayIf': ('sequenceMatch', 'ArrayIf'), 'covarPopArrayIf': ('covarPop', 'ArrayIf'), 'sequenceCountArrayIf': ('sequenceCount', 'ArrayIf'), 'argMinArrayIf': ('argMin', 'ArrayIf'), 'covarSampArrayIf': ('covarSamp', 'ArrayIf'), 'quantilesTDigestArrayIf': ('quantilesTDigest', 'ArrayIf'), 'groupBitOrArrayIf': ('groupBitOr', 'ArrayIf'), 'largestTriangleThreeBucketsArrayIf': ('largestTriangleThreeBuckets', 'ArrayIf'), 'anyLastArrayIf': ('anyLast', 'ArrayIf'), 'histogramArrayIf': ('histogram', 'ArrayIf'), 'groupBitmapXorArrayIf': ('groupBitmapXor', 'ArrayIf'), 'last_valueArrayIf': ('last_value', 'ArrayIf'), 'groupArrayLastArrayIf': ('groupArrayLast', 'ArrayIf'), 'kurtPopArrayIf': ('kurtPop', 'ArrayIf'), 'sparkBarArrayIf': ('sparkBar', 'ArrayIf'), 'topKWeightedArrayIf': ('topKWeighted', 'ArrayIf'), 'quantilesArrayIf': ('quantiles', 'ArrayIf'), 'quantilesTimingWeightedArrayIf': ('quantilesTimingWeighted', 'ArrayIf'), 'quantileArrayIf': ('quantile', 'ArrayIf'), 'studentTTestArrayIf': ('studentTTest', 'ArrayIf'), 'groupArrayArrayIf': ('groupArray', 'ArrayIf'), 'groupBitAndMap': ('groupBitAnd', 'Map'), 'quantileExactMap': ('quantileExact', 'Map'), 'stddevPopMap': ('stddevPop', 'Map'), 'groupBitmapMap': ('groupBitmap', 'Map'), 'uniqThetaMap': ('uniqTheta', 'Map'), 'windowFunnelMap': ('windowFunnel', 'Map'), 'quantilesTimingMap': ('quantilesTiming', 'Map'), 'groupBitmapOrMap': ('groupBitmapOr', 'Map'), 'quantilesExactMap': ('quantilesExact', 'Map'), 'quantilesBFloat16Map': ('quantilesBFloat16', 'Map'), 'quantileBFloat16WeightedMap': ('quantileBFloat16Weighted', 'Map'), 'stochasticLogisticRegressionMap': ('stochasticLogisticRegression', 'Map'), 'groupArrayMovingSumMap': ('groupArrayMovingSum', 'Map'), 'contingencyMap': ('contingency', 'Map'), 'quantilesExactWeightedMap': ('quantilesExactWeighted', 'Map'), 'quantilesInterpolatedWeightedMap': ('quantilesInterpolatedWeighted', 'Map'), 'kurtSampMap': ('kurtSamp', 'Map'), 'deltaSumTimestampMap': ('deltaSumTimestamp', 'Map'), 'maxIntersectionsPositionMap': ('maxIntersectionsPosition', 'Map'), 'entropyMap': ('entropy', 'Map'), 'avgMap': ('avg', 'Map'), 'cramersVMap': ('cramersV', 'Map'), 'minMapMap': ('minMap', 'Map'), 'quantileExactWeightedMap': ('quantileExactWeighted', 'Map'), 'exponentialMovingAverageMap': ('exponentialMovingAverage', 'Map'), 'categoricalInformationValueMap': ('categoricalInformationValue', 'Map'), 'corrMap': ('corr', 'Map'), 'anyHeavyMap': ('anyHeavy', 'Map'), 'medianMap': ('median', 'Map'), 'quantileDeterministicMap': ('quantileDeterministic', 'Map'), 'quantileBFloat16Map': ('quantileBFloat16', 'Map'), 'meanZTestMap': ('meanZTest', 'Map'), 'quantileInterpolatedWeightedMap': ('quantileInterpolatedWeighted', 'Map'), 'sumCountMap': ('sumCount', 'Map'), 'welchTTestMap': ('welchTTest', 'Map'), 'simpleLinearRegressionMap': ('simpleLinearRegression', 'Map'), 'groupArrayInsertAtMap': ('groupArrayInsertAt', 'Map'), 'quantilesDeterministicMap': ('quantilesDeterministic', 'Map'), 'anyMap': ('any', 'Map'), 'boundingRatioMap': ('boundingRatio', 'Map'), 'minMap': ('minMap', ''), 'quantilesExactLowMap': ('quantilesExactLow', 'Map'), 'kolmogorovSmirnovTestMap': ('kolmogorovSmirnovTest', 'Map'), 'groupBitmapAndMap': ('groupBitmapAnd', 'Map'), 'uniqHLL12Map': ('uniqHLL12', 'Map'), 'stochasticLinearRegressionMap': ('stochasticLinearRegression', 'Map'), 'maxMap': ('maxMap', ''), 'quantileGKMap': ('quantileGK', 'Map'), 'sequenceNextNodeMap': ('sequenceNextNode', 'Map'), 'quantilesBFloat16WeightedMap': ('quantilesBFloat16Weighted', 'Map'), 'countMap': ('count', 'Map'), 'maxIntersectionsMap': ('maxIntersections', 'Map'), 'sumKahanMap': ('sumKahan', 'Map'), 'quantilesGKMap': ('quantilesGK', 'Map'), 'exponentialTimeDecayedAvgMap': ('exponentialTimeDecayedAvg', 'Map'), 'quantileExactHighMap': ('quantileExactHigh', 'Map'), 'varSampMap': ('varSamp', 'Map'), 'avgWeightedMap': ('avgWeighted', 'Map'), 'uniqCombined64Map': ('uniqCombined64', 'Map'), 'groupUniqArrayMap': ('groupUniqArray', 'Map'), 'quantileTDigestMap': ('quantileTDigest', 'Map'), 'uniqCombinedMap': ('uniqCombined', 'Map'), 'cramersVBiasCorrectedMap': ('cramersVBiasCorrected', 'Map'), 'first_valueMap': ('first_value', 'Map'), 'skewSampMap': ('skewSamp', 'Map'), 'uniqUpToMap': ('uniqUpTo', 'Map'), 'groupArraySampleMap': ('groupArraySample', 'Map'), 'groupArrayMovingAvgMap': ('groupArrayMovingAvg', 'Map'), 'skewPopMap': ('skewPop', 'Map'), 'groupBitXorMap': ('groupBitXor', 'Map'), 'quantileTimingWeightedMap': ('quantileTimingWeighted', 'Map'), 'maxMapMap': ('maxMap', 'Map'), 'uniqExactMap': ('uniqExact', 'Map'), 'sumWithOverflowMap': ('sumWithOverflow', 'Map'), 'intervalLengthSumMap': ('intervalLengthSum', 'Map'), 'quantileTDigestWeightedMap': ('quantileTDigestWeighted', 'Map'), 'argMaxMap': ('argMax', 'Map'), 'deltaSumMap': ('deltaSum', 'Map'), 'quantilesExactHighMap': ('quantilesExactHigh', 'Map'), 'theilsUMap': ('theilsU', 'Map'), 'sumMap': ('sumMap', ''), 'uniqMap': ('uniq', 'Map'), 'quantileExactLowMap': ('quantileExactLow', 'Map'), 'topKMap': ('topK', 'Map'), 'retentionMap': ('retention', 'Map'), 'quantilesTDigestWeightedMap': ('quantilesTDigestWeighted', 'Map'), 'quantileTimingMap': ('quantileTiming', 'Map'), 'sumMapMap': ('sumMap', 'Map'), 'mannWhitneyUTestMap': ('mannWhitneyUTest', 'Map'), 'rankCorrMap': ('rankCorr', 'Map'), 'stddevSampMap': ('stddevSamp', 'Map'), 'varPopMap': ('varPop', 'Map'), 'sequenceMatchMap': ('sequenceMatch', 'Map'), 'covarPopMap': ('covarPop', 'Map'), 'sequenceCountMap': ('sequenceCount', 'Map'), 'argMinMap': ('argMin', 'Map'), 'covarSampMap': ('covarSamp', 'Map'), 'quantilesTDigestMap': ('quantilesTDigest', 'Map'), 'groupBitOrMap': ('groupBitOr', 'Map'), 'largestTriangleThreeBucketsMap': ('largestTriangleThreeBuckets', 'Map'), 'anyLastMap': ('anyLast', 'Map'), 'histogramMap': ('histogram', 'Map'), 'groupBitmapXorMap': ('groupBitmapXor', 'Map'), 'last_valueMap': ('last_value', 'Map'), 'groupArrayLastMap': ('groupArrayLast', 'Map'), 'kurtPopMap': ('kurtPop', 'Map'), 'sparkBarMap': ('sparkBar', 'Map'), 'topKWeightedMap': ('topKWeighted', 'Map'), 'quantilesMap': ('quantiles', 'Map'), 'quantilesTimingWeightedMap': ('quantilesTimingWeighted', 'Map'), 'quantileMap': ('quantile', 'Map'), 'studentTTestMap': ('studentTTest', 'Map'), 'groupArrayMap': ('groupArray', 'Map'), 'groupBitAndSimpleState': ('groupBitAnd', 'SimpleState'), 'quantileExactSimpleState': ('quantileExact', 'SimpleState'), 'stddevPopSimpleState': ('stddevPop', 'SimpleState'), 'groupBitmapSimpleState': ('groupBitmap', 'SimpleState'), 'uniqThetaSimpleState': ('uniqTheta', 'SimpleState'), 'windowFunnelSimpleState': ('windowFunnel', 'SimpleState'), 'quantilesTimingSimpleState': ('quantilesTiming', 'SimpleState'), 'groupBitmapOrSimpleState': ('groupBitmapOr', 'SimpleState'), 'quantilesExactSimpleState': ('quantilesExact', 'SimpleState'), 'quantilesBFloat16SimpleState': ('quantilesBFloat16', 'SimpleState'), 'quantileBFloat16WeightedSimpleState': ('quantileBFloat16Weighted', 'SimpleState'), 'stochasticLogisticRegressionSimpleState': ('stochasticLogisticRegression', 'SimpleState'), 'groupArrayMovingSumSimpleState': ('groupArrayMovingSum', 'SimpleState'), 'contingencySimpleState': ('contingency', 'SimpleState'), 'quantilesExactWeightedSimpleState': ('quantilesExactWeighted', 'SimpleState'), 'quantilesInterpolatedWeightedSimpleState': ('quantilesInterpolatedWeighted', 'SimpleState'), 'kurtSampSimpleState': ('kurtSamp', 'SimpleState'), 'deltaSumTimestampSimpleState': ('deltaSumTimestamp', 'SimpleState'), 'maxIntersectionsPositionSimpleState': ('maxIntersectionsPosition', 'SimpleState'), 'entropySimpleState': ('entropy', 'SimpleState'), 'avgSimpleState': ('avg', 'SimpleState'), 'cramersVSimpleState': ('cramersV', 'SimpleState'), 'minMapSimpleState': ('minMap', 'SimpleState'), 'quantileExactWeightedSimpleState': ('quantileExactWeighted', 'SimpleState'), 'exponentialMovingAverageSimpleState': ('exponentialMovingAverage', 'SimpleState'), 'categoricalInformationValueSimpleState': ('categoricalInformationValue', 'SimpleState'), 'corrSimpleState': ('corr', 'SimpleState'), 'anyHeavySimpleState': ('anyHeavy', 'SimpleState'), 'medianSimpleState': ('median', 'SimpleState'), 'quantileDeterministicSimpleState': ('quantileDeterministic', 'SimpleState'), 'quantileBFloat16SimpleState': ('quantileBFloat16', 'SimpleState'), 'meanZTestSimpleState': ('meanZTest', 'SimpleState'), 'quantileInterpolatedWeightedSimpleState': ('quantileInterpolatedWeighted', 'SimpleState'), 'sumCountSimpleState': ('sumCount', 'SimpleState'), 'welchTTestSimpleState': ('welchTTest', 'SimpleState'), 'simpleLinearRegressionSimpleState': ('simpleLinearRegression', 'SimpleState'), 'groupArrayInsertAtSimpleState': ('groupArrayInsertAt', 'SimpleState'), 'quantilesDeterministicSimpleState': ('quantilesDeterministic', 'SimpleState'), 'anySimpleState': ('any', 'SimpleState'), 'boundingRatioSimpleState': ('boundingRatio', 'SimpleState'), 'minSimpleState': ('min', 'SimpleState'), 'quantilesExactLowSimpleState': ('quantilesExactLow', 'SimpleState'), 'kolmogorovSmirnovTestSimpleState': ('kolmogorovSmirnovTest', 'SimpleState'), 'groupBitmapAndSimpleState': ('groupBitmapAnd', 'SimpleState'), 'uniqHLL12SimpleState': ('uniqHLL12', 'SimpleState'), 'stochasticLinearRegressionSimpleState': ('stochasticLinearRegression', 'SimpleState'), 'maxSimpleState': ('max', 'SimpleState'), 'quantileGKSimpleState': ('quantileGK', 'SimpleState'), 'sequenceNextNodeSimpleState': ('sequenceNextNode', 'SimpleState'), 'quantilesBFloat16WeightedSimpleState': ('quantilesBFloat16Weighted', 'SimpleState'), 'countSimpleState': ('count', 'SimpleState'), 'maxIntersectionsSimpleState': ('maxIntersections', 'SimpleState'), 'sumKahanSimpleState': ('sumKahan', 'SimpleState'), 'quantilesGKSimpleState': ('quantilesGK', 'SimpleState'), 'exponentialTimeDecayedAvgSimpleState': ('exponentialTimeDecayedAvg', 'SimpleState'), 'quantileExactHighSimpleState': ('quantileExactHigh', 'SimpleState'), 'varSampSimpleState': ('varSamp', 'SimpleState'), 'avgWeightedSimpleState': ('avgWeighted', 'SimpleState'), 'uniqCombined64SimpleState': ('uniqCombined64', 'SimpleState'), 'groupUniqArraySimpleState': ('groupUniqArray', 'SimpleState'), 'quantileTDigestSimpleState': ('quantileTDigest', 'SimpleState'), 'uniqCombinedSimpleState': ('uniqCombined', 'SimpleState'), 'cramersVBiasCorrectedSimpleState': ('cramersVBiasCorrected', 'SimpleState'), 'first_valueSimpleState': ('first_value', 'SimpleState'), 'skewSampSimpleState': ('skewSamp', 'SimpleState'), 'uniqUpToSimpleState': ('uniqUpTo', 'SimpleState'), 'groupArraySampleSimpleState': ('groupArraySample', 'SimpleState'), 'groupArrayMovingAvgSimpleState': ('groupArrayMovingAvg', 'SimpleState'), 'skewPopSimpleState': ('skewPop', 'SimpleState'), 'groupBitXorSimpleState': ('groupBitXor', 'SimpleState'), 'quantileTimingWeightedSimpleState': ('quantileTimingWeighted', 'SimpleState'), 'maxMapSimpleState': ('maxMap', 'SimpleState'), 'uniqExactSimpleState': ('uniqExact', 'SimpleState'), 'sumWithOverflowSimpleState': ('sumWithOverflow', 'SimpleState'), 'intervalLengthSumSimpleState': ('intervalLengthSum', 'SimpleState'), 'quantileTDigestWeightedSimpleState': ('quantileTDigestWeighted', 'SimpleState'), 'argMaxSimpleState': ('argMax', 'SimpleState'), 'deltaSumSimpleState': ('deltaSum', 'SimpleState'), 'quantilesExactHighSimpleState': ('quantilesExactHigh', 'SimpleState'), 'theilsUSimpleState': ('theilsU', 'SimpleState'), 'sumSimpleState': ('sum', 'SimpleState'), 'uniqSimpleState': ('uniq', 'SimpleState'), 'quantileExactLowSimpleState': ('quantileExactLow', 'SimpleState'), 'topKSimpleState': ('topK', 'SimpleState'), 'retentionSimpleState': ('retention', 'SimpleState'), 'quantilesTDigestWeightedSimpleState': ('quantilesTDigestWeighted', 'SimpleState'), 'quantileTimingSimpleState': ('quantileTiming', 'SimpleState'), 'sumMapSimpleState': ('sumMap', 'SimpleState'), 'mannWhitneyUTestSimpleState': ('mannWhitneyUTest', 'SimpleState'), 'rankCorrSimpleState': ('rankCorr', 'SimpleState'), 'stddevSampSimpleState': ('stddevSamp', 'SimpleState'), 'varPopSimpleState': ('varPop', 'SimpleState'), 'sequenceMatchSimpleState': ('sequenceMatch', 'SimpleState'), 'covarPopSimpleState': ('covarPop', 'SimpleState'), 'sequenceCountSimpleState': ('sequenceCount', 'SimpleState'), 'argMinSimpleState': ('argMin', 'SimpleState'), 'covarSampSimpleState': ('covarSamp', 'SimpleState'), 'quantilesTDigestSimpleState': ('quantilesTDigest', 'SimpleState'), 'groupBitOrSimpleState': ('groupBitOr', 'SimpleState'), 'largestTriangleThreeBucketsSimpleState': ('largestTriangleThreeBuckets', 'SimpleState'), 'anyLastSimpleState': ('anyLast', 'SimpleState'), 'histogramSimpleState': ('histogram', 'SimpleState'), 'groupBitmapXorSimpleState': ('groupBitmapXor', 'SimpleState'), 'last_valueSimpleState': ('last_value', 'SimpleState'), 'groupArrayLastSimpleState': ('groupArrayLast', 'SimpleState'), 'kurtPopSimpleState': ('kurtPop', 'SimpleState'), 'sparkBarSimpleState': ('sparkBar', 'SimpleState'), 'topKWeightedSimpleState': ('topKWeighted', 'SimpleState'), 'quantilesSimpleState': ('quantiles', 'SimpleState'), 'quantilesTimingWeightedSimpleState': ('quantilesTimingWeighted', 'SimpleState'), 'quantileSimpleState': ('quantile', 'SimpleState'), 'studentTTestSimpleState': ('studentTTest', 'SimpleState'), 'groupArraySimpleState': ('groupArray', 'SimpleState'), 'groupBitAndState': ('groupBitAnd', 'State'), 'quantileExactState': ('quantileExact', 'State'), 'stddevPopState': ('stddevPop', 'State'), 'groupBitmapState': ('groupBitmap', 'State'), 'uniqThetaState': ('uniqTheta', 'State'), 'windowFunnelState': ('windowFunnel', 'State'), 'quantilesTimingState': ('quantilesTiming', 'State'), 'groupBitmapOrState': ('groupBitmapOr', 'State'), 'quantilesExactState': ('quantilesExact', 'State'), 'quantilesBFloat16State': ('quantilesBFloat16', 'State'), 'quantileBFloat16WeightedState': ('quantileBFloat16Weighted', 'State'), 'stochasticLogisticRegressionState': ('stochasticLogisticRegression', 'State'), 'groupArrayMovingSumState': ('groupArrayMovingSum', 'State'), 'contingencyState': ('contingency', 'State'), 'quantilesExactWeightedState': ('quantilesExactWeighted', 'State'), 'quantilesInterpolatedWeightedState': ('quantilesInterpolatedWeighted', 'State'), 'kurtSampState': ('kurtSamp', 'State'), 'deltaSumTimestampState': ('deltaSumTimestamp', 'State'), 'maxIntersectionsPositionState': ('maxIntersectionsPosition', 'State'), 'entropyState': ('entropy', 'State'), 'avgState': ('avg', 'State'), 'cramersVState': ('cramersV', 'State'), 'minMapState': ('minMap', 'State'), 'quantileExactWeightedState': ('quantileExactWeighted', 'State'), 'exponentialMovingAverageState': ('exponentialMovingAverage', 'State'), 'categoricalInformationValueState': ('categoricalInformationValue', 'State'), 'corrState': ('corr', 'State'), 'anyHeavyState': ('anyHeavy', 'State'), 'medianState': ('median', 'State'), 'quantileDeterministicState': ('quantileDeterministic', 'State'), 'quantileBFloat16State': ('quantileBFloat16', 'State'), 'meanZTestState': ('meanZTest', 'State'), 'quantileInterpolatedWeightedState': ('quantileInterpolatedWeighted', 'State'), 'sumCountState': ('sumCount', 'State'), 'welchTTestState': ('welchTTest', 'State'), 'simpleLinearRegressionState': ('simpleLinearRegression', 'State'), 'groupArrayInsertAtState': ('groupArrayInsertAt', 'State'), 'quantilesDeterministicState': ('quantilesDeterministic', 'State'), 'anyState': ('any', 'State'), 'boundingRatioState': ('boundingRatio', 'State'), 'minState': ('min', 'State'), 'quantilesExactLowState': ('quantilesExactLow', 'State'), 'kolmogorovSmirnovTestState': ('kolmogorovSmirnovTest', 'State'), 'groupBitmapAndState': ('groupBitmapAnd', 'State'), 'uniqHLL12State': ('uniqHLL12', 'State'), 'stochasticLinearRegressionState': ('stochasticLinearRegression', 'State'), 'maxState': ('max', 'State'), 'quantileGKState': ('quantileGK', 'State'), 'sequenceNextNodeState': ('sequenceNextNode', 'State'), 'quantilesBFloat16WeightedState': ('quantilesBFloat16Weighted', 'State'), 'countState': ('count', 'State'), 'maxIntersectionsState': ('maxIntersections', 'State'), 'sumKahanState': ('sumKahan', 'State'), 'quantilesGKState': ('quantilesGK', 'State'), 'exponentialTimeDecayedAvgState': ('exponentialTimeDecayedAvg', 'State'), 'quantileExactHighState': ('quantileExactHigh', 'State'), 'varSampState': ('varSamp', 'State'), 'avgWeightedState': ('avgWeighted', 'State'), 'uniqCombined64State': ('uniqCombined64', 'State'), 'groupUniqArrayState': ('groupUniqArray', 'State'), 'quantileTDigestState': ('quantileTDigest', 'State'), 'uniqCombinedState': ('uniqCombined', 'State'), 'cramersVBiasCorrectedState': ('cramersVBiasCorrected', 'State'), 'first_valueState': ('first_value', 'State'), 'skewSampState': ('skewSamp', 'State'), 'uniqUpToState': ('uniqUpTo', 'State'), 'groupArraySampleState': ('groupArraySample', 'State'), 'groupArrayMovingAvgState': ('groupArrayMovingAvg', 'State'), 'skewPopState': ('skewPop', 'State'), 'groupBitXorState': ('groupBitXor', 'State'), 'quantileTimingWeightedState': ('quantileTimingWeighted', 'State'), 'maxMapState': ('maxMap', 'State'), 'uniqExactState': ('uniqExact', 'State'), 'sumWithOverflowState': ('sumWithOverflow', 'State'), 'intervalLengthSumState': ('intervalLengthSum', 'State'), 'quantileTDigestWeightedState': ('quantileTDigestWeighted', 'State'), 'argMaxState': ('argMax', 'State'), 'deltaSumState': ('deltaSum', 'State'), 'quantilesExactHighState': ('quantilesExactHigh', 'State'), 'theilsUState': ('theilsU', 'State'), 'sumState': ('sum', 'State'), 'uniqState': ('uniq', 'State'), 'quantileExactLowState': ('quantileExactLow', 'State'), 'topKState': ('topK', 'State'), 'retentionState': ('retention', 'State'), 'quantilesTDigestWeightedState': ('quantilesTDigestWeighted', 'State'), 'quantileTimingState': ('quantileTiming', 'State'), 'sumMapState': ('sumMap', 'State'), 'mannWhitneyUTestState': ('mannWhitneyUTest', 'State'), 'rankCorrState': ('rankCorr', 'State'), 'stddevSampState': ('stddevSamp', 'State'), 'varPopState': ('varPop', 'State'), 'sequenceMatchState': ('sequenceMatch', 'State'), 'covarPopState': ('covarPop', 'State'), 'sequenceCountState': ('sequenceCount', 'State'), 'argMinState': ('argMin', 'State'), 'covarSampState': ('covarSamp', 'State'), 'quantilesTDigestState': ('quantilesTDigest', 'State'), 'groupBitOrState': ('groupBitOr', 'State'), 'largestTriangleThreeBucketsState': ('largestTriangleThreeBuckets', 'State'), 'anyLastState': ('anyLast', 'State'), 'histogramState': ('histogram', 'State'), 'groupBitmapXorState': ('groupBitmapXor', 'State'), 'last_valueState': ('last_value', 'State'), 'groupArrayLastState': ('groupArrayLast', 'State'), 'kurtPopState': ('kurtPop', 'State'), 'sparkBarState': ('sparkBar', 'State'), 'topKWeightedState': ('topKWeighted', 'State'), 'quantilesState': ('quantiles', 'State'), 'quantilesTimingWeightedState': ('quantilesTimingWeighted', 'State'), 'quantileState': ('quantile', 'State'), 'studentTTestState': ('studentTTest', 'State'), 'groupArrayState': ('groupArray', 'State'), 'groupBitAndMerge': ('groupBitAnd', 'Merge'), 'quantileExactMerge': ('quantileExact', 'Merge'), 'stddevPopMerge': ('stddevPop', 'Merge'), 'groupBitmapMerge': ('groupBitmap', 'Merge'), 'uniqThetaMerge': ('uniqTheta', 'Merge'), 'windowFunnelMerge': ('windowFunnel', 'Merge'), 'quantilesTimingMerge': ('quantilesTiming', 'Merge'), 'groupBitmapOrMerge': ('groupBitmapOr', 'Merge'), 'quantilesExactMerge': ('quantilesExact', 'Merge'), 'quantilesBFloat16Merge': ('quantilesBFloat16', 'Merge'), 'quantileBFloat16WeightedMerge': ('quantileBFloat16Weighted', 'Merge'), 'stochasticLogisticRegressionMerge': ('stochasticLogisticRegression', 'Merge'), 'groupArrayMovingSumMerge': ('groupArrayMovingSum', 'Merge'), 'contingencyMerge': ('contingency', 'Merge'), 'quantilesExactWeightedMerge': ('quantilesExactWeighted', 'Merge'), 'quantilesInterpolatedWeightedMerge': ('quantilesInterpolatedWeighted', 'Merge'), 'kurtSampMerge': ('kurtSamp', 'Merge'), 'deltaSumTimestampMerge': ('deltaSumTimestamp', 'Merge'), 'maxIntersectionsPositionMerge': ('maxIntersectionsPosition', 'Merge'), 'entropyMerge': ('entropy', 'Merge'), 'avgMerge': ('avg', 'Merge'), 'cramersVMerge': ('cramersV', 'Merge'), 'minMapMerge': ('minMap', 'Merge'), 'quantileExactWeightedMerge': ('quantileExactWeighted', 'Merge'), 'exponentialMovingAverageMerge': ('exponentialMovingAverage', 'Merge'), 'categoricalInformationValueMerge': ('categoricalInformationValue', 'Merge'), 'corrMerge': ('corr', 'Merge'), 'anyHeavyMerge': ('anyHeavy', 'Merge'), 'medianMerge': ('median', 'Merge'), 'quantileDeterministicMerge': ('quantileDeterministic', 'Merge'), 'quantileBFloat16Merge': ('quantileBFloat16', 'Merge'), 'meanZTestMerge': ('meanZTest', 'Merge'), 'quantileInterpolatedWeightedMerge': ('quantileInterpolatedWeighted', 'Merge'), 'sumCountMerge': ('sumCount', 'Merge'), 'welchTTestMerge': ('welchTTest', 'Merge'), 'simpleLinearRegressionMerge': ('simpleLinearRegression', 'Merge'), 'groupArrayInsertAtMerge': ('groupArrayInsertAt', 'Merge'), 'quantilesDeterministicMerge': ('quantilesDeterministic', 'Merge'), 'anyMerge': ('any', 'Merge'), 'boundingRatioMerge': ('boundingRatio', 'Merge'), 'minMerge': ('min', 'Merge'), 'quantilesExactLowMerge': ('quantilesExactLow', 'Merge'), 'kolmogorovSmirnovTestMerge': ('kolmogorovSmirnovTest', 'Merge'), 'groupBitmapAndMerge': ('groupBitmapAnd', 'Merge'), 'uniqHLL12Merge': ('uniqHLL12', 'Merge'), 'stochasticLinearRegressionMerge': ('stochasticLinearRegression', 'Merge'), 'maxMerge': ('max', 'Merge'), 'quantileGKMerge': ('quantileGK', 'Merge'), 'sequenceNextNodeMerge': ('sequenceNextNode', 'Merge'), 'quantilesBFloat16WeightedMerge': ('quantilesBFloat16Weighted', 'Merge'), 'countMerge': ('count', 'Merge'), 'maxIntersectionsMerge': ('maxIntersections', 'Merge'), 'sumKahanMerge': ('sumKahan', 'Merge'), 'quantilesGKMerge': ('quantilesGK', 'Merge'), 'exponentialTimeDecayedAvgMerge': ('exponentialTimeDecayedAvg', 'Merge'), 'quantileExactHighMerge': ('quantileExactHigh', 'Merge'), 'varSampMerge': ('varSamp', 'Merge'), 'avgWeightedMerge': ('avgWeighted', 'Merge'), 'uniqCombined64Merge': ('uniqCombined64', 'Merge'), 'groupUniqArrayMerge': ('groupUniqArray', 'Merge'), 'quantileTDigestMerge': ('quantileTDigest', 'Merge'), 'uniqCombinedMerge': ('uniqCombined', 'Merge'), 'cramersVBiasCorrectedMerge': ('cramersVBiasCorrected', 'Merge'), 'first_valueMerge': ('first_value', 'Merge'), 'skewSampMerge': ('skewSamp', 'Merge'), 'uniqUpToMerge': ('uniqUpTo', 'Merge'), 'groupArraySampleMerge': ('groupArraySample', 'Merge'), 'groupArrayMovingAvgMerge': ('groupArrayMovingAvg', 'Merge'), 'skewPopMerge': ('skewPop', 'Merge'), 'groupBitXorMerge': ('groupBitXor', 'Merge'), 'quantileTimingWeightedMerge': ('quantileTimingWeighted', 'Merge'), 'maxMapMerge': ('maxMap', 'Merge'), 'uniqExactMerge': ('uniqExact', 'Merge'), 'sumWithOverflowMerge': ('sumWithOverflow', 'Merge'), 'intervalLengthSumMerge': ('intervalLengthSum', 'Merge'), 'quantileTDigestWeightedMerge': ('quantileTDigestWeighted', 'Merge'), 'argMaxMerge': ('argMax', 'Merge'), 'deltaSumMerge': ('deltaSum', 'Merge'), 'quantilesExactHighMerge': ('quantilesExactHigh', 'Merge'), 'theilsUMerge': ('theilsU', 'Merge'), 'sumMerge': ('sum', 'Merge'), 'uniqMerge': ('uniq', 'Merge'), 'quantileExactLowMerge': ('quantileExactLow', 'Merge'), 'topKMerge': ('topK', 'Merge'), 'retentionMerge': ('retention', 'Merge'), 'quantilesTDigestWeightedMerge': ('quantilesTDigestWeighted', 'Merge'), 'quantileTimingMerge': ('quantileTiming', 'Merge'), 'sumMapMerge': ('sumMap', 'Merge'), 'mannWhitneyUTestMerge': ('mannWhitneyUTest', 'Merge'), 'rankCorrMerge': ('rankCorr', 'Merge'), 'stddevSampMerge': ('stddevSamp', 'Merge'), 'varPopMerge': ('varPop', 'Merge'), 'sequenceMatchMerge': ('sequenceMatch', 'Merge'), 'covarPopMerge': ('covarPop', 'Merge'), 'sequenceCountMerge': ('sequenceCount', 'Merge'), 'argMinMerge': ('argMin', 'Merge'), 'covarSampMerge': ('covarSamp', 'Merge'), 'quantilesTDigestMerge': ('quantilesTDigest', 'Merge'), 'groupBitOrMerge': ('groupBitOr', 'Merge'), 'largestTriangleThreeBucketsMerge': ('largestTriangleThreeBuckets', 'Merge'), 'anyLastMerge': ('anyLast', 'Merge'), 'histogramMerge': ('histogram', 'Merge'), 'groupBitmapXorMerge': ('groupBitmapXor', 'Merge'), 'last_valueMerge': ('last_value', 'Merge'), 'groupArrayLastMerge': ('groupArrayLast', 'Merge'), 'kurtPopMerge': ('kurtPop', 'Merge'), 'sparkBarMerge': ('sparkBar', 'Merge'), 'topKWeightedMerge': ('topKWeighted', 'Merge'), 'quantilesMerge': ('quantiles', 'Merge'), 'quantilesTimingWeightedMerge': ('quantilesTimingWeighted', 'Merge'), 'quantileMerge': ('quantile', 'Merge'), 'studentTTestMerge': ('studentTTest', 'Merge'), 'groupArrayMerge': ('groupArray', 'Merge'), 'groupBitAndMergeState': ('groupBitAnd', 'MergeState'), 'quantileExactMergeState': ('quantileExact', 'MergeState'), 'stddevPopMergeState': ('stddevPop', 'MergeState'), 'groupBitmapMergeState': ('groupBitmap', 'MergeState'), 'uniqThetaMergeState': ('uniqTheta', 'MergeState'), 'windowFunnelMergeState': ('windowFunnel', 'MergeState'), 'quantilesTimingMergeState': ('quantilesTiming', 'MergeState'), 'groupBitmapOrMergeState': ('groupBitmapOr', 'MergeState'), 'quantilesExactMergeState': ('quantilesExact', 'MergeState'), 'quantilesBFloat16MergeState': ('quantilesBFloat16', 'MergeState'), 'quantileBFloat16WeightedMergeState': ('quantileBFloat16Weighted', 'MergeState'), 'stochasticLogisticRegressionMergeState': ('stochasticLogisticRegression', 'MergeState'), 'groupArrayMovingSumMergeState': ('groupArrayMovingSum', 'MergeState'), 'contingencyMergeState': ('contingency', 'MergeState'), 'quantilesExactWeightedMergeState': ('quantilesExactWeighted', 'MergeState'), 'quantilesInterpolatedWeightedMergeState': ('quantilesInterpolatedWeighted', 'MergeState'), 'kurtSampMergeState': ('kurtSamp', 'MergeState'), 'deltaSumTimestampMergeState': ('deltaSumTimestamp', 'MergeState'), 'maxIntersectionsPositionMergeState': ('maxIntersectionsPosition', 'MergeState'), 'entropyMergeState': ('entropy', 'MergeState'), 'avgMergeState': ('avg', 'MergeState'), 'cramersVMergeState': ('cramersV', 'MergeState'), 'minMapMergeState': ('minMap', 'MergeState'), 'quantileExactWeightedMergeState': ('quantileExactWeighted', 'MergeState'), 'exponentialMovingAverageMergeState': ('exponentialMovingAverage', 'MergeState'), 'categoricalInformationValueMergeState': ('categoricalInformationValue', 'MergeState'), 'corrMergeState': ('corr', 'MergeState'), 'anyHeavyMergeState': ('anyHeavy', 'MergeState'), 'medianMergeState': ('median', 'MergeState'), 'quantileDeterministicMergeState': ('quantileDeterministic', 'MergeState'), 'quantileBFloat16MergeState': ('quantileBFloat16', 'MergeState'), 'meanZTestMergeState': ('meanZTest', 'MergeState'), 'quantileInterpolatedWeightedMergeState': ('quantileInterpolatedWeighted', 'MergeState'), 'sumCountMergeState': ('sumCount', 'MergeState'), 'welchTTestMergeState': ('welchTTest', 'MergeState'), 'simpleLinearRegressionMergeState': ('simpleLinearRegression', 'MergeState'), 'groupArrayInsertAtMergeState': ('groupArrayInsertAt', 'MergeState'), 'quantilesDeterministicMergeState': ('quantilesDeterministic', 'MergeState'), 'anyMergeState': ('any', 'MergeState'), 'boundingRatioMergeState': ('boundingRatio', 'MergeState'), 'minMergeState': ('min', 'MergeState'), 'quantilesExactLowMergeState': ('quantilesExactLow', 'MergeState'), 'kolmogorovSmirnovTestMergeState': ('kolmogorovSmirnovTest', 'MergeState'), 'groupBitmapAndMergeState': ('groupBitmapAnd', 'MergeState'), 'uniqHLL12MergeState': ('uniqHLL12', 'MergeState'), 'stochasticLinearRegressionMergeState': ('stochasticLinearRegression', 'MergeState'), 'maxMergeState': ('max', 'MergeState'), 'quantileGKMergeState': ('quantileGK', 'MergeState'), 'sequenceNextNodeMergeState': ('sequenceNextNode', 'MergeState'), 'quantilesBFloat16WeightedMergeState': ('quantilesBFloat16Weighted', 'MergeState'), 'countMergeState': ('count', 'MergeState'), 'maxIntersectionsMergeState': ('maxIntersections', 'MergeState'), 'sumKahanMergeState': ('sumKahan', 'MergeState'), 'quantilesGKMergeState': ('quantilesGK', 'MergeState'), 'exponentialTimeDecayedAvgMergeState': ('exponentialTimeDecayedAvg', 'MergeState'), 'quantileExactHighMergeState': ('quantileExactHigh', 'MergeState'), 'varSampMergeState': ('varSamp', 'MergeState'), 'avgWeightedMergeState': ('avgWeighted', 'MergeState'), 'uniqCombined64MergeState': ('uniqCombined64', 'MergeState'), 'groupUniqArrayMergeState': ('groupUniqArray', 'MergeState'), 'quantileTDigestMergeState': ('quantileTDigest', 'MergeState'), 'uniqCombinedMergeState': ('uniqCombined', 'MergeState'), 'cramersVBiasCorrectedMergeState': ('cramersVBiasCorrected', 'MergeState'), 'first_valueMergeState': ('first_value', 'MergeState'), 'skewSampMergeState': ('skewSamp', 'MergeState'), 'uniqUpToMergeState': ('uniqUpTo', 'MergeState'), 'groupArraySampleMergeState': ('groupArraySample', 'MergeState'), 'groupArrayMovingAvgMergeState': ('groupArrayMovingAvg', 'MergeState'), 'skewPopMergeState': ('skewPop', 'MergeState'), 'groupBitXorMergeState': ('groupBitXor', 'MergeState'), 'quantileTimingWeightedMergeState': ('quantileTimingWeighted', 'MergeState'), 'maxMapMergeState': ('maxMap', 'MergeState'), 'uniqExactMergeState': ('uniqExact', 'MergeState'), 'sumWithOverflowMergeState': ('sumWithOverflow', 'MergeState'), 'intervalLengthSumMergeState': ('intervalLengthSum', 'MergeState'), 'quantileTDigestWeightedMergeState': ('quantileTDigestWeighted', 'MergeState'), 'argMaxMergeState': ('argMax', 'MergeState'), 'deltaSumMergeState': ('deltaSum', 'MergeState'), 'quantilesExactHighMergeState': ('quantilesExactHigh', 'MergeState'), 'theilsUMergeState': ('theilsU', 'MergeState'), 'sumMergeState': ('sum', 'MergeState'), 'uniqMergeState': ('uniq', 'MergeState'), 'quantileExactLowMergeState': ('quantileExactLow', 'MergeState'), 'topKMergeState': ('topK', 'MergeState'), 'retentionMergeState': ('retention', 'MergeState'), 'quantilesTDigestWeightedMergeState': ('quantilesTDigestWeighted', 'MergeState'), 'quantileTimingMergeState': ('quantileTiming', 'MergeState'), 'sumMapMergeState': ('sumMap', 'MergeState'), 'mannWhitneyUTestMergeState': ('mannWhitneyUTest', 'MergeState'), 'rankCorrMergeState': ('rankCorr', 'MergeState'), 'stddevSampMergeState': ('stddevSamp', 'MergeState'), 'varPopMergeState': ('varPop', 'MergeState'), 'sequenceMatchMergeState': ('sequenceMatch', 'MergeState'), 'covarPopMergeState': ('covarPop', 'MergeState'), 'sequenceCountMergeState': ('sequenceCount', 'MergeState'), 'argMinMergeState': ('argMin', 'MergeState'), 'covarSampMergeState': ('covarSamp', 'MergeState'), 'quantilesTDigestMergeState': ('quantilesTDigest', 'MergeState'), 'groupBitOrMergeState': ('groupBitOr', 'MergeState'), 'largestTriangleThreeBucketsMergeState': ('largestTriangleThreeBuckets', 'MergeState'), 'anyLastMergeState': ('anyLast', 'MergeState'), 'histogramMergeState': ('histogram', 'MergeState'), 'groupBitmapXorMergeState': ('groupBitmapXor', 'MergeState'), 'last_valueMergeState': ('last_value', 'MergeState'), 'groupArrayLastMergeState': ('groupArrayLast', 'MergeState'), 'kurtPopMergeState': ('kurtPop', 'MergeState'), 'sparkBarMergeState': ('sparkBar', 'MergeState'), 'topKWeightedMergeState': ('topKWeighted', 'MergeState'), 'quantilesMergeState': ('quantiles', 'MergeState'), 'quantilesTimingWeightedMergeState': ('quantilesTimingWeighted', 'MergeState'), 'quantileMergeState': ('quantile', 'MergeState'), 'studentTTestMergeState': ('studentTTest', 'MergeState'), 'groupArrayMergeState': ('groupArray', 'MergeState'), 'groupBitAndForEach': ('groupBitAnd', 'ForEach'), 'quantileExactForEach': ('quantileExact', 'ForEach'), 'stddevPopForEach': ('stddevPop', 'ForEach'), 'groupBitmapForEach': ('groupBitmap', 'ForEach'), 'uniqThetaForEach': ('uniqTheta', 'ForEach'), 'windowFunnelForEach': ('windowFunnel', 'ForEach'), 'quantilesTimingForEach': ('quantilesTiming', 'ForEach'), 'groupBitmapOrForEach': ('groupBitmapOr', 'ForEach'), 'quantilesExactForEach': ('quantilesExact', 'ForEach'), 'quantilesBFloat16ForEach': ('quantilesBFloat16', 'ForEach'), 'quantileBFloat16WeightedForEach': ('quantileBFloat16Weighted', 'ForEach'), 'stochasticLogisticRegressionForEach': ('stochasticLogisticRegression', 'ForEach'), 'groupArrayMovingSumForEach': ('groupArrayMovingSum', 'ForEach'), 'contingencyForEach': ('contingency', 'ForEach'), 'quantilesExactWeightedForEach': ('quantilesExactWeighted', 'ForEach'), 'quantilesInterpolatedWeightedForEach': ('quantilesInterpolatedWeighted', 'ForEach'), 'kurtSampForEach': ('kurtSamp', 'ForEach'), 'deltaSumTimestampForEach': ('deltaSumTimestamp', 'ForEach'), 'maxIntersectionsPositionForEach': ('maxIntersectionsPosition', 'ForEach'), 'entropyForEach': ('entropy', 'ForEach'), 'avgForEach': ('avg', 'ForEach'), 'cramersVForEach': ('cramersV', 'ForEach'), 'minMapForEach': ('minMap', 'ForEach'), 'quantileExactWeightedForEach': ('quantileExactWeighted', 'ForEach'), 'exponentialMovingAverageForEach': ('exponentialMovingAverage', 'ForEach'), 'categoricalInformationValueForEach': ('categoricalInformationValue', 'ForEach'), 'corrForEach': ('corr', 'ForEach'), 'anyHeavyForEach': ('anyHeavy', 'ForEach'), 'medianForEach': ('median', 'ForEach'), 'quantileDeterministicForEach': ('quantileDeterministic', 'ForEach'), 'quantileBFloat16ForEach': ('quantileBFloat16', 'ForEach'), 'meanZTestForEach': ('meanZTest', 'ForEach'), 'quantileInterpolatedWeightedForEach': ('quantileInterpolatedWeighted', 'ForEach'), 'sumCountForEach': ('sumCount', 'ForEach'), 'welchTTestForEach': ('welchTTest', 'ForEach'), 'simpleLinearRegressionForEach': ('simpleLinearRegression', 'ForEach'), 'groupArrayInsertAtForEach': ('groupArrayInsertAt', 'ForEach'), 'quantilesDeterministicForEach': ('quantilesDeterministic', 'ForEach'), 'anyForEach': ('any', 'ForEach'), 'boundingRatioForEach': ('boundingRatio', 'ForEach'), 'minForEach': ('min', 'ForEach'), 'quantilesExactLowForEach': ('quantilesExactLow', 'ForEach'), 'kolmogorovSmirnovTestForEach': ('kolmogorovSmirnovTest', 'ForEach'), 'groupBitmapAndForEach': ('groupBitmapAnd', 'ForEach'), 'uniqHLL12ForEach': ('uniqHLL12', 'ForEach'), 'stochasticLinearRegressionForEach': ('stochasticLinearRegression', 'ForEach'), 'maxForEach': ('max', 'ForEach'), 'quantileGKForEach': ('quantileGK', 'ForEach'), 'sequenceNextNodeForEach': ('sequenceNextNode', 'ForEach'), 'quantilesBFloat16WeightedForEach': ('quantilesBFloat16Weighted', 'ForEach'), 'countForEach': ('count', 'ForEach'), 'maxIntersectionsForEach': ('maxIntersections', 'ForEach'), 'sumKahanForEach': ('sumKahan', 'ForEach'), 'quantilesGKForEach': ('quantilesGK', 'ForEach'), 'exponentialTimeDecayedAvgForEach': ('exponentialTimeDecayedAvg', 'ForEach'), 'quantileExactHighForEach': ('quantileExactHigh', 'ForEach'), 'varSampForEach': ('varSamp', 'ForEach'), 'avgWeightedForEach': ('avgWeighted', 'ForEach'), 'uniqCombined64ForEach': ('uniqCombined64', 'ForEach'), 'groupUniqArrayForEach': ('groupUniqArray', 'ForEach'), 'quantileTDigestForEach': ('quantileTDigest', 'ForEach'), 'uniqCombinedForEach': ('uniqCombined', 'ForEach'), 'cramersVBiasCorrectedForEach': ('cramersVBiasCorrected', 'ForEach'), 'first_valueForEach': ('first_value', 'ForEach'), 'skewSampForEach': ('skewSamp', 'ForEach'), 'uniqUpToForEach': ('uniqUpTo', 'ForEach'), 'groupArraySampleForEach': ('groupArraySample', 'ForEach'), 'groupArrayMovingAvgForEach': ('groupArrayMovingAvg', 'ForEach'), 'skewPopForEach': ('skewPop', 'ForEach'), 'groupBitXorForEach': ('groupBitXor', 'ForEach'), 'quantileTimingWeightedForEach': ('quantileTimingWeighted', 'ForEach'), 'maxMapForEach': ('maxMap', 'ForEach'), 'uniqExactForEach': ('uniqExact', 'ForEach'), 'sumWithOverflowForEach': ('sumWithOverflow', 'ForEach'), 'intervalLengthSumForEach': ('intervalLengthSum', 'ForEach'), 'quantileTDigestWeightedForEach': ('quantileTDigestWeighted', 'ForEach'), 'argMaxForEach': ('argMax', 'ForEach'), 'deltaSumForEach': ('deltaSum', 'ForEach'), 'quantilesExactHighForEach': ('quantilesExactHigh', 'ForEach'), 'theilsUForEach': ('theilsU', 'ForEach'), 'sumForEach': ('sum', 'ForEach'), 'uniqForEach': ('uniq', 'ForEach'), 'quantileExactLowForEach': ('quantileExactLow', 'ForEach'), 'topKForEach': ('topK', 'ForEach'), 'retentionForEach': ('retention', 'ForEach'), 'quantilesTDigestWeightedForEach': ('quantilesTDigestWeighted', 'ForEach'), 'quantileTimingForEach': ('quantileTiming', 'ForEach'), 'sumMapForEach': ('sumMap', 'ForEach'), 'mannWhitneyUTestForEach': ('mannWhitneyUTest', 'ForEach'), 'rankCorrForEach': ('rankCorr', 'ForEach'), 'stddevSampForEach': ('stddevSamp', 'ForEach'), 'varPopForEach': ('varPop', 'ForEach'), 'sequenceMatchForEach': ('sequenceMatch', 'ForEach'), 'covarPopForEach': ('covarPop', 'ForEach'), 'sequenceCountForEach': ('sequenceCount', 'ForEach'), 'argMinForEach': ('argMin', 'ForEach'), 'covarSampForEach': ('covarSamp', 'ForEach'), 'quantilesTDigestForEach': ('quantilesTDigest', 'ForEach'), 'groupBitOrForEach': ('groupBitOr', 'ForEach'), 'largestTriangleThreeBucketsForEach': ('largestTriangleThreeBuckets', 'ForEach'), 'anyLastForEach': ('anyLast', 'ForEach'), 'histogramForEach': ('histogram', 'ForEach'), 'groupBitmapXorForEach': ('groupBitmapXor', 'ForEach'), 'last_valueForEach': ('last_value', 'ForEach'), 'groupArrayLastForEach': ('groupArrayLast', 'ForEach'), 'kurtPopForEach': ('kurtPop', 'ForEach'), 'sparkBarForEach': ('sparkBar', 'ForEach'), 'topKWeightedForEach': ('topKWeighted', 'ForEach'), 'quantilesForEach': ('quantiles', 'ForEach'), 'quantilesTimingWeightedForEach': ('quantilesTimingWeighted', 'ForEach'), 'quantileForEach': ('quantile', 'ForEach'), 'studentTTestForEach': ('studentTTest', 'ForEach'), 'groupArrayForEach': ('groupArray', 'ForEach'), 'groupBitAndDistinct': ('groupBitAnd', 'Distinct'), 'quantileExactDistinct': ('quantileExact', 'Distinct'), 'stddevPopDistinct': ('stddevPop', 'Distinct'), 'groupBitmapDistinct': ('groupBitmap', 'Distinct'), 'uniqThetaDistinct': ('uniqTheta', 'Distinct'), 'windowFunnelDistinct': ('windowFunnel', 'Distinct'), 'quantilesTimingDistinct': ('quantilesTiming', 'Distinct'), 'groupBitmapOrDistinct': ('groupBitmapOr', 'Distinct'), 'quantilesExactDistinct': ('quantilesExact', 'Distinct'), 'quantilesBFloat16Distinct': ('quantilesBFloat16', 'Distinct'), 'quantileBFloat16WeightedDistinct': ('quantileBFloat16Weighted', 'Distinct'), 'stochasticLogisticRegressionDistinct': ('stochasticLogisticRegression', 'Distinct'), 'groupArrayMovingSumDistinct': ('groupArrayMovingSum', 'Distinct'), 'contingencyDistinct': ('contingency', 'Distinct'), 'quantilesExactWeightedDistinct': ('quantilesExactWeighted', 'Distinct'), 'quantilesInterpolatedWeightedDistinct': ('quantilesInterpolatedWeighted', 'Distinct'), 'kurtSampDistinct': ('kurtSamp', 'Distinct'), 'deltaSumTimestampDistinct': ('deltaSumTimestamp', 'Distinct'), 'maxIntersectionsPositionDistinct': ('maxIntersectionsPosition', 'Distinct'), 'entropyDistinct': ('entropy', 'Distinct'), 'avgDistinct': ('avg', 'Distinct'), 'cramersVDistinct': ('cramersV', 'Distinct'), 'minMapDistinct': ('minMap', 'Distinct'), 'quantileExactWeightedDistinct': ('quantileExactWeighted', 'Distinct'), 'exponentialMovingAverageDistinct': ('exponentialMovingAverage', 'Distinct'), 'categoricalInformationValueDistinct': ('categoricalInformationValue', 'Distinct'), 'corrDistinct': ('corr', 'Distinct'), 'anyHeavyDistinct': ('anyHeavy', 'Distinct'), 'medianDistinct': ('median', 'Distinct'), 'quantileDeterministicDistinct': ('quantileDeterministic', 'Distinct'), 'quantileBFloat16Distinct': ('quantileBFloat16', 'Distinct'), 'meanZTestDistinct': ('meanZTest', 'Distinct'), 'quantileInterpolatedWeightedDistinct': ('quantileInterpolatedWeighted', 'Distinct'), 'sumCountDistinct': ('sumCount', 'Distinct'), 'welchTTestDistinct': ('welchTTest', 'Distinct'), 'simpleLinearRegressionDistinct': ('simpleLinearRegression', 'Distinct'), 'groupArrayInsertAtDistinct': ('groupArrayInsertAt', 'Distinct'), 'quantilesDeterministicDistinct': ('quantilesDeterministic', 'Distinct'), 'anyDistinct': ('any', 'Distinct'), 'boundingRatioDistinct': ('boundingRatio', 'Distinct'), 'minDistinct': ('min', 'Distinct'), 'quantilesExactLowDistinct': ('quantilesExactLow', 'Distinct'), 'kolmogorovSmirnovTestDistinct': ('kolmogorovSmirnovTest', 'Distinct'), 'groupBitmapAndDistinct': ('groupBitmapAnd', 'Distinct'), 'uniqHLL12Distinct': ('uniqHLL12', 'Distinct'), 'stochasticLinearRegressionDistinct': ('stochasticLinearRegression', 'Distinct'), 'maxDistinct': ('max', 'Distinct'), 'quantileGKDistinct': ('quantileGK', 'Distinct'), 'sequenceNextNodeDistinct': ('sequenceNextNode', 'Distinct'), 'quantilesBFloat16WeightedDistinct': ('quantilesBFloat16Weighted', 'Distinct'), 'countDistinct': ('count', 'Distinct'), 'maxIntersectionsDistinct': ('maxIntersections', 'Distinct'), 'sumKahanDistinct': ('sumKahan', 'Distinct'), 'quantilesGKDistinct': ('quantilesGK', 'Distinct'), 'exponentialTimeDecayedAvgDistinct': ('exponentialTimeDecayedAvg', 'Distinct'), 'quantileExactHighDistinct': ('quantileExactHigh', 'Distinct'), 'varSampDistinct': ('varSamp', 'Distinct'), 'avgWeightedDistinct': ('avgWeighted', 'Distinct'), 'uniqCombined64Distinct': ('uniqCombined64', 'Distinct'), 'groupUniqArrayDistinct': ('groupUniqArray', 'Distinct'), 'quantileTDigestDistinct': ('quantileTDigest', 'Distinct'), 'uniqCombinedDistinct': ('uniqCombined', 'Distinct'), 'cramersVBiasCorrectedDistinct': ('cramersVBiasCorrected', 'Distinct'), 'first_valueDistinct': ('first_value', 'Distinct'), 'skewSampDistinct': ('skewSamp', 'Distinct'), 'uniqUpToDistinct': ('uniqUpTo', 'Distinct'), 'groupArraySampleDistinct': ('groupArraySample', 'Distinct'), 'groupArrayMovingAvgDistinct': ('groupArrayMovingAvg', 'Distinct'), 'skewPopDistinct': ('skewPop', 'Distinct'), 'groupBitXorDistinct': ('groupBitXor', 'Distinct'), 'quantileTimingWeightedDistinct': ('quantileTimingWeighted', 'Distinct'), 'maxMapDistinct': ('maxMap', 'Distinct'), 'uniqExactDistinct': ('uniqExact', 'Distinct'), 'sumWithOverflowDistinct': ('sumWithOverflow', 'Distinct'), 'intervalLengthSumDistinct': ('intervalLengthSum', 'Distinct'), 'quantileTDigestWeightedDistinct': ('quantileTDigestWeighted', 'Distinct'), 'argMaxDistinct': ('argMax', 'Distinct'), 'deltaSumDistinct': ('deltaSum', 'Distinct'), 'quantilesExactHighDistinct': ('quantilesExactHigh', 'Distinct'), 'theilsUDistinct': ('theilsU', 'Distinct'), 'sumDistinct': ('sum', 'Distinct'), 'uniqDistinct': ('uniq', 'Distinct'), 'quantileExactLowDistinct': ('quantileExactLow', 'Distinct'), 'topKDistinct': ('topK', 'Distinct'), 'retentionDistinct': ('retention', 'Distinct'), 'quantilesTDigestWeightedDistinct': ('quantilesTDigestWeighted', 'Distinct'), 'quantileTimingDistinct': ('quantileTiming', 'Distinct'), 'sumMapDistinct': ('sumMap', 'Distinct'), 'mannWhitneyUTestDistinct': ('mannWhitneyUTest', 'Distinct'), 'rankCorrDistinct': ('rankCorr', 'Distinct'), 'stddevSampDistinct': ('stddevSamp', 'Distinct'), 'varPopDistinct': ('varPop', 'Distinct'), 'sequenceMatchDistinct': ('sequenceMatch', 'Distinct'), 'covarPopDistinct': ('covarPop', 'Distinct'), 'sequenceCountDistinct': ('sequenceCount', 'Distinct'), 'argMinDistinct': ('argMin', 'Distinct'), 'covarSampDistinct': ('covarSamp', 'Distinct'), 'quantilesTDigestDistinct': ('quantilesTDigest', 'Distinct'), 'groupBitOrDistinct': ('groupBitOr', 'Distinct'), 'largestTriangleThreeBucketsDistinct': ('largestTriangleThreeBuckets', 'Distinct'), 'anyLastDistinct': ('anyLast', 'Distinct'), 'histogramDistinct': ('histogram', 'Distinct'), 'groupBitmapXorDistinct': ('groupBitmapXor', 'Distinct'), 'last_valueDistinct': ('last_value', 'Distinct'), 'groupArrayLastDistinct': ('groupArrayLast', 'Distinct'), 'kurtPopDistinct': ('kurtPop', 'Distinct'), 'sparkBarDistinct': ('sparkBar', 'Distinct'), 'topKWeightedDistinct': ('topKWeighted', 'Distinct'), 'quantilesDistinct': ('quantiles', 'Distinct'), 'quantilesTimingWeightedDistinct': ('quantilesTimingWeighted', 'Distinct'), 'quantileDistinct': ('quantile', 'Distinct'), 'studentTTestDistinct': ('studentTTest', 'Distinct'), 'groupArrayDistinct': ('groupArray', 'Distinct'), 'groupBitAndOrDefault': ('groupBitAnd', 'OrDefault'), 'quantileExactOrDefault': ('quantileExact', 'OrDefault'), 'stddevPopOrDefault': ('stddevPop', 'OrDefault'), 'groupBitmapOrDefault': ('groupBitmap', 'OrDefault'), 'uniqThetaOrDefault': ('uniqTheta', 'OrDefault'), 'windowFunnelOrDefault': ('windowFunnel', 'OrDefault'), 'quantilesTimingOrDefault': ('quantilesTiming', 'OrDefault'), 'groupBitmapOrOrDefault': ('groupBitmapOr', 'OrDefault'), 'quantilesExactOrDefault': ('quantilesExact', 'OrDefault'), 'quantilesBFloat16OrDefault': ('quantilesBFloat16', 'OrDefault'), 'quantileBFloat16WeightedOrDefault': ('quantileBFloat16Weighted', 'OrDefault'), 'stochasticLogisticRegressionOrDefault': ('stochasticLogisticRegression', 'OrDefault'), 'groupArrayMovingSumOrDefault': ('groupArrayMovingSum', 'OrDefault'), 'contingencyOrDefault': ('contingency', 'OrDefault'), 'quantilesExactWeightedOrDefault': ('quantilesExactWeighted', 'OrDefault'), 'quantilesInterpolatedWeightedOrDefault': ('quantilesInterpolatedWeighted', 'OrDefault'), 'kurtSampOrDefault': ('kurtSamp', 'OrDefault'), 'deltaSumTimestampOrDefault': ('deltaSumTimestamp', 'OrDefault'), 'maxIntersectionsPositionOrDefault': ('maxIntersectionsPosition', 'OrDefault'), 'entropyOrDefault': ('entropy', 'OrDefault'), 'avgOrDefault': ('avg', 'OrDefault'), 'cramersVOrDefault': ('cramersV', 'OrDefault'), 'minMapOrDefault': ('minMap', 'OrDefault'), 'quantileExactWeightedOrDefault': ('quantileExactWeighted', 'OrDefault'), 'exponentialMovingAverageOrDefault': ('exponentialMovingAverage', 'OrDefault'), 'categoricalInformationValueOrDefault': ('categoricalInformationValue', 'OrDefault'), 'corrOrDefault': ('corr', 'OrDefault'), 'anyHeavyOrDefault': ('anyHeavy', 'OrDefault'), 'medianOrDefault': ('median', 'OrDefault'), 'quantileDeterministicOrDefault': ('quantileDeterministic', 'OrDefault'), 'quantileBFloat16OrDefault': ('quantileBFloat16', 'OrDefault'), 'meanZTestOrDefault': ('meanZTest', 'OrDefault'), 'quantileInterpolatedWeightedOrDefault': ('quantileInterpolatedWeighted', 'OrDefault'), 'sumCountOrDefault': ('sumCount', 'OrDefault'), 'welchTTestOrDefault': ('welchTTest', 'OrDefault'), 'simpleLinearRegressionOrDefault': ('simpleLinearRegression', 'OrDefault'), 'groupArrayInsertAtOrDefault': ('groupArrayInsertAt', 'OrDefault'), 'quantilesDeterministicOrDefault': ('quantilesDeterministic', 'OrDefault'), 'anyOrDefault': ('any', 'OrDefault'), 'boundingRatioOrDefault': ('boundingRatio', 'OrDefault'), 'minOrDefault': ('min', 'OrDefault'), 'quantilesExactLowOrDefault': ('quantilesExactLow', 'OrDefault'), 'kolmogorovSmirnovTestOrDefault': ('kolmogorovSmirnovTest', 'OrDefault'), 'groupBitmapAndOrDefault': ('groupBitmapAnd', 'OrDefault'), 'uniqHLL12OrDefault': ('uniqHLL12', 'OrDefault'), 'stochasticLinearRegressionOrDefault': ('stochasticLinearRegression', 'OrDefault'), 'maxOrDefault': ('max', 'OrDefault'), 'quantileGKOrDefault': ('quantileGK', 'OrDefault'), 'sequenceNextNodeOrDefault': ('sequenceNextNode', 'OrDefault'), 'quantilesBFloat16WeightedOrDefault': ('quantilesBFloat16Weighted', 'OrDefault'), 'countOrDefault': ('count', 'OrDefault'), 'maxIntersectionsOrDefault': ('maxIntersections', 'OrDefault'), 'sumKahanOrDefault': ('sumKahan', 'OrDefault'), 'quantilesGKOrDefault': ('quantilesGK', 'OrDefault'), 'exponentialTimeDecayedAvgOrDefault': ('exponentialTimeDecayedAvg', 'OrDefault'), 'quantileExactHighOrDefault': ('quantileExactHigh', 'OrDefault'), 'varSampOrDefault': ('varSamp', 'OrDefault'), 'avgWeightedOrDefault': ('avgWeighted', 'OrDefault'), 'uniqCombined64OrDefault': ('uniqCombined64', 'OrDefault'), 'groupUniqArrayOrDefault': ('groupUniqArray', 'OrDefault'), 'quantileTDigestOrDefault': ('quantileTDigest', 'OrDefault'), 'uniqCombinedOrDefault': ('uniqCombined', 'OrDefault'), 'cramersVBiasCorrectedOrDefault': ('cramersVBiasCorrected', 'OrDefault'), 'first_valueOrDefault': ('first_value', 'OrDefault'), 'skewSampOrDefault': ('skewSamp', 'OrDefault'), 'uniqUpToOrDefault': ('uniqUpTo', 'OrDefault'), 'groupArraySampleOrDefault': ('groupArraySample', 'OrDefault'), 'groupArrayMovingAvgOrDefault': ('groupArrayMovingAvg', 'OrDefault'), 'skewPopOrDefault': ('skewPop', 'OrDefault'), 'groupBitXorOrDefault': ('groupBitXor', 'OrDefault'), 'quantileTimingWeightedOrDefault': ('quantileTimingWeighted', 'OrDefault'), 'maxMapOrDefault': ('maxMap', 'OrDefault'), 'uniqExactOrDefault': ('uniqExact', 'OrDefault'), 'sumWithOverflowOrDefault': ('sumWithOverflow', 'OrDefault'), 'intervalLengthSumOrDefault': ('intervalLengthSum', 'OrDefault'), 'quantileTDigestWeightedOrDefault': ('quantileTDigestWeighted', 'OrDefault'), 'argMaxOrDefault': ('argMax', 'OrDefault'), 'deltaSumOrDefault': ('deltaSum', 'OrDefault'), 'quantilesExactHighOrDefault': ('quantilesExactHigh', 'OrDefault'), 'theilsUOrDefault': ('theilsU', 'OrDefault'), 'sumOrDefault': ('sum', 'OrDefault'), 'uniqOrDefault': ('uniq', 'OrDefault'), 'quantileExactLowOrDefault': ('quantileExactLow', 'OrDefault'), 'topKOrDefault': ('topK', 'OrDefault'), 'retentionOrDefault': ('retention', 'OrDefault'), 'quantilesTDigestWeightedOrDefault': ('quantilesTDigestWeighted', 'OrDefault'), 'quantileTimingOrDefault': ('quantileTiming', 'OrDefault'), 'sumMapOrDefault': ('sumMap', 'OrDefault'), 'mannWhitneyUTestOrDefault': ('mannWhitneyUTest', 'OrDefault'), 'rankCorrOrDefault': ('rankCorr', 'OrDefault'), 'stddevSampOrDefault': ('stddevSamp', 'OrDefault'), 'varPopOrDefault': ('varPop', 'OrDefault'), 'sequenceMatchOrDefault': ('sequenceMatch', 'OrDefault'), 'covarPopOrDefault': ('covarPop', 'OrDefault'), 'sequenceCountOrDefault': ('sequenceCount', 'OrDefault'), 'argMinOrDefault': ('argMin', 'OrDefault'), 'covarSampOrDefault': ('covarSamp', 'OrDefault'), 'quantilesTDigestOrDefault': ('quantilesTDigest', 'OrDefault'), 'groupBitOrOrDefault': ('groupBitOr', 'OrDefault'), 'largestTriangleThreeBucketsOrDefault': ('largestTriangleThreeBuckets', 'OrDefault'), 'anyLastOrDefault': ('anyLast', 'OrDefault'), 'histogramOrDefault': ('histogram', 'OrDefault'), 'groupBitmapXorOrDefault': ('groupBitmapXor', 'OrDefault'), 'last_valueOrDefault': ('last_value', 'OrDefault'), 'groupArrayLastOrDefault': ('groupArrayLast', 'OrDefault'), 'kurtPopOrDefault': ('kurtPop', 'OrDefault'), 'sparkBarOrDefault': ('sparkBar', 'OrDefault'), 'topKWeightedOrDefault': ('topKWeighted', 'OrDefault'), 'quantilesOrDefault': ('quantiles', 'OrDefault'), 'quantilesTimingWeightedOrDefault': ('quantilesTimingWeighted', 'OrDefault'), 'quantileOrDefault': ('quantile', 'OrDefault'), 'studentTTestOrDefault': ('studentTTest', 'OrDefault'), 'groupArrayOrDefault': ('groupArray', 'OrDefault'), 'groupBitAndOrNull': ('groupBitAnd', 'OrNull'), 'quantileExactOrNull': ('quantileExact', 'OrNull'), 'stddevPopOrNull': ('stddevPop', 'OrNull'), 'groupBitmapOrNull': ('groupBitmap', 'OrNull'), 'uniqThetaOrNull': ('uniqTheta', 'OrNull'), 'windowFunnelOrNull': ('windowFunnel', 'OrNull'), 'quantilesTimingOrNull': ('quantilesTiming', 'OrNull'), 'groupBitmapOrOrNull': ('groupBitmapOr', 'OrNull'), 'quantilesExactOrNull': ('quantilesExact', 'OrNull'), 'quantilesBFloat16OrNull': ('quantilesBFloat16', 'OrNull'), 'quantileBFloat16WeightedOrNull': ('quantileBFloat16Weighted', 'OrNull'), 'stochasticLogisticRegressionOrNull': ('stochasticLogisticRegression', 'OrNull'), 'groupArrayMovingSumOrNull': ('groupArrayMovingSum', 'OrNull'), 'contingencyOrNull': ('contingency', 'OrNull'), 'quantilesExactWeightedOrNull': ('quantilesExactWeighted', 'OrNull'), 'quantilesInterpolatedWeightedOrNull': ('quantilesInterpolatedWeighted', 'OrNull'), 'kurtSampOrNull': ('kurtSamp', 'OrNull'), 'deltaSumTimestampOrNull': ('deltaSumTimestamp', 'OrNull'), 'maxIntersectionsPositionOrNull': ('maxIntersectionsPosition', 'OrNull'), 'entropyOrNull': ('entropy', 'OrNull'), 'avgOrNull': ('avg', 'OrNull'), 'cramersVOrNull': ('cramersV', 'OrNull'), 'minMapOrNull': ('minMap', 'OrNull'), 'quantileExactWeightedOrNull': ('quantileExactWeighted', 'OrNull'), 'exponentialMovingAverageOrNull': ('exponentialMovingAverage', 'OrNull'), 'categoricalInformationValueOrNull': ('categoricalInformationValue', 'OrNull'), 'corrOrNull': ('corr', 'OrNull'), 'anyHeavyOrNull': ('anyHeavy', 'OrNull'), 'medianOrNull': ('median', 'OrNull'), 'quantileDeterministicOrNull': ('quantileDeterministic', 'OrNull'), 'quantileBFloat16OrNull': ('quantileBFloat16', 'OrNull'), 'meanZTestOrNull': ('meanZTest', 'OrNull'), 'quantileInterpolatedWeightedOrNull': ('quantileInterpolatedWeighted', 'OrNull'), 'sumCountOrNull': ('sumCount', 'OrNull'), 'welchTTestOrNull': ('welchTTest', 'OrNull'), 'simpleLinearRegressionOrNull': ('simpleLinearRegression', 'OrNull'), 'groupArrayInsertAtOrNull': ('groupArrayInsertAt', 'OrNull'), 'quantilesDeterministicOrNull': ('quantilesDeterministic', 'OrNull'), 'anyOrNull': ('any', 'OrNull'), 'boundingRatioOrNull': ('boundingRatio', 'OrNull'), 'minOrNull': ('min', 'OrNull'), 'quantilesExactLowOrNull': ('quantilesExactLow', 'OrNull'), 'kolmogorovSmirnovTestOrNull': ('kolmogorovSmirnovTest', 'OrNull'), 'groupBitmapAndOrNull': ('groupBitmapAnd', 'OrNull'), 'uniqHLL12OrNull': ('uniqHLL12', 'OrNull'), 'stochasticLinearRegressionOrNull': ('stochasticLinearRegression', 'OrNull'), 'maxOrNull': ('max', 'OrNull'), 'quantileGKOrNull': ('quantileGK', 'OrNull'), 'sequenceNextNodeOrNull': ('sequenceNextNode', 'OrNull'), 'quantilesBFloat16WeightedOrNull': ('quantilesBFloat16Weighted', 'OrNull'), 'countOrNull': ('count', 'OrNull'), 'maxIntersectionsOrNull': ('maxIntersections', 'OrNull'), 'sumKahanOrNull': ('sumKahan', 'OrNull'), 'quantilesGKOrNull': ('quantilesGK', 'OrNull'), 'exponentialTimeDecayedAvgOrNull': ('exponentialTimeDecayedAvg', 'OrNull'), 'quantileExactHighOrNull': ('quantileExactHigh', 'OrNull'), 'varSampOrNull': ('varSamp', 'OrNull'), 'avgWeightedOrNull': ('avgWeighted', 'OrNull'), 'uniqCombined64OrNull': ('uniqCombined64', 'OrNull'), 'groupUniqArrayOrNull': ('groupUniqArray', 'OrNull'), 'quantileTDigestOrNull': ('quantileTDigest', 'OrNull'), 'uniqCombinedOrNull': ('uniqCombined', 'OrNull'), 'cramersVBiasCorrectedOrNull': ('cramersVBiasCorrected', 'OrNull'), 'first_valueOrNull': ('first_value', 'OrNull'), 'skewSampOrNull': ('skewSamp', 'OrNull'), 'uniqUpToOrNull': ('uniqUpTo', 'OrNull'), 'groupArraySampleOrNull': ('groupArraySample', 'OrNull'), 'groupArrayMovingAvgOrNull': ('groupArrayMovingAvg', 'OrNull'), 'skewPopOrNull': ('skewPop', 'OrNull'), 'groupBitXorOrNull': ('groupBitXor', 'OrNull'), 'quantileTimingWeightedOrNull': ('quantileTimingWeighted', 'OrNull'), 'maxMapOrNull': ('maxMap', 'OrNull'), 'uniqExactOrNull': ('uniqExact', 'OrNull'), 'sumWithOverflowOrNull': ('sumWithOverflow', 'OrNull'), 'intervalLengthSumOrNull': ('intervalLengthSum', 'OrNull'), 'quantileTDigestWeightedOrNull': ('quantileTDigestWeighted', 'OrNull'), 'argMaxOrNull': ('argMax', 'OrNull'), 'deltaSumOrNull': ('deltaSum', 'OrNull'), 'quantilesExactHighOrNull': ('quantilesExactHigh', 'OrNull'), 'theilsUOrNull': ('theilsU', 'OrNull'), 'sumOrNull': ('sum', 'OrNull'), 'uniqOrNull': ('uniq', 'OrNull'), 'quantileExactLowOrNull': ('quantileExactLow', 'OrNull'), 'topKOrNull': ('topK', 'OrNull'), 'retentionOrNull': ('retention', 'OrNull'), 'quantilesTDigestWeightedOrNull': ('quantilesTDigestWeighted', 'OrNull'), 'quantileTimingOrNull': ('quantileTiming', 'OrNull'), 'sumMapOrNull': ('sumMap', 'OrNull'), 'mannWhitneyUTestOrNull': ('mannWhitneyUTest', 'OrNull'), 'rankCorrOrNull': ('rankCorr', 'OrNull'), 'stddevSampOrNull': ('stddevSamp', 'OrNull'), 'varPopOrNull': ('varPop', 'OrNull'), 'sequenceMatchOrNull': ('sequenceMatch', 'OrNull'), 'covarPopOrNull': ('covarPop', 'OrNull'), 'sequenceCountOrNull': ('sequenceCount', 'OrNull'), 'argMinOrNull': ('argMin', 'OrNull'), 'covarSampOrNull': ('covarSamp', 'OrNull'), 'quantilesTDigestOrNull': ('quantilesTDigest', 'OrNull'), 'groupBitOrOrNull': ('groupBitOr', 'OrNull'), 'largestTriangleThreeBucketsOrNull': ('largestTriangleThreeBuckets', 'OrNull'), 'anyLastOrNull': ('anyLast', 'OrNull'), 'histogramOrNull': ('histogram', 'OrNull'), 'groupBitmapXorOrNull': ('groupBitmapXor', 'OrNull'), 'last_valueOrNull': ('last_value', 'OrNull'), 'groupArrayLastOrNull': ('groupArrayLast', 'OrNull'), 'kurtPopOrNull': ('kurtPop', 'OrNull'), 'sparkBarOrNull': ('sparkBar', 'OrNull'), 'topKWeightedOrNull': ('topKWeighted', 'OrNull'), 'quantilesOrNull': ('quantiles', 'OrNull'), 'quantilesTimingWeightedOrNull': ('quantilesTimingWeighted', 'OrNull'), 'quantileOrNull': ('quantile', 'OrNull'), 'studentTTestOrNull': ('studentTTest', 'OrNull'), 'groupArrayOrNull': ('groupArray', 'OrNull'), 'groupBitAndResample': ('groupBitAnd', 'Resample'), 'quantileExactResample': ('quantileExact', 'Resample'), 'stddevPopResample': ('stddevPop', 'Resample'), 'groupBitmapResample': ('groupBitmap', 'Resample'), 'uniqThetaResample': ('uniqTheta', 'Resample'), 'windowFunnelResample': ('windowFunnel', 'Resample'), 'quantilesTimingResample': ('quantilesTiming', 'Resample'), 'groupBitmapOrResample': ('groupBitmapOr', 'Resample'), 'quantilesExactResample': ('quantilesExact', 'Resample'), 'quantilesBFloat16Resample': ('quantilesBFloat16', 'Resample'), 'quantileBFloat16WeightedResample': ('quantileBFloat16Weighted', 'Resample'), 'stochasticLogisticRegressionResample': ('stochasticLogisticRegression', 'Resample'), 'groupArrayMovingSumResample': ('groupArrayMovingSum', 'Resample'), 'contingencyResample': ('contingency', 'Resample'), 'quantilesExactWeightedResample': ('quantilesExactWeighted', 'Resample'), 'quantilesInterpolatedWeightedResample': ('quantilesInterpolatedWeighted', 'Resample'), 'kurtSampResample': ('kurtSamp', 'Resample'), 'deltaSumTimestampResample': ('deltaSumTimestamp', 'Resample'), 'maxIntersectionsPositionResample': ('maxIntersectionsPosition', 'Resample'), 'entropyResample': ('entropy', 'Resample'), 'avgResample': ('avg', 'Resample'), 'cramersVResample': ('cramersV', 'Resample'), 'minMapResample': ('minMap', 'Resample'), 'quantileExactWeightedResample': ('quantileExactWeighted', 'Resample'), 'exponentialMovingAverageResample': ('exponentialMovingAverage', 'Resample'), 'categoricalInformationValueResample': ('categoricalInformationValue', 'Resample'), 'corrResample': ('corr', 'Resample'), 'anyHeavyResample': ('anyHeavy', 'Resample'), 'medianResample': ('median', 'Resample'), 'quantileDeterministicResample': ('quantileDeterministic', 'Resample'), 'quantileBFloat16Resample': ('quantileBFloat16', 'Resample'), 'meanZTestResample': ('meanZTest', 'Resample'), 'quantileInterpolatedWeightedResample': ('quantileInterpolatedWeighted', 'Resample'), 'sumCountResample': ('sumCount', 'Resample'), 'welchTTestResample': ('welchTTest', 'Resample'), 'simpleLinearRegressionResample': ('simpleLinearRegression', 'Resample'), 'groupArrayInsertAtResample': ('groupArrayInsertAt', 'Resample'), 'quantilesDeterministicResample': ('quantilesDeterministic', 'Resample'), 'anyResample': ('any', 'Resample'), 'boundingRatioResample': ('boundingRatio', 'Resample'), 'minResample': ('min', 'Resample'), 'quantilesExactLowResample': ('quantilesExactLow', 'Resample'), 'kolmogorovSmirnovTestResample': ('kolmogorovSmirnovTest', 'Resample'), 'groupBitmapAndResample': ('groupBitmapAnd', 'Resample'), 'uniqHLL12Resample': ('uniqHLL12', 'Resample'), 'stochasticLinearRegressionResample': ('stochasticLinearRegression', 'Resample'), 'maxResample': ('max', 'Resample'), 'quantileGKResample': ('quantileGK', 'Resample'), 'sequenceNextNodeResample': ('sequenceNextNode', 'Resample'), 'quantilesBFloat16WeightedResample': ('quantilesBFloat16Weighted', 'Resample'), 'countResample': ('count', 'Resample'), 'maxIntersectionsResample': ('maxIntersections', 'Resample'), 'sumKahanResample': ('sumKahan', 'Resample'), 'quantilesGKResample': ('quantilesGK', 'Resample'), 'exponentialTimeDecayedAvgResample': ('exponentialTimeDecayedAvg', 'Resample'), 'quantileExactHighResample': ('quantileExactHigh', 'Resample'), 'varSampResample': ('varSamp', 'Resample'), 'avgWeightedResample': ('avgWeighted', 'Resample'), 'uniqCombined64Resample': ('uniqCombined64', 'Resample'), 'groupUniqArrayResample': ('groupUniqArray', 'Resample'), 'quantileTDigestResample': ('quantileTDigest', 'Resample'), 'uniqCombinedResample': ('uniqCombined', 'Resample'), 'cramersVBiasCorrectedResample': ('cramersVBiasCorrected', 'Resample'), 'first_valueResample': ('first_value', 'Resample'), 'skewSampResample': ('skewSamp', 'Resample'), 'uniqUpToResample': ('uniqUpTo', 'Resample'), 'groupArraySampleResample': ('groupArraySample', 'Resample'), 'groupArrayMovingAvgResample': ('groupArrayMovingAvg', 'Resample'), 'skewPopResample': ('skewPop', 'Resample'), 'groupBitXorResample': ('groupBitXor', 'Resample'), 'quantileTimingWeightedResample': ('quantileTimingWeighted', 'Resample'), 'maxMapResample': ('maxMap', 'Resample'), 'uniqExactResample': ('uniqExact', 'Resample'), 'sumWithOverflowResample': ('sumWithOverflow', 'Resample'), 'intervalLengthSumResample': ('intervalLengthSum', 'Resample'), 'quantileTDigestWeightedResample': ('quantileTDigestWeighted', 'Resample'), 'argMaxResample': ('argMax', 'Resample'), 'deltaSumResample': ('deltaSum', 'Resample'), 'quantilesExactHighResample': ('quantilesExactHigh', 'Resample'), 'theilsUResample': ('theilsU', 'Resample'), 'sumResample': ('sum', 'Resample'), 'uniqResample': ('uniq', 'Resample'), 'quantileExactLowResample': ('quantileExactLow', 'Resample'), 'topKResample': ('topK', 'Resample'), 'retentionResample': ('retention', 'Resample'), 'quantilesTDigestWeightedResample': ('quantilesTDigestWeighted', 'Resample'), 'quantileTimingResample': ('quantileTiming', 'Resample'), 'sumMapResample': ('sumMap', 'Resample'), 'mannWhitneyUTestResample': ('mannWhitneyUTest', 'Resample'), 'rankCorrResample': ('rankCorr', 'Resample'), 'stddevSampResample': ('stddevSamp', 'Resample'), 'varPopResample': ('varPop', 'Resample'), 'sequenceMatchResample': ('sequenceMatch', 'Resample'), 'covarPopResample': ('covarPop', 'Resample'), 'sequenceCountResample': ('sequenceCount', 'Resample'), 'argMinResample': ('argMin', 'Resample'), 'covarSampResample': ('covarSamp', 'Resample'), 'quantilesTDigestResample': ('quantilesTDigest', 'Resample'), 'groupBitOrResample': ('groupBitOr', 'Resample'), 'largestTriangleThreeBucketsResample': ('largestTriangleThreeBuckets', 'Resample'), 'anyLastResample': ('anyLast', 'Resample'), 'histogramResample': ('histogram', 'Resample'), 'groupBitmapXorResample': ('groupBitmapXor', 'Resample'), 'last_valueResample': ('last_value', 'Resample'), 'groupArrayLastResample': ('groupArrayLast', 'Resample'), 'kurtPopResample': ('kurtPop', 'Resample'), 'sparkBarResample': ('sparkBar', 'Resample'), 'topKWeightedResample': ('topKWeighted', 'Resample'), 'quantilesResample': ('quantiles', 'Resample'), 'quantilesTimingWeightedResample': ('quantilesTimingWeighted', 'Resample'), 'quantileResample': ('quantile', 'Resample'), 'studentTTestResample': ('studentTTest', 'Resample'), 'groupArrayResample': ('groupArray', 'Resample'), 'groupBitAndArgMin': ('groupBitAnd', 'ArgMin'), 'quantileExactArgMin': ('quantileExact', 'ArgMin'), 'stddevPopArgMin': ('stddevPop', 'ArgMin'), 'groupBitmapArgMin': ('groupBitmap', 'ArgMin'), 'uniqThetaArgMin': ('uniqTheta', 'ArgMin'), 'windowFunnelArgMin': ('windowFunnel', 'ArgMin'), 'quantilesTimingArgMin': ('quantilesTiming', 'ArgMin'), 'groupBitmapOrArgMin': ('groupBitmapOr', 'ArgMin'), 'quantilesExactArgMin': ('quantilesExact', 'ArgMin'), 'quantilesBFloat16ArgMin': ('quantilesBFloat16', 'ArgMin'), 'quantileBFloat16WeightedArgMin': ('quantileBFloat16Weighted', 'ArgMin'), 'stochasticLogisticRegressionArgMin': ('stochasticLogisticRegression', 'ArgMin'), 'groupArrayMovingSumArgMin': ('groupArrayMovingSum', 'ArgMin'), 'contingencyArgMin': ('contingency', 'ArgMin'), 'quantilesExactWeightedArgMin': ('quantilesExactWeighted', 'ArgMin'), 'quantilesInterpolatedWeightedArgMin': ('quantilesInterpolatedWeighted', 'ArgMin'), 'kurtSampArgMin': ('kurtSamp', 'ArgMin'), 'deltaSumTimestampArgMin': ('deltaSumTimestamp', 'ArgMin'), 'maxIntersectionsPositionArgMin': ('maxIntersectionsPosition', 'ArgMin'), 'entropyArgMin': ('entropy', 'ArgMin'), 'avgArgMin': ('avg', 'ArgMin'), 'cramersVArgMin': ('cramersV', 'ArgMin'), 'minMapArgMin': ('minMap', 'ArgMin'), 'quantileExactWeightedArgMin': ('quantileExactWeighted', 'ArgMin'), 'exponentialMovingAverageArgMin': ('exponentialMovingAverage', 'ArgMin'), 'categoricalInformationValueArgMin': ('categoricalInformationValue', 'ArgMin'), 'corrArgMin': ('corr', 'ArgMin'), 'anyHeavyArgMin': ('anyHeavy', 'ArgMin'), 'medianArgMin': ('median', 'ArgMin'), 'quantileDeterministicArgMin': ('quantileDeterministic', 'ArgMin'), 'quantileBFloat16ArgMin': ('quantileBFloat16', 'ArgMin'), 'meanZTestArgMin': ('meanZTest', 'ArgMin'), 'quantileInterpolatedWeightedArgMin': ('quantileInterpolatedWeighted', 'ArgMin'), 'sumCountArgMin': ('sumCount', 'ArgMin'), 'welchTTestArgMin': ('welchTTest', 'ArgMin'), 'simpleLinearRegressionArgMin': ('simpleLinearRegression', 'ArgMin'), 'groupArrayInsertAtArgMin': ('groupArrayInsertAt', 'ArgMin'), 'quantilesDeterministicArgMin': ('quantilesDeterministic', 'ArgMin'), 'anyArgMin': ('any', 'ArgMin'), 'boundingRatioArgMin': ('boundingRatio', 'ArgMin'), 'minArgMin': ('min', 'ArgMin'), 'quantilesExactLowArgMin': ('quantilesExactLow', 'ArgMin'), 'kolmogorovSmirnovTestArgMin': ('kolmogorovSmirnovTest', 'ArgMin'), 'groupBitmapAndArgMin': ('groupBitmapAnd', 'ArgMin'), 'uniqHLL12ArgMin': ('uniqHLL12', 'ArgMin'), 'stochasticLinearRegressionArgMin': ('stochasticLinearRegression', 'ArgMin'), 'maxArgMin': ('max', 'ArgMin'), 'quantileGKArgMin': ('quantileGK', 'ArgMin'), 'sequenceNextNodeArgMin': ('sequenceNextNode', 'ArgMin'), 'quantilesBFloat16WeightedArgMin': ('quantilesBFloat16Weighted', 'ArgMin'), 'countArgMin': ('count', 'ArgMin'), 'maxIntersectionsArgMin': ('maxIntersections', 'ArgMin'), 'sumKahanArgMin': ('sumKahan', 'ArgMin'), 'quantilesGKArgMin': ('quantilesGK', 'ArgMin'), 'exponentialTimeDecayedAvgArgMin': ('exponentialTimeDecayedAvg', 'ArgMin'), 'quantileExactHighArgMin': ('quantileExactHigh', 'ArgMin'), 'varSampArgMin': ('varSamp', 'ArgMin'), 'avgWeightedArgMin': ('avgWeighted', 'ArgMin'), 'uniqCombined64ArgMin': ('uniqCombined64', 'ArgMin'), 'groupUniqArrayArgMin': ('groupUniqArray', 'ArgMin'), 'quantileTDigestArgMin': ('quantileTDigest', 'ArgMin'), 'uniqCombinedArgMin': ('uniqCombined', 'ArgMin'), 'cramersVBiasCorrectedArgMin': ('cramersVBiasCorrected', 'ArgMin'), 'first_valueArgMin': ('first_value', 'ArgMin'), 'skewSampArgMin': ('skewSamp', 'ArgMin'), 'uniqUpToArgMin': ('uniqUpTo', 'ArgMin'), 'groupArraySampleArgMin': ('groupArraySample', 'ArgMin'), 'groupArrayMovingAvgArgMin': ('groupArrayMovingAvg', 'ArgMin'), 'skewPopArgMin': ('skewPop', 'ArgMin'), 'groupBitXorArgMin': ('groupBitXor', 'ArgMin'), 'quantileTimingWeightedArgMin': ('quantileTimingWeighted', 'ArgMin'), 'maxMapArgMin': ('maxMap', 'ArgMin'), 'uniqExactArgMin': ('uniqExact', 'ArgMin'), 'sumWithOverflowArgMin': ('sumWithOverflow', 'ArgMin'), 'intervalLengthSumArgMin': ('intervalLengthSum', 'ArgMin'), 'quantileTDigestWeightedArgMin': ('quantileTDigestWeighted', 'ArgMin'), 'argMaxArgMin': ('argMax', 'ArgMin'), 'deltaSumArgMin': ('deltaSum', 'ArgMin'), 'quantilesExactHighArgMin': ('quantilesExactHigh', 'ArgMin'), 'theilsUArgMin': ('theilsU', 'ArgMin'), 'sumArgMin': ('sum', 'ArgMin'), 'uniqArgMin': ('uniq', 'ArgMin'), 'quantileExactLowArgMin': ('quantileExactLow', 'ArgMin'), 'topKArgMin': ('topK', 'ArgMin'), 'retentionArgMin': ('retention', 'ArgMin'), 'quantilesTDigestWeightedArgMin': ('quantilesTDigestWeighted', 'ArgMin'), 'quantileTimingArgMin': ('quantileTiming', 'ArgMin'), 'sumMapArgMin': ('sumMap', 'ArgMin'), 'mannWhitneyUTestArgMin': ('mannWhitneyUTest', 'ArgMin'), 'rankCorrArgMin': ('rankCorr', 'ArgMin'), 'stddevSampArgMin': ('stddevSamp', 'ArgMin'), 'varPopArgMin': ('varPop', 'ArgMin'), 'sequenceMatchArgMin': ('sequenceMatch', 'ArgMin'), 'covarPopArgMin': ('covarPop', 'ArgMin'), 'sequenceCountArgMin': ('sequenceCount', 'ArgMin'), 'argMinArgMin': ('argMin', 'ArgMin'), 'covarSampArgMin': ('covarSamp', 'ArgMin'), 'quantilesTDigestArgMin': ('quantilesTDigest', 'ArgMin'), 'groupBitOrArgMin': ('groupBitOr', 'ArgMin'), 'largestTriangleThreeBucketsArgMin': ('largestTriangleThreeBuckets', 'ArgMin'), 'anyLastArgMin': ('anyLast', 'ArgMin'), 'histogramArgMin': ('histogram', 'ArgMin'), 'groupBitmapXorArgMin': ('groupBitmapXor', 'ArgMin'), 'last_valueArgMin': ('last_value', 'ArgMin'), 'groupArrayLastArgMin': ('groupArrayLast', 'ArgMin'), 'kurtPopArgMin': ('kurtPop', 'ArgMin'), 'sparkBarArgMin': ('sparkBar', 'ArgMin'), 'topKWeightedArgMin': ('topKWeighted', 'ArgMin'), 'quantilesArgMin': ('quantiles', 'ArgMin'), 'quantilesTimingWeightedArgMin': ('quantilesTimingWeighted', 'ArgMin'), 'quantileArgMin': ('quantile', 'ArgMin'), 'studentTTestArgMin': ('studentTTest', 'ArgMin'), 'groupArrayArgMin': ('groupArray', 'ArgMin'), 'groupBitAndArgMax': ('groupBitAnd', 'ArgMax'), 'quantileExactArgMax': ('quantileExact', 'ArgMax'), 'stddevPopArgMax': ('stddevPop', 'ArgMax'), 'groupBitmapArgMax': ('groupBitmap', 'ArgMax'), 'uniqThetaArgMax': ('uniqTheta', 'ArgMax'), 'windowFunnelArgMax': ('windowFunnel', 'ArgMax'), 'quantilesTimingArgMax': ('quantilesTiming', 'ArgMax'), 'groupBitmapOrArgMax': ('groupBitmapOr', 'ArgMax'), 'quantilesExactArgMax': ('quantilesExact', 'ArgMax'), 'quantilesBFloat16ArgMax': ('quantilesBFloat16', 'ArgMax'), 'quantileBFloat16WeightedArgMax': ('quantileBFloat16Weighted', 'ArgMax'), 'stochasticLogisticRegressionArgMax': ('stochasticLogisticRegression', 'ArgMax'), 'groupArrayMovingSumArgMax': ('groupArrayMovingSum', 'ArgMax'), 'contingencyArgMax': ('contingency', 'ArgMax'), 'quantilesExactWeightedArgMax': ('quantilesExactWeighted', 'ArgMax'), 'quantilesInterpolatedWeightedArgMax': ('quantilesInterpolatedWeighted', 'ArgMax'), 'kurtSampArgMax': ('kurtSamp', 'ArgMax'), 'deltaSumTimestampArgMax': ('deltaSumTimestamp', 'ArgMax'), 'maxIntersectionsPositionArgMax': ('maxIntersectionsPosition', 'ArgMax'), 'entropyArgMax': ('entropy', 'ArgMax'), 'avgArgMax': ('avg', 'ArgMax'), 'cramersVArgMax': ('cramersV', 'ArgMax'), 'minMapArgMax': ('minMap', 'ArgMax'), 'quantileExactWeightedArgMax': ('quantileExactWeighted', 'ArgMax'), 'exponentialMovingAverageArgMax': ('exponentialMovingAverage', 'ArgMax'), 'categoricalInformationValueArgMax': ('categoricalInformationValue', 'ArgMax'), 'corrArgMax': ('corr', 'ArgMax'), 'anyHeavyArgMax': ('anyHeavy', 'ArgMax'), 'medianArgMax': ('median', 'ArgMax'), 'quantileDeterministicArgMax': ('quantileDeterministic', 'ArgMax'), 'quantileBFloat16ArgMax': ('quantileBFloat16', 'ArgMax'), 'meanZTestArgMax': ('meanZTest', 'ArgMax'), 'quantileInterpolatedWeightedArgMax': ('quantileInterpolatedWeighted', 'ArgMax'), 'sumCountArgMax': ('sumCount', 'ArgMax'), 'welchTTestArgMax': ('welchTTest', 'ArgMax'), 'simpleLinearRegressionArgMax': ('simpleLinearRegression', 'ArgMax'), 'groupArrayInsertAtArgMax': ('groupArrayInsertAt', 'ArgMax'), 'quantilesDeterministicArgMax': ('quantilesDeterministic', 'ArgMax'), 'anyArgMax': ('any', 'ArgMax'), 'boundingRatioArgMax': ('boundingRatio', 'ArgMax'), 'minArgMax': ('min', 'ArgMax'), 'quantilesExactLowArgMax': ('quantilesExactLow', 'ArgMax'), 'kolmogorovSmirnovTestArgMax': ('kolmogorovSmirnovTest', 'ArgMax'), 'groupBitmapAndArgMax': ('groupBitmapAnd', 'ArgMax'), 'uniqHLL12ArgMax': ('uniqHLL12', 'ArgMax'), 'stochasticLinearRegressionArgMax': ('stochasticLinearRegression', 'ArgMax'), 'maxArgMax': ('max', 'ArgMax'), 'quantileGKArgMax': ('quantileGK', 'ArgMax'), 'sequenceNextNodeArgMax': ('sequenceNextNode', 'ArgMax'), 'quantilesBFloat16WeightedArgMax': ('quantilesBFloat16Weighted', 'ArgMax'), 'countArgMax': ('count', 'ArgMax'), 'maxIntersectionsArgMax': ('maxIntersections', 'ArgMax'), 'sumKahanArgMax': ('sumKahan', 'ArgMax'), 'quantilesGKArgMax': ('quantilesGK', 'ArgMax'), 'exponentialTimeDecayedAvgArgMax': ('exponentialTimeDecayedAvg', 'ArgMax'), 'quantileExactHighArgMax': ('quantileExactHigh', 'ArgMax'), 'varSampArgMax': ('varSamp', 'ArgMax'), 'avgWeightedArgMax': ('avgWeighted', 'ArgMax'), 'uniqCombined64ArgMax': ('uniqCombined64', 'ArgMax'), 'groupUniqArrayArgMax': ('groupUniqArray', 'ArgMax'), 'quantileTDigestArgMax': ('quantileTDigest', 'ArgMax'), 'uniqCombinedArgMax': ('uniqCombined', 'ArgMax'), 'cramersVBiasCorrectedArgMax': ('cramersVBiasCorrected', 'ArgMax'), 'first_valueArgMax': ('first_value', 'ArgMax'), 'skewSampArgMax': ('skewSamp', 'ArgMax'), 'uniqUpToArgMax': ('uniqUpTo', 'ArgMax'), 'groupArraySampleArgMax': ('groupArraySample', 'ArgMax'), 'groupArrayMovingAvgArgMax': ('groupArrayMovingAvg', 'ArgMax'), 'skewPopArgMax': ('skewPop', 'ArgMax'), 'groupBitXorArgMax': ('groupBitXor', 'ArgMax'), 'quantileTimingWeightedArgMax': ('quantileTimingWeighted', 'ArgMax'), 'maxMapArgMax': ('maxMap', 'ArgMax'), 'uniqExactArgMax': ('uniqExact', 'ArgMax'), 'sumWithOverflowArgMax': ('sumWithOverflow', 'ArgMax'), 'intervalLengthSumArgMax': ('intervalLengthSum', 'ArgMax'), 'quantileTDigestWeightedArgMax': ('quantileTDigestWeighted', 'ArgMax'), 'argMaxArgMax': ('argMax', 'ArgMax'), 'deltaSumArgMax': ('deltaSum', 'ArgMax'), 'quantilesExactHighArgMax': ('quantilesExactHigh', 'ArgMax'), 'theilsUArgMax': ('theilsU', 'ArgMax'), 'sumArgMax': ('sum', 'ArgMax'), 'uniqArgMax': ('uniq', 'ArgMax'), 'quantileExactLowArgMax': ('quantileExactLow', 'ArgMax'), 'topKArgMax': ('topK', 'ArgMax'), 'retentionArgMax': ('retention', 'ArgMax'), 'quantilesTDigestWeightedArgMax': ('quantilesTDigestWeighted', 'ArgMax'), 'quantileTimingArgMax': ('quantileTiming', 'ArgMax'), 'sumMapArgMax': ('sumMap', 'ArgMax'), 'mannWhitneyUTestArgMax': ('mannWhitneyUTest', 'ArgMax'), 'rankCorrArgMax': ('rankCorr', 'ArgMax'), 'stddevSampArgMax': ('stddevSamp', 'ArgMax'), 'varPopArgMax': ('varPop', 'ArgMax'), 'sequenceMatchArgMax': ('sequenceMatch', 'ArgMax'), 'covarPopArgMax': ('covarPop', 'ArgMax'), 'sequenceCountArgMax': ('sequenceCount', 'ArgMax'), 'argMinArgMax': ('argMin', 'ArgMax'), 'covarSampArgMax': ('covarSamp', 'ArgMax'), 'quantilesTDigestArgMax': ('quantilesTDigest', 'ArgMax'), 'groupBitOrArgMax': ('groupBitOr', 'ArgMax'), 'largestTriangleThreeBucketsArgMax': ('largestTriangleThreeBuckets', 'ArgMax'), 'anyLastArgMax': ('anyLast', 'ArgMax'), 'histogramArgMax': ('histogram', 'ArgMax'), 'groupBitmapXorArgMax': ('groupBitmapXor', 'ArgMax'), 'last_valueArgMax': ('last_value', 'ArgMax'), 'groupArrayLastArgMax': ('groupArrayLast', 'ArgMax'), 'kurtPopArgMax': ('kurtPop', 'ArgMax'), 'sparkBarArgMax': ('sparkBar', 'ArgMax'), 'topKWeightedArgMax': ('topKWeighted', 'ArgMax'), 'quantilesArgMax': ('quantiles', 'ArgMax'), 'quantilesTimingWeightedArgMax': ('quantilesTimingWeighted', 'ArgMax'), 'quantileArgMax': ('quantile', 'ArgMax'), 'studentTTestArgMax': ('studentTTest', 'ArgMax'), 'groupArrayArgMax': ('groupArray', 'ArgMax'), 'groupBitAnd': ('groupBitAnd', ''), 'quantileExact': ('quantileExact', ''), 'stddevPop': ('stddevPop', ''), 'groupBitmap': ('groupBitmap', ''), 'uniqTheta': ('uniqTheta', ''), 'windowFunnel': ('windowFunnel', ''), 'quantilesTiming': ('quantilesTiming', ''), 'groupBitmapOr': ('groupBitmapOr', ''), 'quantilesExact': ('quantilesExact', ''), 'quantilesBFloat16': ('quantilesBFloat16', ''), 'quantileBFloat16Weighted': ('quantileBFloat16Weighted', ''), 'stochasticLogisticRegression': ('stochasticLogisticRegression', ''), 'groupArrayMovingSum': ('groupArrayMovingSum', ''), 'contingency': ('contingency', ''), 'quantilesExactWeighted': ('quantilesExactWeighted', ''), 'quantilesInterpolatedWeighted': ('quantilesInterpolatedWeighted', ''), 'kurtSamp': ('kurtSamp', ''), 'deltaSumTimestamp': ('deltaSumTimestamp', ''), 'maxIntersectionsPosition': ('maxIntersectionsPosition', ''), 'entropy': ('entropy', ''), 'avg': ('avg', ''), 'cramersV': ('cramersV', ''), 'quantileExactWeighted': ('quantileExactWeighted', ''), 'exponentialMovingAverage': ('exponentialMovingAverage', ''), 'categoricalInformationValue': ('categoricalInformationValue', ''), 'corr': ('corr', ''), 'anyHeavy': ('anyHeavy', ''), 'median': ('median', ''), 'quantileDeterministic': ('quantileDeterministic', ''), 'quantileBFloat16': ('quantileBFloat16', ''), 'meanZTest': ('meanZTest', ''), 'quantileInterpolatedWeighted': ('quantileInterpolatedWeighted', ''), 'sumCount': ('sumCount', ''), 'welchTTest': ('welchTTest', ''), 'simpleLinearRegression': ('simpleLinearRegression', ''), 'groupArrayInsertAt': ('groupArrayInsertAt', ''), 'quantilesDeterministic': ('quantilesDeterministic', ''), 'any': ('any', ''), 'boundingRatio': ('boundingRatio', ''), 'min': ('min', ''), 'quantilesExactLow': ('quantilesExactLow', ''), 'kolmogorovSmirnovTest': ('kolmogorovSmirnovTest', ''), 'groupBitmapAnd': ('groupBitmapAnd', ''), 'uniqHLL12': ('uniqHLL12', ''), 'stochasticLinearRegression': ('stochasticLinearRegression', ''), 'max': ('max', ''), 'quantileGK': ('quantileGK', ''), 'sequenceNextNode': ('sequenceNextNode', ''), 'quantilesBFloat16Weighted': ('quantilesBFloat16Weighted', ''), 'count': ('count', ''), 'maxIntersections': ('maxIntersections', ''), 'sumKahan': ('sumKahan', ''), 'quantilesGK': ('quantilesGK', ''), 'exponentialTimeDecayedAvg': ('exponentialTimeDecayedAvg', ''), 'quantileExactHigh': ('quantileExactHigh', ''), 'varSamp': ('varSamp', ''), 'avgWeighted': ('avgWeighted', ''), 'uniqCombined64': ('uniqCombined64', ''), 'groupUniqArray': ('groupUniqArray', ''), 'quantileTDigest': ('quantileTDigest', ''), 'uniqCombined': ('uniqCombined', ''), 'cramersVBiasCorrected': ('cramersVBiasCorrected', ''), 'first_value': ('first_value', ''), 'skewSamp': ('skewSamp', ''), 'uniqUpTo': ('uniqUpTo', ''), 'groupArraySample': ('groupArraySample', ''), 'groupArrayMovingAvg': ('groupArrayMovingAvg', ''), 'skewPop': ('skewPop', ''), 'groupBitXor': ('groupBitXor', ''), 'quantileTimingWeighted': ('quantileTimingWeighted', ''), 'uniqExact': ('uniqExact', ''), 'sumWithOverflow': ('sumWithOverflow', ''), 'intervalLengthSum': ('intervalLengthSum', ''), 'quantileTDigestWeighted': ('quantileTDigestWeighted', ''), 'argMax': ('argMax', ''), 'deltaSum': ('deltaSum', ''), 'quantilesExactHigh': ('quantilesExactHigh', ''), 'theilsU': ('theilsU', ''), 'sum': ('sum', ''), 'uniq': ('uniq', ''), 'quantileExactLow': ('quantileExactLow', ''), 'topK': ('topK', ''), 'retention': ('retention', ''), 'quantilesTDigestWeighted': ('quantilesTDigestWeighted', ''), 'quantileTiming': ('quantileTiming', ''), 'mannWhitneyUTest': ('mannWhitneyUTest', ''), 'rankCorr': ('rankCorr', ''), 'stddevSamp': ('stddevSamp', ''), 'varPop': ('varPop', ''), 'sequenceMatch': ('sequenceMatch', ''), 'covarPop': ('covarPop', ''), 'sequenceCount': ('sequenceCount', ''), 'argMin': ('argMin', ''), 'covarSamp': ('covarSamp', ''), 'quantilesTDigest': ('quantilesTDigest', ''), 'groupBitOr': ('groupBitOr', ''), 'largestTriangleThreeBuckets': ('largestTriangleThreeBuckets', ''), 'anyLast': ('anyLast', ''), 'histogram': ('histogram', ''), 'groupBitmapXor': ('groupBitmapXor', ''), 'last_value': ('last_value', ''), 'groupArrayLast': ('groupArrayLast', ''), 'kurtPop': ('kurtPop', ''), 'sparkBar': ('sparkBar', ''), 'topKWeighted': ('topKWeighted', ''), 'quantiles': ('quantiles', ''), 'quantilesTimingWeighted': ('quantilesTimingWeighted', ''), 'quantile': ('quantile', ''), 'studentTTest': ('studentTTest', ''), 'groupArray': ('groupArray', '')}"}, "sqlglot.dialects.clickhouse.ClickHouse.Parser.FUNCTIONS_WITH_ALIASED_ARGS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Parser.FUNCTIONS_WITH_ALIASED_ARGS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Parser.FUNCTIONS_WITH_ALIASED_ARGS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'STRUCT', 'TUPLE'}"}, "sqlglot.dialects.clickhouse.ClickHouse.Parser.FUNCTION_PARSERS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Parser.FUNCTION_PARSERS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Parser.FUNCTION_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'CAST': <function Parser.<lambda>>, 'CONVERT': <function Parser.<lambda>>, 'DECODE': <function Parser.<lambda>>, 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'IF': <function Parser.<lambda>>, 'NEXT': <function Parser.<lambda>>}"}, "sqlglot.dialects.clickhouse.ClickHouse.Parser.RANGE_PARSERS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Parser.RANGE_PARSERS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Parser.RANGE_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.BETWEEN: 'BETWEEN'>: <function Parser.<lambda>>, <TokenType.GLOB: 'GLOB'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.ILIKE: 'ILIKE'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.IN: 'IN'>: <function Parser.<lambda>>, <TokenType.IRLIKE: 'IRLIKE'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.IS: 'IS'>: <function Parser.<lambda>>, <TokenType.LIKE: 'LIKE'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.OVERLAPS: 'OVERLAPS'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.RLIKE: 'RLIKE'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.SIMILAR_TO: 'SIMILAR_TO'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.FOR: 'FOR'>: <function Parser.<lambda>>, <TokenType.GLOBAL: 'GLOBAL'>: <function ClickHouse.Parser.<lambda>>}"}, "sqlglot.dialects.clickhouse.ClickHouse.Parser.COLUMN_OPERATORS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Parser.COLUMN_OPERATORS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Parser.COLUMN_OPERATORS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.DOT: 'DOT'>: None, <TokenType.DCOLON: 'DCOLON'>: <function Parser.<lambda>>, <TokenType.ARROW: 'ARROW'>: <function Parser.<lambda>>, <TokenType.DARROW: 'DARROW'>: <function Parser.<lambda>>, <TokenType.HASH_ARROW: 'HASH_ARROW'>: <function Parser.<lambda>>, <TokenType.DHASH_ARROW: 'DHASH_ARROW'>: <function Parser.<lambda>>}"}, "sqlglot.dialects.clickhouse.ClickHouse.Parser.JOIN_KINDS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Parser.JOIN_KINDS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Parser.JOIN_KINDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.ARRAY: 'ARRAY'>, <TokenType.ASOF: 'ASOF'>, <TokenType.ANY: 'ANY'>, <TokenType.CROSS: 'CROSS'>, <TokenType.INNER: 'INNER'>, <TokenType.ANTI: 'ANTI'>, <TokenType.SEMI: 'SEMI'>, <TokenType.OUTER: 'OUTER'>}"}, "sqlglot.dialects.clickhouse.ClickHouse.Parser.TABLE_ALIAS_TOKENS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Parser.TABLE_ALIAS_TOKENS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Parser.TABLE_ALIAS_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.KILL: 'KILL'>, <TokenType.MONEY: 'MONEY'>, <TokenType.COPY: 'COPY'>, <TokenType.PERCENT: 'PERCENT'>, <TokenType.TAG: 'TAG'>, <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, <TokenType.VOLATILE: 'VOLATILE'>, <TokenType.IDENTIFIER: 'IDENTIFIER'>, <TokenType.VARBINARY: 'VARBINARY'>, <TokenType.HSTORE: 'HSTORE'>, <TokenType.ASC: 'ASC'>, <TokenType.IPADDRESS: 'IPADDRESS'>, <TokenType.ISNULL: 'ISNULL'>, <TokenType.TEMPORARY: 'TEMPORARY'>, <TokenType.PROCEDURE: 'PROCEDURE'>, <TokenType.SCHEMA: 'SCHEMA'>, <TokenType.NUMRANGE: 'NUMRANGE'>, <TokenType.DATE32: 'DATE32'>, <TokenType.INT8RANGE: 'INT8RANGE'>, <TokenType.AGGREGATEFUNCTION: 'AGGREGATEFUNCTION'>, <TokenType.VIEW: 'VIEW'>, <TokenType.VARCHAR: 'VARCHAR'>, <TokenType.TIMETZ: 'TIMETZ'>, <TokenType.GEOMETRY: 'GEOMETRY'>, <TokenType.BEGIN: 'BEGIN'>, <TokenType.ENUM8: 'ENUM8'>, <TokenType.INDEX: 'INDEX'>, <TokenType.PARTITION: 'PARTITION'>, <TokenType.UINT256: 'UINT256'>, <TokenType.BIGINT: 'BIGINT'>, <TokenType.CACHE: 'CACHE'>, <TokenType.OPERATOR: 'OPERATOR'>, <TokenType.COLUMN: 'COLUMN'>, <TokenType.INT128: 'INT128'>, <TokenType.SMALLMONEY: 'SMALLMONEY'>, <TokenType.HLLSKETCH: 'HLLSKETCH'>, <TokenType.UNPIVOT: 'UNPIVOT'>, <TokenType.SMALLINT: 'SMALLINT'>, <TokenType.INT256: 'INT256'>, <TokenType.FLOAT: 'FLOAT'>, <TokenType.COMMIT: 'COMMIT'>, <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, <TokenType.EXISTS: 'EXISTS'>, <TokenType.NULL: 'NULL'>, <TokenType.RECURSIVE: 'RECURSIVE'>, <TokenType.SET: 'SET'>, <TokenType.NULLABLE: 'NULLABLE'>, <TokenType.REFRESH: 'REFRESH'>, <TokenType.TINYTEXT: 'TINYTEXT'>, <TokenType.SHOW: 'SHOW'>, <TokenType.DEFAULT: 'DEFAULT'>, <TokenType.DATE: 'DATE'>, <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <TokenType.MERGE: 'MERGE'>, <TokenType.FIRST: 'FIRST'>, <TokenType.BINARY: 'BINARY'>, <TokenType.SERIAL: 'SERIAL'>, <TokenType.EXECUTE: 'EXECUTE'>, <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, <TokenType.INTERVAL: 'INTERVAL'>, <TokenType.PRAGMA: 'PRAGMA'>, <TokenType.STORAGE_INTEGRATION: 'STORAGE_INTEGRATION'>, <TokenType.BPCHAR: 'BPCHAR'>, <TokenType.BIT: 'BIT'>, <TokenType.UINT: 'UINT'>, <TokenType.UUID: 'UUID'>, <TokenType.STRUCT: 'STRUCT'>, <TokenType.FALSE: 'FALSE'>, <TokenType.FUNCTION: 'FUNCTION'>, <TokenType.TOP: 'TOP'>, <TokenType.SUPER: 'SUPER'>, <TokenType.CASE: 'CASE'>, <TokenType.IMAGE: 'IMAGE'>, <TokenType.UBIGINT: 'UBIGINT'>, <TokenType.LONGBLOB: 'LONGBLOB'>, <TokenType.ROLLUP: 'ROLLUP'>, <TokenType.VAR: 'VAR'>, <TokenType.COMMAND: 'COMMAND'>, <TokenType.LOAD: 'LOAD'>, <TokenType.TRUNCATE: 'TRUNCATE'>, <TokenType.KEEP: 'KEEP'>, <TokenType.UMEDIUMINT: 'UMEDIUMINT'>, <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, <TokenType.UINT128: 'UINT128'>, <TokenType.END: 'END'>, <TokenType.MAP: 'MAP'>, <TokenType.IPV4: 'IPV4'>, <TokenType.USERDEFINED: 'USERDEFINED'>, <TokenType.REFERENCES: 'REFERENCES'>, <TokenType.REPLACE: 'REPLACE'>, <TokenType.RANGE: 'RANGE'>, <TokenType.NVARCHAR: 'NVARCHAR'>, <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, <TokenType.TRUE: 'TRUE'>, <TokenType.TIMESTAMP_MS: 'TIMESTAMP_MS'>, <TokenType.VARIANT: 'VARIANT'>, <TokenType.ENUM: 'ENUM'>, <TokenType.USE: 'USE'>, <TokenType.USMALLINT: 'USMALLINT'>, <TokenType.OVERLAPS: 'OVERLAPS'>, <TokenType.TIMESTAMP_S: 'TIMESTAMP_S'>, <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, <TokenType.UNIQUE: 'UNIQUE'>, <TokenType.ORDINALITY: 'ORDINALITY'>, <TokenType.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>, <TokenType.TEXT: 'TEXT'>, <TokenType.DATABASE: 'DATABASE'>, <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, <TokenType.PSEUDO_TYPE: 'PSEUDO_TYPE'>, <TokenType.FIXEDSTRING: 'FIXEDSTRING'>, <TokenType.NEXT: 'NEXT'>, <TokenType.INT: 'INT'>, <TokenType.BIGSERIAL: 'BIGSERIAL'>, <TokenType.BOOLEAN: 'BOOLEAN'>, <TokenType.IS: 'IS'>, <TokenType.CONSTRAINT: 'CONSTRAINT'>, <TokenType.UNKNOWN: 'UNKNOWN'>, <TokenType.ROWS: 'ROWS'>, <TokenType.TSTZRANGE: 'TSTZRANGE'>, <TokenType.DATETIME64: 'DATETIME64'>, <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, <TokenType.DATETIME: 'DATETIME'>, <TokenType.MEDIUMINT: 'MEDIUMINT'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>, <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, <TokenType.XML: 'XML'>, <TokenType.JSON: 'JSON'>, <TokenType.UTINYINT: 'UTINYINT'>, <TokenType.DELETE: 'DELETE'>, <TokenType.TIME: 'TIME'>, <TokenType.UDECIMAL: 'UDECIMAL'>, <TokenType.NESTED: 'NESTED'>, <TokenType.DESC: 'DESC'>, <TokenType.ROWVERSION: 'ROWVERSION'>, <TokenType.TIMESTAMP_NS: 'TIMESTAMP_NS'>, <TokenType.DIV: 'DIV'>, <TokenType.DICTIONARY: 'DICTIONARY'>, <TokenType.INET: 'INET'>, <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, <TokenType.COMMENT: 'COMMENT'>, <TokenType.CURRENT_USER: 'CURRENT_USER'>, <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>, <TokenType.ALL: 'ALL'>, <TokenType.NAME: 'NAME'>, <TokenType.SOME: 'SOME'>, <TokenType.ENUM16: 'ENUM16'>, <TokenType.YEAR: 'YEAR'>, <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, <TokenType.DOUBLE: 'DOUBLE'>, <TokenType.INT4RANGE: 'INT4RANGE'>, <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, <TokenType.IPPREFIX: 'IPPREFIX'>, <TokenType.OVERWRITE: 'OVERWRITE'>, <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>, <TokenType.COLLATE: 'COLLATE'>, <TokenType.FILTER: 'FILTER'>, <TokenType.JSONB: 'JSONB'>, <TokenType.TDIGEST: 'TDIGEST'>, <TokenType.CHAR: 'CHAR'>, <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.ROW: 'ROW'>, <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.TABLE: 'TABLE'>, <TokenType.DATERANGE: 'DATERANGE'>, <TokenType.TSRANGE: 'TSRANGE'>, <TokenType.ESCAPE: 'ESCAPE'>, <TokenType.PIVOT: 'PIVOT'>, <TokenType.DECIMAL: 'DECIMAL'>, <TokenType.NCHAR: 'NCHAR'>, <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, <TokenType.UPDATE: 'UPDATE'>, <TokenType.MODEL: 'MODEL'>, <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, <TokenType.SEQUENCE: 'SEQUENCE'>, <TokenType.LONGTEXT: 'LONGTEXT'>, <TokenType.DESCRIBE: 'DESCRIBE'>, <TokenType.IPV6: 'IPV6'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, <TokenType.TINYINT: 'TINYINT'>, <TokenType.TINYBLOB: 'TINYBLOB'>}"}, "sqlglot.dialects.clickhouse.ClickHouse.Parser.ALIAS_TOKENS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Parser.ALIAS_TOKENS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Parser.ALIAS_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.KILL: 'KILL'>, <TokenType.MONEY: 'MONEY'>, <TokenType.COPY: 'COPY'>, <TokenType.PERCENT: 'PERCENT'>, <TokenType.TAG: 'TAG'>, <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, <TokenType.VOLATILE: 'VOLATILE'>, <TokenType.IDENTIFIER: 'IDENTIFIER'>, <TokenType.VARBINARY: 'VARBINARY'>, <TokenType.HSTORE: 'HSTORE'>, <TokenType.ASC: 'ASC'>, <TokenType.IPADDRESS: 'IPADDRESS'>, <TokenType.ISNULL: 'ISNULL'>, <TokenType.TEMPORARY: 'TEMPORARY'>, <TokenType.PROCEDURE: 'PROCEDURE'>, <TokenType.SCHEMA: 'SCHEMA'>, <TokenType.NUMRANGE: 'NUMRANGE'>, <TokenType.DATE32: 'DATE32'>, <TokenType.INT8RANGE: 'INT8RANGE'>, <TokenType.AGGREGATEFUNCTION: 'AGGREGATEFUNCTION'>, <TokenType.VIEW: 'VIEW'>, <TokenType.VARCHAR: 'VARCHAR'>, <TokenType.TIMETZ: 'TIMETZ'>, <TokenType.GEOMETRY: 'GEOMETRY'>, <TokenType.BEGIN: 'BEGIN'>, <TokenType.ENUM8: 'ENUM8'>, <TokenType.INDEX: 'INDEX'>, <TokenType.PARTITION: 'PARTITION'>, <TokenType.UINT256: 'UINT256'>, <TokenType.BIGINT: 'BIGINT'>, <TokenType.CACHE: 'CACHE'>, <TokenType.OPERATOR: 'OPERATOR'>, <TokenType.COLUMN: 'COLUMN'>, <TokenType.INT128: 'INT128'>, <TokenType.SMALLMONEY: 'SMALLMONEY'>, <TokenType.HLLSKETCH: 'HLLSKETCH'>, <TokenType.UNPIVOT: 'UNPIVOT'>, <TokenType.SMALLINT: 'SMALLINT'>, <TokenType.INT256: 'INT256'>, <TokenType.FLOAT: 'FLOAT'>, <TokenType.COMMIT: 'COMMIT'>, <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, <TokenType.EXISTS: 'EXISTS'>, <TokenType.NULL: 'NULL'>, <TokenType.RECURSIVE: 'RECURSIVE'>, <TokenType.SET: 'SET'>, <TokenType.NULLABLE: 'NULLABLE'>, <TokenType.REFRESH: 'REFRESH'>, <TokenType.TINYTEXT: 'TINYTEXT'>, <TokenType.SHOW: 'SHOW'>, <TokenType.DEFAULT: 'DEFAULT'>, <TokenType.DATE: 'DATE'>, <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <TokenType.MERGE: 'MERGE'>, <TokenType.FIRST: 'FIRST'>, <TokenType.BINARY: 'BINARY'>, <TokenType.ARRAY: 'ARRAY'>, <TokenType.SERIAL: 'SERIAL'>, <TokenType.EXECUTE: 'EXECUTE'>, <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, <TokenType.INTERVAL: 'INTERVAL'>, <TokenType.PRAGMA: 'PRAGMA'>, <TokenType.APPLY: 'APPLY'>, <TokenType.STORAGE_INTEGRATION: 'STORAGE_INTEGRATION'>, <TokenType.ASOF: 'ASOF'>, <TokenType.WINDOW: 'WINDOW'>, <TokenType.RIGHT: 'RIGHT'>, <TokenType.BPCHAR: 'BPCHAR'>, <TokenType.BIT: 'BIT'>, <TokenType.UINT: 'UINT'>, <TokenType.UUID: 'UUID'>, <TokenType.STRUCT: 'STRUCT'>, <TokenType.FALSE: 'FALSE'>, <TokenType.LEFT: 'LEFT'>, <TokenType.TOP: 'TOP'>, <TokenType.FUNCTION: 'FUNCTION'>, <TokenType.SUPER: 'SUPER'>, <TokenType.CASE: 'CASE'>, <TokenType.IMAGE: 'IMAGE'>, <TokenType.UBIGINT: 'UBIGINT'>, <TokenType.LONGBLOB: 'LONGBLOB'>, <TokenType.ROLLUP: 'ROLLUP'>, <TokenType.VAR: 'VAR'>, <TokenType.COMMAND: 'COMMAND'>, <TokenType.LOAD: 'LOAD'>, <TokenType.TRUNCATE: 'TRUNCATE'>, <TokenType.KEEP: 'KEEP'>, <TokenType.UMEDIUMINT: 'UMEDIUMINT'>, <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, <TokenType.UINT128: 'UINT128'>, <TokenType.END: 'END'>, <TokenType.MAP: 'MAP'>, <TokenType.IPV4: 'IPV4'>, <TokenType.USERDEFINED: 'USERDEFINED'>, <TokenType.REFERENCES: 'REFERENCES'>, <TokenType.REPLACE: 'REPLACE'>, <TokenType.RANGE: 'RANGE'>, <TokenType.NVARCHAR: 'NVARCHAR'>, <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, <TokenType.TRUE: 'TRUE'>, <TokenType.TIMESTAMP_MS: 'TIMESTAMP_MS'>, <TokenType.VARIANT: 'VARIANT'>, <TokenType.ENUM: 'ENUM'>, <TokenType.USE: 'USE'>, <TokenType.USMALLINT: 'USMALLINT'>, <TokenType.OVERLAPS: 'OVERLAPS'>, <TokenType.TIMESTAMP_S: 'TIMESTAMP_S'>, <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, <TokenType.UNIQUE: 'UNIQUE'>, <TokenType.ORDINALITY: 'ORDINALITY'>, <TokenType.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>, <TokenType.TEXT: 'TEXT'>, <TokenType.DATABASE: 'DATABASE'>, <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, <TokenType.PSEUDO_TYPE: 'PSEUDO_TYPE'>, <TokenType.FIXEDSTRING: 'FIXEDSTRING'>, <TokenType.NEXT: 'NEXT'>, <TokenType.INT: 'INT'>, <TokenType.BIGSERIAL: 'BIGSERIAL'>, <TokenType.BOOLEAN: 'BOOLEAN'>, <TokenType.IS: 'IS'>, <TokenType.CONSTRAINT: 'CONSTRAINT'>, <TokenType.FINAL: 'FINAL'>, <TokenType.UNKNOWN: 'UNKNOWN'>, <TokenType.SETTINGS: 'SETTINGS'>, <TokenType.ROWS: 'ROWS'>, <TokenType.TSTZRANGE: 'TSTZRANGE'>, <TokenType.DATETIME64: 'DATETIME64'>, <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, <TokenType.DATETIME: 'DATETIME'>, <TokenType.MEDIUMINT: 'MEDIUMINT'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>, <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, <TokenType.XML: 'XML'>, <TokenType.SEMI: 'SEMI'>, <TokenType.JSON: 'JSON'>, <TokenType.DELETE: 'DELETE'>, <TokenType.UTINYINT: 'UTINYINT'>, <TokenType.TIME: 'TIME'>, <TokenType.UDECIMAL: 'UDECIMAL'>, <TokenType.NESTED: 'NESTED'>, <TokenType.DESC: 'DESC'>, <TokenType.ROWVERSION: 'ROWVERSION'>, <TokenType.OFFSET: 'OFFSET'>, <TokenType.TIMESTAMP_NS: 'TIMESTAMP_NS'>, <TokenType.ANY: 'ANY'>, <TokenType.DIV: 'DIV'>, <TokenType.DICTIONARY: 'DICTIONARY'>, <TokenType.INET: 'INET'>, <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, <TokenType.COMMENT: 'COMMENT'>, <TokenType.CURRENT_USER: 'CURRENT_USER'>, <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>, <TokenType.ALL: 'ALL'>, <TokenType.NAME: 'NAME'>, <TokenType.SOME: 'SOME'>, <TokenType.ENUM16: 'ENUM16'>, <TokenType.YEAR: 'YEAR'>, <TokenType.FULL: 'FULL'>, <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, <TokenType.TINYBLOB: 'TINYBLOB'>, <TokenType.DOUBLE: 'DOUBLE'>, <TokenType.INT4RANGE: 'INT4RANGE'>, <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, <TokenType.IPPREFIX: 'IPPREFIX'>, <TokenType.OVERWRITE: 'OVERWRITE'>, <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>, <TokenType.COLLATE: 'COLLATE'>, <TokenType.FILTER: 'FILTER'>, <TokenType.JSONB: 'JSONB'>, <TokenType.TDIGEST: 'TDIGEST'>, <TokenType.CHAR: 'CHAR'>, <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.ROW: 'ROW'>, <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.TABLE: 'TABLE'>, <TokenType.DATERANGE: 'DATERANGE'>, <TokenType.NATURAL: 'NATURAL'>, <TokenType.TSRANGE: 'TSRANGE'>, <TokenType.ESCAPE: 'ESCAPE'>, <TokenType.PIVOT: 'PIVOT'>, <TokenType.DECIMAL: 'DECIMAL'>, <TokenType.NCHAR: 'NCHAR'>, <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, <TokenType.UPDATE: 'UPDATE'>, <TokenType.MODEL: 'MODEL'>, <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, <TokenType.SEQUENCE: 'SEQUENCE'>, <TokenType.LONGTEXT: 'LONGTEXT'>, <TokenType.DESCRIBE: 'DESCRIBE'>, <TokenType.IPV6: 'IPV6'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, <TokenType.TINYINT: 'TINYINT'>, <TokenType.ANTI: 'ANTI'>}"}, "sqlglot.dialects.clickhouse.ClickHouse.Parser.LOG_DEFAULTS_TO_LN": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Parser.LOG_DEFAULTS_TO_LN", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Parser.LOG_DEFAULTS_TO_LN", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.clickhouse.ClickHouse.Parser.QUERY_MODIFIER_PARSERS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Parser.QUERY_MODIFIER_PARSERS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Parser.QUERY_MODIFIER_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.MATCH_RECOGNIZE: 'MATCH_RECOGNIZE'>: <function Parser.<lambda>>, <TokenType.PREWHERE: 'PREWHERE'>: <function Parser.<lambda>>, <TokenType.WHERE: 'WHERE'>: <function Parser.<lambda>>, <TokenType.GROUP_BY: 'GROUP_BY'>: <function Parser.<lambda>>, <TokenType.HAVING: 'HAVING'>: <function Parser.<lambda>>, <TokenType.QUALIFY: 'QUALIFY'>: <function Parser.<lambda>>, <TokenType.WINDOW: 'WINDOW'>: <function Parser.<lambda>>, <TokenType.ORDER_BY: 'ORDER_BY'>: <function Parser.<lambda>>, <TokenType.LIMIT: 'LIMIT'>: <function Parser.<lambda>>, <TokenType.FETCH: 'FETCH'>: <function Parser.<lambda>>, <TokenType.OFFSET: 'OFFSET'>: <function Parser.<lambda>>, <TokenType.FOR: 'FOR'>: <function Parser.<lambda>>, <TokenType.LOCK: 'LOCK'>: <function Parser.<lambda>>, <TokenType.TABLE_SAMPLE: 'TABLE_SAMPLE'>: <function Parser.<lambda>>, <TokenType.USING: 'USING'>: <function Parser.<lambda>>, <TokenType.CLUSTER_BY: 'CLUSTER_BY'>: <function Parser.<lambda>>, <TokenType.DISTRIBUTE_BY: 'DISTRIBUTE_BY'>: <function Parser.<lambda>>, <TokenType.SORT_BY: 'SORT_BY'>: <function Parser.<lambda>>, <TokenType.CONNECT_BY: 'CONNECT_BY'>: <function Parser.<lambda>>, <TokenType.START_WITH: 'START_WITH'>: <function Parser.<lambda>>, <TokenType.SETTINGS: 'SETTINGS'>: <function ClickHouse.Parser.<lambda>>, <TokenType.FORMAT: 'FORMAT'>: <function ClickHouse.Parser.<lambda>>}"}, "sqlglot.dialects.clickhouse.ClickHouse.Parser.CONSTRAINT_PARSERS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Parser.CONSTRAINT_PARSERS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Parser.CONSTRAINT_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'AUTOINCREMENT': <function Parser.<lambda>>, 'AUTO_INCREMENT': <function Parser.<lambda>>, 'CASESPECIFIC': <function Parser.<lambda>>, 'CHARACTER SET': <function Parser.<lambda>>, 'CHECK': <function Parser.<lambda>>, 'COLLATE': <function Parser.<lambda>>, 'COMMENT': <function Parser.<lambda>>, 'COMPRESS': <function Parser.<lambda>>, 'CLUSTERED': <function Parser.<lambda>>, 'NONCLUSTERED': <function Parser.<lambda>>, 'DEFAULT': <function Parser.<lambda>>, 'ENCODE': <function Parser.<lambda>>, 'EPHEMERAL': <function Parser.<lambda>>, 'EXCLUDE': <function Parser.<lambda>>, 'FOREIGN KEY': <function Parser.<lambda>>, 'FORMAT': <function Parser.<lambda>>, 'GENERATED': <function Parser.<lambda>>, 'IDENTITY': <function Parser.<lambda>>, 'INLINE': <function Parser.<lambda>>, 'LIKE': <function Parser.<lambda>>, 'NOT': <function Parser.<lambda>>, 'NULL': <function Parser.<lambda>>, 'ON': <function Parser.<lambda>>, 'PATH': <function Parser.<lambda>>, 'PERIOD': <function Parser.<lambda>>, 'PRIMARY KEY': <function Parser.<lambda>>, 'REFERENCES': <function Parser.<lambda>>, 'TITLE': <function Parser.<lambda>>, 'TTL': <function Parser.<lambda>>, 'UNIQUE': <function Parser.<lambda>>, 'UPPERCASE': <function Parser.<lambda>>, 'WITH': <function Parser.<lambda>>, 'INDEX': <function ClickHouse.Parser.<lambda>>, 'CODEC': <function ClickHouse.Parser.<lambda>>}"}, "sqlglot.dialects.clickhouse.ClickHouse.Parser.ALTER_PARSERS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Parser.ALTER_PARSERS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Parser.ALTER_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ADD': <function Parser.<lambda>>, 'ALTER': <function Parser.<lambda>>, 'CLUSTER BY': <function Parser.<lambda>>, 'DELETE': <function Parser.<lambda>>, 'DROP': <function Parser.<lambda>>, 'RENAME': <function Parser.<lambda>>, 'SET': <function Parser.<lambda>>, 'REPLACE': <function ClickHouse.Parser.<lambda>>}"}, "sqlglot.dialects.clickhouse.ClickHouse.Parser.SCHEMA_UNNAMED_CONSTRAINTS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Parser.SCHEMA_UNNAMED_CONSTRAINTS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Parser.SCHEMA_UNNAMED_CONSTRAINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'EXCLUDE', 'CHECK', 'PERIOD', 'UNIQUE', 'PRIMARY KEY', 'LIKE', 'FOREIGN KEY', 'INDEX'}"}, "sqlglot.dialects.clickhouse.ClickHouse.Parser.SHOW_TRIE": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Parser.SHOW_TRIE", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Parser.SHOW_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.clickhouse.ClickHouse.Parser.SET_TRIE": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Parser.SET_TRIE", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Parser.SET_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'GLOBAL': {0: True}, 'LOCAL': {0: True}, 'SESSION': {0: True}, 'TRANSACTION': {0: True}}"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator", "kind": "class", "doc": "<p>Generator converts a given syntax tree to the corresponding SQL string.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>pretty:</strong> Whether to format the produced SQL string.\nDefault: False.</li>\n<li><strong>identify:</strong> Determines when an identifier should be quoted. Possible values are:\nFalse (default): Never quote, except in cases where it's mandatory by the dialect.\nTrue or 'always': Always quote.\n'safe': Only quote identifiers that are case insensitive.</li>\n<li><strong>normalize:</strong> Whether to normalize identifiers to lowercase.\nDefault: False.</li>\n<li><strong>pad:</strong> The pad size in a formatted string. For example, this affects the indentation of\na projection in a query, relative to its nesting level.\nDefault: 2.</li>\n<li><strong>indent:</strong> The indentation size in a formatted string. For example, this affects the\nindentation of subqueries and filters under a <code>WHERE</code> clause.\nDefault: 2.</li>\n<li><strong>normalize_functions:</strong> How to normalize function names. Possible values are:\n\"upper\" or True (default): Convert names to uppercase.\n\"lower\": Convert names to lowercase.\nFalse: Disables function name normalization.</li>\n<li><strong>unsupported_level:</strong> Determines the generator's behavior when it encounters unsupported expressions.\nDefault ErrorLevel.WARN.</li>\n<li><strong>max_unsupported:</strong> Maximum number of unsupported messages to include in a raised UnsupportedError.\nThis is only relevant if unsupported_level is ErrorLevel.RAISE.\nDefault: 3</li>\n<li><strong>leading_comma:</strong> Whether the comma is leading or trailing in select expressions.\nThis is only relevant when generating in pretty mode.\nDefault: False</li>\n<li><strong>max_text_width:</strong> The max number of characters in a segment before creating new lines in pretty mode.\nThe default is on the smaller end because the length only represents a segment and not the true\nline length.\nDefault: 80</li>\n<li><strong>comments:</strong> Whether to preserve comments in the output SQL code.\nDefault: True</li>\n</ul>\n", "bases": "sqlglot.generator.Generator"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.QUERY_HINTS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.QUERY_HINTS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.QUERY_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.STRUCT_DELIMITER": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.STRUCT_DELIMITER", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.STRUCT_DELIMITER", "kind": "variable", "doc": "<p></p>\n", "default_value": "('(', ')')"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.NVL2_SUPPORTED": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.NVL2_SUPPORTED", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.NVL2_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.TABLESAMPLE_REQUIRES_PARENS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.TABLESAMPLE_REQUIRES_PARENS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.TABLESAMPLE_REQUIRES_PARENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.TABLESAMPLE_SIZE_IS_ROWS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.TABLESAMPLE_SIZE_IS_ROWS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.TABLESAMPLE_SIZE_IS_ROWS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.TABLESAMPLE_KEYWORDS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.TABLESAMPLE_KEYWORDS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.TABLESAMPLE_KEYWORDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "'SAMPLE'"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.LAST_DAY_SUPPORTS_DATE_PART": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.LAST_DAY_SUPPORTS_DATE_PART", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.LAST_DAY_SUPPORTS_DATE_PART", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.CAN_IMPLEMENT_ARRAY_ANY": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.CAN_IMPLEMENT_ARRAY_ANY", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.CAN_IMPLEMENT_ARRAY_ANY", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.SUPPORTS_TO_NUMBER": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.SUPPORTS_TO_NUMBER", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.SUPPORTS_TO_NUMBER", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.STRING_TYPE_MAPPING": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.STRING_TYPE_MAPPING", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.STRING_TYPE_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.CHAR: 'CHAR'>: 'String', <Type.LONGBLOB: 'LONGBLOB'>: 'String', <Type.LONGTEXT: 'LONGTEXT'>: 'String', <Type.MEDIUMBLOB: 'MEDIUMBLOB'>: 'String', <Type.MEDIUMTEXT: 'MEDIUMTEXT'>: 'String', <Type.TINYBLOB: 'TINYBLOB'>: 'String', <Type.TINYTEXT: 'TINYTEXT'>: 'String', <Type.TEXT: 'TEXT'>: 'String', <Type.VARBINARY: 'VARBINARY'>: 'String', <Type.VARCHAR: 'VARCHAR'>: 'String'}"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.SUPPORTED_JSON_PATH_PARTS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.SUPPORTED_JSON_PATH_PARTS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.SUPPORTED_JSON_PATH_PARTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.JSONPathSubscript'>, <class 'sqlglot.expressions.JSONPathRoot'>, <class 'sqlglot.expressions.JSONPathKey'>}"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.TYPE_MAPPING": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.TYPE_MAPPING", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.TYPE_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.NCHAR: 'NCHAR'>: 'CHAR', <Type.NVARCHAR: 'NVARCHAR'>: 'VARCHAR', <Type.MEDIUMTEXT: 'MEDIUMTEXT'>: 'String', <Type.LONGTEXT: 'LONGTEXT'>: 'String', <Type.TINYTEXT: 'TINYTEXT'>: 'String', <Type.MEDIUMBLOB: 'MEDIUMBLOB'>: 'String', <Type.LONGBLOB: 'LONGBLOB'>: 'String', <Type.TINYBLOB: 'TINYBLOB'>: 'String', <Type.INET: 'INET'>: 'INET', <Type.ROWVERSION: 'ROWVERSION'>: 'VARBINARY', <Type.CHAR: 'CHAR'>: 'String', <Type.TEXT: 'TEXT'>: 'String', <Type.VARBINARY: 'VARBINARY'>: 'String', <Type.VARCHAR: 'VARCHAR'>: 'String', <Type.ARRAY: 'ARRAY'>: 'Array', <Type.BIGINT: 'BIGINT'>: 'Int64', <Type.DATE32: 'DATE32'>: 'Date32', <Type.DATETIME64: 'DATETIME64'>: 'DateTime64', <Type.DOUBLE: 'DOUBLE'>: 'Float64', <Type.ENUM: 'ENUM'>: 'Enum', <Type.ENUM8: 'ENUM8'>: 'Enum8', <Type.ENUM16: 'ENUM16'>: 'Enum16', <Type.FIXEDSTRING: 'FIXEDSTRING'>: 'FixedString', <Type.FLOAT: 'FLOAT'>: 'Float32', <Type.INT: 'INT'>: 'Int32', <Type.MEDIUMINT: 'MEDIUMINT'>: 'Int32', <Type.INT128: 'INT128'>: 'Int128', <Type.INT256: 'INT256'>: 'Int256', <Type.LOWCARDINALITY: 'LOWCARDINALITY'>: 'LowCardinality', <Type.MAP: 'MAP'>: 'Map', <Type.NESTED: 'NESTED'>: 'Nested', <Type.NULLABLE: 'NULLABLE'>: 'Nullable', <Type.SMALLINT: 'SMALLINT'>: 'Int16', <Type.STRUCT: 'STRUCT'>: 'Tuple', <Type.TINYINT: 'TINYINT'>: 'Int8', <Type.UBIGINT: 'UBIGINT'>: 'UInt64', <Type.UINT: 'UINT'>: 'UInt32', <Type.UINT128: 'UINT128'>: 'UInt128', <Type.UINT256: 'UINT256'>: 'UInt256', <Type.USMALLINT: 'USMALLINT'>: 'UInt16', <Type.UTINYINT: 'UTINYINT'>: 'UInt8', <Type.IPV4: 'IPV4'>: 'IPv4', <Type.IPV6: 'IPV6'>: 'IPv6', <Type.AGGREGATEFUNCTION: 'AGGREGATEFUNCTION'>: 'AggregateFunction', <Type.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>: 'SimpleAggregateFunction'}"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.TRANSFORMS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.TRANSFORMS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.JSONPathKey'>: <function json_path_key_only_name>, <class 'sqlglot.expressions.JSONPathRoot'>: <function ClickHouse.Generator.<lambda>>, <class 'sqlglot.expressions.JSONPathSubscript'>: <function <lambda>>, <class 'sqlglot.expressions.AllowedValuesProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.BackupProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CaseSpecificColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CollateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CommentColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DateFormatColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DefaultColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EncodeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EphemeralColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExcludeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExternalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.GlobalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.HeapProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IcebergProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InheritsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InlineLengthColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IntervalSpan'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtract'>: <function json_extract_segments.<locals>._json_extract_segments>, <class 'sqlglot.expressions.JSONExtractScalar'>: <function json_extract_segments.<locals>._json_extract_segments>, <class 'sqlglot.expressions.LanguageProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LocationProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LogProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.MaterializedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NonClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NotForReplicationColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnCommitProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnUpdateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OutputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.PathColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ReturnsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SampleProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetConfigProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SettingsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SharingProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlReadWriteProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlSecurityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StabilityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StrictProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TemporaryProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TitleColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.Timestamp'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransformModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransientProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UppercaseColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UnloggedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VarMap'>: <function ClickHouse.Generator.<lambda>>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VolatileProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithOperator'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.AnyValue'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ApproxDistinct'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ArrayFilter'>: <function ClickHouse.Generator.<lambda>>, <class 'sqlglot.expressions.ArraySize'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ArraySum'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ArgMax'>: <function arg_max_or_min_no_count.<locals>._arg_max_or_min_sql>, <class 'sqlglot.expressions.ArgMin'>: <function arg_max_or_min_no_count.<locals>._arg_max_or_min_sql>, <class 'sqlglot.expressions.Array'>: <function inline_array_sql>, <class 'sqlglot.expressions.CastToStrType'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.CountIf'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.CompressColumnConstraint'>: <function ClickHouse.Generator.<lambda>>, <class 'sqlglot.expressions.ComputedColumnConstraint'>: <function ClickHouse.Generator.<lambda>>, <class 'sqlglot.expressions.CurrentDate'>: <function ClickHouse.Generator.<lambda>>, <class 'sqlglot.expressions.DateAdd'>: <function date_delta_sql.<locals>._delta_sql>, <class 'sqlglot.expressions.DateDiff'>: <function date_delta_sql.<locals>._delta_sql>, <class 'sqlglot.expressions.Explode'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.Final'>: <function ClickHouse.Generator.<lambda>>, <class 'sqlglot.expressions.IsNan'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.Map'>: <function ClickHouse.Generator.<lambda>>, <class 'sqlglot.expressions.Nullif'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.PartitionedByProperty'>: <function ClickHouse.Generator.<lambda>>, <class 'sqlglot.expressions.Pivot'>: <function no_pivot_sql>, <class 'sqlglot.expressions.Quantile'>: <function _quantile_sql>, <class 'sqlglot.expressions.RegexpLike'>: <function ClickHouse.Generator.<lambda>>, <class 'sqlglot.expressions.Rand'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.Select'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.StartsWith'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.StrPosition'>: <function ClickHouse.Generator.<lambda>>, <class 'sqlglot.expressions.TimeToStr'>: <function ClickHouse.Generator.<lambda>>, <class 'sqlglot.expressions.Xor'>: <function ClickHouse.Generator.<lambda>>, <class 'sqlglot.expressions.MD5Digest'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.MD5'>: <function ClickHouse.Generator.<lambda>>, <class 'sqlglot.expressions.SHA'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.SHA2'>: <function ClickHouse.Generator.<lambda>>, <class 'sqlglot.expressions.UnixToTime'>: <function _unix_to_time_sql>, <class 'sqlglot.expressions.TimestampTrunc'>: <function timestamptrunc_sql.<locals>._timestamptrunc_sql>, <class 'sqlglot.expressions.Variance'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.Stddev'>: <function rename_func.<locals>.<lambda>>}"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.PROPERTIES_LOCATION": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.PROPERTIES_LOCATION", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.PROPERTIES_LOCATION", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.AllowedValuesProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.AlgorithmProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.AutoIncrementProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.BackupProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.BlockCompressionProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.CharacterSetProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ChecksumProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.CollateProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Cluster'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ClusteredByProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DataBlocksizeProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.DataDeletionProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DefinerProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.DictRange'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DictProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DistKeyProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DistStyleProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.EngineProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ExternalProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.FallbackProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.FileFormatProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.FreespaceProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.GlobalProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.HeapProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.InheritsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.IcebergProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.InputModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.IsolatedLoadingProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.JournalProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.LanguageProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LikeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LocationProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LockProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LockingProperty'>: <Location.POST_ALIAS: 'POST_ALIAS'>, <class 'sqlglot.expressions.LogProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.MaterializedProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.MergeBlockRatioProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.OnProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.OnCommitProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.Order'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.OutputModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.PartitionedByProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.PartitionedOfProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.PrimaryKey'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Property'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ReturnsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatDelimitedProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatSerdeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SampleProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SchemaCommentProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SerdeProperties'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Set'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SettingsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SetProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 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'sqlglot.expressions.TransformModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.MergeTreeTTL'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.UnloggedProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.VolatileProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.WithDataProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.WithSystemVersioningProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.OnCluster'>: <Location.POST_NAME: 'POST_NAME'>}"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.JOIN_HINTS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.JOIN_HINTS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.JOIN_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.TABLE_HINTS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.TABLE_HINTS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.TABLE_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.EXPLICIT_UNION": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.EXPLICIT_UNION", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.EXPLICIT_UNION", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.GROUPINGS_SEP": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.GROUPINGS_SEP", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.GROUPINGS_SEP", "kind": "variable", "doc": "<p></p>\n", "default_value": "''"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.OUTER_UNION_MODIFIERS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.OUTER_UNION_MODIFIERS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.OUTER_UNION_MODIFIERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.ON_CLUSTER_TARGETS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.ON_CLUSTER_TARGETS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.ON_CLUSTER_TARGETS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'DATABASE', 'VIEW', 'NAMED COLLECTION', 'DICTIONARY', 'TABLE', 'FUNCTION', 'INDEX'}"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.likeproperty_sql": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.likeproperty_sql", "modulename": "sqlglot.dialects.clickhouse", "qualname": 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class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">EQ</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.neq_sql": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.neq_sql", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.neq_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">NEQ</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.regexpilike_sql": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.regexpilike_sql", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.regexpilike_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">RegexpILike</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.datatype_sql": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.datatype_sql", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.datatype_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.cte_sql": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.cte_sql", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.cte_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">CTE</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.after_limit_modifiers": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.after_limit_modifiers", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.after_limit_modifiers", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.parameterizedagg_sql": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.parameterizedagg_sql", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.parameterizedagg_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ParameterizedAgg</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.anonymousaggfunc_sql": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.anonymousaggfunc_sql", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.anonymousaggfunc_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">AnonymousAggFunc</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.combinedaggfunc_sql": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.combinedaggfunc_sql", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.combinedaggfunc_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">CombinedAggFunc</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.combinedparameterizedagg_sql": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.combinedparameterizedagg_sql", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.combinedparameterizedagg_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">CombinedParameterizedAgg</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.placeholder_sql": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.placeholder_sql", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.placeholder_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Placeholder</span></span><span class=\"return-annotation\">) -> 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"sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.createable_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Create</span>,</span><span class=\"param\">\t<span class=\"n\">locations</span><span class=\"p\">:</span> <span class=\"n\">DefaultDict</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.prewhere_sql": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.prewhere_sql", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.prewhere_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">PreWhere</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.indexcolumnconstraint_sql": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.indexcolumnconstraint_sql", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.indexcolumnconstraint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">IndexColumnConstraint</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.partition_sql": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.partition_sql", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.partition_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Partition</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.partitionid_sql": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.partitionid_sql", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.partitionid_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">PartitionId</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.replacepartition_sql": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.replacepartition_sql", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.replacepartition_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ReplacePartition</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.projectiondef_sql": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.projectiondef_sql", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.projectiondef_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ProjectionDef</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.SELECT_KINDS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.SELECT_KINDS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.SELECT_KINDS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Tuple[str, ...]", "default_value": "()"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.TRY_SUPPORTED": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.TRY_SUPPORTED", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.TRY_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.clickhouse.ClickHouse.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'qualify': <function Generator.<lambda>>, 'windows': <function Generator.<lambda>>}"}, "sqlglot.dialects.clickhouse.ClickHouse.tokenizer_class": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.tokenizer_class", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.tokenizer_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.clickhouse.ClickHouse.Tokenizer'>"}, "sqlglot.dialects.clickhouse.ClickHouse.parser_class": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.parser_class", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.parser_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.clickhouse.ClickHouse.Parser'>"}, "sqlglot.dialects.clickhouse.ClickHouse.generator_class": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.generator_class", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.generator_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.clickhouse.ClickHouse.Generator'>"}, "sqlglot.dialects.clickhouse.ClickHouse.TIME_TRIE": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.TIME_TRIE", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.clickhouse.ClickHouse.FORMAT_TRIE": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.FORMAT_TRIE", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.FORMAT_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.clickhouse.ClickHouse.INVERSE_TIME_MAPPING": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.INVERSE_TIME_MAPPING", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.INVERSE_TIME_MAPPING", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{}"}, "sqlglot.dialects.clickhouse.ClickHouse.INVERSE_TIME_TRIE": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.INVERSE_TIME_TRIE", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.INVERSE_TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.clickhouse.ClickHouse.ESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.ESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.ESCAPED_SEQUENCES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'\\x07': '\\\\a', '\\x08': '\\\\b', '\\x0c': '\\\\f', '\\n': '\\\\n', '\\r': '\\\\r', '\\t': '\\\\t', '\\x0b': '\\\\v', '\\\\': '\\\\\\\\', '\\x00': '\\\\0'}"}, "sqlglot.dialects.clickhouse.ClickHouse.QUOTE_START": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.QUOTE_START", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.QUOTE_START", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.clickhouse.ClickHouse.QUOTE_END": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.QUOTE_END", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.QUOTE_END", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.clickhouse.ClickHouse.IDENTIFIER_START": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.IDENTIFIER_START", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.IDENTIFIER_START", "kind": "variable", "doc": "<p></p>\n", "default_value": "'"'"}, "sqlglot.dialects.clickhouse.ClickHouse.IDENTIFIER_END": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.IDENTIFIER_END", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.IDENTIFIER_END", "kind": "variable", "doc": "<p></p>\n", "default_value": "'"'"}, "sqlglot.dialects.clickhouse.ClickHouse.BIT_START": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.BIT_START", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.BIT_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "'0b'"}, "sqlglot.dialects.clickhouse.ClickHouse.BIT_END": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.BIT_END", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.BIT_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "''"}, "sqlglot.dialects.clickhouse.ClickHouse.HEX_START": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.HEX_START", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.HEX_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "'0x'"}, "sqlglot.dialects.clickhouse.ClickHouse.HEX_END": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.HEX_END", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.HEX_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "''"}, "sqlglot.dialects.clickhouse.ClickHouse.BYTE_START": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.BYTE_START", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.BYTE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.clickhouse.ClickHouse.BYTE_END": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.BYTE_END", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.BYTE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.clickhouse.ClickHouse.UNICODE_START": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.UNICODE_START", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.UNICODE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.clickhouse.ClickHouse.UNICODE_END": {"fullname": "sqlglot.dialects.clickhouse.ClickHouse.UNICODE_END", "modulename": "sqlglot.dialects.clickhouse", "qualname": "ClickHouse.UNICODE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.databricks": {"fullname": "sqlglot.dialects.databricks", "modulename": "sqlglot.dialects.databricks", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.dialects.databricks.Databricks": {"fullname": "sqlglot.dialects.databricks.Databricks", "modulename": "sqlglot.dialects.databricks", "qualname": "Databricks", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.spark.Spark"}, "sqlglot.dialects.databricks.Databricks.SAFE_DIVISION": {"fullname": "sqlglot.dialects.databricks.Databricks.SAFE_DIVISION", "modulename": "sqlglot.dialects.databricks", "qualname": "Databricks.SAFE_DIVISION", "kind": "variable", "doc": "<p>Whether division by zero throws an error (<code>False</code>) or returns NULL (<code>True</code>).</p>\n", "default_value": "False"}, "sqlglot.dialects.databricks.Databricks.COPY_PARAMS_ARE_CSV": {"fullname": "sqlglot.dialects.databricks.Databricks.COPY_PARAMS_ARE_CSV", "modulename": "sqlglot.dialects.databricks", "qualname": "Databricks.COPY_PARAMS_ARE_CSV", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.databricks.Databricks.Parser": {"fullname": "sqlglot.dialects.databricks.Databricks.Parser", "modulename": "sqlglot.dialects.databricks", "qualname": "Databricks.Parser", "kind": "class", "doc": "<p>Parser consumes a list of tokens produced by the Tokenizer and produces a parsed syntax tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>error_level:</strong> The desired error level.\nDefault: ErrorLevel.IMMEDIATE</li>\n<li><strong>error_message_context:</strong> The amount of context to capture from a query string when displaying\nthe error message (in number of characters).\nDefault: 100</li>\n<li><strong>max_errors:</strong> Maximum number of error messages to include in a raised ParseError.\nThis is only relevant if error_level is ErrorLevel.RAISE.\nDefault: 3</li>\n</ul>\n", "bases": "sqlglot.dialects.spark.Spark.Parser"}, "sqlglot.dialects.databricks.Databricks.Parser.LOG_DEFAULTS_TO_LN": {"fullname": "sqlglot.dialects.databricks.Databricks.Parser.LOG_DEFAULTS_TO_LN", "modulename": "sqlglot.dialects.databricks", "qualname": "Databricks.Parser.LOG_DEFAULTS_TO_LN", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.databricks.Databricks.Parser.STRICT_CAST": {"fullname": "sqlglot.dialects.databricks.Databricks.Parser.STRICT_CAST", "modulename": "sqlglot.dialects.databricks", "qualname": "Databricks.Parser.STRICT_CAST", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.databricks.Databricks.Parser.COLON_IS_JSON_EXTRACT": {"fullname": "sqlglot.dialects.databricks.Databricks.Parser.COLON_IS_JSON_EXTRACT", "modulename": "sqlglot.dialects.databricks", "qualname": "Databricks.Parser.COLON_IS_JSON_EXTRACT", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.databricks.Databricks.Parser.FUNCTIONS": {"fullname": "sqlglot.dialects.databricks.Databricks.Parser.FUNCTIONS", "modulename": "sqlglot.dialects.databricks", "qualname": "Databricks.Parser.FUNCTIONS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ABS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Abs'>>, 'ADD_MONTHS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AddMonths'>>, 'ANONYMOUS_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnonymousAggFunc'>>, 'ANY_VALUE': <function _build_with_ignore_nulls.<locals>._parse>, 'APPROX_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_COUNT_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'APPROX_TOP_K': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxTopK'>>, 'ARG_MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARGMAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'MAX_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARG_MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARGMIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'MIN_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Array'>>, 'ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAgg'>>, 'ARRAY_ALL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAll'>>, 'ARRAY_ANY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAny'>>, 'ARRAY_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CONSTRUCT_COMPACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConstructCompact'>>, 'ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayContains'>>, 'FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_OVERLAPS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayOverlaps'>>, 'ARRAY_SIZE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_SORT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySort'>>, 'ARRAY_SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySum'>>, 'ARRAY_TO_STRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_JOIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_UNION_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUnionAgg'>>, 'ARRAY_UNIQUE_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUniqueAgg'>>, 'AVG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Avg'>>, 'CASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Case'>>, 'CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cast'>>, 'CAST_TO_STR_TYPE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CastToStrType'>>, 'CBRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cbrt'>>, 'CEIL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CEILING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CHR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'COALESCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'IFNULL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'NVL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'COLLATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Collate'>>, 'COMBINED_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedAggFunc'>>, 'COMBINED_PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedParameterizedAgg'>>, 'CONCAT': <function Parser.<lambda>>, 'CONCAT_WS': <function Parser.<lambda>>, 'CONNECT_BY_ROOT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ConnectByRoot'>>, 'CONVERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Convert'>>, 'CORR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Corr'>>, 'COUNT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Count'>>, 'COUNT_IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COUNTIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COVAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarPop'>>, 'COVAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarSamp'>>, 'CURRENT_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDate'>>, 'CURRENT_DATETIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDatetime'>>, 'CURRENT_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTime'>>, 'CURRENT_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTimestamp'>>, 'CURRENT_USER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentUser'>>, 'DATE': <function _build_as_cast.<locals>.<lambda>>, 'DATE_ADD': <function build_date_delta.<locals>._builder>, 'DATEDIFF': <function build_date_delta.<locals>._builder>, 'DATE_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateDiff'>>, 'DATE_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATE_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateStrToDate'>>, 'DATE_SUB': <function Hive.Parser.<lambda>>, 'DATE_TO_DATE_STR': <function Parser.<lambda>>, 'DATE_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateToDi'>>, 'DATE_TRUNC': <function Spark2.Parser.<lambda>>, 'DATETIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeAdd'>>, 'DATETIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeDiff'>>, 'DATETIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeSub'>>, 'DATETIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeTrunc'>>, 'DAY': <function Hive.Parser.<lambda>>, 'DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAYOFMONTH': <function Spark2.Parser.<lambda>>, 'DAY_OF_WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAYOFWEEK': <function Spark2.Parser.<lambda>>, 'DAY_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DAYOFYEAR': <function Spark2.Parser.<lambda>>, 'DECODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Decode'>>, 'DI_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DiToDate'>>, 'ENCODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Encode'>>, 'EXP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Exp'>>, 'EXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Explode'>>, 'EXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ExplodeOuter'>>, 'EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Extract'>>, 'FIRST': <function _build_with_ignore_nulls.<locals>._parse>, 'FIRST_VALUE': <function _build_with_ignore_nulls.<locals>._parse>, 'FLATTEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Flatten'>>, 'FLOOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Floor'>>, 'FROM_BASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase'>>, 'FROM_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase64'>>, 'GENERATE_DATE_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GenerateDateArray'>>, 'GENERATE_SERIES': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GenerateSeries'>>, 'GREATEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Greatest'>>, 'GROUP_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GroupConcat'>>, 'HEX': <function build_hex>, 'HLL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Hll'>>, 'IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'IIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'INITCAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Initcap'>>, 'IS_INF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'ISINF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'IS_NAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'ISNAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'J_S_O_N_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArray'>>, 'J_S_O_N_ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArrayAgg'>>, 'JSON_ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArrayContains'>>, 'JSONB_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONBExtract'>>, 'JSONB_EXTRACT_SCALAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONBExtractScalar'>>, 'JSON_EXTRACT': <function build_extract_json_with_path.<locals>._builder>, 'JSON_EXTRACT_SCALAR': <function build_extract_json_with_path.<locals>._builder>, 'JSON_FORMAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONFormat'>>, 'J_S_O_N_OBJECT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONObject'>>, 'J_S_O_N_OBJECT_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONObjectAgg'>>, 'J_S_O_N_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONTable'>>, 'LAG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lag'>>, 'LAST': <function _build_with_ignore_nulls.<locals>._parse>, 'LAST_DAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastDay'>>, 'LAST_DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastDay'>>, 'LAST_VALUE': <function _build_with_ignore_nulls.<locals>._parse>, 'LEAD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lead'>>, 'LEAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Least'>>, 'LEFT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Left'>>, 'LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Length'>>, 'LEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Length'>>, 'LEVENSHTEIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Levenshtein'>>, 'LN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ln'>>, 'LOG': <function build_logarithm>, 'LOGICAL_AND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'BOOL_AND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'BOOLAND_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'LOGICAL_OR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'BOOL_OR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'BOOLOR_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'LOWER': <function build_lower>, 'LCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lower'>>, 'LOWER_HEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LowerHex'>>, 'MD5': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MD5'>>, 'MD5_DIGEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MD5Digest'>>, 'MAP': <function build_var_map>, 'MAP_FROM_ENTRIES': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MapFromEntries'>>, 'MATCH_AGAINST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MatchAgainst'>>, 'MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Max'>>, 'MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Min'>>, 'MONTH': <function Hive.Parser.<lambda>>, 'MONTHS_BETWEEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MonthsBetween'>>, 'NEXT_VALUE_FOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NextValueFor'>>, 'NTH_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NthValue'>>, 'NULLIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Nullif'>>, 'NUMBER_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NumberToStr'>>, 'NVL2': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Nvl2'>>, 'OPEN_J_S_O_N': <bound method Func.from_arg_list of <class 'sqlglot.expressions.OpenJSON'>>, 'PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParameterizedAgg'>>, 'PARSE_JSON': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParseJSON'>>, 'JSON_PARSE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParseJSON'>>, 'PERCENTILE_CONT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PercentileCont'>>, 'PERCENTILE_DISC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PercentileDisc'>>, 'POSEXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Posexplode'>>, 'POSEXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PosexplodeOuter'>>, 'POWER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Pow'>>, 'POW': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Pow'>>, 'PREDICT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Predict'>>, 'QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quantile'>>, 'QUARTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quarter'>>, 'RAND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'RANDOM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'RANDN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Randn'>>, 'RANGE_N': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RangeN'>>, 'READ_CSV': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ReadCSV'>>, 'REDUCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Reduce'>>, 'REGEXP_EXTRACT': <function Hive.Parser.<lambda>>, 'REGEXP_I_LIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpILike'>>, 'REGEXP_LIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpLike'>>, 'REGEXP_REPLACE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpReplace'>>, 'REGEXP_SPLIT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpSplit'>>, 'REPEAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Repeat'>>, 'RIGHT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Right'>>, 'ROUND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Round'>>, 'ROW_NUMBER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RowNumber'>>, 'SHA': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA'>>, 'SHA1': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA'>>, 'SHA2': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA2'>>, 'SAFE_DIVIDE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SafeDivide'>>, 'SIGN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sign'>>, 'SIGNUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sign'>>, 'SORT_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SortArray'>>, 'SPLIT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpSplit'>>, 'SQRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sqrt'>>, 'STANDARD_HASH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StandardHash'>>, 'STAR_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StarMap'>>, 'STARTS_WITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STARTSWITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STDDEV': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stddev'>>, 'STDDEV_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StddevPop'>>, 'STDDEV_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StddevSamp'>>, 'STR_POSITION': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrPosition'>>, 'STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToDate'>>, 'STR_TO_MAP': <function Hive.Parser.<lambda>>, 'STR_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToTime'>>, 'STR_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToUnix'>>, 'STRUCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Struct'>>, 'STRUCT_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StructExtract'>>, 'STUFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stuff'>>, 'INSERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stuff'>>, 'SUBSTRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Substring'>>, 'SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sum'>>, 'TIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeAdd'>>, 'TIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeDiff'>>, 'TIME_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'TIMEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'TIME_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToDate'>>, 'TIME_STR_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToTime'>>, 'TIME_STR_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToUnix'>>, 'TIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeSub'>>, 'TIME_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeToStr'>>, 'TIME_TO_TIME_STR': <function Parser.<lambda>>, 'TIME_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeToUnix'>>, 'TIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeTrunc'>>, 'TIMESTAMP': <function _build_as_cast.<locals>.<lambda>>, 'TIMESTAMP_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampAdd'>>, 'TIMESTAMPDIFF': <function build_date_delta.<locals>._builder>, 'TIMESTAMP_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampDiff'>>, 'TIMESTAMP_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampFromParts'>>, 'TIMESTAMPFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampFromParts'>>, 'TIMESTAMP_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampSub'>>, 'TIMESTAMP_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampTrunc'>>, 'TO_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToArray'>>, 'TO_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToBase64'>>, 'TO_CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToChar'>>, 'TO_DAYS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToDays'>>, 'TO_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToMap'>>, 'TO_NUMBER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToNumber'>>, 'TRANSFORM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Transform'>>, 'TRIM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Trim'>>, 'TRY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Try'>>, 'TRY_CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TryCast'>>, 'TS_OR_DI_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDiToDi'>>, 'TS_OR_DS_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsAdd'>>, 'TS_OR_DS_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsDiff'>>, 'TS_OR_DS_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToDate'>>, 'TS_OR_DS_TO_DATE_STR': <function Parser.<lambda>>, 'TS_OR_DS_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTime'>>, 'TS_OR_DS_TO_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTimestamp'>>, 'UNHEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Unhex'>>, 'UNIX_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixDate'>>, 'UNIX_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToStr'>>, 'UNIX_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTime'>>, 'UNIX_TO_TIME_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTimeStr'>>, 'UPPER': <function build_upper>, 'UCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Upper'>>, 'VAR_MAP': <function build_var_map>, 'VARIANCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'VAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Week'>>, 'WEEK_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.WeekOfYear'>>, 'WEEKOFYEAR': <function Spark2.Parser.<lambda>>, 'WHEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.When'>>, 'X_M_L_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.XMLTable'>>, 'XOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Xor'>>, 'YEAR': <function Hive.Parser.<lambda>>, 'GLOB': <function Parser.<lambda>>, 'JSON_EXTRACT_PATH_TEXT': <function build_extract_json_with_path.<locals>._builder>, 'LIKE': <function build_like>, 'LOG2': <function Parser.<lambda>>, 'LOG10': <function Parser.<lambda>>, 'MOD': <function build_mod>, 'TO_HEX': <function build_hex>, 'BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToBase64'>>, 'COLLECT_LIST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAgg'>>, 'COLLECT_SET': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUniqueAgg'>>, 'DATE_FORMAT': <function Hive.Parser.<lambda>>, 'FROM_UNIXTIME': <function build_formatted_time.<locals>._builder>, 'GET_JSON_OBJECT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONExtractScalar'>>, 'LOCATE': <function locate_to_strposition>, 'PERCENTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quantile'>>, 'PERCENTILE_APPROX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'SIZE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'TO_DATE': <function build_formatted_time.<locals>._builder>, 'TO_JSON': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONFormat'>>, 'UNBASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase64'>>, 'UNIX_TIMESTAMP': <function Hive.Parser.<lambda>>, 'AGGREGATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Reduce'>>, 'APPROX_PERCENTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'BOOLEAN': <function _build_as_cast.<locals>.<lambda>>, 'DOUBLE': <function _build_as_cast.<locals>.<lambda>>, 'FLOAT': <function _build_as_cast.<locals>.<lambda>>, 'FROM_UTC_TIMESTAMP': <function Spark2.Parser.<lambda>>, 'INT': <function _build_as_cast.<locals>.<lambda>>, 'MAP_FROM_ARRAYS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Map'>>, 'RLIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpLike'>>, 'SHIFTLEFT': <function binary_from_function.<locals>.<lambda>>, 'SHIFTRIGHT': <function binary_from_function.<locals>.<lambda>>, 'STRING': <function _build_as_cast.<locals>.<lambda>>, 'TO_TIMESTAMP': <function Spark2.Parser.<lambda>>, 'TO_UNIX_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToUnix'>>, 'TO_UTC_TIMESTAMP': <function Spark2.Parser.<lambda>>, 'TRUNC': <function Spark2.Parser.<lambda>>, 'TIMESTAMP_LTZ': <function _build_as_cast.<locals>.<lambda>>, 'TIMESTAMP_NTZ': <function _build_as_cast.<locals>.<lambda>>, 'TRY_ELEMENT_AT': <function Spark.Parser.<lambda>>, 'DATEADD': <function build_date_delta.<locals>._builder>}"}, "sqlglot.dialects.databricks.Databricks.Parser.FACTOR": {"fullname": "sqlglot.dialects.databricks.Databricks.Parser.FACTOR", "modulename": "sqlglot.dialects.databricks", "qualname": "Databricks.Parser.FACTOR", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.DIV: 'DIV'>: <class 'sqlglot.expressions.IntDiv'>, <TokenType.LR_ARROW: 'LR_ARROW'>: <class 'sqlglot.expressions.Distance'>, <TokenType.SLASH: 'SLASH'>: <class 'sqlglot.expressions.Div'>, <TokenType.STAR: 'STAR'>: <class 'sqlglot.expressions.Mul'>, <TokenType.COLON: 'COLON'>: <class 'sqlglot.expressions.JSONExtract'>}"}, "sqlglot.dialects.databricks.Databricks.Parser.SHOW_TRIE": {"fullname": "sqlglot.dialects.databricks.Databricks.Parser.SHOW_TRIE", "modulename": "sqlglot.dialects.databricks", "qualname": "Databricks.Parser.SHOW_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.databricks.Databricks.Parser.SET_TRIE": {"fullname": "sqlglot.dialects.databricks.Databricks.Parser.SET_TRIE", "modulename": "sqlglot.dialects.databricks", "qualname": "Databricks.Parser.SET_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'GLOBAL': {0: True}, 'LOCAL': {0: True}, 'SESSION': {0: True}, 'TRANSACTION': {0: True}}"}, "sqlglot.dialects.databricks.Databricks.Generator": {"fullname": "sqlglot.dialects.databricks.Databricks.Generator", "modulename": "sqlglot.dialects.databricks", "qualname": "Databricks.Generator", "kind": "class", "doc": "<p>Generator converts a given syntax tree to the corresponding SQL string.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>pretty:</strong> Whether to format the produced SQL string.\nDefault: False.</li>\n<li><strong>identify:</strong> Determines when an identifier should be quoted. Possible values are:\nFalse (default): Never quote, except in cases where it's mandatory by the dialect.\nTrue or 'always': Always quote.\n'safe': Only quote identifiers that are case insensitive.</li>\n<li><strong>normalize:</strong> Whether to normalize identifiers to lowercase.\nDefault: False.</li>\n<li><strong>pad:</strong> The pad size in a formatted string. For example, this affects the indentation of\na projection in a query, relative to its nesting level.\nDefault: 2.</li>\n<li><strong>indent:</strong> The indentation size in a formatted string. For example, this affects the\nindentation of subqueries and filters under a <code>WHERE</code> clause.\nDefault: 2.</li>\n<li><strong>normalize_functions:</strong> How to normalize function names. Possible values are:\n\"upper\" or True (default): Convert names to uppercase.\n\"lower\": Convert names to lowercase.\nFalse: Disables function name normalization.</li>\n<li><strong>unsupported_level:</strong> Determines the generator's behavior when it encounters unsupported expressions.\nDefault ErrorLevel.WARN.</li>\n<li><strong>max_unsupported:</strong> Maximum number of unsupported messages to include in a raised UnsupportedError.\nThis is only relevant if unsupported_level is ErrorLevel.RAISE.\nDefault: 3</li>\n<li><strong>leading_comma:</strong> Whether the comma is leading or trailing in select expressions.\nThis is only relevant when generating in pretty mode.\nDefault: False</li>\n<li><strong>max_text_width:</strong> The max number of characters in a segment before creating new lines in pretty mode.\nThe default is on the smaller end because the length only represents a segment and not the true\nline length.\nDefault: 80</li>\n<li><strong>comments:</strong> Whether to preserve comments in the output SQL code.\nDefault: True</li>\n</ul>\n", "bases": "sqlglot.dialects.spark.Spark.Generator"}, "sqlglot.dialects.databricks.Databricks.Generator.TABLESAMPLE_SEED_KEYWORD": {"fullname": "sqlglot.dialects.databricks.Databricks.Generator.TABLESAMPLE_SEED_KEYWORD", "modulename": "sqlglot.dialects.databricks", "qualname": "Databricks.Generator.TABLESAMPLE_SEED_KEYWORD", "kind": "variable", "doc": "<p></p>\n", "default_value": "'REPEATABLE'"}, "sqlglot.dialects.databricks.Databricks.Generator.COPY_PARAMS_ARE_WRAPPED": {"fullname": "sqlglot.dialects.databricks.Databricks.Generator.COPY_PARAMS_ARE_WRAPPED", "modulename": "sqlglot.dialects.databricks", "qualname": "Databricks.Generator.COPY_PARAMS_ARE_WRAPPED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.databricks.Databricks.Generator.COPY_PARAMS_EQ_REQUIRED": {"fullname": "sqlglot.dialects.databricks.Databricks.Generator.COPY_PARAMS_EQ_REQUIRED", "modulename": "sqlglot.dialects.databricks", "qualname": "Databricks.Generator.COPY_PARAMS_EQ_REQUIRED", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.databricks.Databricks.Generator.TRANSFORMS": {"fullname": "sqlglot.dialects.databricks.Databricks.Generator.TRANSFORMS", "modulename": "sqlglot.dialects.databricks", "qualname": "Databricks.Generator.TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.JSONPathKey'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRoot'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSubscript'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathWildcard'>: <function <lambda>>, <class 'sqlglot.expressions.AllowedValuesProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.BackupProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CaseSpecificColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ClusteredColumnConstraint'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.CollateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CommentColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DateFormatColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DefaultColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EncodeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EphemeralColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExcludeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExternalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.GlobalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.HeapProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IcebergProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InheritsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InlineLengthColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IntervalSpan'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtract'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtractScalar'>: <function Hive.Generator.<lambda>>, <class 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"sqlglot.dialects.databricks.Databricks.UNICODE_START": {"fullname": "sqlglot.dialects.databricks.Databricks.UNICODE_START", "modulename": "sqlglot.dialects.databricks", "qualname": "Databricks.UNICODE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.databricks.Databricks.UNICODE_END": {"fullname": "sqlglot.dialects.databricks.Databricks.UNICODE_END", "modulename": "sqlglot.dialects.databricks", "qualname": "Databricks.UNICODE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.dialect": {"fullname": "sqlglot.dialects.dialect", "modulename": "sqlglot.dialects.dialect", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.dialects.dialect.DATE_ADD_OR_DIFF": {"fullname": "sqlglot.dialects.dialect.DATE_ADD_OR_DIFF", "modulename": "sqlglot.dialects.dialect", "qualname": "DATE_ADD_OR_DIFF", "kind": "variable", "doc": "<p></p>\n", "default_value": "typing.Union[sqlglot.expressions.DateAdd, sqlglot.expressions.TsOrDsAdd, sqlglot.expressions.DateDiff, sqlglot.expressions.TsOrDsDiff]"}, "sqlglot.dialects.dialect.DATE_ADD_OR_SUB": {"fullname": "sqlglot.dialects.dialect.DATE_ADD_OR_SUB", "modulename": "sqlglot.dialects.dialect", "qualname": "DATE_ADD_OR_SUB", "kind": "variable", "doc": "<p></p>\n", "default_value": "typing.Union[sqlglot.expressions.DateAdd, sqlglot.expressions.TsOrDsAdd, sqlglot.expressions.DateSub]"}, "sqlglot.dialects.dialect.JSON_EXTRACT_TYPE": {"fullname": "sqlglot.dialects.dialect.JSON_EXTRACT_TYPE", "modulename": "sqlglot.dialects.dialect", "qualname": "JSON_EXTRACT_TYPE", "kind": "variable", "doc": "<p></p>\n", "default_value": "typing.Union[sqlglot.expressions.JSONExtract, sqlglot.expressions.JSONExtractScalar]"}, "sqlglot.dialects.dialect.logger": {"fullname": "sqlglot.dialects.dialect.logger", "modulename": "sqlglot.dialects.dialect", "qualname": "logger", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Logger sqlglot (WARNING)>"}, "sqlglot.dialects.dialect.Dialects": {"fullname": "sqlglot.dialects.dialect.Dialects", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialects", "kind": "class", "doc": "<p>Dialects supported by SQLGLot.</p>\n", "bases": "builtins.str, enum.Enum"}, "sqlglot.dialects.dialect.Dialects.DIALECT": {"fullname": "sqlglot.dialects.dialect.Dialects.DIALECT", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialects.DIALECT", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Dialects.DIALECT: ''>"}, "sqlglot.dialects.dialect.Dialects.ATHENA": {"fullname": "sqlglot.dialects.dialect.Dialects.ATHENA", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialects.ATHENA", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Dialects.ATHENA: 'athena'>"}, "sqlglot.dialects.dialect.Dialects.BIGQUERY": {"fullname": "sqlglot.dialects.dialect.Dialects.BIGQUERY", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialects.BIGQUERY", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Dialects.BIGQUERY: 'bigquery'>"}, "sqlglot.dialects.dialect.Dialects.CLICKHOUSE": {"fullname": "sqlglot.dialects.dialect.Dialects.CLICKHOUSE", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialects.CLICKHOUSE", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Dialects.CLICKHOUSE: 'clickhouse'>"}, "sqlglot.dialects.dialect.Dialects.DATABRICKS": {"fullname": "sqlglot.dialects.dialect.Dialects.DATABRICKS", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialects.DATABRICKS", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Dialects.DATABRICKS: 'databricks'>"}, "sqlglot.dialects.dialect.Dialects.DORIS": {"fullname": "sqlglot.dialects.dialect.Dialects.DORIS", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialects.DORIS", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Dialects.DORIS: 'doris'>"}, "sqlglot.dialects.dialect.Dialects.DRILL": {"fullname": "sqlglot.dialects.dialect.Dialects.DRILL", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialects.DRILL", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Dialects.DRILL: 'drill'>"}, "sqlglot.dialects.dialect.Dialects.DUCKDB": {"fullname": "sqlglot.dialects.dialect.Dialects.DUCKDB", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialects.DUCKDB", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Dialects.DUCKDB: 'duckdb'>"}, "sqlglot.dialects.dialect.Dialects.HIVE": {"fullname": "sqlglot.dialects.dialect.Dialects.HIVE", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialects.HIVE", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Dialects.HIVE: 'hive'>"}, "sqlglot.dialects.dialect.Dialects.MYSQL": {"fullname": "sqlglot.dialects.dialect.Dialects.MYSQL", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialects.MYSQL", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Dialects.MYSQL: 'mysql'>"}, "sqlglot.dialects.dialect.Dialects.ORACLE": {"fullname": "sqlglot.dialects.dialect.Dialects.ORACLE", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialects.ORACLE", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Dialects.ORACLE: 'oracle'>"}, "sqlglot.dialects.dialect.Dialects.POSTGRES": {"fullname": "sqlglot.dialects.dialect.Dialects.POSTGRES", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialects.POSTGRES", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Dialects.POSTGRES: 'postgres'>"}, "sqlglot.dialects.dialect.Dialects.PRESTO": {"fullname": "sqlglot.dialects.dialect.Dialects.PRESTO", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialects.PRESTO", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Dialects.PRESTO: 'presto'>"}, "sqlglot.dialects.dialect.Dialects.PRQL": {"fullname": "sqlglot.dialects.dialect.Dialects.PRQL", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialects.PRQL", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Dialects.PRQL: 'prql'>"}, "sqlglot.dialects.dialect.Dialects.REDSHIFT": {"fullname": "sqlglot.dialects.dialect.Dialects.REDSHIFT", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialects.REDSHIFT", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Dialects.REDSHIFT: 'redshift'>"}, "sqlglot.dialects.dialect.Dialects.SNOWFLAKE": {"fullname": "sqlglot.dialects.dialect.Dialects.SNOWFLAKE", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialects.SNOWFLAKE", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Dialects.SNOWFLAKE: 'snowflake'>"}, "sqlglot.dialects.dialect.Dialects.SPARK": {"fullname": "sqlglot.dialects.dialect.Dialects.SPARK", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialects.SPARK", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Dialects.SPARK: 'spark'>"}, "sqlglot.dialects.dialect.Dialects.SPARK2": {"fullname": "sqlglot.dialects.dialect.Dialects.SPARK2", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialects.SPARK2", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Dialects.SPARK2: 'spark2'>"}, "sqlglot.dialects.dialect.Dialects.SQLITE": {"fullname": "sqlglot.dialects.dialect.Dialects.SQLITE", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialects.SQLITE", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Dialects.SQLITE: 'sqlite'>"}, "sqlglot.dialects.dialect.Dialects.STARROCKS": {"fullname": "sqlglot.dialects.dialect.Dialects.STARROCKS", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialects.STARROCKS", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Dialects.STARROCKS: 'starrocks'>"}, "sqlglot.dialects.dialect.Dialects.TABLEAU": {"fullname": "sqlglot.dialects.dialect.Dialects.TABLEAU", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialects.TABLEAU", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Dialects.TABLEAU: 'tableau'>"}, "sqlglot.dialects.dialect.Dialects.TERADATA": {"fullname": "sqlglot.dialects.dialect.Dialects.TERADATA", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialects.TERADATA", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Dialects.TERADATA: 'teradata'>"}, "sqlglot.dialects.dialect.Dialects.TRINO": {"fullname": "sqlglot.dialects.dialect.Dialects.TRINO", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialects.TRINO", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Dialects.TRINO: 'trino'>"}, "sqlglot.dialects.dialect.Dialects.TSQL": {"fullname": "sqlglot.dialects.dialect.Dialects.TSQL", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialects.TSQL", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Dialects.TSQL: 'tsql'>"}, "sqlglot.dialects.dialect.NormalizationStrategy": {"fullname": "sqlglot.dialects.dialect.NormalizationStrategy", "modulename": "sqlglot.dialects.dialect", "qualname": "NormalizationStrategy", "kind": "class", "doc": "<p>Specifies the strategy according to which identifiers should be normalized.</p>\n", "bases": "builtins.str, sqlglot.helper.AutoName"}, "sqlglot.dialects.dialect.NormalizationStrategy.LOWERCASE": {"fullname": "sqlglot.dialects.dialect.NormalizationStrategy.LOWERCASE", "modulename": "sqlglot.dialects.dialect", "qualname": "NormalizationStrategy.LOWERCASE", "kind": "variable", "doc": "<p>Unquoted identifiers are lowercased.</p>\n", "default_value": "<NormalizationStrategy.LOWERCASE: 'LOWERCASE'>"}, "sqlglot.dialects.dialect.NormalizationStrategy.UPPERCASE": {"fullname": "sqlglot.dialects.dialect.NormalizationStrategy.UPPERCASE", "modulename": "sqlglot.dialects.dialect", "qualname": "NormalizationStrategy.UPPERCASE", "kind": "variable", "doc": "<p>Unquoted identifiers are uppercased.</p>\n", "default_value": "<NormalizationStrategy.UPPERCASE: 'UPPERCASE'>"}, "sqlglot.dialects.dialect.NormalizationStrategy.CASE_SENSITIVE": {"fullname": "sqlglot.dialects.dialect.NormalizationStrategy.CASE_SENSITIVE", "modulename": "sqlglot.dialects.dialect", "qualname": "NormalizationStrategy.CASE_SENSITIVE", "kind": "variable", "doc": "<p>Always case-sensitive, regardless of quotes.</p>\n", "default_value": "<NormalizationStrategy.CASE_SENSITIVE: 'CASE_SENSITIVE'>"}, "sqlglot.dialects.dialect.NormalizationStrategy.CASE_INSENSITIVE": {"fullname": "sqlglot.dialects.dialect.NormalizationStrategy.CASE_INSENSITIVE", "modulename": "sqlglot.dialects.dialect", "qualname": "NormalizationStrategy.CASE_INSENSITIVE", "kind": "variable", "doc": "<p>Always case-insensitive, regardless of quotes.</p>\n", "default_value": "<NormalizationStrategy.CASE_INSENSITIVE: 'CASE_INSENSITIVE'>"}, "sqlglot.dialects.dialect.Dialect": {"fullname": "sqlglot.dialects.dialect.Dialect", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect", "kind": "class", "doc": "<p></p>\n"}, "sqlglot.dialects.dialect.Dialect.__init__": {"fullname": "sqlglot.dialects.dialect.Dialect.__init__", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"o\">**</span><span class=\"n\">kwargs</span></span>)</span>"}, "sqlglot.dialects.dialect.Dialect.INDEX_OFFSET": {"fullname": "sqlglot.dialects.dialect.Dialect.INDEX_OFFSET", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.INDEX_OFFSET", "kind": "variable", "doc": "<p>The base index offset for arrays.</p>\n", "default_value": "0"}, "sqlglot.dialects.dialect.Dialect.WEEK_OFFSET": {"fullname": "sqlglot.dialects.dialect.Dialect.WEEK_OFFSET", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.WEEK_OFFSET", "kind": "variable", "doc": "<p>First day of the week in DATE_TRUNC(week). Defaults to 0 (Monday). -1 would be Sunday.</p>\n", "default_value": "0"}, "sqlglot.dialects.dialect.Dialect.UNNEST_COLUMN_ONLY": {"fullname": "sqlglot.dialects.dialect.Dialect.UNNEST_COLUMN_ONLY", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.UNNEST_COLUMN_ONLY", "kind": "variable", "doc": "<p>Whether <code>UNNEST</code> table aliases are treated as column aliases.</p>\n", "default_value": "False"}, "sqlglot.dialects.dialect.Dialect.ALIAS_POST_TABLESAMPLE": {"fullname": "sqlglot.dialects.dialect.Dialect.ALIAS_POST_TABLESAMPLE", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.ALIAS_POST_TABLESAMPLE", "kind": "variable", "doc": "<p>Whether the table alias comes after tablesample.</p>\n", "default_value": "False"}, "sqlglot.dialects.dialect.Dialect.TABLESAMPLE_SIZE_IS_PERCENT": {"fullname": "sqlglot.dialects.dialect.Dialect.TABLESAMPLE_SIZE_IS_PERCENT", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.TABLESAMPLE_SIZE_IS_PERCENT", "kind": "variable", "doc": "<p>Whether a size in the table sample clause represents percentage.</p>\n", "default_value": "False"}, "sqlglot.dialects.dialect.Dialect.NORMALIZATION_STRATEGY": {"fullname": "sqlglot.dialects.dialect.Dialect.NORMALIZATION_STRATEGY", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.NORMALIZATION_STRATEGY", "kind": "variable", "doc": "<p>Specifies the strategy according to which identifiers should be normalized.</p>\n", "default_value": "<NormalizationStrategy.LOWERCASE: 'LOWERCASE'>"}, "sqlglot.dialects.dialect.Dialect.IDENTIFIERS_CAN_START_WITH_DIGIT": {"fullname": "sqlglot.dialects.dialect.Dialect.IDENTIFIERS_CAN_START_WITH_DIGIT", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.IDENTIFIERS_CAN_START_WITH_DIGIT", "kind": "variable", "doc": "<p>Whether an unquoted identifier can start with a digit.</p>\n", "default_value": "False"}, "sqlglot.dialects.dialect.Dialect.DPIPE_IS_STRING_CONCAT": {"fullname": "sqlglot.dialects.dialect.Dialect.DPIPE_IS_STRING_CONCAT", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.DPIPE_IS_STRING_CONCAT", "kind": "variable", "doc": "<p>Whether the DPIPE token (<code>||</code>) is a string concatenation operator.</p>\n", "default_value": "True"}, "sqlglot.dialects.dialect.Dialect.STRICT_STRING_CONCAT": {"fullname": "sqlglot.dialects.dialect.Dialect.STRICT_STRING_CONCAT", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.STRICT_STRING_CONCAT", "kind": "variable", "doc": "<p>Whether <code>CONCAT</code>'s arguments must be strings.</p>\n", "default_value": "False"}, "sqlglot.dialects.dialect.Dialect.SUPPORTS_USER_DEFINED_TYPES": {"fullname": "sqlglot.dialects.dialect.Dialect.SUPPORTS_USER_DEFINED_TYPES", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.SUPPORTS_USER_DEFINED_TYPES", "kind": "variable", "doc": "<p>Whether user-defined data types are supported.</p>\n", "default_value": "True"}, "sqlglot.dialects.dialect.Dialect.SUPPORTS_SEMI_ANTI_JOIN": {"fullname": "sqlglot.dialects.dialect.Dialect.SUPPORTS_SEMI_ANTI_JOIN", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.SUPPORTS_SEMI_ANTI_JOIN", "kind": "variable", "doc": "<p>Whether <code>SEMI</code> or <code>ANTI</code> joins are supported.</p>\n", "default_value": "True"}, "sqlglot.dialects.dialect.Dialect.NORMALIZE_FUNCTIONS": {"fullname": "sqlglot.dialects.dialect.Dialect.NORMALIZE_FUNCTIONS", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.NORMALIZE_FUNCTIONS", "kind": "variable", "doc": "<p>Determines how function names are going to be normalized.</p>\n\n<h6 id=\"possible-values\">Possible values:</h6>\n\n<blockquote>\n <p>\"upper\" or True: Convert names to uppercase.\n \"lower\": Convert names to lowercase.\n False: Disables function name normalization.</p>\n</blockquote>\n", "annotation": ": bool | str", "default_value": "'upper'"}, "sqlglot.dialects.dialect.Dialect.LOG_BASE_FIRST": {"fullname": "sqlglot.dialects.dialect.Dialect.LOG_BASE_FIRST", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.LOG_BASE_FIRST", "kind": "variable", "doc": "<p>Whether the base comes first in the <code>LOG</code> function.\nPossible values: <code>True</code>, <code>False</code>, <code>None</code> (two arguments are not supported by <code>LOG</code>)</p>\n", "annotation": ": Optional[bool]", "default_value": "True"}, "sqlglot.dialects.dialect.Dialect.NULL_ORDERING": {"fullname": "sqlglot.dialects.dialect.Dialect.NULL_ORDERING", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.NULL_ORDERING", "kind": "variable", "doc": "<p>Default <code>NULL</code> ordering method to use if not explicitly set.\nPossible values: <code>\"nulls_are_small\"</code>, <code>\"nulls_are_large\"</code>, <code>\"nulls_are_last\"</code></p>\n", "default_value": "'nulls_are_small'"}, "sqlglot.dialects.dialect.Dialect.TYPED_DIVISION": {"fullname": "sqlglot.dialects.dialect.Dialect.TYPED_DIVISION", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.TYPED_DIVISION", "kind": "variable", "doc": "<p>Whether the behavior of <code>a / b</code> depends on the types of <code>a</code> and <code>b</code>.\nFalse means <code>a / b</code> is always float division.\nTrue means <code>a / b</code> is integer division if both <code>a</code> and <code>b</code> are integers.</p>\n", "default_value": "False"}, "sqlglot.dialects.dialect.Dialect.SAFE_DIVISION": {"fullname": "sqlglot.dialects.dialect.Dialect.SAFE_DIVISION", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.SAFE_DIVISION", "kind": "variable", "doc": "<p>Whether division by zero throws an error (<code>False</code>) or returns NULL (<code>True</code>).</p>\n", "default_value": "False"}, "sqlglot.dialects.dialect.Dialect.CONCAT_COALESCE": {"fullname": "sqlglot.dialects.dialect.Dialect.CONCAT_COALESCE", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.CONCAT_COALESCE", "kind": "variable", "doc": "<p>A <code>NULL</code> arg in <code>CONCAT</code> yields <code>NULL</code> by default, but in some dialects it yields an empty string.</p>\n", "default_value": "False"}, "sqlglot.dialects.dialect.Dialect.HEX_LOWERCASE": {"fullname": "sqlglot.dialects.dialect.Dialect.HEX_LOWERCASE", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.HEX_LOWERCASE", "kind": "variable", "doc": "<p>Whether the <code>HEX</code> function returns a lowercase hexadecimal string.</p>\n", "default_value": "False"}, "sqlglot.dialects.dialect.Dialect.DATE_FORMAT": {"fullname": "sqlglot.dialects.dialect.Dialect.DATE_FORMAT", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.DATE_FORMAT", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'%Y-%m-%d'""}, "sqlglot.dialects.dialect.Dialect.DATEINT_FORMAT": {"fullname": "sqlglot.dialects.dialect.Dialect.DATEINT_FORMAT", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.DATEINT_FORMAT", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'%Y%m%d'""}, "sqlglot.dialects.dialect.Dialect.TIME_FORMAT": {"fullname": "sqlglot.dialects.dialect.Dialect.TIME_FORMAT", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.TIME_FORMAT", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'%Y-%m-%d %H:%M:%S'""}, "sqlglot.dialects.dialect.Dialect.TIME_MAPPING": {"fullname": "sqlglot.dialects.dialect.Dialect.TIME_MAPPING", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.TIME_MAPPING", "kind": "variable", "doc": "<p>Associates this dialect's time formats with their equivalent Python <code>strftime</code> formats.</p>\n", "annotation": ": Dict[str, str]", "default_value": "{}"}, "sqlglot.dialects.dialect.Dialect.FORMAT_MAPPING": {"fullname": "sqlglot.dialects.dialect.Dialect.FORMAT_MAPPING", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.FORMAT_MAPPING", "kind": "variable", "doc": "<p>Helper which is used for parsing the special syntax <code>CAST(x AS DATE FORMAT 'yyyy')</code>.\nIf empty, the corresponding trie will be constructed off of <code>TIME_MAPPING</code>.</p>\n", "annotation": ": Dict[str, str]", "default_value": "{}"}, "sqlglot.dialects.dialect.Dialect.UNESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.dialect.Dialect.UNESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.UNESCAPED_SEQUENCES", "kind": "variable", "doc": "<p>Mapping of an escaped sequence (<code>\\n</code>) to its unescaped version (<code>\n</code>).</p>\n", "annotation": ": Dict[str, str]", "default_value": "{}"}, "sqlglot.dialects.dialect.Dialect.PSEUDOCOLUMNS": {"fullname": "sqlglot.dialects.dialect.Dialect.PSEUDOCOLUMNS", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.PSEUDOCOLUMNS", "kind": "variable", "doc": "<p>Columns that are auto-generated by the engine corresponding to this dialect.\nFor example, such columns may be excluded from <code>SELECT *</code> queries.</p>\n", "annotation": ": Set[str]", "default_value": "set()"}, "sqlglot.dialects.dialect.Dialect.PREFER_CTE_ALIAS_COLUMN": {"fullname": "sqlglot.dialects.dialect.Dialect.PREFER_CTE_ALIAS_COLUMN", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.PREFER_CTE_ALIAS_COLUMN", "kind": "variable", "doc": "<p>Some dialects, such as Snowflake, allow you to reference a CTE column alias in the\nHAVING clause of the CTE. This flag will cause the CTE alias columns to override\nany projection aliases in the subquery.</p>\n\n<p>For example,\n WITH y(c) AS (\n SELECT SUM(a) FROM (SELECT 1 a) AS x HAVING c > 0\n ) SELECT c FROM y;</p>\n\n<pre><code>will be rewritten as\n\nWITH y(c) AS (\n SELECT SUM(a) AS c FROM (SELECT 1 AS a) AS x HAVING c > 0\n) SELECT c FROM y;\n</code></pre>\n", "default_value": "False"}, "sqlglot.dialects.dialect.Dialect.tokenizer_class": {"fullname": "sqlglot.dialects.dialect.Dialect.tokenizer_class", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.tokenizer_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.tokens.Tokenizer'>"}, "sqlglot.dialects.dialect.Dialect.parser_class": {"fullname": "sqlglot.dialects.dialect.Dialect.parser_class", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.parser_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.parser.Parser'>"}, "sqlglot.dialects.dialect.Dialect.generator_class": {"fullname": "sqlglot.dialects.dialect.Dialect.generator_class", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.generator_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.generator.Generator'>"}, "sqlglot.dialects.dialect.Dialect.TIME_TRIE": {"fullname": "sqlglot.dialects.dialect.Dialect.TIME_TRIE", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.dialect.Dialect.FORMAT_TRIE": {"fullname": "sqlglot.dialects.dialect.Dialect.FORMAT_TRIE", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.FORMAT_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.dialect.Dialect.INVERSE_TIME_MAPPING": {"fullname": "sqlglot.dialects.dialect.Dialect.INVERSE_TIME_MAPPING", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.INVERSE_TIME_MAPPING", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{}"}, "sqlglot.dialects.dialect.Dialect.INVERSE_TIME_TRIE": {"fullname": "sqlglot.dialects.dialect.Dialect.INVERSE_TIME_TRIE", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.INVERSE_TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.dialect.Dialect.ESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.dialect.Dialect.ESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.ESCAPED_SEQUENCES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{}"}, "sqlglot.dialects.dialect.Dialect.QUOTE_START": {"fullname": "sqlglot.dialects.dialect.Dialect.QUOTE_START", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.QUOTE_START", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.dialect.Dialect.QUOTE_END": {"fullname": "sqlglot.dialects.dialect.Dialect.QUOTE_END", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.QUOTE_END", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.dialect.Dialect.IDENTIFIER_START": {"fullname": "sqlglot.dialects.dialect.Dialect.IDENTIFIER_START", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.IDENTIFIER_START", "kind": "variable", "doc": "<p></p>\n", "default_value": "'"'"}, "sqlglot.dialects.dialect.Dialect.IDENTIFIER_END": {"fullname": "sqlglot.dialects.dialect.Dialect.IDENTIFIER_END", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.IDENTIFIER_END", "kind": "variable", "doc": "<p></p>\n", "default_value": "'"'"}, "sqlglot.dialects.dialect.Dialect.BIT_START": {"fullname": "sqlglot.dialects.dialect.Dialect.BIT_START", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.BIT_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.dialect.Dialect.BIT_END": {"fullname": "sqlglot.dialects.dialect.Dialect.BIT_END", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.BIT_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.dialect.Dialect.HEX_START": {"fullname": "sqlglot.dialects.dialect.Dialect.HEX_START", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.HEX_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.dialect.Dialect.HEX_END": {"fullname": "sqlglot.dialects.dialect.Dialect.HEX_END", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.HEX_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.dialect.Dialect.BYTE_START": {"fullname": "sqlglot.dialects.dialect.Dialect.BYTE_START", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.BYTE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.dialect.Dialect.BYTE_END": {"fullname": "sqlglot.dialects.dialect.Dialect.BYTE_END", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.BYTE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.dialect.Dialect.UNICODE_START": {"fullname": "sqlglot.dialects.dialect.Dialect.UNICODE_START", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.UNICODE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.dialect.Dialect.UNICODE_END": {"fullname": "sqlglot.dialects.dialect.Dialect.UNICODE_END", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.UNICODE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.dialect.Dialect.COPY_PARAMS_ARE_CSV": {"fullname": "sqlglot.dialects.dialect.Dialect.COPY_PARAMS_ARE_CSV", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.COPY_PARAMS_ARE_CSV", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.dialect.Dialect.get_or_raise": {"fullname": "sqlglot.dialects.dialect.Dialect.get_or_raise", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.get_or_raise", "kind": "function", "doc": "<p>Look up a dialect in the global dialect registry and return it if it exists.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>dialect:</strong> The target dialect. If this is a string, it can be optionally followed by\nadditional key-value pairs that are separated by commas and are used to specify\ndialect settings, such as whether the dialect's identifiers are case-sensitive.</li>\n</ul>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">dialect</span> <span class=\"o\">=</span> <span class=\"n\">dialect_class</span> <span class=\"o\">=</span> <span class=\"n\">get_or_raise</span><span class=\"p\">(</span><span class=\"s2\">"duckdb"</span><span class=\"p\">)</span>\n<span class=\"gp\">>>> </span><span class=\"n\">dialect</span> <span class=\"o\">=</span> <span class=\"n\">get_or_raise</span><span class=\"p\">(</span><span class=\"s2\">"mysql, normalization_strategy = case_sensitive"</span><span class=\"p\">)</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The corresponding Dialect instance.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">cls</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.Dialect.format_time": {"fullname": "sqlglot.dialects.dialect.Dialect.format_time", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.format_time", "kind": "function", "doc": "<p>Converts a time format in this dialect to its equivalent Python <code>strftime</code> format.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">cls</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.Dialect.normalize_identifier": {"fullname": "sqlglot.dialects.dialect.Dialect.normalize_identifier", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.normalize_identifier", "kind": "function", "doc": "<p>Transforms an identifier in a way that resembles how it'd be resolved by this dialect.</p>\n\n<p>For example, an identifier like <code>FoO</code> would be resolved as <code>foo</code> in Postgres, because it\nlowercases all unquoted identifiers. On the other hand, Snowflake uppercases them, so\nit would resolve it as <code>FOO</code>. If it was quoted, it'd need to be treated as case-sensitive,\nand so any normalization would be prohibited in order to avoid \"breaking\" the identifier.</p>\n\n<p>There are also dialects like Spark, which are case-insensitive even when quotes are\npresent, and dialects like MySQL, whose resolution rules match those employed by the\nunderlying operating system, for example they may always be case-sensitive in Linux.</p>\n\n<p>Finally, the normalization behavior of some engines can even be controlled through flags,\nlike in Redshift's case, where users can explicitly set enable_case_sensitive_identifier.</p>\n\n<p>SQLGlot aims to understand and handle all of these different behaviors gracefully, so\nthat it can analyze queries in the optimizer and successfully capture their semantics.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"o\">~</span><span class=\"n\">E</span></span><span class=\"return-annotation\">) -> <span class=\"o\">~</span><span class=\"n\">E</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.Dialect.case_sensitive": {"fullname": "sqlglot.dialects.dialect.Dialect.case_sensitive", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.case_sensitive", "kind": "function", "doc": "<p>Checks if text contains any case sensitive characters, based on the dialect's rules.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">text</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">bool</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.Dialect.can_identify": {"fullname": "sqlglot.dialects.dialect.Dialect.can_identify", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.can_identify", "kind": "function", "doc": "<p>Checks if text can be identified given an identify option.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>text:</strong> The text to check.</li>\n<li><strong>identify:</strong> <code>\"always\"</code> or <code>True</code>: Always returns <code>True</code>.\n<code>\"safe\"</code>: Only returns <code>True</code> if the identifier is case-insensitive.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>Whether the given text can be identified.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">text</span><span class=\"p\">:</span> <span class=\"nb\">str</span>, </span><span class=\"param\"><span class=\"n\">identify</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"s1\">'safe'</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">bool</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.Dialect.quote_identifier": {"fullname": "sqlglot.dialects.dialect.Dialect.quote_identifier", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.quote_identifier", "kind": "function", "doc": "<p>Adds quotes to a given identifier.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> The expression of interest. If it's not an <code>Identifier</code>, this method is a no-op.</li>\n<li><strong>identify:</strong> If set to <code>False</code>, the quotes will only be added if the identifier is deemed\n\"unsafe\", with respect to its characters and this dialect's normalization strategy.</li>\n</ul>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"o\">~</span><span class=\"n\">E</span>, </span><span class=\"param\"><span class=\"n\">identify</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"o\">~</span><span class=\"n\">E</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.Dialect.to_json_path": {"fullname": "sqlglot.dialects.dialect.Dialect.to_json_path", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.to_json_path", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">path</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.Dialect.parse": {"fullname": "sqlglot.dialects.dialect.Dialect.parse", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.parse", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">sql</span><span class=\"p\">:</span> <span class=\"nb\">str</span>, </span><span class=\"param\"><span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.Dialect.parse_into": {"fullname": "sqlglot.dialects.dialect.Dialect.parse_into", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.parse_into", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression_type</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">],</span> <span class=\"n\">Collection</span><span class=\"p\">[</span><span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]]]]</span>,</span><span class=\"param\">\t<span class=\"n\">sql</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.Dialect.generate": {"fullname": "sqlglot.dialects.dialect.Dialect.generate", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.generate", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.Dialect.transpile": {"fullname": "sqlglot.dialects.dialect.Dialect.transpile", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.transpile", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">sql</span><span class=\"p\">:</span> <span class=\"nb\">str</span>, </span><span class=\"param\"><span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.Dialect.tokenize": {"fullname": "sqlglot.dialects.dialect.Dialect.tokenize", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.tokenize", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">sql</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">tokens</span><span class=\"o\">.</span><span class=\"n\">Token</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.Dialect.tokenizer": {"fullname": "sqlglot.dialects.dialect.Dialect.tokenizer", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.tokenizer", "kind": "variable", "doc": "<p></p>\n", "annotation": ": sqlglot.tokens.Tokenizer"}, "sqlglot.dialects.dialect.Dialect.parser": {"fullname": "sqlglot.dialects.dialect.Dialect.parser", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.parser", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parser</span><span class=\"o\">.</span><span class=\"n\">Parser</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.Dialect.generator": {"fullname": "sqlglot.dialects.dialect.Dialect.generator", "modulename": "sqlglot.dialects.dialect", "qualname": "Dialect.generator", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.DialectType": {"fullname": "sqlglot.dialects.dialect.DialectType", "modulename": "sqlglot.dialects.dialect", "qualname": "DialectType", "kind": "variable", "doc": "<p></p>\n", "default_value": "typing.Union[str, sqlglot.dialects.dialect.Dialect, typing.Type[sqlglot.dialects.dialect.Dialect], NoneType]"}, "sqlglot.dialects.dialect.rename_func": {"fullname": "sqlglot.dialects.dialect.rename_func", "modulename": "sqlglot.dialects.dialect", "qualname": "rename_func", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">name</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">],</span> <span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.approx_count_distinct_sql": {"fullname": "sqlglot.dialects.dialect.approx_count_distinct_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "approx_count_distinct_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ApproxDistinct</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.if_sql": {"fullname": "sqlglot.dialects.dialect.if_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "if_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">name</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">'IF'</span>,</span><span class=\"param\">\t<span class=\"n\">false_value</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">If</span><span class=\"p\">],</span> <span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.arrow_json_extract_sql": {"fullname": "sqlglot.dialects.dialect.arrow_json_extract_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "arrow_json_extract_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">JSONExtract</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">JSONExtractScalar</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.inline_array_sql": {"fullname": "sqlglot.dialects.dialect.inline_array_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "inline_array_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Array</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.inline_array_unless_query": {"fullname": "sqlglot.dialects.dialect.inline_array_unless_query", "modulename": "sqlglot.dialects.dialect", "qualname": "inline_array_unless_query", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Array</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.no_ilike_sql": {"fullname": "sqlglot.dialects.dialect.no_ilike_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "no_ilike_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ILike</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.no_paren_current_date_sql": {"fullname": "sqlglot.dialects.dialect.no_paren_current_date_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "no_paren_current_date_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">CurrentDate</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.no_recursive_cte_sql": {"fullname": "sqlglot.dialects.dialect.no_recursive_cte_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "no_recursive_cte_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">With</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.no_safe_divide_sql": {"fullname": "sqlglot.dialects.dialect.no_safe_divide_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "no_safe_divide_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">SafeDivide</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.no_tablesample_sql": {"fullname": "sqlglot.dialects.dialect.no_tablesample_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "no_tablesample_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TableSample</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.no_pivot_sql": {"fullname": "sqlglot.dialects.dialect.no_pivot_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "no_pivot_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Pivot</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.no_trycast_sql": {"fullname": "sqlglot.dialects.dialect.no_trycast_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "no_trycast_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TryCast</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.no_comment_column_constraint_sql": {"fullname": "sqlglot.dialects.dialect.no_comment_column_constraint_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "no_comment_column_constraint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">CommentColumnConstraint</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.no_map_from_entries_sql": {"fullname": "sqlglot.dialects.dialect.no_map_from_entries_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "no_map_from_entries_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">MapFromEntries</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.str_position_sql": {"fullname": "sqlglot.dialects.dialect.str_position_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "str_position_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">StrPosition</span>,</span><span class=\"param\">\t<span class=\"n\">generate_instance</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.struct_extract_sql": {"fullname": "sqlglot.dialects.dialect.struct_extract_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "struct_extract_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">StructExtract</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.var_map_sql": {"fullname": "sqlglot.dialects.dialect.var_map_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "var_map_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Map</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">VarMap</span>,</span><span class=\"param\">\t<span class=\"n\">map_func_name</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">'MAP'</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.build_formatted_time": {"fullname": "sqlglot.dialects.dialect.build_formatted_time", "modulename": "sqlglot.dialects.dialect", "qualname": "build_formatted_time", "kind": "function", "doc": "<p>Helper used for time expressions.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>exp_class:</strong> the expression class to instantiate.</li>\n<li><strong>dialect:</strong> target sql dialect.</li>\n<li><strong>default:</strong> the default format, True being time.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>A callable that can be used to return the appropriately formatted time expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">exp_class</span><span class=\"p\">:</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">E</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">default</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"nb\">bool</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">List</span><span class=\"p\">],</span> <span class=\"o\">~</span><span class=\"n\">E</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.time_format": {"fullname": "sqlglot.dialects.dialect.time_format", "modulename": "sqlglot.dialects.dialect", "qualname": "time_format", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">UnixToStr</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">StrToUnix</span><span class=\"p\">],</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.build_date_delta": {"fullname": "sqlglot.dialects.dialect.build_date_delta", "modulename": "sqlglot.dialects.dialect", "qualname": "build_date_delta", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">exp_class</span><span class=\"p\">:</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">E</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">unit_mapping</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">List</span><span class=\"p\">],</span> <span class=\"o\">~</span><span class=\"n\">E</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.build_date_delta_with_interval": {"fullname": "sqlglot.dialects.dialect.build_date_delta_with_interval", "modulename": "sqlglot.dialects.dialect", "qualname": "build_date_delta_with_interval", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression_class</span><span class=\"p\">:</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">E</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">List</span><span class=\"p\">],</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">E</span><span class=\"p\">]]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.date_trunc_to_time": {"fullname": "sqlglot.dialects.dialect.date_trunc_to_time", "modulename": "sqlglot.dialects.dialect", "qualname": "date_trunc_to_time", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">args</span><span class=\"p\">:</span> <span class=\"n\">List</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DateTrunc</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TimestampTrunc</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.date_add_interval_sql": {"fullname": "sqlglot.dialects.dialect.date_add_interval_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "date_add_interval_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">data_type</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">kind</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">],</span> <span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.timestamptrunc_sql": {"fullname": "sqlglot.dialects.dialect.timestamptrunc_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "timestamptrunc_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">zone</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TimestampTrunc</span><span class=\"p\">],</span> <span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.no_timestamp_sql": {"fullname": "sqlglot.dialects.dialect.no_timestamp_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "no_timestamp_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Timestamp</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.locate_to_strposition": {"fullname": "sqlglot.dialects.dialect.locate_to_strposition", "modulename": "sqlglot.dialects.dialect", "qualname": "locate_to_strposition", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">args</span><span class=\"p\">:</span> <span class=\"n\">List</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.strposition_to_locate_sql": {"fullname": "sqlglot.dialects.dialect.strposition_to_locate_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "strposition_to_locate_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">StrPosition</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.left_to_substring_sql": {"fullname": "sqlglot.dialects.dialect.left_to_substring_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "left_to_substring_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Left</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.right_to_substring_sql": {"fullname": "sqlglot.dialects.dialect.right_to_substring_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "right_to_substring_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Left</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.timestrtotime_sql": {"fullname": "sqlglot.dialects.dialect.timestrtotime_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "timestrtotime_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TimeStrToTime</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.datestrtodate_sql": {"fullname": "sqlglot.dialects.dialect.datestrtodate_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "datestrtodate_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DateStrToDate</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.encode_decode_sql": {"fullname": "sqlglot.dialects.dialect.encode_decode_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "encode_decode_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">name</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">replace</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.min_or_least": {"fullname": "sqlglot.dialects.dialect.min_or_least", "modulename": "sqlglot.dialects.dialect", "qualname": "min_or_least", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Min</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.max_or_greatest": {"fullname": "sqlglot.dialects.dialect.max_or_greatest", "modulename": "sqlglot.dialects.dialect", "qualname": "max_or_greatest", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Max</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.count_if_to_sum": {"fullname": "sqlglot.dialects.dialect.count_if_to_sum", "modulename": "sqlglot.dialects.dialect", "qualname": "count_if_to_sum", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">CountIf</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.trim_sql": {"fullname": "sqlglot.dialects.dialect.trim_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "trim_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Trim</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.str_to_time_sql": {"fullname": "sqlglot.dialects.dialect.str_to_time_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "str_to_time_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.concat_to_dpipe_sql": {"fullname": "sqlglot.dialects.dialect.concat_to_dpipe_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "concat_to_dpipe_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Concat</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.concat_ws_to_dpipe_sql": {"fullname": "sqlglot.dialects.dialect.concat_ws_to_dpipe_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "concat_ws_to_dpipe_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ConcatWs</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.regexp_extract_sql": {"fullname": "sqlglot.dialects.dialect.regexp_extract_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "regexp_extract_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">RegexpExtract</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.regexp_replace_sql": {"fullname": "sqlglot.dialects.dialect.regexp_replace_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "regexp_replace_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">RegexpReplace</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.pivot_column_names": {"fullname": "sqlglot.dialects.dialect.pivot_column_names", "modulename": "sqlglot.dialects.dialect", "qualname": "pivot_column_names", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">aggregations</span><span class=\"p\">:</span> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.binary_from_function": {"fullname": "sqlglot.dialects.dialect.binary_from_function", "modulename": "sqlglot.dialects.dialect", "qualname": "binary_from_function", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expr_type</span><span class=\"p\">:</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">B</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">List</span><span class=\"p\">],</span> <span class=\"o\">~</span><span class=\"n\">B</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.build_timestamp_trunc": {"fullname": "sqlglot.dialects.dialect.build_timestamp_trunc", "modulename": "sqlglot.dialects.dialect", "qualname": "build_timestamp_trunc", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">args</span><span class=\"p\">:</span> <span class=\"n\">List</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TimestampTrunc</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.any_value_to_max_sql": {"fullname": "sqlglot.dialects.dialect.any_value_to_max_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "any_value_to_max_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">AnyValue</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.bool_xor_sql": {"fullname": "sqlglot.dialects.dialect.bool_xor_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "bool_xor_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Xor</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.is_parse_json": {"fullname": "sqlglot.dialects.dialect.is_parse_json", "modulename": "sqlglot.dialects.dialect", "qualname": "is_parse_json", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">bool</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.isnull_to_is_null": {"fullname": "sqlglot.dialects.dialect.isnull_to_is_null", "modulename": "sqlglot.dialects.dialect", "qualname": "isnull_to_is_null", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">args</span><span class=\"p\">:</span> <span class=\"n\">List</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.generatedasidentitycolumnconstraint_sql": {"fullname": "sqlglot.dialects.dialect.generatedasidentitycolumnconstraint_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "generatedasidentitycolumnconstraint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">GeneratedAsIdentityColumnConstraint</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.arg_max_or_min_no_count": {"fullname": "sqlglot.dialects.dialect.arg_max_or_min_no_count", "modulename": "sqlglot.dialects.dialect", "qualname": "arg_max_or_min_no_count", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">name</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ArgMax</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ArgMin</span><span class=\"p\">],</span> <span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.ts_or_ds_add_cast": {"fullname": "sqlglot.dialects.dialect.ts_or_ds_add_cast", "modulename": "sqlglot.dialects.dialect", "qualname": "ts_or_ds_add_cast", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TsOrDsAdd</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TsOrDsAdd</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.date_delta_sql": {"fullname": "sqlglot.dialects.dialect.date_delta_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "date_delta_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">name</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">cast</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span><span class=\"p\">,</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DateAdd</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TsOrDsAdd</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DateDiff</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TsOrDsDiff</span><span class=\"p\">]],</span> <span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.unit_to_str": {"fullname": "sqlglot.dialects.dialect.unit_to_str", "modulename": "sqlglot.dialects.dialect", "qualname": "unit_to_str", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">default</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">'DAY'</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.unit_to_var": {"fullname": "sqlglot.dialects.dialect.unit_to_var", "modulename": "sqlglot.dialects.dialect", "qualname": "unit_to_var", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">default</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">'DAY'</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.no_last_day_sql": {"fullname": "sqlglot.dialects.dialect.no_last_day_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "no_last_day_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">LastDay</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.merge_without_target_sql": {"fullname": "sqlglot.dialects.dialect.merge_without_target_sql", "modulename": "sqlglot.dialects.dialect", "qualname": "merge_without_target_sql", "kind": "function", "doc": "<p>Remove table refs from columns in when statements.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Merge</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.build_json_extract_path": {"fullname": "sqlglot.dialects.dialect.build_json_extract_path", "modulename": "sqlglot.dialects.dialect", "qualname": "build_json_extract_path", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expr_type</span><span class=\"p\">:</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">F</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">zero_based_indexing</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">arrow_req_json_type</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">List</span><span class=\"p\">],</span> <span class=\"o\">~</span><span class=\"n\">F</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.json_extract_segments": {"fullname": "sqlglot.dialects.dialect.json_extract_segments", "modulename": "sqlglot.dialects.dialect", "qualname": "json_extract_segments", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">name</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">quoted_index</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">op</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span><span class=\"p\">,</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">JSONExtract</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">JSONExtractScalar</span><span class=\"p\">]],</span> <span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.json_path_key_only_name": {"fullname": "sqlglot.dialects.dialect.json_path_key_only_name", "modulename": "sqlglot.dialects.dialect", "qualname": "json_path_key_only_name", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">JSONPathKey</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.filter_array_using_unnest": {"fullname": "sqlglot.dialects.dialect.filter_array_using_unnest", "modulename": "sqlglot.dialects.dialect", "qualname": "filter_array_using_unnest", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ArrayFilter</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.to_number_with_nls_param": {"fullname": "sqlglot.dialects.dialect.to_number_with_nls_param", "modulename": "sqlglot.dialects.dialect", "qualname": "to_number_with_nls_param", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ToNumber</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.dialect.build_default_decimal_type": {"fullname": "sqlglot.dialects.dialect.build_default_decimal_type", "modulename": "sqlglot.dialects.dialect", "qualname": "build_default_decimal_type", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">precision</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">int</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">scale</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">int</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"p\">],</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.doris": {"fullname": "sqlglot.dialects.doris", "modulename": "sqlglot.dialects.doris", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.dialects.doris.Doris": {"fullname": "sqlglot.dialects.doris.Doris", "modulename": "sqlglot.dialects.doris", "qualname": "Doris", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.mysql.MySQL"}, "sqlglot.dialects.doris.Doris.DATE_FORMAT": {"fullname": "sqlglot.dialects.doris.Doris.DATE_FORMAT", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.DATE_FORMAT", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'yyyy-MM-dd'""}, "sqlglot.dialects.doris.Doris.DATEINT_FORMAT": {"fullname": "sqlglot.dialects.doris.Doris.DATEINT_FORMAT", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.DATEINT_FORMAT", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'yyyyMMdd'""}, "sqlglot.dialects.doris.Doris.TIME_FORMAT": {"fullname": "sqlglot.dialects.doris.Doris.TIME_FORMAT", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.TIME_FORMAT", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'yyyy-MM-dd HH:mm:ss'""}, "sqlglot.dialects.doris.Doris.Parser": {"fullname": "sqlglot.dialects.doris.Doris.Parser", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.Parser", "kind": "class", "doc": "<p>Parser consumes a list of tokens produced by the Tokenizer and produces a parsed syntax tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>error_level:</strong> The desired error level.\nDefault: ErrorLevel.IMMEDIATE</li>\n<li><strong>error_message_context:</strong> The amount of context to capture from a query string when displaying\nthe error message (in number of characters).\nDefault: 100</li>\n<li><strong>max_errors:</strong> Maximum number of error messages to include in a raised ParseError.\nThis is only relevant if error_level is ErrorLevel.RAISE.\nDefault: 3</li>\n</ul>\n", "bases": "sqlglot.dialects.mysql.MySQL.Parser"}, "sqlglot.dialects.doris.Doris.Parser.FUNCTIONS": {"fullname": "sqlglot.dialects.doris.Doris.Parser.FUNCTIONS", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.Parser.FUNCTIONS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ABS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Abs'>>, 'ADD_MONTHS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AddMonths'>>, 'ANONYMOUS_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnonymousAggFunc'>>, 'ANY_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnyValue'>>, 'APPROX_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_COUNT_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'APPROX_TOP_K': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxTopK'>>, 'ARG_MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARGMAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'MAX_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARG_MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARGMIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'MIN_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Array'>>, 'ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAgg'>>, 'ARRAY_ALL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAll'>>, 'ARRAY_ANY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAny'>>, 'ARRAY_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CONSTRUCT_COMPACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConstructCompact'>>, 'ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayContains'>>, 'FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_OVERLAPS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayOverlaps'>>, 'ARRAY_SIZE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_SORT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySort'>>, 'ARRAY_SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySum'>>, 'ARRAY_TO_STRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_JOIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_UNION_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUnionAgg'>>, 'ARRAY_UNIQUE_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUniqueAgg'>>, 'AVG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Avg'>>, 'CASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Case'>>, 'CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cast'>>, 'CAST_TO_STR_TYPE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CastToStrType'>>, 'CBRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cbrt'>>, 'CEIL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CEILING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CHR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'COALESCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'IFNULL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'NVL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'COLLATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Collate'>>, 'COMBINED_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedAggFunc'>>, 'COMBINED_PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedParameterizedAgg'>>, 'CONCAT': <function Parser.<lambda>>, 'CONCAT_WS': <function Parser.<lambda>>, 'CONNECT_BY_ROOT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ConnectByRoot'>>, 'CONVERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Convert'>>, 'CORR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Corr'>>, 'COUNT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Count'>>, 'COUNT_IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COUNTIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COVAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarPop'>>, 'COVAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarSamp'>>, 'CURRENT_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDate'>>, 'CURRENT_DATETIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDatetime'>>, 'CURRENT_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTime'>>, 'CURRENT_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTimestamp'>>, 'CURRENT_USER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentUser'>>, 'DATE': <function MySQL.Parser.<lambda>>, 'DATE_ADD': <function build_date_delta_with_interval.<locals>._builder>, 'DATEDIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateDiff'>>, 'DATE_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateDiff'>>, 'DATE_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATE_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateStrToDate'>>, 'DATE_SUB': <function build_date_delta_with_interval.<locals>._builder>, 'DATE_TO_DATE_STR': <function Parser.<lambda>>, 'DATE_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateToDi'>>, 'DATE_TRUNC': <function build_timestamp_trunc>, 'DATETIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeAdd'>>, 'DATETIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeDiff'>>, 'DATETIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeSub'>>, 'DATETIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeTrunc'>>, 'DAY': <function MySQL.Parser.<lambda>>, 'DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAYOFMONTH': <function MySQL.Parser.<lambda>>, 'DAY_OF_WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAYOFWEEK': <function MySQL.Parser.<lambda>>, 'DAY_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DAYOFYEAR': <function MySQL.Parser.<lambda>>, 'DECODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Decode'>>, 'DI_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DiToDate'>>, 'ENCODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Encode'>>, 'EXP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Exp'>>, 'EXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Explode'>>, 'EXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ExplodeOuter'>>, 'EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Extract'>>, 'FIRST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.First'>>, 'FIRST_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FirstValue'>>, 'FLATTEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Flatten'>>, 'FLOOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Floor'>>, 'FROM_BASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase'>>, 'FROM_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase64'>>, 'GENERATE_DATE_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GenerateDateArray'>>, 'GENERATE_SERIES': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GenerateSeries'>>, 'GREATEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Greatest'>>, 'GROUP_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GroupConcat'>>, 'HEX': <function build_hex>, 'HLL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Hll'>>, 'IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'IIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'INITCAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Initcap'>>, 'IS_INF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'ISINF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'IS_NAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'ISNAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'J_S_O_N_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArray'>>, 'J_S_O_N_ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArrayAgg'>>, 'JSON_ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArrayContains'>>, 'JSONB_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONBExtract'>>, 'JSONB_EXTRACT_SCALAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONBExtractScalar'>>, 'JSON_EXTRACT': <function build_extract_json_with_path.<locals>._builder>, 'JSON_EXTRACT_SCALAR': <function build_extract_json_with_path.<locals>._builder>, 'JSON_FORMAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONFormat'>>, 'J_S_O_N_OBJECT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONObject'>>, 'J_S_O_N_OBJECT_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONObjectAgg'>>, 'J_S_O_N_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONTable'>>, 'LAG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lag'>>, 'LAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Last'>>, 'LAST_DAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastDay'>>, 'LAST_DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastDay'>>, 'LAST_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastValue'>>, 'LEAD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lead'>>, 'LEAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Least'>>, 'LEFT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Left'>>, 'LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Length'>>, 'LEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Length'>>, 'LEVENSHTEIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Levenshtein'>>, 'LN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ln'>>, 'LOG': <function build_logarithm>, 'LOGICAL_AND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'BOOL_AND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'BOOLAND_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'LOGICAL_OR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'BOOL_OR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'BOOLOR_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'LOWER': <function build_lower>, 'LCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lower'>>, 'LOWER_HEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LowerHex'>>, 'MD5': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MD5'>>, 'MD5_DIGEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MD5Digest'>>, 'MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Map'>>, 'MAP_FROM_ENTRIES': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MapFromEntries'>>, 'MATCH_AGAINST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MatchAgainst'>>, 'MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Max'>>, 'MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Min'>>, 'MONTH': <function MySQL.Parser.<lambda>>, 'MONTHS_BETWEEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MonthsBetween'>>, 'NEXT_VALUE_FOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NextValueFor'>>, 'NTH_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NthValue'>>, 'NULLIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Nullif'>>, 'NUMBER_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NumberToStr'>>, 'NVL2': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Nvl2'>>, 'OPEN_J_S_O_N': <bound method Func.from_arg_list of <class 'sqlglot.expressions.OpenJSON'>>, 'PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParameterizedAgg'>>, 'PARSE_JSON': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParseJSON'>>, 'JSON_PARSE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParseJSON'>>, 'PERCENTILE_CONT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PercentileCont'>>, 'PERCENTILE_DISC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PercentileDisc'>>, 'POSEXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Posexplode'>>, 'POSEXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PosexplodeOuter'>>, 'POWER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Pow'>>, 'POW': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Pow'>>, 'PREDICT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Predict'>>, 'QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quantile'>>, 'QUARTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quarter'>>, 'RAND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'RANDOM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'RANDN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Randn'>>, 'RANGE_N': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RangeN'>>, 'READ_CSV': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ReadCSV'>>, 'REDUCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Reduce'>>, 'REGEXP_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpExtract'>>, 'REGEXP_I_LIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpILike'>>, 'REGEXP_LIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpLike'>>, 'REGEXP_REPLACE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpReplace'>>, 'REGEXP_SPLIT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpSplit'>>, 'REPEAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Repeat'>>, 'RIGHT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Right'>>, 'ROUND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Round'>>, 'ROW_NUMBER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RowNumber'>>, 'SHA': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA'>>, 'SHA1': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA'>>, 'SHA2': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA2'>>, 'SAFE_DIVIDE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SafeDivide'>>, 'SIGN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sign'>>, 'SIGNUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sign'>>, 'SORT_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SortArray'>>, 'SPLIT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Split'>>, 'SQRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sqrt'>>, 'STANDARD_HASH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StandardHash'>>, 'STAR_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StarMap'>>, 'STARTS_WITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STARTSWITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STDDEV': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stddev'>>, 'STDDEV_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StddevPop'>>, 'STDDEV_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StddevSamp'>>, 'STR_POSITION': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrPosition'>>, 'STR_TO_DATE': <function _str_to_date>, 'STR_TO_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToMap'>>, 'STR_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToTime'>>, 'STR_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToUnix'>>, 'STRUCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Struct'>>, 'STRUCT_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StructExtract'>>, 'STUFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stuff'>>, 'INSERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stuff'>>, 'SUBSTRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Substring'>>, 'SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sum'>>, 'TIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeAdd'>>, 'TIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeDiff'>>, 'TIME_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'TIMEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'TIME_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToDate'>>, 'TIME_STR_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToTime'>>, 'TIME_STR_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToUnix'>>, 'TIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeSub'>>, 'TIME_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeToStr'>>, 'TIME_TO_TIME_STR': <function Parser.<lambda>>, 'TIME_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeToUnix'>>, 'TIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeTrunc'>>, 'TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Timestamp'>>, 'TIMESTAMP_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampAdd'>>, 'TIMESTAMPDIFF': <function build_date_delta.<locals>._builder>, 'TIMESTAMP_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampDiff'>>, 'TIMESTAMP_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampFromParts'>>, 'TIMESTAMPFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampFromParts'>>, 'TIMESTAMP_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampSub'>>, 'TIMESTAMP_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampTrunc'>>, 'TO_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToArray'>>, 'TO_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToBase64'>>, 'TO_CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToChar'>>, 'TO_DAYS': <function MySQL.Parser.<lambda>>, 'TO_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToMap'>>, 'TO_NUMBER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToNumber'>>, 'TRANSFORM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Transform'>>, 'TRIM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Trim'>>, 'TRY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Try'>>, 'TRY_CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TryCast'>>, 'TS_OR_DI_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDiToDi'>>, 'TS_OR_DS_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsAdd'>>, 'TS_OR_DS_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsDiff'>>, 'TS_OR_DS_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToDate'>>, 'TS_OR_DS_TO_DATE_STR': <function Parser.<lambda>>, 'TS_OR_DS_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTime'>>, 'TS_OR_DS_TO_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTimestamp'>>, 'UNHEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Unhex'>>, 'UNIX_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixDate'>>, 'UNIX_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToStr'>>, 'UNIX_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTime'>>, 'UNIX_TO_TIME_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTimeStr'>>, 'UPPER': <function build_upper>, 'UCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Upper'>>, 'VAR_MAP': <function build_var_map>, 'VARIANCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'VAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'WEEK': <function MySQL.Parser.<lambda>>, 'WEEK_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.WeekOfYear'>>, 'WEEKOFYEAR': <function MySQL.Parser.<lambda>>, 'WHEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.When'>>, 'X_M_L_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.XMLTable'>>, 'XOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Xor'>>, 'YEAR': <function MySQL.Parser.<lambda>>, 'GLOB': <function Parser.<lambda>>, 'JSON_EXTRACT_PATH_TEXT': <function build_extract_json_with_path.<locals>._builder>, 'LIKE': <function build_like>, 'LOG2': <function Parser.<lambda>>, 'LOG10': <function Parser.<lambda>>, 'MOD': <function build_mod>, 'TO_HEX': <function build_hex>, 'DATE_FORMAT': <function build_formatted_time.<locals>._builder>, 'INSTR': <function MySQL.Parser.<lambda>>, 'FROM_UNIXTIME': <function build_formatted_time.<locals>._builder>, 'ISNULL': <function isnull_to_is_null>, 'LOCATE': <function locate_to_strposition>, 'MAKETIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'MONTHNAME': <function MySQL.Parser.<lambda>>, 'COLLECT_SET': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUniqueAgg'>>, 'MONTHS_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AddMonths'>>, 'REGEXP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpLike'>>, 'TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToDate'>>}"}, "sqlglot.dialects.doris.Doris.Parser.TABLE_ALIAS_TOKENS": {"fullname": "sqlglot.dialects.doris.Doris.Parser.TABLE_ALIAS_TOKENS", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.Parser.TABLE_ALIAS_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.KILL: 'KILL'>, <TokenType.MONEY: 'MONEY'>, <TokenType.COPY: 'COPY'>, <TokenType.PERCENT: 'PERCENT'>, <TokenType.TAG: 'TAG'>, <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, <TokenType.VOLATILE: 'VOLATILE'>, <TokenType.IDENTIFIER: 'IDENTIFIER'>, <TokenType.VARBINARY: 'VARBINARY'>, <TokenType.HSTORE: 'HSTORE'>, <TokenType.ASC: 'ASC'>, <TokenType.IPADDRESS: 'IPADDRESS'>, <TokenType.ISNULL: 'ISNULL'>, <TokenType.TEMPORARY: 'TEMPORARY'>, <TokenType.PROCEDURE: 'PROCEDURE'>, <TokenType.SCHEMA: 'SCHEMA'>, <TokenType.NUMRANGE: 'NUMRANGE'>, <TokenType.DATE32: 'DATE32'>, <TokenType.INT8RANGE: 'INT8RANGE'>, <TokenType.ANTI: 'ANTI'>, <TokenType.AGGREGATEFUNCTION: 'AGGREGATEFUNCTION'>, <TokenType.VIEW: 'VIEW'>, <TokenType.VARCHAR: 'VARCHAR'>, <TokenType.TIMETZ: 'TIMETZ'>, <TokenType.GEOMETRY: 'GEOMETRY'>, <TokenType.BEGIN: 'BEGIN'>, <TokenType.ENUM8: 'ENUM8'>, <TokenType.INDEX: 'INDEX'>, <TokenType.PARTITION: 'PARTITION'>, <TokenType.UINT256: 'UINT256'>, <TokenType.BIGINT: 'BIGINT'>, <TokenType.CACHE: 'CACHE'>, <TokenType.OPERATOR: 'OPERATOR'>, <TokenType.COLUMN: 'COLUMN'>, <TokenType.INT128: 'INT128'>, <TokenType.SMALLMONEY: 'SMALLMONEY'>, <TokenType.HLLSKETCH: 'HLLSKETCH'>, <TokenType.UNPIVOT: 'UNPIVOT'>, <TokenType.SMALLINT: 'SMALLINT'>, <TokenType.INT256: 'INT256'>, <TokenType.FLOAT: 'FLOAT'>, <TokenType.COMMIT: 'COMMIT'>, <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, <TokenType.EXISTS: 'EXISTS'>, <TokenType.NULL: 'NULL'>, <TokenType.RECURSIVE: 'RECURSIVE'>, <TokenType.SET: 'SET'>, <TokenType.NULLABLE: 'NULLABLE'>, <TokenType.REFRESH: 'REFRESH'>, <TokenType.TINYTEXT: 'TINYTEXT'>, <TokenType.SHOW: 'SHOW'>, <TokenType.DEFAULT: 'DEFAULT'>, <TokenType.DATE: 'DATE'>, <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <TokenType.MERGE: 'MERGE'>, <TokenType.FIRST: 'FIRST'>, <TokenType.BINARY: 'BINARY'>, <TokenType.ARRAY: 'ARRAY'>, <TokenType.SERIAL: 'SERIAL'>, <TokenType.EXECUTE: 'EXECUTE'>, <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, <TokenType.INTERVAL: 'INTERVAL'>, <TokenType.PRAGMA: 'PRAGMA'>, <TokenType.STORAGE_INTEGRATION: 'STORAGE_INTEGRATION'>, <TokenType.BPCHAR: 'BPCHAR'>, <TokenType.BIT: 'BIT'>, <TokenType.UINT: 'UINT'>, <TokenType.UUID: 'UUID'>, <TokenType.STRUCT: 'STRUCT'>, <TokenType.FALSE: 'FALSE'>, <TokenType.FUNCTION: 'FUNCTION'>, <TokenType.TOP: 'TOP'>, <TokenType.SUPER: 'SUPER'>, <TokenType.CASE: 'CASE'>, <TokenType.IMAGE: 'IMAGE'>, <TokenType.UBIGINT: 'UBIGINT'>, <TokenType.LONGBLOB: 'LONGBLOB'>, <TokenType.ROLLUP: 'ROLLUP'>, <TokenType.VAR: 'VAR'>, <TokenType.COMMAND: 'COMMAND'>, <TokenType.LOAD: 'LOAD'>, <TokenType.TRUNCATE: 'TRUNCATE'>, <TokenType.KEEP: 'KEEP'>, <TokenType.UMEDIUMINT: 'UMEDIUMINT'>, <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, <TokenType.UINT128: 'UINT128'>, <TokenType.END: 'END'>, <TokenType.MAP: 'MAP'>, <TokenType.IPV4: 'IPV4'>, <TokenType.USERDEFINED: 'USERDEFINED'>, <TokenType.REFERENCES: 'REFERENCES'>, <TokenType.REPLACE: 'REPLACE'>, <TokenType.RANGE: 'RANGE'>, <TokenType.NVARCHAR: 'NVARCHAR'>, <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, <TokenType.TRUE: 'TRUE'>, <TokenType.TIMESTAMP_MS: 'TIMESTAMP_MS'>, <TokenType.VARIANT: 'VARIANT'>, <TokenType.ENUM: 'ENUM'>, <TokenType.USMALLINT: 'USMALLINT'>, <TokenType.OVERLAPS: 'OVERLAPS'>, <TokenType.TIMESTAMP_S: 'TIMESTAMP_S'>, <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, <TokenType.UNIQUE: 'UNIQUE'>, <TokenType.ORDINALITY: 'ORDINALITY'>, <TokenType.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>, <TokenType.TEXT: 'TEXT'>, <TokenType.DATABASE: 'DATABASE'>, <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, <TokenType.PSEUDO_TYPE: 'PSEUDO_TYPE'>, <TokenType.FIXEDSTRING: 'FIXEDSTRING'>, <TokenType.NEXT: 'NEXT'>, <TokenType.INT: 'INT'>, <TokenType.BIGSERIAL: 'BIGSERIAL'>, <TokenType.BOOLEAN: 'BOOLEAN'>, <TokenType.IS: 'IS'>, <TokenType.CONSTRAINT: 'CONSTRAINT'>, <TokenType.FINAL: 'FINAL'>, <TokenType.UNKNOWN: 'UNKNOWN'>, <TokenType.SETTINGS: 'SETTINGS'>, <TokenType.ROWS: 'ROWS'>, <TokenType.TSTZRANGE: 'TSTZRANGE'>, <TokenType.DATETIME64: 'DATETIME64'>, <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, <TokenType.DATETIME: 'DATETIME'>, <TokenType.MEDIUMINT: 'MEDIUMINT'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>, <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, <TokenType.XML: 'XML'>, <TokenType.JSON: 'JSON'>, <TokenType.UTINYINT: 'UTINYINT'>, <TokenType.DELETE: 'DELETE'>, <TokenType.TIME: 'TIME'>, <TokenType.UDECIMAL: 'UDECIMAL'>, <TokenType.NESTED: 'NESTED'>, <TokenType.SEMI: 'SEMI'>, <TokenType.DESC: 'DESC'>, <TokenType.ROWVERSION: 'ROWVERSION'>, <TokenType.TIMESTAMP_NS: 'TIMESTAMP_NS'>, <TokenType.ANY: 'ANY'>, <TokenType.DIV: 'DIV'>, <TokenType.DICTIONARY: 'DICTIONARY'>, <TokenType.INET: 'INET'>, <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, <TokenType.COMMENT: 'COMMENT'>, <TokenType.CURRENT_USER: 'CURRENT_USER'>, <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>, <TokenType.ALL: 'ALL'>, <TokenType.NAME: 'NAME'>, <TokenType.SOME: 'SOME'>, <TokenType.ENUM16: 'ENUM16'>, <TokenType.YEAR: 'YEAR'>, <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, <TokenType.DOUBLE: 'DOUBLE'>, <TokenType.INT4RANGE: 'INT4RANGE'>, <TokenType.FORMAT: 'FORMAT'>, <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, <TokenType.IPPREFIX: 'IPPREFIX'>, <TokenType.OVERWRITE: 'OVERWRITE'>, <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>, <TokenType.COLLATE: 'COLLATE'>, <TokenType.FILTER: 'FILTER'>, <TokenType.JSONB: 'JSONB'>, <TokenType.TDIGEST: 'TDIGEST'>, <TokenType.CHAR: 'CHAR'>, <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.ROW: 'ROW'>, <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.TABLE: 'TABLE'>, <TokenType.DATERANGE: 'DATERANGE'>, <TokenType.TSRANGE: 'TSRANGE'>, <TokenType.ESCAPE: 'ESCAPE'>, <TokenType.PIVOT: 'PIVOT'>, <TokenType.DECIMAL: 'DECIMAL'>, <TokenType.NCHAR: 'NCHAR'>, <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, <TokenType.UPDATE: 'UPDATE'>, <TokenType.MODEL: 'MODEL'>, <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, <TokenType.SEQUENCE: 'SEQUENCE'>, <TokenType.LONGTEXT: 'LONGTEXT'>, <TokenType.DESCRIBE: 'DESCRIBE'>, <TokenType.IPV6: 'IPV6'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, <TokenType.TINYINT: 'TINYINT'>, <TokenType.TINYBLOB: 'TINYBLOB'>}"}, "sqlglot.dialects.doris.Doris.Parser.SHOW_TRIE": {"fullname": "sqlglot.dialects.doris.Doris.Parser.SHOW_TRIE", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.Parser.SHOW_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'BINARY': {'LOGS': {0: True}}, 'MASTER': {'LOGS': {0: True}, 'STATUS': {0: True}}, 'BINLOG': {'EVENTS': {0: True}}, 'CHARACTER': {'SET': {0: True}}, 'CHARSET': {0: True}, 'COLLATION': {0: True}, 'FULL': {'COLUMNS': {0: True}, 'PROCESSLIST': {0: True}, 'TABLES': {0: True}}, 'COLUMNS': {0: True}, 'CREATE': {'DATABASE': {0: True}, 'EVENT': {0: True}, 'FUNCTION': {0: True}, 'PROCEDURE': {0: True}, 'TABLE': {0: True}, 'TRIGGER': {0: True}, 'VIEW': {0: True}}, 'DATABASES': {0: True}, 'SCHEMAS': {0: True}, 'ENGINE': {0: True}, 'STORAGE': {'ENGINES': {0: True}}, 'ENGINES': {0: True}, 'ERRORS': {0: True}, 'EVENTS': {0: True}, 'FUNCTION': {'CODE': {0: True}, 'STATUS': {0: True}}, 'GRANTS': {0: True}, 'INDEX': {0: True}, 'OPEN': {'TABLES': {0: True}}, 'PLUGINS': {0: True}, 'PROCEDURE': {'CODE': {0: True}, 'STATUS': {0: True}}, 'PRIVILEGES': {0: True}, 'PROCESSLIST': {0: True}, 'PROFILE': {0: True}, 'PROFILES': {0: True}, 'RELAYLOG': {'EVENTS': {0: True}}, 'REPLICAS': {0: True}, 'SLAVE': {'HOSTS': {0: True}, 'STATUS': {0: True}}, 'REPLICA': {'STATUS': {0: True}}, 'GLOBAL': {'STATUS': {0: True}, 'VARIABLES': {0: True}}, 'SESSION': {'STATUS': {0: True}, 'VARIABLES': {0: True}}, 'STATUS': {0: True}, 'TABLE': {'STATUS': {0: True}}, 'TABLES': {0: True}, 'TRIGGERS': {0: True}, 'VARIABLES': {0: True}, 'WARNINGS': {0: True}}"}, "sqlglot.dialects.doris.Doris.Parser.SET_TRIE": {"fullname": "sqlglot.dialects.doris.Doris.Parser.SET_TRIE", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.Parser.SET_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'GLOBAL': {0: True}, 'LOCAL': {0: True}, 'SESSION': {0: True}, 'TRANSACTION': {0: True}, 'PERSIST': {0: True}, 'PERSIST_ONLY': {0: True}, 'CHARACTER': {'SET': {0: True}}, 'CHARSET': {0: True}, 'NAMES': {0: True}}"}, "sqlglot.dialects.doris.Doris.Generator": {"fullname": "sqlglot.dialects.doris.Doris.Generator", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.Generator", "kind": "class", "doc": "<p>Generator converts a given syntax tree to the corresponding SQL string.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>pretty:</strong> Whether to format the produced SQL string.\nDefault: False.</li>\n<li><strong>identify:</strong> Determines when an identifier should be quoted. Possible values are:\nFalse (default): Never quote, except in cases where it's mandatory by the dialect.\nTrue or 'always': Always quote.\n'safe': Only quote identifiers that are case insensitive.</li>\n<li><strong>normalize:</strong> Whether to normalize identifiers to lowercase.\nDefault: False.</li>\n<li><strong>pad:</strong> The pad size in a formatted string. For example, this affects the indentation of\na projection in a query, relative to its nesting level.\nDefault: 2.</li>\n<li><strong>indent:</strong> The indentation size in a formatted string. For example, this affects the\nindentation of subqueries and filters under a <code>WHERE</code> clause.\nDefault: 2.</li>\n<li><strong>normalize_functions:</strong> How to normalize function names. Possible values are:\n\"upper\" or True (default): Convert names to uppercase.\n\"lower\": Convert names to lowercase.\nFalse: Disables function name normalization.</li>\n<li><strong>unsupported_level:</strong> Determines the generator's behavior when it encounters unsupported expressions.\nDefault ErrorLevel.WARN.</li>\n<li><strong>max_unsupported:</strong> Maximum number of unsupported messages to include in a raised UnsupportedError.\nThis is only relevant if unsupported_level is ErrorLevel.RAISE.\nDefault: 3</li>\n<li><strong>leading_comma:</strong> Whether the comma is leading or trailing in select expressions.\nThis is only relevant when generating in pretty mode.\nDefault: False</li>\n<li><strong>max_text_width:</strong> The max number of characters in a segment before creating new lines in pretty mode.\nThe default is on the smaller end because the length only represents a segment and not the true\nline length.\nDefault: 80</li>\n<li><strong>comments:</strong> Whether to preserve comments in the output SQL code.\nDefault: True</li>\n</ul>\n", "bases": "sqlglot.dialects.mysql.MySQL.Generator"}, "sqlglot.dialects.doris.Doris.Generator.LAST_DAY_SUPPORTS_DATE_PART": {"fullname": "sqlglot.dialects.doris.Doris.Generator.LAST_DAY_SUPPORTS_DATE_PART", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.Generator.LAST_DAY_SUPPORTS_DATE_PART", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.doris.Doris.Generator.TYPE_MAPPING": {"fullname": "sqlglot.dialects.doris.Doris.Generator.TYPE_MAPPING", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.Generator.TYPE_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.NCHAR: 'NCHAR'>: 'CHAR', <Type.NVARCHAR: 'NVARCHAR'>: 'VARCHAR', <Type.INET: 'INET'>: 'INET', <Type.ROWVERSION: 'ROWVERSION'>: 'VARBINARY', <Type.UBIGINT: 'UBIGINT'>: 'BIGINT', <Type.UINT: 'UINT'>: 'INT', <Type.UMEDIUMINT: 'UMEDIUMINT'>: 'MEDIUMINT', <Type.USMALLINT: 'USMALLINT'>: 'SMALLINT', <Type.UTINYINT: 'UTINYINT'>: 'TINYINT', <Type.UDECIMAL: 'UDECIMAL'>: 'DECIMAL', <Type.TIMESTAMP: 'TIMESTAMP'>: 'DATETIME', <Type.TIMESTAMPTZ: 'TIMESTAMPTZ'>: 'DATETIME', <Type.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>: 'TIMESTAMP', <Type.TEXT: 'TEXT'>: 'STRING'}"}, "sqlglot.dialects.doris.Doris.Generator.CAST_MAPPING": {"fullname": "sqlglot.dialects.doris.Doris.Generator.CAST_MAPPING", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.Generator.CAST_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{}"}, "sqlglot.dialects.doris.Doris.Generator.TIMESTAMP_FUNC_TYPES": {"fullname": "sqlglot.dialects.doris.Doris.Generator.TIMESTAMP_FUNC_TYPES", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.Generator.TIMESTAMP_FUNC_TYPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "set()"}, "sqlglot.dialects.doris.Doris.Generator.TRANSFORMS": {"fullname": "sqlglot.dialects.doris.Doris.Generator.TRANSFORMS", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.Generator.TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.JSONPathFilter'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathKey'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRecursive'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRoot'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathScript'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSelector'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSlice'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSubscript'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathUnion'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathWildcard'>: <function <lambda>>, <class 'sqlglot.expressions.AllowedValuesProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.BackupProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CaseSpecificColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CollateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CommentColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DateFormatColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DefaultColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EncodeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EphemeralColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExcludeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExternalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.GlobalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.HeapProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IcebergProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InheritsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InlineLengthColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IntervalSpan'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtract'>: <function arrow_json_extract_sql>, <class 'sqlglot.expressions.JSONExtractScalar'>: <function arrow_json_extract_sql>, <class 'sqlglot.expressions.LanguageProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LocationProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LogProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.MaterializedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NonClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NotForReplicationColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnCommitProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnUpdateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OutputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.PathColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ReturnsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SampleProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetConfigProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SettingsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SharingProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlReadWriteProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlSecurityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StabilityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StrictProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TemporaryProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TitleColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.Timestamp'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransformModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransientProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UppercaseColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UnloggedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VarMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VolatileProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithOperator'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ArrayAgg'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.CurrentDate'>: <function no_paren_current_date_sql>, <class 'sqlglot.expressions.DateDiff'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.DateAdd'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.DateStrToDate'>: <function datestrtodate_sql>, <class 'sqlglot.expressions.DateSub'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.DateTrunc'>: <function Doris.Generator.<lambda>>, <class 'sqlglot.expressions.Day'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.DayOfMonth'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.DayOfWeek'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.DayOfYear'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.GroupConcat'>: <function MySQL.Generator.<lambda>>, <class 'sqlglot.expressions.ILike'>: <function no_ilike_sql>, <class 'sqlglot.expressions.Max'>: <function max_or_greatest>, <class 'sqlglot.expressions.Min'>: <function min_or_least>, <class 'sqlglot.expressions.Month'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.NullSafeEQ'>: <function MySQL.Generator.<lambda>>, <class 'sqlglot.expressions.NullSafeNEQ'>: <function MySQL.Generator.<lambda>>, <class 'sqlglot.expressions.ParseJSON'>: <function MySQL.Generator.<lambda>>, <class 'sqlglot.expressions.Pivot'>: <function no_pivot_sql>, <class 'sqlglot.expressions.Select'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.StrPosition'>: <function strposition_to_locate_sql>, <class 'sqlglot.expressions.StrToDate'>: <function _str_to_date_sql>, <class 'sqlglot.expressions.StrToTime'>: <function _str_to_date_sql>, <class 'sqlglot.expressions.Stuff'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.TableSample'>: <function no_tablesample_sql>, <class 'sqlglot.expressions.TimeFromParts'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.TimestampAdd'>: <function date_add_interval_sql.<locals>.func>, <class 'sqlglot.expressions.TimestampDiff'>: <function MySQL.Generator.<lambda>>, <class 'sqlglot.expressions.TimestampSub'>: <function date_add_interval_sql.<locals>.func>, <class 'sqlglot.expressions.TimeStrToUnix'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.TimeStrToTime'>: <function MySQL.Generator.<lambda>>, <class 'sqlglot.expressions.TimeToStr'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.Trim'>: <function _trim_sql>, <class 'sqlglot.expressions.TryCast'>: <function no_trycast_sql>, <class 'sqlglot.expressions.TsOrDsAdd'>: <function Doris.Generator.<lambda>>, <class 'sqlglot.expressions.TsOrDsDiff'>: <function MySQL.Generator.<lambda>>, <class 'sqlglot.expressions.TsOrDsToDate'>: <function Doris.Generator.<lambda>>, <class 'sqlglot.expressions.UnixToTime'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.Week'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.WeekOfYear'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.Year'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.AddMonths'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ApproxDistinct'>: <function approx_count_distinct_sql>, <class 'sqlglot.expressions.ArgMax'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ArgMin'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ArrayUniqueAgg'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.CurrentTimestamp'>: <function Doris.Generator.<lambda>>, <class 'sqlglot.expressions.Map'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.RegexpLike'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.RegexpSplit'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.StrToUnix'>: <function Doris.Generator.<lambda>>, <class 'sqlglot.expressions.Split'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.TimeStrToDate'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.TimeToUnix'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.TimestampTrunc'>: <function Doris.Generator.<lambda>>, <class 'sqlglot.expressions.UnixToStr'>: <function Doris.Generator.<lambda>>}"}, "sqlglot.dialects.doris.Doris.Generator.SELECT_KINDS": {"fullname": "sqlglot.dialects.doris.Doris.Generator.SELECT_KINDS", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.Generator.SELECT_KINDS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Tuple[str, ...]", "default_value": "()"}, "sqlglot.dialects.doris.Doris.Generator.TRY_SUPPORTED": {"fullname": "sqlglot.dialects.doris.Doris.Generator.TRY_SUPPORTED", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.Generator.TRY_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.doris.Doris.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS": {"fullname": "sqlglot.dialects.doris.Doris.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'qualify': <function Generator.<lambda>>, 'windows': <function Generator.<lambda>>}"}, "sqlglot.dialects.doris.Doris.UNESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.doris.Doris.UNESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.UNESCAPED_SEQUENCES", "kind": "variable", "doc": "<p>Mapping of an escaped sequence (<code>\\n</code>) to its unescaped version (<code>\n</code>).</p>\n", "annotation": ": Dict[str, str]", "default_value": "{'\\\\a': '\\x07', '\\\\b': '\\x08', '\\\\f': '\\x0c', '\\\\n': '\\n', '\\\\r': '\\r', '\\\\t': '\\t', '\\\\v': '\\x0b', '\\\\\\\\': '\\\\'}"}, "sqlglot.dialects.doris.Doris.tokenizer_class": {"fullname": "sqlglot.dialects.doris.Doris.tokenizer_class", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.tokenizer_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.tokens.Tokenizer'>"}, "sqlglot.dialects.doris.Doris.parser_class": {"fullname": "sqlglot.dialects.doris.Doris.parser_class", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.parser_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.doris.Doris.Parser'>"}, "sqlglot.dialects.doris.Doris.generator_class": {"fullname": "sqlglot.dialects.doris.Doris.generator_class", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.generator_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.doris.Doris.Generator'>"}, "sqlglot.dialects.doris.Doris.TIME_TRIE": {"fullname": "sqlglot.dialects.doris.Doris.TIME_TRIE", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'%': {'M': {0: True}, 'c': {0: True}, 'e': {0: True}, 'h': {0: True}, 'i': {0: True}, 's': {0: True}, 'u': {0: True}, 'k': {0: True}, 'l': {0: True}, 'T': {0: True}, 'W': {0: True}}}"}, "sqlglot.dialects.doris.Doris.FORMAT_TRIE": {"fullname": "sqlglot.dialects.doris.Doris.FORMAT_TRIE", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.FORMAT_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'%': {'M': {0: True}, 'c': {0: True}, 'e': {0: True}, 'h': {0: True}, 'i': {0: True}, 's': {0: True}, 'u': {0: True}, 'k': {0: True}, 'l': {0: True}, 'T': {0: True}, 'W': {0: True}}}"}, "sqlglot.dialects.doris.Doris.INVERSE_TIME_MAPPING": {"fullname": "sqlglot.dialects.doris.Doris.INVERSE_TIME_MAPPING", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.INVERSE_TIME_MAPPING", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'%B': '%M', '%-m': '%c', '%-d': '%e', '%I': '%h', '%M': '%i', '%S': '%s', '%W': '%u', '%-H': '%k', '%-I': '%l', '%H:%M:%S': '%T', '%a': '%W'}"}, "sqlglot.dialects.doris.Doris.INVERSE_TIME_TRIE": {"fullname": "sqlglot.dialects.doris.Doris.INVERSE_TIME_TRIE", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.INVERSE_TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'%': {'B': {0: True}, '-': {'m': {0: True}, 'd': {0: True}, 'H': {0: True}, 'I': {0: True}}, 'I': {0: True}, 'M': {0: True}, 'S': {0: True}, 'W': {0: True}, 'H': {':': {'%': {'M': {':': {'%': {'S': {0: True}}}}}}}, 'a': {0: True}}}"}, "sqlglot.dialects.doris.Doris.ESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.doris.Doris.ESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.ESCAPED_SEQUENCES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'\\x07': '\\\\a', '\\x08': '\\\\b', '\\x0c': '\\\\f', '\\n': '\\\\n', '\\r': '\\\\r', '\\t': '\\\\t', '\\x0b': '\\\\v', '\\\\': '\\\\\\\\'}"}, "sqlglot.dialects.doris.Doris.QUOTE_START": {"fullname": "sqlglot.dialects.doris.Doris.QUOTE_START", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.QUOTE_START", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.doris.Doris.QUOTE_END": {"fullname": "sqlglot.dialects.doris.Doris.QUOTE_END", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.QUOTE_END", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.doris.Doris.IDENTIFIER_START": {"fullname": "sqlglot.dialects.doris.Doris.IDENTIFIER_START", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.IDENTIFIER_START", "kind": "variable", "doc": "<p></p>\n", "default_value": "'`'"}, "sqlglot.dialects.doris.Doris.IDENTIFIER_END": {"fullname": "sqlglot.dialects.doris.Doris.IDENTIFIER_END", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.IDENTIFIER_END", "kind": "variable", "doc": "<p></p>\n", "default_value": "'`'"}, "sqlglot.dialects.doris.Doris.BIT_START": {"fullname": "sqlglot.dialects.doris.Doris.BIT_START", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.BIT_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""b'""}, "sqlglot.dialects.doris.Doris.BIT_END": {"fullname": "sqlglot.dialects.doris.Doris.BIT_END", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.BIT_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""'""}, "sqlglot.dialects.doris.Doris.HEX_START": {"fullname": "sqlglot.dialects.doris.Doris.HEX_START", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.HEX_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""x'""}, "sqlglot.dialects.doris.Doris.HEX_END": {"fullname": "sqlglot.dialects.doris.Doris.HEX_END", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.HEX_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""'""}, "sqlglot.dialects.doris.Doris.BYTE_START": {"fullname": "sqlglot.dialects.doris.Doris.BYTE_START", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.BYTE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.doris.Doris.BYTE_END": {"fullname": "sqlglot.dialects.doris.Doris.BYTE_END", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.BYTE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.doris.Doris.UNICODE_START": {"fullname": "sqlglot.dialects.doris.Doris.UNICODE_START", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.UNICODE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.doris.Doris.UNICODE_END": {"fullname": "sqlglot.dialects.doris.Doris.UNICODE_END", "modulename": "sqlglot.dialects.doris", "qualname": "Doris.UNICODE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.drill": {"fullname": "sqlglot.dialects.drill", "modulename": "sqlglot.dialects.drill", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.dialects.drill.Drill": {"fullname": "sqlglot.dialects.drill.Drill", "modulename": "sqlglot.dialects.drill", "qualname": "Drill", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.dialect.Dialect"}, "sqlglot.dialects.drill.Drill.NORMALIZE_FUNCTIONS": {"fullname": "sqlglot.dialects.drill.Drill.NORMALIZE_FUNCTIONS", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.NORMALIZE_FUNCTIONS", "kind": "variable", "doc": "<p>Determines how function names are going to be normalized.</p>\n\n<h6 id=\"possible-values\">Possible values:</h6>\n\n<blockquote>\n <p>\"upper\" or True: Convert names to uppercase.\n \"lower\": Convert names to lowercase.\n False: Disables function name normalization.</p>\n</blockquote>\n", "annotation": ": bool | str", "default_value": "False"}, "sqlglot.dialects.drill.Drill.NULL_ORDERING": {"fullname": "sqlglot.dialects.drill.Drill.NULL_ORDERING", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.NULL_ORDERING", "kind": "variable", "doc": "<p>Default <code>NULL</code> ordering method to use if not explicitly set.\nPossible values: <code>\"nulls_are_small\"</code>, <code>\"nulls_are_large\"</code>, <code>\"nulls_are_last\"</code></p>\n", "default_value": "'nulls_are_last'"}, "sqlglot.dialects.drill.Drill.DATE_FORMAT": {"fullname": "sqlglot.dialects.drill.Drill.DATE_FORMAT", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.DATE_FORMAT", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'yyyy-MM-dd'""}, "sqlglot.dialects.drill.Drill.DATEINT_FORMAT": {"fullname": "sqlglot.dialects.drill.Drill.DATEINT_FORMAT", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.DATEINT_FORMAT", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'yyyyMMdd'""}, "sqlglot.dialects.drill.Drill.TIME_FORMAT": {"fullname": "sqlglot.dialects.drill.Drill.TIME_FORMAT", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.TIME_FORMAT", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'yyyy-MM-dd HH:mm:ss'""}, "sqlglot.dialects.drill.Drill.SUPPORTS_USER_DEFINED_TYPES": {"fullname": "sqlglot.dialects.drill.Drill.SUPPORTS_USER_DEFINED_TYPES", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.SUPPORTS_USER_DEFINED_TYPES", "kind": "variable", "doc": "<p>Whether user-defined data types are supported.</p>\n", "default_value": "False"}, "sqlglot.dialects.drill.Drill.SUPPORTS_SEMI_ANTI_JOIN": {"fullname": "sqlglot.dialects.drill.Drill.SUPPORTS_SEMI_ANTI_JOIN", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.SUPPORTS_SEMI_ANTI_JOIN", "kind": "variable", "doc": "<p>Whether <code>SEMI</code> or <code>ANTI</code> joins are supported.</p>\n", "default_value": "False"}, "sqlglot.dialects.drill.Drill.TYPED_DIVISION": {"fullname": "sqlglot.dialects.drill.Drill.TYPED_DIVISION", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.TYPED_DIVISION", "kind": "variable", "doc": "<p>Whether the behavior of <code>a / b</code> depends on the types of <code>a</code> and <code>b</code>.\nFalse means <code>a / b</code> is always float division.\nTrue means <code>a / b</code> is integer division if both <code>a</code> and <code>b</code> are integers.</p>\n", "default_value": "True"}, "sqlglot.dialects.drill.Drill.CONCAT_COALESCE": {"fullname": "sqlglot.dialects.drill.Drill.CONCAT_COALESCE", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.CONCAT_COALESCE", "kind": "variable", "doc": "<p>A <code>NULL</code> arg in <code>CONCAT</code> yields <code>NULL</code> by default, but in some dialects it yields an empty string.</p>\n", "default_value": "True"}, "sqlglot.dialects.drill.Drill.TIME_MAPPING": {"fullname": "sqlglot.dialects.drill.Drill.TIME_MAPPING", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.TIME_MAPPING", "kind": "variable", "doc": "<p>Associates this dialect's time formats with their equivalent Python <code>strftime</code> formats.</p>\n", "default_value": "{'y': '%Y', 'Y': '%Y', 'YYYY': '%Y', 'yyyy': '%Y', 'YY': '%y', 'yy': '%y', 'MMMM': '%B', 'MMM': '%b', 'MM': '%m', 'M': '%-m', 'dd': '%d', 'd': '%-d', 'HH': '%H', 'H': '%-H', 'hh': '%I', 'h': '%-I', 'mm': '%M', 'm': '%-M', 'ss': '%S', 's': '%-S', 'SSSSSS': '%f', 'a': '%p', 'DD': '%j', 'D': '%-j', 'E': '%a', 'EE': '%a', 'EEE': '%a', 'EEEE': '%A', "''T''": 'T'}"}, "sqlglot.dialects.drill.Drill.Tokenizer": {"fullname": "sqlglot.dialects.drill.Drill.Tokenizer", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.Tokenizer", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.tokens.Tokenizer"}, "sqlglot.dialects.drill.Drill.Tokenizer.IDENTIFIERS": {"fullname": "sqlglot.dialects.drill.Drill.Tokenizer.IDENTIFIERS", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.Tokenizer.IDENTIFIERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "['`']"}, "sqlglot.dialects.drill.Drill.Tokenizer.STRING_ESCAPES": {"fullname": "sqlglot.dialects.drill.Drill.Tokenizer.STRING_ESCAPES", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.Tokenizer.STRING_ESCAPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "['\\\\']"}, "sqlglot.dialects.drill.Drill.Parser": {"fullname": "sqlglot.dialects.drill.Drill.Parser", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.Parser", "kind": "class", "doc": "<p>Parser consumes a list of tokens produced by the Tokenizer and produces a parsed syntax tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>error_level:</strong> The desired error level.\nDefault: ErrorLevel.IMMEDIATE</li>\n<li><strong>error_message_context:</strong> The amount of context to capture from a query string when displaying\nthe error message (in number of characters).\nDefault: 100</li>\n<li><strong>max_errors:</strong> Maximum number of error messages to include in a raised ParseError.\nThis is only relevant if error_level is ErrorLevel.RAISE.\nDefault: 3</li>\n</ul>\n", "bases": "sqlglot.parser.Parser"}, "sqlglot.dialects.drill.Drill.Parser.STRICT_CAST": {"fullname": "sqlglot.dialects.drill.Drill.Parser.STRICT_CAST", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.Parser.STRICT_CAST", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.drill.Drill.Parser.FUNCTIONS": {"fullname": "sqlglot.dialects.drill.Drill.Parser.FUNCTIONS", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.Parser.FUNCTIONS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ABS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Abs'>>, 'ADD_MONTHS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AddMonths'>>, 'ANONYMOUS_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnonymousAggFunc'>>, 'ANY_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnyValue'>>, 'APPROX_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_COUNT_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'APPROX_TOP_K': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxTopK'>>, 'ARG_MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARGMAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'MAX_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARG_MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARGMIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'MIN_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Array'>>, 'ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAgg'>>, 'ARRAY_ALL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAll'>>, 'ARRAY_ANY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAny'>>, 'ARRAY_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CONSTRUCT_COMPACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConstructCompact'>>, 'ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayContains'>>, 'FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_OVERLAPS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayOverlaps'>>, 'ARRAY_SIZE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_SORT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySort'>>, 'ARRAY_SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySum'>>, 'ARRAY_TO_STRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_JOIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_UNION_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUnionAgg'>>, 'ARRAY_UNIQUE_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUniqueAgg'>>, 'AVG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Avg'>>, 'CASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Case'>>, 'CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cast'>>, 'CAST_TO_STR_TYPE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CastToStrType'>>, 'CBRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cbrt'>>, 'CEIL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CEILING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CHR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'COALESCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'IFNULL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'NVL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'COLLATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Collate'>>, 'COMBINED_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedAggFunc'>>, 'COMBINED_PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedParameterizedAgg'>>, 'CONCAT': <function Parser.<lambda>>, 'CONCAT_WS': <function Parser.<lambda>>, 'CONNECT_BY_ROOT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ConnectByRoot'>>, 'CONVERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Convert'>>, 'CORR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Corr'>>, 'COUNT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Count'>>, 'COUNT_IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COUNTIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COVAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarPop'>>, 'COVAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarSamp'>>, 'CURRENT_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDate'>>, 'CURRENT_DATETIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDatetime'>>, 'CURRENT_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTime'>>, 'CURRENT_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTimestamp'>>, 'CURRENT_USER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentUser'>>, 'DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Date'>>, 'DATE_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateAdd'>>, 'DATEDIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateDiff'>>, 'DATE_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateDiff'>>, 'DATE_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATE_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateStrToDate'>>, 'DATE_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateSub'>>, 'DATE_TO_DATE_STR': <function Parser.<lambda>>, 'DATE_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateToDi'>>, 'DATE_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateTrunc'>>, 'DATETIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeAdd'>>, 'DATETIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeDiff'>>, 'DATETIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeSub'>>, 'DATETIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeTrunc'>>, 'DAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Day'>>, 'DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAYOFMONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAY_OF_WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAYOFWEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAY_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DAYOFYEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DECODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Decode'>>, 'DI_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DiToDate'>>, 'ENCODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Encode'>>, 'EXP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Exp'>>, 'EXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Explode'>>, 'EXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ExplodeOuter'>>, 'EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Extract'>>, 'FIRST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.First'>>, 'FIRST_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FirstValue'>>, 'FLATTEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Flatten'>>, 'FLOOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Floor'>>, 'FROM_BASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase'>>, 'FROM_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase64'>>, 'GENERATE_DATE_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GenerateDateArray'>>, 'GENERATE_SERIES': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GenerateSeries'>>, 'GREATEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Greatest'>>, 'GROUP_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GroupConcat'>>, 'HEX': <function build_hex>, 'HLL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Hll'>>, 'IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'IIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'INITCAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Initcap'>>, 'IS_INF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'ISINF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'IS_NAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'ISNAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'J_S_O_N_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArray'>>, 'J_S_O_N_ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArrayAgg'>>, 'JSON_ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArrayContains'>>, 'JSONB_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONBExtract'>>, 'JSONB_EXTRACT_SCALAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONBExtractScalar'>>, 'JSON_EXTRACT': <function build_extract_json_with_path.<locals>._builder>, 'JSON_EXTRACT_SCALAR': <function build_extract_json_with_path.<locals>._builder>, 'JSON_FORMAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONFormat'>>, 'J_S_O_N_OBJECT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONObject'>>, 'J_S_O_N_OBJECT_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONObjectAgg'>>, 'J_S_O_N_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONTable'>>, 'LAG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lag'>>, 'LAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Last'>>, 'LAST_DAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastDay'>>, 'LAST_DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastDay'>>, 'LAST_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastValue'>>, 'LEAD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lead'>>, 'LEAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Least'>>, 'LEFT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Left'>>, 'LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Length'>>, 'LEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Length'>>, 'LEVENSHTEIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Levenshtein'>>, 'LN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ln'>>, 'LOG': <function build_logarithm>, 'LOGICAL_AND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'BOOL_AND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'BOOLAND_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'LOGICAL_OR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'BOOL_OR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'BOOLOR_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'LOWER': <function build_lower>, 'LCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lower'>>, 'LOWER_HEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LowerHex'>>, 'MD5': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MD5'>>, 'MD5_DIGEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MD5Digest'>>, 'MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Map'>>, 'MAP_FROM_ENTRIES': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MapFromEntries'>>, 'MATCH_AGAINST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MatchAgainst'>>, 'MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Max'>>, 'MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Min'>>, 'MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Month'>>, 'MONTHS_BETWEEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MonthsBetween'>>, 'NEXT_VALUE_FOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NextValueFor'>>, 'NTH_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NthValue'>>, 'NULLIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Nullif'>>, 'NUMBER_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NumberToStr'>>, 'NVL2': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Nvl2'>>, 'OPEN_J_S_O_N': <bound method Func.from_arg_list of <class 'sqlglot.expressions.OpenJSON'>>, 'PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParameterizedAgg'>>, 'PARSE_JSON': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParseJSON'>>, 'JSON_PARSE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParseJSON'>>, 'PERCENTILE_CONT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PercentileCont'>>, 'PERCENTILE_DISC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PercentileDisc'>>, 'POSEXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Posexplode'>>, 'POSEXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PosexplodeOuter'>>, 'POWER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Pow'>>, 'POW': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Pow'>>, 'PREDICT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Predict'>>, 'QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quantile'>>, 'QUARTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quarter'>>, 'RAND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'RANDOM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'RANDN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Randn'>>, 'RANGE_N': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RangeN'>>, 'READ_CSV': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ReadCSV'>>, 'REDUCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Reduce'>>, 'REGEXP_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpExtract'>>, 'REGEXP_I_LIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpILike'>>, 'REGEXP_LIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpLike'>>, 'REGEXP_REPLACE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpReplace'>>, 'REGEXP_SPLIT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpSplit'>>, 'REPEAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Repeat'>>, 'RIGHT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Right'>>, 'ROUND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Round'>>, 'ROW_NUMBER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RowNumber'>>, 'SHA': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA'>>, 'SHA1': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA'>>, 'SHA2': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA2'>>, 'SAFE_DIVIDE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SafeDivide'>>, 'SIGN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sign'>>, 'SIGNUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sign'>>, 'SORT_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SortArray'>>, 'SPLIT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Split'>>, 'SQRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sqrt'>>, 'STANDARD_HASH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StandardHash'>>, 'STAR_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StarMap'>>, 'STARTS_WITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STARTSWITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STDDEV': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stddev'>>, 'STDDEV_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StddevPop'>>, 'STDDEV_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StddevSamp'>>, 'STR_POSITION': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrPosition'>>, 'STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToDate'>>, 'STR_TO_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToMap'>>, 'STR_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToTime'>>, 'STR_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToUnix'>>, 'STRUCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Struct'>>, 'STRUCT_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StructExtract'>>, 'STUFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stuff'>>, 'INSERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stuff'>>, 'SUBSTRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Substring'>>, 'SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sum'>>, 'TIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeAdd'>>, 'TIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeDiff'>>, 'TIME_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'TIMEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'TIME_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToDate'>>, 'TIME_STR_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToTime'>>, 'TIME_STR_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToUnix'>>, 'TIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeSub'>>, 'TIME_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeToStr'>>, 'TIME_TO_TIME_STR': <function Parser.<lambda>>, 'TIME_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeToUnix'>>, 'TIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeTrunc'>>, 'TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Timestamp'>>, 'TIMESTAMP_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampAdd'>>, 'TIMESTAMPDIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampDiff'>>, 'TIMESTAMP_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampDiff'>>, 'TIMESTAMP_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampFromParts'>>, 'TIMESTAMPFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampFromParts'>>, 'TIMESTAMP_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampSub'>>, 'TIMESTAMP_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampTrunc'>>, 'TO_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToArray'>>, 'TO_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToBase64'>>, 'TO_CHAR': <function build_formatted_time.<locals>._builder>, 'TO_DAYS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToDays'>>, 'TO_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToMap'>>, 'TO_NUMBER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToNumber'>>, 'TRANSFORM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Transform'>>, 'TRIM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Trim'>>, 'TRY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Try'>>, 'TRY_CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TryCast'>>, 'TS_OR_DI_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDiToDi'>>, 'TS_OR_DS_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsAdd'>>, 'TS_OR_DS_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsDiff'>>, 'TS_OR_DS_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToDate'>>, 'TS_OR_DS_TO_DATE_STR': <function Parser.<lambda>>, 'TS_OR_DS_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTime'>>, 'TS_OR_DS_TO_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTimestamp'>>, 'UNHEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Unhex'>>, 'UNIX_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixDate'>>, 'UNIX_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToStr'>>, 'UNIX_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTime'>>, 'UNIX_TO_TIME_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTimeStr'>>, 'UPPER': <function build_upper>, 'UCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Upper'>>, 'VAR_MAP': <function build_var_map>, 'VARIANCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'VAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Week'>>, 'WEEK_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.WeekOfYear'>>, 'WEEKOFYEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.WeekOfYear'>>, 'WHEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.When'>>, 'X_M_L_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.XMLTable'>>, 'XOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Xor'>>, 'YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Year'>>, 'GLOB': <function Parser.<lambda>>, 'JSON_EXTRACT_PATH_TEXT': <function build_extract_json_with_path.<locals>._builder>, 'LIKE': <function build_like>, 'LOG2': <function Parser.<lambda>>, 'LOG10': <function Parser.<lambda>>, 'MOD': <function build_mod>, 'TO_HEX': <function build_hex>, 'TO_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToTime'>>}"}, "sqlglot.dialects.drill.Drill.Parser.LOG_DEFAULTS_TO_LN": {"fullname": "sqlglot.dialects.drill.Drill.Parser.LOG_DEFAULTS_TO_LN", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.Parser.LOG_DEFAULTS_TO_LN", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.drill.Drill.Parser.TABLE_ALIAS_TOKENS": {"fullname": "sqlglot.dialects.drill.Drill.Parser.TABLE_ALIAS_TOKENS", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.Parser.TABLE_ALIAS_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.KILL: 'KILL'>, <TokenType.MONEY: 'MONEY'>, <TokenType.COPY: 'COPY'>, <TokenType.PERCENT: 'PERCENT'>, <TokenType.TAG: 'TAG'>, <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, <TokenType.VOLATILE: 'VOLATILE'>, <TokenType.IDENTIFIER: 'IDENTIFIER'>, <TokenType.VARBINARY: 'VARBINARY'>, <TokenType.HSTORE: 'HSTORE'>, <TokenType.ASC: 'ASC'>, <TokenType.IPADDRESS: 'IPADDRESS'>, <TokenType.ISNULL: 'ISNULL'>, <TokenType.TEMPORARY: 'TEMPORARY'>, <TokenType.PROCEDURE: 'PROCEDURE'>, <TokenType.SCHEMA: 'SCHEMA'>, <TokenType.NUMRANGE: 'NUMRANGE'>, <TokenType.DATE32: 'DATE32'>, <TokenType.INT8RANGE: 'INT8RANGE'>, <TokenType.ANTI: 'ANTI'>, <TokenType.AGGREGATEFUNCTION: 'AGGREGATEFUNCTION'>, <TokenType.VIEW: 'VIEW'>, <TokenType.VARCHAR: 'VARCHAR'>, <TokenType.TIMETZ: 'TIMETZ'>, <TokenType.GEOMETRY: 'GEOMETRY'>, <TokenType.BEGIN: 'BEGIN'>, <TokenType.ENUM8: 'ENUM8'>, <TokenType.INDEX: 'INDEX'>, <TokenType.PARTITION: 'PARTITION'>, <TokenType.UINT256: 'UINT256'>, <TokenType.BIGINT: 'BIGINT'>, <TokenType.CACHE: 'CACHE'>, <TokenType.OPERATOR: 'OPERATOR'>, <TokenType.COLUMN: 'COLUMN'>, <TokenType.INT128: 'INT128'>, <TokenType.SMALLMONEY: 'SMALLMONEY'>, <TokenType.HLLSKETCH: 'HLLSKETCH'>, <TokenType.UNPIVOT: 'UNPIVOT'>, <TokenType.SMALLINT: 'SMALLINT'>, <TokenType.INT256: 'INT256'>, <TokenType.FLOAT: 'FLOAT'>, <TokenType.COMMIT: 'COMMIT'>, <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, <TokenType.EXISTS: 'EXISTS'>, <TokenType.NULL: 'NULL'>, <TokenType.RECURSIVE: 'RECURSIVE'>, <TokenType.SET: 'SET'>, <TokenType.NULLABLE: 'NULLABLE'>, <TokenType.REFRESH: 'REFRESH'>, <TokenType.TINYTEXT: 'TINYTEXT'>, <TokenType.SHOW: 'SHOW'>, <TokenType.DEFAULT: 'DEFAULT'>, <TokenType.DATE: 'DATE'>, <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <TokenType.MERGE: 'MERGE'>, <TokenType.FIRST: 'FIRST'>, <TokenType.BINARY: 'BINARY'>, <TokenType.ARRAY: 'ARRAY'>, <TokenType.SERIAL: 'SERIAL'>, <TokenType.EXECUTE: 'EXECUTE'>, <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, <TokenType.INTERVAL: 'INTERVAL'>, <TokenType.PRAGMA: 'PRAGMA'>, <TokenType.STORAGE_INTEGRATION: 'STORAGE_INTEGRATION'>, <TokenType.BPCHAR: 'BPCHAR'>, <TokenType.BIT: 'BIT'>, <TokenType.UINT: 'UINT'>, <TokenType.UUID: 'UUID'>, <TokenType.STRUCT: 'STRUCT'>, <TokenType.FALSE: 'FALSE'>, <TokenType.FUNCTION: 'FUNCTION'>, <TokenType.TOP: 'TOP'>, <TokenType.SUPER: 'SUPER'>, <TokenType.CASE: 'CASE'>, <TokenType.IMAGE: 'IMAGE'>, <TokenType.UBIGINT: 'UBIGINT'>, <TokenType.LONGBLOB: 'LONGBLOB'>, <TokenType.ROLLUP: 'ROLLUP'>, <TokenType.VAR: 'VAR'>, <TokenType.COMMAND: 'COMMAND'>, <TokenType.LOAD: 'LOAD'>, <TokenType.TRUNCATE: 'TRUNCATE'>, <TokenType.KEEP: 'KEEP'>, <TokenType.UMEDIUMINT: 'UMEDIUMINT'>, <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, <TokenType.UINT128: 'UINT128'>, <TokenType.END: 'END'>, <TokenType.MAP: 'MAP'>, <TokenType.IPV4: 'IPV4'>, <TokenType.USERDEFINED: 'USERDEFINED'>, <TokenType.REFERENCES: 'REFERENCES'>, <TokenType.REPLACE: 'REPLACE'>, <TokenType.RANGE: 'RANGE'>, <TokenType.NVARCHAR: 'NVARCHAR'>, <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, <TokenType.TRUE: 'TRUE'>, <TokenType.TIMESTAMP_MS: 'TIMESTAMP_MS'>, <TokenType.VARIANT: 'VARIANT'>, <TokenType.ENUM: 'ENUM'>, <TokenType.USE: 'USE'>, <TokenType.USMALLINT: 'USMALLINT'>, <TokenType.OVERLAPS: 'OVERLAPS'>, <TokenType.TIMESTAMP_S: 'TIMESTAMP_S'>, <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, <TokenType.UNIQUE: 'UNIQUE'>, <TokenType.ORDINALITY: 'ORDINALITY'>, <TokenType.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>, <TokenType.TEXT: 'TEXT'>, <TokenType.DATABASE: 'DATABASE'>, <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, <TokenType.PSEUDO_TYPE: 'PSEUDO_TYPE'>, <TokenType.FIXEDSTRING: 'FIXEDSTRING'>, <TokenType.NEXT: 'NEXT'>, <TokenType.INT: 'INT'>, <TokenType.BIGSERIAL: 'BIGSERIAL'>, <TokenType.BOOLEAN: 'BOOLEAN'>, <TokenType.IS: 'IS'>, <TokenType.CONSTRAINT: 'CONSTRAINT'>, <TokenType.FINAL: 'FINAL'>, <TokenType.UNKNOWN: 'UNKNOWN'>, <TokenType.SETTINGS: 'SETTINGS'>, <TokenType.ROWS: 'ROWS'>, <TokenType.TSTZRANGE: 'TSTZRANGE'>, <TokenType.DATETIME64: 'DATETIME64'>, <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, <TokenType.DATETIME: 'DATETIME'>, <TokenType.MEDIUMINT: 'MEDIUMINT'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>, <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, <TokenType.XML: 'XML'>, <TokenType.JSON: 'JSON'>, <TokenType.UTINYINT: 'UTINYINT'>, <TokenType.DELETE: 'DELETE'>, <TokenType.TIME: 'TIME'>, <TokenType.UDECIMAL: 'UDECIMAL'>, <TokenType.NESTED: 'NESTED'>, <TokenType.SEMI: 'SEMI'>, <TokenType.DESC: 'DESC'>, <TokenType.ROWVERSION: 'ROWVERSION'>, <TokenType.TIMESTAMP_NS: 'TIMESTAMP_NS'>, <TokenType.ANY: 'ANY'>, <TokenType.DIV: 'DIV'>, <TokenType.DICTIONARY: 'DICTIONARY'>, <TokenType.INET: 'INET'>, <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, <TokenType.COMMENT: 'COMMENT'>, <TokenType.CURRENT_USER: 'CURRENT_USER'>, <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>, <TokenType.ALL: 'ALL'>, <TokenType.NAME: 'NAME'>, <TokenType.SOME: 'SOME'>, <TokenType.ENUM16: 'ENUM16'>, <TokenType.YEAR: 'YEAR'>, <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, <TokenType.DOUBLE: 'DOUBLE'>, <TokenType.INT4RANGE: 'INT4RANGE'>, <TokenType.FORMAT: 'FORMAT'>, <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, <TokenType.IPPREFIX: 'IPPREFIX'>, <TokenType.OVERWRITE: 'OVERWRITE'>, <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>, <TokenType.COLLATE: 'COLLATE'>, <TokenType.FILTER: 'FILTER'>, <TokenType.JSONB: 'JSONB'>, <TokenType.TDIGEST: 'TDIGEST'>, <TokenType.CHAR: 'CHAR'>, <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.ROW: 'ROW'>, <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.TABLE: 'TABLE'>, <TokenType.DATERANGE: 'DATERANGE'>, <TokenType.TSRANGE: 'TSRANGE'>, <TokenType.ESCAPE: 'ESCAPE'>, <TokenType.PIVOT: 'PIVOT'>, <TokenType.DECIMAL: 'DECIMAL'>, <TokenType.NCHAR: 'NCHAR'>, <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, <TokenType.UPDATE: 'UPDATE'>, <TokenType.MODEL: 'MODEL'>, <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, <TokenType.SEQUENCE: 'SEQUENCE'>, <TokenType.LONGTEXT: 'LONGTEXT'>, <TokenType.DESCRIBE: 'DESCRIBE'>, <TokenType.IPV6: 'IPV6'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, <TokenType.TINYINT: 'TINYINT'>, <TokenType.TINYBLOB: 'TINYBLOB'>}"}, "sqlglot.dialects.drill.Drill.Parser.SHOW_TRIE": {"fullname": "sqlglot.dialects.drill.Drill.Parser.SHOW_TRIE", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.Parser.SHOW_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.drill.Drill.Parser.SET_TRIE": {"fullname": "sqlglot.dialects.drill.Drill.Parser.SET_TRIE", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.Parser.SET_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'GLOBAL': {0: True}, 'LOCAL': {0: True}, 'SESSION': {0: True}, 'TRANSACTION': {0: True}}"}, "sqlglot.dialects.drill.Drill.Generator": {"fullname": "sqlglot.dialects.drill.Drill.Generator", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.Generator", "kind": "class", "doc": "<p>Generator converts a given syntax tree to the corresponding SQL string.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>pretty:</strong> Whether to format the produced SQL string.\nDefault: False.</li>\n<li><strong>identify:</strong> Determines when an identifier should be quoted. Possible values are:\nFalse (default): Never quote, except in cases where it's mandatory by the dialect.\nTrue or 'always': Always quote.\n'safe': Only quote identifiers that are case insensitive.</li>\n<li><strong>normalize:</strong> Whether to normalize identifiers to lowercase.\nDefault: False.</li>\n<li><strong>pad:</strong> The pad size in a formatted string. For example, this affects the indentation of\na projection in a query, relative to its nesting level.\nDefault: 2.</li>\n<li><strong>indent:</strong> The indentation size in a formatted string. For example, this affects the\nindentation of subqueries and filters under a <code>WHERE</code> clause.\nDefault: 2.</li>\n<li><strong>normalize_functions:</strong> How to normalize function names. Possible values are:\n\"upper\" or True (default): Convert names to uppercase.\n\"lower\": Convert names to lowercase.\nFalse: Disables function name normalization.</li>\n<li><strong>unsupported_level:</strong> Determines the generator's behavior when it encounters unsupported expressions.\nDefault ErrorLevel.WARN.</li>\n<li><strong>max_unsupported:</strong> Maximum number of unsupported messages to include in a raised UnsupportedError.\nThis is only relevant if unsupported_level is ErrorLevel.RAISE.\nDefault: 3</li>\n<li><strong>leading_comma:</strong> Whether the comma is leading or trailing in select expressions.\nThis is only relevant when generating in pretty mode.\nDefault: False</li>\n<li><strong>max_text_width:</strong> The max number of characters in a segment before creating new lines in pretty mode.\nThe default is on the smaller end because the length only represents a segment and not the true\nline length.\nDefault: 80</li>\n<li><strong>comments:</strong> Whether to preserve comments in the output SQL code.\nDefault: True</li>\n</ul>\n", "bases": "sqlglot.generator.Generator"}, "sqlglot.dialects.drill.Drill.Generator.JOIN_HINTS": {"fullname": "sqlglot.dialects.drill.Drill.Generator.JOIN_HINTS", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.Generator.JOIN_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.drill.Drill.Generator.TABLE_HINTS": {"fullname": "sqlglot.dialects.drill.Drill.Generator.TABLE_HINTS", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.Generator.TABLE_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.drill.Drill.Generator.QUERY_HINTS": {"fullname": "sqlglot.dialects.drill.Drill.Generator.QUERY_HINTS", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.Generator.QUERY_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.drill.Drill.Generator.NVL2_SUPPORTED": {"fullname": "sqlglot.dialects.drill.Drill.Generator.NVL2_SUPPORTED", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.Generator.NVL2_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.drill.Drill.Generator.LAST_DAY_SUPPORTS_DATE_PART": {"fullname": "sqlglot.dialects.drill.Drill.Generator.LAST_DAY_SUPPORTS_DATE_PART", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.Generator.LAST_DAY_SUPPORTS_DATE_PART", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.drill.Drill.Generator.SUPPORTS_CREATE_TABLE_LIKE": {"fullname": "sqlglot.dialects.drill.Drill.Generator.SUPPORTS_CREATE_TABLE_LIKE", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.Generator.SUPPORTS_CREATE_TABLE_LIKE", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.drill.Drill.Generator.TYPE_MAPPING": {"fullname": "sqlglot.dialects.drill.Drill.Generator.TYPE_MAPPING", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.Generator.TYPE_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.NCHAR: 'NCHAR'>: 'VARCHAR', <Type.NVARCHAR: 'NVARCHAR'>: 'VARCHAR', <Type.MEDIUMTEXT: 'MEDIUMTEXT'>: 'TEXT', <Type.LONGTEXT: 'LONGTEXT'>: 'TEXT', <Type.TINYTEXT: 'TINYTEXT'>: 'TEXT', <Type.MEDIUMBLOB: 'MEDIUMBLOB'>: 'BLOB', <Type.LONGBLOB: 'LONGBLOB'>: 'BLOB', <Type.TINYBLOB: 'TINYBLOB'>: 'BLOB', <Type.INET: 'INET'>: 'INET', <Type.ROWVERSION: 'ROWVERSION'>: 'VARBINARY', <Type.INT: 'INT'>: 'INTEGER', <Type.SMALLINT: 'SMALLINT'>: 'INTEGER', <Type.TINYINT: 'TINYINT'>: 'INTEGER', <Type.BINARY: 'BINARY'>: 'VARBINARY', <Type.TEXT: 'TEXT'>: 'VARCHAR', <Type.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>: 'TIMESTAMP', <Type.TIMESTAMPTZ: 'TIMESTAMPTZ'>: 'TIMESTAMP', <Type.DATETIME: 'DATETIME'>: 'TIMESTAMP'}"}, "sqlglot.dialects.drill.Drill.Generator.PROPERTIES_LOCATION": {"fullname": "sqlglot.dialects.drill.Drill.Generator.PROPERTIES_LOCATION", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.Generator.PROPERTIES_LOCATION", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.AllowedValuesProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.AlgorithmProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.AutoIncrementProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.BackupProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.BlockCompressionProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.CharacterSetProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ChecksumProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.CollateProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Cluster'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ClusteredByProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DataBlocksizeProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.DataDeletionProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DefinerProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.DictRange'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DictProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DistKeyProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DistStyleProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.EngineProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ExternalProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.FallbackProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.FileFormatProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.FreespaceProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.GlobalProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.HeapProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.InheritsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.IcebergProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.InputModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.IsolatedLoadingProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.JournalProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.LanguageProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LikeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LocationProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LockProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LockingProperty'>: <Location.POST_ALIAS: 'POST_ALIAS'>, <class 'sqlglot.expressions.LogProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.MaterializedProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.MergeBlockRatioProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.OnProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.OnCommitProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.Order'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.OutputModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.PartitionedByProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.PartitionedOfProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.PrimaryKey'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Property'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ReturnsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatDelimitedProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatSerdeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SampleProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SchemaCommentProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SerdeProperties'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Set'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SettingsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SetProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.SetConfigProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SharingProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.SequenceProperties'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.SortKeyProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SqlReadWriteProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SqlSecurityProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.StabilityProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.StrictProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.TemporaryProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.ToTableProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.TransientProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.TransformModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.MergeTreeTTL'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.UnloggedProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.VolatileProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.WithDataProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.WithSystemVersioningProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>}"}, "sqlglot.dialects.drill.Drill.Generator.TRANSFORMS": {"fullname": "sqlglot.dialects.drill.Drill.Generator.TRANSFORMS", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.Generator.TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.JSONPathFilter'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathKey'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRecursive'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRoot'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathScript'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSelector'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSlice'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSubscript'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathUnion'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathWildcard'>: <function <lambda>>, <class 'sqlglot.expressions.AllowedValuesProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.BackupProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CaseSpecificColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CollateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CommentColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DateFormatColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DefaultColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EncodeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EphemeralColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExcludeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExternalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.GlobalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.HeapProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IcebergProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InheritsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InlineLengthColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IntervalSpan'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtract'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtractScalar'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LanguageProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LocationProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LogProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.MaterializedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NonClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NotForReplicationColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnCommitProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnUpdateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OutputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.PathColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ReturnsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SampleProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetConfigProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SettingsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SharingProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlReadWriteProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlSecurityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StabilityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StrictProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TemporaryProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TitleColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.Timestamp'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransformModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransientProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UppercaseColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UnloggedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VarMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VolatileProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithOperator'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CurrentTimestamp'>: <function Drill.Generator.<lambda>>, <class 'sqlglot.expressions.ArrayContains'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ArraySize'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.Create'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.DateAdd'>: <function date_add_sql.<locals>.func>, <class 'sqlglot.expressions.DateStrToDate'>: <function datestrtodate_sql>, <class 'sqlglot.expressions.DateSub'>: <function date_add_sql.<locals>.func>, <class 'sqlglot.expressions.DateToDi'>: <function Drill.Generator.<lambda>>, <class 'sqlglot.expressions.DiToDate'>: <function Drill.Generator.<lambda>>, <class 'sqlglot.expressions.If'>: <function Drill.Generator.<lambda>>, <class 'sqlglot.expressions.ILike'>: <function Drill.Generator.<lambda>>, <class 'sqlglot.expressions.Levenshtein'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.PartitionedByProperty'>: <function Drill.Generator.<lambda>>, <class 'sqlglot.expressions.RegexpLike'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.StrPosition'>: <function str_position_sql>, <class 'sqlglot.expressions.StrToDate'>: <function _str_to_date>, <class 'sqlglot.expressions.Pow'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.Select'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.StrToTime'>: <function Drill.Generator.<lambda>>, <class 'sqlglot.expressions.TimeStrToDate'>: <function Drill.Generator.<lambda>>, <class 'sqlglot.expressions.TimeStrToTime'>: <function timestrtotime_sql>, <class 'sqlglot.expressions.TimeStrToUnix'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.TimeToStr'>: <function Drill.Generator.<lambda>>, <class 'sqlglot.expressions.TimeToUnix'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ToChar'>: <function Drill.Generator.<lambda>>, <class 'sqlglot.expressions.TryCast'>: <function no_trycast_sql>, <class 'sqlglot.expressions.TsOrDsAdd'>: <function Drill.Generator.<lambda>>, <class 'sqlglot.expressions.TsOrDiToDi'>: <function Drill.Generator.<lambda>>}"}, "sqlglot.dialects.drill.Drill.Generator.SELECT_KINDS": {"fullname": "sqlglot.dialects.drill.Drill.Generator.SELECT_KINDS", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.Generator.SELECT_KINDS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Tuple[str, ...]", "default_value": "()"}, "sqlglot.dialects.drill.Drill.Generator.TRY_SUPPORTED": {"fullname": "sqlglot.dialects.drill.Drill.Generator.TRY_SUPPORTED", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.Generator.TRY_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.drill.Drill.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS": {"fullname": "sqlglot.dialects.drill.Drill.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'qualify': <function Generator.<lambda>>, 'windows': <function Generator.<lambda>>}"}, "sqlglot.dialects.drill.Drill.UNESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.drill.Drill.UNESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.UNESCAPED_SEQUENCES", "kind": "variable", "doc": "<p>Mapping of an escaped sequence (<code>\\n</code>) to its unescaped version (<code>\n</code>).</p>\n", "annotation": ": Dict[str, str]", "default_value": "{'\\\\a': '\\x07', '\\\\b': '\\x08', '\\\\f': '\\x0c', '\\\\n': '\\n', '\\\\r': '\\r', '\\\\t': '\\t', '\\\\v': '\\x0b', '\\\\\\\\': '\\\\'}"}, "sqlglot.dialects.drill.Drill.tokenizer_class": {"fullname": "sqlglot.dialects.drill.Drill.tokenizer_class", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.tokenizer_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.drill.Drill.Tokenizer'>"}, "sqlglot.dialects.drill.Drill.parser_class": {"fullname": "sqlglot.dialects.drill.Drill.parser_class", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.parser_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.drill.Drill.Parser'>"}, "sqlglot.dialects.drill.Drill.generator_class": {"fullname": "sqlglot.dialects.drill.Drill.generator_class", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.generator_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.drill.Drill.Generator'>"}, "sqlglot.dialects.drill.Drill.TIME_TRIE": {"fullname": "sqlglot.dialects.drill.Drill.TIME_TRIE", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'y': {0: True, 'y': {'y': {'y': {0: True}}, 0: True}}, 'Y': {0: True, 'Y': {'Y': {'Y': {0: True}}, 0: True}}, 'M': {'M': {'M': {'M': {0: True}, 0: True}, 0: True}, 0: True}, 'd': {'d': {0: True}, 0: True}, 'H': {'H': {0: True}, 0: True}, 'h': {'h': {0: True}, 0: True}, 'm': {'m': {0: True}, 0: True}, 's': {'s': {0: True}, 0: True}, 'S': {'S': {'S': {'S': {'S': {'S': {0: True}}}}}}, 'a': {0: True}, 'D': {'D': {0: True}, 0: True}, 'E': {0: True, 'E': {0: True, 'E': {0: True, 'E': {0: True}}}}, "'": {"'": {'T': {"'": {"'": {0: True}}}}}}"}, "sqlglot.dialects.drill.Drill.FORMAT_TRIE": {"fullname": "sqlglot.dialects.drill.Drill.FORMAT_TRIE", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.FORMAT_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'y': {0: True, 'y': {'y': {'y': {0: True}}, 0: True}}, 'Y': {0: True, 'Y': {'Y': {'Y': {0: True}}, 0: True}}, 'M': {'M': {'M': {'M': {0: True}, 0: True}, 0: True}, 0: True}, 'd': {'d': {0: True}, 0: True}, 'H': {'H': {0: True}, 0: True}, 'h': {'h': {0: True}, 0: True}, 'm': {'m': {0: True}, 0: True}, 's': {'s': {0: True}, 0: True}, 'S': {'S': {'S': {'S': {'S': {'S': {0: True}}}}}}, 'a': {0: True}, 'D': {'D': {0: True}, 0: True}, 'E': {0: True, 'E': {0: True, 'E': {0: True, 'E': {0: True}}}}, "'": {"'": {'T': {"'": {"'": {0: True}}}}}}"}, "sqlglot.dialects.drill.Drill.INVERSE_TIME_MAPPING": {"fullname": "sqlglot.dialects.drill.Drill.INVERSE_TIME_MAPPING", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.INVERSE_TIME_MAPPING", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'%Y': 'yyyy', '%y': 'yy', '%B': 'MMMM', '%b': 'MMM', '%m': 'MM', '%-m': 'M', '%d': 'dd', '%-d': 'd', '%H': 'HH', '%-H': 'H', '%I': 'hh', '%-I': 'h', '%M': 'mm', '%-M': 'm', '%S': 'ss', '%-S': 's', '%f': 'SSSSSS', '%p': 'a', '%j': 'DD', '%-j': 'D', '%a': 'EEE', '%A': 'EEEE', 'T': "''T''"}"}, "sqlglot.dialects.drill.Drill.INVERSE_TIME_TRIE": {"fullname": "sqlglot.dialects.drill.Drill.INVERSE_TIME_TRIE", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.INVERSE_TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'%': {'Y': {0: True}, 'y': {0: True}, 'B': {0: True}, 'b': {0: True}, 'm': {0: True}, '-': {'m': {0: True}, 'd': {0: True}, 'H': {0: True}, 'I': {0: True}, 'M': {0: True}, 'S': {0: True}, 'j': {0: True}}, 'd': {0: True}, 'H': {0: True}, 'I': {0: True}, 'M': {0: True}, 'S': {0: True}, 'f': {0: True}, 'p': {0: True}, 'j': {0: True}, 'a': {0: True}, 'A': {0: True}}, 'T': {0: True}}"}, "sqlglot.dialects.drill.Drill.ESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.drill.Drill.ESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.ESCAPED_SEQUENCES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'\\x07': '\\\\a', '\\x08': '\\\\b', '\\x0c': '\\\\f', '\\n': '\\\\n', '\\r': '\\\\r', '\\t': '\\\\t', '\\x0b': '\\\\v', '\\\\': '\\\\\\\\'}"}, "sqlglot.dialects.drill.Drill.QUOTE_START": {"fullname": "sqlglot.dialects.drill.Drill.QUOTE_START", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.QUOTE_START", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.drill.Drill.QUOTE_END": {"fullname": "sqlglot.dialects.drill.Drill.QUOTE_END", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.QUOTE_END", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.drill.Drill.IDENTIFIER_START": {"fullname": "sqlglot.dialects.drill.Drill.IDENTIFIER_START", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.IDENTIFIER_START", "kind": "variable", "doc": "<p></p>\n", "default_value": "'`'"}, "sqlglot.dialects.drill.Drill.IDENTIFIER_END": {"fullname": "sqlglot.dialects.drill.Drill.IDENTIFIER_END", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.IDENTIFIER_END", "kind": "variable", "doc": "<p></p>\n", "default_value": "'`'"}, "sqlglot.dialects.drill.Drill.BIT_START": {"fullname": "sqlglot.dialects.drill.Drill.BIT_START", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.BIT_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.drill.Drill.BIT_END": {"fullname": "sqlglot.dialects.drill.Drill.BIT_END", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.BIT_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.drill.Drill.HEX_START": {"fullname": "sqlglot.dialects.drill.Drill.HEX_START", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.HEX_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.drill.Drill.HEX_END": {"fullname": "sqlglot.dialects.drill.Drill.HEX_END", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.HEX_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.drill.Drill.BYTE_START": {"fullname": "sqlglot.dialects.drill.Drill.BYTE_START", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.BYTE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.drill.Drill.BYTE_END": {"fullname": "sqlglot.dialects.drill.Drill.BYTE_END", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.BYTE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.drill.Drill.UNICODE_START": {"fullname": "sqlglot.dialects.drill.Drill.UNICODE_START", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.UNICODE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.drill.Drill.UNICODE_END": {"fullname": "sqlglot.dialects.drill.Drill.UNICODE_END", "modulename": "sqlglot.dialects.drill", "qualname": "Drill.UNICODE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.duckdb": {"fullname": "sqlglot.dialects.duckdb", "modulename": "sqlglot.dialects.duckdb", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.dialects.duckdb.DuckDB": {"fullname": "sqlglot.dialects.duckdb.DuckDB", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.dialect.Dialect"}, "sqlglot.dialects.duckdb.DuckDB.NULL_ORDERING": {"fullname": "sqlglot.dialects.duckdb.DuckDB.NULL_ORDERING", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.NULL_ORDERING", "kind": "variable", "doc": "<p>Default <code>NULL</code> ordering method to use if not explicitly set.\nPossible values: <code>\"nulls_are_small\"</code>, <code>\"nulls_are_large\"</code>, <code>\"nulls_are_last\"</code></p>\n", "default_value": "'nulls_are_last'"}, "sqlglot.dialects.duckdb.DuckDB.SUPPORTS_USER_DEFINED_TYPES": {"fullname": "sqlglot.dialects.duckdb.DuckDB.SUPPORTS_USER_DEFINED_TYPES", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.SUPPORTS_USER_DEFINED_TYPES", "kind": "variable", "doc": "<p>Whether user-defined data types are supported.</p>\n", "default_value": "False"}, "sqlglot.dialects.duckdb.DuckDB.SAFE_DIVISION": {"fullname": "sqlglot.dialects.duckdb.DuckDB.SAFE_DIVISION", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.SAFE_DIVISION", "kind": "variable", "doc": "<p>Whether division by zero throws an error (<code>False</code>) or returns NULL (<code>True</code>).</p>\n", "default_value": "True"}, "sqlglot.dialects.duckdb.DuckDB.INDEX_OFFSET": {"fullname": "sqlglot.dialects.duckdb.DuckDB.INDEX_OFFSET", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.INDEX_OFFSET", "kind": "variable", "doc": "<p>The base index offset for arrays.</p>\n", "default_value": "1"}, "sqlglot.dialects.duckdb.DuckDB.CONCAT_COALESCE": {"fullname": "sqlglot.dialects.duckdb.DuckDB.CONCAT_COALESCE", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.CONCAT_COALESCE", "kind": "variable", "doc": "<p>A <code>NULL</code> arg in <code>CONCAT</code> yields <code>NULL</code> by default, but in some dialects it yields an empty string.</p>\n", "default_value": "True"}, "sqlglot.dialects.duckdb.DuckDB.NORMALIZATION_STRATEGY": {"fullname": "sqlglot.dialects.duckdb.DuckDB.NORMALIZATION_STRATEGY", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.NORMALIZATION_STRATEGY", "kind": "variable", "doc": "<p>Specifies the strategy according to which identifiers should be normalized.</p>\n", "default_value": "<NormalizationStrategy.CASE_INSENSITIVE: 'CASE_INSENSITIVE'>"}, "sqlglot.dialects.duckdb.DuckDB.to_json_path": {"fullname": "sqlglot.dialects.duckdb.DuckDB.to_json_path", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.to_json_path", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">path</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.duckdb.DuckDB.Tokenizer": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Tokenizer", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Tokenizer", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.tokens.Tokenizer"}, "sqlglot.dialects.duckdb.DuckDB.Tokenizer.HEREDOC_STRINGS": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Tokenizer.HEREDOC_STRINGS", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Tokenizer.HEREDOC_STRINGS", "kind": "variable", "doc": "<p></p>\n", "default_value": "['$']"}, "sqlglot.dialects.duckdb.DuckDB.Tokenizer.HEREDOC_TAG_IS_IDENTIFIER": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Tokenizer.HEREDOC_TAG_IS_IDENTIFIER", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Tokenizer.HEREDOC_TAG_IS_IDENTIFIER", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.duckdb.DuckDB.Tokenizer.HEREDOC_STRING_ALTERNATIVE": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Tokenizer.HEREDOC_STRING_ALTERNATIVE", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Tokenizer.HEREDOC_STRING_ALTERNATIVE", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.PARAMETER: 'PARAMETER'>"}, "sqlglot.dialects.duckdb.DuckDB.Tokenizer.KEYWORDS": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Tokenizer.KEYWORDS", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Tokenizer.KEYWORDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'{%': <TokenType.BLOCK_START: 'BLOCK_START'>, '{%+': <TokenType.BLOCK_START: 'BLOCK_START'>, '{%-': <TokenType.BLOCK_START: 'BLOCK_START'>, '%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '+%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '-%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '{{+': <TokenType.BLOCK_START: 'BLOCK_START'>, '{{-': <TokenType.BLOCK_START: 'BLOCK_START'>, '+}}': <TokenType.BLOCK_END: 'BLOCK_END'>, '-}}': <TokenType.BLOCK_END: 'BLOCK_END'>, '/*+': <TokenType.HINT: 'HINT'>, '==': <TokenType.EQ: 'EQ'>, '::': <TokenType.DCOLON: 'DCOLON'>, '||': <TokenType.DPIPE: 'DPIPE'>, '>=': <TokenType.GTE: 'GTE'>, '<=': <TokenType.LTE: 'LTE'>, '<>': <TokenType.NEQ: 'NEQ'>, '!=': <TokenType.NEQ: 'NEQ'>, ':=': <TokenType.COLON_EQ: 'COLON_EQ'>, '<=>': <TokenType.NULLSAFE_EQ: 'NULLSAFE_EQ'>, '->': <TokenType.ARROW: 'ARROW'>, '->>': <TokenType.DARROW: 'DARROW'>, '=>': <TokenType.FARROW: 'FARROW'>, '#>': <TokenType.HASH_ARROW: 'HASH_ARROW'>, '#>>': <TokenType.DHASH_ARROW: 'DHASH_ARROW'>, '<->': <TokenType.LR_ARROW: 'LR_ARROW'>, '&&': <TokenType.DAMP: 'DAMP'>, '??': <TokenType.DQMARK: 'DQMARK'>, 'ALL': <TokenType.ALL: 'ALL'>, 'ALWAYS': <TokenType.ALWAYS: 'ALWAYS'>, 'AND': <TokenType.AND: 'AND'>, 'ANTI': <TokenType.ANTI: 'ANTI'>, 'ANY': <TokenType.ANY: 'ANY'>, 'ASC': <TokenType.ASC: 'ASC'>, 'AS': <TokenType.ALIAS: 'ALIAS'>, 'ASOF': <TokenType.ASOF: 'ASOF'>, 'AUTOINCREMENT': <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, 'AUTO_INCREMENT': <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, 'BEGIN': <TokenType.BEGIN: 'BEGIN'>, 'BETWEEN': <TokenType.BETWEEN: 'BETWEEN'>, 'CACHE': <TokenType.CACHE: 'CACHE'>, 'UNCACHE': <TokenType.UNCACHE: 'UNCACHE'>, 'CASE': <TokenType.CASE: 'CASE'>, 'CHARACTER SET': <TokenType.CHARACTER_SET: 'CHARACTER_SET'>, 'CLUSTER BY': <TokenType.CLUSTER_BY: 'CLUSTER_BY'>, 'COLLATE': <TokenType.COLLATE: 'COLLATE'>, 'COLUMN': <TokenType.COLUMN: 'COLUMN'>, 'COMMIT': <TokenType.COMMIT: 'COMMIT'>, 'CONNECT BY': <TokenType.CONNECT_BY: 'CONNECT_BY'>, 'CONSTRAINT': <TokenType.CONSTRAINT: 'CONSTRAINT'>, 'COPY': <TokenType.COPY: 'COPY'>, 'CREATE': <TokenType.CREATE: 'CREATE'>, 'CROSS': <TokenType.CROSS: 'CROSS'>, 'CUBE': <TokenType.CUBE: 'CUBE'>, 'CURRENT_DATE': <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, 'CURRENT_TIME': <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, 'CURRENT_TIMESTAMP': <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, 'CURRENT_USER': <TokenType.CURRENT_USER: 'CURRENT_USER'>, 'DATABASE': <TokenType.DATABASE: 'DATABASE'>, 'DEFAULT': <TokenType.DEFAULT: 'DEFAULT'>, 'DELETE': <TokenType.DELETE: 'DELETE'>, 'DESC': <TokenType.DESC: 'DESC'>, 'DESCRIBE': <TokenType.DESCRIBE: 'DESCRIBE'>, 'DISTINCT': <TokenType.DISTINCT: 'DISTINCT'>, 'DISTRIBUTE BY': <TokenType.DISTRIBUTE_BY: 'DISTRIBUTE_BY'>, 'DIV': <TokenType.DIV: 'DIV'>, 'DROP': <TokenType.DROP: 'DROP'>, 'ELSE': <TokenType.ELSE: 'ELSE'>, 'END': <TokenType.END: 'END'>, 'ENUM': <TokenType.ENUM: 'ENUM'>, 'ESCAPE': <TokenType.ESCAPE: 'ESCAPE'>, 'EXCEPT': <TokenType.EXCEPT: 'EXCEPT'>, 'EXECUTE': <TokenType.EXECUTE: 'EXECUTE'>, 'EXISTS': <TokenType.EXISTS: 'EXISTS'>, 'FALSE': <TokenType.FALSE: 'FALSE'>, 'FETCH': <TokenType.FETCH: 'FETCH'>, 'FILTER': <TokenType.FILTER: 'FILTER'>, 'FIRST': <TokenType.FIRST: 'FIRST'>, 'FULL': <TokenType.FULL: 'FULL'>, 'FUNCTION': <TokenType.FUNCTION: 'FUNCTION'>, 'FOR': <TokenType.FOR: 'FOR'>, 'FOREIGN KEY': <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, 'FORMAT': <TokenType.FORMAT: 'FORMAT'>, 'FROM': <TokenType.FROM: 'FROM'>, 'GEOGRAPHY': <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, 'GEOMETRY': <TokenType.GEOMETRY: 'GEOMETRY'>, 'GLOB': <TokenType.GLOB: 'GLOB'>, 'GROUP BY': <TokenType.GROUP_BY: 'GROUP_BY'>, 'GROUPING SETS': <TokenType.GROUPING_SETS: 'GROUPING_SETS'>, 'HAVING': <TokenType.HAVING: 'HAVING'>, 'ILIKE': <TokenType.ILIKE: 'ILIKE'>, 'IN': <TokenType.IN: 'IN'>, 'INDEX': <TokenType.INDEX: 'INDEX'>, 'INET': <TokenType.INET: 'INET'>, 'INNER': <TokenType.INNER: 'INNER'>, 'INSERT': <TokenType.INSERT: 'INSERT'>, 'INTERVAL': <TokenType.INTERVAL: 'INTERVAL'>, 'INTERSECT': <TokenType.INTERSECT: 'INTERSECT'>, 'INTO': <TokenType.INTO: 'INTO'>, 'IS': <TokenType.IS: 'IS'>, 'ISNULL': <TokenType.ISNULL: 'ISNULL'>, 'JOIN': <TokenType.JOIN: 'JOIN'>, 'KEEP': <TokenType.KEEP: 'KEEP'>, 'KILL': <TokenType.KILL: 'KILL'>, 'LATERAL': <TokenType.LATERAL: 'LATERAL'>, 'LEFT': <TokenType.LEFT: 'LEFT'>, 'LIKE': <TokenType.LIKE: 'LIKE'>, 'LIMIT': <TokenType.LIMIT: 'LIMIT'>, 'LOAD': <TokenType.LOAD: 'LOAD'>, 'LOCK': <TokenType.LOCK: 'LOCK'>, 'MERGE': <TokenType.MERGE: 'MERGE'>, 'NATURAL': <TokenType.NATURAL: 'NATURAL'>, 'NEXT': <TokenType.NEXT: 'NEXT'>, 'NOT': <TokenType.NOT: 'NOT'>, 'NOTNULL': <TokenType.NOTNULL: 'NOTNULL'>, 'NULL': <TokenType.NULL: 'NULL'>, 'OBJECT': <TokenType.OBJECT: 'OBJECT'>, 'OFFSET': <TokenType.OFFSET: 'OFFSET'>, 'ON': <TokenType.ON: 'ON'>, 'OR': <TokenType.OR: 'OR'>, 'XOR': <TokenType.XOR: 'XOR'>, 'ORDER BY': <TokenType.ORDER_BY: 'ORDER_BY'>, 'ORDINALITY': <TokenType.ORDINALITY: 'ORDINALITY'>, 'OUTER': <TokenType.OUTER: 'OUTER'>, 'OVER': <TokenType.OVER: 'OVER'>, 'OVERLAPS': <TokenType.OVERLAPS: 'OVERLAPS'>, 'OVERWRITE': <TokenType.OVERWRITE: 'OVERWRITE'>, 'PARTITION': <TokenType.PARTITION: 'PARTITION'>, 'PARTITION BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PARTITIONED BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PARTITIONED_BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PERCENT': <TokenType.PERCENT: 'PERCENT'>, 'PIVOT': <TokenType.PIVOT: 'PIVOT'>, 'PRAGMA': <TokenType.PRAGMA: 'PRAGMA'>, 'PRIMARY KEY': <TokenType.PRIMARY_KEY: 'PRIMARY_KEY'>, 'PROCEDURE': <TokenType.PROCEDURE: 'PROCEDURE'>, 'QUALIFY': <TokenType.QUALIFY: 'QUALIFY'>, 'RANGE': <TokenType.RANGE: 'RANGE'>, 'RECURSIVE': <TokenType.RECURSIVE: 'RECURSIVE'>, 'REGEXP': <TokenType.RLIKE: 'RLIKE'>, 'REPLACE': <TokenType.REPLACE: 'REPLACE'>, 'RETURNING': <TokenType.RETURNING: 'RETURNING'>, 'REFERENCES': <TokenType.REFERENCES: 'REFERENCES'>, 'RIGHT': <TokenType.RIGHT: 'RIGHT'>, 'RLIKE': <TokenType.RLIKE: 'RLIKE'>, 'ROLLBACK': <TokenType.ROLLBACK: 'ROLLBACK'>, 'ROLLUP': <TokenType.ROLLUP: 'ROLLUP'>, 'ROW': <TokenType.ROW: 'ROW'>, 'ROWS': <TokenType.ROWS: 'ROWS'>, 'SCHEMA': <TokenType.SCHEMA: 'SCHEMA'>, 'SELECT': <TokenType.SELECT: 'SELECT'>, 'SEMI': <TokenType.SEMI: 'SEMI'>, 'SET': <TokenType.SET: 'SET'>, 'SETTINGS': <TokenType.SETTINGS: 'SETTINGS'>, 'SHOW': <TokenType.SHOW: 'SHOW'>, 'SIMILAR TO': <TokenType.SIMILAR_TO: 'SIMILAR_TO'>, 'SOME': <TokenType.SOME: 'SOME'>, 'SORT BY': <TokenType.SORT_BY: 'SORT_BY'>, 'START WITH': <TokenType.START_WITH: 'START_WITH'>, 'TABLE': <TokenType.TABLE: 'TABLE'>, 'TABLESAMPLE': <TokenType.TABLE_SAMPLE: 'TABLE_SAMPLE'>, 'TEMP': <TokenType.TEMPORARY: 'TEMPORARY'>, 'TEMPORARY': <TokenType.TEMPORARY: 'TEMPORARY'>, 'THEN': <TokenType.THEN: 'THEN'>, 'TRUE': <TokenType.TRUE: 'TRUE'>, 'TRUNCATE': <TokenType.TRUNCATE: 'TRUNCATE'>, 'UNION': <TokenType.UNION: 'UNION'>, 'UNKNOWN': <TokenType.UNKNOWN: 'UNKNOWN'>, 'UNNEST': <TokenType.UNNEST: 'UNNEST'>, 'UNPIVOT': <TokenType.UNPIVOT: 'UNPIVOT'>, 'UPDATE': <TokenType.UPDATE: 'UPDATE'>, 'USE': <TokenType.USE: 'USE'>, 'USING': <TokenType.USING: 'USING'>, 'UUID': <TokenType.UUID: 'UUID'>, 'VALUES': <TokenType.VALUES: 'VALUES'>, 'VIEW': <TokenType.VIEW: 'VIEW'>, 'VOLATILE': <TokenType.VOLATILE: 'VOLATILE'>, 'WHEN': <TokenType.WHEN: 'WHEN'>, 'WHERE': <TokenType.WHERE: 'WHERE'>, 'WINDOW': <TokenType.WINDOW: 'WINDOW'>, 'WITH': <TokenType.WITH: 'WITH'>, 'APPLY': <TokenType.APPLY: 'APPLY'>, 'ARRAY': <TokenType.ARRAY: 'ARRAY'>, 'BIT': <TokenType.BIT: 'BIT'>, 'BOOL': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BOOLEAN': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BYTE': <TokenType.TINYINT: 'TINYINT'>, 'MEDIUMINT': <TokenType.MEDIUMINT: 'MEDIUMINT'>, 'INT1': <TokenType.TINYINT: 'TINYINT'>, 'TINYINT': <TokenType.TINYINT: 'TINYINT'>, 'INT16': <TokenType.SMALLINT: 'SMALLINT'>, 'SHORT': <TokenType.SMALLINT: 'SMALLINT'>, 'SMALLINT': <TokenType.SMALLINT: 'SMALLINT'>, 'INT128': <TokenType.INT128: 'INT128'>, 'HUGEINT': <TokenType.INT128: 'INT128'>, 'INT2': <TokenType.SMALLINT: 'SMALLINT'>, 'INTEGER': <TokenType.INT: 'INT'>, 'INT': <TokenType.INT: 'INT'>, 'INT4': <TokenType.INT: 'INT'>, 'INT32': <TokenType.INT: 'INT'>, 'INT64': <TokenType.BIGINT: 'BIGINT'>, 'LONG': <TokenType.BIGINT: 'BIGINT'>, 'BIGINT': <TokenType.BIGINT: 'BIGINT'>, 'INT8': <TokenType.TINYINT: 'TINYINT'>, 'UINT': <TokenType.UINT: 'UINT'>, 'DEC': <TokenType.DECIMAL: 'DECIMAL'>, 'DECIMAL': <TokenType.DECIMAL: 'DECIMAL'>, 'BIGDECIMAL': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'BIGNUMERIC': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'MAP': <TokenType.MAP: 'MAP'>, 'NULLABLE': <TokenType.NULLABLE: 'NULLABLE'>, 'NUMBER': <TokenType.DECIMAL: 'DECIMAL'>, 'NUMERIC': <TokenType.DECIMAL: 'DECIMAL'>, 'FIXED': <TokenType.DECIMAL: 'DECIMAL'>, 'REAL': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT4': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT8': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE PRECISION': <TokenType.DOUBLE: 'DOUBLE'>, 'JSON': <TokenType.JSON: 'JSON'>, 'CHAR': <TokenType.TEXT: 'TEXT'>, 'CHARACTER': <TokenType.CHAR: 'CHAR'>, 'NCHAR': <TokenType.NCHAR: 'NCHAR'>, 'VARCHAR': <TokenType.VARCHAR: 'VARCHAR'>, 'VARCHAR2': <TokenType.VARCHAR: 'VARCHAR'>, 'NVARCHAR': <TokenType.NVARCHAR: 'NVARCHAR'>, 'NVARCHAR2': <TokenType.NVARCHAR: 'NVARCHAR'>, 'BPCHAR': <TokenType.TEXT: 'TEXT'>, 'STR': <TokenType.TEXT: 'TEXT'>, 'STRING': <TokenType.VARCHAR: 'VARCHAR'>, 'TEXT': <TokenType.TEXT: 'TEXT'>, 'LONGTEXT': <TokenType.LONGTEXT: 'LONGTEXT'>, 'MEDIUMTEXT': <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, 'TINYTEXT': <TokenType.TINYTEXT: 'TINYTEXT'>, 'CLOB': <TokenType.TEXT: 'TEXT'>, 'LONGVARCHAR': <TokenType.TEXT: 'TEXT'>, 'BINARY': <TokenType.VARBINARY: 'VARBINARY'>, 'BLOB': <TokenType.VARBINARY: 'VARBINARY'>, 'LONGBLOB': <TokenType.LONGBLOB: 'LONGBLOB'>, 'MEDIUMBLOB': <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, 'TINYBLOB': <TokenType.TINYBLOB: 'TINYBLOB'>, 'BYTEA': <TokenType.VARBINARY: 'VARBINARY'>, 'VARBINARY': <TokenType.VARBINARY: 'VARBINARY'>, 'TIME': <TokenType.TIME: 'TIME'>, 'TIMETZ': <TokenType.TIMETZ: 'TIMETZ'>, 'TIMESTAMP': <TokenType.TIMESTAMP: 'TIMESTAMP'>, 'TIMESTAMPTZ': <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, 'TIMESTAMPLTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMP_LTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMPNTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'TIMESTAMP_NTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'DATE': <TokenType.DATE: 'DATE'>, 'DATETIME': <TokenType.DATETIME: 'DATETIME'>, 'INT4RANGE': <TokenType.INT4RANGE: 'INT4RANGE'>, 'INT4MULTIRANGE': <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, 'INT8RANGE': <TokenType.INT8RANGE: 'INT8RANGE'>, 'INT8MULTIRANGE': <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, 'NUMRANGE': <TokenType.NUMRANGE: 'NUMRANGE'>, 'NUMMULTIRANGE': <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, 'TSRANGE': <TokenType.TSRANGE: 'TSRANGE'>, 'TSMULTIRANGE': <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, 'TSTZRANGE': <TokenType.TSTZRANGE: 'TSTZRANGE'>, 'TSTZMULTIRANGE': <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, 'DATERANGE': <TokenType.DATERANGE: 'DATERANGE'>, 'DATEMULTIRANGE': <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, 'UNIQUE': <TokenType.UNIQUE: 'UNIQUE'>, 'STRUCT': <TokenType.STRUCT: 'STRUCT'>, 'SEQUENCE': <TokenType.SEQUENCE: 'SEQUENCE'>, 'VARIANT': <TokenType.VARIANT: 'VARIANT'>, 'ALTER': <TokenType.ALTER: 'ALTER'>, 'ANALYZE': <TokenType.COMMAND: 'COMMAND'>, 'CALL': <TokenType.COMMAND: 'COMMAND'>, 'COMMENT': <TokenType.COMMENT: 'COMMENT'>, 'EXPLAIN': <TokenType.COMMAND: 'COMMAND'>, 'GRANT': <TokenType.COMMAND: 'COMMAND'>, 'OPTIMIZE': <TokenType.COMMAND: 'COMMAND'>, 'PREPARE': <TokenType.COMMAND: 'COMMAND'>, 'VACUUM': <TokenType.COMMAND: 'COMMAND'>, 'USER-DEFINED': <TokenType.USERDEFINED: 'USERDEFINED'>, 'FOR VERSION': <TokenType.VERSION_SNAPSHOT: 'VERSION_SNAPSHOT'>, 'FOR TIMESTAMP': <TokenType.TIMESTAMP_SNAPSHOT: 'TIMESTAMP_SNAPSHOT'>, '//': <TokenType.DIV: 'DIV'>, 'ATTACH': <TokenType.COMMAND: 'COMMAND'>, 'BITSTRING': <TokenType.BIT: 'BIT'>, 'CHARACTER VARYING': <TokenType.TEXT: 'TEXT'>, 'EXCLUDE': <TokenType.EXCEPT: 'EXCEPT'>, 'LOGICAL': <TokenType.BOOLEAN: 'BOOLEAN'>, 'ONLY': <TokenType.ONLY: 'ONLY'>, 'PIVOT_WIDER': <TokenType.PIVOT: 'PIVOT'>, 'POSITIONAL': <TokenType.POSITIONAL: 'POSITIONAL'>, 'SIGNED': <TokenType.INT: 'INT'>, 'UBIGINT': <TokenType.UBIGINT: 'UBIGINT'>, 'UINTEGER': <TokenType.UINT: 'UINT'>, 'USMALLINT': <TokenType.USMALLINT: 'USMALLINT'>, 'UTINYINT': <TokenType.UTINYINT: 'UTINYINT'>, 'TIMESTAMP_S': <TokenType.TIMESTAMP_S: 'TIMESTAMP_S'>, 'TIMESTAMP_MS': <TokenType.TIMESTAMP_MS: 'TIMESTAMP_MS'>, 'TIMESTAMP_NS': <TokenType.TIMESTAMP_NS: 'TIMESTAMP_NS'>, 'TIMESTAMP_US': <TokenType.TIMESTAMP: 'TIMESTAMP'>}"}, "sqlglot.dialects.duckdb.DuckDB.Tokenizer.SINGLE_TOKENS": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Tokenizer.SINGLE_TOKENS", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Tokenizer.SINGLE_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'(': <TokenType.L_PAREN: 'L_PAREN'>, ')': <TokenType.R_PAREN: 'R_PAREN'>, '[': <TokenType.L_BRACKET: 'L_BRACKET'>, ']': <TokenType.R_BRACKET: 'R_BRACKET'>, '{': <TokenType.L_BRACE: 'L_BRACE'>, '}': <TokenType.R_BRACE: 'R_BRACE'>, '&': <TokenType.AMP: 'AMP'>, '^': <TokenType.CARET: 'CARET'>, ':': <TokenType.COLON: 'COLON'>, ',': <TokenType.COMMA: 'COMMA'>, '.': <TokenType.DOT: 'DOT'>, '-': <TokenType.DASH: 'DASH'>, '=': <TokenType.EQ: 'EQ'>, '>': <TokenType.GT: 'GT'>, '<': <TokenType.LT: 'LT'>, '%': <TokenType.MOD: 'MOD'>, '!': <TokenType.NOT: 'NOT'>, '|': <TokenType.PIPE: 'PIPE'>, '+': <TokenType.PLUS: 'PLUS'>, ';': <TokenType.SEMICOLON: 'SEMICOLON'>, '/': <TokenType.SLASH: 'SLASH'>, '\\\\': <TokenType.BACKSLASH: 'BACKSLASH'>, '*': <TokenType.STAR: 'STAR'>, '~': <TokenType.TILDA: 'TILDA'>, '?': <TokenType.PLACEHOLDER: 'PLACEHOLDER'>, '@': <TokenType.PARAMETER: 'PARAMETER'>, '#': <TokenType.HASH: 'HASH'>, "'": <TokenType.UNKNOWN: 'UNKNOWN'>, '`': <TokenType.UNKNOWN: 'UNKNOWN'>, '"': <TokenType.UNKNOWN: 'UNKNOWN'>, '$': <TokenType.PARAMETER: 'PARAMETER'>}"}, "sqlglot.dialects.duckdb.DuckDB.Parser": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Parser", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Parser", "kind": "class", "doc": "<p>Parser consumes a list of tokens produced by the Tokenizer and produces a parsed syntax tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>error_level:</strong> The desired error level.\nDefault: ErrorLevel.IMMEDIATE</li>\n<li><strong>error_message_context:</strong> The amount of context to capture from a query string when displaying\nthe error message (in number of characters).\nDefault: 100</li>\n<li><strong>max_errors:</strong> Maximum number of error messages to include in a raised ParseError.\nThis is only relevant if error_level is ErrorLevel.RAISE.\nDefault: 3</li>\n</ul>\n", "bases": "sqlglot.parser.Parser"}, "sqlglot.dialects.duckdb.DuckDB.Parser.BITWISE": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Parser.BITWISE", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Parser.BITWISE", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.AMP: 'AMP'>: <class 'sqlglot.expressions.BitwiseAnd'>, <TokenType.CARET: 'CARET'>: <class 'sqlglot.expressions.BitwiseXor'>, <TokenType.PIPE: 'PIPE'>: <class 'sqlglot.expressions.BitwiseOr'>, <TokenType.TILDA: 'TILDA'>: <class 'sqlglot.expressions.RegexpLike'>}"}, "sqlglot.dialects.duckdb.DuckDB.Parser.FUNCTIONS_WITH_ALIASED_ARGS": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Parser.FUNCTIONS_WITH_ALIASED_ARGS", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Parser.FUNCTIONS_WITH_ALIASED_ARGS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'STRUCT', 'STRUCT_PACK'}"}, "sqlglot.dialects.duckdb.DuckDB.Parser.FUNCTIONS": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Parser.FUNCTIONS", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Parser.FUNCTIONS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ABS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Abs'>>, 'ADD_MONTHS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AddMonths'>>, 'ANONYMOUS_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnonymousAggFunc'>>, 'ANY_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnyValue'>>, 'APPROX_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_COUNT_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'APPROX_TOP_K': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxTopK'>>, 'ARG_MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARGMAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'MAX_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARG_MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARGMIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'MIN_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Array'>>, 'ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAgg'>>, 'ARRAY_ALL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAll'>>, 'ARRAY_ANY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAny'>>, 'ARRAY_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CONSTRUCT_COMPACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConstructCompact'>>, 'ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayContains'>>, 'FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_OVERLAPS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayOverlaps'>>, 'ARRAY_SIZE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_SORT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SortArray'>>, 'ARRAY_SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySum'>>, 'ARRAY_TO_STRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_JOIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_UNION_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUnionAgg'>>, 'ARRAY_UNIQUE_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUniqueAgg'>>, 'AVG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Avg'>>, 'CASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Case'>>, 'CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cast'>>, 'CAST_TO_STR_TYPE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CastToStrType'>>, 'CBRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cbrt'>>, 'CEIL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CEILING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CHR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'COALESCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'IFNULL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'NVL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'COLLATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Collate'>>, 'COMBINED_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedAggFunc'>>, 'COMBINED_PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedParameterizedAgg'>>, 'CONCAT': <function Parser.<lambda>>, 'CONCAT_WS': <function Parser.<lambda>>, 'CONNECT_BY_ROOT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ConnectByRoot'>>, 'CONVERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Convert'>>, 'CORR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Corr'>>, 'COUNT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Count'>>, 'COUNT_IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COUNTIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COVAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarPop'>>, 'COVAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarSamp'>>, 'CURRENT_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDate'>>, 'CURRENT_DATETIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDatetime'>>, 'CURRENT_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTime'>>, 'CURRENT_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTimestamp'>>, 'CURRENT_USER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentUser'>>, 'DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Date'>>, 'DATE_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateAdd'>>, 'DATEDIFF': <function _build_date_diff>, 'DATE_DIFF': <function _build_date_diff>, 'DATE_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATE_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateStrToDate'>>, 'DATE_TO_DATE_STR': <function Parser.<lambda>>, 'DATE_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateToDi'>>, 'DATE_TRUNC': <function date_trunc_to_time>, 'DATETIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeAdd'>>, 'DATETIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeDiff'>>, 'DATETIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeSub'>>, 'DATETIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeTrunc'>>, 'DAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Day'>>, 'DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAYOFMONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAY_OF_WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAYOFWEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAY_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DAYOFYEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DECODE': <function DuckDB.Parser.<lambda>>, 'DI_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DiToDate'>>, 'ENCODE': <function DuckDB.Parser.<lambda>>, 'EXP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Exp'>>, 'EXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Explode'>>, 'EXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ExplodeOuter'>>, 'EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Extract'>>, 'FIRST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.First'>>, 'FIRST_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FirstValue'>>, 'FLATTEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Flatten'>>, 'FLOOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Floor'>>, 'FROM_BASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase'>>, 'FROM_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase64'>>, 'GENERATE_DATE_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GenerateDateArray'>>, 'GENERATE_SERIES': <function _build_generate_series.<locals>._builder>, 'GREATEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Greatest'>>, 'GROUP_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GroupConcat'>>, 'HEX': <function build_hex>, 'HLL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Hll'>>, 'IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'IIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'INITCAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Initcap'>>, 'IS_INF': <bound method Func.from_arg_list of <class 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'sqlglot.expressions.Explode'>>, 'RANGE': <function _build_generate_series.<locals>._builder>}"}, "sqlglot.dialects.duckdb.DuckDB.Parser.FUNCTION_PARSERS": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Parser.FUNCTION_PARSERS", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Parser.FUNCTION_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'CAST': <function Parser.<lambda>>, 'CONVERT': <function Parser.<lambda>>, 'EXTRACT': <function Parser.<lambda>>, 'JSON_OBJECT': <function Parser.<lambda>>, 'JSON_OBJECTAGG': <function Parser.<lambda>>, 'JSON_TABLE': <function Parser.<lambda>>, 'MATCH': <function Parser.<lambda>>, 'OPENJSON': <function Parser.<lambda>>, 'POSITION': <function Parser.<lambda>>, 'PREDICT': <function Parser.<lambda>>, 'SAFE_CAST': <function Parser.<lambda>>, 'STRING_AGG': <function Parser.<lambda>>, 'SUBSTRING': <function Parser.<lambda>>, 'TRIM': <function Parser.<lambda>>, 'TRY_CAST': <function Parser.<lambda>>, 'TRY_CONVERT': <function Parser.<lambda>>}"}, "sqlglot.dialects.duckdb.DuckDB.Parser.NO_PAREN_FUNCTION_PARSERS": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Parser.NO_PAREN_FUNCTION_PARSERS", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Parser.NO_PAREN_FUNCTION_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ANY': <function Parser.<lambda>>, 'CASE': <function Parser.<lambda>>, 'IF': <function Parser.<lambda>>, 'NEXT': <function Parser.<lambda>>, 'MAP': <function DuckDB.Parser.<lambda>>}"}, "sqlglot.dialects.duckdb.DuckDB.Parser.TABLE_ALIAS_TOKENS": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Parser.TABLE_ALIAS_TOKENS", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Parser.TABLE_ALIAS_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.KILL: 'KILL'>, <TokenType.MONEY: 'MONEY'>, <TokenType.COPY: 'COPY'>, <TokenType.PERCENT: 'PERCENT'>, <TokenType.TAG: 'TAG'>, <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, <TokenType.VOLATILE: 'VOLATILE'>, <TokenType.IDENTIFIER: 'IDENTIFIER'>, <TokenType.VARBINARY: 'VARBINARY'>, <TokenType.HSTORE: 'HSTORE'>, <TokenType.ASC: 'ASC'>, <TokenType.IPADDRESS: 'IPADDRESS'>, <TokenType.ISNULL: 'ISNULL'>, <TokenType.TEMPORARY: 'TEMPORARY'>, <TokenType.PROCEDURE: 'PROCEDURE'>, <TokenType.SCHEMA: 'SCHEMA'>, <TokenType.NUMRANGE: 'NUMRANGE'>, <TokenType.DATE32: 'DATE32'>, <TokenType.INT8RANGE: 'INT8RANGE'>, <TokenType.AGGREGATEFUNCTION: 'AGGREGATEFUNCTION'>, <TokenType.VIEW: 'VIEW'>, <TokenType.VARCHAR: 'VARCHAR'>, <TokenType.TIMETZ: 'TIMETZ'>, <TokenType.GEOMETRY: 'GEOMETRY'>, <TokenType.BEGIN: 'BEGIN'>, <TokenType.ENUM8: 'ENUM8'>, <TokenType.INDEX: 'INDEX'>, <TokenType.PARTITION: 'PARTITION'>, <TokenType.UINT256: 'UINT256'>, <TokenType.BIGINT: 'BIGINT'>, <TokenType.CACHE: 'CACHE'>, <TokenType.OPERATOR: 'OPERATOR'>, <TokenType.COLUMN: 'COLUMN'>, <TokenType.INT128: 'INT128'>, <TokenType.SMALLMONEY: 'SMALLMONEY'>, <TokenType.HLLSKETCH: 'HLLSKETCH'>, <TokenType.UNPIVOT: 'UNPIVOT'>, <TokenType.SMALLINT: 'SMALLINT'>, <TokenType.INT256: 'INT256'>, <TokenType.FLOAT: 'FLOAT'>, <TokenType.COMMIT: 'COMMIT'>, <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, <TokenType.EXISTS: 'EXISTS'>, <TokenType.NULL: 'NULL'>, <TokenType.RECURSIVE: 'RECURSIVE'>, <TokenType.SET: 'SET'>, <TokenType.NULLABLE: 'NULLABLE'>, <TokenType.REFRESH: 'REFRESH'>, <TokenType.TINYTEXT: 'TINYTEXT'>, <TokenType.SHOW: 'SHOW'>, <TokenType.DEFAULT: 'DEFAULT'>, <TokenType.DATE: 'DATE'>, <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <TokenType.MERGE: 'MERGE'>, <TokenType.FIRST: 'FIRST'>, <TokenType.BINARY: 'BINARY'>, <TokenType.ARRAY: 'ARRAY'>, <TokenType.SERIAL: 'SERIAL'>, <TokenType.EXECUTE: 'EXECUTE'>, <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, <TokenType.INTERVAL: 'INTERVAL'>, <TokenType.PRAGMA: 'PRAGMA'>, <TokenType.STORAGE_INTEGRATION: 'STORAGE_INTEGRATION'>, <TokenType.BPCHAR: 'BPCHAR'>, <TokenType.BIT: 'BIT'>, <TokenType.UINT: 'UINT'>, <TokenType.UUID: 'UUID'>, <TokenType.STRUCT: 'STRUCT'>, <TokenType.FALSE: 'FALSE'>, <TokenType.FUNCTION: 'FUNCTION'>, <TokenType.TOP: 'TOP'>, <TokenType.SUPER: 'SUPER'>, <TokenType.CASE: 'CASE'>, <TokenType.IMAGE: 'IMAGE'>, <TokenType.UBIGINT: 'UBIGINT'>, <TokenType.LONGBLOB: 'LONGBLOB'>, <TokenType.ROLLUP: 'ROLLUP'>, <TokenType.VAR: 'VAR'>, <TokenType.COMMAND: 'COMMAND'>, <TokenType.LOAD: 'LOAD'>, <TokenType.TRUNCATE: 'TRUNCATE'>, <TokenType.KEEP: 'KEEP'>, <TokenType.UMEDIUMINT: 'UMEDIUMINT'>, <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, <TokenType.UINT128: 'UINT128'>, <TokenType.END: 'END'>, <TokenType.MAP: 'MAP'>, <TokenType.IPV4: 'IPV4'>, <TokenType.USERDEFINED: 'USERDEFINED'>, <TokenType.REFERENCES: 'REFERENCES'>, <TokenType.REPLACE: 'REPLACE'>, <TokenType.RANGE: 'RANGE'>, <TokenType.NVARCHAR: 'NVARCHAR'>, <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, <TokenType.TRUE: 'TRUE'>, <TokenType.TIMESTAMP_MS: 'TIMESTAMP_MS'>, <TokenType.VARIANT: 'VARIANT'>, <TokenType.ENUM: 'ENUM'>, <TokenType.USE: 'USE'>, <TokenType.USMALLINT: 'USMALLINT'>, <TokenType.OVERLAPS: 'OVERLAPS'>, <TokenType.TIMESTAMP_S: 'TIMESTAMP_S'>, <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, <TokenType.UNIQUE: 'UNIQUE'>, <TokenType.ORDINALITY: 'ORDINALITY'>, <TokenType.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>, <TokenType.TEXT: 'TEXT'>, <TokenType.DATABASE: 'DATABASE'>, <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, <TokenType.PSEUDO_TYPE: 'PSEUDO_TYPE'>, <TokenType.FIXEDSTRING: 'FIXEDSTRING'>, <TokenType.NEXT: 'NEXT'>, <TokenType.INT: 'INT'>, <TokenType.BIGSERIAL: 'BIGSERIAL'>, <TokenType.BOOLEAN: 'BOOLEAN'>, <TokenType.IS: 'IS'>, <TokenType.CONSTRAINT: 'CONSTRAINT'>, <TokenType.FINAL: 'FINAL'>, <TokenType.UNKNOWN: 'UNKNOWN'>, <TokenType.SETTINGS: 'SETTINGS'>, <TokenType.ROWS: 'ROWS'>, <TokenType.TSTZRANGE: 'TSTZRANGE'>, <TokenType.DATETIME64: 'DATETIME64'>, <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, <TokenType.DATETIME: 'DATETIME'>, <TokenType.MEDIUMINT: 'MEDIUMINT'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>, <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, <TokenType.XML: 'XML'>, <TokenType.JSON: 'JSON'>, <TokenType.UTINYINT: 'UTINYINT'>, <TokenType.DELETE: 'DELETE'>, <TokenType.TIME: 'TIME'>, <TokenType.UDECIMAL: 'UDECIMAL'>, <TokenType.NESTED: 'NESTED'>, <TokenType.DESC: 'DESC'>, <TokenType.ROWVERSION: 'ROWVERSION'>, <TokenType.TIMESTAMP_NS: 'TIMESTAMP_NS'>, <TokenType.ANY: 'ANY'>, <TokenType.DIV: 'DIV'>, <TokenType.DICTIONARY: 'DICTIONARY'>, <TokenType.INET: 'INET'>, <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, <TokenType.COMMENT: 'COMMENT'>, <TokenType.CURRENT_USER: 'CURRENT_USER'>, <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>, <TokenType.ALL: 'ALL'>, <TokenType.NAME: 'NAME'>, <TokenType.SOME: 'SOME'>, <TokenType.ENUM16: 'ENUM16'>, <TokenType.YEAR: 'YEAR'>, <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, <TokenType.DOUBLE: 'DOUBLE'>, <TokenType.INT4RANGE: 'INT4RANGE'>, <TokenType.FORMAT: 'FORMAT'>, <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, <TokenType.IPPREFIX: 'IPPREFIX'>, <TokenType.OVERWRITE: 'OVERWRITE'>, <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>, <TokenType.COLLATE: 'COLLATE'>, <TokenType.FILTER: 'FILTER'>, <TokenType.JSONB: 'JSONB'>, <TokenType.TDIGEST: 'TDIGEST'>, <TokenType.CHAR: 'CHAR'>, <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.ROW: 'ROW'>, <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.TABLE: 'TABLE'>, <TokenType.DATERANGE: 'DATERANGE'>, <TokenType.TSRANGE: 'TSRANGE'>, <TokenType.ESCAPE: 'ESCAPE'>, <TokenType.PIVOT: 'PIVOT'>, <TokenType.DECIMAL: 'DECIMAL'>, <TokenType.NCHAR: 'NCHAR'>, <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, <TokenType.UPDATE: 'UPDATE'>, <TokenType.MODEL: 'MODEL'>, <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, <TokenType.SEQUENCE: 'SEQUENCE'>, <TokenType.LONGTEXT: 'LONGTEXT'>, <TokenType.DESCRIBE: 'DESCRIBE'>, <TokenType.IPV6: 'IPV6'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, <TokenType.TINYINT: 'TINYINT'>, <TokenType.TINYBLOB: 'TINYBLOB'>}"}, "sqlglot.dialects.duckdb.DuckDB.Parser.PLACEHOLDER_PARSERS": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Parser.PLACEHOLDER_PARSERS", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Parser.PLACEHOLDER_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.PLACEHOLDER: 'PLACEHOLDER'>: <function Parser.<lambda>>, <TokenType.PARAMETER: 'PARAMETER'>: <function DuckDB.Parser.<lambda>>, <TokenType.COLON: 'COLON'>: <function Parser.<lambda>>}"}, "sqlglot.dialects.duckdb.DuckDB.Parser.TYPE_CONVERTER": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Parser.TYPE_CONVERTER", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Parser.TYPE_CONVERTER", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.DECIMAL: 'DECIMAL'>: <function build_default_decimal_type.<locals>._builder>}"}, "sqlglot.dialects.duckdb.DuckDB.Parser.SHOW_TRIE": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Parser.SHOW_TRIE", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Parser.SHOW_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.duckdb.DuckDB.Parser.SET_TRIE": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Parser.SET_TRIE", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Parser.SET_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'GLOBAL': {0: True}, 'LOCAL': {0: True}, 'SESSION': {0: True}, 'TRANSACTION': {0: True}}"}, "sqlglot.dialects.duckdb.DuckDB.Generator": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator", "kind": "class", "doc": "<p>Generator converts a given syntax tree to the corresponding SQL string.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>pretty:</strong> Whether to format the produced SQL string.\nDefault: False.</li>\n<li><strong>identify:</strong> Determines when an identifier should be quoted. Possible values are:\nFalse (default): Never quote, except in cases where it's mandatory by the dialect.\nTrue or 'always': Always quote.\n'safe': Only quote identifiers that are case insensitive.</li>\n<li><strong>normalize:</strong> Whether to normalize identifiers to lowercase.\nDefault: False.</li>\n<li><strong>pad:</strong> The pad size in a formatted string. For example, this affects the indentation of\na projection in a query, relative to its nesting level.\nDefault: 2.</li>\n<li><strong>indent:</strong> The indentation size in a formatted string. For example, this affects the\nindentation of subqueries and filters under a <code>WHERE</code> clause.\nDefault: 2.</li>\n<li><strong>normalize_functions:</strong> How to normalize function names. Possible values are:\n\"upper\" or True (default): Convert names to uppercase.\n\"lower\": Convert names to lowercase.\nFalse: Disables function name normalization.</li>\n<li><strong>unsupported_level:</strong> Determines the generator's behavior when it encounters unsupported expressions.\nDefault ErrorLevel.WARN.</li>\n<li><strong>max_unsupported:</strong> Maximum number of unsupported messages to include in a raised UnsupportedError.\nThis is only relevant if unsupported_level is ErrorLevel.RAISE.\nDefault: 3</li>\n<li><strong>leading_comma:</strong> Whether the comma is leading or trailing in select expressions.\nThis is only relevant when generating in pretty mode.\nDefault: False</li>\n<li><strong>max_text_width:</strong> The max number of characters in a segment before creating new lines in pretty mode.\nThe default is on the smaller end because the length only represents a segment and not the true\nline length.\nDefault: 80</li>\n<li><strong>comments:</strong> Whether to preserve comments in the output SQL code.\nDefault: True</li>\n</ul>\n", "bases": "sqlglot.generator.Generator"}, "sqlglot.dialects.duckdb.DuckDB.Generator.PARAMETER_TOKEN": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.PARAMETER_TOKEN", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.PARAMETER_TOKEN", "kind": "variable", "doc": "<p></p>\n", "default_value": "'$'"}, "sqlglot.dialects.duckdb.DuckDB.Generator.NAMED_PLACEHOLDER_TOKEN": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.NAMED_PLACEHOLDER_TOKEN", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.NAMED_PLACEHOLDER_TOKEN", "kind": "variable", "doc": "<p></p>\n", "default_value": "'$'"}, "sqlglot.dialects.duckdb.DuckDB.Generator.JOIN_HINTS": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.JOIN_HINTS", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.JOIN_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.duckdb.DuckDB.Generator.TABLE_HINTS": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.TABLE_HINTS", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.TABLE_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.duckdb.DuckDB.Generator.QUERY_HINTS": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.QUERY_HINTS", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.QUERY_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.duckdb.DuckDB.Generator.LIMIT_FETCH": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.LIMIT_FETCH", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.LIMIT_FETCH", "kind": "variable", "doc": "<p></p>\n", "default_value": "'LIMIT'"}, "sqlglot.dialects.duckdb.DuckDB.Generator.STRUCT_DELIMITER": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.STRUCT_DELIMITER", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.STRUCT_DELIMITER", "kind": "variable", "doc": "<p></p>\n", "default_value": "('(', ')')"}, "sqlglot.dialects.duckdb.DuckDB.Generator.RENAME_TABLE_WITH_DB": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.RENAME_TABLE_WITH_DB", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.RENAME_TABLE_WITH_DB", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.duckdb.DuckDB.Generator.NVL2_SUPPORTED": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.NVL2_SUPPORTED", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.NVL2_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.duckdb.DuckDB.Generator.SEMI_ANTI_JOIN_WITH_SIDE": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.SEMI_ANTI_JOIN_WITH_SIDE", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.SEMI_ANTI_JOIN_WITH_SIDE", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.duckdb.DuckDB.Generator.TABLESAMPLE_KEYWORDS": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.TABLESAMPLE_KEYWORDS", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.TABLESAMPLE_KEYWORDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "'USING SAMPLE'"}, "sqlglot.dialects.duckdb.DuckDB.Generator.TABLESAMPLE_SEED_KEYWORD": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.TABLESAMPLE_SEED_KEYWORD", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.TABLESAMPLE_SEED_KEYWORD", "kind": "variable", "doc": "<p></p>\n", "default_value": "'REPEATABLE'"}, "sqlglot.dialects.duckdb.DuckDB.Generator.LAST_DAY_SUPPORTS_DATE_PART": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.LAST_DAY_SUPPORTS_DATE_PART", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.LAST_DAY_SUPPORTS_DATE_PART", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.duckdb.DuckDB.Generator.JSON_KEY_VALUE_PAIR_SEP": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.JSON_KEY_VALUE_PAIR_SEP", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.JSON_KEY_VALUE_PAIR_SEP", "kind": "variable", "doc": "<p></p>\n", "default_value": "','"}, "sqlglot.dialects.duckdb.DuckDB.Generator.IGNORE_NULLS_IN_FUNC": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.IGNORE_NULLS_IN_FUNC", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.IGNORE_NULLS_IN_FUNC", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.duckdb.DuckDB.Generator.JSON_PATH_BRACKETED_KEY_SUPPORTED": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.JSON_PATH_BRACKETED_KEY_SUPPORTED", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.JSON_PATH_BRACKETED_KEY_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.duckdb.DuckDB.Generator.SUPPORTS_CREATE_TABLE_LIKE": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.SUPPORTS_CREATE_TABLE_LIKE", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.SUPPORTS_CREATE_TABLE_LIKE", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.duckdb.DuckDB.Generator.MULTI_ARG_DISTINCT": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.MULTI_ARG_DISTINCT", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.MULTI_ARG_DISTINCT", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.duckdb.DuckDB.Generator.CAN_IMPLEMENT_ARRAY_ANY": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.CAN_IMPLEMENT_ARRAY_ANY", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.CAN_IMPLEMENT_ARRAY_ANY", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.duckdb.DuckDB.Generator.SUPPORTS_TO_NUMBER": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.SUPPORTS_TO_NUMBER", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.SUPPORTS_TO_NUMBER", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.duckdb.DuckDB.Generator.COPY_HAS_INTO_KEYWORD": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.COPY_HAS_INTO_KEYWORD", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.COPY_HAS_INTO_KEYWORD", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.duckdb.DuckDB.Generator.STAR_EXCEPT": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.STAR_EXCEPT", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.STAR_EXCEPT", "kind": "variable", "doc": "<p></p>\n", "default_value": "'EXCLUDE'"}, "sqlglot.dialects.duckdb.DuckDB.Generator.TRANSFORMS": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.TRANSFORMS", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.JSONPathKey'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRoot'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSubscript'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathWildcard'>: <function <lambda>>, <class 'sqlglot.expressions.AllowedValuesProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.BackupProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CaseSpecificColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CollateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CommentColumnConstraint'>: <function no_comment_column_constraint_sql>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DateFormatColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DefaultColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EncodeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EphemeralColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExcludeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExternalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.GlobalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.HeapProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IcebergProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InheritsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InlineLengthColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IntervalSpan'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtract'>: <function _arrow_json_extract_sql>, <class 'sqlglot.expressions.JSONExtractScalar'>: <function _arrow_json_extract_sql>, <class 'sqlglot.expressions.LanguageProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LocationProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LogProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.MaterializedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NonClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NotForReplicationColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnCommitProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnUpdateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OutputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.PathColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ReturnsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SampleProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetConfigProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SettingsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SharingProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlReadWriteProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlSecurityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StabilityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StrictProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TemporaryProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TitleColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.Timestamp'>: <function no_timestamp_sql>, <class 'sqlglot.expressions.ToMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransformModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransientProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UppercaseColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UnloggedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VarMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VolatileProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithOperator'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ApproxDistinct'>: <function approx_count_distinct_sql>, <class 'sqlglot.expressions.Array'>: <function inline_array_unless_query>, <class 'sqlglot.expressions.ArrayFilter'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ArraySize'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ArgMax'>: <function arg_max_or_min_no_count.<locals>._arg_max_or_min_sql>, <class 'sqlglot.expressions.ArgMin'>: <function arg_max_or_min_no_count.<locals>._arg_max_or_min_sql>, <class 'sqlglot.expressions.ArraySort'>: <function _array_sort_sql>, <class 'sqlglot.expressions.ArraySum'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.BitwiseXor'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.CurrentDate'>: <function DuckDB.Generator.<lambda>>, <class 'sqlglot.expressions.CurrentTime'>: <function DuckDB.Generator.<lambda>>, <class 'sqlglot.expressions.CurrentTimestamp'>: <function DuckDB.Generator.<lambda>>, <class 'sqlglot.expressions.DayOfMonth'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.DayOfWeek'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.DayOfYear'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.DataType'>: <function _datatype_sql>, <class 'sqlglot.expressions.Date'>: <function _date_sql>, <class 'sqlglot.expressions.DateAdd'>: <function _date_delta_sql>, <class 'sqlglot.expressions.DateFromParts'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.DateSub'>: <function _date_delta_sql>, <class 'sqlglot.expressions.DateDiff'>: <function DuckDB.Generator.<lambda>>, <class 'sqlglot.expressions.DateStrToDate'>: <function datestrtodate_sql>, <class 'sqlglot.expressions.DateToDi'>: <function DuckDB.Generator.<lambda>>, <class 'sqlglot.expressions.Decode'>: <function DuckDB.Generator.<lambda>>, <class 'sqlglot.expressions.DiToDate'>: <function DuckDB.Generator.<lambda>>, <class 'sqlglot.expressions.Encode'>: <function DuckDB.Generator.<lambda>>, <class 'sqlglot.expressions.Explode'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.IntDiv'>: <function DuckDB.Generator.<lambda>>, <class 'sqlglot.expressions.IsInf'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.IsNan'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.JSONFormat'>: <function _json_format_sql>, <class 'sqlglot.expressions.LogicalOr'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.LogicalAnd'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.MD5Digest'>: <function DuckDB.Generator.<lambda>>, <class 'sqlglot.expressions.MonthsBetween'>: <function DuckDB.Generator.<lambda>>, <class 'sqlglot.expressions.ParseJSON'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.PercentileCont'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.PercentileDisc'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.Pivot'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.RegexpExtract'>: <function regexp_extract_sql>, <class 'sqlglot.expressions.RegexpReplace'>: <function DuckDB.Generator.<lambda>>, <class 'sqlglot.expressions.RegexpLike'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.RegexpSplit'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.Rand'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.SafeDivide'>: <function no_safe_divide_sql>, <class 'sqlglot.expressions.Split'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.SortArray'>: <function _sort_array_sql>, <class 'sqlglot.expressions.StrPosition'>: <function str_position_sql>, <class 'sqlglot.expressions.StrToDate'>: <function DuckDB.Generator.<lambda>>, <class 'sqlglot.expressions.StrToTime'>: <function str_to_time_sql>, <class 'sqlglot.expressions.StrToUnix'>: <function DuckDB.Generator.<lambda>>, <class 'sqlglot.expressions.Struct'>: <function _struct_sql>, <class 'sqlglot.expressions.TimeAdd'>: <function _date_delta_sql>, <class 'sqlglot.expressions.TimestampDiff'>: <function DuckDB.Generator.<lambda>>, <class 'sqlglot.expressions.TimestampTrunc'>: <function timestamptrunc_sql.<locals>._timestamptrunc_sql>, <class 'sqlglot.expressions.TimeStrToDate'>: <function DuckDB.Generator.<lambda>>, <class 'sqlglot.expressions.TimeStrToTime'>: <function timestrtotime_sql>, <class 'sqlglot.expressions.TimeStrToUnix'>: <function DuckDB.Generator.<lambda>>, <class 'sqlglot.expressions.TimeToStr'>: <function DuckDB.Generator.<lambda>>, <class 'sqlglot.expressions.TimeToUnix'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.TsOrDiToDi'>: <function DuckDB.Generator.<lambda>>, <class 'sqlglot.expressions.TsOrDsAdd'>: <function _ts_or_ds_add_sql>, <class 'sqlglot.expressions.TsOrDsDiff'>: <function DuckDB.Generator.<lambda>>, <class 'sqlglot.expressions.UnixToStr'>: <function DuckDB.Generator.<lambda>>, <class 'sqlglot.expressions.UnixToTime'>: <function _unix_to_time_sql>, <class 'sqlglot.expressions.UnixToTimeStr'>: <function DuckDB.Generator.<lambda>>, <class 'sqlglot.expressions.VariancePop'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.WeekOfYear'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.Xor'>: <function bool_xor_sql>}"}, "sqlglot.dialects.duckdb.DuckDB.Generator.SUPPORTED_JSON_PATH_PARTS": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.SUPPORTED_JSON_PATH_PARTS", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.SUPPORTED_JSON_PATH_PARTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.JSONPathWildcard'>, <class 'sqlglot.expressions.JSONPathSubscript'>, <class 'sqlglot.expressions.JSONPathRoot'>, <class 'sqlglot.expressions.JSONPathKey'>}"}, "sqlglot.dialects.duckdb.DuckDB.Generator.TYPE_MAPPING": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.TYPE_MAPPING", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.TYPE_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.NCHAR: 'NCHAR'>: 'TEXT', <Type.NVARCHAR: 'NVARCHAR'>: 'TEXT', <Type.MEDIUMTEXT: 'MEDIUMTEXT'>: 'TEXT', <Type.LONGTEXT: 'LONGTEXT'>: 'TEXT', <Type.TINYTEXT: 'TINYTEXT'>: 'TEXT', <Type.MEDIUMBLOB: 'MEDIUMBLOB'>: 'BLOB', <Type.LONGBLOB: 'LONGBLOB'>: 'BLOB', <Type.TINYBLOB: 'TINYBLOB'>: 'BLOB', <Type.INET: 'INET'>: 'INET', <Type.ROWVERSION: 'ROWVERSION'>: 'BLOB', <Type.BINARY: 'BINARY'>: 'BLOB', <Type.CHAR: 'CHAR'>: 'TEXT', <Type.FLOAT: 'FLOAT'>: 'REAL', <Type.UINT: 'UINT'>: 'UINTEGER', <Type.VARBINARY: 'VARBINARY'>: 'BLOB', <Type.VARCHAR: 'VARCHAR'>: 'TEXT', <Type.TIMESTAMP_S: 'TIMESTAMP_S'>: 'TIMESTAMP_S', <Type.TIMESTAMP_MS: 'TIMESTAMP_MS'>: 'TIMESTAMP_MS', <Type.TIMESTAMP_NS: 'TIMESTAMP_NS'>: 'TIMESTAMP_NS'}"}, "sqlglot.dialects.duckdb.DuckDB.Generator.UNWRAPPED_INTERVAL_VALUES": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.UNWRAPPED_INTERVAL_VALUES", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.UNWRAPPED_INTERVAL_VALUES", "kind": "variable", "doc": "<p></p>\n", "default_value": "(<class 'sqlglot.expressions.Literal'>, <class 'sqlglot.expressions.Paren'>)"}, "sqlglot.dialects.duckdb.DuckDB.Generator.PROPERTIES_LOCATION": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.PROPERTIES_LOCATION", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.PROPERTIES_LOCATION", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.AllowedValuesProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.AlgorithmProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.AutoIncrementProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.BackupProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.BlockCompressionProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.CharacterSetProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.ChecksumProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.CollateProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.Cluster'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.ClusteredByProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.DataBlocksizeProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.DataDeletionProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.DefinerProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.DictRange'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.DictProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.DistKeyProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.DistStyleProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.EngineProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.ExternalProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.FallbackProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.FileFormatProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.FreespaceProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.GlobalProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.HeapProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.InheritsProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.IcebergProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.InputModelProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.IsolatedLoadingProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.JournalProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.LanguageProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.LikeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LocationProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.LockProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.LockingProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.LogProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.MaterializedProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.MergeBlockRatioProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.OnProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.OnCommitProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.Order'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.OutputModelProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.PartitionedByProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.PartitionedOfProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.PrimaryKey'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.Property'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.ReturnsProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.RowFormatProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.RowFormatDelimitedProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.RowFormatSerdeProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.SampleProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.SchemaCommentProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.SerdeProperties'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.Set'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.SettingsProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.SetProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.SetConfigProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.SharingProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.SequenceProperties'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.SortKeyProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.SqlReadWriteProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.SqlSecurityProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.StabilityProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.StrictProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.TemporaryProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.ToTableProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.TransientProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.TransformModelProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.MergeTreeTTL'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.UnloggedProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.VolatileProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.WithDataProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.WithSystemVersioningProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>}"}, "sqlglot.dialects.duckdb.DuckDB.Generator.timefromparts_sql": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.timefromparts_sql", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.timefromparts_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TimeFromParts</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.duckdb.DuckDB.Generator.timestampfromparts_sql": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.timestampfromparts_sql", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.timestampfromparts_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TimestampFromParts</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.duckdb.DuckDB.Generator.tablesample_sql": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.tablesample_sql", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.tablesample_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TableSample</span>,</span><span class=\"param\">\t<span class=\"n\">sep</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">' AS '</span>,</span><span class=\"param\">\t<span class=\"n\">tablesample_keyword</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.duckdb.DuckDB.Generator.interval_sql": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.interval_sql", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.interval_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Interval</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.duckdb.DuckDB.Generator.columndef_sql": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.columndef_sql", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.columndef_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ColumnDef</span>, </span><span class=\"param\"><span class=\"n\">sep</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">' '</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.duckdb.DuckDB.Generator.join_sql": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.join_sql", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.join_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Join</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.duckdb.DuckDB.Generator.generateseries_sql": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.generateseries_sql", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.generateseries_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">GenerateSeries</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.duckdb.DuckDB.Generator.bracket_sql": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.bracket_sql", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.bracket_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Bracket</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.duckdb.DuckDB.Generator.withingroup_sql": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.withingroup_sql", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.withingroup_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">WithinGroup</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.duckdb.DuckDB.Generator.SELECT_KINDS": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.SELECT_KINDS", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.SELECT_KINDS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Tuple[str, ...]", "default_value": "()"}, "sqlglot.dialects.duckdb.DuckDB.Generator.TRY_SUPPORTED": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.TRY_SUPPORTED", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.TRY_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.duckdb.DuckDB.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS": {"fullname": "sqlglot.dialects.duckdb.DuckDB.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'qualify': <function Generator.<lambda>>, 'windows': <function Generator.<lambda>>}"}, "sqlglot.dialects.duckdb.DuckDB.tokenizer_class": {"fullname": "sqlglot.dialects.duckdb.DuckDB.tokenizer_class", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.tokenizer_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.duckdb.DuckDB.Tokenizer'>"}, "sqlglot.dialects.duckdb.DuckDB.parser_class": {"fullname": "sqlglot.dialects.duckdb.DuckDB.parser_class", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.parser_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.duckdb.DuckDB.Parser'>"}, "sqlglot.dialects.duckdb.DuckDB.generator_class": {"fullname": "sqlglot.dialects.duckdb.DuckDB.generator_class", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.generator_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.duckdb.DuckDB.Generator'>"}, "sqlglot.dialects.duckdb.DuckDB.TIME_TRIE": {"fullname": "sqlglot.dialects.duckdb.DuckDB.TIME_TRIE", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.duckdb.DuckDB.FORMAT_TRIE": {"fullname": "sqlglot.dialects.duckdb.DuckDB.FORMAT_TRIE", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.FORMAT_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.duckdb.DuckDB.INVERSE_TIME_MAPPING": {"fullname": "sqlglot.dialects.duckdb.DuckDB.INVERSE_TIME_MAPPING", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.INVERSE_TIME_MAPPING", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{}"}, "sqlglot.dialects.duckdb.DuckDB.INVERSE_TIME_TRIE": {"fullname": "sqlglot.dialects.duckdb.DuckDB.INVERSE_TIME_TRIE", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.INVERSE_TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.duckdb.DuckDB.ESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.duckdb.DuckDB.ESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.ESCAPED_SEQUENCES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{}"}, "sqlglot.dialects.duckdb.DuckDB.QUOTE_START": {"fullname": "sqlglot.dialects.duckdb.DuckDB.QUOTE_START", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.QUOTE_START", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.duckdb.DuckDB.QUOTE_END": {"fullname": "sqlglot.dialects.duckdb.DuckDB.QUOTE_END", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.QUOTE_END", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.duckdb.DuckDB.IDENTIFIER_START": {"fullname": "sqlglot.dialects.duckdb.DuckDB.IDENTIFIER_START", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.IDENTIFIER_START", "kind": "variable", "doc": "<p></p>\n", "default_value": "'"'"}, "sqlglot.dialects.duckdb.DuckDB.IDENTIFIER_END": {"fullname": "sqlglot.dialects.duckdb.DuckDB.IDENTIFIER_END", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.IDENTIFIER_END", "kind": "variable", "doc": "<p></p>\n", "default_value": "'"'"}, "sqlglot.dialects.duckdb.DuckDB.BIT_START": {"fullname": "sqlglot.dialects.duckdb.DuckDB.BIT_START", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.BIT_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.duckdb.DuckDB.BIT_END": {"fullname": "sqlglot.dialects.duckdb.DuckDB.BIT_END", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.BIT_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.duckdb.DuckDB.HEX_START": {"fullname": "sqlglot.dialects.duckdb.DuckDB.HEX_START", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.HEX_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.duckdb.DuckDB.HEX_END": {"fullname": "sqlglot.dialects.duckdb.DuckDB.HEX_END", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.HEX_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.duckdb.DuckDB.BYTE_START": {"fullname": "sqlglot.dialects.duckdb.DuckDB.BYTE_START", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.BYTE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.duckdb.DuckDB.BYTE_END": {"fullname": "sqlglot.dialects.duckdb.DuckDB.BYTE_END", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.BYTE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.duckdb.DuckDB.UNICODE_START": {"fullname": "sqlglot.dialects.duckdb.DuckDB.UNICODE_START", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.UNICODE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.duckdb.DuckDB.UNICODE_END": {"fullname": "sqlglot.dialects.duckdb.DuckDB.UNICODE_END", "modulename": "sqlglot.dialects.duckdb", "qualname": "DuckDB.UNICODE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.hive": {"fullname": "sqlglot.dialects.hive", "modulename": "sqlglot.dialects.hive", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.dialects.hive.DATE_DELTA_INTERVAL": {"fullname": "sqlglot.dialects.hive.DATE_DELTA_INTERVAL", "modulename": "sqlglot.dialects.hive", "qualname": "DATE_DELTA_INTERVAL", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'YEAR': ('ADD_MONTHS', 12), 'MONTH': ('ADD_MONTHS', 1), 'QUARTER': ('ADD_MONTHS', 3), 'WEEK': ('DATE_ADD', 7), 'DAY': ('DATE_ADD', 1)}"}, "sqlglot.dialects.hive.TIME_DIFF_FACTOR": {"fullname": "sqlglot.dialects.hive.TIME_DIFF_FACTOR", "modulename": "sqlglot.dialects.hive", "qualname": "TIME_DIFF_FACTOR", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'MILLISECOND': ' * 1000', 'SECOND': '', 'MINUTE': ' / 60', 'HOUR': ' / 3600'}"}, "sqlglot.dialects.hive.DIFF_MONTH_SWITCH": {"fullname": "sqlglot.dialects.hive.DIFF_MONTH_SWITCH", "modulename": "sqlglot.dialects.hive", "qualname": "DIFF_MONTH_SWITCH", "kind": "variable", "doc": "<p></p>\n", "default_value": "('YEAR', 'QUARTER', 'MONTH')"}, "sqlglot.dialects.hive.Hive": {"fullname": "sqlglot.dialects.hive.Hive", "modulename": "sqlglot.dialects.hive", "qualname": "Hive", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.dialect.Dialect"}, "sqlglot.dialects.hive.Hive.ALIAS_POST_TABLESAMPLE": {"fullname": "sqlglot.dialects.hive.Hive.ALIAS_POST_TABLESAMPLE", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.ALIAS_POST_TABLESAMPLE", "kind": "variable", "doc": "<p>Whether the table alias comes after tablesample.</p>\n", "default_value": "True"}, "sqlglot.dialects.hive.Hive.IDENTIFIERS_CAN_START_WITH_DIGIT": {"fullname": "sqlglot.dialects.hive.Hive.IDENTIFIERS_CAN_START_WITH_DIGIT", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.IDENTIFIERS_CAN_START_WITH_DIGIT", "kind": "variable", "doc": "<p>Whether an unquoted identifier can start with a digit.</p>\n", "default_value": "True"}, "sqlglot.dialects.hive.Hive.SUPPORTS_USER_DEFINED_TYPES": {"fullname": "sqlglot.dialects.hive.Hive.SUPPORTS_USER_DEFINED_TYPES", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.SUPPORTS_USER_DEFINED_TYPES", "kind": "variable", "doc": "<p>Whether user-defined data types are supported.</p>\n", "default_value": "False"}, "sqlglot.dialects.hive.Hive.SAFE_DIVISION": {"fullname": "sqlglot.dialects.hive.Hive.SAFE_DIVISION", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.SAFE_DIVISION", "kind": "variable", "doc": "<p>Whether division by zero throws an error (<code>False</code>) or returns NULL (<code>True</code>).</p>\n", "default_value": "True"}, "sqlglot.dialects.hive.Hive.NORMALIZATION_STRATEGY": {"fullname": "sqlglot.dialects.hive.Hive.NORMALIZATION_STRATEGY", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.NORMALIZATION_STRATEGY", "kind": "variable", "doc": "<p>Specifies the strategy according to which identifiers should be normalized.</p>\n", "default_value": "<NormalizationStrategy.CASE_INSENSITIVE: 'CASE_INSENSITIVE'>"}, "sqlglot.dialects.hive.Hive.TIME_MAPPING": {"fullname": "sqlglot.dialects.hive.Hive.TIME_MAPPING", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.TIME_MAPPING", "kind": "variable", "doc": "<p>Associates this dialect's time formats with their equivalent Python <code>strftime</code> formats.</p>\n", "annotation": ": Dict[str, str]", "default_value": "{'y': '%Y', 'Y': '%Y', 'YYYY': '%Y', 'yyyy': '%Y', 'YY': '%y', 'yy': '%y', 'MMMM': '%B', 'MMM': '%b', 'MM': '%m', 'M': '%-m', 'dd': '%d', 'd': '%-d', 'HH': '%H', 'H': '%-H', 'hh': '%I', 'h': '%-I', 'mm': '%M', 'm': '%-M', 'ss': '%S', 's': '%-S', 'SSSSSS': '%f', 'a': '%p', 'DD': '%j', 'D': '%-j', 'E': '%a', 'EE': '%a', 'EEE': '%a', 'EEEE': '%A'}"}, "sqlglot.dialects.hive.Hive.DATE_FORMAT": {"fullname": "sqlglot.dialects.hive.Hive.DATE_FORMAT", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.DATE_FORMAT", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'yyyy-MM-dd'""}, "sqlglot.dialects.hive.Hive.DATEINT_FORMAT": {"fullname": "sqlglot.dialects.hive.Hive.DATEINT_FORMAT", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.DATEINT_FORMAT", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'yyyyMMdd'""}, "sqlglot.dialects.hive.Hive.TIME_FORMAT": {"fullname": "sqlglot.dialects.hive.Hive.TIME_FORMAT", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.TIME_FORMAT", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'yyyy-MM-dd HH:mm:ss'""}, "sqlglot.dialects.hive.Hive.Tokenizer": {"fullname": "sqlglot.dialects.hive.Hive.Tokenizer", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Tokenizer", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.tokens.Tokenizer"}, "sqlglot.dialects.hive.Hive.Tokenizer.QUOTES": {"fullname": "sqlglot.dialects.hive.Hive.Tokenizer.QUOTES", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Tokenizer.QUOTES", "kind": "variable", "doc": "<p></p>\n", "default_value": "["'", '"']"}, "sqlglot.dialects.hive.Hive.Tokenizer.IDENTIFIERS": {"fullname": "sqlglot.dialects.hive.Hive.Tokenizer.IDENTIFIERS", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Tokenizer.IDENTIFIERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "['`']"}, "sqlglot.dialects.hive.Hive.Tokenizer.STRING_ESCAPES": {"fullname": "sqlglot.dialects.hive.Hive.Tokenizer.STRING_ESCAPES", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Tokenizer.STRING_ESCAPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "['\\\\']"}, "sqlglot.dialects.hive.Hive.Tokenizer.SINGLE_TOKENS": {"fullname": "sqlglot.dialects.hive.Hive.Tokenizer.SINGLE_TOKENS", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Tokenizer.SINGLE_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'(': <TokenType.L_PAREN: 'L_PAREN'>, ')': <TokenType.R_PAREN: 'R_PAREN'>, '[': <TokenType.L_BRACKET: 'L_BRACKET'>, ']': <TokenType.R_BRACKET: 'R_BRACKET'>, '{': <TokenType.L_BRACE: 'L_BRACE'>, '}': <TokenType.R_BRACE: 'R_BRACE'>, '&': <TokenType.AMP: 'AMP'>, '^': <TokenType.CARET: 'CARET'>, ':': <TokenType.COLON: 'COLON'>, ',': <TokenType.COMMA: 'COMMA'>, '.': <TokenType.DOT: 'DOT'>, '-': <TokenType.DASH: 'DASH'>, '=': <TokenType.EQ: 'EQ'>, '>': <TokenType.GT: 'GT'>, '<': <TokenType.LT: 'LT'>, '%': <TokenType.MOD: 'MOD'>, '!': <TokenType.NOT: 'NOT'>, '|': <TokenType.PIPE: 'PIPE'>, '+': <TokenType.PLUS: 'PLUS'>, ';': <TokenType.SEMICOLON: 'SEMICOLON'>, '/': <TokenType.SLASH: 'SLASH'>, '\\\\': <TokenType.BACKSLASH: 'BACKSLASH'>, '*': <TokenType.STAR: 'STAR'>, '~': <TokenType.TILDA: 'TILDA'>, '?': <TokenType.PLACEHOLDER: 'PLACEHOLDER'>, '@': <TokenType.PARAMETER: 'PARAMETER'>, '#': <TokenType.HASH: 'HASH'>, "'": <TokenType.UNKNOWN: 'UNKNOWN'>, '`': <TokenType.UNKNOWN: 'UNKNOWN'>, '"': <TokenType.UNKNOWN: 'UNKNOWN'>, '$': <TokenType.PARAMETER: 'PARAMETER'>}"}, "sqlglot.dialects.hive.Hive.Tokenizer.KEYWORDS": {"fullname": "sqlglot.dialects.hive.Hive.Tokenizer.KEYWORDS", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Tokenizer.KEYWORDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'{%': <TokenType.BLOCK_START: 'BLOCK_START'>, '{%+': <TokenType.BLOCK_START: 'BLOCK_START'>, '{%-': <TokenType.BLOCK_START: 'BLOCK_START'>, '%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '+%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '-%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '{{+': <TokenType.BLOCK_START: 'BLOCK_START'>, '{{-': <TokenType.BLOCK_START: 'BLOCK_START'>, '+}}': <TokenType.BLOCK_END: 'BLOCK_END'>, '-}}': <TokenType.BLOCK_END: 'BLOCK_END'>, '/*+': <TokenType.HINT: 'HINT'>, '==': <TokenType.EQ: 'EQ'>, '::': <TokenType.DCOLON: 'DCOLON'>, '||': <TokenType.DPIPE: 'DPIPE'>, '>=': <TokenType.GTE: 'GTE'>, '<=': <TokenType.LTE: 'LTE'>, '<>': <TokenType.NEQ: 'NEQ'>, '!=': <TokenType.NEQ: 'NEQ'>, ':=': <TokenType.COLON_EQ: 'COLON_EQ'>, '<=>': <TokenType.NULLSAFE_EQ: 'NULLSAFE_EQ'>, '->': <TokenType.ARROW: 'ARROW'>, '->>': <TokenType.DARROW: 'DARROW'>, '=>': <TokenType.FARROW: 'FARROW'>, '#>': <TokenType.HASH_ARROW: 'HASH_ARROW'>, '#>>': <TokenType.DHASH_ARROW: 'DHASH_ARROW'>, '<->': <TokenType.LR_ARROW: 'LR_ARROW'>, '&&': <TokenType.DAMP: 'DAMP'>, '??': <TokenType.DQMARK: 'DQMARK'>, 'ALL': <TokenType.ALL: 'ALL'>, 'ALWAYS': <TokenType.ALWAYS: 'ALWAYS'>, 'AND': <TokenType.AND: 'AND'>, 'ANTI': <TokenType.ANTI: 'ANTI'>, 'ANY': <TokenType.ANY: 'ANY'>, 'ASC': <TokenType.ASC: 'ASC'>, 'AS': <TokenType.ALIAS: 'ALIAS'>, 'ASOF': <TokenType.ASOF: 'ASOF'>, 'AUTOINCREMENT': <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, 'AUTO_INCREMENT': <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, 'BEGIN': <TokenType.BEGIN: 'BEGIN'>, 'BETWEEN': <TokenType.BETWEEN: 'BETWEEN'>, 'CACHE': <TokenType.CACHE: 'CACHE'>, 'UNCACHE': <TokenType.UNCACHE: 'UNCACHE'>, 'CASE': <TokenType.CASE: 'CASE'>, 'CHARACTER SET': <TokenType.CHARACTER_SET: 'CHARACTER_SET'>, 'CLUSTER BY': <TokenType.CLUSTER_BY: 'CLUSTER_BY'>, 'COLLATE': <TokenType.COLLATE: 'COLLATE'>, 'COLUMN': <TokenType.COLUMN: 'COLUMN'>, 'COMMIT': <TokenType.COMMIT: 'COMMIT'>, 'CONNECT BY': <TokenType.CONNECT_BY: 'CONNECT_BY'>, 'CONSTRAINT': <TokenType.CONSTRAINT: 'CONSTRAINT'>, 'COPY': <TokenType.COPY: 'COPY'>, 'CREATE': <TokenType.CREATE: 'CREATE'>, 'CROSS': <TokenType.CROSS: 'CROSS'>, 'CUBE': <TokenType.CUBE: 'CUBE'>, 'CURRENT_DATE': <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, 'CURRENT_TIME': <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, 'CURRENT_TIMESTAMP': <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, 'CURRENT_USER': <TokenType.CURRENT_USER: 'CURRENT_USER'>, 'DATABASE': <TokenType.DATABASE: 'DATABASE'>, 'DEFAULT': <TokenType.DEFAULT: 'DEFAULT'>, 'DELETE': <TokenType.DELETE: 'DELETE'>, 'DESC': <TokenType.DESC: 'DESC'>, 'DESCRIBE': <TokenType.DESCRIBE: 'DESCRIBE'>, 'DISTINCT': <TokenType.DISTINCT: 'DISTINCT'>, 'DISTRIBUTE BY': <TokenType.DISTRIBUTE_BY: 'DISTRIBUTE_BY'>, 'DIV': <TokenType.DIV: 'DIV'>, 'DROP': <TokenType.DROP: 'DROP'>, 'ELSE': <TokenType.ELSE: 'ELSE'>, 'END': <TokenType.END: 'END'>, 'ENUM': <TokenType.ENUM: 'ENUM'>, 'ESCAPE': <TokenType.ESCAPE: 'ESCAPE'>, 'EXCEPT': <TokenType.EXCEPT: 'EXCEPT'>, 'EXECUTE': <TokenType.EXECUTE: 'EXECUTE'>, 'EXISTS': <TokenType.EXISTS: 'EXISTS'>, 'FALSE': <TokenType.FALSE: 'FALSE'>, 'FETCH': <TokenType.FETCH: 'FETCH'>, 'FILTER': <TokenType.FILTER: 'FILTER'>, 'FIRST': <TokenType.FIRST: 'FIRST'>, 'FULL': <TokenType.FULL: 'FULL'>, 'FUNCTION': <TokenType.FUNCTION: 'FUNCTION'>, 'FOR': <TokenType.FOR: 'FOR'>, 'FOREIGN KEY': <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, 'FORMAT': <TokenType.FORMAT: 'FORMAT'>, 'FROM': <TokenType.FROM: 'FROM'>, 'GEOGRAPHY': <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, 'GEOMETRY': <TokenType.GEOMETRY: 'GEOMETRY'>, 'GLOB': <TokenType.GLOB: 'GLOB'>, 'GROUP BY': <TokenType.GROUP_BY: 'GROUP_BY'>, 'GROUPING SETS': <TokenType.GROUPING_SETS: 'GROUPING_SETS'>, 'HAVING': <TokenType.HAVING: 'HAVING'>, 'ILIKE': <TokenType.ILIKE: 'ILIKE'>, 'IN': <TokenType.IN: 'IN'>, 'INDEX': <TokenType.INDEX: 'INDEX'>, 'INET': <TokenType.INET: 'INET'>, 'INNER': <TokenType.INNER: 'INNER'>, 'INSERT': <TokenType.INSERT: 'INSERT'>, 'INTERVAL': <TokenType.INTERVAL: 'INTERVAL'>, 'INTERSECT': <TokenType.INTERSECT: 'INTERSECT'>, 'INTO': <TokenType.INTO: 'INTO'>, 'IS': <TokenType.IS: 'IS'>, 'ISNULL': <TokenType.ISNULL: 'ISNULL'>, 'JOIN': <TokenType.JOIN: 'JOIN'>, 'KEEP': <TokenType.KEEP: 'KEEP'>, 'KILL': <TokenType.KILL: 'KILL'>, 'LATERAL': <TokenType.LATERAL: 'LATERAL'>, 'LEFT': <TokenType.LEFT: 'LEFT'>, 'LIKE': <TokenType.LIKE: 'LIKE'>, 'LIMIT': <TokenType.LIMIT: 'LIMIT'>, 'LOAD': <TokenType.LOAD: 'LOAD'>, 'LOCK': <TokenType.LOCK: 'LOCK'>, 'MERGE': <TokenType.MERGE: 'MERGE'>, 'NATURAL': <TokenType.NATURAL: 'NATURAL'>, 'NEXT': <TokenType.NEXT: 'NEXT'>, 'NOT': <TokenType.NOT: 'NOT'>, 'NOTNULL': <TokenType.NOTNULL: 'NOTNULL'>, 'NULL': <TokenType.NULL: 'NULL'>, 'OBJECT': <TokenType.OBJECT: 'OBJECT'>, 'OFFSET': <TokenType.OFFSET: 'OFFSET'>, 'ON': <TokenType.ON: 'ON'>, 'OR': <TokenType.OR: 'OR'>, 'XOR': <TokenType.XOR: 'XOR'>, 'ORDER BY': <TokenType.ORDER_BY: 'ORDER_BY'>, 'ORDINALITY': <TokenType.ORDINALITY: 'ORDINALITY'>, 'OUTER': <TokenType.OUTER: 'OUTER'>, 'OVER': <TokenType.OVER: 'OVER'>, 'OVERLAPS': <TokenType.OVERLAPS: 'OVERLAPS'>, 'OVERWRITE': <TokenType.OVERWRITE: 'OVERWRITE'>, 'PARTITION': <TokenType.PARTITION: 'PARTITION'>, 'PARTITION BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PARTITIONED BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PARTITIONED_BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PERCENT': <TokenType.PERCENT: 'PERCENT'>, 'PIVOT': <TokenType.PIVOT: 'PIVOT'>, 'PRAGMA': <TokenType.PRAGMA: 'PRAGMA'>, 'PRIMARY KEY': <TokenType.PRIMARY_KEY: 'PRIMARY_KEY'>, 'PROCEDURE': <TokenType.PROCEDURE: 'PROCEDURE'>, 'QUALIFY': <TokenType.QUALIFY: 'QUALIFY'>, 'RANGE': <TokenType.RANGE: 'RANGE'>, 'RECURSIVE': <TokenType.RECURSIVE: 'RECURSIVE'>, 'REGEXP': <TokenType.RLIKE: 'RLIKE'>, 'REPLACE': <TokenType.REPLACE: 'REPLACE'>, 'RETURNING': <TokenType.RETURNING: 'RETURNING'>, 'REFERENCES': <TokenType.REFERENCES: 'REFERENCES'>, 'RIGHT': <TokenType.RIGHT: 'RIGHT'>, 'RLIKE': <TokenType.RLIKE: 'RLIKE'>, 'ROLLBACK': <TokenType.ROLLBACK: 'ROLLBACK'>, 'ROLLUP': <TokenType.ROLLUP: 'ROLLUP'>, 'ROW': <TokenType.ROW: 'ROW'>, 'ROWS': <TokenType.ROWS: 'ROWS'>, 'SCHEMA': <TokenType.SCHEMA: 'SCHEMA'>, 'SELECT': <TokenType.SELECT: 'SELECT'>, 'SEMI': <TokenType.SEMI: 'SEMI'>, 'SET': <TokenType.SET: 'SET'>, 'SETTINGS': <TokenType.SETTINGS: 'SETTINGS'>, 'SHOW': <TokenType.SHOW: 'SHOW'>, 'SIMILAR TO': <TokenType.SIMILAR_TO: 'SIMILAR_TO'>, 'SOME': <TokenType.SOME: 'SOME'>, 'SORT BY': <TokenType.SORT_BY: 'SORT_BY'>, 'START WITH': <TokenType.START_WITH: 'START_WITH'>, 'TABLE': <TokenType.TABLE: 'TABLE'>, 'TABLESAMPLE': <TokenType.TABLE_SAMPLE: 'TABLE_SAMPLE'>, 'TEMP': <TokenType.TEMPORARY: 'TEMPORARY'>, 'TEMPORARY': <TokenType.TEMPORARY: 'TEMPORARY'>, 'THEN': <TokenType.THEN: 'THEN'>, 'TRUE': <TokenType.TRUE: 'TRUE'>, 'TRUNCATE': <TokenType.TRUNCATE: 'TRUNCATE'>, 'UNION': <TokenType.UNION: 'UNION'>, 'UNKNOWN': <TokenType.UNKNOWN: 'UNKNOWN'>, 'UNNEST': <TokenType.UNNEST: 'UNNEST'>, 'UNPIVOT': <TokenType.UNPIVOT: 'UNPIVOT'>, 'UPDATE': <TokenType.UPDATE: 'UPDATE'>, 'USE': <TokenType.USE: 'USE'>, 'USING': <TokenType.USING: 'USING'>, 'UUID': <TokenType.UUID: 'UUID'>, 'VALUES': <TokenType.VALUES: 'VALUES'>, 'VIEW': <TokenType.VIEW: 'VIEW'>, 'VOLATILE': <TokenType.VOLATILE: 'VOLATILE'>, 'WHEN': <TokenType.WHEN: 'WHEN'>, 'WHERE': <TokenType.WHERE: 'WHERE'>, 'WINDOW': <TokenType.WINDOW: 'WINDOW'>, 'WITH': <TokenType.WITH: 'WITH'>, 'APPLY': <TokenType.APPLY: 'APPLY'>, 'ARRAY': <TokenType.ARRAY: 'ARRAY'>, 'BIT': <TokenType.BIT: 'BIT'>, 'BOOL': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BOOLEAN': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BYTE': <TokenType.TINYINT: 'TINYINT'>, 'MEDIUMINT': <TokenType.MEDIUMINT: 'MEDIUMINT'>, 'INT1': <TokenType.TINYINT: 'TINYINT'>, 'TINYINT': <TokenType.TINYINT: 'TINYINT'>, 'INT16': <TokenType.SMALLINT: 'SMALLINT'>, 'SHORT': <TokenType.SMALLINT: 'SMALLINT'>, 'SMALLINT': <TokenType.SMALLINT: 'SMALLINT'>, 'INT128': <TokenType.INT128: 'INT128'>, 'HUGEINT': <TokenType.INT128: 'INT128'>, 'INT2': <TokenType.SMALLINT: 'SMALLINT'>, 'INTEGER': <TokenType.INT: 'INT'>, 'INT': <TokenType.INT: 'INT'>, 'INT4': <TokenType.INT: 'INT'>, 'INT32': <TokenType.INT: 'INT'>, 'INT64': <TokenType.BIGINT: 'BIGINT'>, 'LONG': <TokenType.BIGINT: 'BIGINT'>, 'BIGINT': <TokenType.BIGINT: 'BIGINT'>, 'INT8': <TokenType.TINYINT: 'TINYINT'>, 'UINT': <TokenType.UINT: 'UINT'>, 'DEC': <TokenType.DECIMAL: 'DECIMAL'>, 'DECIMAL': <TokenType.DECIMAL: 'DECIMAL'>, 'BIGDECIMAL': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'BIGNUMERIC': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'MAP': <TokenType.MAP: 'MAP'>, 'NULLABLE': <TokenType.NULLABLE: 'NULLABLE'>, 'NUMBER': <TokenType.DECIMAL: 'DECIMAL'>, 'NUMERIC': <TokenType.DECIMAL: 'DECIMAL'>, 'FIXED': <TokenType.DECIMAL: 'DECIMAL'>, 'REAL': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT4': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT8': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE PRECISION': <TokenType.DOUBLE: 'DOUBLE'>, 'JSON': <TokenType.JSON: 'JSON'>, 'CHAR': <TokenType.CHAR: 'CHAR'>, 'CHARACTER': <TokenType.CHAR: 'CHAR'>, 'NCHAR': <TokenType.NCHAR: 'NCHAR'>, 'VARCHAR': <TokenType.VARCHAR: 'VARCHAR'>, 'VARCHAR2': <TokenType.VARCHAR: 'VARCHAR'>, 'NVARCHAR': <TokenType.NVARCHAR: 'NVARCHAR'>, 'NVARCHAR2': <TokenType.NVARCHAR: 'NVARCHAR'>, 'BPCHAR': <TokenType.BPCHAR: 'BPCHAR'>, 'STR': <TokenType.TEXT: 'TEXT'>, 'STRING': <TokenType.TEXT: 'TEXT'>, 'TEXT': <TokenType.TEXT: 'TEXT'>, 'LONGTEXT': <TokenType.LONGTEXT: 'LONGTEXT'>, 'MEDIUMTEXT': <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, 'TINYTEXT': <TokenType.TINYTEXT: 'TINYTEXT'>, 'CLOB': <TokenType.TEXT: 'TEXT'>, 'LONGVARCHAR': <TokenType.TEXT: 'TEXT'>, 'BINARY': <TokenType.BINARY: 'BINARY'>, 'BLOB': <TokenType.VARBINARY: 'VARBINARY'>, 'LONGBLOB': <TokenType.LONGBLOB: 'LONGBLOB'>, 'MEDIUMBLOB': <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, 'TINYBLOB': <TokenType.TINYBLOB: 'TINYBLOB'>, 'BYTEA': <TokenType.VARBINARY: 'VARBINARY'>, 'VARBINARY': <TokenType.VARBINARY: 'VARBINARY'>, 'TIME': <TokenType.TIME: 'TIME'>, 'TIMETZ': <TokenType.TIMETZ: 'TIMETZ'>, 'TIMESTAMP': <TokenType.TIMESTAMP: 'TIMESTAMP'>, 'TIMESTAMPTZ': <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, 'TIMESTAMPLTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMP_LTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMPNTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'TIMESTAMP_NTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'DATE': <TokenType.DATE: 'DATE'>, 'DATETIME': <TokenType.DATETIME: 'DATETIME'>, 'INT4RANGE': <TokenType.INT4RANGE: 'INT4RANGE'>, 'INT4MULTIRANGE': <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, 'INT8RANGE': <TokenType.INT8RANGE: 'INT8RANGE'>, 'INT8MULTIRANGE': <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, 'NUMRANGE': <TokenType.NUMRANGE: 'NUMRANGE'>, 'NUMMULTIRANGE': <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, 'TSRANGE': <TokenType.TSRANGE: 'TSRANGE'>, 'TSMULTIRANGE': <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, 'TSTZRANGE': <TokenType.TSTZRANGE: 'TSTZRANGE'>, 'TSTZMULTIRANGE': <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, 'DATERANGE': <TokenType.DATERANGE: 'DATERANGE'>, 'DATEMULTIRANGE': <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, 'UNIQUE': <TokenType.UNIQUE: 'UNIQUE'>, 'STRUCT': <TokenType.STRUCT: 'STRUCT'>, 'SEQUENCE': <TokenType.SEQUENCE: 'SEQUENCE'>, 'VARIANT': <TokenType.VARIANT: 'VARIANT'>, 'ALTER': <TokenType.ALTER: 'ALTER'>, 'ANALYZE': <TokenType.COMMAND: 'COMMAND'>, 'CALL': <TokenType.COMMAND: 'COMMAND'>, 'COMMENT': <TokenType.COMMENT: 'COMMENT'>, 'EXPLAIN': <TokenType.COMMAND: 'COMMAND'>, 'GRANT': <TokenType.COMMAND: 'COMMAND'>, 'OPTIMIZE': <TokenType.COMMAND: 'COMMAND'>, 'PREPARE': <TokenType.COMMAND: 'COMMAND'>, 'VACUUM': <TokenType.COMMAND: 'COMMAND'>, 'USER-DEFINED': <TokenType.USERDEFINED: 'USERDEFINED'>, 'FOR VERSION': <TokenType.VERSION_SNAPSHOT: 'VERSION_SNAPSHOT'>, 'FOR TIMESTAMP': <TokenType.TIMESTAMP_SNAPSHOT: 'TIMESTAMP_SNAPSHOT'>, 'ADD ARCHIVE': <TokenType.COMMAND: 'COMMAND'>, 'ADD ARCHIVES': <TokenType.COMMAND: 'COMMAND'>, 'ADD FILE': <TokenType.COMMAND: 'COMMAND'>, 'ADD FILES': <TokenType.COMMAND: 'COMMAND'>, 'ADD JAR': <TokenType.COMMAND: 'COMMAND'>, 'ADD JARS': <TokenType.COMMAND: 'COMMAND'>, 'MSCK REPAIR': <TokenType.COMMAND: 'COMMAND'>, 'REFRESH': <TokenType.REFRESH: 'REFRESH'>, 'TIMESTAMP AS OF': <TokenType.TIMESTAMP_SNAPSHOT: 'TIMESTAMP_SNAPSHOT'>, 'VERSION AS OF': <TokenType.VERSION_SNAPSHOT: 'VERSION_SNAPSHOT'>, 'SERDEPROPERTIES': <TokenType.SERDE_PROPERTIES: 'SERDE_PROPERTIES'>}"}, "sqlglot.dialects.hive.Hive.Tokenizer.NUMERIC_LITERALS": {"fullname": "sqlglot.dialects.hive.Hive.Tokenizer.NUMERIC_LITERALS", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Tokenizer.NUMERIC_LITERALS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'L': 'BIGINT', 'S': 'SMALLINT', 'Y': 'TINYINT', 'D': 'DOUBLE', 'F': 'FLOAT', 'BD': 'DECIMAL'}"}, "sqlglot.dialects.hive.Hive.Parser": {"fullname": "sqlglot.dialects.hive.Hive.Parser", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Parser", "kind": "class", "doc": "<p>Parser consumes a list of tokens produced by the Tokenizer and produces a parsed syntax tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>error_level:</strong> The desired error level.\nDefault: ErrorLevel.IMMEDIATE</li>\n<li><strong>error_message_context:</strong> The amount of context to capture from a query string when displaying\nthe error message (in number of characters).\nDefault: 100</li>\n<li><strong>max_errors:</strong> Maximum number of error messages to include in a raised ParseError.\nThis is only relevant if error_level is ErrorLevel.RAISE.\nDefault: 3</li>\n</ul>\n", "bases": "sqlglot.parser.Parser"}, "sqlglot.dialects.hive.Hive.Parser.LOG_DEFAULTS_TO_LN": {"fullname": "sqlglot.dialects.hive.Hive.Parser.LOG_DEFAULTS_TO_LN", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Parser.LOG_DEFAULTS_TO_LN", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.hive.Hive.Parser.STRICT_CAST": {"fullname": "sqlglot.dialects.hive.Hive.Parser.STRICT_CAST", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Parser.STRICT_CAST", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.hive.Hive.Parser.VALUES_FOLLOWED_BY_PAREN": {"fullname": "sqlglot.dialects.hive.Hive.Parser.VALUES_FOLLOWED_BY_PAREN", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Parser.VALUES_FOLLOWED_BY_PAREN", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.hive.Hive.Parser.FUNCTIONS": {"fullname": "sqlglot.dialects.hive.Hive.Parser.FUNCTIONS", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Parser.FUNCTIONS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ABS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Abs'>>, 'ADD_MONTHS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AddMonths'>>, 'ANONYMOUS_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnonymousAggFunc'>>, 'ANY_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnyValue'>>, 'APPROX_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_COUNT_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'APPROX_TOP_K': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxTopK'>>, 'ARG_MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARGMAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'MAX_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARG_MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARGMIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'MIN_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Array'>>, 'ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAgg'>>, 'ARRAY_ALL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAll'>>, 'ARRAY_ANY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAny'>>, 'ARRAY_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CONSTRUCT_COMPACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConstructCompact'>>, 'ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayContains'>>, 'FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_OVERLAPS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayOverlaps'>>, 'ARRAY_SIZE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_SORT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySort'>>, 'ARRAY_SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySum'>>, 'ARRAY_TO_STRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_JOIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_UNION_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUnionAgg'>>, 'ARRAY_UNIQUE_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUniqueAgg'>>, 'AVG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Avg'>>, 'CASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Case'>>, 'CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cast'>>, 'CAST_TO_STR_TYPE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CastToStrType'>>, 'CBRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cbrt'>>, 'CEIL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CEILING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CHR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'COALESCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'IFNULL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'NVL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'COLLATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Collate'>>, 'COMBINED_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedAggFunc'>>, 'COMBINED_PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedParameterizedAgg'>>, 'CONCAT': <function Parser.<lambda>>, 'CONCAT_WS': <function Parser.<lambda>>, 'CONNECT_BY_ROOT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ConnectByRoot'>>, 'CONVERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Convert'>>, 'CORR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Corr'>>, 'COUNT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Count'>>, 'COUNT_IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COUNTIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COVAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarPop'>>, 'COVAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarSamp'>>, 'CURRENT_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDate'>>, 'CURRENT_DATETIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDatetime'>>, 'CURRENT_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTime'>>, 'CURRENT_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTimestamp'>>, 'CURRENT_USER': <bound method 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"sqlglot.dialects.hive.Hive.Parser.PROPERTY_PARSERS", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Parser.PROPERTY_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ALLOWED_VALUES': <function Parser.<lambda>>, 'ALGORITHM': <function Parser.<lambda>>, 'AUTO': <function Parser.<lambda>>, 'AUTO_INCREMENT': <function Parser.<lambda>>, 'BACKUP': <function Parser.<lambda>>, 'BLOCKCOMPRESSION': <function Parser.<lambda>>, 'CHARSET': <function Parser.<lambda>>, 'CHARACTER SET': <function Parser.<lambda>>, 'CHECKSUM': <function Parser.<lambda>>, 'CLUSTER BY': <function Parser.<lambda>>, 'CLUSTERED': <function Parser.<lambda>>, 'COLLATE': <function Parser.<lambda>>, 'COMMENT': <function Parser.<lambda>>, 'CONTAINS': <function Parser.<lambda>>, 'COPY': <function Parser.<lambda>>, 'DATABLOCKSIZE': <function Parser.<lambda>>, 'DATA_DELETION': <function Parser.<lambda>>, 'DEFINER': <function Parser.<lambda>>, 'DETERMINISTIC': <function Parser.<lambda>>, 'DISTKEY': <function Parser.<lambda>>, 'DISTSTYLE': <function Parser.<lambda>>, 'ENGINE': <function Parser.<lambda>>, 'EXECUTE': <function Parser.<lambda>>, 'EXTERNAL': <function Parser.<lambda>>, 'FALLBACK': <function Parser.<lambda>>, 'FORMAT': <function Parser.<lambda>>, 'FREESPACE': <function Parser.<lambda>>, 'GLOBAL': <function Parser.<lambda>>, 'HEAP': <function Parser.<lambda>>, 'ICEBERG': <function Parser.<lambda>>, 'IMMUTABLE': <function Parser.<lambda>>, 'INHERITS': <function Parser.<lambda>>, 'INPUT': <function Parser.<lambda>>, 'JOURNAL': <function Parser.<lambda>>, 'LANGUAGE': <function Parser.<lambda>>, 'LAYOUT': <function Parser.<lambda>>, 'LIFETIME': <function Parser.<lambda>>, 'LIKE': <function Parser.<lambda>>, 'LOCATION': <function Parser.<lambda>>, 'LOCK': <function Parser.<lambda>>, 'LOCKING': <function Parser.<lambda>>, 'LOG': <function Parser.<lambda>>, 'MATERIALIZED': <function Parser.<lambda>>, 'MERGEBLOCKRATIO': <function Parser.<lambda>>, 'MODIFIES': <function Parser.<lambda>>, 'MULTISET': <function Parser.<lambda>>, 'NO': <function Parser.<lambda>>, 'ON': <function Parser.<lambda>>, 'ORDER BY': <function Parser.<lambda>>, 'OUTPUT': <function Parser.<lambda>>, 'PARTITION': <function Parser.<lambda>>, 'PARTITION BY': <function Parser.<lambda>>, 'PARTITIONED BY': <function Parser.<lambda>>, 'PARTITIONED_BY': <function Parser.<lambda>>, 'PRIMARY KEY': <function Parser.<lambda>>, 'RANGE': <function Parser.<lambda>>, 'READS': <function Parser.<lambda>>, 'REMOTE': <function Parser.<lambda>>, 'RETURNS': <function Parser.<lambda>>, 'STRICT': <function Parser.<lambda>>, 'ROW': <function Parser.<lambda>>, 'ROW_FORMAT': <function Parser.<lambda>>, 'SAMPLE': <function Parser.<lambda>>, 'SET': <function Parser.<lambda>>, 'SETTINGS': <function Parser.<lambda>>, 'SHARING': <function Parser.<lambda>>, 'SORTKEY': <function Parser.<lambda>>, 'SOURCE': <function Parser.<lambda>>, 'STABLE': <function Parser.<lambda>>, 'STORED': <function Parser.<lambda>>, 'SYSTEM_VERSIONING': <function Parser.<lambda>>, 'TBLPROPERTIES': <function Parser.<lambda>>, 'TEMP': <function Parser.<lambda>>, 'TEMPORARY': <function Parser.<lambda>>, 'TO': <function Parser.<lambda>>, 'TRANSIENT': <function Parser.<lambda>>, 'TRANSFORM': <function Parser.<lambda>>, 'TTL': <function Parser.<lambda>>, 'USING': <function Parser.<lambda>>, 'UNLOGGED': <function Parser.<lambda>>, 'VOLATILE': <function Parser.<lambda>>, 'WITH': <function Parser.<lambda>>, 'SERDEPROPERTIES': <function Hive.Parser.<lambda>>}"}, "sqlglot.dialects.hive.Hive.Parser.SHOW_TRIE": {"fullname": "sqlglot.dialects.hive.Hive.Parser.SHOW_TRIE", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Parser.SHOW_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.hive.Hive.Parser.SET_TRIE": {"fullname": "sqlglot.dialects.hive.Hive.Parser.SET_TRIE", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Parser.SET_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'GLOBAL': {0: True}, 'LOCAL': {0: True}, 'SESSION': {0: True}, 'TRANSACTION': {0: True}}"}, "sqlglot.dialects.hive.Hive.Generator": {"fullname": "sqlglot.dialects.hive.Hive.Generator", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator", "kind": "class", "doc": "<p>Generator converts a given syntax tree to the corresponding SQL string.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>pretty:</strong> Whether to format the produced SQL string.\nDefault: False.</li>\n<li><strong>identify:</strong> Determines when an identifier should be quoted. Possible values are:\nFalse (default): Never quote, except in cases where it's mandatory by the dialect.\nTrue or 'always': Always quote.\n'safe': Only quote identifiers that are case insensitive.</li>\n<li><strong>normalize:</strong> Whether to normalize identifiers to lowercase.\nDefault: False.</li>\n<li><strong>pad:</strong> The pad size in a formatted string. For example, this affects the indentation of\na projection in a query, relative to its nesting level.\nDefault: 2.</li>\n<li><strong>indent:</strong> The indentation size in a formatted string. For example, this affects the\nindentation of subqueries and filters under a <code>WHERE</code> clause.\nDefault: 2.</li>\n<li><strong>normalize_functions:</strong> How to normalize function names. Possible values are:\n\"upper\" or True (default): Convert names to uppercase.\n\"lower\": Convert names to lowercase.\nFalse: Disables function name normalization.</li>\n<li><strong>unsupported_level:</strong> Determines the generator's behavior when it encounters unsupported expressions.\nDefault ErrorLevel.WARN.</li>\n<li><strong>max_unsupported:</strong> Maximum number of unsupported messages to include in a raised UnsupportedError.\nThis is only relevant if unsupported_level is ErrorLevel.RAISE.\nDefault: 3</li>\n<li><strong>leading_comma:</strong> Whether the comma is leading or trailing in select expressions.\nThis is only relevant when generating in pretty mode.\nDefault: False</li>\n<li><strong>max_text_width:</strong> The max number of characters in a segment before creating new lines in pretty mode.\nThe default is on the smaller end because the length only represents a segment and not the true\nline length.\nDefault: 80</li>\n<li><strong>comments:</strong> Whether to preserve comments in the output SQL code.\nDefault: True</li>\n</ul>\n", "bases": "sqlglot.generator.Generator"}, "sqlglot.dialects.hive.Hive.Generator.LIMIT_FETCH": {"fullname": "sqlglot.dialects.hive.Hive.Generator.LIMIT_FETCH", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.LIMIT_FETCH", "kind": "variable", "doc": "<p></p>\n", "default_value": "'LIMIT'"}, "sqlglot.dialects.hive.Hive.Generator.TABLESAMPLE_WITH_METHOD": {"fullname": "sqlglot.dialects.hive.Hive.Generator.TABLESAMPLE_WITH_METHOD", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.TABLESAMPLE_WITH_METHOD", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.hive.Hive.Generator.JOIN_HINTS": {"fullname": "sqlglot.dialects.hive.Hive.Generator.JOIN_HINTS", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.JOIN_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.hive.Hive.Generator.TABLE_HINTS": {"fullname": "sqlglot.dialects.hive.Hive.Generator.TABLE_HINTS", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.TABLE_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.hive.Hive.Generator.QUERY_HINTS": {"fullname": "sqlglot.dialects.hive.Hive.Generator.QUERY_HINTS", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.QUERY_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.hive.Hive.Generator.INDEX_ON": {"fullname": "sqlglot.dialects.hive.Hive.Generator.INDEX_ON", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.INDEX_ON", "kind": "variable", "doc": "<p></p>\n", "default_value": "'ON TABLE'"}, "sqlglot.dialects.hive.Hive.Generator.EXTRACT_ALLOWS_QUOTES": {"fullname": "sqlglot.dialects.hive.Hive.Generator.EXTRACT_ALLOWS_QUOTES", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.EXTRACT_ALLOWS_QUOTES", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.hive.Hive.Generator.NVL2_SUPPORTED": {"fullname": "sqlglot.dialects.hive.Hive.Generator.NVL2_SUPPORTED", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.NVL2_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.hive.Hive.Generator.LAST_DAY_SUPPORTS_DATE_PART": {"fullname": "sqlglot.dialects.hive.Hive.Generator.LAST_DAY_SUPPORTS_DATE_PART", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.LAST_DAY_SUPPORTS_DATE_PART", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.hive.Hive.Generator.JSON_PATH_SINGLE_QUOTE_ESCAPE": {"fullname": "sqlglot.dialects.hive.Hive.Generator.JSON_PATH_SINGLE_QUOTE_ESCAPE", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.JSON_PATH_SINGLE_QUOTE_ESCAPE", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.hive.Hive.Generator.SUPPORTS_TO_NUMBER": {"fullname": "sqlglot.dialects.hive.Hive.Generator.SUPPORTS_TO_NUMBER", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.SUPPORTS_TO_NUMBER", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.hive.Hive.Generator.WITH_PROPERTIES_PREFIX": {"fullname": "sqlglot.dialects.hive.Hive.Generator.WITH_PROPERTIES_PREFIX", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.WITH_PROPERTIES_PREFIX", "kind": "variable", "doc": "<p></p>\n", "default_value": "'TBLPROPERTIES'"}, "sqlglot.dialects.hive.Hive.Generator.EXPRESSIONS_WITHOUT_NESTED_CTES": {"fullname": "sqlglot.dialects.hive.Hive.Generator.EXPRESSIONS_WITHOUT_NESTED_CTES", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.EXPRESSIONS_WITHOUT_NESTED_CTES", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.Select'>, <class 'sqlglot.expressions.Union'>, <class 'sqlglot.expressions.Insert'>, <class 'sqlglot.expressions.Subquery'>}"}, "sqlglot.dialects.hive.Hive.Generator.SUPPORTED_JSON_PATH_PARTS": {"fullname": "sqlglot.dialects.hive.Hive.Generator.SUPPORTED_JSON_PATH_PARTS", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.SUPPORTED_JSON_PATH_PARTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.JSONPathWildcard'>, <class 'sqlglot.expressions.JSONPathSubscript'>, <class 'sqlglot.expressions.JSONPathRoot'>, <class 'sqlglot.expressions.JSONPathKey'>}"}, "sqlglot.dialects.hive.Hive.Generator.TYPE_MAPPING": {"fullname": "sqlglot.dialects.hive.Hive.Generator.TYPE_MAPPING", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.TYPE_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.NCHAR: 'NCHAR'>: 'CHAR', <Type.NVARCHAR: 'NVARCHAR'>: 'VARCHAR', <Type.MEDIUMTEXT: 'MEDIUMTEXT'>: 'TEXT', <Type.LONGTEXT: 'LONGTEXT'>: 'TEXT', <Type.TINYTEXT: 'TINYTEXT'>: 'TEXT', <Type.MEDIUMBLOB: 'MEDIUMBLOB'>: 'BLOB', <Type.LONGBLOB: 'LONGBLOB'>: 'BLOB', <Type.TINYBLOB: 'TINYBLOB'>: 'BLOB', <Type.INET: 'INET'>: 'INET', <Type.ROWVERSION: 'ROWVERSION'>: 'BINARY', <Type.BIT: 'BIT'>: 'BOOLEAN', <Type.DATETIME: 'DATETIME'>: 'TIMESTAMP', <Type.TEXT: 'TEXT'>: 'STRING', <Type.TIME: 'TIME'>: 'TIMESTAMP', <Type.TIMESTAMPTZ: 'TIMESTAMPTZ'>: 'TIMESTAMP', <Type.UTINYINT: 'UTINYINT'>: 'SMALLINT', <Type.VARBINARY: 'VARBINARY'>: 'BINARY'}"}, "sqlglot.dialects.hive.Hive.Generator.TRANSFORMS": {"fullname": "sqlglot.dialects.hive.Hive.Generator.TRANSFORMS", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.JSONPathKey'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRoot'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSubscript'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathWildcard'>: <function <lambda>>, <class 'sqlglot.expressions.AllowedValuesProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.BackupProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CaseSpecificColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ClusteredColumnConstraint'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.CollateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CommentColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DateFormatColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DefaultColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EncodeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EphemeralColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExcludeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExternalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.GlobalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.HeapProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IcebergProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InheritsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InlineLengthColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IntervalSpan'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtract'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtractScalar'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.LanguageProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LocationProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LogProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.MaterializedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NonClusteredColumnConstraint'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NotForReplicationColumnConstraint'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.OnCommitProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnProperty'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.OnUpdateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OutputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.PathColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ReturnsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SampleProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetConfigProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SettingsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SharingProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlReadWriteProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlSecurityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StabilityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StrictProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TemporaryProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TitleColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.Timestamp'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransformModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransientProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UppercaseColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UnloggedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VarMap'>: <function var_map_sql>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VolatileProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithOperator'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.Group'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.Select'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.Property'>: <function _property_sql>, <class 'sqlglot.expressions.AnyValue'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ApproxDistinct'>: <function approx_count_distinct_sql>, <class 'sqlglot.expressions.ArgMax'>: <function arg_max_or_min_no_count.<locals>._arg_max_or_min_sql>, <class 'sqlglot.expressions.ArgMin'>: <function arg_max_or_min_no_count.<locals>._arg_max_or_min_sql>, <class 'sqlglot.expressions.ArrayConcat'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ArrayToString'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.ArraySize'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ArraySort'>: <function _array_sort_sql>, <class 'sqlglot.expressions.With'>: <function no_recursive_cte_sql>, <class 'sqlglot.expressions.DateAdd'>: <function _add_date_sql>, <class 'sqlglot.expressions.DateDiff'>: <function _date_diff_sql>, <class 'sqlglot.expressions.DateStrToDate'>: <function datestrtodate_sql>, <class 'sqlglot.expressions.DateSub'>: <function _add_date_sql>, <class 'sqlglot.expressions.DateToDi'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.DiToDate'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.FileFormatProperty'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.FromBase64'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.If'>: <function if_sql.<locals>._if_sql>, <class 'sqlglot.expressions.ILike'>: <function no_ilike_sql>, <class 'sqlglot.expressions.IsNan'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.JSONFormat'>: <function _json_format_sql>, <class 'sqlglot.expressions.Left'>: <function left_to_substring_sql>, <class 'sqlglot.expressions.Map'>: <function var_map_sql>, <class 'sqlglot.expressions.Max'>: <function max_or_greatest>, <class 'sqlglot.expressions.MD5Digest'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.Min'>: <function min_or_least>, <class 'sqlglot.expressions.MonthsBetween'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.NotNullColumnConstraint'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.Create'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.Quantile'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ApproxQuantile'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.RegexpExtract'>: <function regexp_extract_sql>, <class 'sqlglot.expressions.RegexpReplace'>: <function regexp_replace_sql>, <class 'sqlglot.expressions.RegexpLike'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.RegexpSplit'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.Right'>: <function right_to_substring_sql>, <class 'sqlglot.expressions.SafeDivide'>: <function no_safe_divide_sql>, <class 'sqlglot.expressions.SchemaCommentProperty'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.ArrayUniqueAgg'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.Split'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.StrPosition'>: <function strposition_to_locate_sql>, <class 'sqlglot.expressions.StrToDate'>: <function _str_to_date_sql>, <class 'sqlglot.expressions.StrToTime'>: <function _str_to_time_sql>, <class 'sqlglot.expressions.StrToUnix'>: <function _str_to_unix_sql>, <class 'sqlglot.expressions.StructExtract'>: <function struct_extract_sql>, <class 'sqlglot.expressions.TimeStrToDate'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.TimeStrToTime'>: <function timestrtotime_sql>, <class 'sqlglot.expressions.TimeStrToUnix'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.TimeToStr'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.TimeToUnix'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ToBase64'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.TsOrDiToDi'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.TsOrDsAdd'>: <function _add_date_sql>, <class 'sqlglot.expressions.TsOrDsDiff'>: <function _date_diff_sql>, <class 'sqlglot.expressions.TsOrDsToDate'>: <function _to_date_sql>, <class 'sqlglot.expressions.TryCast'>: <function no_trycast_sql>, <class 'sqlglot.expressions.UnixToStr'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.UnixToTime'>: <function _unix_to_time_sql>, <class 'sqlglot.expressions.UnixToTimeStr'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.PartitionedByProperty'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.NumberToStr'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.National'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.PrimaryKeyColumnConstraint'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.ParseJSON'>: <function Hive.Generator.<lambda>>}"}, "sqlglot.dialects.hive.Hive.Generator.PROPERTIES_LOCATION": {"fullname": "sqlglot.dialects.hive.Hive.Generator.PROPERTIES_LOCATION", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.PROPERTIES_LOCATION", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.AllowedValuesProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.AlgorithmProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.AutoIncrementProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.BackupProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.BlockCompressionProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.CharacterSetProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ChecksumProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.CollateProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Cluster'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ClusteredByProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DataBlocksizeProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.DataDeletionProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DefinerProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.DictRange'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DictProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DistKeyProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DistStyleProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.EngineProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ExternalProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.FallbackProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.FileFormatProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.FreespaceProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.GlobalProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.HeapProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.InheritsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.IcebergProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.InputModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.IsolatedLoadingProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.JournalProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.LanguageProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LikeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LocationProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LockProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LockingProperty'>: <Location.POST_ALIAS: 'POST_ALIAS'>, <class 'sqlglot.expressions.LogProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.MaterializedProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.MergeBlockRatioProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.OnProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.OnCommitProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.Order'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.OutputModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.PartitionedByProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.PartitionedOfProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.PrimaryKey'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Property'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ReturnsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatDelimitedProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatSerdeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SampleProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SchemaCommentProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SerdeProperties'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Set'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SettingsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SetProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.SetConfigProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SharingProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.SequenceProperties'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.SortKeyProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SqlReadWriteProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SqlSecurityProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.StabilityProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.StrictProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.TemporaryProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.ToTableProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.TransientProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.TransformModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.MergeTreeTTL'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.UnloggedProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.VolatileProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.WithDataProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.WithSystemVersioningProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>}"}, "sqlglot.dialects.hive.Hive.Generator.parameter_sql": {"fullname": "sqlglot.dialects.hive.Hive.Generator.parameter_sql", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.parameter_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Parameter</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.hive.Hive.Generator.schema_sql": {"fullname": "sqlglot.dialects.hive.Hive.Generator.schema_sql", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.schema_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Schema</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.hive.Hive.Generator.constraint_sql": {"fullname": "sqlglot.dialects.hive.Hive.Generator.constraint_sql", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.constraint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Constraint</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.hive.Hive.Generator.rowformatserdeproperty_sql": {"fullname": "sqlglot.dialects.hive.Hive.Generator.rowformatserdeproperty_sql", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.rowformatserdeproperty_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">RowFormatSerdeProperty</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.hive.Hive.Generator.arrayagg_sql": {"fullname": "sqlglot.dialects.hive.Hive.Generator.arrayagg_sql", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.arrayagg_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ArrayAgg</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.hive.Hive.Generator.datatype_sql": {"fullname": "sqlglot.dialects.hive.Hive.Generator.datatype_sql", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.datatype_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.hive.Hive.Generator.version_sql": {"fullname": "sqlglot.dialects.hive.Hive.Generator.version_sql", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.version_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Version</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.hive.Hive.Generator.struct_sql": {"fullname": "sqlglot.dialects.hive.Hive.Generator.struct_sql", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.struct_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Struct</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.hive.Hive.Generator.alterset_sql": {"fullname": "sqlglot.dialects.hive.Hive.Generator.alterset_sql", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.alterset_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">AlterSet</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.hive.Hive.Generator.serdeproperties_sql": {"fullname": "sqlglot.dialects.hive.Hive.Generator.serdeproperties_sql", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.serdeproperties_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">SerdeProperties</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.hive.Hive.Generator.SELECT_KINDS": {"fullname": "sqlglot.dialects.hive.Hive.Generator.SELECT_KINDS", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.SELECT_KINDS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Tuple[str, ...]", "default_value": "()"}, "sqlglot.dialects.hive.Hive.Generator.TRY_SUPPORTED": {"fullname": "sqlglot.dialects.hive.Hive.Generator.TRY_SUPPORTED", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.Generator.TRY_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.hive.Hive.UNESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.hive.Hive.UNESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.UNESCAPED_SEQUENCES", "kind": "variable", "doc": "<p>Mapping of an escaped sequence (<code>\\n</code>) to its unescaped version (<code>\n</code>).</p>\n", "annotation": ": Dict[str, str]", "default_value": "{'\\\\a': '\\x07', '\\\\b': '\\x08', '\\\\f': '\\x0c', '\\\\n': '\\n', '\\\\r': '\\r', '\\\\t': '\\t', '\\\\v': '\\x0b', '\\\\\\\\': '\\\\'}"}, "sqlglot.dialects.hive.Hive.tokenizer_class": {"fullname": "sqlglot.dialects.hive.Hive.tokenizer_class", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.tokenizer_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.hive.Hive.Tokenizer'>"}, "sqlglot.dialects.hive.Hive.parser_class": {"fullname": "sqlglot.dialects.hive.Hive.parser_class", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.parser_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.hive.Hive.Parser'>"}, "sqlglot.dialects.hive.Hive.generator_class": {"fullname": "sqlglot.dialects.hive.Hive.generator_class", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.generator_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.hive.Hive.Generator'>"}, "sqlglot.dialects.hive.Hive.TIME_TRIE": {"fullname": "sqlglot.dialects.hive.Hive.TIME_TRIE", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'y': {0: True, 'y': {'y': {'y': {0: True}}, 0: True}}, 'Y': {0: True, 'Y': {'Y': {'Y': {0: True}}, 0: True}}, 'M': {'M': {'M': {'M': {0: True}, 0: True}, 0: True}, 0: True}, 'd': {'d': {0: True}, 0: True}, 'H': {'H': {0: True}, 0: True}, 'h': {'h': {0: True}, 0: True}, 'm': {'m': {0: True}, 0: True}, 's': {'s': {0: True}, 0: True}, 'S': {'S': {'S': {'S': {'S': {'S': {0: True}}}}}}, 'a': {0: True}, 'D': {'D': {0: True}, 0: True}, 'E': {0: True, 'E': {0: True, 'E': {0: True, 'E': {0: True}}}}}"}, "sqlglot.dialects.hive.Hive.FORMAT_TRIE": {"fullname": "sqlglot.dialects.hive.Hive.FORMAT_TRIE", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.FORMAT_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'y': {0: True, 'y': {'y': {'y': {0: True}}, 0: True}}, 'Y': {0: True, 'Y': {'Y': {'Y': {0: True}}, 0: True}}, 'M': {'M': {'M': {'M': {0: True}, 0: True}, 0: True}, 0: True}, 'd': {'d': {0: True}, 0: True}, 'H': {'H': {0: True}, 0: True}, 'h': {'h': {0: True}, 0: True}, 'm': {'m': {0: True}, 0: True}, 's': {'s': {0: True}, 0: True}, 'S': {'S': {'S': {'S': {'S': {'S': {0: True}}}}}}, 'a': {0: True}, 'D': {'D': {0: True}, 0: True}, 'E': {0: True, 'E': {0: True, 'E': {0: True, 'E': {0: True}}}}}"}, "sqlglot.dialects.hive.Hive.INVERSE_TIME_MAPPING": {"fullname": "sqlglot.dialects.hive.Hive.INVERSE_TIME_MAPPING", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.INVERSE_TIME_MAPPING", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'%Y': 'yyyy', '%y': 'yy', '%B': 'MMMM', '%b': 'MMM', '%m': 'MM', '%-m': 'M', '%d': 'dd', '%-d': 'd', '%H': 'HH', '%-H': 'H', '%I': 'hh', '%-I': 'h', '%M': 'mm', '%-M': 'm', '%S': 'ss', '%-S': 's', '%f': 'SSSSSS', '%p': 'a', '%j': 'DD', '%-j': 'D', '%a': 'EEE', '%A': 'EEEE'}"}, "sqlglot.dialects.hive.Hive.INVERSE_TIME_TRIE": {"fullname": "sqlglot.dialects.hive.Hive.INVERSE_TIME_TRIE", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.INVERSE_TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'%': {'Y': {0: True}, 'y': {0: True}, 'B': {0: True}, 'b': {0: True}, 'm': {0: True}, '-': {'m': {0: True}, 'd': {0: True}, 'H': {0: True}, 'I': {0: True}, 'M': {0: True}, 'S': {0: True}, 'j': {0: True}}, 'd': {0: True}, 'H': {0: True}, 'I': {0: True}, 'M': {0: True}, 'S': {0: True}, 'f': {0: True}, 'p': {0: True}, 'j': {0: True}, 'a': {0: True}, 'A': {0: True}}}"}, "sqlglot.dialects.hive.Hive.ESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.hive.Hive.ESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.ESCAPED_SEQUENCES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'\\x07': '\\\\a', '\\x08': '\\\\b', '\\x0c': '\\\\f', '\\n': '\\\\n', '\\r': '\\\\r', '\\t': '\\\\t', '\\x0b': '\\\\v', '\\\\': '\\\\\\\\'}"}, "sqlglot.dialects.hive.Hive.QUOTE_START": {"fullname": "sqlglot.dialects.hive.Hive.QUOTE_START", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.QUOTE_START", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.hive.Hive.QUOTE_END": {"fullname": "sqlglot.dialects.hive.Hive.QUOTE_END", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.QUOTE_END", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.hive.Hive.IDENTIFIER_START": {"fullname": "sqlglot.dialects.hive.Hive.IDENTIFIER_START", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.IDENTIFIER_START", "kind": "variable", "doc": "<p></p>\n", "default_value": "'`'"}, "sqlglot.dialects.hive.Hive.IDENTIFIER_END": {"fullname": "sqlglot.dialects.hive.Hive.IDENTIFIER_END", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.IDENTIFIER_END", "kind": "variable", "doc": "<p></p>\n", "default_value": "'`'"}, "sqlglot.dialects.hive.Hive.BIT_START": {"fullname": "sqlglot.dialects.hive.Hive.BIT_START", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.BIT_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.hive.Hive.BIT_END": {"fullname": "sqlglot.dialects.hive.Hive.BIT_END", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.BIT_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.hive.Hive.HEX_START": {"fullname": "sqlglot.dialects.hive.Hive.HEX_START", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.HEX_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.hive.Hive.HEX_END": {"fullname": "sqlglot.dialects.hive.Hive.HEX_END", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.HEX_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.hive.Hive.BYTE_START": {"fullname": "sqlglot.dialects.hive.Hive.BYTE_START", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.BYTE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.hive.Hive.BYTE_END": {"fullname": "sqlglot.dialects.hive.Hive.BYTE_END", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.BYTE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.hive.Hive.UNICODE_START": {"fullname": "sqlglot.dialects.hive.Hive.UNICODE_START", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.UNICODE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.hive.Hive.UNICODE_END": {"fullname": "sqlglot.dialects.hive.Hive.UNICODE_END", "modulename": "sqlglot.dialects.hive", "qualname": "Hive.UNICODE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.mysql": {"fullname": "sqlglot.dialects.mysql", "modulename": "sqlglot.dialects.mysql", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.dialects.mysql.TIME_SPECIFIERS": {"fullname": "sqlglot.dialects.mysql.TIME_SPECIFIERS", "modulename": "sqlglot.dialects.mysql", "qualname": "TIME_SPECIFIERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'f', 's', 'p', 'k', 'r', 'H', 'h', 'I', 'l', 'i', 'T', 'S'}"}, "sqlglot.dialects.mysql.date_add_sql": {"fullname": "sqlglot.dialects.mysql.date_add_sql", "modulename": "sqlglot.dialects.mysql", "qualname": "date_add_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">kind</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">],</span> <span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.mysql.MySQL": {"fullname": "sqlglot.dialects.mysql.MySQL", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.dialect.Dialect"}, "sqlglot.dialects.mysql.MySQL.IDENTIFIERS_CAN_START_WITH_DIGIT": {"fullname": "sqlglot.dialects.mysql.MySQL.IDENTIFIERS_CAN_START_WITH_DIGIT", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.IDENTIFIERS_CAN_START_WITH_DIGIT", "kind": "variable", "doc": "<p>Whether an unquoted identifier can start with a digit.</p>\n", "default_value": "True"}, "sqlglot.dialects.mysql.MySQL.NORMALIZATION_STRATEGY": {"fullname": "sqlglot.dialects.mysql.MySQL.NORMALIZATION_STRATEGY", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.NORMALIZATION_STRATEGY", "kind": "variable", "doc": "<p>Specifies the strategy according to which identifiers should be normalized.</p>\n", "default_value": "<NormalizationStrategy.CASE_SENSITIVE: 'CASE_SENSITIVE'>"}, "sqlglot.dialects.mysql.MySQL.TIME_FORMAT": {"fullname": "sqlglot.dialects.mysql.MySQL.TIME_FORMAT", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.TIME_FORMAT", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'%Y-%m-%d %T'""}, "sqlglot.dialects.mysql.MySQL.DPIPE_IS_STRING_CONCAT": {"fullname": "sqlglot.dialects.mysql.MySQL.DPIPE_IS_STRING_CONCAT", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.DPIPE_IS_STRING_CONCAT", "kind": "variable", "doc": "<p>Whether the DPIPE token (<code>||</code>) is a string concatenation operator.</p>\n", "default_value": "False"}, "sqlglot.dialects.mysql.MySQL.SUPPORTS_USER_DEFINED_TYPES": {"fullname": "sqlglot.dialects.mysql.MySQL.SUPPORTS_USER_DEFINED_TYPES", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.SUPPORTS_USER_DEFINED_TYPES", "kind": "variable", "doc": "<p>Whether user-defined data types are supported.</p>\n", "default_value": "False"}, "sqlglot.dialects.mysql.MySQL.SUPPORTS_SEMI_ANTI_JOIN": {"fullname": "sqlglot.dialects.mysql.MySQL.SUPPORTS_SEMI_ANTI_JOIN", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.SUPPORTS_SEMI_ANTI_JOIN", "kind": "variable", "doc": "<p>Whether <code>SEMI</code> or <code>ANTI</code> joins are supported.</p>\n", "default_value": "False"}, "sqlglot.dialects.mysql.MySQL.SAFE_DIVISION": {"fullname": "sqlglot.dialects.mysql.MySQL.SAFE_DIVISION", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.SAFE_DIVISION", "kind": "variable", "doc": "<p>Whether division by zero throws an error (<code>False</code>) or returns NULL (<code>True</code>).</p>\n", "default_value": "True"}, "sqlglot.dialects.mysql.MySQL.TIME_MAPPING": {"fullname": "sqlglot.dialects.mysql.MySQL.TIME_MAPPING", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.TIME_MAPPING", "kind": "variable", "doc": "<p>Associates this dialect's time formats with their equivalent Python <code>strftime</code> formats.</p>\n", "annotation": ": Dict[str, str]", "default_value": "{'%M': '%B', '%c': '%-m', '%e': '%-d', '%h': '%I', '%i': '%M', '%s': '%S', '%u': '%W', '%k': '%-H', '%l': '%-I', '%T': '%H:%M:%S', '%W': '%a'}"}, "sqlglot.dialects.mysql.MySQL.Tokenizer": {"fullname": "sqlglot.dialects.mysql.MySQL.Tokenizer", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Tokenizer", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.tokens.Tokenizer"}, "sqlglot.dialects.mysql.MySQL.Tokenizer.QUOTES": {"fullname": "sqlglot.dialects.mysql.MySQL.Tokenizer.QUOTES", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Tokenizer.QUOTES", "kind": "variable", "doc": "<p></p>\n", "default_value": "["'", '"']"}, "sqlglot.dialects.mysql.MySQL.Tokenizer.COMMENTS": {"fullname": "sqlglot.dialects.mysql.MySQL.Tokenizer.COMMENTS", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Tokenizer.COMMENTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "['--', '#', ('/*', '*/')]"}, "sqlglot.dialects.mysql.MySQL.Tokenizer.IDENTIFIERS": {"fullname": "sqlglot.dialects.mysql.MySQL.Tokenizer.IDENTIFIERS", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Tokenizer.IDENTIFIERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "['`']"}, "sqlglot.dialects.mysql.MySQL.Tokenizer.STRING_ESCAPES": {"fullname": "sqlglot.dialects.mysql.MySQL.Tokenizer.STRING_ESCAPES", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Tokenizer.STRING_ESCAPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "["'", '"', '\\\\']"}, "sqlglot.dialects.mysql.MySQL.Tokenizer.BIT_STRINGS": {"fullname": "sqlglot.dialects.mysql.MySQL.Tokenizer.BIT_STRINGS", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Tokenizer.BIT_STRINGS", "kind": "variable", "doc": "<p></p>\n", "default_value": "[("b'", "'"), ("B'", "'"), ('0b', '')]"}, "sqlglot.dialects.mysql.MySQL.Tokenizer.HEX_STRINGS": {"fullname": "sqlglot.dialects.mysql.MySQL.Tokenizer.HEX_STRINGS", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Tokenizer.HEX_STRINGS", "kind": "variable", "doc": "<p></p>\n", "default_value": "[("x'", "'"), ("X'", "'"), ('0x', '')]"}, "sqlglot.dialects.mysql.MySQL.Tokenizer.KEYWORDS": {"fullname": "sqlglot.dialects.mysql.MySQL.Tokenizer.KEYWORDS", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Tokenizer.KEYWORDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'{%': <TokenType.BLOCK_START: 'BLOCK_START'>, '{%+': <TokenType.BLOCK_START: 'BLOCK_START'>, '{%-': <TokenType.BLOCK_START: 'BLOCK_START'>, '%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '+%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '-%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '{{+': <TokenType.BLOCK_START: 'BLOCK_START'>, '{{-': <TokenType.BLOCK_START: 'BLOCK_START'>, '+}}': <TokenType.BLOCK_END: 'BLOCK_END'>, '-}}': <TokenType.BLOCK_END: 'BLOCK_END'>, '/*+': <TokenType.HINT: 'HINT'>, '==': <TokenType.EQ: 'EQ'>, '::': <TokenType.DCOLON: 'DCOLON'>, '||': <TokenType.DPIPE: 'DPIPE'>, '>=': <TokenType.GTE: 'GTE'>, '<=': <TokenType.LTE: 'LTE'>, '<>': <TokenType.NEQ: 'NEQ'>, '!=': <TokenType.NEQ: 'NEQ'>, ':=': <TokenType.COLON_EQ: 'COLON_EQ'>, '<=>': <TokenType.NULLSAFE_EQ: 'NULLSAFE_EQ'>, '->': <TokenType.ARROW: 'ARROW'>, '->>': <TokenType.DARROW: 'DARROW'>, '=>': <TokenType.FARROW: 'FARROW'>, '#>': <TokenType.HASH_ARROW: 'HASH_ARROW'>, '#>>': <TokenType.DHASH_ARROW: 'DHASH_ARROW'>, '<->': <TokenType.LR_ARROW: 'LR_ARROW'>, '&&': <TokenType.DAMP: 'DAMP'>, '??': <TokenType.DQMARK: 'DQMARK'>, 'ALL': <TokenType.ALL: 'ALL'>, 'ALWAYS': <TokenType.ALWAYS: 'ALWAYS'>, 'AND': <TokenType.AND: 'AND'>, 'ANTI': <TokenType.ANTI: 'ANTI'>, 'ANY': <TokenType.ANY: 'ANY'>, 'ASC': <TokenType.ASC: 'ASC'>, 'AS': <TokenType.ALIAS: 'ALIAS'>, 'ASOF': <TokenType.ASOF: 'ASOF'>, 'AUTOINCREMENT': <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, 'AUTO_INCREMENT': <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, 'BEGIN': <TokenType.BEGIN: 'BEGIN'>, 'BETWEEN': <TokenType.BETWEEN: 'BETWEEN'>, 'CACHE': <TokenType.CACHE: 'CACHE'>, 'UNCACHE': <TokenType.UNCACHE: 'UNCACHE'>, 'CASE': <TokenType.CASE: 'CASE'>, 'CHARACTER SET': <TokenType.CHARACTER_SET: 'CHARACTER_SET'>, 'CLUSTER BY': <TokenType.CLUSTER_BY: 'CLUSTER_BY'>, 'COLLATE': <TokenType.COLLATE: 'COLLATE'>, 'COLUMN': <TokenType.COLUMN: 'COLUMN'>, 'COMMIT': <TokenType.COMMIT: 'COMMIT'>, 'CONNECT BY': <TokenType.CONNECT_BY: 'CONNECT_BY'>, 'CONSTRAINT': <TokenType.CONSTRAINT: 'CONSTRAINT'>, 'COPY': <TokenType.COPY: 'COPY'>, 'CREATE': <TokenType.CREATE: 'CREATE'>, 'CROSS': <TokenType.CROSS: 'CROSS'>, 'CUBE': <TokenType.CUBE: 'CUBE'>, 'CURRENT_DATE': <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, 'CURRENT_TIME': <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, 'CURRENT_TIMESTAMP': <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, 'CURRENT_USER': <TokenType.CURRENT_USER: 'CURRENT_USER'>, 'DATABASE': <TokenType.DATABASE: 'DATABASE'>, 'DEFAULT': <TokenType.DEFAULT: 'DEFAULT'>, 'DELETE': <TokenType.DELETE: 'DELETE'>, 'DESC': <TokenType.DESC: 'DESC'>, 'DESCRIBE': <TokenType.DESCRIBE: 'DESCRIBE'>, 'DISTINCT': <TokenType.DISTINCT: 'DISTINCT'>, 'DISTRIBUTE BY': <TokenType.DISTRIBUTE_BY: 'DISTRIBUTE_BY'>, 'DIV': <TokenType.DIV: 'DIV'>, 'DROP': <TokenType.DROP: 'DROP'>, 'ELSE': <TokenType.ELSE: 'ELSE'>, 'END': <TokenType.END: 'END'>, 'ENUM': <TokenType.ENUM: 'ENUM'>, 'ESCAPE': <TokenType.ESCAPE: 'ESCAPE'>, 'EXCEPT': <TokenType.EXCEPT: 'EXCEPT'>, 'EXECUTE': <TokenType.EXECUTE: 'EXECUTE'>, 'EXISTS': <TokenType.EXISTS: 'EXISTS'>, 'FALSE': <TokenType.FALSE: 'FALSE'>, 'FETCH': <TokenType.FETCH: 'FETCH'>, 'FILTER': <TokenType.FILTER: 'FILTER'>, 'FIRST': <TokenType.FIRST: 'FIRST'>, 'FULL': <TokenType.FULL: 'FULL'>, 'FUNCTION': <TokenType.FUNCTION: 'FUNCTION'>, 'FOR': <TokenType.FOR: 'FOR'>, 'FOREIGN KEY': <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, 'FORMAT': <TokenType.FORMAT: 'FORMAT'>, 'FROM': <TokenType.FROM: 'FROM'>, 'GEOGRAPHY': <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, 'GEOMETRY': <TokenType.GEOMETRY: 'GEOMETRY'>, 'GLOB': <TokenType.GLOB: 'GLOB'>, 'GROUP BY': <TokenType.GROUP_BY: 'GROUP_BY'>, 'GROUPING SETS': <TokenType.GROUPING_SETS: 'GROUPING_SETS'>, 'HAVING': <TokenType.HAVING: 'HAVING'>, 'ILIKE': <TokenType.ILIKE: 'ILIKE'>, 'IN': <TokenType.IN: 'IN'>, 'INDEX': <TokenType.INDEX: 'INDEX'>, 'INET': <TokenType.INET: 'INET'>, 'INNER': <TokenType.INNER: 'INNER'>, 'INSERT': <TokenType.INSERT: 'INSERT'>, 'INTERVAL': <TokenType.INTERVAL: 'INTERVAL'>, 'INTERSECT': <TokenType.INTERSECT: 'INTERSECT'>, 'INTO': <TokenType.INTO: 'INTO'>, 'IS': <TokenType.IS: 'IS'>, 'ISNULL': <TokenType.ISNULL: 'ISNULL'>, 'JOIN': <TokenType.JOIN: 'JOIN'>, 'KEEP': <TokenType.KEEP: 'KEEP'>, 'KILL': <TokenType.KILL: 'KILL'>, 'LATERAL': <TokenType.LATERAL: 'LATERAL'>, 'LEFT': <TokenType.LEFT: 'LEFT'>, 'LIKE': <TokenType.LIKE: 'LIKE'>, 'LIMIT': <TokenType.LIMIT: 'LIMIT'>, 'LOAD': <TokenType.LOAD: 'LOAD'>, 'LOCK': <TokenType.LOCK: 'LOCK'>, 'MERGE': <TokenType.MERGE: 'MERGE'>, 'NATURAL': <TokenType.NATURAL: 'NATURAL'>, 'NEXT': <TokenType.NEXT: 'NEXT'>, 'NOT': <TokenType.NOT: 'NOT'>, 'NOTNULL': <TokenType.NOTNULL: 'NOTNULL'>, 'NULL': <TokenType.NULL: 'NULL'>, 'OBJECT': <TokenType.OBJECT: 'OBJECT'>, 'OFFSET': <TokenType.OFFSET: 'OFFSET'>, 'ON': <TokenType.ON: 'ON'>, 'OR': <TokenType.OR: 'OR'>, 'XOR': <TokenType.XOR: 'XOR'>, 'ORDER BY': <TokenType.ORDER_BY: 'ORDER_BY'>, 'ORDINALITY': <TokenType.ORDINALITY: 'ORDINALITY'>, 'OUTER': <TokenType.OUTER: 'OUTER'>, 'OVER': <TokenType.OVER: 'OVER'>, 'OVERLAPS': <TokenType.OVERLAPS: 'OVERLAPS'>, 'OVERWRITE': <TokenType.OVERWRITE: 'OVERWRITE'>, 'PARTITION': <TokenType.PARTITION: 'PARTITION'>, 'PARTITION BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PARTITIONED BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PARTITIONED_BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PERCENT': <TokenType.PERCENT: 'PERCENT'>, 'PIVOT': <TokenType.PIVOT: 'PIVOT'>, 'PRAGMA': <TokenType.PRAGMA: 'PRAGMA'>, 'PRIMARY KEY': <TokenType.PRIMARY_KEY: 'PRIMARY_KEY'>, 'PROCEDURE': <TokenType.PROCEDURE: 'PROCEDURE'>, 'QUALIFY': <TokenType.QUALIFY: 'QUALIFY'>, 'RANGE': <TokenType.RANGE: 'RANGE'>, 'RECURSIVE': <TokenType.RECURSIVE: 'RECURSIVE'>, 'REGEXP': <TokenType.RLIKE: 'RLIKE'>, 'REPLACE': <TokenType.REPLACE: 'REPLACE'>, 'RETURNING': <TokenType.RETURNING: 'RETURNING'>, 'REFERENCES': <TokenType.REFERENCES: 'REFERENCES'>, 'RIGHT': <TokenType.RIGHT: 'RIGHT'>, 'RLIKE': <TokenType.RLIKE: 'RLIKE'>, 'ROLLBACK': <TokenType.ROLLBACK: 'ROLLBACK'>, 'ROLLUP': <TokenType.ROLLUP: 'ROLLUP'>, 'ROW': <TokenType.ROW: 'ROW'>, 'ROWS': <TokenType.ROWS: 'ROWS'>, 'SCHEMA': <TokenType.SCHEMA: 'SCHEMA'>, 'SELECT': <TokenType.SELECT: 'SELECT'>, 'SEMI': <TokenType.SEMI: 'SEMI'>, 'SET': <TokenType.SET: 'SET'>, 'SETTINGS': <TokenType.SETTINGS: 'SETTINGS'>, 'SHOW': <TokenType.SHOW: 'SHOW'>, 'SIMILAR TO': <TokenType.SIMILAR_TO: 'SIMILAR_TO'>, 'SOME': <TokenType.SOME: 'SOME'>, 'SORT BY': <TokenType.SORT_BY: 'SORT_BY'>, 'START WITH': <TokenType.START_WITH: 'START_WITH'>, 'TABLE': <TokenType.TABLE: 'TABLE'>, 'TABLESAMPLE': <TokenType.TABLE_SAMPLE: 'TABLE_SAMPLE'>, 'TEMP': <TokenType.TEMPORARY: 'TEMPORARY'>, 'TEMPORARY': <TokenType.TEMPORARY: 'TEMPORARY'>, 'THEN': <TokenType.THEN: 'THEN'>, 'TRUE': <TokenType.TRUE: 'TRUE'>, 'TRUNCATE': <TokenType.TRUNCATE: 'TRUNCATE'>, 'UNION': <TokenType.UNION: 'UNION'>, 'UNKNOWN': <TokenType.UNKNOWN: 'UNKNOWN'>, 'UNNEST': <TokenType.UNNEST: 'UNNEST'>, 'UNPIVOT': <TokenType.UNPIVOT: 'UNPIVOT'>, 'UPDATE': <TokenType.UPDATE: 'UPDATE'>, 'USE': <TokenType.USE: 'USE'>, 'USING': <TokenType.USING: 'USING'>, 'UUID': <TokenType.UUID: 'UUID'>, 'VALUES': <TokenType.VALUES: 'VALUES'>, 'VIEW': <TokenType.VIEW: 'VIEW'>, 'VOLATILE': <TokenType.VOLATILE: 'VOLATILE'>, 'WHEN': <TokenType.WHEN: 'WHEN'>, 'WHERE': <TokenType.WHERE: 'WHERE'>, 'WINDOW': <TokenType.WINDOW: 'WINDOW'>, 'WITH': <TokenType.WITH: 'WITH'>, 'APPLY': <TokenType.APPLY: 'APPLY'>, 'ARRAY': <TokenType.ARRAY: 'ARRAY'>, 'BIT': <TokenType.BIT: 'BIT'>, 'BOOL': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BOOLEAN': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BYTE': <TokenType.TINYINT: 'TINYINT'>, 'MEDIUMINT': <TokenType.MEDIUMINT: 'MEDIUMINT'>, 'INT1': <TokenType.TINYINT: 'TINYINT'>, 'TINYINT': <TokenType.TINYINT: 'TINYINT'>, 'INT16': <TokenType.SMALLINT: 'SMALLINT'>, 'SHORT': <TokenType.SMALLINT: 'SMALLINT'>, 'SMALLINT': <TokenType.SMALLINT: 'SMALLINT'>, 'INT128': <TokenType.INT128: 'INT128'>, 'HUGEINT': <TokenType.INT128: 'INT128'>, 'INT2': <TokenType.SMALLINT: 'SMALLINT'>, 'INTEGER': <TokenType.INT: 'INT'>, 'INT': <TokenType.INT: 'INT'>, 'INT4': <TokenType.INT: 'INT'>, 'INT32': <TokenType.INT: 'INT'>, 'INT64': <TokenType.BIGINT: 'BIGINT'>, 'LONG': <TokenType.BIGINT: 'BIGINT'>, 'BIGINT': <TokenType.BIGINT: 'BIGINT'>, 'INT8': <TokenType.TINYINT: 'TINYINT'>, 'UINT': <TokenType.UINT: 'UINT'>, 'DEC': <TokenType.DECIMAL: 'DECIMAL'>, 'DECIMAL': <TokenType.DECIMAL: 'DECIMAL'>, 'BIGDECIMAL': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'BIGNUMERIC': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'MAP': <TokenType.MAP: 'MAP'>, 'NULLABLE': <TokenType.NULLABLE: 'NULLABLE'>, 'NUMBER': <TokenType.DECIMAL: 'DECIMAL'>, 'NUMERIC': <TokenType.DECIMAL: 'DECIMAL'>, 'FIXED': <TokenType.DECIMAL: 'DECIMAL'>, 'REAL': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT4': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT8': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE PRECISION': <TokenType.DOUBLE: 'DOUBLE'>, 'JSON': <TokenType.JSON: 'JSON'>, 'CHAR': <TokenType.CHAR: 'CHAR'>, 'CHARACTER': <TokenType.CHAR: 'CHAR'>, 'NCHAR': <TokenType.NCHAR: 'NCHAR'>, 'VARCHAR': <TokenType.VARCHAR: 'VARCHAR'>, 'VARCHAR2': <TokenType.VARCHAR: 'VARCHAR'>, 'NVARCHAR': <TokenType.NVARCHAR: 'NVARCHAR'>, 'NVARCHAR2': <TokenType.NVARCHAR: 'NVARCHAR'>, 'BPCHAR': <TokenType.BPCHAR: 'BPCHAR'>, 'STR': <TokenType.TEXT: 'TEXT'>, 'STRING': <TokenType.TEXT: 'TEXT'>, 'TEXT': <TokenType.TEXT: 'TEXT'>, 'LONGTEXT': <TokenType.LONGTEXT: 'LONGTEXT'>, 'MEDIUMTEXT': <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, 'TINYTEXT': <TokenType.TINYTEXT: 'TINYTEXT'>, 'CLOB': <TokenType.TEXT: 'TEXT'>, 'LONGVARCHAR': <TokenType.TEXT: 'TEXT'>, 'BINARY': <TokenType.BINARY: 'BINARY'>, 'BLOB': <TokenType.VARBINARY: 'VARBINARY'>, 'LONGBLOB': <TokenType.LONGBLOB: 'LONGBLOB'>, 'MEDIUMBLOB': <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, 'TINYBLOB': <TokenType.TINYBLOB: 'TINYBLOB'>, 'BYTEA': <TokenType.VARBINARY: 'VARBINARY'>, 'VARBINARY': <TokenType.VARBINARY: 'VARBINARY'>, 'TIME': <TokenType.TIME: 'TIME'>, 'TIMETZ': <TokenType.TIMETZ: 'TIMETZ'>, 'TIMESTAMP': <TokenType.TIMESTAMP: 'TIMESTAMP'>, 'TIMESTAMPTZ': <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, 'TIMESTAMPLTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMP_LTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMPNTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'TIMESTAMP_NTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'DATE': <TokenType.DATE: 'DATE'>, 'DATETIME': <TokenType.DATETIME: 'DATETIME'>, 'INT4RANGE': <TokenType.INT4RANGE: 'INT4RANGE'>, 'INT4MULTIRANGE': <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, 'INT8RANGE': <TokenType.INT8RANGE: 'INT8RANGE'>, 'INT8MULTIRANGE': <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, 'NUMRANGE': <TokenType.NUMRANGE: 'NUMRANGE'>, 'NUMMULTIRANGE': <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, 'TSRANGE': <TokenType.TSRANGE: 'TSRANGE'>, 'TSMULTIRANGE': <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, 'TSTZRANGE': <TokenType.TSTZRANGE: 'TSTZRANGE'>, 'TSTZMULTIRANGE': <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, 'DATERANGE': <TokenType.DATERANGE: 'DATERANGE'>, 'DATEMULTIRANGE': <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, 'UNIQUE': <TokenType.UNIQUE: 'UNIQUE'>, 'STRUCT': <TokenType.STRUCT: 'STRUCT'>, 'SEQUENCE': <TokenType.SEQUENCE: 'SEQUENCE'>, 'VARIANT': <TokenType.VARIANT: 'VARIANT'>, 'ALTER': <TokenType.ALTER: 'ALTER'>, 'ANALYZE': <TokenType.COMMAND: 'COMMAND'>, 'CALL': <TokenType.COMMAND: 'COMMAND'>, 'COMMENT': <TokenType.COMMENT: 'COMMENT'>, 'EXPLAIN': <TokenType.COMMAND: 'COMMAND'>, 'GRANT': <TokenType.COMMAND: 'COMMAND'>, 'OPTIMIZE': <TokenType.COMMAND: 'COMMAND'>, 'PREPARE': <TokenType.COMMAND: 'COMMAND'>, 'VACUUM': <TokenType.COMMAND: 'COMMAND'>, 'USER-DEFINED': <TokenType.USERDEFINED: 'USERDEFINED'>, 'FOR VERSION': <TokenType.VERSION_SNAPSHOT: 'VERSION_SNAPSHOT'>, 'FOR TIMESTAMP': <TokenType.TIMESTAMP_SNAPSHOT: 'TIMESTAMP_SNAPSHOT'>, 'CHARSET': <TokenType.CHARACTER_SET: 'CHARACTER_SET'>, 'FORCE': <TokenType.FORCE: 'FORCE'>, 'IGNORE': <TokenType.IGNORE: 'IGNORE'>, 'LOCK TABLES': <TokenType.COMMAND: 'COMMAND'>, 'MEMBER OF': <TokenType.MEMBER_OF: 'MEMBER_OF'>, 'SEPARATOR': <TokenType.SEPARATOR: 'SEPARATOR'>, 'START': <TokenType.BEGIN: 'BEGIN'>, 'SIGNED': <TokenType.BIGINT: 'BIGINT'>, 'SIGNED INTEGER': <TokenType.BIGINT: 'BIGINT'>, 'UNLOCK TABLES': <TokenType.COMMAND: 'COMMAND'>, 'UNSIGNED': <TokenType.UBIGINT: 'UBIGINT'>, 'UNSIGNED INTEGER': <TokenType.UBIGINT: 'UBIGINT'>, 'YEAR': <TokenType.YEAR: 'YEAR'>, '_ARMSCII8': <TokenType.INTRODUCER: 'INTRODUCER'>, '_ASCII': <TokenType.INTRODUCER: 'INTRODUCER'>, '_BIG5': <TokenType.INTRODUCER: 'INTRODUCER'>, '_BINARY': <TokenType.INTRODUCER: 'INTRODUCER'>, '_CP1250': <TokenType.INTRODUCER: 'INTRODUCER'>, '_CP1251': <TokenType.INTRODUCER: 'INTRODUCER'>, '_CP1256': <TokenType.INTRODUCER: 'INTRODUCER'>, '_CP1257': <TokenType.INTRODUCER: 'INTRODUCER'>, '_CP850': <TokenType.INTRODUCER: 'INTRODUCER'>, '_CP852': <TokenType.INTRODUCER: 'INTRODUCER'>, '_CP866': <TokenType.INTRODUCER: 'INTRODUCER'>, '_CP932': <TokenType.INTRODUCER: 'INTRODUCER'>, '_DEC8': <TokenType.INTRODUCER: 'INTRODUCER'>, '_EUCJPMS': <TokenType.INTRODUCER: 'INTRODUCER'>, '_EUCKR': <TokenType.INTRODUCER: 'INTRODUCER'>, '_GB18030': <TokenType.INTRODUCER: 'INTRODUCER'>, '_GB2312': <TokenType.INTRODUCER: 'INTRODUCER'>, '_GBK': <TokenType.INTRODUCER: 'INTRODUCER'>, '_GEOSTD8': <TokenType.INTRODUCER: 'INTRODUCER'>, '_GREEK': <TokenType.INTRODUCER: 'INTRODUCER'>, '_HEBREW': <TokenType.INTRODUCER: 'INTRODUCER'>, '_HP8': <TokenType.INTRODUCER: 'INTRODUCER'>, '_KEYBCS2': <TokenType.INTRODUCER: 'INTRODUCER'>, '_KOI8R': <TokenType.INTRODUCER: 'INTRODUCER'>, '_KOI8U': <TokenType.INTRODUCER: 'INTRODUCER'>, '_LATIN1': <TokenType.INTRODUCER: 'INTRODUCER'>, '_LATIN2': <TokenType.INTRODUCER: 'INTRODUCER'>, '_LATIN5': <TokenType.INTRODUCER: 'INTRODUCER'>, '_LATIN7': <TokenType.INTRODUCER: 'INTRODUCER'>, '_MACCE': <TokenType.INTRODUCER: 'INTRODUCER'>, '_MACROMAN': <TokenType.INTRODUCER: 'INTRODUCER'>, '_SJIS': <TokenType.INTRODUCER: 'INTRODUCER'>, '_SWE7': <TokenType.INTRODUCER: 'INTRODUCER'>, '_TIS620': <TokenType.INTRODUCER: 'INTRODUCER'>, '_UCS2': <TokenType.INTRODUCER: 'INTRODUCER'>, '_UJIS': <TokenType.INTRODUCER: 'INTRODUCER'>, '_UTF8': <TokenType.INTRODUCER: 'INTRODUCER'>, '_UTF16': <TokenType.INTRODUCER: 'INTRODUCER'>, '_UTF16LE': <TokenType.INTRODUCER: 'INTRODUCER'>, '_UTF32': <TokenType.INTRODUCER: 'INTRODUCER'>, '_UTF8MB3': <TokenType.INTRODUCER: 'INTRODUCER'>, '_UTF8MB4': <TokenType.INTRODUCER: 'INTRODUCER'>, '@@': <TokenType.SESSION_PARAMETER: 'SESSION_PARAMETER'>}"}, "sqlglot.dialects.mysql.MySQL.Tokenizer.COMMANDS": {"fullname": "sqlglot.dialects.mysql.MySQL.Tokenizer.COMMANDS", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Tokenizer.COMMANDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.REPLACE: 'REPLACE'>, <TokenType.EXECUTE: 'EXECUTE'>, <TokenType.FETCH: 'FETCH'>, <TokenType.COMMAND: 'COMMAND'>}"}, "sqlglot.dialects.mysql.MySQL.Parser": {"fullname": "sqlglot.dialects.mysql.MySQL.Parser", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Parser", "kind": "class", "doc": "<p>Parser consumes a list of tokens produced by the Tokenizer and produces a parsed syntax tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>error_level:</strong> The desired error level.\nDefault: ErrorLevel.IMMEDIATE</li>\n<li><strong>error_message_context:</strong> The amount of context to capture from a query string when displaying\nthe error message (in number of characters).\nDefault: 100</li>\n<li><strong>max_errors:</strong> Maximum number of error messages to include in a raised ParseError.\nThis is only relevant if error_level is ErrorLevel.RAISE.\nDefault: 3</li>\n</ul>\n", "bases": "sqlglot.parser.Parser"}, "sqlglot.dialects.mysql.MySQL.Parser.FUNC_TOKENS": {"fullname": "sqlglot.dialects.mysql.MySQL.Parser.FUNC_TOKENS", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Parser.FUNC_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.MONEY: 'MONEY'>, <TokenType.PRIMARY_KEY: 'PRIMARY_KEY'>, <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, <TokenType.IDENTIFIER: 'IDENTIFIER'>, <TokenType.VARBINARY: 'VARBINARY'>, <TokenType.HSTORE: 'HSTORE'>, <TokenType.IPADDRESS: 'IPADDRESS'>, <TokenType.ISNULL: 'ISNULL'>, <TokenType.SCHEMA: 'SCHEMA'>, <TokenType.NUMRANGE: 'NUMRANGE'>, <TokenType.DATE32: 'DATE32'>, <TokenType.INT8RANGE: 'INT8RANGE'>, <TokenType.AGGREGATEFUNCTION: 'AGGREGATEFUNCTION'>, <TokenType.VARCHAR: 'VARCHAR'>, <TokenType.TIMETZ: 'TIMETZ'>, <TokenType.GEOMETRY: 'GEOMETRY'>, <TokenType.ENUM8: 'ENUM8'>, <TokenType.INDEX: 'INDEX'>, <TokenType.UINT256: 'UINT256'>, <TokenType.BIGINT: 'BIGINT'>, <TokenType.INT128: 'INT128'>, <TokenType.SMALLMONEY: 'SMALLMONEY'>, <TokenType.HLLSKETCH: 'HLLSKETCH'>, <TokenType.RLIKE: 'RLIKE'>, <TokenType.SMALLINT: 'SMALLINT'>, <TokenType.INT256: 'INT256'>, <TokenType.GLOB: 'GLOB'>, <TokenType.FLOAT: 'FLOAT'>, <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, <TokenType.UNNEST: 'UNNEST'>, <TokenType.EXISTS: 'EXISTS'>, <TokenType.NULL: 'NULL'>, <TokenType.XOR: 'XOR'>, <TokenType.NULLABLE: 'NULLABLE'>, <TokenType.TINYTEXT: 'TINYTEXT'>, <TokenType.DATE: 'DATE'>, <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <TokenType.MERGE: 'MERGE'>, <TokenType.FIRST: 'FIRST'>, <TokenType.BINARY: 'BINARY'>, <TokenType.ARRAY: 'ARRAY'>, <TokenType.SERIAL: 'SERIAL'>, <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, <TokenType.INTERVAL: 'INTERVAL'>, <TokenType.WINDOW: 'WINDOW'>, <TokenType.RIGHT: 'RIGHT'>, <TokenType.BPCHAR: 'BPCHAR'>, <TokenType.BIT: 'BIT'>, <TokenType.UINT: 'UINT'>, <TokenType.ILIKE: 'ILIKE'>, <TokenType.UUID: 'UUID'>, <TokenType.STRUCT: 'STRUCT'>, <TokenType.LEFT: 'LEFT'>, <TokenType.SUPER: 'SUPER'>, <TokenType.IMAGE: 'IMAGE'>, <TokenType.UBIGINT: 'UBIGINT'>, <TokenType.LONGBLOB: 'LONGBLOB'>, <TokenType.VAR: 'VAR'>, <TokenType.COMMAND: 'COMMAND'>, <TokenType.TRUNCATE: 'TRUNCATE'>, <TokenType.UMEDIUMINT: 'UMEDIUMINT'>, <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, <TokenType.UINT128: 'UINT128'>, <TokenType.MAP: 'MAP'>, <TokenType.IPV4: 'IPV4'>, <TokenType.USERDEFINED: 'USERDEFINED'>, <TokenType.REPLACE: 'REPLACE'>, <TokenType.RANGE: 'RANGE'>, <TokenType.NVARCHAR: 'NVARCHAR'>, <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, <TokenType.TIMESTAMP_MS: 'TIMESTAMP_MS'>, <TokenType.VARIANT: 'VARIANT'>, <TokenType.ENUM: 'ENUM'>, <TokenType.USMALLINT: 'USMALLINT'>, <TokenType.TIMESTAMP_S: 'TIMESTAMP_S'>, <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, <TokenType.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>, <TokenType.TEXT: 'TEXT'>, <TokenType.DATABASE: 'DATABASE'>, <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, <TokenType.PSEUDO_TYPE: 'PSEUDO_TYPE'>, <TokenType.FIXEDSTRING: 'FIXEDSTRING'>, <TokenType.INT: 'INT'>, <TokenType.BIGSERIAL: 'BIGSERIAL'>, <TokenType.BOOLEAN: 'BOOLEAN'>, <TokenType.UNKNOWN: 'UNKNOWN'>, <TokenType.TSTZRANGE: 'TSTZRANGE'>, <TokenType.DATETIME64: 'DATETIME64'>, <TokenType.DATETIME: 'DATETIME'>, <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, <TokenType.MEDIUMINT: 'MEDIUMINT'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>, <TokenType.LIKE: 'LIKE'>, <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, <TokenType.XML: 'XML'>, <TokenType.JSON: 'JSON'>, <TokenType.UTINYINT: 'UTINYINT'>, <TokenType.TIME: 'TIME'>, <TokenType.UDECIMAL: 'UDECIMAL'>, <TokenType.NESTED: 'NESTED'>, <TokenType.ROWVERSION: 'ROWVERSION'>, <TokenType.OFFSET: 'OFFSET'>, <TokenType.INSERT: 'INSERT'>, <TokenType.TIMESTAMP_NS: 'TIMESTAMP_NS'>, <TokenType.ANY: 'ANY'>, <TokenType.VALUES: 'VALUES'>, <TokenType.INET: 'INET'>, <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, <TokenType.CURRENT_USER: 'CURRENT_USER'>, <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>, <TokenType.ALL: 'ALL'>, <TokenType.NAME: 'NAME'>, <TokenType.SOME: 'SOME'>, <TokenType.ENUM16: 'ENUM16'>, <TokenType.YEAR: 'YEAR'>, <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, <TokenType.DOUBLE: 'DOUBLE'>, <TokenType.INT4RANGE: 'INT4RANGE'>, <TokenType.FORMAT: 'FORMAT'>, <TokenType.IPPREFIX: 'IPPREFIX'>, <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>, <TokenType.COLLATE: 'COLLATE'>, <TokenType.FILTER: 'FILTER'>, <TokenType.JSONB: 'JSONB'>, <TokenType.TDIGEST: 'TDIGEST'>, <TokenType.CHAR: 'CHAR'>, <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.ROW: 'ROW'>, <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.TABLE: 'TABLE'>, <TokenType.DATERANGE: 'DATERANGE'>, <TokenType.TSRANGE: 'TSRANGE'>, <TokenType.DECIMAL: 'DECIMAL'>, <TokenType.NCHAR: 'NCHAR'>, <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, <TokenType.SEQUENCE: 'SEQUENCE'>, <TokenType.LONGTEXT: 'LONGTEXT'>, <TokenType.IPV6: 'IPV6'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, <TokenType.TINYINT: 'TINYINT'>, <TokenType.TINYBLOB: 'TINYBLOB'>}"}, "sqlglot.dialects.mysql.MySQL.Parser.CONJUNCTION": {"fullname": "sqlglot.dialects.mysql.MySQL.Parser.CONJUNCTION", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Parser.CONJUNCTION", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.AND: 'AND'>: <class 'sqlglot.expressions.And'>, <TokenType.OR: 'OR'>: <class 'sqlglot.expressions.Or'>, <TokenType.DAMP: 'DAMP'>: <class 'sqlglot.expressions.And'>, <TokenType.XOR: 'XOR'>: <class 'sqlglot.expressions.Xor'>, <TokenType.DPIPE: 'DPIPE'>: <class 'sqlglot.expressions.Or'>}"}, "sqlglot.dialects.mysql.MySQL.Parser.TABLE_ALIAS_TOKENS": {"fullname": "sqlglot.dialects.mysql.MySQL.Parser.TABLE_ALIAS_TOKENS", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Parser.TABLE_ALIAS_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.KILL: 'KILL'>, <TokenType.MONEY: 'MONEY'>, <TokenType.COPY: 'COPY'>, <TokenType.PERCENT: 'PERCENT'>, <TokenType.TAG: 'TAG'>, <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, <TokenType.VOLATILE: 'VOLATILE'>, <TokenType.IDENTIFIER: 'IDENTIFIER'>, <TokenType.VARBINARY: 'VARBINARY'>, <TokenType.HSTORE: 'HSTORE'>, <TokenType.ASC: 'ASC'>, <TokenType.IPADDRESS: 'IPADDRESS'>, <TokenType.ISNULL: 'ISNULL'>, <TokenType.TEMPORARY: 'TEMPORARY'>, <TokenType.PROCEDURE: 'PROCEDURE'>, <TokenType.SCHEMA: 'SCHEMA'>, <TokenType.NUMRANGE: 'NUMRANGE'>, <TokenType.DATE32: 'DATE32'>, <TokenType.INT8RANGE: 'INT8RANGE'>, <TokenType.ANTI: 'ANTI'>, <TokenType.AGGREGATEFUNCTION: 'AGGREGATEFUNCTION'>, <TokenType.VIEW: 'VIEW'>, <TokenType.VARCHAR: 'VARCHAR'>, <TokenType.TIMETZ: 'TIMETZ'>, <TokenType.GEOMETRY: 'GEOMETRY'>, <TokenType.BEGIN: 'BEGIN'>, <TokenType.ENUM8: 'ENUM8'>, <TokenType.INDEX: 'INDEX'>, <TokenType.PARTITION: 'PARTITION'>, <TokenType.UINT256: 'UINT256'>, <TokenType.BIGINT: 'BIGINT'>, <TokenType.CACHE: 'CACHE'>, <TokenType.OPERATOR: 'OPERATOR'>, <TokenType.COLUMN: 'COLUMN'>, <TokenType.INT128: 'INT128'>, <TokenType.SMALLMONEY: 'SMALLMONEY'>, <TokenType.HLLSKETCH: 'HLLSKETCH'>, <TokenType.UNPIVOT: 'UNPIVOT'>, <TokenType.SMALLINT: 'SMALLINT'>, <TokenType.INT256: 'INT256'>, <TokenType.FLOAT: 'FLOAT'>, <TokenType.COMMIT: 'COMMIT'>, <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, <TokenType.EXISTS: 'EXISTS'>, <TokenType.NULL: 'NULL'>, <TokenType.RECURSIVE: 'RECURSIVE'>, <TokenType.SET: 'SET'>, <TokenType.NULLABLE: 'NULLABLE'>, <TokenType.REFRESH: 'REFRESH'>, <TokenType.TINYTEXT: 'TINYTEXT'>, <TokenType.SHOW: 'SHOW'>, <TokenType.DEFAULT: 'DEFAULT'>, <TokenType.DATE: 'DATE'>, <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <TokenType.MERGE: 'MERGE'>, <TokenType.FIRST: 'FIRST'>, <TokenType.BINARY: 'BINARY'>, <TokenType.ARRAY: 'ARRAY'>, <TokenType.SERIAL: 'SERIAL'>, <TokenType.EXECUTE: 'EXECUTE'>, <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, <TokenType.INTERVAL: 'INTERVAL'>, <TokenType.PRAGMA: 'PRAGMA'>, <TokenType.STORAGE_INTEGRATION: 'STORAGE_INTEGRATION'>, <TokenType.BPCHAR: 'BPCHAR'>, <TokenType.BIT: 'BIT'>, <TokenType.UINT: 'UINT'>, <TokenType.UUID: 'UUID'>, <TokenType.STRUCT: 'STRUCT'>, <TokenType.FALSE: 'FALSE'>, <TokenType.FUNCTION: 'FUNCTION'>, <TokenType.TOP: 'TOP'>, <TokenType.SUPER: 'SUPER'>, <TokenType.CASE: 'CASE'>, <TokenType.IMAGE: 'IMAGE'>, <TokenType.UBIGINT: 'UBIGINT'>, <TokenType.LONGBLOB: 'LONGBLOB'>, <TokenType.ROLLUP: 'ROLLUP'>, <TokenType.VAR: 'VAR'>, <TokenType.COMMAND: 'COMMAND'>, <TokenType.LOAD: 'LOAD'>, <TokenType.TRUNCATE: 'TRUNCATE'>, <TokenType.KEEP: 'KEEP'>, <TokenType.UMEDIUMINT: 'UMEDIUMINT'>, <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, <TokenType.UINT128: 'UINT128'>, <TokenType.END: 'END'>, <TokenType.MAP: 'MAP'>, <TokenType.IPV4: 'IPV4'>, <TokenType.USERDEFINED: 'USERDEFINED'>, <TokenType.REFERENCES: 'REFERENCES'>, <TokenType.REPLACE: 'REPLACE'>, <TokenType.RANGE: 'RANGE'>, <TokenType.NVARCHAR: 'NVARCHAR'>, <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, <TokenType.TRUE: 'TRUE'>, <TokenType.TIMESTAMP_MS: 'TIMESTAMP_MS'>, <TokenType.VARIANT: 'VARIANT'>, <TokenType.ENUM: 'ENUM'>, <TokenType.USMALLINT: 'USMALLINT'>, <TokenType.OVERLAPS: 'OVERLAPS'>, <TokenType.TIMESTAMP_S: 'TIMESTAMP_S'>, <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, <TokenType.UNIQUE: 'UNIQUE'>, <TokenType.ORDINALITY: 'ORDINALITY'>, <TokenType.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>, <TokenType.TEXT: 'TEXT'>, <TokenType.DATABASE: 'DATABASE'>, <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, <TokenType.PSEUDO_TYPE: 'PSEUDO_TYPE'>, <TokenType.FIXEDSTRING: 'FIXEDSTRING'>, <TokenType.NEXT: 'NEXT'>, <TokenType.INT: 'INT'>, <TokenType.BIGSERIAL: 'BIGSERIAL'>, <TokenType.BOOLEAN: 'BOOLEAN'>, <TokenType.IS: 'IS'>, <TokenType.CONSTRAINT: 'CONSTRAINT'>, <TokenType.FINAL: 'FINAL'>, <TokenType.UNKNOWN: 'UNKNOWN'>, <TokenType.SETTINGS: 'SETTINGS'>, <TokenType.ROWS: 'ROWS'>, <TokenType.TSTZRANGE: 'TSTZRANGE'>, <TokenType.DATETIME64: 'DATETIME64'>, <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, <TokenType.DATETIME: 'DATETIME'>, <TokenType.MEDIUMINT: 'MEDIUMINT'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>, <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, <TokenType.XML: 'XML'>, <TokenType.JSON: 'JSON'>, <TokenType.UTINYINT: 'UTINYINT'>, <TokenType.DELETE: 'DELETE'>, <TokenType.TIME: 'TIME'>, <TokenType.UDECIMAL: 'UDECIMAL'>, <TokenType.NESTED: 'NESTED'>, <TokenType.SEMI: 'SEMI'>, <TokenType.DESC: 'DESC'>, <TokenType.ROWVERSION: 'ROWVERSION'>, <TokenType.TIMESTAMP_NS: 'TIMESTAMP_NS'>, <TokenType.ANY: 'ANY'>, <TokenType.DIV: 'DIV'>, <TokenType.DICTIONARY: 'DICTIONARY'>, <TokenType.INET: 'INET'>, <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, <TokenType.COMMENT: 'COMMENT'>, <TokenType.CURRENT_USER: 'CURRENT_USER'>, <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>, <TokenType.ALL: 'ALL'>, <TokenType.NAME: 'NAME'>, <TokenType.SOME: 'SOME'>, <TokenType.ENUM16: 'ENUM16'>, <TokenType.YEAR: 'YEAR'>, <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, <TokenType.DOUBLE: 'DOUBLE'>, <TokenType.INT4RANGE: 'INT4RANGE'>, <TokenType.FORMAT: 'FORMAT'>, <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, <TokenType.IPPREFIX: 'IPPREFIX'>, <TokenType.OVERWRITE: 'OVERWRITE'>, <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>, <TokenType.COLLATE: 'COLLATE'>, <TokenType.FILTER: 'FILTER'>, <TokenType.JSONB: 'JSONB'>, <TokenType.TDIGEST: 'TDIGEST'>, <TokenType.CHAR: 'CHAR'>, <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.ROW: 'ROW'>, <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.TABLE: 'TABLE'>, <TokenType.DATERANGE: 'DATERANGE'>, <TokenType.TSRANGE: 'TSRANGE'>, <TokenType.ESCAPE: 'ESCAPE'>, <TokenType.PIVOT: 'PIVOT'>, <TokenType.DECIMAL: 'DECIMAL'>, <TokenType.NCHAR: 'NCHAR'>, <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, <TokenType.UPDATE: 'UPDATE'>, <TokenType.MODEL: 'MODEL'>, <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, <TokenType.SEQUENCE: 'SEQUENCE'>, <TokenType.LONGTEXT: 'LONGTEXT'>, <TokenType.DESCRIBE: 'DESCRIBE'>, <TokenType.IPV6: 'IPV6'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, <TokenType.TINYINT: 'TINYINT'>, <TokenType.TINYBLOB: 'TINYBLOB'>}"}, "sqlglot.dialects.mysql.MySQL.Parser.RANGE_PARSERS": {"fullname": "sqlglot.dialects.mysql.MySQL.Parser.RANGE_PARSERS", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Parser.RANGE_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.BETWEEN: 'BETWEEN'>: <function Parser.<lambda>>, <TokenType.GLOB: 'GLOB'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.ILIKE: 'ILIKE'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.IN: 'IN'>: <function Parser.<lambda>>, <TokenType.IRLIKE: 'IRLIKE'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.IS: 'IS'>: <function Parser.<lambda>>, <TokenType.LIKE: 'LIKE'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.OVERLAPS: 'OVERLAPS'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.RLIKE: 'RLIKE'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.SIMILAR_TO: 'SIMILAR_TO'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.FOR: 'FOR'>: <function Parser.<lambda>>, <TokenType.MEMBER_OF: 'MEMBER_OF'>: <function MySQL.Parser.<lambda>>}"}, "sqlglot.dialects.mysql.MySQL.Parser.FUNCTIONS": {"fullname": "sqlglot.dialects.mysql.MySQL.Parser.FUNCTIONS", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Parser.FUNCTIONS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ABS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Abs'>>, 'ADD_MONTHS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AddMonths'>>, 'ANONYMOUS_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnonymousAggFunc'>>, 'ANY_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnyValue'>>, 'APPROX_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_COUNT_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'APPROX_TOP_K': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxTopK'>>, 'ARG_MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARGMAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'MAX_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARG_MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARGMIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'MIN_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Array'>>, 'ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAgg'>>, 'ARRAY_ALL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAll'>>, 'ARRAY_ANY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAny'>>, 'ARRAY_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CONSTRUCT_COMPACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConstructCompact'>>, 'ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayContains'>>, 'FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_OVERLAPS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayOverlaps'>>, 'ARRAY_SIZE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_SORT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySort'>>, 'ARRAY_SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySum'>>, 'ARRAY_TO_STRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_JOIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_UNION_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUnionAgg'>>, 'ARRAY_UNIQUE_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUniqueAgg'>>, 'AVG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Avg'>>, 'CASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Case'>>, 'CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cast'>>, 'CAST_TO_STR_TYPE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CastToStrType'>>, 'CBRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cbrt'>>, 'CEIL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CEILING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CHR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'COALESCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'IFNULL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'NVL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'COLLATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Collate'>>, 'COMBINED_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedAggFunc'>>, 'COMBINED_PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedParameterizedAgg'>>, 'CONCAT': <function Parser.<lambda>>, 'CONCAT_WS': <function Parser.<lambda>>, 'CONNECT_BY_ROOT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ConnectByRoot'>>, 'CONVERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Convert'>>, 'CORR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Corr'>>, 'COUNT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Count'>>, 'COUNT_IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COUNTIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COVAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarPop'>>, 'COVAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarSamp'>>, 'CURRENT_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDate'>>, 'CURRENT_DATETIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDatetime'>>, 'CURRENT_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTime'>>, 'CURRENT_TIMESTAMP': <bound method Func.from_arg_list of 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of <class 'sqlglot.expressions.DateTrunc'>>, 'DATETIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeAdd'>>, 'DATETIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeDiff'>>, 'DATETIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeSub'>>, 'DATETIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeTrunc'>>, 'DAY': <function MySQL.Parser.<lambda>>, 'DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAYOFMONTH': <function MySQL.Parser.<lambda>>, 'DAY_OF_WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAYOFWEEK': <function MySQL.Parser.<lambda>>, 'DAY_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DAYOFYEAR': <function MySQL.Parser.<lambda>>, 'DECODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Decode'>>, 'DI_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DiToDate'>>, 'ENCODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Encode'>>, 'EXP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Exp'>>, 'EXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Explode'>>, 'EXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ExplodeOuter'>>, 'EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Extract'>>, 'FIRST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.First'>>, 'FIRST_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FirstValue'>>, 'FLATTEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Flatten'>>, 'FLOOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Floor'>>, 'FROM_BASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase'>>, 'FROM_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase64'>>, 'GENERATE_DATE_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GenerateDateArray'>>, 'GENERATE_SERIES': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GenerateSeries'>>, 'GREATEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Greatest'>>, 'GROUP_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GroupConcat'>>, 'HEX': <function build_hex>, 'HLL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Hll'>>, 'IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'IIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'INITCAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Initcap'>>, 'IS_INF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'ISINF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'IS_NAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'ISNAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'J_S_O_N_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArray'>>, 'J_S_O_N_ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArrayAgg'>>, 'JSON_ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArrayContains'>>, 'JSONB_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONBExtract'>>, 'JSONB_EXTRACT_SCALAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONBExtractScalar'>>, 'JSON_EXTRACT': <function build_extract_json_with_path.<locals>._builder>, 'JSON_EXTRACT_SCALAR': <function build_extract_json_with_path.<locals>._builder>, 'JSON_FORMAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONFormat'>>, 'J_S_O_N_OBJECT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONObject'>>, 'J_S_O_N_OBJECT_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONObjectAgg'>>, 'J_S_O_N_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONTable'>>, 'LAG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lag'>>, 'LAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Last'>>, 'LAST_DAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastDay'>>, 'LAST_DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastDay'>>, 'LAST_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastValue'>>, 'LEAD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lead'>>, 'LEAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Least'>>, 'LEFT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Left'>>, 'LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Length'>>, 'LEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Length'>>, 'LEVENSHTEIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Levenshtein'>>, 'LN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ln'>>, 'LOG': <function build_logarithm>, 'LOGICAL_AND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'BOOL_AND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'BOOLAND_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'LOGICAL_OR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'BOOL_OR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'BOOLOR_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'LOWER': <function build_lower>, 'LCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lower'>>, 'LOWER_HEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LowerHex'>>, 'MD5': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MD5'>>, 'MD5_DIGEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MD5Digest'>>, 'MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Map'>>, 'MAP_FROM_ENTRIES': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MapFromEntries'>>, 'MATCH_AGAINST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MatchAgainst'>>, 'MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Max'>>, 'MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Min'>>, 'MONTH': <function MySQL.Parser.<lambda>>, 'MONTHS_BETWEEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MonthsBetween'>>, 'NEXT_VALUE_FOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NextValueFor'>>, 'NTH_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NthValue'>>, 'NULLIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Nullif'>>, 'NUMBER_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NumberToStr'>>, 'NVL2': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Nvl2'>>, 'OPEN_J_S_O_N': <bound method Func.from_arg_list of <class 'sqlglot.expressions.OpenJSON'>>, 'PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParameterizedAgg'>>, 'PARSE_JSON': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParseJSON'>>, 'JSON_PARSE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParseJSON'>>, 'PERCENTILE_CONT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PercentileCont'>>, 'PERCENTILE_DISC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PercentileDisc'>>, 'POSEXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Posexplode'>>, 'POSEXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PosexplodeOuter'>>, 'POWER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Pow'>>, 'POW': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Pow'>>, 'PREDICT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Predict'>>, 'QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quantile'>>, 'QUARTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quarter'>>, 'RAND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'RANDOM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'RANDN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Randn'>>, 'RANGE_N': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RangeN'>>, 'READ_CSV': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ReadCSV'>>, 'REDUCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Reduce'>>, 'REGEXP_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpExtract'>>, 'REGEXP_I_LIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpILike'>>, 'REGEXP_LIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpLike'>>, 'REGEXP_REPLACE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpReplace'>>, 'REGEXP_SPLIT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpSplit'>>, 'REPEAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Repeat'>>, 'RIGHT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Right'>>, 'ROUND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Round'>>, 'ROW_NUMBER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RowNumber'>>, 'SHA': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA'>>, 'SHA1': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA'>>, 'SHA2': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA2'>>, 'SAFE_DIVIDE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SafeDivide'>>, 'SIGN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sign'>>, 'SIGNUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sign'>>, 'SORT_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SortArray'>>, 'SPLIT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Split'>>, 'SQRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sqrt'>>, 'STANDARD_HASH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StandardHash'>>, 'STAR_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StarMap'>>, 'STARTS_WITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STARTSWITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STDDEV': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stddev'>>, 'STDDEV_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StddevPop'>>, 'STDDEV_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StddevSamp'>>, 'STR_POSITION': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrPosition'>>, 'STR_TO_DATE': <function _str_to_date>, 'STR_TO_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToMap'>>, 'STR_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToTime'>>, 'STR_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToUnix'>>, 'STRUCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Struct'>>, 'STRUCT_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StructExtract'>>, 'STUFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stuff'>>, 'INSERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stuff'>>, 'SUBSTRING': 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'sqlglot.expressions.TimeToStr'>>, 'TIME_TO_TIME_STR': <function Parser.<lambda>>, 'TIME_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeToUnix'>>, 'TIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeTrunc'>>, 'TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Timestamp'>>, 'TIMESTAMP_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampAdd'>>, 'TIMESTAMPDIFF': <function build_date_delta.<locals>._builder>, 'TIMESTAMP_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampDiff'>>, 'TIMESTAMP_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampFromParts'>>, 'TIMESTAMPFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampFromParts'>>, 'TIMESTAMP_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampSub'>>, 'TIMESTAMP_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampTrunc'>>, 'TO_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToArray'>>, 'TO_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToBase64'>>, 'TO_CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToChar'>>, 'TO_DAYS': <function MySQL.Parser.<lambda>>, 'TO_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToMap'>>, 'TO_NUMBER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToNumber'>>, 'TRANSFORM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Transform'>>, 'TRIM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Trim'>>, 'TRY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Try'>>, 'TRY_CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TryCast'>>, 'TS_OR_DI_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDiToDi'>>, 'TS_OR_DS_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsAdd'>>, 'TS_OR_DS_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsDiff'>>, 'TS_OR_DS_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToDate'>>, 'TS_OR_DS_TO_DATE_STR': <function Parser.<lambda>>, 'TS_OR_DS_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTime'>>, 'TS_OR_DS_TO_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTimestamp'>>, 'UNHEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Unhex'>>, 'UNIX_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixDate'>>, 'UNIX_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToStr'>>, 'UNIX_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTime'>>, 'UNIX_TO_TIME_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTimeStr'>>, 'UPPER': <function build_upper>, 'UCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Upper'>>, 'VAR_MAP': <function build_var_map>, 'VARIANCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'VAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'WEEK': <function MySQL.Parser.<lambda>>, 'WEEK_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.WeekOfYear'>>, 'WEEKOFYEAR': <function MySQL.Parser.<lambda>>, 'WHEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.When'>>, 'X_M_L_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.XMLTable'>>, 'XOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Xor'>>, 'YEAR': <function MySQL.Parser.<lambda>>, 'GLOB': <function Parser.<lambda>>, 'JSON_EXTRACT_PATH_TEXT': <function build_extract_json_with_path.<locals>._builder>, 'LIKE': <function build_like>, 'LOG2': <function Parser.<lambda>>, 'LOG10': <function Parser.<lambda>>, 'MOD': <function build_mod>, 'TO_HEX': <function build_hex>, 'DATE_FORMAT': <function build_formatted_time.<locals>._builder>, 'INSTR': <function MySQL.Parser.<lambda>>, 'FROM_UNIXTIME': <function build_formatted_time.<locals>._builder>, 'ISNULL': <function isnull_to_is_null>, 'LOCATE': <function locate_to_strposition>, 'MAKETIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'MONTHNAME': <function MySQL.Parser.<lambda>>}"}, "sqlglot.dialects.mysql.MySQL.Parser.FUNCTION_PARSERS": {"fullname": "sqlglot.dialects.mysql.MySQL.Parser.FUNCTION_PARSERS", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Parser.FUNCTION_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'CAST': <function Parser.<lambda>>, 'CONVERT': <function Parser.<lambda>>, 'DECODE': <function Parser.<lambda>>, 'EXTRACT': <function Parser.<lambda>>, 'JSON_OBJECT': <function Parser.<lambda>>, 'JSON_OBJECTAGG': <function Parser.<lambda>>, 'JSON_TABLE': <function Parser.<lambda>>, 'MATCH': <function Parser.<lambda>>, 'OPENJSON': <function Parser.<lambda>>, 'POSITION': <function Parser.<lambda>>, 'PREDICT': <function Parser.<lambda>>, 'SAFE_CAST': <function Parser.<lambda>>, 'STRING_AGG': <function Parser.<lambda>>, 'SUBSTRING': <function Parser.<lambda>>, 'TRIM': <function Parser.<lambda>>, 'TRY_CAST': <function Parser.<lambda>>, 'TRY_CONVERT': <function Parser.<lambda>>, 'CHAR': <function MySQL.Parser.<lambda>>, 'GROUP_CONCAT': <function MySQL.Parser.<lambda>>, 'VALUES': <function MySQL.Parser.<lambda>>}"}, "sqlglot.dialects.mysql.MySQL.Parser.STATEMENT_PARSERS": {"fullname": "sqlglot.dialects.mysql.MySQL.Parser.STATEMENT_PARSERS", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Parser.STATEMENT_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.ALTER: 'ALTER'>: <function Parser.<lambda>>, <TokenType.BEGIN: 'BEGIN'>: <function Parser.<lambda>>, <TokenType.CACHE: 'CACHE'>: <function Parser.<lambda>>, <TokenType.COMMENT: 'COMMENT'>: <function Parser.<lambda>>, <TokenType.COMMIT: 'COMMIT'>: <function Parser.<lambda>>, <TokenType.COPY: 'COPY'>: <function Parser.<lambda>>, <TokenType.CREATE: 'CREATE'>: <function Parser.<lambda>>, <TokenType.DELETE: 'DELETE'>: <function Parser.<lambda>>, <TokenType.DESC: 'DESC'>: <function Parser.<lambda>>, <TokenType.DESCRIBE: 'DESCRIBE'>: <function Parser.<lambda>>, <TokenType.DROP: 'DROP'>: <function Parser.<lambda>>, <TokenType.INSERT: 'INSERT'>: <function Parser.<lambda>>, <TokenType.KILL: 'KILL'>: <function Parser.<lambda>>, <TokenType.LOAD: 'LOAD'>: <function Parser.<lambda>>, <TokenType.MERGE: 'MERGE'>: <function Parser.<lambda>>, <TokenType.PIVOT: 'PIVOT'>: <function Parser.<lambda>>, <TokenType.PRAGMA: 'PRAGMA'>: <function Parser.<lambda>>, <TokenType.REFRESH: 'REFRESH'>: <function Parser.<lambda>>, <TokenType.ROLLBACK: 'ROLLBACK'>: <function Parser.<lambda>>, <TokenType.SET: 'SET'>: <function Parser.<lambda>>, <TokenType.TRUNCATE: 'TRUNCATE'>: <function Parser.<lambda>>, <TokenType.UNCACHE: 'UNCACHE'>: <function Parser.<lambda>>, <TokenType.UPDATE: 'UPDATE'>: <function Parser.<lambda>>, <TokenType.USE: 'USE'>: <function Parser.<lambda>>, <TokenType.SEMICOLON: 'SEMICOLON'>: <function Parser.<lambda>>, <TokenType.SHOW: 'SHOW'>: <function MySQL.Parser.<lambda>>}"}, "sqlglot.dialects.mysql.MySQL.Parser.SHOW_PARSERS": {"fullname": "sqlglot.dialects.mysql.MySQL.Parser.SHOW_PARSERS", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Parser.SHOW_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'BINARY LOGS': <function _show_parser.<locals>._parse>, 'MASTER LOGS': <function _show_parser.<locals>._parse>, 'BINLOG EVENTS': <function _show_parser.<locals>._parse>, 'CHARACTER SET': <function _show_parser.<locals>._parse>, 'CHARSET': <function _show_parser.<locals>._parse>, 'COLLATION': <function _show_parser.<locals>._parse>, 'FULL COLUMNS': <function _show_parser.<locals>._parse>, 'COLUMNS': <function _show_parser.<locals>._parse>, 'CREATE DATABASE': <function _show_parser.<locals>._parse>, 'CREATE EVENT': <function _show_parser.<locals>._parse>, 'CREATE FUNCTION': <function _show_parser.<locals>._parse>, 'CREATE PROCEDURE': <function _show_parser.<locals>._parse>, 'CREATE TABLE': <function _show_parser.<locals>._parse>, 'CREATE TRIGGER': <function _show_parser.<locals>._parse>, 'CREATE VIEW': <function _show_parser.<locals>._parse>, 'DATABASES': <function _show_parser.<locals>._parse>, 'SCHEMAS': <function _show_parser.<locals>._parse>, 'ENGINE': <function _show_parser.<locals>._parse>, 'STORAGE ENGINES': <function _show_parser.<locals>._parse>, 'ENGINES': <function _show_parser.<locals>._parse>, 'ERRORS': <function _show_parser.<locals>._parse>, 'EVENTS': <function _show_parser.<locals>._parse>, 'FUNCTION CODE': <function _show_parser.<locals>._parse>, 'FUNCTION STATUS': <function _show_parser.<locals>._parse>, 'GRANTS': <function _show_parser.<locals>._parse>, 'INDEX': <function _show_parser.<locals>._parse>, 'MASTER STATUS': <function _show_parser.<locals>._parse>, 'OPEN TABLES': <function _show_parser.<locals>._parse>, 'PLUGINS': <function _show_parser.<locals>._parse>, 'PROCEDURE CODE': <function _show_parser.<locals>._parse>, 'PROCEDURE STATUS': <function _show_parser.<locals>._parse>, 'PRIVILEGES': <function _show_parser.<locals>._parse>, 'FULL PROCESSLIST': <function _show_parser.<locals>._parse>, 'PROCESSLIST': <function _show_parser.<locals>._parse>, 'PROFILE': <function _show_parser.<locals>._parse>, 'PROFILES': <function _show_parser.<locals>._parse>, 'RELAYLOG EVENTS': <function _show_parser.<locals>._parse>, 'REPLICAS': <function _show_parser.<locals>._parse>, 'SLAVE HOSTS': <function _show_parser.<locals>._parse>, 'REPLICA STATUS': <function _show_parser.<locals>._parse>, 'SLAVE STATUS': <function _show_parser.<locals>._parse>, 'GLOBAL STATUS': <function _show_parser.<locals>._parse>, 'SESSION STATUS': <function _show_parser.<locals>._parse>, 'STATUS': <function _show_parser.<locals>._parse>, 'TABLE STATUS': <function _show_parser.<locals>._parse>, 'FULL TABLES': <function _show_parser.<locals>._parse>, 'TABLES': <function _show_parser.<locals>._parse>, 'TRIGGERS': <function _show_parser.<locals>._parse>, 'GLOBAL VARIABLES': <function _show_parser.<locals>._parse>, 'SESSION VARIABLES': <function _show_parser.<locals>._parse>, 'VARIABLES': <function _show_parser.<locals>._parse>, 'WARNINGS': <function _show_parser.<locals>._parse>}"}, "sqlglot.dialects.mysql.MySQL.Parser.PROPERTY_PARSERS": {"fullname": "sqlglot.dialects.mysql.MySQL.Parser.PROPERTY_PARSERS", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Parser.PROPERTY_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ALLOWED_VALUES': <function Parser.<lambda>>, 'ALGORITHM': <function Parser.<lambda>>, 'AUTO': <function Parser.<lambda>>, 'AUTO_INCREMENT': <function Parser.<lambda>>, 'BACKUP': <function Parser.<lambda>>, 'BLOCKCOMPRESSION': <function Parser.<lambda>>, 'CHARSET': <function Parser.<lambda>>, 'CHARACTER SET': <function Parser.<lambda>>, 'CHECKSUM': <function Parser.<lambda>>, 'CLUSTER BY': <function Parser.<lambda>>, 'CLUSTERED': <function Parser.<lambda>>, 'COLLATE': <function Parser.<lambda>>, 'COMMENT': <function Parser.<lambda>>, 'CONTAINS': <function Parser.<lambda>>, 'COPY': <function Parser.<lambda>>, 'DATABLOCKSIZE': <function Parser.<lambda>>, 'DATA_DELETION': <function Parser.<lambda>>, 'DEFINER': <function Parser.<lambda>>, 'DETERMINISTIC': <function Parser.<lambda>>, 'DISTKEY': <function Parser.<lambda>>, 'DISTSTYLE': <function Parser.<lambda>>, 'ENGINE': <function Parser.<lambda>>, 'EXECUTE': <function Parser.<lambda>>, 'EXTERNAL': <function Parser.<lambda>>, 'FALLBACK': <function Parser.<lambda>>, 'FORMAT': <function Parser.<lambda>>, 'FREESPACE': <function Parser.<lambda>>, 'GLOBAL': <function Parser.<lambda>>, 'HEAP': <function Parser.<lambda>>, 'ICEBERG': <function Parser.<lambda>>, 'IMMUTABLE': <function Parser.<lambda>>, 'INHERITS': <function Parser.<lambda>>, 'INPUT': <function Parser.<lambda>>, 'JOURNAL': <function Parser.<lambda>>, 'LANGUAGE': <function Parser.<lambda>>, 'LAYOUT': <function Parser.<lambda>>, 'LIFETIME': <function Parser.<lambda>>, 'LIKE': <function Parser.<lambda>>, 'LOCATION': <function Parser.<lambda>>, 'LOCK': <function MySQL.Parser.<lambda>>, 'LOCKING': <function Parser.<lambda>>, 'LOG': <function Parser.<lambda>>, 'MATERIALIZED': <function Parser.<lambda>>, 'MERGEBLOCKRATIO': <function Parser.<lambda>>, 'MODIFIES': <function Parser.<lambda>>, 'MULTISET': <function Parser.<lambda>>, 'NO': <function Parser.<lambda>>, 'ON': <function Parser.<lambda>>, 'ORDER BY': <function Parser.<lambda>>, 'OUTPUT': <function Parser.<lambda>>, 'PARTITION': <function Parser.<lambda>>, 'PARTITION BY': <function Parser.<lambda>>, 'PARTITIONED BY': <function Parser.<lambda>>, 'PARTITIONED_BY': <function Parser.<lambda>>, 'PRIMARY KEY': <function Parser.<lambda>>, 'RANGE': <function Parser.<lambda>>, 'READS': <function Parser.<lambda>>, 'REMOTE': <function Parser.<lambda>>, 'RETURNS': <function Parser.<lambda>>, 'STRICT': <function Parser.<lambda>>, 'ROW': <function Parser.<lambda>>, 'ROW_FORMAT': <function Parser.<lambda>>, 'SAMPLE': <function Parser.<lambda>>, 'SET': <function Parser.<lambda>>, 'SETTINGS': <function Parser.<lambda>>, 'SHARING': <function Parser.<lambda>>, 'SORTKEY': <function Parser.<lambda>>, 'SOURCE': <function Parser.<lambda>>, 'STABLE': <function Parser.<lambda>>, 'STORED': <function Parser.<lambda>>, 'SYSTEM_VERSIONING': <function Parser.<lambda>>, 'TBLPROPERTIES': <function Parser.<lambda>>, 'TEMP': <function Parser.<lambda>>, 'TEMPORARY': <function Parser.<lambda>>, 'TO': <function Parser.<lambda>>, 'TRANSIENT': <function Parser.<lambda>>, 'TRANSFORM': <function Parser.<lambda>>, 'TTL': <function Parser.<lambda>>, 'USING': <function Parser.<lambda>>, 'UNLOGGED': <function Parser.<lambda>>, 'VOLATILE': <function Parser.<lambda>>, 'WITH': <function Parser.<lambda>>}"}, "sqlglot.dialects.mysql.MySQL.Parser.SET_PARSERS": {"fullname": "sqlglot.dialects.mysql.MySQL.Parser.SET_PARSERS", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Parser.SET_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'GLOBAL': <function Parser.<lambda>>, 'LOCAL': <function Parser.<lambda>>, 'SESSION': <function Parser.<lambda>>, 'TRANSACTION': <function Parser.<lambda>>, 'PERSIST': <function MySQL.Parser.<lambda>>, 'PERSIST_ONLY': <function MySQL.Parser.<lambda>>, 'CHARACTER SET': <function MySQL.Parser.<lambda>>, 'CHARSET': <function MySQL.Parser.<lambda>>, 'NAMES': <function MySQL.Parser.<lambda>>}"}, "sqlglot.dialects.mysql.MySQL.Parser.CONSTRAINT_PARSERS": {"fullname": "sqlglot.dialects.mysql.MySQL.Parser.CONSTRAINT_PARSERS", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Parser.CONSTRAINT_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'AUTOINCREMENT': <function Parser.<lambda>>, 'AUTO_INCREMENT': <function Parser.<lambda>>, 'CASESPECIFIC': <function Parser.<lambda>>, 'CHARACTER SET': <function Parser.<lambda>>, 'CHECK': <function Parser.<lambda>>, 'COLLATE': <function Parser.<lambda>>, 'COMMENT': <function Parser.<lambda>>, 'COMPRESS': <function Parser.<lambda>>, 'CLUSTERED': <function Parser.<lambda>>, 'NONCLUSTERED': <function Parser.<lambda>>, 'DEFAULT': <function Parser.<lambda>>, 'ENCODE': <function Parser.<lambda>>, 'EPHEMERAL': <function Parser.<lambda>>, 'EXCLUDE': <function Parser.<lambda>>, 'FOREIGN KEY': <function Parser.<lambda>>, 'FORMAT': <function Parser.<lambda>>, 'GENERATED': <function Parser.<lambda>>, 'IDENTITY': <function Parser.<lambda>>, 'INLINE': <function Parser.<lambda>>, 'LIKE': <function Parser.<lambda>>, 'NOT': <function Parser.<lambda>>, 'NULL': <function Parser.<lambda>>, 'ON': <function Parser.<lambda>>, 'PATH': <function Parser.<lambda>>, 'PERIOD': <function Parser.<lambda>>, 'PRIMARY KEY': <function Parser.<lambda>>, 'REFERENCES': <function Parser.<lambda>>, 'TITLE': <function Parser.<lambda>>, 'TTL': <function Parser.<lambda>>, 'UNIQUE': <function Parser.<lambda>>, 'UPPERCASE': <function Parser.<lambda>>, 'WITH': <function Parser.<lambda>>, 'FULLTEXT': <function MySQL.Parser.<lambda>>, 'INDEX': <function MySQL.Parser.<lambda>>, 'KEY': <function MySQL.Parser.<lambda>>, 'SPATIAL': <function MySQL.Parser.<lambda>>}"}, "sqlglot.dialects.mysql.MySQL.Parser.ALTER_PARSERS": {"fullname": "sqlglot.dialects.mysql.MySQL.Parser.ALTER_PARSERS", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Parser.ALTER_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ADD': <function Parser.<lambda>>, 'ALTER': <function Parser.<lambda>>, 'CLUSTER BY': <function Parser.<lambda>>, 'DELETE': <function Parser.<lambda>>, 'DROP': <function Parser.<lambda>>, 'RENAME': <function Parser.<lambda>>, 'SET': <function Parser.<lambda>>, 'MODIFY': <function MySQL.Parser.<lambda>>}"}, "sqlglot.dialects.mysql.MySQL.Parser.SCHEMA_UNNAMED_CONSTRAINTS": {"fullname": "sqlglot.dialects.mysql.MySQL.Parser.SCHEMA_UNNAMED_CONSTRAINTS", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Parser.SCHEMA_UNNAMED_CONSTRAINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'EXCLUDE', 'FULLTEXT', 'KEY', 'UNIQUE', 'LIKE', 'CHECK', 'FOREIGN KEY', 'PERIOD', 'SPATIAL', 'PRIMARY KEY', 'INDEX'}"}, "sqlglot.dialects.mysql.MySQL.Parser.PROFILE_TYPES": {"fullname": "sqlglot.dialects.mysql.MySQL.Parser.PROFILE_TYPES", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Parser.PROFILE_TYPES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, Sequence[Union[Sequence[str], str]]]", "default_value": "{'ALL': (), 'CPU': (), 'IPC': (), 'MEMORY': (), 'SOURCE': (), 'SWAPS': (), 'BLOCK': ('IO',), 'CONTEXT': ('SWITCHES',), 'PAGE': ('FAULTS',)}"}, "sqlglot.dialects.mysql.MySQL.Parser.TYPE_TOKENS": {"fullname": "sqlglot.dialects.mysql.MySQL.Parser.TYPE_TOKENS", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Parser.TYPE_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.MONEY: 'MONEY'>, <TokenType.TIMESTAMP_MS: 'TIMESTAMP_MS'>, <TokenType.VARIANT: 'VARIANT'>, <TokenType.ENUM: 'ENUM'>, <TokenType.USMALLINT: 'USMALLINT'>, <TokenType.TIMESTAMP_S: 'TIMESTAMP_S'>, <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, <TokenType.VARBINARY: 'VARBINARY'>, <TokenType.HSTORE: 'HSTORE'>, <TokenType.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>, <TokenType.IPADDRESS: 'IPADDRESS'>, <TokenType.TEXT: 'TEXT'>, <TokenType.NUMRANGE: 'NUMRANGE'>, <TokenType.DATE32: 'DATE32'>, <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, <TokenType.INT8RANGE: 'INT8RANGE'>, <TokenType.PSEUDO_TYPE: 'PSEUDO_TYPE'>, <TokenType.FIXEDSTRING: 'FIXEDSTRING'>, <TokenType.AGGREGATEFUNCTION: 'AGGREGATEFUNCTION'>, <TokenType.VARCHAR: 'VARCHAR'>, <TokenType.TIMETZ: 'TIMETZ'>, <TokenType.INT: 'INT'>, <TokenType.GEOMETRY: 'GEOMETRY'>, <TokenType.ENUM8: 'ENUM8'>, <TokenType.BIGSERIAL: 'BIGSERIAL'>, <TokenType.UINT256: 'UINT256'>, <TokenType.BIGINT: 'BIGINT'>, <TokenType.INT128: 'INT128'>, <TokenType.BOOLEAN: 'BOOLEAN'>, <TokenType.SMALLMONEY: 'SMALLMONEY'>, <TokenType.UNKNOWN: 'UNKNOWN'>, <TokenType.HLLSKETCH: 'HLLSKETCH'>, <TokenType.SMALLINT: 'SMALLINT'>, <TokenType.TSTZRANGE: 'TSTZRANGE'>, <TokenType.INT256: 'INT256'>, <TokenType.DATETIME64: 'DATETIME64'>, <TokenType.FLOAT: 'FLOAT'>, <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, <TokenType.DATETIME: 'DATETIME'>, <TokenType.MEDIUMINT: 'MEDIUMINT'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>, <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, <TokenType.XML: 'XML'>, <TokenType.NULL: 'NULL'>, <TokenType.JSON: 'JSON'>, <TokenType.UTINYINT: 'UTINYINT'>, <TokenType.TIME: 'TIME'>, <TokenType.UDECIMAL: 'UDECIMAL'>, <TokenType.NESTED: 'NESTED'>, <TokenType.SET: 'SET'>, <TokenType.NULLABLE: 'NULLABLE'>, <TokenType.ROWVERSION: 'ROWVERSION'>, <TokenType.TIMESTAMP_NS: 'TIMESTAMP_NS'>, <TokenType.TINYTEXT: 'TINYTEXT'>, <TokenType.INET: 'INET'>, <TokenType.DATE: 'DATE'>, <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <TokenType.BINARY: 'BINARY'>, <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>, <TokenType.ARRAY: 'ARRAY'>, <TokenType.SERIAL: 'SERIAL'>, <TokenType.NAME: 'NAME'>, <TokenType.ENUM16: 'ENUM16'>, <TokenType.YEAR: 'YEAR'>, <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, <TokenType.INTERVAL: 'INTERVAL'>, <TokenType.DOUBLE: 'DOUBLE'>, <TokenType.INT4RANGE: 'INT4RANGE'>, <TokenType.BPCHAR: 'BPCHAR'>, <TokenType.BIT: 'BIT'>, <TokenType.UINT: 'UINT'>, <TokenType.IPPREFIX: 'IPPREFIX'>, <TokenType.UUID: 'UUID'>, <TokenType.STRUCT: 'STRUCT'>, <TokenType.SUPER: 'SUPER'>, <TokenType.JSONB: 'JSONB'>, <TokenType.TDIGEST: 'TDIGEST'>, <TokenType.CHAR: 'CHAR'>, <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.IMAGE: 'IMAGE'>, <TokenType.UBIGINT: 'UBIGINT'>, <TokenType.LONGBLOB: 'LONGBLOB'>, <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.UMEDIUMINT: 'UMEDIUMINT'>, <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, <TokenType.UINT128: 'UINT128'>, <TokenType.DATERANGE: 'DATERANGE'>, <TokenType.TSRANGE: 'TSRANGE'>, <TokenType.DECIMAL: 'DECIMAL'>, <TokenType.NCHAR: 'NCHAR'>, <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, <TokenType.MAP: 'MAP'>, <TokenType.IPV4: 'IPV4'>, <TokenType.USERDEFINED: 'USERDEFINED'>, <TokenType.LONGTEXT: 'LONGTEXT'>, <TokenType.IPV6: 'IPV6'>, <TokenType.TINYINT: 'TINYINT'>, <TokenType.TINYBLOB: 'TINYBLOB'>, <TokenType.NVARCHAR: 'NVARCHAR'>, <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>}"}, "sqlglot.dialects.mysql.MySQL.Parser.ENUM_TYPE_TOKENS": {"fullname": "sqlglot.dialects.mysql.MySQL.Parser.ENUM_TYPE_TOKENS", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Parser.ENUM_TYPE_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.ENUM: 'ENUM'>, <TokenType.ENUM8: 'ENUM8'>, <TokenType.SET: 'SET'>, <TokenType.ENUM16: 'ENUM16'>}"}, "sqlglot.dialects.mysql.MySQL.Parser.LOG_DEFAULTS_TO_LN": {"fullname": "sqlglot.dialects.mysql.MySQL.Parser.LOG_DEFAULTS_TO_LN", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Parser.LOG_DEFAULTS_TO_LN", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.mysql.MySQL.Parser.STRING_ALIASES": {"fullname": "sqlglot.dialects.mysql.MySQL.Parser.STRING_ALIASES", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Parser.STRING_ALIASES", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.mysql.MySQL.Parser.VALUES_FOLLOWED_BY_PAREN": {"fullname": "sqlglot.dialects.mysql.MySQL.Parser.VALUES_FOLLOWED_BY_PAREN", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Parser.VALUES_FOLLOWED_BY_PAREN", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.mysql.MySQL.Parser.SUPPORTS_PARTITION_SELECTION": {"fullname": "sqlglot.dialects.mysql.MySQL.Parser.SUPPORTS_PARTITION_SELECTION", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Parser.SUPPORTS_PARTITION_SELECTION", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.mysql.MySQL.Parser.SHOW_TRIE": {"fullname": "sqlglot.dialects.mysql.MySQL.Parser.SHOW_TRIE", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Parser.SHOW_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'BINARY': {'LOGS': {0: True}}, 'MASTER': {'LOGS': {0: True}, 'STATUS': {0: True}}, 'BINLOG': {'EVENTS': {0: True}}, 'CHARACTER': {'SET': {0: True}}, 'CHARSET': {0: True}, 'COLLATION': {0: True}, 'FULL': {'COLUMNS': {0: True}, 'PROCESSLIST': {0: True}, 'TABLES': {0: True}}, 'COLUMNS': {0: True}, 'CREATE': {'DATABASE': {0: True}, 'EVENT': {0: True}, 'FUNCTION': {0: True}, 'PROCEDURE': {0: True}, 'TABLE': {0: True}, 'TRIGGER': {0: True}, 'VIEW': {0: True}}, 'DATABASES': {0: True}, 'SCHEMAS': {0: True}, 'ENGINE': {0: True}, 'STORAGE': {'ENGINES': {0: True}}, 'ENGINES': {0: True}, 'ERRORS': {0: True}, 'EVENTS': {0: True}, 'FUNCTION': {'CODE': {0: True}, 'STATUS': {0: True}}, 'GRANTS': {0: True}, 'INDEX': {0: True}, 'OPEN': {'TABLES': {0: True}}, 'PLUGINS': {0: True}, 'PROCEDURE': {'CODE': {0: True}, 'STATUS': {0: True}}, 'PRIVILEGES': {0: True}, 'PROCESSLIST': {0: True}, 'PROFILE': {0: True}, 'PROFILES': {0: True}, 'RELAYLOG': {'EVENTS': {0: True}}, 'REPLICAS': {0: True}, 'SLAVE': {'HOSTS': {0: True}, 'STATUS': {0: True}}, 'REPLICA': {'STATUS': {0: True}}, 'GLOBAL': {'STATUS': {0: True}, 'VARIABLES': {0: True}}, 'SESSION': {'STATUS': {0: True}, 'VARIABLES': {0: True}}, 'STATUS': {0: True}, 'TABLE': {'STATUS': {0: True}}, 'TABLES': {0: True}, 'TRIGGERS': {0: True}, 'VARIABLES': {0: True}, 'WARNINGS': {0: True}}"}, "sqlglot.dialects.mysql.MySQL.Parser.SET_TRIE": {"fullname": "sqlglot.dialects.mysql.MySQL.Parser.SET_TRIE", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Parser.SET_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'GLOBAL': {0: True}, 'LOCAL': {0: True}, 'SESSION': {0: True}, 'TRANSACTION': {0: True}, 'PERSIST': {0: True}, 'PERSIST_ONLY': {0: True}, 'CHARACTER': {'SET': {0: True}}, 'CHARSET': {0: True}, 'NAMES': {0: True}}"}, "sqlglot.dialects.mysql.MySQL.Generator": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator", "kind": "class", "doc": "<p>Generator converts a given syntax tree to the corresponding SQL string.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>pretty:</strong> Whether to format the produced SQL string.\nDefault: False.</li>\n<li><strong>identify:</strong> Determines when an identifier should be quoted. Possible values are:\nFalse (default): Never quote, except in cases where it's mandatory by the dialect.\nTrue or 'always': Always quote.\n'safe': Only quote identifiers that are case insensitive.</li>\n<li><strong>normalize:</strong> Whether to normalize identifiers to lowercase.\nDefault: False.</li>\n<li><strong>pad:</strong> The pad size in a formatted string. For example, this affects the indentation of\na projection in a query, relative to its nesting level.\nDefault: 2.</li>\n<li><strong>indent:</strong> The indentation size in a formatted string. For example, this affects the\nindentation of subqueries and filters under a <code>WHERE</code> clause.\nDefault: 2.</li>\n<li><strong>normalize_functions:</strong> How to normalize function names. Possible values are:\n\"upper\" or True (default): Convert names to uppercase.\n\"lower\": Convert names to lowercase.\nFalse: Disables function name normalization.</li>\n<li><strong>unsupported_level:</strong> Determines the generator's behavior when it encounters unsupported expressions.\nDefault ErrorLevel.WARN.</li>\n<li><strong>max_unsupported:</strong> Maximum number of unsupported messages to include in a raised UnsupportedError.\nThis is only relevant if unsupported_level is ErrorLevel.RAISE.\nDefault: 3</li>\n<li><strong>leading_comma:</strong> Whether the comma is leading or trailing in select expressions.\nThis is only relevant when generating in pretty mode.\nDefault: False</li>\n<li><strong>max_text_width:</strong> The max number of characters in a segment before creating new lines in pretty mode.\nThe default is on the smaller end because the length only represents a segment and not the true\nline length.\nDefault: 80</li>\n<li><strong>comments:</strong> Whether to preserve comments in the output SQL code.\nDefault: True</li>\n</ul>\n", "bases": "sqlglot.generator.Generator"}, "sqlglot.dialects.mysql.MySQL.Generator.LOCKING_READS_SUPPORTED": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.LOCKING_READS_SUPPORTED", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.LOCKING_READS_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.mysql.MySQL.Generator.NULL_ORDERING_SUPPORTED": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.NULL_ORDERING_SUPPORTED", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.NULL_ORDERING_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "None"}, "sqlglot.dialects.mysql.MySQL.Generator.JOIN_HINTS": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.JOIN_HINTS", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.JOIN_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.mysql.MySQL.Generator.TABLE_HINTS": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.TABLE_HINTS", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.TABLE_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.mysql.MySQL.Generator.DUPLICATE_KEY_UPDATE_WITH_SET": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.DUPLICATE_KEY_UPDATE_WITH_SET", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.DUPLICATE_KEY_UPDATE_WITH_SET", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.mysql.MySQL.Generator.QUERY_HINT_SEP": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.QUERY_HINT_SEP", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.QUERY_HINT_SEP", "kind": "variable", "doc": "<p></p>\n", "default_value": "' '"}, "sqlglot.dialects.mysql.MySQL.Generator.VALUES_AS_TABLE": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.VALUES_AS_TABLE", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.VALUES_AS_TABLE", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.mysql.MySQL.Generator.NVL2_SUPPORTED": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.NVL2_SUPPORTED", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.NVL2_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.mysql.MySQL.Generator.LAST_DAY_SUPPORTS_DATE_PART": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.LAST_DAY_SUPPORTS_DATE_PART", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.LAST_DAY_SUPPORTS_DATE_PART", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.mysql.MySQL.Generator.JSON_TYPE_REQUIRED_FOR_EXTRACTION": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.JSON_TYPE_REQUIRED_FOR_EXTRACTION", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.JSON_TYPE_REQUIRED_FOR_EXTRACTION", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.mysql.MySQL.Generator.JSON_PATH_BRACKETED_KEY_SUPPORTED": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.JSON_PATH_BRACKETED_KEY_SUPPORTED", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.JSON_PATH_BRACKETED_KEY_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.mysql.MySQL.Generator.JSON_KEY_VALUE_PAIR_SEP": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.JSON_KEY_VALUE_PAIR_SEP", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.JSON_KEY_VALUE_PAIR_SEP", "kind": "variable", "doc": "<p></p>\n", "default_value": "','"}, "sqlglot.dialects.mysql.MySQL.Generator.SUPPORTS_TO_NUMBER": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.SUPPORTS_TO_NUMBER", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.SUPPORTS_TO_NUMBER", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.mysql.MySQL.Generator.TRANSFORMS": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.TRANSFORMS", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.JSONPathFilter'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathKey'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRecursive'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRoot'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathScript'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSelector'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSlice'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSubscript'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathUnion'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathWildcard'>: <function <lambda>>, <class 'sqlglot.expressions.AllowedValuesProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.BackupProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CaseSpecificColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CollateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CommentColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DateFormatColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DefaultColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EncodeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EphemeralColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExcludeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExternalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.GlobalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.HeapProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IcebergProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InheritsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InlineLengthColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IntervalSpan'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtract'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtractScalar'>: <function arrow_json_extract_sql>, <class 'sqlglot.expressions.LanguageProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LocationProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LogProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.MaterializedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NonClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NotForReplicationColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnCommitProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnUpdateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OutputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.PathColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ReturnsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SampleProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetConfigProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SettingsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SharingProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlReadWriteProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlSecurityProperty'>: <function Generator.<lambda>>, <class 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Generator.<lambda>>, <class 'sqlglot.expressions.VolatileProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithOperator'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ArrayAgg'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.CurrentDate'>: <function no_paren_current_date_sql>, <class 'sqlglot.expressions.DateDiff'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.DateAdd'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.DateStrToDate'>: <function datestrtodate_sql>, <class 'sqlglot.expressions.DateSub'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.DateTrunc'>: <function _date_trunc_sql>, <class 'sqlglot.expressions.Day'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.DayOfMonth'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.DayOfWeek'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.DayOfYear'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.GroupConcat'>: <function MySQL.Generator.<lambda>>, <class 'sqlglot.expressions.ILike'>: <function no_ilike_sql>, <class 'sqlglot.expressions.Max'>: <function max_or_greatest>, <class 'sqlglot.expressions.Min'>: <function min_or_least>, <class 'sqlglot.expressions.Month'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.NullSafeEQ'>: <function MySQL.Generator.<lambda>>, <class 'sqlglot.expressions.NullSafeNEQ'>: <function MySQL.Generator.<lambda>>, <class 'sqlglot.expressions.ParseJSON'>: <function MySQL.Generator.<lambda>>, <class 'sqlglot.expressions.Pivot'>: <function no_pivot_sql>, <class 'sqlglot.expressions.Select'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.StrPosition'>: <function strposition_to_locate_sql>, <class 'sqlglot.expressions.StrToDate'>: <function _str_to_date_sql>, <class 'sqlglot.expressions.StrToTime'>: <function _str_to_date_sql>, <class 'sqlglot.expressions.Stuff'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.TableSample'>: <function no_tablesample_sql>, <class 'sqlglot.expressions.TimeFromParts'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.TimestampAdd'>: <function date_add_interval_sql.<locals>.func>, <class 'sqlglot.expressions.TimestampDiff'>: <function MySQL.Generator.<lambda>>, <class 'sqlglot.expressions.TimestampSub'>: <function date_add_interval_sql.<locals>.func>, <class 'sqlglot.expressions.TimeStrToUnix'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.TimeStrToTime'>: <function MySQL.Generator.<lambda>>, <class 'sqlglot.expressions.TimeToStr'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.Trim'>: <function _trim_sql>, <class 'sqlglot.expressions.TryCast'>: <function no_trycast_sql>, <class 'sqlglot.expressions.TsOrDsAdd'>: <function date_add_sql.<locals>.func>, <class 'sqlglot.expressions.TsOrDsDiff'>: <function MySQL.Generator.<lambda>>, <class 'sqlglot.expressions.TsOrDsToDate'>: <function _ts_or_ds_to_date_sql>, <class 'sqlglot.expressions.UnixToTime'>: <function _unix_to_time_sql>, <class 'sqlglot.expressions.Week'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.WeekOfYear'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.Year'>: <function _remove_ts_or_ds_to_date.<locals>.func>}"}, "sqlglot.dialects.mysql.MySQL.Generator.UNSIGNED_TYPE_MAPPING": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.UNSIGNED_TYPE_MAPPING", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.UNSIGNED_TYPE_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.UBIGINT: 'UBIGINT'>: 'BIGINT', <Type.UINT: 'UINT'>: 'INT', <Type.UMEDIUMINT: 'UMEDIUMINT'>: 'MEDIUMINT', <Type.USMALLINT: 'USMALLINT'>: 'SMALLINT', <Type.UTINYINT: 'UTINYINT'>: 'TINYINT', <Type.UDECIMAL: 'UDECIMAL'>: 'DECIMAL'}"}, "sqlglot.dialects.mysql.MySQL.Generator.TIMESTAMP_TYPE_MAPPING": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.TIMESTAMP_TYPE_MAPPING", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.TIMESTAMP_TYPE_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.TIMESTAMP: 'TIMESTAMP'>: 'DATETIME', <Type.TIMESTAMPTZ: 'TIMESTAMPTZ'>: 'TIMESTAMP', <Type.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>: 'TIMESTAMP'}"}, "sqlglot.dialects.mysql.MySQL.Generator.TYPE_MAPPING": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.TYPE_MAPPING", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.TYPE_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.NCHAR: 'NCHAR'>: 'CHAR', <Type.NVARCHAR: 'NVARCHAR'>: 'VARCHAR', <Type.INET: 'INET'>: 'INET', <Type.ROWVERSION: 'ROWVERSION'>: 'VARBINARY', <Type.UBIGINT: 'UBIGINT'>: 'BIGINT', <Type.UINT: 'UINT'>: 'INT', <Type.UMEDIUMINT: 'UMEDIUMINT'>: 'MEDIUMINT', <Type.USMALLINT: 'USMALLINT'>: 'SMALLINT', <Type.UTINYINT: 'UTINYINT'>: 'TINYINT', <Type.UDECIMAL: 'UDECIMAL'>: 'DECIMAL', <Type.TIMESTAMP: 'TIMESTAMP'>: 'DATETIME', <Type.TIMESTAMPTZ: 'TIMESTAMPTZ'>: 'TIMESTAMP', <Type.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>: 'TIMESTAMP'}"}, "sqlglot.dialects.mysql.MySQL.Generator.PROPERTIES_LOCATION": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.PROPERTIES_LOCATION", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.PROPERTIES_LOCATION", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.AllowedValuesProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.AlgorithmProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.AutoIncrementProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.BackupProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.BlockCompressionProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.CharacterSetProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ChecksumProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.CollateProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Cluster'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ClusteredByProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DataBlocksizeProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.DataDeletionProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DefinerProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.DictRange'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DictProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DistKeyProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DistStyleProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.EngineProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ExternalProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.FallbackProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.FileFormatProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.FreespaceProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.GlobalProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.HeapProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.InheritsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.IcebergProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.InputModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.IsolatedLoadingProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.JournalProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.LanguageProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LikeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LocationProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LockProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LockingProperty'>: <Location.POST_ALIAS: 'POST_ALIAS'>, <class 'sqlglot.expressions.LogProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.MaterializedProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.MergeBlockRatioProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.OnProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.OnCommitProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.Order'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.OutputModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.PartitionedByProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.PartitionedOfProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.PrimaryKey'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Property'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ReturnsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatDelimitedProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatSerdeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SampleProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SchemaCommentProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SerdeProperties'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Set'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SettingsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SetProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.SetConfigProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SharingProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.SequenceProperties'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.SortKeyProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SqlReadWriteProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SqlSecurityProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.StabilityProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.StrictProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.TemporaryProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.ToTableProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.TransientProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.TransformModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.MergeTreeTTL'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.UnloggedProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.VolatileProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.WithDataProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.WithSystemVersioningProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>}"}, "sqlglot.dialects.mysql.MySQL.Generator.LIMIT_FETCH": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.LIMIT_FETCH", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.LIMIT_FETCH", "kind": "variable", "doc": "<p></p>\n", "default_value": "'LIMIT'"}, "sqlglot.dialects.mysql.MySQL.Generator.LIMIT_ONLY_LITERALS": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.LIMIT_ONLY_LITERALS", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.LIMIT_ONLY_LITERALS", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.mysql.MySQL.Generator.CHAR_CAST_MAPPING": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.CHAR_CAST_MAPPING", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.CHAR_CAST_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.LONGTEXT: 'LONGTEXT'>: 'CHAR', <Type.LONGBLOB: 'LONGBLOB'>: 'CHAR', <Type.MEDIUMBLOB: 'MEDIUMBLOB'>: 'CHAR', <Type.MEDIUMTEXT: 'MEDIUMTEXT'>: 'CHAR', <Type.TEXT: 'TEXT'>: 'CHAR', <Type.TINYBLOB: 'TINYBLOB'>: 'CHAR', <Type.TINYTEXT: 'TINYTEXT'>: 'CHAR', <Type.VARCHAR: 'VARCHAR'>: 'CHAR'}"}, "sqlglot.dialects.mysql.MySQL.Generator.SIGNED_CAST_MAPPING": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.SIGNED_CAST_MAPPING", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.SIGNED_CAST_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.BIGINT: 'BIGINT'>: 'SIGNED', <Type.BOOLEAN: 'BOOLEAN'>: 'SIGNED', <Type.INT: 'INT'>: 'SIGNED', <Type.SMALLINT: 'SMALLINT'>: 'SIGNED', <Type.TINYINT: 'TINYINT'>: 'SIGNED', <Type.MEDIUMINT: 'MEDIUMINT'>: 'SIGNED'}"}, "sqlglot.dialects.mysql.MySQL.Generator.CAST_MAPPING": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.CAST_MAPPING", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.CAST_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.LONGTEXT: 'LONGTEXT'>: 'CHAR', <Type.LONGBLOB: 'LONGBLOB'>: 'CHAR', <Type.MEDIUMBLOB: 'MEDIUMBLOB'>: 'CHAR', <Type.MEDIUMTEXT: 'MEDIUMTEXT'>: 'CHAR', <Type.TEXT: 'TEXT'>: 'CHAR', <Type.TINYBLOB: 'TINYBLOB'>: 'CHAR', <Type.TINYTEXT: 'TINYTEXT'>: 'CHAR', <Type.VARCHAR: 'VARCHAR'>: 'CHAR', <Type.BIGINT: 'BIGINT'>: 'SIGNED', <Type.BOOLEAN: 'BOOLEAN'>: 'SIGNED', <Type.INT: 'INT'>: 'SIGNED', <Type.SMALLINT: 'SMALLINT'>: 'SIGNED', <Type.TINYINT: 'TINYINT'>: 'SIGNED', <Type.MEDIUMINT: 'MEDIUMINT'>: 'SIGNED', <Type.UBIGINT: 'UBIGINT'>: 'UNSIGNED'}"}, "sqlglot.dialects.mysql.MySQL.Generator.TIMESTAMP_FUNC_TYPES": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.TIMESTAMP_FUNC_TYPES", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.TIMESTAMP_FUNC_TYPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <Type.TIMESTAMPTZ: 'TIMESTAMPTZ'>}"}, "sqlglot.dialects.mysql.MySQL.Generator.dpipe_sql": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.dpipe_sql", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.dpipe_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DPipe</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.mysql.MySQL.Generator.extract_sql": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.extract_sql", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.extract_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Extract</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.mysql.MySQL.Generator.datatype_sql": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.datatype_sql", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.datatype_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.mysql.MySQL.Generator.jsonarraycontains_sql": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.jsonarraycontains_sql", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.jsonarraycontains_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">JSONArrayContains</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.mysql.MySQL.Generator.cast_sql": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.cast_sql", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.cast_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Cast</span>,</span><span class=\"param\">\t<span class=\"n\">safe_prefix</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.mysql.MySQL.Generator.show_sql": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.show_sql", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.show_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Show</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.mysql.MySQL.Generator.altercolumn_sql": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.altercolumn_sql", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.altercolumn_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">AlterColumn</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.mysql.MySQL.Generator.chr_sql": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.chr_sql", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.chr_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Chr</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.mysql.MySQL.Generator.timestamptrunc_sql": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.timestamptrunc_sql", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.timestamptrunc_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TimestampTrunc</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.mysql.MySQL.Generator.SELECT_KINDS": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.SELECT_KINDS", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.SELECT_KINDS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Tuple[str, ...]", "default_value": "()"}, "sqlglot.dialects.mysql.MySQL.Generator.TRY_SUPPORTED": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.TRY_SUPPORTED", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.TRY_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.mysql.MySQL.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS": {"fullname": "sqlglot.dialects.mysql.MySQL.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'qualify': <function Generator.<lambda>>, 'windows': <function Generator.<lambda>>}"}, "sqlglot.dialects.mysql.MySQL.UNESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.mysql.MySQL.UNESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.UNESCAPED_SEQUENCES", "kind": "variable", "doc": "<p>Mapping of an escaped sequence (<code>\\n</code>) to its unescaped version (<code>\n</code>).</p>\n", "annotation": ": Dict[str, str]", "default_value": "{'\\\\a': '\\x07', '\\\\b': '\\x08', '\\\\f': '\\x0c', '\\\\n': '\\n', '\\\\r': '\\r', '\\\\t': '\\t', '\\\\v': '\\x0b', '\\\\\\\\': '\\\\'}"}, "sqlglot.dialects.mysql.MySQL.tokenizer_class": {"fullname": "sqlglot.dialects.mysql.MySQL.tokenizer_class", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.tokenizer_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.mysql.MySQL.Tokenizer'>"}, "sqlglot.dialects.mysql.MySQL.parser_class": {"fullname": "sqlglot.dialects.mysql.MySQL.parser_class", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.parser_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.mysql.MySQL.Parser'>"}, "sqlglot.dialects.mysql.MySQL.generator_class": {"fullname": "sqlglot.dialects.mysql.MySQL.generator_class", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.generator_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.mysql.MySQL.Generator'>"}, "sqlglot.dialects.mysql.MySQL.TIME_TRIE": {"fullname": "sqlglot.dialects.mysql.MySQL.TIME_TRIE", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'%': {'M': {0: True}, 'c': {0: True}, 'e': {0: True}, 'h': {0: True}, 'i': {0: True}, 's': {0: True}, 'u': {0: True}, 'k': {0: True}, 'l': {0: True}, 'T': {0: True}, 'W': {0: True}}}"}, "sqlglot.dialects.mysql.MySQL.FORMAT_TRIE": {"fullname": "sqlglot.dialects.mysql.MySQL.FORMAT_TRIE", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.FORMAT_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'%': {'M': {0: True}, 'c': {0: True}, 'e': {0: True}, 'h': {0: True}, 'i': {0: True}, 's': {0: True}, 'u': {0: True}, 'k': {0: True}, 'l': {0: True}, 'T': {0: True}, 'W': {0: True}}}"}, "sqlglot.dialects.mysql.MySQL.INVERSE_TIME_MAPPING": {"fullname": "sqlglot.dialects.mysql.MySQL.INVERSE_TIME_MAPPING", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.INVERSE_TIME_MAPPING", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'%B': '%M', '%-m': '%c', '%-d': '%e', '%I': '%h', '%M': '%i', '%S': '%s', '%W': '%u', '%-H': '%k', '%-I': '%l', '%H:%M:%S': '%T', '%a': '%W'}"}, "sqlglot.dialects.mysql.MySQL.INVERSE_TIME_TRIE": {"fullname": "sqlglot.dialects.mysql.MySQL.INVERSE_TIME_TRIE", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.INVERSE_TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'%': {'B': {0: True}, '-': {'m': {0: True}, 'd': {0: True}, 'H': {0: True}, 'I': {0: True}}, 'I': {0: True}, 'M': {0: True}, 'S': {0: True}, 'W': {0: True}, 'H': {':': {'%': {'M': {':': {'%': {'S': {0: True}}}}}}}, 'a': {0: True}}}"}, "sqlglot.dialects.mysql.MySQL.ESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.mysql.MySQL.ESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.ESCAPED_SEQUENCES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'\\x07': '\\\\a', '\\x08': '\\\\b', '\\x0c': '\\\\f', '\\n': '\\\\n', '\\r': '\\\\r', '\\t': '\\\\t', '\\x0b': '\\\\v', '\\\\': '\\\\\\\\'}"}, "sqlglot.dialects.mysql.MySQL.QUOTE_START": {"fullname": "sqlglot.dialects.mysql.MySQL.QUOTE_START", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.QUOTE_START", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.mysql.MySQL.QUOTE_END": {"fullname": "sqlglot.dialects.mysql.MySQL.QUOTE_END", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.QUOTE_END", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.mysql.MySQL.IDENTIFIER_START": {"fullname": "sqlglot.dialects.mysql.MySQL.IDENTIFIER_START", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.IDENTIFIER_START", "kind": "variable", "doc": "<p></p>\n", "default_value": "'`'"}, "sqlglot.dialects.mysql.MySQL.IDENTIFIER_END": {"fullname": "sqlglot.dialects.mysql.MySQL.IDENTIFIER_END", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.IDENTIFIER_END", "kind": "variable", "doc": "<p></p>\n", "default_value": "'`'"}, "sqlglot.dialects.mysql.MySQL.BIT_START": {"fullname": "sqlglot.dialects.mysql.MySQL.BIT_START", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.BIT_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""b'""}, "sqlglot.dialects.mysql.MySQL.BIT_END": {"fullname": "sqlglot.dialects.mysql.MySQL.BIT_END", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.BIT_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""'""}, "sqlglot.dialects.mysql.MySQL.HEX_START": {"fullname": "sqlglot.dialects.mysql.MySQL.HEX_START", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.HEX_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""x'""}, "sqlglot.dialects.mysql.MySQL.HEX_END": {"fullname": "sqlglot.dialects.mysql.MySQL.HEX_END", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.HEX_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""'""}, "sqlglot.dialects.mysql.MySQL.BYTE_START": {"fullname": "sqlglot.dialects.mysql.MySQL.BYTE_START", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.BYTE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.mysql.MySQL.BYTE_END": {"fullname": "sqlglot.dialects.mysql.MySQL.BYTE_END", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.BYTE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.mysql.MySQL.UNICODE_START": {"fullname": "sqlglot.dialects.mysql.MySQL.UNICODE_START", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.UNICODE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.mysql.MySQL.UNICODE_END": {"fullname": "sqlglot.dialects.mysql.MySQL.UNICODE_END", "modulename": "sqlglot.dialects.mysql", "qualname": "MySQL.UNICODE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.oracle": {"fullname": "sqlglot.dialects.oracle", "modulename": "sqlglot.dialects.oracle", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.dialects.oracle.Oracle": {"fullname": "sqlglot.dialects.oracle.Oracle", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.dialect.Dialect"}, "sqlglot.dialects.oracle.Oracle.ALIAS_POST_TABLESAMPLE": {"fullname": "sqlglot.dialects.oracle.Oracle.ALIAS_POST_TABLESAMPLE", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.ALIAS_POST_TABLESAMPLE", "kind": "variable", "doc": "<p>Whether the table alias comes after tablesample.</p>\n", "default_value": "True"}, "sqlglot.dialects.oracle.Oracle.LOCKING_READS_SUPPORTED": {"fullname": "sqlglot.dialects.oracle.Oracle.LOCKING_READS_SUPPORTED", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.LOCKING_READS_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.oracle.Oracle.TABLESAMPLE_SIZE_IS_PERCENT": {"fullname": "sqlglot.dialects.oracle.Oracle.TABLESAMPLE_SIZE_IS_PERCENT", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.TABLESAMPLE_SIZE_IS_PERCENT", "kind": "variable", "doc": "<p>Whether a size in the table sample clause represents percentage.</p>\n", "default_value": "True"}, "sqlglot.dialects.oracle.Oracle.NORMALIZATION_STRATEGY": {"fullname": "sqlglot.dialects.oracle.Oracle.NORMALIZATION_STRATEGY", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.NORMALIZATION_STRATEGY", "kind": "variable", "doc": "<p>Specifies the strategy according to which identifiers should be normalized.</p>\n", "default_value": "<NormalizationStrategy.UPPERCASE: 'UPPERCASE'>"}, "sqlglot.dialects.oracle.Oracle.TIME_MAPPING": {"fullname": "sqlglot.dialects.oracle.Oracle.TIME_MAPPING", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.TIME_MAPPING", "kind": "variable", "doc": "<p>Associates this dialect's time formats with their equivalent Python <code>strftime</code> formats.</p>\n", "annotation": ": Dict[str, str]", "default_value": "{'AM': '%p', 'A.M.': '%p', 'PM': '%p', 'P.M.': '%p', 'D': '%u', 'DAY': '%A', 'DD': '%d', 'DDD': '%j', 'DY': '%a', 'HH': '%I', 'HH12': '%I', 'HH24': '%H', 'IW': '%V', 'MI': '%M', 'MM': '%m', 'MON': '%b', 'MONTH': '%B', 'SS': '%S', 'WW': '%W', 'YY': '%y', 'YYYY': '%Y', 'FF6': '%f'}"}, "sqlglot.dialects.oracle.Oracle.Tokenizer": {"fullname": "sqlglot.dialects.oracle.Oracle.Tokenizer", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Tokenizer", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.tokens.Tokenizer"}, "sqlglot.dialects.oracle.Oracle.Tokenizer.VAR_SINGLE_TOKENS": {"fullname": "sqlglot.dialects.oracle.Oracle.Tokenizer.VAR_SINGLE_TOKENS", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Tokenizer.VAR_SINGLE_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'$', '@', '#'}"}, "sqlglot.dialects.oracle.Oracle.Tokenizer.KEYWORDS": {"fullname": "sqlglot.dialects.oracle.Oracle.Tokenizer.KEYWORDS", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Tokenizer.KEYWORDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'{%': <TokenType.BLOCK_START: 'BLOCK_START'>, '{%+': <TokenType.BLOCK_START: 'BLOCK_START'>, '{%-': <TokenType.BLOCK_START: 'BLOCK_START'>, '%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '+%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '-%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '{{+': <TokenType.BLOCK_START: 'BLOCK_START'>, '{{-': <TokenType.BLOCK_START: 'BLOCK_START'>, '+}}': <TokenType.BLOCK_END: 'BLOCK_END'>, '-}}': <TokenType.BLOCK_END: 'BLOCK_END'>, '/*+': <TokenType.HINT: 'HINT'>, '==': <TokenType.EQ: 'EQ'>, '::': <TokenType.DCOLON: 'DCOLON'>, '||': <TokenType.DPIPE: 'DPIPE'>, '>=': <TokenType.GTE: 'GTE'>, '<=': <TokenType.LTE: 'LTE'>, '<>': <TokenType.NEQ: 'NEQ'>, '!=': <TokenType.NEQ: 'NEQ'>, ':=': <TokenType.COLON_EQ: 'COLON_EQ'>, '<=>': <TokenType.NULLSAFE_EQ: 'NULLSAFE_EQ'>, '->': <TokenType.ARROW: 'ARROW'>, '->>': <TokenType.DARROW: 'DARROW'>, '=>': <TokenType.FARROW: 'FARROW'>, '#>': <TokenType.HASH_ARROW: 'HASH_ARROW'>, '#>>': <TokenType.DHASH_ARROW: 'DHASH_ARROW'>, '<->': <TokenType.LR_ARROW: 'LR_ARROW'>, '&&': <TokenType.DAMP: 'DAMP'>, '??': <TokenType.DQMARK: 'DQMARK'>, 'ALL': <TokenType.ALL: 'ALL'>, 'ALWAYS': <TokenType.ALWAYS: 'ALWAYS'>, 'AND': <TokenType.AND: 'AND'>, 'ANTI': <TokenType.ANTI: 'ANTI'>, 'ANY': <TokenType.ANY: 'ANY'>, 'ASC': <TokenType.ASC: 'ASC'>, 'AS': <TokenType.ALIAS: 'ALIAS'>, 'ASOF': <TokenType.ASOF: 'ASOF'>, 'AUTOINCREMENT': <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, 'AUTO_INCREMENT': <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, 'BEGIN': <TokenType.BEGIN: 'BEGIN'>, 'BETWEEN': <TokenType.BETWEEN: 'BETWEEN'>, 'CACHE': <TokenType.CACHE: 'CACHE'>, 'UNCACHE': <TokenType.UNCACHE: 'UNCACHE'>, 'CASE': <TokenType.CASE: 'CASE'>, 'CHARACTER SET': <TokenType.CHARACTER_SET: 'CHARACTER_SET'>, 'CLUSTER BY': <TokenType.CLUSTER_BY: 'CLUSTER_BY'>, 'COLLATE': <TokenType.COLLATE: 'COLLATE'>, 'COLUMN': <TokenType.COLUMN: 'COLUMN'>, 'COMMIT': <TokenType.COMMIT: 'COMMIT'>, 'CONNECT BY': <TokenType.CONNECT_BY: 'CONNECT_BY'>, 'CONSTRAINT': <TokenType.CONSTRAINT: 'CONSTRAINT'>, 'COPY': <TokenType.COPY: 'COPY'>, 'CREATE': <TokenType.CREATE: 'CREATE'>, 'CROSS': <TokenType.CROSS: 'CROSS'>, 'CUBE': <TokenType.CUBE: 'CUBE'>, 'CURRENT_DATE': <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, 'CURRENT_TIME': <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, 'CURRENT_TIMESTAMP': <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, 'CURRENT_USER': <TokenType.CURRENT_USER: 'CURRENT_USER'>, 'DATABASE': <TokenType.DATABASE: 'DATABASE'>, 'DEFAULT': <TokenType.DEFAULT: 'DEFAULT'>, 'DELETE': <TokenType.DELETE: 'DELETE'>, 'DESC': <TokenType.DESC: 'DESC'>, 'DESCRIBE': <TokenType.DESCRIBE: 'DESCRIBE'>, 'DISTINCT': <TokenType.DISTINCT: 'DISTINCT'>, 'DISTRIBUTE BY': <TokenType.DISTRIBUTE_BY: 'DISTRIBUTE_BY'>, 'DIV': <TokenType.DIV: 'DIV'>, 'DROP': <TokenType.DROP: 'DROP'>, 'ELSE': <TokenType.ELSE: 'ELSE'>, 'END': <TokenType.END: 'END'>, 'ENUM': <TokenType.ENUM: 'ENUM'>, 'ESCAPE': <TokenType.ESCAPE: 'ESCAPE'>, 'EXCEPT': <TokenType.EXCEPT: 'EXCEPT'>, 'EXECUTE': <TokenType.EXECUTE: 'EXECUTE'>, 'EXISTS': <TokenType.EXISTS: 'EXISTS'>, 'FALSE': <TokenType.FALSE: 'FALSE'>, 'FETCH': <TokenType.FETCH: 'FETCH'>, 'FILTER': <TokenType.FILTER: 'FILTER'>, 'FIRST': <TokenType.FIRST: 'FIRST'>, 'FULL': <TokenType.FULL: 'FULL'>, 'FUNCTION': <TokenType.FUNCTION: 'FUNCTION'>, 'FOR': <TokenType.FOR: 'FOR'>, 'FOREIGN KEY': <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, 'FORMAT': <TokenType.FORMAT: 'FORMAT'>, 'FROM': <TokenType.FROM: 'FROM'>, 'GEOGRAPHY': <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, 'GEOMETRY': <TokenType.GEOMETRY: 'GEOMETRY'>, 'GLOB': <TokenType.GLOB: 'GLOB'>, 'GROUP BY': <TokenType.GROUP_BY: 'GROUP_BY'>, 'GROUPING SETS': <TokenType.GROUPING_SETS: 'GROUPING_SETS'>, 'HAVING': <TokenType.HAVING: 'HAVING'>, 'ILIKE': <TokenType.ILIKE: 'ILIKE'>, 'IN': <TokenType.IN: 'IN'>, 'INDEX': <TokenType.INDEX: 'INDEX'>, 'INET': <TokenType.INET: 'INET'>, 'INNER': <TokenType.INNER: 'INNER'>, 'INSERT': <TokenType.INSERT: 'INSERT'>, 'INTERVAL': <TokenType.INTERVAL: 'INTERVAL'>, 'INTERSECT': <TokenType.INTERSECT: 'INTERSECT'>, 'INTO': <TokenType.INTO: 'INTO'>, 'IS': <TokenType.IS: 'IS'>, 'ISNULL': <TokenType.ISNULL: 'ISNULL'>, 'JOIN': <TokenType.JOIN: 'JOIN'>, 'KEEP': <TokenType.KEEP: 'KEEP'>, 'KILL': <TokenType.KILL: 'KILL'>, 'LATERAL': <TokenType.LATERAL: 'LATERAL'>, 'LEFT': <TokenType.LEFT: 'LEFT'>, 'LIKE': <TokenType.LIKE: 'LIKE'>, 'LIMIT': <TokenType.LIMIT: 'LIMIT'>, 'LOAD': <TokenType.LOAD: 'LOAD'>, 'LOCK': <TokenType.LOCK: 'LOCK'>, 'MERGE': <TokenType.MERGE: 'MERGE'>, 'NATURAL': <TokenType.NATURAL: 'NATURAL'>, 'NEXT': <TokenType.NEXT: 'NEXT'>, 'NOT': <TokenType.NOT: 'NOT'>, 'NOTNULL': <TokenType.NOTNULL: 'NOTNULL'>, 'NULL': <TokenType.NULL: 'NULL'>, 'OBJECT': <TokenType.OBJECT: 'OBJECT'>, 'OFFSET': <TokenType.OFFSET: 'OFFSET'>, 'ON': <TokenType.ON: 'ON'>, 'OR': <TokenType.OR: 'OR'>, 'XOR': <TokenType.XOR: 'XOR'>, 'ORDER BY': <TokenType.ORDER_BY: 'ORDER_BY'>, 'ORDINALITY': <TokenType.ORDINALITY: 'ORDINALITY'>, 'OUTER': <TokenType.OUTER: 'OUTER'>, 'OVER': <TokenType.OVER: 'OVER'>, 'OVERLAPS': <TokenType.OVERLAPS: 'OVERLAPS'>, 'OVERWRITE': <TokenType.OVERWRITE: 'OVERWRITE'>, 'PARTITION': <TokenType.PARTITION: 'PARTITION'>, 'PARTITION BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PARTITIONED BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PARTITIONED_BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PERCENT': <TokenType.PERCENT: 'PERCENT'>, 'PIVOT': <TokenType.PIVOT: 'PIVOT'>, 'PRAGMA': <TokenType.PRAGMA: 'PRAGMA'>, 'PRIMARY KEY': <TokenType.PRIMARY_KEY: 'PRIMARY_KEY'>, 'PROCEDURE': <TokenType.PROCEDURE: 'PROCEDURE'>, 'QUALIFY': <TokenType.QUALIFY: 'QUALIFY'>, 'RANGE': <TokenType.RANGE: 'RANGE'>, 'RECURSIVE': <TokenType.RECURSIVE: 'RECURSIVE'>, 'REGEXP': <TokenType.RLIKE: 'RLIKE'>, 'REPLACE': <TokenType.REPLACE: 'REPLACE'>, 'RETURNING': <TokenType.RETURNING: 'RETURNING'>, 'REFERENCES': <TokenType.REFERENCES: 'REFERENCES'>, 'RIGHT': <TokenType.RIGHT: 'RIGHT'>, 'RLIKE': <TokenType.RLIKE: 'RLIKE'>, 'ROLLBACK': <TokenType.ROLLBACK: 'ROLLBACK'>, 'ROLLUP': <TokenType.ROLLUP: 'ROLLUP'>, 'ROW': <TokenType.ROW: 'ROW'>, 'ROWS': <TokenType.ROWS: 'ROWS'>, 'SCHEMA': <TokenType.SCHEMA: 'SCHEMA'>, 'SELECT': <TokenType.SELECT: 'SELECT'>, 'SEMI': <TokenType.SEMI: 'SEMI'>, 'SET': <TokenType.SET: 'SET'>, 'SETTINGS': <TokenType.SETTINGS: 'SETTINGS'>, 'SHOW': <TokenType.SHOW: 'SHOW'>, 'SIMILAR TO': <TokenType.SIMILAR_TO: 'SIMILAR_TO'>, 'SOME': <TokenType.SOME: 'SOME'>, 'SORT BY': <TokenType.SORT_BY: 'SORT_BY'>, 'START WITH': <TokenType.START_WITH: 'START_WITH'>, 'TABLE': <TokenType.TABLE: 'TABLE'>, 'TABLESAMPLE': <TokenType.TABLE_SAMPLE: 'TABLE_SAMPLE'>, 'TEMP': <TokenType.TEMPORARY: 'TEMPORARY'>, 'TEMPORARY': <TokenType.TEMPORARY: 'TEMPORARY'>, 'THEN': <TokenType.THEN: 'THEN'>, 'TRUE': <TokenType.TRUE: 'TRUE'>, 'TRUNCATE': <TokenType.TRUNCATE: 'TRUNCATE'>, 'UNION': <TokenType.UNION: 'UNION'>, 'UNKNOWN': <TokenType.UNKNOWN: 'UNKNOWN'>, 'UNNEST': <TokenType.UNNEST: 'UNNEST'>, 'UNPIVOT': <TokenType.UNPIVOT: 'UNPIVOT'>, 'UPDATE': <TokenType.UPDATE: 'UPDATE'>, 'USE': <TokenType.USE: 'USE'>, 'USING': <TokenType.USING: 'USING'>, 'UUID': <TokenType.UUID: 'UUID'>, 'VALUES': <TokenType.VALUES: 'VALUES'>, 'VIEW': <TokenType.VIEW: 'VIEW'>, 'VOLATILE': <TokenType.VOLATILE: 'VOLATILE'>, 'WHEN': <TokenType.WHEN: 'WHEN'>, 'WHERE': <TokenType.WHERE: 'WHERE'>, 'WINDOW': <TokenType.WINDOW: 'WINDOW'>, 'WITH': <TokenType.WITH: 'WITH'>, 'APPLY': <TokenType.APPLY: 'APPLY'>, 'ARRAY': <TokenType.ARRAY: 'ARRAY'>, 'BIT': <TokenType.BIT: 'BIT'>, 'BOOL': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BOOLEAN': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BYTE': <TokenType.TINYINT: 'TINYINT'>, 'MEDIUMINT': <TokenType.MEDIUMINT: 'MEDIUMINT'>, 'INT1': <TokenType.TINYINT: 'TINYINT'>, 'TINYINT': <TokenType.TINYINT: 'TINYINT'>, 'INT16': <TokenType.SMALLINT: 'SMALLINT'>, 'SHORT': <TokenType.SMALLINT: 'SMALLINT'>, 'SMALLINT': <TokenType.SMALLINT: 'SMALLINT'>, 'INT128': <TokenType.INT128: 'INT128'>, 'HUGEINT': <TokenType.INT128: 'INT128'>, 'INT2': <TokenType.SMALLINT: 'SMALLINT'>, 'INTEGER': <TokenType.INT: 'INT'>, 'INT': <TokenType.INT: 'INT'>, 'INT4': <TokenType.INT: 'INT'>, 'INT32': <TokenType.INT: 'INT'>, 'INT64': <TokenType.BIGINT: 'BIGINT'>, 'LONG': <TokenType.BIGINT: 'BIGINT'>, 'BIGINT': <TokenType.BIGINT: 'BIGINT'>, 'INT8': <TokenType.TINYINT: 'TINYINT'>, 'UINT': <TokenType.UINT: 'UINT'>, 'DEC': <TokenType.DECIMAL: 'DECIMAL'>, 'DECIMAL': <TokenType.DECIMAL: 'DECIMAL'>, 'BIGDECIMAL': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'BIGNUMERIC': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'MAP': <TokenType.MAP: 'MAP'>, 'NULLABLE': <TokenType.NULLABLE: 'NULLABLE'>, 'NUMBER': <TokenType.DECIMAL: 'DECIMAL'>, 'NUMERIC': <TokenType.DECIMAL: 'DECIMAL'>, 'FIXED': <TokenType.DECIMAL: 'DECIMAL'>, 'REAL': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT4': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT8': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE PRECISION': <TokenType.DOUBLE: 'DOUBLE'>, 'JSON': <TokenType.JSON: 'JSON'>, 'CHAR': <TokenType.CHAR: 'CHAR'>, 'CHARACTER': <TokenType.CHAR: 'CHAR'>, 'NCHAR': <TokenType.NCHAR: 'NCHAR'>, 'VARCHAR': <TokenType.VARCHAR: 'VARCHAR'>, 'VARCHAR2': <TokenType.VARCHAR: 'VARCHAR'>, 'NVARCHAR': <TokenType.NVARCHAR: 'NVARCHAR'>, 'NVARCHAR2': <TokenType.NVARCHAR: 'NVARCHAR'>, 'BPCHAR': <TokenType.BPCHAR: 'BPCHAR'>, 'STR': <TokenType.TEXT: 'TEXT'>, 'STRING': <TokenType.TEXT: 'TEXT'>, 'TEXT': <TokenType.TEXT: 'TEXT'>, 'LONGTEXT': <TokenType.LONGTEXT: 'LONGTEXT'>, 'MEDIUMTEXT': <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, 'TINYTEXT': <TokenType.TINYTEXT: 'TINYTEXT'>, 'CLOB': <TokenType.TEXT: 'TEXT'>, 'LONGVARCHAR': <TokenType.TEXT: 'TEXT'>, 'BINARY': <TokenType.BINARY: 'BINARY'>, 'BLOB': <TokenType.VARBINARY: 'VARBINARY'>, 'LONGBLOB': <TokenType.LONGBLOB: 'LONGBLOB'>, 'MEDIUMBLOB': <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, 'TINYBLOB': <TokenType.TINYBLOB: 'TINYBLOB'>, 'BYTEA': <TokenType.VARBINARY: 'VARBINARY'>, 'VARBINARY': <TokenType.VARBINARY: 'VARBINARY'>, 'TIME': <TokenType.TIME: 'TIME'>, 'TIMETZ': <TokenType.TIMETZ: 'TIMETZ'>, 'TIMESTAMP': <TokenType.TIMESTAMP: 'TIMESTAMP'>, 'TIMESTAMPTZ': <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, 'TIMESTAMPLTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMP_LTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMPNTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'TIMESTAMP_NTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'DATE': <TokenType.DATE: 'DATE'>, 'DATETIME': <TokenType.DATETIME: 'DATETIME'>, 'INT4RANGE': <TokenType.INT4RANGE: 'INT4RANGE'>, 'INT4MULTIRANGE': <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, 'INT8RANGE': <TokenType.INT8RANGE: 'INT8RANGE'>, 'INT8MULTIRANGE': <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, 'NUMRANGE': <TokenType.NUMRANGE: 'NUMRANGE'>, 'NUMMULTIRANGE': <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, 'TSRANGE': <TokenType.TSRANGE: 'TSRANGE'>, 'TSMULTIRANGE': <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, 'TSTZRANGE': <TokenType.TSTZRANGE: 'TSTZRANGE'>, 'TSTZMULTIRANGE': <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, 'DATERANGE': <TokenType.DATERANGE: 'DATERANGE'>, 'DATEMULTIRANGE': <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, 'UNIQUE': <TokenType.UNIQUE: 'UNIQUE'>, 'STRUCT': <TokenType.STRUCT: 'STRUCT'>, 'SEQUENCE': <TokenType.SEQUENCE: 'SEQUENCE'>, 'VARIANT': <TokenType.VARIANT: 'VARIANT'>, 'ALTER': <TokenType.ALTER: 'ALTER'>, 'ANALYZE': <TokenType.COMMAND: 'COMMAND'>, 'CALL': <TokenType.COMMAND: 'COMMAND'>, 'COMMENT': <TokenType.COMMENT: 'COMMENT'>, 'EXPLAIN': <TokenType.COMMAND: 'COMMAND'>, 'GRANT': <TokenType.COMMAND: 'COMMAND'>, 'OPTIMIZE': <TokenType.COMMAND: 'COMMAND'>, 'PREPARE': <TokenType.COMMAND: 'COMMAND'>, 'VACUUM': <TokenType.COMMAND: 'COMMAND'>, 'USER-DEFINED': <TokenType.USERDEFINED: 'USERDEFINED'>, 'FOR VERSION': <TokenType.VERSION_SNAPSHOT: 'VERSION_SNAPSHOT'>, 'FOR TIMESTAMP': <TokenType.TIMESTAMP_SNAPSHOT: 'TIMESTAMP_SNAPSHOT'>, '(+)': <TokenType.JOIN_MARKER: 'JOIN_MARKER'>, 'BINARY_DOUBLE': <TokenType.DOUBLE: 'DOUBLE'>, 'BINARY_FLOAT': <TokenType.FLOAT: 'FLOAT'>, 'COLUMNS': <TokenType.COLUMN: 'COLUMN'>, 'MATCH_RECOGNIZE': <TokenType.MATCH_RECOGNIZE: 'MATCH_RECOGNIZE'>, 'MINUS': <TokenType.EXCEPT: 'EXCEPT'>, 'ORDER SIBLINGS BY': <TokenType.ORDER_SIBLINGS_BY: 'ORDER_SIBLINGS_BY'>, 'SAMPLE': <TokenType.TABLE_SAMPLE: 'TABLE_SAMPLE'>, 'START': <TokenType.BEGIN: 'BEGIN'>, 'SYSDATE': <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, 'TOP': <TokenType.TOP: 'TOP'>}"}, "sqlglot.dialects.oracle.Oracle.Parser": {"fullname": "sqlglot.dialects.oracle.Oracle.Parser", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Parser", "kind": "class", "doc": "<p>Parser consumes a list of tokens produced by the Tokenizer and produces a parsed syntax tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>error_level:</strong> The desired error level.\nDefault: ErrorLevel.IMMEDIATE</li>\n<li><strong>error_message_context:</strong> The amount of context to capture from a query string when displaying\nthe error message (in number of characters).\nDefault: 100</li>\n<li><strong>max_errors:</strong> Maximum number of error messages to include in a raised ParseError.\nThis is only relevant if error_level is ErrorLevel.RAISE.\nDefault: 3</li>\n</ul>\n", "bases": "sqlglot.parser.Parser"}, "sqlglot.dialects.oracle.Oracle.Parser.ALTER_TABLE_ADD_REQUIRED_FOR_EACH_COLUMN": {"fullname": "sqlglot.dialects.oracle.Oracle.Parser.ALTER_TABLE_ADD_REQUIRED_FOR_EACH_COLUMN", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Parser.ALTER_TABLE_ADD_REQUIRED_FOR_EACH_COLUMN", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.oracle.Oracle.Parser.WINDOW_BEFORE_PAREN_TOKENS": {"fullname": "sqlglot.dialects.oracle.Oracle.Parser.WINDOW_BEFORE_PAREN_TOKENS", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Parser.WINDOW_BEFORE_PAREN_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.OVER: 'OVER'>, <TokenType.KEEP: 'KEEP'>}"}, "sqlglot.dialects.oracle.Oracle.Parser.VALUES_FOLLOWED_BY_PAREN": {"fullname": "sqlglot.dialects.oracle.Oracle.Parser.VALUES_FOLLOWED_BY_PAREN", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Parser.VALUES_FOLLOWED_BY_PAREN", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.oracle.Oracle.Parser.FUNCTIONS": {"fullname": "sqlglot.dialects.oracle.Oracle.Parser.FUNCTIONS", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Parser.FUNCTIONS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ABS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Abs'>>, 'ADD_MONTHS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AddMonths'>>, 'ANONYMOUS_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnonymousAggFunc'>>, 'ANY_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnyValue'>>, 'APPROX_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_COUNT_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'APPROX_TOP_K': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxTopK'>>, 'ARG_MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARGMAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'MAX_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARG_MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARGMIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'MIN_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Array'>>, 'ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAgg'>>, 'ARRAY_ALL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAll'>>, 'ARRAY_ANY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAny'>>, 'ARRAY_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CONSTRUCT_COMPACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConstructCompact'>>, 'ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayContains'>>, 'FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_OVERLAPS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayOverlaps'>>, 'ARRAY_SIZE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_SORT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySort'>>, 'ARRAY_SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySum'>>, 'ARRAY_TO_STRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_JOIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_UNION_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUnionAgg'>>, 'ARRAY_UNIQUE_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUniqueAgg'>>, 'AVG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Avg'>>, 'CASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Case'>>, 'CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cast'>>, 'CAST_TO_STR_TYPE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CastToStrType'>>, 'CBRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cbrt'>>, 'CEIL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CEILING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CHR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'COALESCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'IFNULL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'NVL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'COLLATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Collate'>>, 'COMBINED_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedAggFunc'>>, 'COMBINED_PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedParameterizedAgg'>>, 'CONCAT': <function Parser.<lambda>>, 'CONCAT_WS': <function Parser.<lambda>>, 'CONNECT_BY_ROOT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ConnectByRoot'>>, 'CONVERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Convert'>>, 'CORR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Corr'>>, 'COUNT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Count'>>, 'COUNT_IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COUNTIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COVAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarPop'>>, 'COVAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarSamp'>>, 'CURRENT_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDate'>>, 'CURRENT_DATETIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDatetime'>>, 'CURRENT_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTime'>>, 'CURRENT_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTimestamp'>>, 'CURRENT_USER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentUser'>>, 'DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Date'>>, 'DATE_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateAdd'>>, 'DATEDIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateDiff'>>, 'DATE_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateDiff'>>, 'DATE_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATE_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateStrToDate'>>, 'DATE_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateSub'>>, 'DATE_TO_DATE_STR': <function Parser.<lambda>>, 'DATE_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateToDi'>>, 'DATE_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateTrunc'>>, 'DATETIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeAdd'>>, 'DATETIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeDiff'>>, 'DATETIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeSub'>>, 'DATETIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeTrunc'>>, 'DAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Day'>>, 'DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAYOFMONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAY_OF_WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAYOFWEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAY_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DAYOFYEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DECODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Decode'>>, 'DI_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DiToDate'>>, 'ENCODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Encode'>>, 'EXP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Exp'>>, 'EXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Explode'>>, 'EXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ExplodeOuter'>>, 'EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Extract'>>, 'FIRST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.First'>>, 'FIRST_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FirstValue'>>, 'FLATTEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Flatten'>>, 'FLOOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Floor'>>, 'FROM_BASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase'>>, 'FROM_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase64'>>, 'GENERATE_DATE_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GenerateDateArray'>>, 'GENERATE_SERIES': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GenerateSeries'>>, 'GREATEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Greatest'>>, 'GROUP_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GroupConcat'>>, 'HEX': <function build_hex>, 'HLL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Hll'>>, 'IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'IIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'INITCAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Initcap'>>, 'IS_INF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'ISINF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'IS_NAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'ISNAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'J_S_O_N_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArray'>>, 'J_S_O_N_ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArrayAgg'>>, 'JSON_ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArrayContains'>>, 'JSONB_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONBExtract'>>, 'JSONB_EXTRACT_SCALAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONBExtractScalar'>>, 'JSON_EXTRACT': <function build_extract_json_with_path.<locals>._builder>, 'JSON_EXTRACT_SCALAR': <function build_extract_json_with_path.<locals>._builder>, 'JSON_FORMAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONFormat'>>, 'J_S_O_N_OBJECT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONObject'>>, 'J_S_O_N_OBJECT_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONObjectAgg'>>, 'J_S_O_N_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONTable'>>, 'LAG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lag'>>, 'LAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Last'>>, 'LAST_DAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastDay'>>, 'LAST_DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastDay'>>, 'LAST_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastValue'>>, 'LEAD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lead'>>, 'LEAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Least'>>, 'LEFT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Left'>>, 'LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Length'>>, 'LEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Length'>>, 'LEVENSHTEIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Levenshtein'>>, 'LN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ln'>>, 'LOG': <function build_logarithm>, 'LOGICAL_AND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'BOOL_AND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'BOOLAND_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'LOGICAL_OR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'BOOL_OR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'BOOLOR_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'LOWER': <function build_lower>, 'LCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lower'>>, 'LOWER_HEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LowerHex'>>, 'MD5': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MD5'>>, 'MD5_DIGEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MD5Digest'>>, 'MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Map'>>, 'MAP_FROM_ENTRIES': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MapFromEntries'>>, 'MATCH_AGAINST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MatchAgainst'>>, 'MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Max'>>, 'MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Min'>>, 'MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Month'>>, 'MONTHS_BETWEEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MonthsBetween'>>, 'NEXT_VALUE_FOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NextValueFor'>>, 'NTH_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NthValue'>>, 'NULLIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Nullif'>>, 'NUMBER_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NumberToStr'>>, 'NVL2': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Nvl2'>>, 'OPEN_J_S_O_N': <bound method Func.from_arg_list of <class 'sqlglot.expressions.OpenJSON'>>, 'PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParameterizedAgg'>>, 'PARSE_JSON': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParseJSON'>>, 'JSON_PARSE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParseJSON'>>, 'PERCENTILE_CONT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PercentileCont'>>, 'PERCENTILE_DISC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PercentileDisc'>>, 'POSEXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Posexplode'>>, 'POSEXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PosexplodeOuter'>>, 'POWER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Pow'>>, 'POW': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Pow'>>, 'PREDICT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Predict'>>, 'QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quantile'>>, 'QUARTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quarter'>>, 'RAND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'RANDOM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'RANDN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Randn'>>, 'RANGE_N': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RangeN'>>, 'READ_CSV': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ReadCSV'>>, 'REDUCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Reduce'>>, 'REGEXP_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpExtract'>>, 'REGEXP_I_LIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpILike'>>, 'REGEXP_LIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpLike'>>, 'REGEXP_REPLACE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpReplace'>>, 'REGEXP_SPLIT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpSplit'>>, 'REPEAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Repeat'>>, 'RIGHT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Right'>>, 'ROUND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Round'>>, 'ROW_NUMBER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RowNumber'>>, 'SHA': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA'>>, 'SHA1': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA'>>, 'SHA2': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA2'>>, 'SAFE_DIVIDE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SafeDivide'>>, 'SIGN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sign'>>, 'SIGNUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sign'>>, 'SORT_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SortArray'>>, 'SPLIT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Split'>>, 'SQRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sqrt'>>, 'STANDARD_HASH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StandardHash'>>, 'STAR_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StarMap'>>, 'STARTS_WITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STARTSWITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STDDEV': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stddev'>>, 'STDDEV_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StddevPop'>>, 'STDDEV_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StddevSamp'>>, 'STR_POSITION': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrPosition'>>, 'STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToDate'>>, 'STR_TO_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToMap'>>, 'STR_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToTime'>>, 'STR_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToUnix'>>, 'STRUCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Struct'>>, 'STRUCT_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StructExtract'>>, 'STUFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stuff'>>, 'INSERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stuff'>>, 'SUBSTRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Substring'>>, 'SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sum'>>, 'TIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeAdd'>>, 'TIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeDiff'>>, 'TIME_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'TIMEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'TIME_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToDate'>>, 'TIME_STR_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToTime'>>, 'TIME_STR_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToUnix'>>, 'TIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeSub'>>, 'TIME_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeToStr'>>, 'TIME_TO_TIME_STR': <function Parser.<lambda>>, 'TIME_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeToUnix'>>, 'TIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeTrunc'>>, 'TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Timestamp'>>, 'TIMESTAMP_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampAdd'>>, 'TIMESTAMPDIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampDiff'>>, 'TIMESTAMP_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampDiff'>>, 'TIMESTAMP_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampFromParts'>>, 'TIMESTAMPFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampFromParts'>>, 'TIMESTAMP_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampSub'>>, 'TIMESTAMP_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampTrunc'>>, 'TO_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToArray'>>, 'TO_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToBase64'>>, 'TO_CHAR': <function _build_timetostr_or_tochar>, 'TO_DAYS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToDays'>>, 'TO_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToMap'>>, 'TO_NUMBER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToNumber'>>, 'TRANSFORM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Transform'>>, 'TRIM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Trim'>>, 'TRY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Try'>>, 'TRY_CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TryCast'>>, 'TS_OR_DI_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDiToDi'>>, 'TS_OR_DS_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsAdd'>>, 'TS_OR_DS_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsDiff'>>, 'TS_OR_DS_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToDate'>>, 'TS_OR_DS_TO_DATE_STR': <function Parser.<lambda>>, 'TS_OR_DS_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTime'>>, 'TS_OR_DS_TO_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTimestamp'>>, 'UNHEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Unhex'>>, 'UNIX_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixDate'>>, 'UNIX_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToStr'>>, 'UNIX_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTime'>>, 'UNIX_TO_TIME_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTimeStr'>>, 'UPPER': <function build_upper>, 'UCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Upper'>>, 'VAR_MAP': <function build_var_map>, 'VARIANCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'VAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Week'>>, 'WEEK_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.WeekOfYear'>>, 'WEEKOFYEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.WeekOfYear'>>, 'WHEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.When'>>, 'X_M_L_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.XMLTable'>>, 'XOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Xor'>>, 'YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Year'>>, 'GLOB': <function Parser.<lambda>>, 'JSON_EXTRACT_PATH_TEXT': <function build_extract_json_with_path.<locals>._builder>, 'LIKE': <function build_like>, 'LOG2': <function Parser.<lambda>>, 'LOG10': <function Parser.<lambda>>, 'MOD': <function build_mod>, 'TO_HEX': <function build_hex>, 'SQUARE': <function Oracle.Parser.<lambda>>, 'TO_TIMESTAMP': <function build_formatted_time.<locals>._builder>, 'TO_DATE': <function build_formatted_time.<locals>._builder>}"}, "sqlglot.dialects.oracle.Oracle.Parser.FUNCTION_PARSERS": {"fullname": "sqlglot.dialects.oracle.Oracle.Parser.FUNCTION_PARSERS", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Parser.FUNCTION_PARSERS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, Callable]", "default_value": "{'CAST': <function Parser.<lambda>>, 'CONVERT': <function Parser.<lambda>>, 'DECODE': <function Parser.<lambda>>, 'EXTRACT': <function Parser.<lambda>>, 'JSON_OBJECT': <function Parser.<lambda>>, 'JSON_OBJECTAGG': <function Parser.<lambda>>, 'JSON_TABLE': <function Parser.<lambda>>, 'MATCH': <function Parser.<lambda>>, 'OPENJSON': <function Parser.<lambda>>, 'POSITION': <function Parser.<lambda>>, 'PREDICT': <function Parser.<lambda>>, 'SAFE_CAST': <function Parser.<lambda>>, 'STRING_AGG': <function Parser.<lambda>>, 'SUBSTRING': <function Parser.<lambda>>, 'TRIM': <function Parser.<lambda>>, 'TRY_CAST': <function Parser.<lambda>>, 'TRY_CONVERT': <function Parser.<lambda>>, 'JSON_ARRAY': <function Oracle.Parser.<lambda>>, 'JSON_ARRAYAGG': <function Oracle.Parser.<lambda>>, 'XMLTABLE': <function Oracle.Parser.<lambda>>}"}, "sqlglot.dialects.oracle.Oracle.Parser.NO_PAREN_FUNCTION_PARSERS": {"fullname": "sqlglot.dialects.oracle.Oracle.Parser.NO_PAREN_FUNCTION_PARSERS", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Parser.NO_PAREN_FUNCTION_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ANY': <function Parser.<lambda>>, 'CASE': <function Parser.<lambda>>, 'IF': <function Parser.<lambda>>, 'NEXT': <function Parser.<lambda>>, 'CONNECT_BY_ROOT': <function Oracle.Parser.<lambda>>}"}, "sqlglot.dialects.oracle.Oracle.Parser.PROPERTY_PARSERS": {"fullname": "sqlglot.dialects.oracle.Oracle.Parser.PROPERTY_PARSERS", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Parser.PROPERTY_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ALLOWED_VALUES': <function Parser.<lambda>>, 'ALGORITHM': <function Parser.<lambda>>, 'AUTO': <function Parser.<lambda>>, 'AUTO_INCREMENT': <function Parser.<lambda>>, 'BACKUP': <function Parser.<lambda>>, 'BLOCKCOMPRESSION': <function Parser.<lambda>>, 'CHARSET': <function Parser.<lambda>>, 'CHARACTER SET': <function Parser.<lambda>>, 'CHECKSUM': <function Parser.<lambda>>, 'CLUSTER BY': <function Parser.<lambda>>, 'CLUSTERED': <function Parser.<lambda>>, 'COLLATE': <function Parser.<lambda>>, 'COMMENT': <function Parser.<lambda>>, 'CONTAINS': <function Parser.<lambda>>, 'COPY': <function Parser.<lambda>>, 'DATABLOCKSIZE': <function Parser.<lambda>>, 'DATA_DELETION': <function Parser.<lambda>>, 'DEFINER': <function Parser.<lambda>>, 'DETERMINISTIC': <function Parser.<lambda>>, 'DISTKEY': <function Parser.<lambda>>, 'DISTSTYLE': <function Parser.<lambda>>, 'ENGINE': <function Parser.<lambda>>, 'EXECUTE': <function Parser.<lambda>>, 'EXTERNAL': <function Parser.<lambda>>, 'FALLBACK': <function Parser.<lambda>>, 'FORMAT': <function Parser.<lambda>>, 'FREESPACE': <function Parser.<lambda>>, 'GLOBAL': <function Oracle.Parser.<lambda>>, 'HEAP': <function Parser.<lambda>>, 'ICEBERG': <function Parser.<lambda>>, 'IMMUTABLE': <function Parser.<lambda>>, 'INHERITS': <function Parser.<lambda>>, 'INPUT': <function Parser.<lambda>>, 'JOURNAL': <function Parser.<lambda>>, 'LANGUAGE': <function Parser.<lambda>>, 'LAYOUT': <function Parser.<lambda>>, 'LIFETIME': <function Parser.<lambda>>, 'LIKE': <function Parser.<lambda>>, 'LOCATION': <function Parser.<lambda>>, 'LOCK': <function Parser.<lambda>>, 'LOCKING': <function Parser.<lambda>>, 'LOG': <function Parser.<lambda>>, 'MATERIALIZED': <function Parser.<lambda>>, 'MERGEBLOCKRATIO': <function Parser.<lambda>>, 'MODIFIES': <function Parser.<lambda>>, 'MULTISET': <function Parser.<lambda>>, 'NO': <function Parser.<lambda>>, 'ON': <function Parser.<lambda>>, 'ORDER BY': <function Parser.<lambda>>, 'OUTPUT': <function Parser.<lambda>>, 'PARTITION': <function Parser.<lambda>>, 'PARTITION BY': <function Parser.<lambda>>, 'PARTITIONED BY': <function Parser.<lambda>>, 'PARTITIONED_BY': <function Parser.<lambda>>, 'PRIMARY KEY': <function Parser.<lambda>>, 'RANGE': <function Parser.<lambda>>, 'READS': <function Parser.<lambda>>, 'REMOTE': <function Parser.<lambda>>, 'RETURNS': <function Parser.<lambda>>, 'STRICT': <function Parser.<lambda>>, 'ROW': <function Parser.<lambda>>, 'ROW_FORMAT': <function Parser.<lambda>>, 'SAMPLE': <function Parser.<lambda>>, 'SET': <function Parser.<lambda>>, 'SETTINGS': <function Parser.<lambda>>, 'SHARING': <function Parser.<lambda>>, 'SORTKEY': <function Parser.<lambda>>, 'SOURCE': <function Parser.<lambda>>, 'STABLE': <function Parser.<lambda>>, 'STORED': <function Parser.<lambda>>, 'SYSTEM_VERSIONING': <function Parser.<lambda>>, 'TBLPROPERTIES': <function Parser.<lambda>>, 'TEMP': <function Parser.<lambda>>, 'TEMPORARY': <function Parser.<lambda>>, 'TO': <function Parser.<lambda>>, 'TRANSIENT': <function Parser.<lambda>>, 'TRANSFORM': <function Parser.<lambda>>, 'TTL': <function Parser.<lambda>>, 'USING': <function Parser.<lambda>>, 'UNLOGGED': <function Parser.<lambda>>, 'VOLATILE': <function Parser.<lambda>>, 'WITH': <function Parser.<lambda>>, 'PRIVATE': <function Oracle.Parser.<lambda>>}"}, "sqlglot.dialects.oracle.Oracle.Parser.QUERY_MODIFIER_PARSERS": {"fullname": "sqlglot.dialects.oracle.Oracle.Parser.QUERY_MODIFIER_PARSERS", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Parser.QUERY_MODIFIER_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.MATCH_RECOGNIZE: 'MATCH_RECOGNIZE'>: <function Parser.<lambda>>, <TokenType.PREWHERE: 'PREWHERE'>: <function Parser.<lambda>>, <TokenType.WHERE: 'WHERE'>: <function Parser.<lambda>>, <TokenType.GROUP_BY: 'GROUP_BY'>: <function Parser.<lambda>>, <TokenType.HAVING: 'HAVING'>: <function Parser.<lambda>>, <TokenType.QUALIFY: 'QUALIFY'>: <function Parser.<lambda>>, <TokenType.WINDOW: 'WINDOW'>: <function Parser.<lambda>>, <TokenType.ORDER_BY: 'ORDER_BY'>: <function Parser.<lambda>>, <TokenType.LIMIT: 'LIMIT'>: <function Parser.<lambda>>, <TokenType.FETCH: 'FETCH'>: <function Parser.<lambda>>, <TokenType.OFFSET: 'OFFSET'>: <function Parser.<lambda>>, <TokenType.FOR: 'FOR'>: <function Parser.<lambda>>, <TokenType.LOCK: 'LOCK'>: <function Parser.<lambda>>, <TokenType.TABLE_SAMPLE: 'TABLE_SAMPLE'>: <function Parser.<lambda>>, <TokenType.USING: 'USING'>: <function Parser.<lambda>>, <TokenType.CLUSTER_BY: 'CLUSTER_BY'>: <function Parser.<lambda>>, <TokenType.DISTRIBUTE_BY: 'DISTRIBUTE_BY'>: <function Parser.<lambda>>, <TokenType.SORT_BY: 'SORT_BY'>: <function Parser.<lambda>>, <TokenType.CONNECT_BY: 'CONNECT_BY'>: <function Parser.<lambda>>, <TokenType.START_WITH: 'START_WITH'>: <function Parser.<lambda>>, <TokenType.ORDER_SIBLINGS_BY: 'ORDER_SIBLINGS_BY'>: <function Oracle.Parser.<lambda>>}"}, "sqlglot.dialects.oracle.Oracle.Parser.TYPE_LITERAL_PARSERS": {"fullname": "sqlglot.dialects.oracle.Oracle.Parser.TYPE_LITERAL_PARSERS", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Parser.TYPE_LITERAL_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.DATE: 'DATE'>: <function Oracle.Parser.<lambda>>}"}, "sqlglot.dialects.oracle.Oracle.Parser.DISTINCT_TOKENS": {"fullname": "sqlglot.dialects.oracle.Oracle.Parser.DISTINCT_TOKENS", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Parser.DISTINCT_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.UNIQUE: 'UNIQUE'>, <TokenType.DISTINCT: 'DISTINCT'>}"}, "sqlglot.dialects.oracle.Oracle.Parser.SHOW_TRIE": {"fullname": "sqlglot.dialects.oracle.Oracle.Parser.SHOW_TRIE", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Parser.SHOW_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.oracle.Oracle.Parser.SET_TRIE": {"fullname": "sqlglot.dialects.oracle.Oracle.Parser.SET_TRIE", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Parser.SET_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'GLOBAL': {0: True}, 'LOCAL': {0: True}, 'SESSION': {0: True}, 'TRANSACTION': {0: True}}"}, "sqlglot.dialects.oracle.Oracle.Generator": {"fullname": "sqlglot.dialects.oracle.Oracle.Generator", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Generator", "kind": "class", "doc": "<p>Generator converts a given syntax tree to the corresponding SQL string.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>pretty:</strong> Whether to format the produced SQL string.\nDefault: False.</li>\n<li><strong>identify:</strong> Determines when an identifier should be quoted. Possible values are:\nFalse (default): Never quote, except in cases where it's mandatory by the dialect.\nTrue or 'always': Always quote.\n'safe': Only quote identifiers that are case insensitive.</li>\n<li><strong>normalize:</strong> Whether to normalize identifiers to lowercase.\nDefault: False.</li>\n<li><strong>pad:</strong> The pad size in a formatted string. For example, this affects the indentation of\na projection in a query, relative to its nesting level.\nDefault: 2.</li>\n<li><strong>indent:</strong> The indentation size in a formatted string. For example, this affects the\nindentation of subqueries and filters under a <code>WHERE</code> clause.\nDefault: 2.</li>\n<li><strong>normalize_functions:</strong> How to normalize function names. Possible values are:\n\"upper\" or True (default): Convert names to uppercase.\n\"lower\": Convert names to lowercase.\nFalse: Disables function name normalization.</li>\n<li><strong>unsupported_level:</strong> Determines the generator's behavior when it encounters unsupported expressions.\nDefault ErrorLevel.WARN.</li>\n<li><strong>max_unsupported:</strong> Maximum number of unsupported messages to include in a raised UnsupportedError.\nThis is only relevant if unsupported_level is ErrorLevel.RAISE.\nDefault: 3</li>\n<li><strong>leading_comma:</strong> Whether the comma is leading or trailing in select expressions.\nThis is only relevant when generating in pretty mode.\nDefault: False</li>\n<li><strong>max_text_width:</strong> The max number of characters in a segment before creating new lines in pretty mode.\nThe default is on the smaller end because the length only represents a segment and not the true\nline length.\nDefault: 80</li>\n<li><strong>comments:</strong> Whether to preserve comments in the output SQL code.\nDefault: True</li>\n</ul>\n", "bases": "sqlglot.generator.Generator"}, "sqlglot.dialects.oracle.Oracle.Generator.LOCKING_READS_SUPPORTED": {"fullname": "sqlglot.dialects.oracle.Oracle.Generator.LOCKING_READS_SUPPORTED", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Generator.LOCKING_READS_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.oracle.Oracle.Generator.JOIN_HINTS": {"fullname": "sqlglot.dialects.oracle.Oracle.Generator.JOIN_HINTS", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Generator.JOIN_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.oracle.Oracle.Generator.TABLE_HINTS": {"fullname": "sqlglot.dialects.oracle.Oracle.Generator.TABLE_HINTS", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Generator.TABLE_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.oracle.Oracle.Generator.COLUMN_JOIN_MARKS_SUPPORTED": {"fullname": "sqlglot.dialects.oracle.Oracle.Generator.COLUMN_JOIN_MARKS_SUPPORTED", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Generator.COLUMN_JOIN_MARKS_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.oracle.Oracle.Generator.DATA_TYPE_SPECIFIERS_ALLOWED": {"fullname": "sqlglot.dialects.oracle.Oracle.Generator.DATA_TYPE_SPECIFIERS_ALLOWED", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Generator.DATA_TYPE_SPECIFIERS_ALLOWED", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.oracle.Oracle.Generator.ALTER_TABLE_INCLUDE_COLUMN_KEYWORD": {"fullname": "sqlglot.dialects.oracle.Oracle.Generator.ALTER_TABLE_INCLUDE_COLUMN_KEYWORD", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Generator.ALTER_TABLE_INCLUDE_COLUMN_KEYWORD", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.oracle.Oracle.Generator.LIMIT_FETCH": {"fullname": "sqlglot.dialects.oracle.Oracle.Generator.LIMIT_FETCH", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Generator.LIMIT_FETCH", "kind": "variable", "doc": "<p></p>\n", "default_value": "'FETCH'"}, "sqlglot.dialects.oracle.Oracle.Generator.TABLESAMPLE_KEYWORDS": {"fullname": "sqlglot.dialects.oracle.Oracle.Generator.TABLESAMPLE_KEYWORDS", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Generator.TABLESAMPLE_KEYWORDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "'SAMPLE'"}, "sqlglot.dialects.oracle.Oracle.Generator.LAST_DAY_SUPPORTS_DATE_PART": {"fullname": "sqlglot.dialects.oracle.Oracle.Generator.LAST_DAY_SUPPORTS_DATE_PART", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Generator.LAST_DAY_SUPPORTS_DATE_PART", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.oracle.Oracle.Generator.SUPPORTS_SELECT_INTO": {"fullname": "sqlglot.dialects.oracle.Oracle.Generator.SUPPORTS_SELECT_INTO", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Generator.SUPPORTS_SELECT_INTO", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.oracle.Oracle.Generator.TZ_TO_WITH_TIME_ZONE": {"fullname": "sqlglot.dialects.oracle.Oracle.Generator.TZ_TO_WITH_TIME_ZONE", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Generator.TZ_TO_WITH_TIME_ZONE", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.oracle.Oracle.Generator.TYPE_MAPPING": {"fullname": "sqlglot.dialects.oracle.Oracle.Generator.TYPE_MAPPING", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Generator.TYPE_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.NCHAR: 'NCHAR'>: 'NCHAR', <Type.NVARCHAR: 'NVARCHAR'>: 'NVARCHAR2', <Type.MEDIUMTEXT: 'MEDIUMTEXT'>: 'TEXT', <Type.LONGTEXT: 'LONGTEXT'>: 'TEXT', <Type.TINYTEXT: 'TINYTEXT'>: 'TEXT', <Type.MEDIUMBLOB: 'MEDIUMBLOB'>: 'BLOB', <Type.LONGBLOB: 'LONGBLOB'>: 'BLOB', <Type.TINYBLOB: 'TINYBLOB'>: 'BLOB', <Type.INET: 'INET'>: 'INET', <Type.ROWVERSION: 'ROWVERSION'>: 'BLOB', <Type.TINYINT: 'TINYINT'>: 'NUMBER', <Type.SMALLINT: 'SMALLINT'>: 'NUMBER', <Type.INT: 'INT'>: 'NUMBER', <Type.BIGINT: 'BIGINT'>: 'NUMBER', <Type.DECIMAL: 'DECIMAL'>: 'NUMBER', <Type.DOUBLE: 'DOUBLE'>: 'DOUBLE PRECISION', <Type.VARCHAR: 'VARCHAR'>: 'VARCHAR2', <Type.TEXT: 'TEXT'>: 'CLOB', <Type.TIMETZ: 'TIMETZ'>: 'TIME', <Type.TIMESTAMPTZ: 'TIMESTAMPTZ'>: 'TIMESTAMP', <Type.BINARY: 'BINARY'>: 'BLOB', <Type.VARBINARY: 'VARBINARY'>: 'BLOB'}"}, "sqlglot.dialects.oracle.Oracle.Generator.TRANSFORMS": {"fullname": "sqlglot.dialects.oracle.Oracle.Generator.TRANSFORMS", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Generator.TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.JSONPathFilter'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathKey'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRecursive'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRoot'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathScript'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSelector'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSlice'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSubscript'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathUnion'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathWildcard'>: <function <lambda>>, <class 'sqlglot.expressions.AllowedValuesProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.BackupProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CaseSpecificColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetColumnConstraint'>: 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'sqlglot.expressions.ExternalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.GlobalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.HeapProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IcebergProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InheritsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InlineLengthColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IntervalSpan'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtract'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtractScalar'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LanguageProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LocationProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LogProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.MaterializedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NonClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NotForReplicationColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnCommitProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnUpdateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OutputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.PathColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ReturnsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SampleProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetConfigProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SettingsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SharingProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlReadWriteProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlSecurityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StabilityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StrictProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TemporaryProperty'>: <function Oracle.Generator.<lambda>>, <class 'sqlglot.expressions.TitleColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.Timestamp'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransformModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransientProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UppercaseColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UnloggedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VarMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VolatileProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithOperator'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ConnectByRoot'>: <function Oracle.Generator.<lambda>>, <class 'sqlglot.expressions.DateStrToDate'>: <function Oracle.Generator.<lambda>>, <class 'sqlglot.expressions.Group'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.ILike'>: <function no_ilike_sql>, <class 'sqlglot.expressions.Select'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.StrToTime'>: <function Oracle.Generator.<lambda>>, <class 'sqlglot.expressions.StrToDate'>: <function Oracle.Generator.<lambda>>, <class 'sqlglot.expressions.Subquery'>: <function Oracle.Generator.<lambda>>, <class 'sqlglot.expressions.Substring'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.Table'>: <function Oracle.Generator.<lambda>>, <class 'sqlglot.expressions.TableSample'>: <function Oracle.Generator.<lambda>>, <class 'sqlglot.expressions.TimeToStr'>: <function Oracle.Generator.<lambda>>, <class 'sqlglot.expressions.ToChar'>: <function Oracle.Generator.<lambda>>, <class 'sqlglot.expressions.ToNumber'>: <function to_number_with_nls_param>, <class 'sqlglot.expressions.Trim'>: <function trim_sql>, <class 'sqlglot.expressions.UnixToTime'>: <function Oracle.Generator.<lambda>>}"}, "sqlglot.dialects.oracle.Oracle.Generator.PROPERTIES_LOCATION": {"fullname": "sqlglot.dialects.oracle.Oracle.Generator.PROPERTIES_LOCATION", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Generator.PROPERTIES_LOCATION", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.AllowedValuesProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.AlgorithmProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.AutoIncrementProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.BackupProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.BlockCompressionProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.CharacterSetProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ChecksumProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.CollateProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Cluster'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ClusteredByProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DataBlocksizeProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.DataDeletionProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DefinerProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.DictRange'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DictProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DistKeyProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DistStyleProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.EngineProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ExternalProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.FallbackProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.FileFormatProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.FreespaceProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.GlobalProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.HeapProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.InheritsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.IcebergProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.InputModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.IsolatedLoadingProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.JournalProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.LanguageProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LikeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LocationProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LockProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LockingProperty'>: <Location.POST_ALIAS: 'POST_ALIAS'>, <class 'sqlglot.expressions.LogProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.MaterializedProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.MergeBlockRatioProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.OnProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.OnCommitProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.Order'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.OutputModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.PartitionedByProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.PartitionedOfProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.PrimaryKey'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Property'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ReturnsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatDelimitedProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatSerdeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SampleProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SchemaCommentProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SerdeProperties'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Set'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SettingsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SetProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.SetConfigProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SharingProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.SequenceProperties'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.SortKeyProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SqlReadWriteProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SqlSecurityProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.StabilityProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.StrictProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.TemporaryProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.ToTableProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.TransientProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.TransformModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.MergeTreeTTL'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.UnloggedProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.VolatileProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.WithDataProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.WithSystemVersioningProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>}"}, "sqlglot.dialects.oracle.Oracle.Generator.currenttimestamp_sql": {"fullname": "sqlglot.dialects.oracle.Oracle.Generator.currenttimestamp_sql", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Generator.currenttimestamp_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">CurrentTimestamp</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.oracle.Oracle.Generator.offset_sql": {"fullname": "sqlglot.dialects.oracle.Oracle.Generator.offset_sql", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Generator.offset_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Offset</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.oracle.Oracle.Generator.xmltable_sql": {"fullname": "sqlglot.dialects.oracle.Oracle.Generator.xmltable_sql", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Generator.xmltable_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">XMLTable</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.oracle.Oracle.Generator.add_column_sql": {"fullname": "sqlglot.dialects.oracle.Oracle.Generator.add_column_sql", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Generator.add_column_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">AlterTable</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.oracle.Oracle.Generator.SELECT_KINDS": {"fullname": "sqlglot.dialects.oracle.Oracle.Generator.SELECT_KINDS", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Generator.SELECT_KINDS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Tuple[str, ...]", "default_value": "()"}, "sqlglot.dialects.oracle.Oracle.Generator.TRY_SUPPORTED": {"fullname": "sqlglot.dialects.oracle.Oracle.Generator.TRY_SUPPORTED", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Generator.TRY_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.oracle.Oracle.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS": {"fullname": "sqlglot.dialects.oracle.Oracle.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'qualify': <function Generator.<lambda>>, 'windows': <function Generator.<lambda>>}"}, "sqlglot.dialects.oracle.Oracle.tokenizer_class": {"fullname": "sqlglot.dialects.oracle.Oracle.tokenizer_class", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.tokenizer_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.oracle.Oracle.Tokenizer'>"}, "sqlglot.dialects.oracle.Oracle.parser_class": {"fullname": "sqlglot.dialects.oracle.Oracle.parser_class", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.parser_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.oracle.Oracle.Parser'>"}, "sqlglot.dialects.oracle.Oracle.generator_class": {"fullname": "sqlglot.dialects.oracle.Oracle.generator_class", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.generator_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.oracle.Oracle.Generator'>"}, "sqlglot.dialects.oracle.Oracle.TIME_TRIE": {"fullname": "sqlglot.dialects.oracle.Oracle.TIME_TRIE", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'A': {'M': {0: True}, '.': {'M': {'.': {0: True}}}}, 'P': {'M': {0: True}, '.': {'M': {'.': {0: True}}}}, 'D': {0: True, 'A': {'Y': {0: True}}, 'D': {0: True, 'D': {0: True}}, 'Y': {0: True}}, 'H': {'H': {0: True, '1': {'2': {0: True}}, '2': {'4': {0: True}}}}, 'I': {'W': {0: True}}, 'M': {'I': {0: True}, 'M': {0: True}, 'O': {'N': {0: True, 'T': {'H': {0: True}}}}}, 'S': {'S': {0: True}}, 'W': {'W': {0: True}}, 'Y': {'Y': {0: True, 'Y': {'Y': {0: True}}}}, 'F': {'F': {'6': {0: True}}}}"}, "sqlglot.dialects.oracle.Oracle.FORMAT_TRIE": {"fullname": "sqlglot.dialects.oracle.Oracle.FORMAT_TRIE", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.FORMAT_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'A': {'M': {0: True}, '.': {'M': {'.': {0: True}}}}, 'P': {'M': {0: True}, '.': {'M': {'.': {0: True}}}}, 'D': {0: True, 'A': {'Y': {0: True}}, 'D': {0: True, 'D': {0: True}}, 'Y': {0: True}}, 'H': {'H': {0: True, '1': {'2': {0: True}}, '2': {'4': {0: True}}}}, 'I': {'W': {0: True}}, 'M': {'I': {0: True}, 'M': {0: True}, 'O': {'N': {0: True, 'T': {'H': {0: True}}}}}, 'S': {'S': {0: True}}, 'W': {'W': {0: True}}, 'Y': {'Y': {0: True, 'Y': {'Y': {0: True}}}}, 'F': {'F': {'6': {0: True}}}}"}, "sqlglot.dialects.oracle.Oracle.INVERSE_TIME_MAPPING": {"fullname": "sqlglot.dialects.oracle.Oracle.INVERSE_TIME_MAPPING", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.INVERSE_TIME_MAPPING", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'%p': 'P.M.', '%u': 'D', '%A': 'DAY', '%d': 'DD', '%j': 'DDD', '%a': 'DY', '%I': 'HH12', '%H': 'HH24', '%V': 'IW', '%M': 'MI', '%m': 'MM', '%b': 'MON', '%B': 'MONTH', '%S': 'SS', '%W': 'WW', '%y': 'YY', '%Y': 'YYYY', '%f': 'FF6'}"}, "sqlglot.dialects.oracle.Oracle.INVERSE_TIME_TRIE": {"fullname": "sqlglot.dialects.oracle.Oracle.INVERSE_TIME_TRIE", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.INVERSE_TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'%': {'p': {0: True}, 'u': {0: True}, 'A': {0: True}, 'd': {0: True}, 'j': {0: True}, 'a': {0: True}, 'I': {0: True}, 'H': {0: True}, 'V': {0: True}, 'M': {0: True}, 'm': {0: True}, 'b': {0: True}, 'B': {0: True}, 'S': {0: True}, 'W': {0: True}, 'y': {0: True}, 'Y': {0: True}, 'f': {0: True}}}"}, "sqlglot.dialects.oracle.Oracle.ESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.oracle.Oracle.ESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.ESCAPED_SEQUENCES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{}"}, "sqlglot.dialects.oracle.Oracle.QUOTE_START": {"fullname": "sqlglot.dialects.oracle.Oracle.QUOTE_START", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.QUOTE_START", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.oracle.Oracle.QUOTE_END": {"fullname": "sqlglot.dialects.oracle.Oracle.QUOTE_END", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.QUOTE_END", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.oracle.Oracle.IDENTIFIER_START": {"fullname": "sqlglot.dialects.oracle.Oracle.IDENTIFIER_START", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.IDENTIFIER_START", "kind": "variable", "doc": "<p></p>\n", "default_value": "'"'"}, "sqlglot.dialects.oracle.Oracle.IDENTIFIER_END": {"fullname": "sqlglot.dialects.oracle.Oracle.IDENTIFIER_END", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.IDENTIFIER_END", "kind": "variable", "doc": "<p></p>\n", "default_value": "'"'"}, "sqlglot.dialects.oracle.Oracle.BIT_START": {"fullname": "sqlglot.dialects.oracle.Oracle.BIT_START", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.BIT_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.oracle.Oracle.BIT_END": {"fullname": "sqlglot.dialects.oracle.Oracle.BIT_END", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.BIT_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.oracle.Oracle.HEX_START": {"fullname": "sqlglot.dialects.oracle.Oracle.HEX_START", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.HEX_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.oracle.Oracle.HEX_END": {"fullname": "sqlglot.dialects.oracle.Oracle.HEX_END", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.HEX_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.oracle.Oracle.BYTE_START": {"fullname": "sqlglot.dialects.oracle.Oracle.BYTE_START", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.BYTE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.oracle.Oracle.BYTE_END": {"fullname": "sqlglot.dialects.oracle.Oracle.BYTE_END", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.BYTE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.oracle.Oracle.UNICODE_START": {"fullname": "sqlglot.dialects.oracle.Oracle.UNICODE_START", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.UNICODE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.oracle.Oracle.UNICODE_END": {"fullname": "sqlglot.dialects.oracle.Oracle.UNICODE_END", "modulename": "sqlglot.dialects.oracle", "qualname": "Oracle.UNICODE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.postgres": {"fullname": "sqlglot.dialects.postgres", "modulename": "sqlglot.dialects.postgres", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.dialects.postgres.DATE_DIFF_FACTOR": {"fullname": "sqlglot.dialects.postgres.DATE_DIFF_FACTOR", "modulename": "sqlglot.dialects.postgres", "qualname": "DATE_DIFF_FACTOR", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'MICROSECOND': ' * 1000000', 'MILLISECOND': ' * 1000', 'SECOND': '', 'MINUTE': ' / 60', 'HOUR': ' / 3600', 'DAY': ' / 86400'}"}, "sqlglot.dialects.postgres.Postgres": {"fullname": "sqlglot.dialects.postgres.Postgres", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.dialect.Dialect"}, "sqlglot.dialects.postgres.Postgres.INDEX_OFFSET": {"fullname": "sqlglot.dialects.postgres.Postgres.INDEX_OFFSET", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.INDEX_OFFSET", "kind": "variable", "doc": "<p>The base index offset for arrays.</p>\n", "default_value": "1"}, "sqlglot.dialects.postgres.Postgres.TYPED_DIVISION": {"fullname": "sqlglot.dialects.postgres.Postgres.TYPED_DIVISION", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.TYPED_DIVISION", "kind": "variable", "doc": "<p>Whether the behavior of <code>a / b</code> depends on the types of <code>a</code> and <code>b</code>.\nFalse means <code>a / b</code> is always float division.\nTrue means <code>a / b</code> is integer division if both <code>a</code> and <code>b</code> are integers.</p>\n", "default_value": "True"}, "sqlglot.dialects.postgres.Postgres.CONCAT_COALESCE": {"fullname": "sqlglot.dialects.postgres.Postgres.CONCAT_COALESCE", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.CONCAT_COALESCE", "kind": "variable", "doc": "<p>A <code>NULL</code> arg in <code>CONCAT</code> yields <code>NULL</code> by default, but in some dialects it yields an empty string.</p>\n", "default_value": "True"}, "sqlglot.dialects.postgres.Postgres.NULL_ORDERING": {"fullname": "sqlglot.dialects.postgres.Postgres.NULL_ORDERING", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.NULL_ORDERING", "kind": "variable", "doc": "<p>Default <code>NULL</code> ordering method to use if not explicitly set.\nPossible values: <code>\"nulls_are_small\"</code>, <code>\"nulls_are_large\"</code>, <code>\"nulls_are_last\"</code></p>\n", "default_value": "'nulls_are_large'"}, "sqlglot.dialects.postgres.Postgres.TIME_FORMAT": {"fullname": "sqlglot.dialects.postgres.Postgres.TIME_FORMAT", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.TIME_FORMAT", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'YYYY-MM-DD HH24:MI:SS'""}, "sqlglot.dialects.postgres.Postgres.TABLESAMPLE_SIZE_IS_PERCENT": {"fullname": "sqlglot.dialects.postgres.Postgres.TABLESAMPLE_SIZE_IS_PERCENT", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.TABLESAMPLE_SIZE_IS_PERCENT", "kind": "variable", "doc": "<p>Whether a size in the table sample clause represents percentage.</p>\n", "default_value": "True"}, "sqlglot.dialects.postgres.Postgres.TIME_MAPPING": {"fullname": "sqlglot.dialects.postgres.Postgres.TIME_MAPPING", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.TIME_MAPPING", "kind": "variable", "doc": "<p>Associates this dialect's time formats with their equivalent Python <code>strftime</code> formats.</p>\n", "annotation": ": Dict[str, str]", "default_value": "{'AM': '%p', 'PM': '%p', 'D': '%u', 'DD': '%d', 'DDD': '%j', 'FMDD': '%-d', 'FMDDD': '%-j', 'FMHH12': '%-I', 'FMHH24': '%-H', 'FMMI': '%-M', 'FMMM': '%-m', 'FMSS': '%-S', 'HH12': '%I', 'HH24': '%H', 'MI': '%M', 'MM': '%m', 'OF': '%z', 'SS': '%S', 'TMDay': '%A', 'TMDy': '%a', 'TMMon': '%b', 'TMMonth': '%B', 'TZ': '%Z', 'US': '%f', 'WW': '%U', 'YY': '%y', 'YYYY': '%Y'}"}, "sqlglot.dialects.postgres.Postgres.Tokenizer": {"fullname": "sqlglot.dialects.postgres.Postgres.Tokenizer", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Tokenizer", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.tokens.Tokenizer"}, "sqlglot.dialects.postgres.Postgres.Tokenizer.BIT_STRINGS": {"fullname": "sqlglot.dialects.postgres.Postgres.Tokenizer.BIT_STRINGS", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Tokenizer.BIT_STRINGS", "kind": "variable", "doc": "<p></p>\n", "default_value": "[("b'", "'"), ("B'", "'")]"}, "sqlglot.dialects.postgres.Postgres.Tokenizer.HEX_STRINGS": {"fullname": "sqlglot.dialects.postgres.Postgres.Tokenizer.HEX_STRINGS", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Tokenizer.HEX_STRINGS", "kind": "variable", "doc": "<p></p>\n", "default_value": "[("x'", "'"), ("X'", "'")]"}, "sqlglot.dialects.postgres.Postgres.Tokenizer.BYTE_STRINGS": {"fullname": "sqlglot.dialects.postgres.Postgres.Tokenizer.BYTE_STRINGS", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Tokenizer.BYTE_STRINGS", "kind": "variable", "doc": "<p></p>\n", "default_value": "[("e'", "'"), ("E'", "'")]"}, "sqlglot.dialects.postgres.Postgres.Tokenizer.HEREDOC_STRINGS": {"fullname": "sqlglot.dialects.postgres.Postgres.Tokenizer.HEREDOC_STRINGS", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Tokenizer.HEREDOC_STRINGS", "kind": "variable", "doc": "<p></p>\n", "default_value": "['$']"}, "sqlglot.dialects.postgres.Postgres.Tokenizer.HEREDOC_TAG_IS_IDENTIFIER": {"fullname": "sqlglot.dialects.postgres.Postgres.Tokenizer.HEREDOC_TAG_IS_IDENTIFIER", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Tokenizer.HEREDOC_TAG_IS_IDENTIFIER", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.postgres.Postgres.Tokenizer.HEREDOC_STRING_ALTERNATIVE": {"fullname": "sqlglot.dialects.postgres.Postgres.Tokenizer.HEREDOC_STRING_ALTERNATIVE", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Tokenizer.HEREDOC_STRING_ALTERNATIVE", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.PARAMETER: 'PARAMETER'>"}, "sqlglot.dialects.postgres.Postgres.Tokenizer.KEYWORDS": {"fullname": "sqlglot.dialects.postgres.Postgres.Tokenizer.KEYWORDS", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Tokenizer.KEYWORDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'{%': <TokenType.BLOCK_START: 'BLOCK_START'>, '{%+': <TokenType.BLOCK_START: 'BLOCK_START'>, '{%-': <TokenType.BLOCK_START: 'BLOCK_START'>, '%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '+%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '-%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '{{+': <TokenType.BLOCK_START: 'BLOCK_START'>, '{{-': <TokenType.BLOCK_START: 'BLOCK_START'>, '+}}': <TokenType.BLOCK_END: 'BLOCK_END'>, '-}}': <TokenType.BLOCK_END: 'BLOCK_END'>, '/*+': <TokenType.HINT: 'HINT'>, '==': <TokenType.EQ: 'EQ'>, '::': <TokenType.DCOLON: 'DCOLON'>, '||': <TokenType.DPIPE: 'DPIPE'>, '>=': <TokenType.GTE: 'GTE'>, '<=': <TokenType.LTE: 'LTE'>, '<>': <TokenType.NEQ: 'NEQ'>, '!=': <TokenType.NEQ: 'NEQ'>, ':=': <TokenType.COLON_EQ: 'COLON_EQ'>, '<=>': <TokenType.NULLSAFE_EQ: 'NULLSAFE_EQ'>, '->': <TokenType.ARROW: 'ARROW'>, '->>': <TokenType.DARROW: 'DARROW'>, '=>': <TokenType.FARROW: 'FARROW'>, '#>': <TokenType.HASH_ARROW: 'HASH_ARROW'>, '#>>': <TokenType.DHASH_ARROW: 'DHASH_ARROW'>, '<->': <TokenType.LR_ARROW: 'LR_ARROW'>, '&&': <TokenType.DAMP: 'DAMP'>, '??': <TokenType.DQMARK: 'DQMARK'>, 'ALL': <TokenType.ALL: 'ALL'>, 'ALWAYS': <TokenType.ALWAYS: 'ALWAYS'>, 'AND': <TokenType.AND: 'AND'>, 'ANTI': <TokenType.ANTI: 'ANTI'>, 'ANY': <TokenType.ANY: 'ANY'>, 'ASC': <TokenType.ASC: 'ASC'>, 'AS': <TokenType.ALIAS: 'ALIAS'>, 'ASOF': <TokenType.ASOF: 'ASOF'>, 'AUTOINCREMENT': <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, 'AUTO_INCREMENT': <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, 'BEGIN': <TokenType.COMMAND: 'COMMAND'>, 'BETWEEN': <TokenType.BETWEEN: 'BETWEEN'>, 'CACHE': <TokenType.CACHE: 'CACHE'>, 'UNCACHE': <TokenType.UNCACHE: 'UNCACHE'>, 'CASE': <TokenType.CASE: 'CASE'>, 'CHARACTER SET': <TokenType.CHARACTER_SET: 'CHARACTER_SET'>, 'CLUSTER BY': <TokenType.CLUSTER_BY: 'CLUSTER_BY'>, 'COLLATE': <TokenType.COLLATE: 'COLLATE'>, 'COLUMN': <TokenType.COLUMN: 'COLUMN'>, 'COMMIT': <TokenType.COMMIT: 'COMMIT'>, 'CONNECT BY': <TokenType.CONNECT_BY: 'CONNECT_BY'>, 'CONSTRAINT': <TokenType.CONSTRAINT: 'CONSTRAINT'>, 'COPY': <TokenType.COPY: 'COPY'>, 'CREATE': <TokenType.CREATE: 'CREATE'>, 'CROSS': <TokenType.CROSS: 'CROSS'>, 'CUBE': <TokenType.CUBE: 'CUBE'>, 'CURRENT_DATE': <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, 'CURRENT_TIME': <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, 'CURRENT_TIMESTAMP': <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, 'CURRENT_USER': <TokenType.CURRENT_USER: 'CURRENT_USER'>, 'DATABASE': <TokenType.DATABASE: 'DATABASE'>, 'DEFAULT': <TokenType.DEFAULT: 'DEFAULT'>, 'DELETE': <TokenType.DELETE: 'DELETE'>, 'DESC': <TokenType.DESC: 'DESC'>, 'DESCRIBE': <TokenType.DESCRIBE: 'DESCRIBE'>, 'DISTINCT': <TokenType.DISTINCT: 'DISTINCT'>, 'DISTRIBUTE BY': <TokenType.DISTRIBUTE_BY: 'DISTRIBUTE_BY'>, 'DIV': <TokenType.DIV: 'DIV'>, 'DROP': <TokenType.DROP: 'DROP'>, 'ELSE': <TokenType.ELSE: 'ELSE'>, 'END': <TokenType.END: 'END'>, 'ENUM': <TokenType.ENUM: 'ENUM'>, 'ESCAPE': <TokenType.ESCAPE: 'ESCAPE'>, 'EXCEPT': <TokenType.EXCEPT: 'EXCEPT'>, 'EXECUTE': <TokenType.EXECUTE: 'EXECUTE'>, 'EXISTS': <TokenType.EXISTS: 'EXISTS'>, 'FALSE': <TokenType.FALSE: 'FALSE'>, 'FETCH': <TokenType.FETCH: 'FETCH'>, 'FILTER': <TokenType.FILTER: 'FILTER'>, 'FIRST': <TokenType.FIRST: 'FIRST'>, 'FULL': <TokenType.FULL: 'FULL'>, 'FUNCTION': <TokenType.FUNCTION: 'FUNCTION'>, 'FOR': <TokenType.FOR: 'FOR'>, 'FOREIGN KEY': <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, 'FORMAT': <TokenType.FORMAT: 'FORMAT'>, 'FROM': <TokenType.FROM: 'FROM'>, 'GEOGRAPHY': <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, 'GEOMETRY': <TokenType.GEOMETRY: 'GEOMETRY'>, 'GLOB': <TokenType.GLOB: 'GLOB'>, 'GROUP BY': <TokenType.GROUP_BY: 'GROUP_BY'>, 'GROUPING SETS': <TokenType.GROUPING_SETS: 'GROUPING_SETS'>, 'HAVING': <TokenType.HAVING: 'HAVING'>, 'ILIKE': <TokenType.ILIKE: 'ILIKE'>, 'IN': <TokenType.IN: 'IN'>, 'INDEX': <TokenType.INDEX: 'INDEX'>, 'INET': <TokenType.INET: 'INET'>, 'INNER': <TokenType.INNER: 'INNER'>, 'INSERT': <TokenType.INSERT: 'INSERT'>, 'INTERVAL': <TokenType.INTERVAL: 'INTERVAL'>, 'INTERSECT': <TokenType.INTERSECT: 'INTERSECT'>, 'INTO': <TokenType.INTO: 'INTO'>, 'IS': <TokenType.IS: 'IS'>, 'ISNULL': <TokenType.ISNULL: 'ISNULL'>, 'JOIN': <TokenType.JOIN: 'JOIN'>, 'KEEP': <TokenType.KEEP: 'KEEP'>, 'KILL': <TokenType.KILL: 'KILL'>, 'LATERAL': <TokenType.LATERAL: 'LATERAL'>, 'LEFT': <TokenType.LEFT: 'LEFT'>, 'LIKE': <TokenType.LIKE: 'LIKE'>, 'LIMIT': <TokenType.LIMIT: 'LIMIT'>, 'LOAD': <TokenType.LOAD: 'LOAD'>, 'LOCK': <TokenType.LOCK: 'LOCK'>, 'MERGE': <TokenType.MERGE: 'MERGE'>, 'NATURAL': <TokenType.NATURAL: 'NATURAL'>, 'NEXT': <TokenType.NEXT: 'NEXT'>, 'NOT': <TokenType.NOT: 'NOT'>, 'NOTNULL': <TokenType.NOTNULL: 'NOTNULL'>, 'NULL': <TokenType.NULL: 'NULL'>, 'OBJECT': <TokenType.OBJECT: 'OBJECT'>, 'OFFSET': <TokenType.OFFSET: 'OFFSET'>, 'ON': <TokenType.ON: 'ON'>, 'OR': <TokenType.OR: 'OR'>, 'XOR': <TokenType.XOR: 'XOR'>, 'ORDER BY': <TokenType.ORDER_BY: 'ORDER_BY'>, 'ORDINALITY': <TokenType.ORDINALITY: 'ORDINALITY'>, 'OUTER': <TokenType.OUTER: 'OUTER'>, 'OVER': <TokenType.OVER: 'OVER'>, 'OVERLAPS': <TokenType.OVERLAPS: 'OVERLAPS'>, 'OVERWRITE': <TokenType.OVERWRITE: 'OVERWRITE'>, 'PARTITION': <TokenType.PARTITION: 'PARTITION'>, 'PARTITION BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PARTITIONED BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PARTITIONED_BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PERCENT': <TokenType.PERCENT: 'PERCENT'>, 'PIVOT': <TokenType.PIVOT: 'PIVOT'>, 'PRAGMA': <TokenType.PRAGMA: 'PRAGMA'>, 'PRIMARY KEY': <TokenType.PRIMARY_KEY: 'PRIMARY_KEY'>, 'PROCEDURE': <TokenType.PROCEDURE: 'PROCEDURE'>, 'QUALIFY': <TokenType.QUALIFY: 'QUALIFY'>, 'RANGE': <TokenType.RANGE: 'RANGE'>, 'RECURSIVE': <TokenType.RECURSIVE: 'RECURSIVE'>, 'REGEXP': <TokenType.RLIKE: 'RLIKE'>, 'REPLACE': <TokenType.REPLACE: 'REPLACE'>, 'RETURNING': <TokenType.RETURNING: 'RETURNING'>, 'REFERENCES': <TokenType.REFERENCES: 'REFERENCES'>, 'RIGHT': <TokenType.RIGHT: 'RIGHT'>, 'RLIKE': <TokenType.RLIKE: 'RLIKE'>, 'ROLLBACK': <TokenType.ROLLBACK: 'ROLLBACK'>, 'ROLLUP': <TokenType.ROLLUP: 'ROLLUP'>, 'ROW': <TokenType.ROW: 'ROW'>, 'ROWS': <TokenType.ROWS: 'ROWS'>, 'SCHEMA': <TokenType.SCHEMA: 'SCHEMA'>, 'SELECT': <TokenType.SELECT: 'SELECT'>, 'SEMI': <TokenType.SEMI: 'SEMI'>, 'SET': <TokenType.SET: 'SET'>, 'SETTINGS': <TokenType.SETTINGS: 'SETTINGS'>, 'SHOW': <TokenType.SHOW: 'SHOW'>, 'SIMILAR TO': <TokenType.SIMILAR_TO: 'SIMILAR_TO'>, 'SOME': <TokenType.SOME: 'SOME'>, 'SORT BY': <TokenType.SORT_BY: 'SORT_BY'>, 'START WITH': <TokenType.START_WITH: 'START_WITH'>, 'TABLE': <TokenType.TABLE: 'TABLE'>, 'TABLESAMPLE': <TokenType.TABLE_SAMPLE: 'TABLE_SAMPLE'>, 'TEMP': <TokenType.TEMPORARY: 'TEMPORARY'>, 'TEMPORARY': <TokenType.TEMPORARY: 'TEMPORARY'>, 'THEN': <TokenType.THEN: 'THEN'>, 'TRUE': <TokenType.TRUE: 'TRUE'>, 'TRUNCATE': <TokenType.TRUNCATE: 'TRUNCATE'>, 'UNION': <TokenType.UNION: 'UNION'>, 'UNKNOWN': <TokenType.UNKNOWN: 'UNKNOWN'>, 'UNNEST': <TokenType.UNNEST: 'UNNEST'>, 'UNPIVOT': <TokenType.UNPIVOT: 'UNPIVOT'>, 'UPDATE': <TokenType.UPDATE: 'UPDATE'>, 'USE': <TokenType.USE: 'USE'>, 'USING': <TokenType.USING: 'USING'>, 'UUID': <TokenType.UUID: 'UUID'>, 'VALUES': <TokenType.VALUES: 'VALUES'>, 'VIEW': <TokenType.VIEW: 'VIEW'>, 'VOLATILE': <TokenType.VOLATILE: 'VOLATILE'>, 'WHEN': <TokenType.WHEN: 'WHEN'>, 'WHERE': <TokenType.WHERE: 'WHERE'>, 'WINDOW': <TokenType.WINDOW: 'WINDOW'>, 'WITH': <TokenType.WITH: 'WITH'>, 'APPLY': <TokenType.APPLY: 'APPLY'>, 'ARRAY': <TokenType.ARRAY: 'ARRAY'>, 'BIT': <TokenType.BIT: 'BIT'>, 'BOOL': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BOOLEAN': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BYTE': <TokenType.TINYINT: 'TINYINT'>, 'MEDIUMINT': <TokenType.MEDIUMINT: 'MEDIUMINT'>, 'INT1': <TokenType.TINYINT: 'TINYINT'>, 'TINYINT': <TokenType.TINYINT: 'TINYINT'>, 'INT16': <TokenType.SMALLINT: 'SMALLINT'>, 'SHORT': <TokenType.SMALLINT: 'SMALLINT'>, 'SMALLINT': <TokenType.SMALLINT: 'SMALLINT'>, 'INT128': <TokenType.INT128: 'INT128'>, 'HUGEINT': <TokenType.INT128: 'INT128'>, 'INT2': <TokenType.SMALLINT: 'SMALLINT'>, 'INTEGER': <TokenType.INT: 'INT'>, 'INT': <TokenType.INT: 'INT'>, 'INT4': <TokenType.INT: 'INT'>, 'INT32': <TokenType.INT: 'INT'>, 'INT64': <TokenType.BIGINT: 'BIGINT'>, 'LONG': <TokenType.BIGINT: 'BIGINT'>, 'BIGINT': <TokenType.BIGINT: 'BIGINT'>, 'INT8': <TokenType.BIGINT: 'BIGINT'>, 'UINT': <TokenType.UINT: 'UINT'>, 'DEC': <TokenType.DECIMAL: 'DECIMAL'>, 'DECIMAL': <TokenType.DECIMAL: 'DECIMAL'>, 'BIGDECIMAL': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'BIGNUMERIC': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'MAP': <TokenType.MAP: 'MAP'>, 'NULLABLE': <TokenType.NULLABLE: 'NULLABLE'>, 'NUMBER': <TokenType.DECIMAL: 'DECIMAL'>, 'NUMERIC': <TokenType.DECIMAL: 'DECIMAL'>, 'FIXED': <TokenType.DECIMAL: 'DECIMAL'>, 'REAL': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT4': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT8': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE PRECISION': <TokenType.DOUBLE: 'DOUBLE'>, 'JSON': <TokenType.JSON: 'JSON'>, 'CHAR': <TokenType.CHAR: 'CHAR'>, 'CHARACTER': <TokenType.CHAR: 'CHAR'>, 'NCHAR': <TokenType.NCHAR: 'NCHAR'>, 'VARCHAR': <TokenType.VARCHAR: 'VARCHAR'>, 'VARCHAR2': <TokenType.VARCHAR: 'VARCHAR'>, 'NVARCHAR': <TokenType.NVARCHAR: 'NVARCHAR'>, 'NVARCHAR2': <TokenType.NVARCHAR: 'NVARCHAR'>, 'BPCHAR': <TokenType.BPCHAR: 'BPCHAR'>, 'STR': <TokenType.TEXT: 'TEXT'>, 'STRING': <TokenType.TEXT: 'TEXT'>, 'TEXT': <TokenType.TEXT: 'TEXT'>, 'LONGTEXT': <TokenType.LONGTEXT: 'LONGTEXT'>, 'MEDIUMTEXT': <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, 'TINYTEXT': <TokenType.TINYTEXT: 'TINYTEXT'>, 'CLOB': <TokenType.TEXT: 'TEXT'>, 'LONGVARCHAR': <TokenType.TEXT: 'TEXT'>, 'BINARY': <TokenType.BINARY: 'BINARY'>, 'BLOB': <TokenType.VARBINARY: 'VARBINARY'>, 'LONGBLOB': <TokenType.LONGBLOB: 'LONGBLOB'>, 'MEDIUMBLOB': <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, 'TINYBLOB': <TokenType.TINYBLOB: 'TINYBLOB'>, 'BYTEA': <TokenType.VARBINARY: 'VARBINARY'>, 'VARBINARY': <TokenType.VARBINARY: 'VARBINARY'>, 'TIME': <TokenType.TIME: 'TIME'>, 'TIMETZ': <TokenType.TIMETZ: 'TIMETZ'>, 'TIMESTAMP': <TokenType.TIMESTAMP: 'TIMESTAMP'>, 'TIMESTAMPTZ': <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, 'TIMESTAMPLTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMP_LTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMPNTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'TIMESTAMP_NTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'DATE': <TokenType.DATE: 'DATE'>, 'DATETIME': <TokenType.DATETIME: 'DATETIME'>, 'INT4RANGE': <TokenType.INT4RANGE: 'INT4RANGE'>, 'INT4MULTIRANGE': <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, 'INT8RANGE': <TokenType.INT8RANGE: 'INT8RANGE'>, 'INT8MULTIRANGE': <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, 'NUMRANGE': <TokenType.NUMRANGE: 'NUMRANGE'>, 'NUMMULTIRANGE': <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, 'TSRANGE': <TokenType.TSRANGE: 'TSRANGE'>, 'TSMULTIRANGE': <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, 'TSTZRANGE': <TokenType.TSTZRANGE: 'TSTZRANGE'>, 'TSTZMULTIRANGE': <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, 'DATERANGE': <TokenType.DATERANGE: 'DATERANGE'>, 'DATEMULTIRANGE': <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, 'UNIQUE': <TokenType.UNIQUE: 'UNIQUE'>, 'STRUCT': <TokenType.STRUCT: 'STRUCT'>, 'SEQUENCE': <TokenType.SEQUENCE: 'SEQUENCE'>, 'VARIANT': <TokenType.VARIANT: 'VARIANT'>, 'ALTER': <TokenType.ALTER: 'ALTER'>, 'ANALYZE': <TokenType.COMMAND: 'COMMAND'>, 'CALL': <TokenType.COMMAND: 'COMMAND'>, 'COMMENT': <TokenType.COMMENT: 'COMMENT'>, 'EXPLAIN': <TokenType.COMMAND: 'COMMAND'>, 'GRANT': <TokenType.COMMAND: 'COMMAND'>, 'OPTIMIZE': <TokenType.COMMAND: 'COMMAND'>, 'PREPARE': <TokenType.COMMAND: 'COMMAND'>, 'VACUUM': <TokenType.COMMAND: 'COMMAND'>, 'USER-DEFINED': <TokenType.USERDEFINED: 'USERDEFINED'>, 'FOR VERSION': <TokenType.VERSION_SNAPSHOT: 'VERSION_SNAPSHOT'>, 'FOR TIMESTAMP': <TokenType.TIMESTAMP_SNAPSHOT: 'TIMESTAMP_SNAPSHOT'>, '~~': <TokenType.LIKE: 'LIKE'>, '~~*': <TokenType.ILIKE: 'ILIKE'>, '~*': <TokenType.IRLIKE: 'IRLIKE'>, '~': <TokenType.RLIKE: 'RLIKE'>, '@@': <TokenType.DAT: 'DAT'>, '@>': <TokenType.AT_GT: 'AT_GT'>, '<@': <TokenType.LT_AT: 'LT_AT'>, '|/': <TokenType.PIPE_SLASH: 'PIPE_SLASH'>, '||/': <TokenType.DPIPE_SLASH: 'DPIPE_SLASH'>, 'BEGIN TRANSACTION': <TokenType.BEGIN: 'BEGIN'>, 'BIGSERIAL': <TokenType.BIGSERIAL: 'BIGSERIAL'>, 'CHARACTER VARYING': <TokenType.VARCHAR: 'VARCHAR'>, 'CONSTRAINT TRIGGER': <TokenType.COMMAND: 'COMMAND'>, 'CSTRING': <TokenType.PSEUDO_TYPE: 'PSEUDO_TYPE'>, 'DECLARE': <TokenType.COMMAND: 'COMMAND'>, 'DO': <TokenType.COMMAND: 'COMMAND'>, 'EXEC': <TokenType.COMMAND: 'COMMAND'>, 'HSTORE': <TokenType.HSTORE: 'HSTORE'>, 'JSONB': <TokenType.JSONB: 'JSONB'>, 'MONEY': <TokenType.MONEY: 'MONEY'>, 'NAME': <TokenType.NAME: 'NAME'>, 'OID': <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, 'ONLY': <TokenType.ONLY: 'ONLY'>, 'OPERATOR': <TokenType.OPERATOR: 'OPERATOR'>, 'REFRESH': <TokenType.COMMAND: 'COMMAND'>, 'REINDEX': <TokenType.COMMAND: 'COMMAND'>, 'RESET': <TokenType.COMMAND: 'COMMAND'>, 'REVOKE': <TokenType.COMMAND: 'COMMAND'>, 'SERIAL': <TokenType.SERIAL: 'SERIAL'>, 'SMALLSERIAL': <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, 'REGCLASS': <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, 'REGCOLLATION': <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, 'REGCONFIG': <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, 'REGDICTIONARY': <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, 'REGNAMESPACE': <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, 'REGOPER': <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, 'REGOPERATOR': <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, 'REGPROC': <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, 'REGPROCEDURE': <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, 'REGROLE': <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, 'REGTYPE': <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>}"}, "sqlglot.dialects.postgres.Postgres.Tokenizer.SINGLE_TOKENS": {"fullname": "sqlglot.dialects.postgres.Postgres.Tokenizer.SINGLE_TOKENS", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Tokenizer.SINGLE_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'(': <TokenType.L_PAREN: 'L_PAREN'>, ')': <TokenType.R_PAREN: 'R_PAREN'>, '[': <TokenType.L_BRACKET: 'L_BRACKET'>, ']': <TokenType.R_BRACKET: 'R_BRACKET'>, '{': <TokenType.L_BRACE: 'L_BRACE'>, '}': <TokenType.R_BRACE: 'R_BRACE'>, '&': <TokenType.AMP: 'AMP'>, '^': <TokenType.CARET: 'CARET'>, ':': <TokenType.COLON: 'COLON'>, ',': <TokenType.COMMA: 'COMMA'>, '.': <TokenType.DOT: 'DOT'>, '-': <TokenType.DASH: 'DASH'>, '=': <TokenType.EQ: 'EQ'>, '>': <TokenType.GT: 'GT'>, '<': <TokenType.LT: 'LT'>, '%': <TokenType.MOD: 'MOD'>, '!': <TokenType.NOT: 'NOT'>, '|': <TokenType.PIPE: 'PIPE'>, '+': <TokenType.PLUS: 'PLUS'>, ';': <TokenType.SEMICOLON: 'SEMICOLON'>, '/': <TokenType.SLASH: 'SLASH'>, '\\\\': <TokenType.BACKSLASH: 'BACKSLASH'>, '*': <TokenType.STAR: 'STAR'>, '~': <TokenType.TILDA: 'TILDA'>, '?': <TokenType.PLACEHOLDER: 'PLACEHOLDER'>, '@': <TokenType.PARAMETER: 'PARAMETER'>, '#': <TokenType.HASH: 'HASH'>, "'": <TokenType.UNKNOWN: 'UNKNOWN'>, '`': <TokenType.UNKNOWN: 'UNKNOWN'>, '"': <TokenType.UNKNOWN: 'UNKNOWN'>, '$': <TokenType.HEREDOC_STRING: 'HEREDOC_STRING'>}"}, "sqlglot.dialects.postgres.Postgres.Tokenizer.VAR_SINGLE_TOKENS": {"fullname": "sqlglot.dialects.postgres.Postgres.Tokenizer.VAR_SINGLE_TOKENS", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Tokenizer.VAR_SINGLE_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'$'}"}, "sqlglot.dialects.postgres.Postgres.Parser": {"fullname": "sqlglot.dialects.postgres.Postgres.Parser", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Parser", "kind": "class", "doc": "<p>Parser consumes a list of tokens produced by the Tokenizer and produces a parsed syntax tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>error_level:</strong> The desired error level.\nDefault: ErrorLevel.IMMEDIATE</li>\n<li><strong>error_message_context:</strong> The amount of context to capture from a query string when displaying\nthe error message (in number of characters).\nDefault: 100</li>\n<li><strong>max_errors:</strong> Maximum number of error messages to include in a raised ParseError.\nThis is only relevant if error_level is ErrorLevel.RAISE.\nDefault: 3</li>\n</ul>\n", "bases": "sqlglot.parser.Parser"}, "sqlglot.dialects.postgres.Postgres.Parser.PROPERTY_PARSERS": {"fullname": "sqlglot.dialects.postgres.Postgres.Parser.PROPERTY_PARSERS", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Parser.PROPERTY_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ALLOWED_VALUES': <function Parser.<lambda>>, 'ALGORITHM': <function Parser.<lambda>>, 'AUTO': <function Parser.<lambda>>, 'AUTO_INCREMENT': <function Parser.<lambda>>, 'BACKUP': <function Parser.<lambda>>, 'BLOCKCOMPRESSION': <function Parser.<lambda>>, 'CHARSET': <function Parser.<lambda>>, 'CHARACTER SET': <function Parser.<lambda>>, 'CHECKSUM': <function Parser.<lambda>>, 'CLUSTER BY': <function Parser.<lambda>>, 'CLUSTERED': <function Parser.<lambda>>, 'COLLATE': <function Parser.<lambda>>, 'COMMENT': <function Parser.<lambda>>, 'CONTAINS': <function Parser.<lambda>>, 'COPY': <function Parser.<lambda>>, 'DATABLOCKSIZE': <function Parser.<lambda>>, 'DATA_DELETION': <function Parser.<lambda>>, 'DEFINER': <function Parser.<lambda>>, 'DETERMINISTIC': <function Parser.<lambda>>, 'DISTKEY': <function Parser.<lambda>>, 'DISTSTYLE': <function Parser.<lambda>>, 'ENGINE': <function Parser.<lambda>>, 'EXECUTE': <function Parser.<lambda>>, 'EXTERNAL': <function Parser.<lambda>>, 'FALLBACK': <function Parser.<lambda>>, 'FORMAT': <function Parser.<lambda>>, 'FREESPACE': <function Parser.<lambda>>, 'GLOBAL': <function Parser.<lambda>>, 'HEAP': <function Parser.<lambda>>, 'ICEBERG': <function Parser.<lambda>>, 'IMMUTABLE': <function Parser.<lambda>>, 'INHERITS': <function Parser.<lambda>>, 'JOURNAL': <function Parser.<lambda>>, 'LANGUAGE': <function Parser.<lambda>>, 'LAYOUT': <function Parser.<lambda>>, 'LIFETIME': <function Parser.<lambda>>, 'LIKE': <function Parser.<lambda>>, 'LOCATION': <function Parser.<lambda>>, 'LOCK': <function Parser.<lambda>>, 'LOCKING': <function Parser.<lambda>>, 'LOG': <function Parser.<lambda>>, 'MATERIALIZED': <function Parser.<lambda>>, 'MERGEBLOCKRATIO': <function Parser.<lambda>>, 'MODIFIES': <function Parser.<lambda>>, 'MULTISET': <function Parser.<lambda>>, 'NO': <function Parser.<lambda>>, 'ON': <function Parser.<lambda>>, 'ORDER BY': <function Parser.<lambda>>, 'OUTPUT': <function Parser.<lambda>>, 'PARTITION': <function Parser.<lambda>>, 'PARTITION BY': <function Parser.<lambda>>, 'PARTITIONED BY': <function Parser.<lambda>>, 'PARTITIONED_BY': <function Parser.<lambda>>, 'PRIMARY KEY': <function Parser.<lambda>>, 'RANGE': <function Parser.<lambda>>, 'READS': <function Parser.<lambda>>, 'REMOTE': <function Parser.<lambda>>, 'RETURNS': <function Parser.<lambda>>, 'STRICT': <function Parser.<lambda>>, 'ROW': <function Parser.<lambda>>, 'ROW_FORMAT': <function Parser.<lambda>>, 'SAMPLE': <function Parser.<lambda>>, 'SET': <function Postgres.Parser.<lambda>>, 'SETTINGS': <function Parser.<lambda>>, 'SHARING': <function Parser.<lambda>>, 'SORTKEY': <function Parser.<lambda>>, 'SOURCE': <function Parser.<lambda>>, 'STABLE': <function Parser.<lambda>>, 'STORED': <function Parser.<lambda>>, 'SYSTEM_VERSIONING': <function Parser.<lambda>>, 'TBLPROPERTIES': <function Parser.<lambda>>, 'TEMP': <function Parser.<lambda>>, 'TEMPORARY': <function Parser.<lambda>>, 'TO': <function Parser.<lambda>>, 'TRANSIENT': <function Parser.<lambda>>, 'TRANSFORM': <function Parser.<lambda>>, 'TTL': <function Parser.<lambda>>, 'USING': <function Parser.<lambda>>, 'UNLOGGED': <function Parser.<lambda>>, 'VOLATILE': <function Parser.<lambda>>, 'WITH': <function Parser.<lambda>>}"}, "sqlglot.dialects.postgres.Postgres.Parser.FUNCTIONS": {"fullname": "sqlglot.dialects.postgres.Postgres.Parser.FUNCTIONS", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Parser.FUNCTIONS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ABS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Abs'>>, 'ADD_MONTHS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AddMonths'>>, 'ANONYMOUS_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnonymousAggFunc'>>, 'ANY_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnyValue'>>, 'APPROX_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_COUNT_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'APPROX_TOP_K': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxTopK'>>, 'ARG_MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARGMAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'MAX_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARG_MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARGMIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'MIN_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Array'>>, 'ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAgg'>>, 'ARRAY_ALL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAll'>>, 'ARRAY_ANY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAny'>>, 'ARRAY_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CONSTRUCT_COMPACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConstructCompact'>>, 'ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayContains'>>, 'FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_OVERLAPS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayOverlaps'>>, 'ARRAY_SIZE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_SORT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySort'>>, 'ARRAY_SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySum'>>, 'ARRAY_TO_STRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_JOIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_UNION_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUnionAgg'>>, 'ARRAY_UNIQUE_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUniqueAgg'>>, 'AVG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Avg'>>, 'CASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Case'>>, 'CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cast'>>, 'CAST_TO_STR_TYPE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CastToStrType'>>, 'CBRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cbrt'>>, 'CEIL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CEILING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CHR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'COALESCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'IFNULL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'NVL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'COLLATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Collate'>>, 'COMBINED_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedAggFunc'>>, 'COMBINED_PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedParameterizedAgg'>>, 'CONCAT': <function Parser.<lambda>>, 'CONCAT_WS': <function Parser.<lambda>>, 'CONNECT_BY_ROOT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ConnectByRoot'>>, 'CONVERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Convert'>>, 'CORR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Corr'>>, 'COUNT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Count'>>, 'COUNT_IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COUNTIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COVAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarPop'>>, 'COVAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarSamp'>>, 'CURRENT_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDate'>>, 'CURRENT_DATETIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDatetime'>>, 'CURRENT_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTime'>>, 'CURRENT_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTimestamp'>>, 'CURRENT_USER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentUser'>>, 'DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Date'>>, 'DATE_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateAdd'>>, 'DATEDIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateDiff'>>, 'DATE_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateDiff'>>, 'DATE_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATE_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateStrToDate'>>, 'DATE_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateSub'>>, 'DATE_TO_DATE_STR': <function Parser.<lambda>>, 'DATE_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateToDi'>>, 'DATE_TRUNC': <function build_timestamp_trunc>, 'DATETIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeAdd'>>, 'DATETIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeDiff'>>, 'DATETIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeSub'>>, 'DATETIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeTrunc'>>, 'DAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Day'>>, 'DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAYOFMONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAY_OF_WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAYOFWEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAY_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DAYOFYEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DECODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Decode'>>, 'DI_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DiToDate'>>, 'ENCODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Encode'>>, 'EXP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Exp'>>, 'EXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Explode'>>, 'EXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ExplodeOuter'>>, 'EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Extract'>>, 'FIRST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.First'>>, 'FIRST_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FirstValue'>>, 'FLATTEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Flatten'>>, 'FLOOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Floor'>>, 'FROM_BASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase'>>, 'FROM_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase64'>>, 'GENERATE_DATE_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GenerateDateArray'>>, 'GENERATE_SERIES': <function _build_generate_series>, 'GREATEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Greatest'>>, 'GROUP_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GroupConcat'>>, 'HEX': <function build_hex>, 'HLL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Hll'>>, 'IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'IIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'INITCAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Initcap'>>, 'IS_INF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'ISINF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'IS_NAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'ISNAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'J_S_O_N_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArray'>>, 'J_S_O_N_ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArrayAgg'>>, 'JSON_ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArrayContains'>>, 'JSONB_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONBExtract'>>, 'JSONB_EXTRACT_SCALAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONBExtractScalar'>>, 'JSON_EXTRACT': <function build_extract_json_with_path.<locals>._builder>, 'JSON_EXTRACT_SCALAR': <function build_extract_json_with_path.<locals>._builder>, 'JSON_FORMAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONFormat'>>, 'J_S_O_N_OBJECT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONObject'>>, 'J_S_O_N_OBJECT_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONObjectAgg'>>, 'J_S_O_N_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONTable'>>, 'LAG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lag'>>, 'LAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Last'>>, 'LAST_DAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastDay'>>, 'LAST_DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastDay'>>, 'LAST_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastValue'>>, 'LEAD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lead'>>, 'LEAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Least'>>, 'LEFT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Left'>>, 'LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Length'>>, 'LEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Length'>>, 'LEVENSHTEIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Levenshtein'>>, 'LN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ln'>>, 'LOG': <function build_logarithm>, 'LOGICAL_AND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'BOOL_AND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'BOOLAND_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'LOGICAL_OR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'BOOL_OR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'BOOLOR_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'LOWER': <function build_lower>, 'LCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lower'>>, 'LOWER_HEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LowerHex'>>, 'MD5': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MD5'>>, 'MD5_DIGEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MD5Digest'>>, 'MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Map'>>, 'MAP_FROM_ENTRIES': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MapFromEntries'>>, 'MATCH_AGAINST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MatchAgainst'>>, 'MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Max'>>, 'MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Min'>>, 'MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Month'>>, 'MONTHS_BETWEEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MonthsBetween'>>, 'NEXT_VALUE_FOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NextValueFor'>>, 'NTH_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NthValue'>>, 'NULLIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Nullif'>>, 'NUMBER_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NumberToStr'>>, 'NVL2': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Nvl2'>>, 'OPEN_J_S_O_N': <bound method Func.from_arg_list of <class 'sqlglot.expressions.OpenJSON'>>, 'PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParameterizedAgg'>>, 'PARSE_JSON': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParseJSON'>>, 'JSON_PARSE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParseJSON'>>, 'PERCENTILE_CONT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PercentileCont'>>, 'PERCENTILE_DISC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PercentileDisc'>>, 'POSEXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Posexplode'>>, 'POSEXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PosexplodeOuter'>>, 'POWER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Pow'>>, 'POW': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Pow'>>, 'PREDICT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Predict'>>, 'QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quantile'>>, 'QUARTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quarter'>>, 'RAND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'RANDOM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'RANDN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Randn'>>, 'RANGE_N': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RangeN'>>, 'READ_CSV': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ReadCSV'>>, 'REDUCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Reduce'>>, 'REGEXP_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpExtract'>>, 'REGEXP_I_LIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpILike'>>, 'REGEXP_LIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpLike'>>, 'REGEXP_REPLACE': <function _build_regexp_replace>, 'REGEXP_SPLIT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpSplit'>>, 'REPEAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Repeat'>>, 'RIGHT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Right'>>, 'ROUND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Round'>>, 'ROW_NUMBER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RowNumber'>>, 'SHA': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA'>>, 'SHA1': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA'>>, 'SHA2': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA2'>>, 'SAFE_DIVIDE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SafeDivide'>>, 'SIGN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sign'>>, 'SIGNUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sign'>>, 'SORT_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SortArray'>>, 'SPLIT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Split'>>, 'SQRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sqrt'>>, 'STANDARD_HASH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StandardHash'>>, 'STAR_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StarMap'>>, 'STARTS_WITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STARTSWITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STDDEV': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stddev'>>, 'STDDEV_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StddevPop'>>, 'STDDEV_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StddevSamp'>>, 'STR_POSITION': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrPosition'>>, 'STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToDate'>>, 'STR_TO_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToMap'>>, 'STR_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToTime'>>, 'STR_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToUnix'>>, 'STRUCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Struct'>>, 'STRUCT_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StructExtract'>>, 'STUFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stuff'>>, 'INSERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stuff'>>, 'SUBSTRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Substring'>>, 'SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sum'>>, 'TIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeAdd'>>, 'TIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeDiff'>>, 'TIME_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'TIMEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'TIME_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToDate'>>, 'TIME_STR_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToTime'>>, 'TIME_STR_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToUnix'>>, 'TIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeSub'>>, 'TIME_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeToStr'>>, 'TIME_TO_TIME_STR': <function Parser.<lambda>>, 'TIME_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeToUnix'>>, 'TIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeTrunc'>>, 'TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Timestamp'>>, 'TIMESTAMP_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampAdd'>>, 'TIMESTAMPDIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampDiff'>>, 'TIMESTAMP_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampDiff'>>, 'TIMESTAMP_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampFromParts'>>, 'TIMESTAMPFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampFromParts'>>, 'TIMESTAMP_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampSub'>>, 'TIMESTAMP_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampTrunc'>>, 'TO_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToArray'>>, 'TO_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToBase64'>>, 'TO_CHAR': <function build_formatted_time.<locals>._builder>, 'TO_DAYS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToDays'>>, 'TO_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToMap'>>, 'TO_NUMBER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToNumber'>>, 'TRANSFORM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Transform'>>, 'TRIM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Trim'>>, 'TRY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Try'>>, 'TRY_CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TryCast'>>, 'TS_OR_DI_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDiToDi'>>, 'TS_OR_DS_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsAdd'>>, 'TS_OR_DS_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsDiff'>>, 'TS_OR_DS_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToDate'>>, 'TS_OR_DS_TO_DATE_STR': <function Parser.<lambda>>, 'TS_OR_DS_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTime'>>, 'TS_OR_DS_TO_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTimestamp'>>, 'UNHEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Unhex'>>, 'UNIX_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixDate'>>, 'UNIX_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToStr'>>, 'UNIX_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTime'>>, 'UNIX_TO_TIME_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTimeStr'>>, 'UPPER': <function build_upper>, 'UCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Upper'>>, 'VAR_MAP': <function build_var_map>, 'VARIANCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'VAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Week'>>, 'WEEK_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.WeekOfYear'>>, 'WEEKOFYEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.WeekOfYear'>>, 'WHEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.When'>>, 'X_M_L_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.XMLTable'>>, 'XOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Xor'>>, 'YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Year'>>, 'GLOB': <function Parser.<lambda>>, 'JSON_EXTRACT_PATH_TEXT': <function build_json_extract_path.<locals>._builder>, 'LIKE': <function build_like>, 'LOG2': <function Parser.<lambda>>, 'LOG10': <function Parser.<lambda>>, 'MOD': <function build_mod>, 'TO_HEX': <function build_hex>, 'JSON_EXTRACT_PATH': <function build_json_extract_path.<locals>._builder>, 'MAKE_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'MAKE_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampFromParts'>>, 'NOW': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTimestamp'>>, 'TO_TIMESTAMP': <function _build_to_timestamp>, 'UNNEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Explode'>>}"}, "sqlglot.dialects.postgres.Postgres.Parser.FUNCTION_PARSERS": {"fullname": "sqlglot.dialects.postgres.Postgres.Parser.FUNCTION_PARSERS", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Parser.FUNCTION_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'CAST': <function Parser.<lambda>>, 'CONVERT': <function Parser.<lambda>>, 'DECODE': <function Parser.<lambda>>, 'EXTRACT': <function Parser.<lambda>>, 'JSON_OBJECT': <function Parser.<lambda>>, 'JSON_OBJECTAGG': <function Parser.<lambda>>, 'JSON_TABLE': <function Parser.<lambda>>, 'MATCH': <function Parser.<lambda>>, 'OPENJSON': <function Parser.<lambda>>, 'POSITION': <function Parser.<lambda>>, 'PREDICT': <function Parser.<lambda>>, 'SAFE_CAST': <function Parser.<lambda>>, 'STRING_AGG': <function Parser.<lambda>>, 'SUBSTRING': <function Parser.<lambda>>, 'TRIM': <function Parser.<lambda>>, 'TRY_CAST': <function Parser.<lambda>>, 'TRY_CONVERT': <function Parser.<lambda>>, 'DATE_PART': <function Postgres.Parser.<lambda>>}"}, "sqlglot.dialects.postgres.Postgres.Parser.BITWISE": {"fullname": "sqlglot.dialects.postgres.Postgres.Parser.BITWISE", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Parser.BITWISE", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.AMP: 'AMP'>: <class 'sqlglot.expressions.BitwiseAnd'>, <TokenType.CARET: 'CARET'>: <class 'sqlglot.expressions.BitwiseXor'>, <TokenType.PIPE: 'PIPE'>: <class 'sqlglot.expressions.BitwiseOr'>, <TokenType.HASH: 'HASH'>: <class 'sqlglot.expressions.BitwiseXor'>}"}, "sqlglot.dialects.postgres.Postgres.Parser.EXPONENT": {"fullname": "sqlglot.dialects.postgres.Postgres.Parser.EXPONENT", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Parser.EXPONENT", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.CARET: 'CARET'>: <class 'sqlglot.expressions.Pow'>}"}, "sqlglot.dialects.postgres.Postgres.Parser.RANGE_PARSERS": {"fullname": "sqlglot.dialects.postgres.Postgres.Parser.RANGE_PARSERS", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Parser.RANGE_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.BETWEEN: 'BETWEEN'>: <function Parser.<lambda>>, <TokenType.GLOB: 'GLOB'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.ILIKE: 'ILIKE'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.IN: 'IN'>: <function Parser.<lambda>>, <TokenType.IRLIKE: 'IRLIKE'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.IS: 'IS'>: <function Parser.<lambda>>, <TokenType.LIKE: 'LIKE'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.OVERLAPS: 'OVERLAPS'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.RLIKE: 'RLIKE'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.SIMILAR_TO: 'SIMILAR_TO'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.FOR: 'FOR'>: <function Parser.<lambda>>, <TokenType.AT_GT: 'AT_GT'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.DAMP: 'DAMP'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.DAT: 'DAT'>: <function Postgres.Parser.<lambda>>, <TokenType.LT_AT: 'LT_AT'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.OPERATOR: 'OPERATOR'>: <function Postgres.Parser.<lambda>>}"}, "sqlglot.dialects.postgres.Postgres.Parser.STATEMENT_PARSERS": {"fullname": "sqlglot.dialects.postgres.Postgres.Parser.STATEMENT_PARSERS", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Parser.STATEMENT_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.ALTER: 'ALTER'>: <function Parser.<lambda>>, <TokenType.BEGIN: 'BEGIN'>: <function Parser.<lambda>>, <TokenType.CACHE: 'CACHE'>: <function Parser.<lambda>>, <TokenType.COMMENT: 'COMMENT'>: <function Parser.<lambda>>, <TokenType.COMMIT: 'COMMIT'>: <function Parser.<lambda>>, <TokenType.COPY: 'COPY'>: <function Parser.<lambda>>, <TokenType.CREATE: 'CREATE'>: <function Parser.<lambda>>, <TokenType.DELETE: 'DELETE'>: <function Parser.<lambda>>, <TokenType.DESC: 'DESC'>: <function Parser.<lambda>>, <TokenType.DESCRIBE: 'DESCRIBE'>: <function Parser.<lambda>>, <TokenType.DROP: 'DROP'>: <function Parser.<lambda>>, <TokenType.INSERT: 'INSERT'>: <function Parser.<lambda>>, <TokenType.KILL: 'KILL'>: <function Parser.<lambda>>, <TokenType.LOAD: 'LOAD'>: <function Parser.<lambda>>, <TokenType.MERGE: 'MERGE'>: <function Parser.<lambda>>, <TokenType.PIVOT: 'PIVOT'>: <function Parser.<lambda>>, <TokenType.PRAGMA: 'PRAGMA'>: <function Parser.<lambda>>, <TokenType.REFRESH: 'REFRESH'>: <function Parser.<lambda>>, <TokenType.ROLLBACK: 'ROLLBACK'>: <function Parser.<lambda>>, <TokenType.SET: 'SET'>: <function Parser.<lambda>>, <TokenType.TRUNCATE: 'TRUNCATE'>: <function Parser.<lambda>>, <TokenType.UNCACHE: 'UNCACHE'>: <function Parser.<lambda>>, <TokenType.UPDATE: 'UPDATE'>: <function Parser.<lambda>>, <TokenType.USE: 'USE'>: <function Parser.<lambda>>, <TokenType.SEMICOLON: 'SEMICOLON'>: <function Parser.<lambda>>, <TokenType.END: 'END'>: <function Postgres.Parser.<lambda>>}"}, "sqlglot.dialects.postgres.Postgres.Parser.JSON_ARROWS_REQUIRE_JSON_TYPE": {"fullname": "sqlglot.dialects.postgres.Postgres.Parser.JSON_ARROWS_REQUIRE_JSON_TYPE", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Parser.JSON_ARROWS_REQUIRE_JSON_TYPE", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.postgres.Postgres.Parser.COLUMN_OPERATORS": {"fullname": "sqlglot.dialects.postgres.Postgres.Parser.COLUMN_OPERATORS", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Parser.COLUMN_OPERATORS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.DOT: 'DOT'>: None, <TokenType.DCOLON: 'DCOLON'>: <function Parser.<lambda>>, <TokenType.ARROW: 'ARROW'>: <function Postgres.Parser.<lambda>>, <TokenType.DARROW: 'DARROW'>: <function Postgres.Parser.<lambda>>, <TokenType.HASH_ARROW: 'HASH_ARROW'>: <function Parser.<lambda>>, <TokenType.DHASH_ARROW: 'DHASH_ARROW'>: <function Parser.<lambda>>, <TokenType.PLACEHOLDER: 'PLACEHOLDER'>: <function Parser.<lambda>>}"}, "sqlglot.dialects.postgres.Postgres.Parser.SHOW_TRIE": {"fullname": "sqlglot.dialects.postgres.Postgres.Parser.SHOW_TRIE", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Parser.SHOW_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.postgres.Postgres.Parser.SET_TRIE": {"fullname": "sqlglot.dialects.postgres.Postgres.Parser.SET_TRIE", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Parser.SET_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'GLOBAL': {0: True}, 'LOCAL': {0: True}, 'SESSION': {0: True}, 'TRANSACTION': {0: True}}"}, "sqlglot.dialects.postgres.Postgres.Generator": {"fullname": "sqlglot.dialects.postgres.Postgres.Generator", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Generator", "kind": "class", "doc": "<p>Generator converts a given syntax tree to the corresponding SQL string.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>pretty:</strong> Whether to format the produced SQL string.\nDefault: False.</li>\n<li><strong>identify:</strong> Determines when an identifier should be quoted. Possible values are:\nFalse (default): Never quote, except in cases where it's mandatory by the dialect.\nTrue or 'always': Always quote.\n'safe': Only quote identifiers that are case insensitive.</li>\n<li><strong>normalize:</strong> Whether to normalize identifiers to lowercase.\nDefault: False.</li>\n<li><strong>pad:</strong> The pad size in a formatted string. For example, this affects the indentation of\na projection in a query, relative to its nesting level.\nDefault: 2.</li>\n<li><strong>indent:</strong> The indentation size in a formatted string. For example, this affects the\nindentation of subqueries and filters under a <code>WHERE</code> clause.\nDefault: 2.</li>\n<li><strong>normalize_functions:</strong> How to normalize function names. Possible values are:\n\"upper\" or True (default): Convert names to uppercase.\n\"lower\": Convert names to lowercase.\nFalse: Disables function name normalization.</li>\n<li><strong>unsupported_level:</strong> Determines the generator's behavior when it encounters unsupported expressions.\nDefault ErrorLevel.WARN.</li>\n<li><strong>max_unsupported:</strong> Maximum number of unsupported messages to include in a raised UnsupportedError.\nThis is only relevant if unsupported_level is ErrorLevel.RAISE.\nDefault: 3</li>\n<li><strong>leading_comma:</strong> Whether the comma is leading or trailing in select expressions.\nThis is only relevant when generating in pretty mode.\nDefault: False</li>\n<li><strong>max_text_width:</strong> The max number of characters in a segment before creating new lines in pretty mode.\nThe default is on the smaller end because the length only represents a segment and not the true\nline length.\nDefault: 80</li>\n<li><strong>comments:</strong> Whether to preserve comments in the output SQL code.\nDefault: True</li>\n</ul>\n", "bases": "sqlglot.generator.Generator"}, "sqlglot.dialects.postgres.Postgres.Generator.SINGLE_STRING_INTERVAL": {"fullname": "sqlglot.dialects.postgres.Postgres.Generator.SINGLE_STRING_INTERVAL", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Generator.SINGLE_STRING_INTERVAL", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.postgres.Postgres.Generator.RENAME_TABLE_WITH_DB": {"fullname": "sqlglot.dialects.postgres.Postgres.Generator.RENAME_TABLE_WITH_DB", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Generator.RENAME_TABLE_WITH_DB", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.postgres.Postgres.Generator.LOCKING_READS_SUPPORTED": {"fullname": "sqlglot.dialects.postgres.Postgres.Generator.LOCKING_READS_SUPPORTED", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Generator.LOCKING_READS_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.postgres.Postgres.Generator.JOIN_HINTS": {"fullname": "sqlglot.dialects.postgres.Postgres.Generator.JOIN_HINTS", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Generator.JOIN_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.postgres.Postgres.Generator.TABLE_HINTS": {"fullname": "sqlglot.dialects.postgres.Postgres.Generator.TABLE_HINTS", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Generator.TABLE_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.postgres.Postgres.Generator.QUERY_HINTS": {"fullname": "sqlglot.dialects.postgres.Postgres.Generator.QUERY_HINTS", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Generator.QUERY_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.postgres.Postgres.Generator.NVL2_SUPPORTED": {"fullname": "sqlglot.dialects.postgres.Postgres.Generator.NVL2_SUPPORTED", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Generator.NVL2_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.postgres.Postgres.Generator.PARAMETER_TOKEN": {"fullname": "sqlglot.dialects.postgres.Postgres.Generator.PARAMETER_TOKEN", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Generator.PARAMETER_TOKEN", "kind": "variable", "doc": "<p></p>\n", "default_value": "'$'"}, "sqlglot.dialects.postgres.Postgres.Generator.TABLESAMPLE_SIZE_IS_ROWS": {"fullname": "sqlglot.dialects.postgres.Postgres.Generator.TABLESAMPLE_SIZE_IS_ROWS", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Generator.TABLESAMPLE_SIZE_IS_ROWS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.postgres.Postgres.Generator.TABLESAMPLE_SEED_KEYWORD": {"fullname": "sqlglot.dialects.postgres.Postgres.Generator.TABLESAMPLE_SEED_KEYWORD", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Generator.TABLESAMPLE_SEED_KEYWORD", "kind": "variable", "doc": "<p></p>\n", "default_value": "'REPEATABLE'"}, "sqlglot.dialects.postgres.Postgres.Generator.SUPPORTS_SELECT_INTO": {"fullname": "sqlglot.dialects.postgres.Postgres.Generator.SUPPORTS_SELECT_INTO", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Generator.SUPPORTS_SELECT_INTO", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.postgres.Postgres.Generator.JSON_TYPE_REQUIRED_FOR_EXTRACTION": {"fullname": "sqlglot.dialects.postgres.Postgres.Generator.JSON_TYPE_REQUIRED_FOR_EXTRACTION", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Generator.JSON_TYPE_REQUIRED_FOR_EXTRACTION", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.postgres.Postgres.Generator.SUPPORTS_UNLOGGED_TABLES": {"fullname": "sqlglot.dialects.postgres.Postgres.Generator.SUPPORTS_UNLOGGED_TABLES", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Generator.SUPPORTS_UNLOGGED_TABLES", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.postgres.Postgres.Generator.LIKE_PROPERTY_INSIDE_SCHEMA": {"fullname": "sqlglot.dialects.postgres.Postgres.Generator.LIKE_PROPERTY_INSIDE_SCHEMA", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Generator.LIKE_PROPERTY_INSIDE_SCHEMA", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.postgres.Postgres.Generator.MULTI_ARG_DISTINCT": {"fullname": "sqlglot.dialects.postgres.Postgres.Generator.MULTI_ARG_DISTINCT", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Generator.MULTI_ARG_DISTINCT", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, 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"kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">SchemaCommentProperty</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.postgres.Postgres.Generator.commentcolumnconstraint_sql": {"fullname": "sqlglot.dialects.postgres.Postgres.Generator.commentcolumnconstraint_sql", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Generator.commentcolumnconstraint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">CommentColumnConstraint</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.postgres.Postgres.Generator.unnest_sql": {"fullname": "sqlglot.dialects.postgres.Postgres.Generator.unnest_sql", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Generator.unnest_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Unnest</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.postgres.Postgres.Generator.bracket_sql": {"fullname": "sqlglot.dialects.postgres.Postgres.Generator.bracket_sql", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Generator.bracket_sql", "kind": "function", "doc": "<p>Forms like ARRAY[1, 2, 3][3] aren't allowed; we need to wrap the ARRAY.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Bracket</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.postgres.Postgres.Generator.matchagainst_sql": {"fullname": "sqlglot.dialects.postgres.Postgres.Generator.matchagainst_sql", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Generator.matchagainst_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">MatchAgainst</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.postgres.Postgres.Generator.alterset_sql": {"fullname": "sqlglot.dialects.postgres.Postgres.Generator.alterset_sql", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Generator.alterset_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">AlterSet</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.postgres.Postgres.Generator.SELECT_KINDS": {"fullname": "sqlglot.dialects.postgres.Postgres.Generator.SELECT_KINDS", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Generator.SELECT_KINDS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Tuple[str, ...]", "default_value": "()"}, "sqlglot.dialects.postgres.Postgres.Generator.TRY_SUPPORTED": {"fullname": "sqlglot.dialects.postgres.Postgres.Generator.TRY_SUPPORTED", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Generator.TRY_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.postgres.Postgres.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS": {"fullname": "sqlglot.dialects.postgres.Postgres.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'qualify': <function Generator.<lambda>>, 'windows': <function Generator.<lambda>>}"}, "sqlglot.dialects.postgres.Postgres.tokenizer_class": {"fullname": "sqlglot.dialects.postgres.Postgres.tokenizer_class", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.tokenizer_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.postgres.Postgres.Tokenizer'>"}, "sqlglot.dialects.postgres.Postgres.parser_class": {"fullname": "sqlglot.dialects.postgres.Postgres.parser_class", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.parser_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.postgres.Postgres.Parser'>"}, "sqlglot.dialects.postgres.Postgres.generator_class": {"fullname": "sqlglot.dialects.postgres.Postgres.generator_class", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.generator_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.postgres.Postgres.Generator'>"}, "sqlglot.dialects.postgres.Postgres.TIME_TRIE": {"fullname": "sqlglot.dialects.postgres.Postgres.TIME_TRIE", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'A': {'M': {0: True}}, 'P': {'M': {0: True}}, 'D': {0: True, 'D': {0: True, 'D': {0: True}}}, 'F': {'M': {'D': {'D': {0: True, 'D': {0: True}}}, 'H': {'H': {'1': {'2': {0: True}}, '2': {'4': {0: True}}}}, 'M': {'I': {0: True}, 'M': {0: True}}, 'S': {'S': {0: True}}}}, 'H': {'H': {'1': {'2': {0: True}}, '2': {'4': {0: True}}}}, 'M': {'I': {0: True}, 'M': {0: True}}, 'O': {'F': {0: True}}, 'S': {'S': {0: True}}, 'T': {'M': {'D': {'a': {'y': {0: True}}, 'y': {0: True}}, 'M': {'o': {'n': {0: True, 't': {'h': {0: True}}}}}}, 'Z': {0: True}}, 'U': {'S': {0: True}}, 'W': {'W': {0: True}}, 'Y': {'Y': {0: True, 'Y': {'Y': {0: True}}}}}"}, "sqlglot.dialects.postgres.Postgres.FORMAT_TRIE": {"fullname": "sqlglot.dialects.postgres.Postgres.FORMAT_TRIE", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.FORMAT_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'A': {'M': {0: True}}, 'P': {'M': {0: True}}, 'D': {0: True, 'D': {0: True, 'D': {0: True}}}, 'F': {'M': {'D': {'D': {0: True, 'D': {0: True}}}, 'H': {'H': {'1': {'2': {0: True}}, '2': {'4': {0: True}}}}, 'M': {'I': {0: True}, 'M': {0: True}}, 'S': {'S': {0: True}}}}, 'H': {'H': {'1': {'2': {0: True}}, '2': {'4': {0: True}}}}, 'M': {'I': {0: True}, 'M': {0: True}}, 'O': {'F': {0: True}}, 'S': {'S': {0: True}}, 'T': {'M': {'D': {'a': {'y': {0: True}}, 'y': {0: True}}, 'M': {'o': {'n': {0: True, 't': {'h': {0: True}}}}}}, 'Z': {0: True}}, 'U': {'S': {0: True}}, 'W': {'W': {0: True}}, 'Y': {'Y': {0: True, 'Y': {'Y': {0: True}}}}}"}, "sqlglot.dialects.postgres.Postgres.INVERSE_TIME_MAPPING": {"fullname": "sqlglot.dialects.postgres.Postgres.INVERSE_TIME_MAPPING", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.INVERSE_TIME_MAPPING", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'%p': 'PM', '%u': 'D', '%d': 'DD', '%j': 'DDD', '%-d': 'FMDD', '%-j': 'FMDDD', '%-I': 'FMHH12', '%-H': 'FMHH24', '%-M': 'FMMI', '%-m': 'FMMM', '%-S': 'FMSS', '%I': 'HH12', '%H': 'HH24', '%M': 'MI', '%m': 'MM', '%z': 'OF', '%S': 'SS', '%A': 'TMDay', '%a': 'TMDy', '%b': 'TMMon', '%B': 'TMMonth', '%Z': 'TZ', '%f': 'US', '%U': 'WW', '%y': 'YY', '%Y': 'YYYY'}"}, "sqlglot.dialects.postgres.Postgres.INVERSE_TIME_TRIE": {"fullname": "sqlglot.dialects.postgres.Postgres.INVERSE_TIME_TRIE", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.INVERSE_TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'%': {'p': {0: True}, 'u': {0: True}, 'd': {0: True}, 'j': {0: True}, '-': {'d': {0: True}, 'j': {0: True}, 'I': {0: True}, 'H': {0: True}, 'M': {0: True}, 'm': {0: True}, 'S': {0: True}}, 'I': {0: True}, 'H': {0: True}, 'M': {0: True}, 'm': {0: True}, 'z': {0: True}, 'S': {0: True}, 'A': {0: True}, 'a': {0: True}, 'b': {0: True}, 'B': {0: True}, 'Z': {0: True}, 'f': {0: True}, 'U': {0: True}, 'y': {0: True}, 'Y': {0: True}}}"}, "sqlglot.dialects.postgres.Postgres.ESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.postgres.Postgres.ESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.ESCAPED_SEQUENCES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{}"}, "sqlglot.dialects.postgres.Postgres.QUOTE_START": {"fullname": "sqlglot.dialects.postgres.Postgres.QUOTE_START", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.QUOTE_START", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.postgres.Postgres.QUOTE_END": {"fullname": "sqlglot.dialects.postgres.Postgres.QUOTE_END", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.QUOTE_END", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.postgres.Postgres.IDENTIFIER_START": {"fullname": "sqlglot.dialects.postgres.Postgres.IDENTIFIER_START", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.IDENTIFIER_START", "kind": "variable", "doc": "<p></p>\n", "default_value": "'"'"}, "sqlglot.dialects.postgres.Postgres.IDENTIFIER_END": {"fullname": "sqlglot.dialects.postgres.Postgres.IDENTIFIER_END", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.IDENTIFIER_END", "kind": "variable", "doc": "<p></p>\n", "default_value": "'"'"}, "sqlglot.dialects.postgres.Postgres.BIT_START": {"fullname": "sqlglot.dialects.postgres.Postgres.BIT_START", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.BIT_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""b'""}, "sqlglot.dialects.postgres.Postgres.BIT_END": {"fullname": "sqlglot.dialects.postgres.Postgres.BIT_END", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.BIT_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""'""}, "sqlglot.dialects.postgres.Postgres.HEX_START": {"fullname": "sqlglot.dialects.postgres.Postgres.HEX_START", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.HEX_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""x'""}, "sqlglot.dialects.postgres.Postgres.HEX_END": {"fullname": "sqlglot.dialects.postgres.Postgres.HEX_END", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.HEX_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""'""}, "sqlglot.dialects.postgres.Postgres.BYTE_START": {"fullname": "sqlglot.dialects.postgres.Postgres.BYTE_START", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.BYTE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""e'""}, "sqlglot.dialects.postgres.Postgres.BYTE_END": {"fullname": "sqlglot.dialects.postgres.Postgres.BYTE_END", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.BYTE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""'""}, "sqlglot.dialects.postgres.Postgres.UNICODE_START": {"fullname": "sqlglot.dialects.postgres.Postgres.UNICODE_START", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.UNICODE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.postgres.Postgres.UNICODE_END": {"fullname": "sqlglot.dialects.postgres.Postgres.UNICODE_END", "modulename": "sqlglot.dialects.postgres", "qualname": "Postgres.UNICODE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.presto": {"fullname": "sqlglot.dialects.presto", "modulename": "sqlglot.dialects.presto", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.dialects.presto.Presto": {"fullname": "sqlglot.dialects.presto.Presto", "modulename": "sqlglot.dialects.presto", "qualname": "Presto", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.dialect.Dialect"}, "sqlglot.dialects.presto.Presto.INDEX_OFFSET": {"fullname": "sqlglot.dialects.presto.Presto.INDEX_OFFSET", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.INDEX_OFFSET", "kind": "variable", "doc": "<p>The base index offset for arrays.</p>\n", "default_value": "1"}, "sqlglot.dialects.presto.Presto.NULL_ORDERING": {"fullname": "sqlglot.dialects.presto.Presto.NULL_ORDERING", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.NULL_ORDERING", "kind": "variable", "doc": "<p>Default <code>NULL</code> ordering method to use if not explicitly set.\nPossible values: <code>\"nulls_are_small\"</code>, <code>\"nulls_are_large\"</code>, <code>\"nulls_are_last\"</code></p>\n", "default_value": "'nulls_are_last'"}, "sqlglot.dialects.presto.Presto.TIME_FORMAT": {"fullname": "sqlglot.dialects.presto.Presto.TIME_FORMAT", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.TIME_FORMAT", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'%Y-%m-%d %T'""}, "sqlglot.dialects.presto.Presto.TIME_MAPPING": {"fullname": "sqlglot.dialects.presto.Presto.TIME_MAPPING", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.TIME_MAPPING", "kind": "variable", "doc": "<p>Associates this dialect's time formats with their equivalent Python <code>strftime</code> formats.</p>\n", "default_value": "{'%M': '%B', '%c': '%-m', '%e': '%-d', '%h': '%I', '%i': '%M', '%s': '%S', '%u': '%W', '%k': '%-H', '%l': '%-I', '%T': '%H:%M:%S', '%W': '%a'}"}, "sqlglot.dialects.presto.Presto.STRICT_STRING_CONCAT": {"fullname": "sqlglot.dialects.presto.Presto.STRICT_STRING_CONCAT", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.STRICT_STRING_CONCAT", "kind": "variable", "doc": "<p>Whether <code>CONCAT</code>'s arguments must be strings.</p>\n", "default_value": "True"}, "sqlglot.dialects.presto.Presto.SUPPORTS_SEMI_ANTI_JOIN": {"fullname": "sqlglot.dialects.presto.Presto.SUPPORTS_SEMI_ANTI_JOIN", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.SUPPORTS_SEMI_ANTI_JOIN", "kind": "variable", "doc": "<p>Whether <code>SEMI</code> or <code>ANTI</code> joins are supported.</p>\n", "default_value": "False"}, "sqlglot.dialects.presto.Presto.TYPED_DIVISION": {"fullname": "sqlglot.dialects.presto.Presto.TYPED_DIVISION", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.TYPED_DIVISION", "kind": "variable", "doc": "<p>Whether the behavior of <code>a / b</code> depends on the types of <code>a</code> and <code>b</code>.\nFalse means <code>a / b</code> is always float division.\nTrue means <code>a / b</code> is integer division if both <code>a</code> and <code>b</code> are integers.</p>\n", "default_value": "True"}, "sqlglot.dialects.presto.Presto.TABLESAMPLE_SIZE_IS_PERCENT": {"fullname": "sqlglot.dialects.presto.Presto.TABLESAMPLE_SIZE_IS_PERCENT", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.TABLESAMPLE_SIZE_IS_PERCENT", "kind": "variable", "doc": "<p>Whether a size in the table sample clause represents percentage.</p>\n", "default_value": "True"}, "sqlglot.dialects.presto.Presto.LOG_BASE_FIRST": {"fullname": "sqlglot.dialects.presto.Presto.LOG_BASE_FIRST", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.LOG_BASE_FIRST", "kind": "variable", "doc": "<p>Whether the base comes first in the <code>LOG</code> function.\nPossible values: <code>True</code>, <code>False</code>, <code>None</code> (two arguments are not supported by <code>LOG</code>)</p>\n", "annotation": ": Optional[bool]", "default_value": "None"}, "sqlglot.dialects.presto.Presto.NORMALIZATION_STRATEGY": {"fullname": "sqlglot.dialects.presto.Presto.NORMALIZATION_STRATEGY", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.NORMALIZATION_STRATEGY", "kind": "variable", "doc": "<p>Specifies the strategy according to which identifiers should be normalized.</p>\n", "default_value": "<NormalizationStrategy.CASE_INSENSITIVE: 'CASE_INSENSITIVE'>"}, "sqlglot.dialects.presto.Presto.Tokenizer": {"fullname": "sqlglot.dialects.presto.Presto.Tokenizer", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Tokenizer", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.tokens.Tokenizer"}, "sqlglot.dialects.presto.Presto.Tokenizer.UNICODE_STRINGS": {"fullname": "sqlglot.dialects.presto.Presto.Tokenizer.UNICODE_STRINGS", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Tokenizer.UNICODE_STRINGS", "kind": "variable", "doc": "<p></p>\n", "default_value": "[("U&'", "'"), ("u&'", "'")]"}, "sqlglot.dialects.presto.Presto.Tokenizer.KEYWORDS": {"fullname": "sqlglot.dialects.presto.Presto.Tokenizer.KEYWORDS", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Tokenizer.KEYWORDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'{%': <TokenType.BLOCK_START: 'BLOCK_START'>, '{%+': <TokenType.BLOCK_START: 'BLOCK_START'>, '{%-': <TokenType.BLOCK_START: 'BLOCK_START'>, '%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '+%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '-%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '{{+': <TokenType.BLOCK_START: 'BLOCK_START'>, '{{-': <TokenType.BLOCK_START: 'BLOCK_START'>, '+}}': <TokenType.BLOCK_END: 'BLOCK_END'>, '-}}': <TokenType.BLOCK_END: 'BLOCK_END'>, '/*+': <TokenType.HINT: 'HINT'>, '==': <TokenType.EQ: 'EQ'>, '::': <TokenType.DCOLON: 'DCOLON'>, '||': <TokenType.DPIPE: 'DPIPE'>, '>=': <TokenType.GTE: 'GTE'>, '<=': <TokenType.LTE: 'LTE'>, '<>': <TokenType.NEQ: 'NEQ'>, '!=': <TokenType.NEQ: 'NEQ'>, ':=': <TokenType.COLON_EQ: 'COLON_EQ'>, '<=>': <TokenType.NULLSAFE_EQ: 'NULLSAFE_EQ'>, '->': <TokenType.ARROW: 'ARROW'>, '->>': <TokenType.DARROW: 'DARROW'>, '=>': <TokenType.FARROW: 'FARROW'>, '#>': <TokenType.HASH_ARROW: 'HASH_ARROW'>, '#>>': <TokenType.DHASH_ARROW: 'DHASH_ARROW'>, '<->': <TokenType.LR_ARROW: 'LR_ARROW'>, '&&': <TokenType.DAMP: 'DAMP'>, '??': <TokenType.DQMARK: 'DQMARK'>, 'ALL': <TokenType.ALL: 'ALL'>, 'ALWAYS': <TokenType.ALWAYS: 'ALWAYS'>, 'AND': <TokenType.AND: 'AND'>, 'ANTI': <TokenType.ANTI: 'ANTI'>, 'ANY': <TokenType.ANY: 'ANY'>, 'ASC': <TokenType.ASC: 'ASC'>, 'AS': <TokenType.ALIAS: 'ALIAS'>, 'ASOF': <TokenType.ASOF: 'ASOF'>, 'AUTOINCREMENT': <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, 'AUTO_INCREMENT': <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, 'BEGIN': <TokenType.BEGIN: 'BEGIN'>, 'BETWEEN': <TokenType.BETWEEN: 'BETWEEN'>, 'CACHE': <TokenType.CACHE: 'CACHE'>, 'UNCACHE': <TokenType.UNCACHE: 'UNCACHE'>, 'CASE': <TokenType.CASE: 'CASE'>, 'CHARACTER SET': <TokenType.CHARACTER_SET: 'CHARACTER_SET'>, 'CLUSTER BY': <TokenType.CLUSTER_BY: 'CLUSTER_BY'>, 'COLLATE': <TokenType.COLLATE: 'COLLATE'>, 'COLUMN': <TokenType.COLUMN: 'COLUMN'>, 'COMMIT': <TokenType.COMMIT: 'COMMIT'>, 'CONNECT BY': <TokenType.CONNECT_BY: 'CONNECT_BY'>, 'CONSTRAINT': <TokenType.CONSTRAINT: 'CONSTRAINT'>, 'COPY': <TokenType.COPY: 'COPY'>, 'CREATE': <TokenType.CREATE: 'CREATE'>, 'CROSS': <TokenType.CROSS: 'CROSS'>, 'CUBE': <TokenType.CUBE: 'CUBE'>, 'CURRENT_DATE': <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, 'CURRENT_TIME': <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, 'CURRENT_TIMESTAMP': <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, 'CURRENT_USER': <TokenType.CURRENT_USER: 'CURRENT_USER'>, 'DATABASE': <TokenType.DATABASE: 'DATABASE'>, 'DEFAULT': <TokenType.DEFAULT: 'DEFAULT'>, 'DELETE': <TokenType.DELETE: 'DELETE'>, 'DESC': <TokenType.DESC: 'DESC'>, 'DESCRIBE': <TokenType.DESCRIBE: 'DESCRIBE'>, 'DISTINCT': <TokenType.DISTINCT: 'DISTINCT'>, 'DISTRIBUTE BY': <TokenType.DISTRIBUTE_BY: 'DISTRIBUTE_BY'>, 'DIV': <TokenType.DIV: 'DIV'>, 'DROP': <TokenType.DROP: 'DROP'>, 'ELSE': <TokenType.ELSE: 'ELSE'>, 'END': <TokenType.END: 'END'>, 'ENUM': <TokenType.ENUM: 'ENUM'>, 'ESCAPE': <TokenType.ESCAPE: 'ESCAPE'>, 'EXCEPT': <TokenType.EXCEPT: 'EXCEPT'>, 'EXECUTE': <TokenType.EXECUTE: 'EXECUTE'>, 'EXISTS': <TokenType.EXISTS: 'EXISTS'>, 'FALSE': <TokenType.FALSE: 'FALSE'>, 'FETCH': <TokenType.FETCH: 'FETCH'>, 'FILTER': <TokenType.FILTER: 'FILTER'>, 'FIRST': <TokenType.FIRST: 'FIRST'>, 'FULL': <TokenType.FULL: 'FULL'>, 'FUNCTION': <TokenType.FUNCTION: 'FUNCTION'>, 'FOR': <TokenType.FOR: 'FOR'>, 'FOREIGN KEY': <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, 'FORMAT': <TokenType.FORMAT: 'FORMAT'>, 'FROM': <TokenType.FROM: 'FROM'>, 'GEOGRAPHY': <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, 'GEOMETRY': <TokenType.GEOMETRY: 'GEOMETRY'>, 'GLOB': <TokenType.GLOB: 'GLOB'>, 'GROUP BY': <TokenType.GROUP_BY: 'GROUP_BY'>, 'GROUPING SETS': <TokenType.GROUPING_SETS: 'GROUPING_SETS'>, 'HAVING': <TokenType.HAVING: 'HAVING'>, 'ILIKE': <TokenType.ILIKE: 'ILIKE'>, 'IN': <TokenType.IN: 'IN'>, 'INDEX': <TokenType.INDEX: 'INDEX'>, 'INET': <TokenType.INET: 'INET'>, 'INNER': <TokenType.INNER: 'INNER'>, 'INSERT': <TokenType.INSERT: 'INSERT'>, 'INTERVAL': <TokenType.INTERVAL: 'INTERVAL'>, 'INTERSECT': <TokenType.INTERSECT: 'INTERSECT'>, 'INTO': <TokenType.INTO: 'INTO'>, 'IS': <TokenType.IS: 'IS'>, 'ISNULL': <TokenType.ISNULL: 'ISNULL'>, 'JOIN': <TokenType.JOIN: 'JOIN'>, 'KEEP': <TokenType.KEEP: 'KEEP'>, 'KILL': <TokenType.KILL: 'KILL'>, 'LATERAL': <TokenType.LATERAL: 'LATERAL'>, 'LEFT': <TokenType.LEFT: 'LEFT'>, 'LIKE': <TokenType.LIKE: 'LIKE'>, 'LIMIT': <TokenType.LIMIT: 'LIMIT'>, 'LOAD': <TokenType.LOAD: 'LOAD'>, 'LOCK': <TokenType.LOCK: 'LOCK'>, 'MERGE': <TokenType.MERGE: 'MERGE'>, 'NATURAL': <TokenType.NATURAL: 'NATURAL'>, 'NEXT': <TokenType.NEXT: 'NEXT'>, 'NOT': <TokenType.NOT: 'NOT'>, 'NOTNULL': <TokenType.NOTNULL: 'NOTNULL'>, 'NULL': <TokenType.NULL: 'NULL'>, 'OBJECT': <TokenType.OBJECT: 'OBJECT'>, 'OFFSET': <TokenType.OFFSET: 'OFFSET'>, 'ON': <TokenType.ON: 'ON'>, 'OR': <TokenType.OR: 'OR'>, 'XOR': <TokenType.XOR: 'XOR'>, 'ORDER BY': <TokenType.ORDER_BY: 'ORDER_BY'>, 'ORDINALITY': <TokenType.ORDINALITY: 'ORDINALITY'>, 'OUTER': <TokenType.OUTER: 'OUTER'>, 'OVER': <TokenType.OVER: 'OVER'>, 'OVERLAPS': <TokenType.OVERLAPS: 'OVERLAPS'>, 'OVERWRITE': <TokenType.OVERWRITE: 'OVERWRITE'>, 'PARTITION': <TokenType.PARTITION: 'PARTITION'>, 'PARTITION BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PARTITIONED BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PARTITIONED_BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PERCENT': <TokenType.PERCENT: 'PERCENT'>, 'PIVOT': <TokenType.PIVOT: 'PIVOT'>, 'PRAGMA': <TokenType.PRAGMA: 'PRAGMA'>, 'PRIMARY KEY': <TokenType.PRIMARY_KEY: 'PRIMARY_KEY'>, 'PROCEDURE': <TokenType.PROCEDURE: 'PROCEDURE'>, 'RANGE': <TokenType.RANGE: 'RANGE'>, 'RECURSIVE': <TokenType.RECURSIVE: 'RECURSIVE'>, 'REGEXP': <TokenType.RLIKE: 'RLIKE'>, 'REPLACE': <TokenType.REPLACE: 'REPLACE'>, 'RETURNING': <TokenType.RETURNING: 'RETURNING'>, 'REFERENCES': <TokenType.REFERENCES: 'REFERENCES'>, 'RIGHT': <TokenType.RIGHT: 'RIGHT'>, 'RLIKE': <TokenType.RLIKE: 'RLIKE'>, 'ROLLBACK': <TokenType.ROLLBACK: 'ROLLBACK'>, 'ROLLUP': <TokenType.ROLLUP: 'ROLLUP'>, 'ROW': <TokenType.STRUCT: 'STRUCT'>, 'ROWS': <TokenType.ROWS: 'ROWS'>, 'SCHEMA': <TokenType.SCHEMA: 'SCHEMA'>, 'SELECT': <TokenType.SELECT: 'SELECT'>, 'SEMI': <TokenType.SEMI: 'SEMI'>, 'SET': <TokenType.SET: 'SET'>, 'SETTINGS': <TokenType.SETTINGS: 'SETTINGS'>, 'SHOW': <TokenType.SHOW: 'SHOW'>, 'SIMILAR TO': <TokenType.SIMILAR_TO: 'SIMILAR_TO'>, 'SOME': <TokenType.SOME: 'SOME'>, 'SORT BY': <TokenType.SORT_BY: 'SORT_BY'>, 'START WITH': <TokenType.START_WITH: 'START_WITH'>, 'TABLE': <TokenType.TABLE: 'TABLE'>, 'TABLESAMPLE': <TokenType.TABLE_SAMPLE: 'TABLE_SAMPLE'>, 'TEMP': <TokenType.TEMPORARY: 'TEMPORARY'>, 'TEMPORARY': <TokenType.TEMPORARY: 'TEMPORARY'>, 'THEN': <TokenType.THEN: 'THEN'>, 'TRUE': <TokenType.TRUE: 'TRUE'>, 'TRUNCATE': <TokenType.TRUNCATE: 'TRUNCATE'>, 'UNION': <TokenType.UNION: 'UNION'>, 'UNKNOWN': <TokenType.UNKNOWN: 'UNKNOWN'>, 'UNNEST': <TokenType.UNNEST: 'UNNEST'>, 'UNPIVOT': <TokenType.UNPIVOT: 'UNPIVOT'>, 'UPDATE': <TokenType.UPDATE: 'UPDATE'>, 'USE': <TokenType.USE: 'USE'>, 'USING': <TokenType.USING: 'USING'>, 'UUID': <TokenType.UUID: 'UUID'>, 'VALUES': <TokenType.VALUES: 'VALUES'>, 'VIEW': <TokenType.VIEW: 'VIEW'>, 'VOLATILE': <TokenType.VOLATILE: 'VOLATILE'>, 'WHEN': <TokenType.WHEN: 'WHEN'>, 'WHERE': <TokenType.WHERE: 'WHERE'>, 'WINDOW': <TokenType.WINDOW: 'WINDOW'>, 'WITH': <TokenType.WITH: 'WITH'>, 'APPLY': <TokenType.APPLY: 'APPLY'>, 'ARRAY': <TokenType.ARRAY: 'ARRAY'>, 'BIT': <TokenType.BIT: 'BIT'>, 'BOOL': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BOOLEAN': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BYTE': <TokenType.TINYINT: 'TINYINT'>, 'MEDIUMINT': <TokenType.MEDIUMINT: 'MEDIUMINT'>, 'INT1': <TokenType.TINYINT: 'TINYINT'>, 'TINYINT': <TokenType.TINYINT: 'TINYINT'>, 'INT16': <TokenType.SMALLINT: 'SMALLINT'>, 'SHORT': <TokenType.SMALLINT: 'SMALLINT'>, 'SMALLINT': <TokenType.SMALLINT: 'SMALLINT'>, 'INT128': <TokenType.INT128: 'INT128'>, 'HUGEINT': <TokenType.INT128: 'INT128'>, 'INT2': <TokenType.SMALLINT: 'SMALLINT'>, 'INTEGER': <TokenType.INT: 'INT'>, 'INT': <TokenType.INT: 'INT'>, 'INT4': <TokenType.INT: 'INT'>, 'INT32': <TokenType.INT: 'INT'>, 'INT64': <TokenType.BIGINT: 'BIGINT'>, 'LONG': <TokenType.BIGINT: 'BIGINT'>, 'BIGINT': <TokenType.BIGINT: 'BIGINT'>, 'INT8': <TokenType.TINYINT: 'TINYINT'>, 'UINT': <TokenType.UINT: 'UINT'>, 'DEC': <TokenType.DECIMAL: 'DECIMAL'>, 'DECIMAL': <TokenType.DECIMAL: 'DECIMAL'>, 'BIGDECIMAL': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'BIGNUMERIC': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'MAP': <TokenType.MAP: 'MAP'>, 'NULLABLE': <TokenType.NULLABLE: 'NULLABLE'>, 'NUMBER': <TokenType.DECIMAL: 'DECIMAL'>, 'NUMERIC': <TokenType.DECIMAL: 'DECIMAL'>, 'FIXED': <TokenType.DECIMAL: 'DECIMAL'>, 'REAL': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT4': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT8': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE PRECISION': <TokenType.DOUBLE: 'DOUBLE'>, 'JSON': <TokenType.JSON: 'JSON'>, 'CHAR': <TokenType.CHAR: 'CHAR'>, 'CHARACTER': <TokenType.CHAR: 'CHAR'>, 'NCHAR': <TokenType.NCHAR: 'NCHAR'>, 'VARCHAR': <TokenType.VARCHAR: 'VARCHAR'>, 'VARCHAR2': <TokenType.VARCHAR: 'VARCHAR'>, 'NVARCHAR': <TokenType.NVARCHAR: 'NVARCHAR'>, 'NVARCHAR2': <TokenType.NVARCHAR: 'NVARCHAR'>, 'BPCHAR': <TokenType.BPCHAR: 'BPCHAR'>, 'STR': <TokenType.TEXT: 'TEXT'>, 'STRING': <TokenType.TEXT: 'TEXT'>, 'TEXT': <TokenType.TEXT: 'TEXT'>, 'LONGTEXT': <TokenType.LONGTEXT: 'LONGTEXT'>, 'MEDIUMTEXT': <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, 'TINYTEXT': <TokenType.TINYTEXT: 'TINYTEXT'>, 'CLOB': <TokenType.TEXT: 'TEXT'>, 'LONGVARCHAR': <TokenType.TEXT: 'TEXT'>, 'BINARY': <TokenType.BINARY: 'BINARY'>, 'BLOB': <TokenType.VARBINARY: 'VARBINARY'>, 'LONGBLOB': <TokenType.LONGBLOB: 'LONGBLOB'>, 'MEDIUMBLOB': <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, 'TINYBLOB': <TokenType.TINYBLOB: 'TINYBLOB'>, 'BYTEA': <TokenType.VARBINARY: 'VARBINARY'>, 'VARBINARY': <TokenType.VARBINARY: 'VARBINARY'>, 'TIME': <TokenType.TIME: 'TIME'>, 'TIMETZ': <TokenType.TIMETZ: 'TIMETZ'>, 'TIMESTAMP': <TokenType.TIMESTAMP: 'TIMESTAMP'>, 'TIMESTAMPTZ': <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, 'TIMESTAMPLTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMP_LTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMPNTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'TIMESTAMP_NTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'DATE': <TokenType.DATE: 'DATE'>, 'DATETIME': <TokenType.DATETIME: 'DATETIME'>, 'INT4RANGE': <TokenType.INT4RANGE: 'INT4RANGE'>, 'INT4MULTIRANGE': <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, 'INT8RANGE': <TokenType.INT8RANGE: 'INT8RANGE'>, 'INT8MULTIRANGE': <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, 'NUMRANGE': <TokenType.NUMRANGE: 'NUMRANGE'>, 'NUMMULTIRANGE': <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, 'TSRANGE': <TokenType.TSRANGE: 'TSRANGE'>, 'TSMULTIRANGE': <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, 'TSTZRANGE': <TokenType.TSTZRANGE: 'TSTZRANGE'>, 'TSTZMULTIRANGE': <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, 'DATERANGE': <TokenType.DATERANGE: 'DATERANGE'>, 'DATEMULTIRANGE': <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, 'UNIQUE': <TokenType.UNIQUE: 'UNIQUE'>, 'STRUCT': <TokenType.STRUCT: 'STRUCT'>, 'SEQUENCE': <TokenType.SEQUENCE: 'SEQUENCE'>, 'VARIANT': <TokenType.VARIANT: 'VARIANT'>, 'ALTER': <TokenType.ALTER: 'ALTER'>, 'ANALYZE': <TokenType.COMMAND: 'COMMAND'>, 'CALL': <TokenType.COMMAND: 'COMMAND'>, 'COMMENT': <TokenType.COMMENT: 'COMMENT'>, 'EXPLAIN': <TokenType.COMMAND: 'COMMAND'>, 'GRANT': <TokenType.COMMAND: 'COMMAND'>, 'OPTIMIZE': <TokenType.COMMAND: 'COMMAND'>, 'PREPARE': <TokenType.COMMAND: 'COMMAND'>, 'VACUUM': <TokenType.COMMAND: 'COMMAND'>, 'USER-DEFINED': <TokenType.USERDEFINED: 'USERDEFINED'>, 'FOR VERSION': <TokenType.VERSION_SNAPSHOT: 'VERSION_SNAPSHOT'>, 'FOR TIMESTAMP': <TokenType.TIMESTAMP_SNAPSHOT: 'TIMESTAMP_SNAPSHOT'>, 'START': <TokenType.BEGIN: 'BEGIN'>, 'MATCH_RECOGNIZE': <TokenType.MATCH_RECOGNIZE: 'MATCH_RECOGNIZE'>, 'IPADDRESS': <TokenType.IPADDRESS: 'IPADDRESS'>, 'IPPREFIX': <TokenType.IPPREFIX: 'IPPREFIX'>, 'TDIGEST': <TokenType.TDIGEST: 'TDIGEST'>, 'HYPERLOGLOG': <TokenType.HLLSKETCH: 'HLLSKETCH'>}"}, "sqlglot.dialects.presto.Presto.Parser": {"fullname": "sqlglot.dialects.presto.Presto.Parser", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Parser", "kind": "class", "doc": "<p>Parser consumes a list of tokens produced by the Tokenizer and produces a parsed syntax tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>error_level:</strong> The desired error level.\nDefault: ErrorLevel.IMMEDIATE</li>\n<li><strong>error_message_context:</strong> The amount of context to capture from a query string when displaying\nthe error message (in number of characters).\nDefault: 100</li>\n<li><strong>max_errors:</strong> Maximum number of error messages to include in a raised ParseError.\nThis is only relevant if error_level is ErrorLevel.RAISE.\nDefault: 3</li>\n</ul>\n", "bases": "sqlglot.parser.Parser"}, "sqlglot.dialects.presto.Presto.Parser.VALUES_FOLLOWED_BY_PAREN": {"fullname": "sqlglot.dialects.presto.Presto.Parser.VALUES_FOLLOWED_BY_PAREN", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Parser.VALUES_FOLLOWED_BY_PAREN", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.presto.Presto.Parser.FUNCTIONS": {"fullname": "sqlglot.dialects.presto.Presto.Parser.FUNCTIONS", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Parser.FUNCTIONS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ABS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Abs'>>, 'ADD_MONTHS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AddMonths'>>, 'ANONYMOUS_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnonymousAggFunc'>>, 'ANY_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnyValue'>>, 'APPROX_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_COUNT_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'APPROX_TOP_K': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxTopK'>>, 'ARG_MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARGMAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'MAX_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARG_MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARGMIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'MIN_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Array'>>, 'ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAgg'>>, 'ARRAY_ALL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAll'>>, 'ARRAY_ANY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAny'>>, 'ARRAY_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CONSTRUCT_COMPACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConstructCompact'>>, 'ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayContains'>>, 'FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_OVERLAPS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayOverlaps'>>, 'ARRAY_SIZE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_SORT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySort'>>, 'ARRAY_SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySum'>>, 'ARRAY_TO_STRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_JOIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_UNION_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUnionAgg'>>, 'ARRAY_UNIQUE_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUniqueAgg'>>, 'AVG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Avg'>>, 'CASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Case'>>, 'CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cast'>>, 'CAST_TO_STR_TYPE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CastToStrType'>>, 'CBRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cbrt'>>, 'CEIL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CEILING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CHR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'COALESCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'IFNULL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'NVL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'COLLATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Collate'>>, 'COMBINED_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedAggFunc'>>, 'COMBINED_PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedParameterizedAgg'>>, 'CONCAT': <function Parser.<lambda>>, 'CONCAT_WS': <function Parser.<lambda>>, 'CONNECT_BY_ROOT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ConnectByRoot'>>, 'CONVERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Convert'>>, 'CORR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Corr'>>, 'COUNT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Count'>>, 'COUNT_IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COUNTIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COVAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarPop'>>, 'COVAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarSamp'>>, 'CURRENT_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDate'>>, 'CURRENT_DATETIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDatetime'>>, 'CURRENT_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTime'>>, 'CURRENT_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTimestamp'>>, 'CURRENT_USER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentUser'>>, 'DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Date'>>, 'DATE_ADD': <function Presto.Parser.<lambda>>, 'DATEDIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateDiff'>>, 'DATE_DIFF': <function Presto.Parser.<lambda>>, 'DATE_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATE_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateStrToDate'>>, 'DATE_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateSub'>>, 'DATE_TO_DATE_STR': <function Parser.<lambda>>, 'DATE_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateToDi'>>, 'DATE_TRUNC': <function date_trunc_to_time>, 'DATETIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeAdd'>>, 'DATETIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeDiff'>>, 'DATETIME_SUB': <bound method Func.from_arg_list of <class 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method Func.from_arg_list of <class 'sqlglot.expressions.Sign'>>, 'SIGNUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sign'>>, 'SORT_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SortArray'>>, 'SPLIT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Split'>>, 'SQRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sqrt'>>, 'STANDARD_HASH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StandardHash'>>, 'STAR_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StarMap'>>, 'STARTS_WITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STARTSWITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STDDEV': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stddev'>>, 'STDDEV_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StddevPop'>>, 'STDDEV_SAMP': <bound method 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'sqlglot.expressions.ArrayContains'>>, 'DATE_FORMAT': <function build_formatted_time.<locals>._builder>, 'DATE_PARSE': <function build_formatted_time.<locals>._builder>, 'ELEMENT_AT': <function Presto.Parser.<lambda>>, 'FROM_HEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Unhex'>>, 'FROM_UNIXTIME': <function _build_from_unixtime>, 'FROM_UTF8': <function Presto.Parser.<lambda>>, 'NOW': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTimestamp'>>, 'ROW': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Struct'>>, 'SEQUENCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GenerateSeries'>>, 'SET_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUniqueAgg'>>, 'SPLIT_TO_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToMap'>>, 'STRPOS': <function Presto.Parser.<lambda>>, 'TO_UNIXTIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeToUnix'>>, 'TO_UTF8': <function Presto.Parser.<lambda>>, 'SHA256': <function Presto.Parser.<lambda>>, 'SHA512': <function Presto.Parser.<lambda>>}"}, "sqlglot.dialects.presto.Presto.Parser.FUNCTION_PARSERS": {"fullname": "sqlglot.dialects.presto.Presto.Parser.FUNCTION_PARSERS", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Parser.FUNCTION_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'CAST': <function Parser.<lambda>>, 'CONVERT': <function Parser.<lambda>>, 'DECODE': <function Parser.<lambda>>, 'EXTRACT': <function Parser.<lambda>>, 'JSON_OBJECT': <function Parser.<lambda>>, 'JSON_OBJECTAGG': <function Parser.<lambda>>, 'JSON_TABLE': <function Parser.<lambda>>, 'MATCH': <function Parser.<lambda>>, 'OPENJSON': <function Parser.<lambda>>, 'POSITION': <function Parser.<lambda>>, 'PREDICT': <function Parser.<lambda>>, 'SAFE_CAST': <function Parser.<lambda>>, 'STRING_AGG': <function Parser.<lambda>>, 'SUBSTRING': <function Parser.<lambda>>, 'TRY_CAST': <function Parser.<lambda>>, 'TRY_CONVERT': <function Parser.<lambda>>}"}, "sqlglot.dialects.presto.Presto.Parser.TABLE_ALIAS_TOKENS": {"fullname": "sqlglot.dialects.presto.Presto.Parser.TABLE_ALIAS_TOKENS", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Parser.TABLE_ALIAS_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.KILL: 'KILL'>, <TokenType.MONEY: 'MONEY'>, <TokenType.COPY: 'COPY'>, <TokenType.PERCENT: 'PERCENT'>, <TokenType.TAG: 'TAG'>, <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, <TokenType.VOLATILE: 'VOLATILE'>, <TokenType.IDENTIFIER: 'IDENTIFIER'>, <TokenType.VARBINARY: 'VARBINARY'>, <TokenType.HSTORE: 'HSTORE'>, <TokenType.ASC: 'ASC'>, <TokenType.IPADDRESS: 'IPADDRESS'>, <TokenType.ISNULL: 'ISNULL'>, <TokenType.TEMPORARY: 'TEMPORARY'>, <TokenType.PROCEDURE: 'PROCEDURE'>, <TokenType.SCHEMA: 'SCHEMA'>, <TokenType.NUMRANGE: 'NUMRANGE'>, <TokenType.DATE32: 'DATE32'>, <TokenType.INT8RANGE: 'INT8RANGE'>, <TokenType.ANTI: 'ANTI'>, <TokenType.AGGREGATEFUNCTION: 'AGGREGATEFUNCTION'>, <TokenType.VIEW: 'VIEW'>, <TokenType.VARCHAR: 'VARCHAR'>, <TokenType.TIMETZ: 'TIMETZ'>, <TokenType.GEOMETRY: 'GEOMETRY'>, <TokenType.BEGIN: 'BEGIN'>, <TokenType.ENUM8: 'ENUM8'>, <TokenType.INDEX: 'INDEX'>, <TokenType.PARTITION: 'PARTITION'>, <TokenType.UINT256: 'UINT256'>, <TokenType.BIGINT: 'BIGINT'>, <TokenType.CACHE: 'CACHE'>, <TokenType.OPERATOR: 'OPERATOR'>, <TokenType.COLUMN: 'COLUMN'>, <TokenType.INT128: 'INT128'>, <TokenType.SMALLMONEY: 'SMALLMONEY'>, <TokenType.HLLSKETCH: 'HLLSKETCH'>, <TokenType.UNPIVOT: 'UNPIVOT'>, <TokenType.SMALLINT: 'SMALLINT'>, <TokenType.INT256: 'INT256'>, <TokenType.FLOAT: 'FLOAT'>, <TokenType.COMMIT: 'COMMIT'>, <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, <TokenType.EXISTS: 'EXISTS'>, <TokenType.NULL: 'NULL'>, <TokenType.RECURSIVE: 'RECURSIVE'>, <TokenType.SET: 'SET'>, <TokenType.NULLABLE: 'NULLABLE'>, <TokenType.REFRESH: 'REFRESH'>, <TokenType.TINYTEXT: 'TINYTEXT'>, <TokenType.SHOW: 'SHOW'>, <TokenType.DEFAULT: 'DEFAULT'>, <TokenType.DATE: 'DATE'>, <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <TokenType.MERGE: 'MERGE'>, <TokenType.FIRST: 'FIRST'>, <TokenType.BINARY: 'BINARY'>, <TokenType.ARRAY: 'ARRAY'>, <TokenType.SERIAL: 'SERIAL'>, <TokenType.EXECUTE: 'EXECUTE'>, <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, <TokenType.INTERVAL: 'INTERVAL'>, <TokenType.PRAGMA: 'PRAGMA'>, <TokenType.STORAGE_INTEGRATION: 'STORAGE_INTEGRATION'>, <TokenType.BPCHAR: 'BPCHAR'>, <TokenType.BIT: 'BIT'>, <TokenType.UINT: 'UINT'>, <TokenType.UUID: 'UUID'>, <TokenType.STRUCT: 'STRUCT'>, <TokenType.FALSE: 'FALSE'>, <TokenType.FUNCTION: 'FUNCTION'>, <TokenType.TOP: 'TOP'>, <TokenType.SUPER: 'SUPER'>, <TokenType.CASE: 'CASE'>, <TokenType.IMAGE: 'IMAGE'>, <TokenType.UBIGINT: 'UBIGINT'>, <TokenType.LONGBLOB: 'LONGBLOB'>, <TokenType.ROLLUP: 'ROLLUP'>, <TokenType.VAR: 'VAR'>, <TokenType.COMMAND: 'COMMAND'>, <TokenType.LOAD: 'LOAD'>, <TokenType.TRUNCATE: 'TRUNCATE'>, <TokenType.KEEP: 'KEEP'>, <TokenType.UMEDIUMINT: 'UMEDIUMINT'>, <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, <TokenType.UINT128: 'UINT128'>, <TokenType.END: 'END'>, <TokenType.MAP: 'MAP'>, <TokenType.IPV4: 'IPV4'>, <TokenType.USERDEFINED: 'USERDEFINED'>, <TokenType.REFERENCES: 'REFERENCES'>, <TokenType.REPLACE: 'REPLACE'>, <TokenType.RANGE: 'RANGE'>, <TokenType.NVARCHAR: 'NVARCHAR'>, <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, <TokenType.TRUE: 'TRUE'>, <TokenType.TIMESTAMP_MS: 'TIMESTAMP_MS'>, <TokenType.VARIANT: 'VARIANT'>, <TokenType.ENUM: 'ENUM'>, <TokenType.USE: 'USE'>, <TokenType.USMALLINT: 'USMALLINT'>, <TokenType.OVERLAPS: 'OVERLAPS'>, <TokenType.TIMESTAMP_S: 'TIMESTAMP_S'>, <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, <TokenType.UNIQUE: 'UNIQUE'>, <TokenType.ORDINALITY: 'ORDINALITY'>, <TokenType.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>, <TokenType.TEXT: 'TEXT'>, <TokenType.DATABASE: 'DATABASE'>, <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, <TokenType.PSEUDO_TYPE: 'PSEUDO_TYPE'>, <TokenType.FIXEDSTRING: 'FIXEDSTRING'>, <TokenType.NEXT: 'NEXT'>, <TokenType.INT: 'INT'>, <TokenType.BIGSERIAL: 'BIGSERIAL'>, <TokenType.BOOLEAN: 'BOOLEAN'>, <TokenType.IS: 'IS'>, <TokenType.CONSTRAINT: 'CONSTRAINT'>, <TokenType.FINAL: 'FINAL'>, <TokenType.UNKNOWN: 'UNKNOWN'>, <TokenType.SETTINGS: 'SETTINGS'>, <TokenType.ROWS: 'ROWS'>, <TokenType.TSTZRANGE: 'TSTZRANGE'>, <TokenType.DATETIME64: 'DATETIME64'>, <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, <TokenType.DATETIME: 'DATETIME'>, <TokenType.MEDIUMINT: 'MEDIUMINT'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>, <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, <TokenType.XML: 'XML'>, <TokenType.JSON: 'JSON'>, <TokenType.UTINYINT: 'UTINYINT'>, <TokenType.DELETE: 'DELETE'>, <TokenType.TIME: 'TIME'>, <TokenType.UDECIMAL: 'UDECIMAL'>, <TokenType.NESTED: 'NESTED'>, <TokenType.SEMI: 'SEMI'>, <TokenType.DESC: 'DESC'>, <TokenType.ROWVERSION: 'ROWVERSION'>, <TokenType.TIMESTAMP_NS: 'TIMESTAMP_NS'>, <TokenType.ANY: 'ANY'>, <TokenType.DIV: 'DIV'>, <TokenType.DICTIONARY: 'DICTIONARY'>, <TokenType.INET: 'INET'>, <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, <TokenType.COMMENT: 'COMMENT'>, <TokenType.CURRENT_USER: 'CURRENT_USER'>, <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>, <TokenType.ALL: 'ALL'>, <TokenType.NAME: 'NAME'>, <TokenType.SOME: 'SOME'>, <TokenType.ENUM16: 'ENUM16'>, <TokenType.YEAR: 'YEAR'>, <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, <TokenType.DOUBLE: 'DOUBLE'>, <TokenType.INT4RANGE: 'INT4RANGE'>, <TokenType.FORMAT: 'FORMAT'>, <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, <TokenType.IPPREFIX: 'IPPREFIX'>, <TokenType.OVERWRITE: 'OVERWRITE'>, <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>, <TokenType.COLLATE: 'COLLATE'>, <TokenType.FILTER: 'FILTER'>, <TokenType.JSONB: 'JSONB'>, <TokenType.TDIGEST: 'TDIGEST'>, <TokenType.CHAR: 'CHAR'>, <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.ROW: 'ROW'>, <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.TABLE: 'TABLE'>, <TokenType.DATERANGE: 'DATERANGE'>, <TokenType.TSRANGE: 'TSRANGE'>, <TokenType.ESCAPE: 'ESCAPE'>, <TokenType.PIVOT: 'PIVOT'>, <TokenType.DECIMAL: 'DECIMAL'>, <TokenType.NCHAR: 'NCHAR'>, <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, <TokenType.UPDATE: 'UPDATE'>, <TokenType.MODEL: 'MODEL'>, <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, <TokenType.SEQUENCE: 'SEQUENCE'>, <TokenType.LONGTEXT: 'LONGTEXT'>, <TokenType.DESCRIBE: 'DESCRIBE'>, <TokenType.IPV6: 'IPV6'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, <TokenType.TINYINT: 'TINYINT'>, <TokenType.TINYBLOB: 'TINYBLOB'>}"}, "sqlglot.dialects.presto.Presto.Parser.SHOW_TRIE": {"fullname": "sqlglot.dialects.presto.Presto.Parser.SHOW_TRIE", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Parser.SHOW_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.presto.Presto.Parser.SET_TRIE": {"fullname": "sqlglot.dialects.presto.Presto.Parser.SET_TRIE", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Parser.SET_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'GLOBAL': {0: True}, 'LOCAL': {0: True}, 'SESSION': {0: True}, 'TRANSACTION': {0: True}}"}, "sqlglot.dialects.presto.Presto.Generator": {"fullname": "sqlglot.dialects.presto.Presto.Generator", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator", "kind": "class", "doc": "<p>Generator converts a given syntax tree to the corresponding SQL string.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>pretty:</strong> Whether to format the produced SQL string.\nDefault: False.</li>\n<li><strong>identify:</strong> Determines when an identifier should be quoted. Possible values are:\nFalse (default): Never quote, except in cases where it's mandatory by the dialect.\nTrue or 'always': Always quote.\n'safe': Only quote identifiers that are case insensitive.</li>\n<li><strong>normalize:</strong> Whether to normalize identifiers to lowercase.\nDefault: False.</li>\n<li><strong>pad:</strong> The pad size in a formatted string. For example, this affects the indentation of\na projection in a query, relative to its nesting level.\nDefault: 2.</li>\n<li><strong>indent:</strong> The indentation size in a formatted string. For example, this affects the\nindentation of subqueries and filters under a <code>WHERE</code> clause.\nDefault: 2.</li>\n<li><strong>normalize_functions:</strong> How to normalize function names. Possible values are:\n\"upper\" or True (default): Convert names to uppercase.\n\"lower\": Convert names to lowercase.\nFalse: Disables function name normalization.</li>\n<li><strong>unsupported_level:</strong> Determines the generator's behavior when it encounters unsupported expressions.\nDefault ErrorLevel.WARN.</li>\n<li><strong>max_unsupported:</strong> Maximum number of unsupported messages to include in a raised UnsupportedError.\nThis is only relevant if unsupported_level is ErrorLevel.RAISE.\nDefault: 3</li>\n<li><strong>leading_comma:</strong> Whether the comma is leading or trailing in select expressions.\nThis is only relevant when generating in pretty mode.\nDefault: False</li>\n<li><strong>max_text_width:</strong> The max number of characters in a segment before creating new lines in pretty mode.\nThe default is on the smaller end because the length only represents a segment and not the true\nline length.\nDefault: 80</li>\n<li><strong>comments:</strong> Whether to preserve comments in the output SQL code.\nDefault: True</li>\n</ul>\n", "bases": "sqlglot.generator.Generator"}, "sqlglot.dialects.presto.Presto.Generator.INTERVAL_ALLOWS_PLURAL_FORM": {"fullname": "sqlglot.dialects.presto.Presto.Generator.INTERVAL_ALLOWS_PLURAL_FORM", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.INTERVAL_ALLOWS_PLURAL_FORM", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.presto.Presto.Generator.JOIN_HINTS": {"fullname": "sqlglot.dialects.presto.Presto.Generator.JOIN_HINTS", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.JOIN_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.presto.Presto.Generator.TABLE_HINTS": {"fullname": "sqlglot.dialects.presto.Presto.Generator.TABLE_HINTS", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.TABLE_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.presto.Presto.Generator.QUERY_HINTS": {"fullname": "sqlglot.dialects.presto.Presto.Generator.QUERY_HINTS", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.QUERY_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.presto.Presto.Generator.IS_BOOL_ALLOWED": {"fullname": "sqlglot.dialects.presto.Presto.Generator.IS_BOOL_ALLOWED", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.IS_BOOL_ALLOWED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.presto.Presto.Generator.TZ_TO_WITH_TIME_ZONE": {"fullname": "sqlglot.dialects.presto.Presto.Generator.TZ_TO_WITH_TIME_ZONE", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.TZ_TO_WITH_TIME_ZONE", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.presto.Presto.Generator.NVL2_SUPPORTED": {"fullname": "sqlglot.dialects.presto.Presto.Generator.NVL2_SUPPORTED", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.NVL2_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.presto.Presto.Generator.STRUCT_DELIMITER": {"fullname": "sqlglot.dialects.presto.Presto.Generator.STRUCT_DELIMITER", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.STRUCT_DELIMITER", "kind": "variable", "doc": "<p></p>\n", "default_value": "('(', ')')"}, "sqlglot.dialects.presto.Presto.Generator.LIMIT_ONLY_LITERALS": {"fullname": "sqlglot.dialects.presto.Presto.Generator.LIMIT_ONLY_LITERALS", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.LIMIT_ONLY_LITERALS", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.presto.Presto.Generator.SUPPORTS_SINGLE_ARG_CONCAT": {"fullname": "sqlglot.dialects.presto.Presto.Generator.SUPPORTS_SINGLE_ARG_CONCAT", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.SUPPORTS_SINGLE_ARG_CONCAT", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.presto.Presto.Generator.LIKE_PROPERTY_INSIDE_SCHEMA": {"fullname": "sqlglot.dialects.presto.Presto.Generator.LIKE_PROPERTY_INSIDE_SCHEMA", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.LIKE_PROPERTY_INSIDE_SCHEMA", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.presto.Presto.Generator.MULTI_ARG_DISTINCT": {"fullname": "sqlglot.dialects.presto.Presto.Generator.MULTI_ARG_DISTINCT", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.MULTI_ARG_DISTINCT", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.presto.Presto.Generator.SUPPORTS_TO_NUMBER": {"fullname": "sqlglot.dialects.presto.Presto.Generator.SUPPORTS_TO_NUMBER", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.SUPPORTS_TO_NUMBER", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.presto.Presto.Generator.HEX_FUNC": {"fullname": "sqlglot.dialects.presto.Presto.Generator.HEX_FUNC", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.HEX_FUNC", "kind": "variable", "doc": "<p></p>\n", "default_value": "'TO_HEX'"}, "sqlglot.dialects.presto.Presto.Generator.PROPERTIES_LOCATION": {"fullname": "sqlglot.dialects.presto.Presto.Generator.PROPERTIES_LOCATION", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.PROPERTIES_LOCATION", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.AllowedValuesProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.AlgorithmProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.AutoIncrementProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.BackupProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.BlockCompressionProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.CharacterSetProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ChecksumProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.CollateProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Cluster'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ClusteredByProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DataBlocksizeProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.DataDeletionProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DefinerProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.DictRange'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DictProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DistKeyProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DistStyleProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.EngineProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ExternalProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.FallbackProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.FileFormatProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.FreespaceProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.GlobalProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.HeapProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.InheritsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.IcebergProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.InputModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.IsolatedLoadingProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.JournalProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.LanguageProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LikeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LocationProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.LockProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LockingProperty'>: <Location.POST_ALIAS: 'POST_ALIAS'>, <class 'sqlglot.expressions.LogProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.MaterializedProperty'>: 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'POST_SCHEMA'>, <class 'sqlglot.expressions.ReturnsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatDelimitedProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatSerdeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SampleProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SchemaCommentProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SerdeProperties'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Set'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SettingsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SetProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.SetConfigProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 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'sqlglot.expressions.ApproxQuantile'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ArgMax'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ArgMin'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.Array'>: <function Presto.Generator.<lambda>>, <class 'sqlglot.expressions.ArrayAny'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ArrayConcat'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ArrayContains'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ArraySize'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ArrayToString'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ArrayUniqueAgg'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.AtTimeZone'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.BitwiseAnd'>: <function Presto.Generator.<lambda>>, <class 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Presto.Generator.<lambda>>, <class 'sqlglot.expressions.DiToDate'>: <function Presto.Generator.<lambda>>, <class 'sqlglot.expressions.Encode'>: <function Presto.Generator.<lambda>>, <class 'sqlglot.expressions.FileFormatProperty'>: <function Presto.Generator.<lambda>>, <class 'sqlglot.expressions.First'>: <function _first_last_sql>, <class 'sqlglot.expressions.FirstValue'>: <function _first_last_sql>, <class 'sqlglot.expressions.FromTimeZone'>: <function Presto.Generator.<lambda>>, <class 'sqlglot.expressions.Group'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.GroupConcat'>: <function Presto.Generator.<lambda>>, <class 'sqlglot.expressions.If'>: <function if_sql.<locals>._if_sql>, <class 'sqlglot.expressions.ILike'>: <function no_ilike_sql>, <class 'sqlglot.expressions.Initcap'>: <function _initcap_sql>, <class 'sqlglot.expressions.ParseJSON'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.Last'>: <function _first_last_sql>, <class 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rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.With'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.WithinGroup'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.Xor'>: <function bool_xor_sql>, <class 'sqlglot.expressions.MD5'>: <function Presto.Generator.<lambda>>, <class 'sqlglot.expressions.MD5Digest'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.SHA'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.SHA2'>: <function Presto.Generator.<lambda>>}"}, "sqlglot.dialects.presto.Presto.Generator.RESERVED_KEYWORDS": {"fullname": "sqlglot.dialects.presto.Presto.Generator.RESERVED_KEYWORDS", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.RESERVED_KEYWORDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'else', 'cross', 'except', 'intersect', 'current_time', 'alter', 'false', 'distinct', 'escape', 'extract', 'on', 'end', 'having', 'not', 'group', 'then', 'join', 'into', 'for', 'constraint', 'describe', 'right', 'insert', 'true', 'case', 'natural', 'left', 'exists', 'union', 'in', 'values', 'with', 'as', 'drop', 'select', 'where', 'is', 'null', 'execute', 'from', 'deallocate', 'delete', 'create', 'order', 'by', 'and', 'like', 'outer', 'or', 'prepare', 'using', 'between', 'when', 'current_timestamp', 'cast', 'table', 'inner', 'full'}"}, "sqlglot.dialects.presto.Presto.Generator.strtounix_sql": {"fullname": "sqlglot.dialects.presto.Presto.Generator.strtounix_sql", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.strtounix_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">StrToUnix</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.presto.Presto.Generator.bracket_sql": {"fullname": "sqlglot.dialects.presto.Presto.Generator.bracket_sql", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.bracket_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Bracket</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.presto.Presto.Generator.struct_sql": {"fullname": "sqlglot.dialects.presto.Presto.Generator.struct_sql", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.struct_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Struct</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.presto.Presto.Generator.interval_sql": {"fullname": "sqlglot.dialects.presto.Presto.Generator.interval_sql", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.interval_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Interval</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.presto.Presto.Generator.transaction_sql": {"fullname": "sqlglot.dialects.presto.Presto.Generator.transaction_sql", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.transaction_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Transaction</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.presto.Presto.Generator.generateseries_sql": {"fullname": "sqlglot.dialects.presto.Presto.Generator.generateseries_sql", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.generateseries_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">GenerateSeries</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.presto.Presto.Generator.offset_limit_modifiers": {"fullname": "sqlglot.dialects.presto.Presto.Generator.offset_limit_modifiers", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.offset_limit_modifiers", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">fetch</span><span class=\"p\">:</span> <span class=\"nb\">bool</span>,</span><span class=\"param\">\t<span class=\"n\">limit</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Fetch</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Limit</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.presto.Presto.Generator.create_sql": {"fullname": "sqlglot.dialects.presto.Presto.Generator.create_sql", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.create_sql", "kind": "function", "doc": "<p>Presto doesn't support CREATE VIEW with expressions (ex: <code>CREATE VIEW x (cola)</code> then <code>(cola)</code> is the expression),\nso we need to remove them</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Create</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.presto.Presto.Generator.delete_sql": {"fullname": "sqlglot.dialects.presto.Presto.Generator.delete_sql", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.delete_sql", "kind": "function", "doc": "<p>Presto only supports DELETE FROM for a single table without an alias, so we need\nto remove the unnecessary parts. If the original DELETE statement contains more\nthan one table to be deleted, we can't safely map it 1-1 to a Presto statement.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Delete</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.presto.Presto.Generator.SELECT_KINDS": {"fullname": "sqlglot.dialects.presto.Presto.Generator.SELECT_KINDS", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.SELECT_KINDS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Tuple[str, ...]", "default_value": "()"}, "sqlglot.dialects.presto.Presto.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS": {"fullname": "sqlglot.dialects.presto.Presto.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'qualify': <function Generator.<lambda>>, 'windows': <function Generator.<lambda>>}"}, "sqlglot.dialects.presto.Presto.tokenizer_class": {"fullname": "sqlglot.dialects.presto.Presto.tokenizer_class", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.tokenizer_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.presto.Presto.Tokenizer'>"}, "sqlglot.dialects.presto.Presto.parser_class": {"fullname": "sqlglot.dialects.presto.Presto.parser_class", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.parser_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.presto.Presto.Parser'>"}, "sqlglot.dialects.presto.Presto.generator_class": {"fullname": "sqlglot.dialects.presto.Presto.generator_class", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.generator_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.presto.Presto.Generator'>"}, "sqlglot.dialects.presto.Presto.TIME_TRIE": {"fullname": "sqlglot.dialects.presto.Presto.TIME_TRIE", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'%': {'M': {0: True}, 'c': {0: True}, 'e': {0: True}, 'h': {0: True}, 'i': {0: True}, 's': {0: True}, 'u': {0: True}, 'k': {0: True}, 'l': {0: True}, 'T': {0: True}, 'W': {0: True}}}"}, "sqlglot.dialects.presto.Presto.FORMAT_TRIE": {"fullname": "sqlglot.dialects.presto.Presto.FORMAT_TRIE", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.FORMAT_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'%': {'M': {0: True}, 'c': {0: True}, 'e': {0: True}, 'h': {0: True}, 'i': {0: True}, 's': {0: True}, 'u': {0: True}, 'k': {0: True}, 'l': {0: True}, 'T': {0: True}, 'W': {0: True}}}"}, "sqlglot.dialects.presto.Presto.INVERSE_TIME_MAPPING": {"fullname": "sqlglot.dialects.presto.Presto.INVERSE_TIME_MAPPING", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.INVERSE_TIME_MAPPING", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'%B': '%M', '%-m': '%c', '%-d': '%e', '%I': '%h', '%M': '%i', '%S': '%s', '%W': '%u', '%-H': '%k', '%-I': '%l', '%H:%M:%S': '%T', '%a': '%W'}"}, "sqlglot.dialects.presto.Presto.INVERSE_TIME_TRIE": {"fullname": "sqlglot.dialects.presto.Presto.INVERSE_TIME_TRIE", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.INVERSE_TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'%': {'B': {0: True}, '-': {'m': {0: True}, 'd': {0: True}, 'H': {0: True}, 'I': {0: True}}, 'I': {0: True}, 'M': {0: True}, 'S': {0: True}, 'W': {0: True}, 'H': {':': {'%': {'M': {':': {'%': {'S': {0: True}}}}}}}, 'a': {0: True}}}"}, "sqlglot.dialects.presto.Presto.ESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.presto.Presto.ESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.ESCAPED_SEQUENCES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{}"}, "sqlglot.dialects.presto.Presto.QUOTE_START": {"fullname": "sqlglot.dialects.presto.Presto.QUOTE_START", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.QUOTE_START", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.presto.Presto.QUOTE_END": {"fullname": "sqlglot.dialects.presto.Presto.QUOTE_END", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.QUOTE_END", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.presto.Presto.IDENTIFIER_START": {"fullname": "sqlglot.dialects.presto.Presto.IDENTIFIER_START", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.IDENTIFIER_START", "kind": "variable", "doc": "<p></p>\n", "default_value": "'"'"}, "sqlglot.dialects.presto.Presto.IDENTIFIER_END": {"fullname": "sqlglot.dialects.presto.Presto.IDENTIFIER_END", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.IDENTIFIER_END", "kind": "variable", "doc": "<p></p>\n", "default_value": "'"'"}, "sqlglot.dialects.presto.Presto.BIT_START": {"fullname": "sqlglot.dialects.presto.Presto.BIT_START", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.BIT_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.presto.Presto.BIT_END": {"fullname": "sqlglot.dialects.presto.Presto.BIT_END", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.BIT_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.presto.Presto.HEX_START": {"fullname": "sqlglot.dialects.presto.Presto.HEX_START", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.HEX_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.presto.Presto.HEX_END": {"fullname": "sqlglot.dialects.presto.Presto.HEX_END", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.HEX_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.presto.Presto.BYTE_START": {"fullname": "sqlglot.dialects.presto.Presto.BYTE_START", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.BYTE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.presto.Presto.BYTE_END": {"fullname": "sqlglot.dialects.presto.Presto.BYTE_END", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.BYTE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.presto.Presto.UNICODE_START": {"fullname": "sqlglot.dialects.presto.Presto.UNICODE_START", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.UNICODE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""U&'""}, "sqlglot.dialects.presto.Presto.UNICODE_END": {"fullname": "sqlglot.dialects.presto.Presto.UNICODE_END", "modulename": "sqlglot.dialects.presto", "qualname": "Presto.UNICODE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""'""}, "sqlglot.dialects.prql": {"fullname": "sqlglot.dialects.prql", "modulename": "sqlglot.dialects.prql", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.dialects.prql.PRQL": {"fullname": "sqlglot.dialects.prql.PRQL", "modulename": "sqlglot.dialects.prql", "qualname": "PRQL", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.dialect.Dialect"}, "sqlglot.dialects.prql.PRQL.DPIPE_IS_STRING_CONCAT": {"fullname": "sqlglot.dialects.prql.PRQL.DPIPE_IS_STRING_CONCAT", "modulename": "sqlglot.dialects.prql", "qualname": "PRQL.DPIPE_IS_STRING_CONCAT", "kind": "variable", "doc": "<p>Whether the DPIPE token (<code>||</code>) is a string concatenation operator.</p>\n", "default_value": "False"}, "sqlglot.dialects.prql.PRQL.Tokenizer": {"fullname": "sqlglot.dialects.prql.PRQL.Tokenizer", "modulename": "sqlglot.dialects.prql", "qualname": "PRQL.Tokenizer", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.tokens.Tokenizer"}, "sqlglot.dialects.prql.PRQL.Tokenizer.IDENTIFIERS": {"fullname": "sqlglot.dialects.prql.PRQL.Tokenizer.IDENTIFIERS", "modulename": "sqlglot.dialects.prql", "qualname": "PRQL.Tokenizer.IDENTIFIERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "['`']"}, "sqlglot.dialects.prql.PRQL.Tokenizer.QUOTES": {"fullname": "sqlglot.dialects.prql.PRQL.Tokenizer.QUOTES", "modulename": "sqlglot.dialects.prql", "qualname": "PRQL.Tokenizer.QUOTES", "kind": "variable", "doc": "<p></p>\n", "default_value": "["'", '"']"}, "sqlglot.dialects.prql.PRQL.Tokenizer.SINGLE_TOKENS": {"fullname": "sqlglot.dialects.prql.PRQL.Tokenizer.SINGLE_TOKENS", "modulename": "sqlglot.dialects.prql", "qualname": "PRQL.Tokenizer.SINGLE_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'(': <TokenType.L_PAREN: 'L_PAREN'>, ')': <TokenType.R_PAREN: 'R_PAREN'>, '[': <TokenType.L_BRACKET: 'L_BRACKET'>, ']': <TokenType.R_BRACKET: 'R_BRACKET'>, '{': <TokenType.L_BRACE: 'L_BRACE'>, '}': <TokenType.R_BRACE: 'R_BRACE'>, '&': <TokenType.AMP: 'AMP'>, '^': <TokenType.CARET: 'CARET'>, ':': <TokenType.COLON: 'COLON'>, ',': <TokenType.COMMA: 'COMMA'>, '.': <TokenType.DOT: 'DOT'>, '-': <TokenType.DASH: 'DASH'>, '=': <TokenType.ALIAS: 'ALIAS'>, '>': <TokenType.GT: 'GT'>, '<': <TokenType.LT: 'LT'>, '%': <TokenType.MOD: 'MOD'>, '!': <TokenType.NOT: 'NOT'>, '|': <TokenType.PIPE: 'PIPE'>, '+': <TokenType.PLUS: 'PLUS'>, ';': <TokenType.SEMICOLON: 'SEMICOLON'>, '/': <TokenType.SLASH: 'SLASH'>, '\\\\': <TokenType.BACKSLASH: 'BACKSLASH'>, '*': <TokenType.STAR: 'STAR'>, '~': <TokenType.TILDA: 'TILDA'>, '?': <TokenType.PLACEHOLDER: 'PLACEHOLDER'>, '@': <TokenType.PARAMETER: 'PARAMETER'>, '#': <TokenType.COMMENT: 'COMMENT'>, "'": <TokenType.QUOTE: 'QUOTE'>, '`': <TokenType.IDENTIFIER: 'IDENTIFIER'>, '"': <TokenType.QUOTE: 'QUOTE'>}"}, "sqlglot.dialects.prql.PRQL.Tokenizer.KEYWORDS": {"fullname": "sqlglot.dialects.prql.PRQL.Tokenizer.KEYWORDS", "modulename": "sqlglot.dialects.prql", "qualname": "PRQL.Tokenizer.KEYWORDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'{%': <TokenType.BLOCK_START: 'BLOCK_START'>, '{%+': <TokenType.BLOCK_START: 'BLOCK_START'>, '{%-': <TokenType.BLOCK_START: 'BLOCK_START'>, '%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '+%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '-%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '{{+': <TokenType.BLOCK_START: 'BLOCK_START'>, '{{-': <TokenType.BLOCK_START: 'BLOCK_START'>, '+}}': <TokenType.BLOCK_END: 'BLOCK_END'>, '-}}': <TokenType.BLOCK_END: 'BLOCK_END'>, '/*+': <TokenType.HINT: 'HINT'>, '==': <TokenType.EQ: 'EQ'>, '::': <TokenType.DCOLON: 'DCOLON'>, '||': <TokenType.DPIPE: 'DPIPE'>, '>=': <TokenType.GTE: 'GTE'>, '<=': <TokenType.LTE: 'LTE'>, '<>': <TokenType.NEQ: 'NEQ'>, '!=': <TokenType.NEQ: 'NEQ'>, ':=': <TokenType.COLON_EQ: 'COLON_EQ'>, '<=>': <TokenType.NULLSAFE_EQ: 'NULLSAFE_EQ'>, '->': <TokenType.ARROW: 'ARROW'>, '->>': <TokenType.DARROW: 'DARROW'>, '=>': <TokenType.FARROW: 'FARROW'>, '#>': <TokenType.HASH_ARROW: 'HASH_ARROW'>, '#>>': <TokenType.DHASH_ARROW: 'DHASH_ARROW'>, '<->': <TokenType.LR_ARROW: 'LR_ARROW'>, '&&': <TokenType.DAMP: 'DAMP'>, '??': <TokenType.DQMARK: 'DQMARK'>, 'ALL': <TokenType.ALL: 'ALL'>, 'ALWAYS': <TokenType.ALWAYS: 'ALWAYS'>, 'AND': <TokenType.AND: 'AND'>, 'ANTI': <TokenType.ANTI: 'ANTI'>, 'ANY': <TokenType.ANY: 'ANY'>, 'ASC': <TokenType.ASC: 'ASC'>, 'AS': <TokenType.ALIAS: 'ALIAS'>, 'ASOF': <TokenType.ASOF: 'ASOF'>, 'AUTOINCREMENT': <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, 'AUTO_INCREMENT': <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, 'BEGIN': <TokenType.BEGIN: 'BEGIN'>, 'BETWEEN': <TokenType.BETWEEN: 'BETWEEN'>, 'CACHE': <TokenType.CACHE: 'CACHE'>, 'UNCACHE': <TokenType.UNCACHE: 'UNCACHE'>, 'CASE': <TokenType.CASE: 'CASE'>, 'CHARACTER SET': <TokenType.CHARACTER_SET: 'CHARACTER_SET'>, 'CLUSTER BY': <TokenType.CLUSTER_BY: 'CLUSTER_BY'>, 'COLLATE': <TokenType.COLLATE: 'COLLATE'>, 'COLUMN': <TokenType.COLUMN: 'COLUMN'>, 'COMMIT': <TokenType.COMMIT: 'COMMIT'>, 'CONNECT BY': <TokenType.CONNECT_BY: 'CONNECT_BY'>, 'CONSTRAINT': <TokenType.CONSTRAINT: 'CONSTRAINT'>, 'COPY': <TokenType.COPY: 'COPY'>, 'CREATE': <TokenType.CREATE: 'CREATE'>, 'CROSS': <TokenType.CROSS: 'CROSS'>, 'CUBE': <TokenType.CUBE: 'CUBE'>, 'CURRENT_DATE': <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, 'CURRENT_TIME': <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, 'CURRENT_TIMESTAMP': <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, 'CURRENT_USER': <TokenType.CURRENT_USER: 'CURRENT_USER'>, 'DATABASE': <TokenType.DATABASE: 'DATABASE'>, 'DEFAULT': <TokenType.DEFAULT: 'DEFAULT'>, 'DELETE': <TokenType.DELETE: 'DELETE'>, 'DESC': <TokenType.DESC: 'DESC'>, 'DESCRIBE': <TokenType.DESCRIBE: 'DESCRIBE'>, 'DISTINCT': <TokenType.DISTINCT: 'DISTINCT'>, 'DISTRIBUTE BY': <TokenType.DISTRIBUTE_BY: 'DISTRIBUTE_BY'>, 'DIV': <TokenType.DIV: 'DIV'>, 'DROP': <TokenType.DROP: 'DROP'>, 'ELSE': <TokenType.ELSE: 'ELSE'>, 'END': <TokenType.END: 'END'>, 'ENUM': <TokenType.ENUM: 'ENUM'>, 'ESCAPE': <TokenType.ESCAPE: 'ESCAPE'>, 'EXCEPT': <TokenType.EXCEPT: 'EXCEPT'>, 'EXECUTE': <TokenType.EXECUTE: 'EXECUTE'>, 'EXISTS': <TokenType.EXISTS: 'EXISTS'>, 'FALSE': <TokenType.FALSE: 'FALSE'>, 'FETCH': <TokenType.FETCH: 'FETCH'>, 'FILTER': <TokenType.FILTER: 'FILTER'>, 'FIRST': <TokenType.FIRST: 'FIRST'>, 'FULL': <TokenType.FULL: 'FULL'>, 'FUNCTION': <TokenType.FUNCTION: 'FUNCTION'>, 'FOR': <TokenType.FOR: 'FOR'>, 'FOREIGN KEY': <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, 'FORMAT': <TokenType.FORMAT: 'FORMAT'>, 'FROM': <TokenType.FROM: 'FROM'>, 'GEOGRAPHY': <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, 'GEOMETRY': <TokenType.GEOMETRY: 'GEOMETRY'>, 'GLOB': <TokenType.GLOB: 'GLOB'>, 'GROUP BY': <TokenType.GROUP_BY: 'GROUP_BY'>, 'GROUPING SETS': <TokenType.GROUPING_SETS: 'GROUPING_SETS'>, 'HAVING': <TokenType.HAVING: 'HAVING'>, 'ILIKE': <TokenType.ILIKE: 'ILIKE'>, 'IN': <TokenType.IN: 'IN'>, 'INDEX': <TokenType.INDEX: 'INDEX'>, 'INET': <TokenType.INET: 'INET'>, 'INNER': <TokenType.INNER: 'INNER'>, 'INSERT': <TokenType.INSERT: 'INSERT'>, 'INTERVAL': <TokenType.INTERVAL: 'INTERVAL'>, 'INTERSECT': <TokenType.INTERSECT: 'INTERSECT'>, 'INTO': <TokenType.INTO: 'INTO'>, 'IS': <TokenType.IS: 'IS'>, 'ISNULL': <TokenType.ISNULL: 'ISNULL'>, 'JOIN': <TokenType.JOIN: 'JOIN'>, 'KEEP': <TokenType.KEEP: 'KEEP'>, 'KILL': <TokenType.KILL: 'KILL'>, 'LATERAL': <TokenType.LATERAL: 'LATERAL'>, 'LEFT': <TokenType.LEFT: 'LEFT'>, 'LIKE': <TokenType.LIKE: 'LIKE'>, 'LIMIT': <TokenType.LIMIT: 'LIMIT'>, 'LOAD': <TokenType.LOAD: 'LOAD'>, 'LOCK': <TokenType.LOCK: 'LOCK'>, 'MERGE': <TokenType.MERGE: 'MERGE'>, 'NATURAL': <TokenType.NATURAL: 'NATURAL'>, 'NEXT': <TokenType.NEXT: 'NEXT'>, 'NOT': <TokenType.NOT: 'NOT'>, 'NOTNULL': <TokenType.NOTNULL: 'NOTNULL'>, 'NULL': <TokenType.NULL: 'NULL'>, 'OBJECT': <TokenType.OBJECT: 'OBJECT'>, 'OFFSET': <TokenType.OFFSET: 'OFFSET'>, 'ON': <TokenType.ON: 'ON'>, 'OR': <TokenType.OR: 'OR'>, 'XOR': <TokenType.XOR: 'XOR'>, 'ORDER BY': <TokenType.ORDER_BY: 'ORDER_BY'>, 'ORDINALITY': <TokenType.ORDINALITY: 'ORDINALITY'>, 'OUTER': <TokenType.OUTER: 'OUTER'>, 'OVER': <TokenType.OVER: 'OVER'>, 'OVERLAPS': <TokenType.OVERLAPS: 'OVERLAPS'>, 'OVERWRITE': <TokenType.OVERWRITE: 'OVERWRITE'>, 'PARTITION': <TokenType.PARTITION: 'PARTITION'>, 'PARTITION BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PARTITIONED BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PARTITIONED_BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PERCENT': <TokenType.PERCENT: 'PERCENT'>, 'PIVOT': <TokenType.PIVOT: 'PIVOT'>, 'PRAGMA': <TokenType.PRAGMA: 'PRAGMA'>, 'PRIMARY KEY': <TokenType.PRIMARY_KEY: 'PRIMARY_KEY'>, 'PROCEDURE': <TokenType.PROCEDURE: 'PROCEDURE'>, 'QUALIFY': <TokenType.QUALIFY: 'QUALIFY'>, 'RANGE': <TokenType.RANGE: 'RANGE'>, 'RECURSIVE': <TokenType.RECURSIVE: 'RECURSIVE'>, 'REGEXP': <TokenType.RLIKE: 'RLIKE'>, 'REPLACE': <TokenType.REPLACE: 'REPLACE'>, 'RETURNING': <TokenType.RETURNING: 'RETURNING'>, 'REFERENCES': <TokenType.REFERENCES: 'REFERENCES'>, 'RIGHT': <TokenType.RIGHT: 'RIGHT'>, 'RLIKE': <TokenType.RLIKE: 'RLIKE'>, 'ROLLBACK': <TokenType.ROLLBACK: 'ROLLBACK'>, 'ROLLUP': <TokenType.ROLLUP: 'ROLLUP'>, 'ROW': <TokenType.ROW: 'ROW'>, 'ROWS': <TokenType.ROWS: 'ROWS'>, 'SCHEMA': <TokenType.SCHEMA: 'SCHEMA'>, 'SELECT': <TokenType.SELECT: 'SELECT'>, 'SEMI': <TokenType.SEMI: 'SEMI'>, 'SET': <TokenType.SET: 'SET'>, 'SETTINGS': <TokenType.SETTINGS: 'SETTINGS'>, 'SHOW': <TokenType.SHOW: 'SHOW'>, 'SIMILAR TO': <TokenType.SIMILAR_TO: 'SIMILAR_TO'>, 'SOME': <TokenType.SOME: 'SOME'>, 'SORT BY': <TokenType.SORT_BY: 'SORT_BY'>, 'START WITH': <TokenType.START_WITH: 'START_WITH'>, 'TABLE': <TokenType.TABLE: 'TABLE'>, 'TABLESAMPLE': <TokenType.TABLE_SAMPLE: 'TABLE_SAMPLE'>, 'TEMP': <TokenType.TEMPORARY: 'TEMPORARY'>, 'TEMPORARY': <TokenType.TEMPORARY: 'TEMPORARY'>, 'THEN': <TokenType.THEN: 'THEN'>, 'TRUE': <TokenType.TRUE: 'TRUE'>, 'TRUNCATE': <TokenType.TRUNCATE: 'TRUNCATE'>, 'UNION': <TokenType.UNION: 'UNION'>, 'UNKNOWN': <TokenType.UNKNOWN: 'UNKNOWN'>, 'UNNEST': <TokenType.UNNEST: 'UNNEST'>, 'UNPIVOT': <TokenType.UNPIVOT: 'UNPIVOT'>, 'UPDATE': <TokenType.UPDATE: 'UPDATE'>, 'USE': <TokenType.USE: 'USE'>, 'USING': <TokenType.USING: 'USING'>, 'UUID': <TokenType.UUID: 'UUID'>, 'VALUES': <TokenType.VALUES: 'VALUES'>, 'VIEW': <TokenType.VIEW: 'VIEW'>, 'VOLATILE': <TokenType.VOLATILE: 'VOLATILE'>, 'WHEN': <TokenType.WHEN: 'WHEN'>, 'WHERE': <TokenType.WHERE: 'WHERE'>, 'WINDOW': <TokenType.WINDOW: 'WINDOW'>, 'WITH': <TokenType.WITH: 'WITH'>, 'APPLY': <TokenType.APPLY: 'APPLY'>, 'ARRAY': <TokenType.ARRAY: 'ARRAY'>, 'BIT': <TokenType.BIT: 'BIT'>, 'BOOL': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BOOLEAN': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BYTE': <TokenType.TINYINT: 'TINYINT'>, 'MEDIUMINT': <TokenType.MEDIUMINT: 'MEDIUMINT'>, 'INT1': <TokenType.TINYINT: 'TINYINT'>, 'TINYINT': <TokenType.TINYINT: 'TINYINT'>, 'INT16': <TokenType.SMALLINT: 'SMALLINT'>, 'SHORT': <TokenType.SMALLINT: 'SMALLINT'>, 'SMALLINT': <TokenType.SMALLINT: 'SMALLINT'>, 'INT128': <TokenType.INT128: 'INT128'>, 'HUGEINT': <TokenType.INT128: 'INT128'>, 'INT2': <TokenType.SMALLINT: 'SMALLINT'>, 'INTEGER': <TokenType.INT: 'INT'>, 'INT': <TokenType.INT: 'INT'>, 'INT4': <TokenType.INT: 'INT'>, 'INT32': <TokenType.INT: 'INT'>, 'INT64': <TokenType.BIGINT: 'BIGINT'>, 'LONG': <TokenType.BIGINT: 'BIGINT'>, 'BIGINT': <TokenType.BIGINT: 'BIGINT'>, 'INT8': <TokenType.TINYINT: 'TINYINT'>, 'UINT': <TokenType.UINT: 'UINT'>, 'DEC': <TokenType.DECIMAL: 'DECIMAL'>, 'DECIMAL': <TokenType.DECIMAL: 'DECIMAL'>, 'BIGDECIMAL': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'BIGNUMERIC': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'MAP': <TokenType.MAP: 'MAP'>, 'NULLABLE': <TokenType.NULLABLE: 'NULLABLE'>, 'NUMBER': <TokenType.DECIMAL: 'DECIMAL'>, 'NUMERIC': <TokenType.DECIMAL: 'DECIMAL'>, 'FIXED': <TokenType.DECIMAL: 'DECIMAL'>, 'REAL': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT4': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT8': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE PRECISION': <TokenType.DOUBLE: 'DOUBLE'>, 'JSON': <TokenType.JSON: 'JSON'>, 'CHAR': <TokenType.CHAR: 'CHAR'>, 'CHARACTER': <TokenType.CHAR: 'CHAR'>, 'NCHAR': <TokenType.NCHAR: 'NCHAR'>, 'VARCHAR': <TokenType.VARCHAR: 'VARCHAR'>, 'VARCHAR2': <TokenType.VARCHAR: 'VARCHAR'>, 'NVARCHAR': <TokenType.NVARCHAR: 'NVARCHAR'>, 'NVARCHAR2': <TokenType.NVARCHAR: 'NVARCHAR'>, 'BPCHAR': <TokenType.BPCHAR: 'BPCHAR'>, 'STR': <TokenType.TEXT: 'TEXT'>, 'STRING': <TokenType.TEXT: 'TEXT'>, 'TEXT': <TokenType.TEXT: 'TEXT'>, 'LONGTEXT': <TokenType.LONGTEXT: 'LONGTEXT'>, 'MEDIUMTEXT': <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, 'TINYTEXT': <TokenType.TINYTEXT: 'TINYTEXT'>, 'CLOB': <TokenType.TEXT: 'TEXT'>, 'LONGVARCHAR': <TokenType.TEXT: 'TEXT'>, 'BINARY': <TokenType.BINARY: 'BINARY'>, 'BLOB': <TokenType.VARBINARY: 'VARBINARY'>, 'LONGBLOB': <TokenType.LONGBLOB: 'LONGBLOB'>, 'MEDIUMBLOB': <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, 'TINYBLOB': <TokenType.TINYBLOB: 'TINYBLOB'>, 'BYTEA': <TokenType.VARBINARY: 'VARBINARY'>, 'VARBINARY': <TokenType.VARBINARY: 'VARBINARY'>, 'TIME': <TokenType.TIME: 'TIME'>, 'TIMETZ': <TokenType.TIMETZ: 'TIMETZ'>, 'TIMESTAMP': <TokenType.TIMESTAMP: 'TIMESTAMP'>, 'TIMESTAMPTZ': <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, 'TIMESTAMPLTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMP_LTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMPNTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'TIMESTAMP_NTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'DATE': <TokenType.DATE: 'DATE'>, 'DATETIME': <TokenType.DATETIME: 'DATETIME'>, 'INT4RANGE': <TokenType.INT4RANGE: 'INT4RANGE'>, 'INT4MULTIRANGE': <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, 'INT8RANGE': <TokenType.INT8RANGE: 'INT8RANGE'>, 'INT8MULTIRANGE': <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, 'NUMRANGE': <TokenType.NUMRANGE: 'NUMRANGE'>, 'NUMMULTIRANGE': <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, 'TSRANGE': <TokenType.TSRANGE: 'TSRANGE'>, 'TSMULTIRANGE': <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, 'TSTZRANGE': <TokenType.TSTZRANGE: 'TSTZRANGE'>, 'TSTZMULTIRANGE': <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, 'DATERANGE': <TokenType.DATERANGE: 'DATERANGE'>, 'DATEMULTIRANGE': <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, 'UNIQUE': <TokenType.UNIQUE: 'UNIQUE'>, 'STRUCT': <TokenType.STRUCT: 'STRUCT'>, 'SEQUENCE': <TokenType.SEQUENCE: 'SEQUENCE'>, 'VARIANT': <TokenType.VARIANT: 'VARIANT'>, 'ALTER': <TokenType.ALTER: 'ALTER'>, 'ANALYZE': <TokenType.COMMAND: 'COMMAND'>, 'CALL': <TokenType.COMMAND: 'COMMAND'>, 'COMMENT': <TokenType.COMMENT: 'COMMENT'>, 'EXPLAIN': <TokenType.COMMAND: 'COMMAND'>, 'GRANT': <TokenType.COMMAND: 'COMMAND'>, 'OPTIMIZE': <TokenType.COMMAND: 'COMMAND'>, 'PREPARE': <TokenType.COMMAND: 'COMMAND'>, 'VACUUM': <TokenType.COMMAND: 'COMMAND'>, 'USER-DEFINED': <TokenType.USERDEFINED: 'USERDEFINED'>, 'FOR VERSION': <TokenType.VERSION_SNAPSHOT: 'VERSION_SNAPSHOT'>, 'FOR TIMESTAMP': <TokenType.TIMESTAMP_SNAPSHOT: 'TIMESTAMP_SNAPSHOT'>}"}, "sqlglot.dialects.prql.PRQL.Parser": {"fullname": "sqlglot.dialects.prql.PRQL.Parser", "modulename": "sqlglot.dialects.prql", "qualname": "PRQL.Parser", "kind": "class", "doc": "<p>Parser consumes a list of tokens produced by the Tokenizer and produces a parsed syntax tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>error_level:</strong> The desired error level.\nDefault: ErrorLevel.IMMEDIATE</li>\n<li><strong>error_message_context:</strong> The amount of context to capture from a query string when displaying\nthe error message (in number of characters).\nDefault: 100</li>\n<li><strong>max_errors:</strong> Maximum number of error messages to include in a raised ParseError.\nThis is only relevant if error_level is ErrorLevel.RAISE.\nDefault: 3</li>\n</ul>\n", "bases": "sqlglot.parser.Parser"}, "sqlglot.dialects.prql.PRQL.Parser.CONJUNCTION": {"fullname": "sqlglot.dialects.prql.PRQL.Parser.CONJUNCTION", "modulename": "sqlglot.dialects.prql", "qualname": "PRQL.Parser.CONJUNCTION", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.AND: 'AND'>: <class 'sqlglot.expressions.And'>, <TokenType.OR: 'OR'>: <class 'sqlglot.expressions.Or'>, <TokenType.DAMP: 'DAMP'>: <class 'sqlglot.expressions.And'>, <TokenType.DPIPE: 'DPIPE'>: <class 'sqlglot.expressions.Or'>}"}, "sqlglot.dialects.prql.PRQL.Parser.TRANSFORM_PARSERS": {"fullname": "sqlglot.dialects.prql.PRQL.Parser.TRANSFORM_PARSERS", "modulename": "sqlglot.dialects.prql", "qualname": "PRQL.Parser.TRANSFORM_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'DERIVE': <function PRQL.Parser.<lambda>>, 'SELECT': <function PRQL.Parser.<lambda>>, 'TAKE': <function PRQL.Parser.<lambda>>, 'FILTER': <function PRQL.Parser.<lambda>>, 'APPEND': <function PRQL.Parser.<lambda>>, 'REMOVE': <function PRQL.Parser.<lambda>>, 'INTERSECT': <function PRQL.Parser.<lambda>>, 'SORT': <function PRQL.Parser.<lambda>>, 'AGGREGATE': <function PRQL.Parser.<lambda>>}"}, "sqlglot.dialects.prql.PRQL.Parser.FUNCTIONS": {"fullname": "sqlglot.dialects.prql.PRQL.Parser.FUNCTIONS", "modulename": "sqlglot.dialects.prql", "qualname": "PRQL.Parser.FUNCTIONS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ABS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Abs'>>, 'ADD_MONTHS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AddMonths'>>, 'ANONYMOUS_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnonymousAggFunc'>>, 'ANY_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnyValue'>>, 'APPROX_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_COUNT_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'APPROX_TOP_K': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxTopK'>>, 'ARG_MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARGMAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'MAX_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARG_MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARGMIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'MIN_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Array'>>, 'ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAgg'>>, 'ARRAY_ALL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAll'>>, 'ARRAY_ANY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAny'>>, 'ARRAY_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CONSTRUCT_COMPACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConstructCompact'>>, 'ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayContains'>>, 'FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_OVERLAPS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayOverlaps'>>, 'ARRAY_SIZE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_SORT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySort'>>, 'ARRAY_SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySum'>>, 'ARRAY_TO_STRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_JOIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_UNION_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUnionAgg'>>, 'ARRAY_UNIQUE_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUniqueAgg'>>, 'AVG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Avg'>>, 'CASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Case'>>, 'CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cast'>>, 'CAST_TO_STR_TYPE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CastToStrType'>>, 'CBRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cbrt'>>, 'CEIL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CEILING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CHR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'COALESCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'IFNULL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'NVL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'COLLATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Collate'>>, 'COMBINED_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedAggFunc'>>, 'COMBINED_PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedParameterizedAgg'>>, 'CONCAT': <function Parser.<lambda>>, 'CONCAT_WS': <function Parser.<lambda>>, 'CONNECT_BY_ROOT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ConnectByRoot'>>, 'CONVERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Convert'>>, 'CORR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Corr'>>, 'COUNT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Count'>>, 'COUNT_IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COUNTIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COVAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarPop'>>, 'COVAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarSamp'>>, 'CURRENT_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDate'>>, 'CURRENT_DATETIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDatetime'>>, 'CURRENT_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTime'>>, 'CURRENT_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTimestamp'>>, 'CURRENT_USER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentUser'>>, 'DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Date'>>, 'DATE_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateAdd'>>, 'DATEDIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateDiff'>>, 'DATE_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateDiff'>>, 'DATE_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATE_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateStrToDate'>>, 'DATE_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateSub'>>, 'DATE_TO_DATE_STR': <function Parser.<lambda>>, 'DATE_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateToDi'>>, 'DATE_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateTrunc'>>, 'DATETIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeAdd'>>, 'DATETIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeDiff'>>, 'DATETIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeSub'>>, 'DATETIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeTrunc'>>, 'DAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Day'>>, 'DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAYOFMONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAY_OF_WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAYOFWEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAY_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DAYOFYEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DECODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Decode'>>, 'DI_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DiToDate'>>, 'ENCODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Encode'>>, 'EXP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Exp'>>, 'EXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Explode'>>, 'EXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ExplodeOuter'>>, 'EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Extract'>>, 'FIRST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.First'>>, 'FIRST_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FirstValue'>>, 'FLATTEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Flatten'>>, 'FLOOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Floor'>>, 'FROM_BASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase'>>, 'FROM_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase64'>>, 'GENERATE_DATE_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GenerateDateArray'>>, 'GENERATE_SERIES': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GenerateSeries'>>, 'GREATEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Greatest'>>, 'GROUP_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GroupConcat'>>, 'HEX': <function build_hex>, 'HLL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Hll'>>, 'IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'IIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'INITCAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Initcap'>>, 'IS_INF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'ISINF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'IS_NAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'ISNAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'J_S_O_N_ARRAY': <bound method Func.from_arg_list of <class 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method Func.from_arg_list of <class 'sqlglot.expressions.Pow'>>, 'PREDICT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Predict'>>, 'QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quantile'>>, 'QUARTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quarter'>>, 'RAND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'RANDOM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'RANDN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Randn'>>, 'RANGE_N': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RangeN'>>, 'READ_CSV': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ReadCSV'>>, 'REDUCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Reduce'>>, 'REGEXP_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpExtract'>>, 'REGEXP_I_LIKE': <bound method Func.from_arg_list of <class 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"sqlglot.dialects.prql", "qualname": "PRQL.INVERSE_TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.prql.PRQL.ESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.prql.PRQL.ESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.prql", "qualname": "PRQL.ESCAPED_SEQUENCES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{}"}, "sqlglot.dialects.prql.PRQL.QUOTE_START": {"fullname": "sqlglot.dialects.prql.PRQL.QUOTE_START", "modulename": "sqlglot.dialects.prql", "qualname": "PRQL.QUOTE_START", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.prql.PRQL.QUOTE_END": {"fullname": "sqlglot.dialects.prql.PRQL.QUOTE_END", "modulename": "sqlglot.dialects.prql", "qualname": "PRQL.QUOTE_END", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.prql.PRQL.IDENTIFIER_START": {"fullname": "sqlglot.dialects.prql.PRQL.IDENTIFIER_START", "modulename": "sqlglot.dialects.prql", "qualname": "PRQL.IDENTIFIER_START", "kind": "variable", "doc": "<p></p>\n", "default_value": "'`'"}, "sqlglot.dialects.prql.PRQL.IDENTIFIER_END": {"fullname": "sqlglot.dialects.prql.PRQL.IDENTIFIER_END", "modulename": "sqlglot.dialects.prql", "qualname": "PRQL.IDENTIFIER_END", "kind": "variable", "doc": "<p></p>\n", "default_value": "'`'"}, "sqlglot.dialects.prql.PRQL.BIT_START": {"fullname": "sqlglot.dialects.prql.PRQL.BIT_START", "modulename": "sqlglot.dialects.prql", "qualname": "PRQL.BIT_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.prql.PRQL.BIT_END": {"fullname": "sqlglot.dialects.prql.PRQL.BIT_END", "modulename": "sqlglot.dialects.prql", "qualname": "PRQL.BIT_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.prql.PRQL.HEX_START": {"fullname": "sqlglot.dialects.prql.PRQL.HEX_START", "modulename": "sqlglot.dialects.prql", "qualname": "PRQL.HEX_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.prql.PRQL.HEX_END": {"fullname": "sqlglot.dialects.prql.PRQL.HEX_END", "modulename": "sqlglot.dialects.prql", "qualname": "PRQL.HEX_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.prql.PRQL.BYTE_START": {"fullname": "sqlglot.dialects.prql.PRQL.BYTE_START", "modulename": "sqlglot.dialects.prql", "qualname": "PRQL.BYTE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.prql.PRQL.BYTE_END": {"fullname": "sqlglot.dialects.prql.PRQL.BYTE_END", "modulename": "sqlglot.dialects.prql", "qualname": "PRQL.BYTE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.prql.PRQL.UNICODE_START": {"fullname": "sqlglot.dialects.prql.PRQL.UNICODE_START", "modulename": "sqlglot.dialects.prql", "qualname": "PRQL.UNICODE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.prql.PRQL.UNICODE_END": {"fullname": "sqlglot.dialects.prql.PRQL.UNICODE_END", "modulename": "sqlglot.dialects.prql", "qualname": "PRQL.UNICODE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.redshift": {"fullname": "sqlglot.dialects.redshift", "modulename": "sqlglot.dialects.redshift", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.dialects.redshift.Redshift": {"fullname": "sqlglot.dialects.redshift.Redshift", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.postgres.Postgres"}, "sqlglot.dialects.redshift.Redshift.NORMALIZATION_STRATEGY": {"fullname": "sqlglot.dialects.redshift.Redshift.NORMALIZATION_STRATEGY", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.NORMALIZATION_STRATEGY", "kind": "variable", "doc": "<p>Specifies the strategy according to which identifiers should be normalized.</p>\n", "default_value": "<NormalizationStrategy.CASE_INSENSITIVE: 'CASE_INSENSITIVE'>"}, "sqlglot.dialects.redshift.Redshift.SUPPORTS_USER_DEFINED_TYPES": {"fullname": "sqlglot.dialects.redshift.Redshift.SUPPORTS_USER_DEFINED_TYPES", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.SUPPORTS_USER_DEFINED_TYPES", "kind": "variable", "doc": "<p>Whether user-defined data types are supported.</p>\n", "default_value": "False"}, "sqlglot.dialects.redshift.Redshift.INDEX_OFFSET": {"fullname": "sqlglot.dialects.redshift.Redshift.INDEX_OFFSET", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.INDEX_OFFSET", "kind": "variable", "doc": "<p>The base index offset for arrays.</p>\n", "default_value": "0"}, "sqlglot.dialects.redshift.Redshift.COPY_PARAMS_ARE_CSV": {"fullname": "sqlglot.dialects.redshift.Redshift.COPY_PARAMS_ARE_CSV", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.COPY_PARAMS_ARE_CSV", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.redshift.Redshift.HEX_LOWERCASE": {"fullname": "sqlglot.dialects.redshift.Redshift.HEX_LOWERCASE", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.HEX_LOWERCASE", "kind": "variable", "doc": "<p>Whether the <code>HEX</code> function returns a lowercase hexadecimal string.</p>\n", "default_value": "True"}, "sqlglot.dialects.redshift.Redshift.TIME_FORMAT": {"fullname": "sqlglot.dialects.redshift.Redshift.TIME_FORMAT", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.TIME_FORMAT", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'YYYY-MM-DD HH:MI:SS'""}, "sqlglot.dialects.redshift.Redshift.TIME_MAPPING": {"fullname": "sqlglot.dialects.redshift.Redshift.TIME_MAPPING", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.TIME_MAPPING", "kind": "variable", "doc": "<p>Associates this dialect's time formats with their equivalent Python <code>strftime</code> formats.</p>\n", "annotation": ": Dict[str, str]", "default_value": "{'AM': '%p', 'PM': '%p', 'D': '%u', 'DD': '%d', 'DDD': '%j', 'FMDD': '%-d', 'FMDDD': '%-j', 'FMHH12': '%-I', 'FMHH24': '%-H', 'FMMI': '%-M', 'FMMM': '%-m', 'FMSS': '%-S', 'HH12': '%I', 'HH24': '%H', 'MI': '%M', 'MM': '%m', 'OF': '%z', 'SS': '%S', 'TMDay': '%A', 'TMDy': '%a', 'TMMon': '%b', 'TMMonth': '%B', 'TZ': '%Z', 'US': '%f', 'WW': '%U', 'YY': '%y', 'YYYY': '%Y', 'MON': '%b', 'HH': '%H'}"}, "sqlglot.dialects.redshift.Redshift.Parser": {"fullname": "sqlglot.dialects.redshift.Redshift.Parser", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Parser", "kind": "class", "doc": "<p>Parser consumes a list of tokens produced by the Tokenizer and produces a parsed syntax tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>error_level:</strong> The desired error level.\nDefault: ErrorLevel.IMMEDIATE</li>\n<li><strong>error_message_context:</strong> The amount of context to capture from a query string when displaying\nthe error message (in number of characters).\nDefault: 100</li>\n<li><strong>max_errors:</strong> Maximum number of error messages to include in a raised ParseError.\nThis is only relevant if error_level is ErrorLevel.RAISE.\nDefault: 3</li>\n</ul>\n", "bases": "sqlglot.dialects.postgres.Postgres.Parser"}, "sqlglot.dialects.redshift.Redshift.Parser.FUNCTIONS": {"fullname": "sqlglot.dialects.redshift.Redshift.Parser.FUNCTIONS", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Parser.FUNCTIONS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ABS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Abs'>>, 'ADD_MONTHS': <function Redshift.Parser.<lambda>>, 'ANONYMOUS_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnonymousAggFunc'>>, 'ANY_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnyValue'>>, 'APPROX_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_COUNT_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'APPROX_TOP_K': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxTopK'>>, 'ARG_MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARGMAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'MAX_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARG_MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARGMIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'MIN_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Array'>>, 'ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAgg'>>, 'ARRAY_ALL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAll'>>, 'ARRAY_ANY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAny'>>, 'ARRAY_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CONSTRUCT_COMPACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConstructCompact'>>, 'ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayContains'>>, 'FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_OVERLAPS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayOverlaps'>>, 'ARRAY_SIZE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_SORT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySort'>>, 'ARRAY_SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySum'>>, 'ARRAY_TO_STRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_JOIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_UNION_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUnionAgg'>>, 'ARRAY_UNIQUE_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUniqueAgg'>>, 'AVG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Avg'>>, 'CASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Case'>>, 'CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cast'>>, 'CAST_TO_STR_TYPE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CastToStrType'>>, 'CBRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cbrt'>>, 'CEIL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CEILING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CHR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'COALESCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'IFNULL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'NVL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'COLLATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Collate'>>, 'COMBINED_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedAggFunc'>>, 'COMBINED_PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedParameterizedAgg'>>, 'CONCAT': <function Parser.<lambda>>, 'CONCAT_WS': <function Parser.<lambda>>, 'CONNECT_BY_ROOT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ConnectByRoot'>>, 'CONVERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Convert'>>, 'CORR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Corr'>>, 'COUNT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Count'>>, 'COUNT_IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COUNTIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COVAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarPop'>>, 'COVAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarSamp'>>, 'CURRENT_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDate'>>, 'CURRENT_DATETIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDatetime'>>, 'CURRENT_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTime'>>, 'CURRENT_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTimestamp'>>, 'CURRENT_USER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentUser'>>, 'DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Date'>>, 'DATE_ADD': <function _build_date_delta.<locals>._builder>, 'DATEDIFF': <function _build_date_delta.<locals>._builder>, 'DATE_DIFF': <function _build_date_delta.<locals>._builder>, 'DATE_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATE_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateStrToDate'>>, 'DATE_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateSub'>>, 'DATE_TO_DATE_STR': <function Parser.<lambda>>, 'DATE_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateToDi'>>, 'DATE_TRUNC': <function build_timestamp_trunc>, 'DATETIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeAdd'>>, 'DATETIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeDiff'>>, 'DATETIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeSub'>>, 'DATETIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeTrunc'>>, 'DAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Day'>>, 'DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAYOFMONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAY_OF_WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAYOFWEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAY_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DAYOFYEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DECODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Decode'>>, 'DI_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DiToDate'>>, 'ENCODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Encode'>>, 'EXP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Exp'>>, 'EXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Explode'>>, 'EXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ExplodeOuter'>>, 'EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Extract'>>, 'FIRST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.First'>>, 'FIRST_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FirstValue'>>, 'FLATTEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Flatten'>>, 'FLOOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Floor'>>, 'FROM_BASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase'>>, 'FROM_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase64'>>, 'GENERATE_DATE_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GenerateDateArray'>>, 'GENERATE_SERIES': <function _build_generate_series>, 'GREATEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Greatest'>>, 'GROUP_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GroupConcat'>>, 'HEX': <function build_hex>, 'HLL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Hll'>>, 'IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'IIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'INITCAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Initcap'>>, 'IS_INF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'ISINF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'IS_NAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'ISNAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'J_S_O_N_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArray'>>, 'J_S_O_N_ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArrayAgg'>>, 'JSON_ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArrayContains'>>, 'JSONB_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONBExtract'>>, 'JSONB_EXTRACT_SCALAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONBExtractScalar'>>, 'JSON_EXTRACT': <function build_extract_json_with_path.<locals>._builder>, 'JSON_EXTRACT_SCALAR': <function build_extract_json_with_path.<locals>._builder>, 'JSON_FORMAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONFormat'>>, 'J_S_O_N_OBJECT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONObject'>>, 'J_S_O_N_OBJECT_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONObjectAgg'>>, 'J_S_O_N_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONTable'>>, 'LAG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lag'>>, 'LAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Last'>>, 'LAST_DAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastDay'>>, 'LAST_DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastDay'>>, 'LAST_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastValue'>>, 'LEAD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lead'>>, 'LEAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Least'>>, 'LEFT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Left'>>, 'LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Length'>>, 'LEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Length'>>, 'LEVENSHTEIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Levenshtein'>>, 'LN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ln'>>, 'LOG': <function build_logarithm>, 'LOGICAL_AND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'BOOL_AND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'BOOLAND_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'LOGICAL_OR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'BOOL_OR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'BOOLOR_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'LOWER': <function build_lower>, 'LCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lower'>>, 'LOWER_HEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LowerHex'>>, 'MD5': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MD5'>>, 'MD5_DIGEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MD5Digest'>>, 'MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Map'>>, 'MAP_FROM_ENTRIES': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MapFromEntries'>>, 'MATCH_AGAINST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MatchAgainst'>>, 'MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Max'>>, 'MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Min'>>, 'MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Month'>>, 'MONTHS_BETWEEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MonthsBetween'>>, 'NEXT_VALUE_FOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NextValueFor'>>, 'NTH_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NthValue'>>, 'NULLIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Nullif'>>, 'NUMBER_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NumberToStr'>>, 'NVL2': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Nvl2'>>, 'OPEN_J_S_O_N': <bound method Func.from_arg_list of <class 'sqlglot.expressions.OpenJSON'>>, 'PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParameterizedAgg'>>, 'PARSE_JSON': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParseJSON'>>, 'JSON_PARSE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParseJSON'>>, 'PERCENTILE_CONT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PercentileCont'>>, 'PERCENTILE_DISC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PercentileDisc'>>, 'POSEXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Posexplode'>>, 'POSEXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PosexplodeOuter'>>, 'POWER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Pow'>>, 'POW': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Pow'>>, 'PREDICT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Predict'>>, 'QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quantile'>>, 'QUARTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quarter'>>, 'RAND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'RANDOM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'RANDN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Randn'>>, 'RANGE_N': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RangeN'>>, 'READ_CSV': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ReadCSV'>>, 'REDUCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Reduce'>>, 'REGEXP_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpExtract'>>, 'REGEXP_I_LIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpILike'>>, 'REGEXP_LIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpLike'>>, 'REGEXP_REPLACE': <function _build_regexp_replace>, 'REGEXP_SPLIT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpSplit'>>, 'REPEAT': <bound method Func.from_arg_list of <class 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method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'TIME_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToDate'>>, 'TIME_STR_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToTime'>>, 'TIME_STR_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToUnix'>>, 'TIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeSub'>>, 'TIME_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeToStr'>>, 'TIME_TO_TIME_STR': <function Parser.<lambda>>, 'TIME_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeToUnix'>>, 'TIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeTrunc'>>, 'TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Timestamp'>>, 'TIMESTAMP_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampAdd'>>, 'TIMESTAMPDIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampDiff'>>, 'TIMESTAMP_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampDiff'>>, 'TIMESTAMP_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampFromParts'>>, 'TIMESTAMPFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampFromParts'>>, 'TIMESTAMP_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampSub'>>, 'TIMESTAMP_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampTrunc'>>, 'TO_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToArray'>>, 'TO_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToBase64'>>, 'TO_CHAR': <function build_formatted_time.<locals>._builder>, 'TO_DAYS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToDays'>>, 'TO_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToMap'>>, 'TO_NUMBER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToNumber'>>, 'TRANSFORM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Transform'>>, 'TRIM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Trim'>>, 'TRY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Try'>>, 'TRY_CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TryCast'>>, 'TS_OR_DI_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDiToDi'>>, 'TS_OR_DS_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsAdd'>>, 'TS_OR_DS_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsDiff'>>, 'TS_OR_DS_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToDate'>>, 'TS_OR_DS_TO_DATE_STR': <function Parser.<lambda>>, 'TS_OR_DS_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTime'>>, 'TS_OR_DS_TO_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTimestamp'>>, 'UNHEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Unhex'>>, 'UNIX_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixDate'>>, 'UNIX_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToStr'>>, 'UNIX_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTime'>>, 'UNIX_TO_TIME_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTimeStr'>>, 'UPPER': <function build_upper>, 'UCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Upper'>>, 'VAR_MAP': <function build_var_map>, 'VARIANCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'VAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Week'>>, 'WEEK_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.WeekOfYear'>>, 'WEEKOFYEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.WeekOfYear'>>, 'WHEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.When'>>, 'X_M_L_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.XMLTable'>>, 'XOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Xor'>>, 'YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Year'>>, 'GLOB': <function Parser.<lambda>>, 'JSON_EXTRACT_PATH_TEXT': <function build_json_extract_path.<locals>._builder>, 'LIKE': <function build_like>, 'LOG2': <function Parser.<lambda>>, 'LOG10': <function Parser.<lambda>>, 'MOD': <function build_mod>, 'TO_HEX': <function build_hex>, 'JSON_EXTRACT_PATH': <function build_json_extract_path.<locals>._builder>, 'MAKE_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'MAKE_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampFromParts'>>, 'NOW': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTimestamp'>>, 'TO_TIMESTAMP': <function _build_to_timestamp>, 'UNNEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Explode'>>, 'DATEADD': <function _build_date_delta.<locals>._builder>, 'GETDATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTimestamp'>>, 'LISTAGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GroupConcat'>>, 'STRTOL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase'>>}"}, "sqlglot.dialects.redshift.Redshift.Parser.NO_PAREN_FUNCTION_PARSERS": {"fullname": "sqlglot.dialects.redshift.Redshift.Parser.NO_PAREN_FUNCTION_PARSERS", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Parser.NO_PAREN_FUNCTION_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ANY': <function Parser.<lambda>>, 'CASE': <function Parser.<lambda>>, 'IF': <function Parser.<lambda>>, 'NEXT': <function Parser.<lambda>>, 'APPROXIMATE': <function Redshift.Parser.<lambda>>, 'SYSDATE': <function Redshift.Parser.<lambda>>}"}, "sqlglot.dialects.redshift.Redshift.Parser.SUPPORTS_IMPLICIT_UNNEST": {"fullname": "sqlglot.dialects.redshift.Redshift.Parser.SUPPORTS_IMPLICIT_UNNEST", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Parser.SUPPORTS_IMPLICIT_UNNEST", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.redshift.Redshift.Parser.SHOW_TRIE": {"fullname": "sqlglot.dialects.redshift.Redshift.Parser.SHOW_TRIE", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Parser.SHOW_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.redshift.Redshift.Parser.SET_TRIE": {"fullname": "sqlglot.dialects.redshift.Redshift.Parser.SET_TRIE", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Parser.SET_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'GLOBAL': {0: True}, 'LOCAL': {0: True}, 'SESSION': {0: True}, 'TRANSACTION': {0: True}}"}, "sqlglot.dialects.redshift.Redshift.Tokenizer": {"fullname": "sqlglot.dialects.redshift.Redshift.Tokenizer", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Tokenizer", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.postgres.Postgres.Tokenizer"}, "sqlglot.dialects.redshift.Redshift.Tokenizer.BIT_STRINGS": {"fullname": "sqlglot.dialects.redshift.Redshift.Tokenizer.BIT_STRINGS", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Tokenizer.BIT_STRINGS", "kind": "variable", "doc": "<p></p>\n", "default_value": "[]"}, "sqlglot.dialects.redshift.Redshift.Tokenizer.HEX_STRINGS": {"fullname": "sqlglot.dialects.redshift.Redshift.Tokenizer.HEX_STRINGS", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Tokenizer.HEX_STRINGS", "kind": "variable", "doc": "<p></p>\n", "default_value": "[]"}, "sqlglot.dialects.redshift.Redshift.Tokenizer.STRING_ESCAPES": {"fullname": "sqlglot.dialects.redshift.Redshift.Tokenizer.STRING_ESCAPES", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Tokenizer.STRING_ESCAPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "['\\\\', "'"]"}, "sqlglot.dialects.redshift.Redshift.Tokenizer.KEYWORDS": {"fullname": "sqlglot.dialects.redshift.Redshift.Tokenizer.KEYWORDS", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Tokenizer.KEYWORDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'{%': <TokenType.BLOCK_START: 'BLOCK_START'>, '{%+': <TokenType.BLOCK_START: 'BLOCK_START'>, '{%-': <TokenType.BLOCK_START: 'BLOCK_START'>, '%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '+%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '-%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '{{+': <TokenType.BLOCK_START: 'BLOCK_START'>, '{{-': <TokenType.BLOCK_START: 'BLOCK_START'>, '+}}': <TokenType.BLOCK_END: 'BLOCK_END'>, '-}}': <TokenType.BLOCK_END: 'BLOCK_END'>, '/*+': <TokenType.HINT: 'HINT'>, '==': <TokenType.EQ: 'EQ'>, '::': <TokenType.DCOLON: 'DCOLON'>, '||': <TokenType.DPIPE: 'DPIPE'>, '>=': <TokenType.GTE: 'GTE'>, '<=': <TokenType.LTE: 'LTE'>, '<>': <TokenType.NEQ: 'NEQ'>, '!=': <TokenType.NEQ: 'NEQ'>, ':=': <TokenType.COLON_EQ: 'COLON_EQ'>, '<=>': <TokenType.NULLSAFE_EQ: 'NULLSAFE_EQ'>, '->': <TokenType.ARROW: 'ARROW'>, '->>': <TokenType.DARROW: 'DARROW'>, '=>': <TokenType.FARROW: 'FARROW'>, '#>': <TokenType.HASH_ARROW: 'HASH_ARROW'>, '#>>': <TokenType.DHASH_ARROW: 'DHASH_ARROW'>, '<->': <TokenType.LR_ARROW: 'LR_ARROW'>, '&&': <TokenType.DAMP: 'DAMP'>, '??': <TokenType.DQMARK: 'DQMARK'>, 'ALL': <TokenType.ALL: 'ALL'>, 'ALWAYS': <TokenType.ALWAYS: 'ALWAYS'>, 'AND': <TokenType.AND: 'AND'>, 'ANTI': <TokenType.ANTI: 'ANTI'>, 'ANY': <TokenType.ANY: 'ANY'>, 'ASC': <TokenType.ASC: 'ASC'>, 'AS': <TokenType.ALIAS: 'ALIAS'>, 'ASOF': <TokenType.ASOF: 'ASOF'>, 'AUTOINCREMENT': <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, 'AUTO_INCREMENT': <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, 'BEGIN': <TokenType.COMMAND: 'COMMAND'>, 'BETWEEN': <TokenType.BETWEEN: 'BETWEEN'>, 'CACHE': <TokenType.CACHE: 'CACHE'>, 'UNCACHE': <TokenType.UNCACHE: 'UNCACHE'>, 'CASE': <TokenType.CASE: 'CASE'>, 'CHARACTER SET': <TokenType.CHARACTER_SET: 'CHARACTER_SET'>, 'CLUSTER BY': <TokenType.CLUSTER_BY: 'CLUSTER_BY'>, 'COLLATE': <TokenType.COLLATE: 'COLLATE'>, 'COLUMN': <TokenType.COLUMN: 'COLUMN'>, 'COMMIT': <TokenType.COMMIT: 'COMMIT'>, 'CONNECT BY': <TokenType.CONNECT_BY: 'CONNECT_BY'>, 'CONSTRAINT': <TokenType.CONSTRAINT: 'CONSTRAINT'>, 'COPY': <TokenType.COPY: 'COPY'>, 'CREATE': <TokenType.CREATE: 'CREATE'>, 'CROSS': <TokenType.CROSS: 'CROSS'>, 'CUBE': <TokenType.CUBE: 'CUBE'>, 'CURRENT_DATE': <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, 'CURRENT_TIME': <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, 'CURRENT_TIMESTAMP': <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, 'CURRENT_USER': <TokenType.CURRENT_USER: 'CURRENT_USER'>, 'DATABASE': <TokenType.DATABASE: 'DATABASE'>, 'DEFAULT': <TokenType.DEFAULT: 'DEFAULT'>, 'DELETE': <TokenType.DELETE: 'DELETE'>, 'DESC': <TokenType.DESC: 'DESC'>, 'DESCRIBE': <TokenType.DESCRIBE: 'DESCRIBE'>, 'DISTINCT': <TokenType.DISTINCT: 'DISTINCT'>, 'DISTRIBUTE BY': <TokenType.DISTRIBUTE_BY: 'DISTRIBUTE_BY'>, 'DIV': <TokenType.DIV: 'DIV'>, 'DROP': <TokenType.DROP: 'DROP'>, 'ELSE': <TokenType.ELSE: 'ELSE'>, 'END': <TokenType.END: 'END'>, 'ENUM': <TokenType.ENUM: 'ENUM'>, 'ESCAPE': <TokenType.ESCAPE: 'ESCAPE'>, 'EXCEPT': <TokenType.EXCEPT: 'EXCEPT'>, 'EXECUTE': <TokenType.EXECUTE: 'EXECUTE'>, 'EXISTS': <TokenType.EXISTS: 'EXISTS'>, 'FALSE': <TokenType.FALSE: 'FALSE'>, 'FETCH': <TokenType.FETCH: 'FETCH'>, 'FILTER': <TokenType.FILTER: 'FILTER'>, 'FIRST': <TokenType.FIRST: 'FIRST'>, 'FULL': <TokenType.FULL: 'FULL'>, 'FUNCTION': <TokenType.FUNCTION: 'FUNCTION'>, 'FOR': <TokenType.FOR: 'FOR'>, 'FOREIGN KEY': <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, 'FORMAT': <TokenType.FORMAT: 'FORMAT'>, 'FROM': <TokenType.FROM: 'FROM'>, 'GEOGRAPHY': <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, 'GEOMETRY': <TokenType.GEOMETRY: 'GEOMETRY'>, 'GLOB': <TokenType.GLOB: 'GLOB'>, 'GROUP BY': <TokenType.GROUP_BY: 'GROUP_BY'>, 'GROUPING SETS': <TokenType.GROUPING_SETS: 'GROUPING_SETS'>, 'HAVING': <TokenType.HAVING: 'HAVING'>, 'ILIKE': <TokenType.ILIKE: 'ILIKE'>, 'IN': <TokenType.IN: 'IN'>, 'INDEX': <TokenType.INDEX: 'INDEX'>, 'INET': <TokenType.INET: 'INET'>, 'INNER': <TokenType.INNER: 'INNER'>, 'INSERT': <TokenType.INSERT: 'INSERT'>, 'INTERVAL': <TokenType.INTERVAL: 'INTERVAL'>, 'INTERSECT': <TokenType.INTERSECT: 'INTERSECT'>, 'INTO': <TokenType.INTO: 'INTO'>, 'IS': <TokenType.IS: 'IS'>, 'ISNULL': <TokenType.ISNULL: 'ISNULL'>, 'JOIN': <TokenType.JOIN: 'JOIN'>, 'KEEP': <TokenType.KEEP: 'KEEP'>, 'KILL': <TokenType.KILL: 'KILL'>, 'LATERAL': <TokenType.LATERAL: 'LATERAL'>, 'LEFT': <TokenType.LEFT: 'LEFT'>, 'LIKE': <TokenType.LIKE: 'LIKE'>, 'LIMIT': <TokenType.LIMIT: 'LIMIT'>, 'LOAD': <TokenType.LOAD: 'LOAD'>, 'LOCK': <TokenType.LOCK: 'LOCK'>, 'MERGE': <TokenType.MERGE: 'MERGE'>, 'NATURAL': <TokenType.NATURAL: 'NATURAL'>, 'NEXT': <TokenType.NEXT: 'NEXT'>, 'NOT': <TokenType.NOT: 'NOT'>, 'NOTNULL': <TokenType.NOTNULL: 'NOTNULL'>, 'NULL': <TokenType.NULL: 'NULL'>, 'OBJECT': <TokenType.OBJECT: 'OBJECT'>, 'OFFSET': <TokenType.OFFSET: 'OFFSET'>, 'ON': <TokenType.ON: 'ON'>, 'OR': <TokenType.OR: 'OR'>, 'XOR': <TokenType.XOR: 'XOR'>, 'ORDER BY': <TokenType.ORDER_BY: 'ORDER_BY'>, 'ORDINALITY': <TokenType.ORDINALITY: 'ORDINALITY'>, 'OUTER': <TokenType.OUTER: 'OUTER'>, 'OVER': <TokenType.OVER: 'OVER'>, 'OVERLAPS': <TokenType.OVERLAPS: 'OVERLAPS'>, 'OVERWRITE': <TokenType.OVERWRITE: 'OVERWRITE'>, 'PARTITION': <TokenType.PARTITION: 'PARTITION'>, 'PARTITION BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PARTITIONED BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PARTITIONED_BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PERCENT': <TokenType.PERCENT: 'PERCENT'>, 'PIVOT': <TokenType.PIVOT: 'PIVOT'>, 'PRAGMA': <TokenType.PRAGMA: 'PRAGMA'>, 'PRIMARY KEY': <TokenType.PRIMARY_KEY: 'PRIMARY_KEY'>, 'PROCEDURE': <TokenType.PROCEDURE: 'PROCEDURE'>, 'QUALIFY': <TokenType.QUALIFY: 'QUALIFY'>, 'RANGE': <TokenType.RANGE: 'RANGE'>, 'RECURSIVE': <TokenType.RECURSIVE: 'RECURSIVE'>, 'REGEXP': <TokenType.RLIKE: 'RLIKE'>, 'REPLACE': <TokenType.REPLACE: 'REPLACE'>, 'RETURNING': <TokenType.RETURNING: 'RETURNING'>, 'REFERENCES': <TokenType.REFERENCES: 'REFERENCES'>, 'RIGHT': <TokenType.RIGHT: 'RIGHT'>, 'RLIKE': <TokenType.RLIKE: 'RLIKE'>, 'ROLLBACK': <TokenType.ROLLBACK: 'ROLLBACK'>, 'ROLLUP': <TokenType.ROLLUP: 'ROLLUP'>, 'ROW': <TokenType.ROW: 'ROW'>, 'ROWS': <TokenType.ROWS: 'ROWS'>, 'SCHEMA': <TokenType.SCHEMA: 'SCHEMA'>, 'SELECT': <TokenType.SELECT: 'SELECT'>, 'SEMI': <TokenType.SEMI: 'SEMI'>, 'SET': <TokenType.SET: 'SET'>, 'SETTINGS': <TokenType.SETTINGS: 'SETTINGS'>, 'SHOW': <TokenType.SHOW: 'SHOW'>, 'SIMILAR TO': <TokenType.SIMILAR_TO: 'SIMILAR_TO'>, 'SOME': <TokenType.SOME: 'SOME'>, 'SORT BY': <TokenType.SORT_BY: 'SORT_BY'>, 'START WITH': <TokenType.START_WITH: 'START_WITH'>, 'TABLE': <TokenType.TABLE: 'TABLE'>, 'TABLESAMPLE': <TokenType.TABLE_SAMPLE: 'TABLE_SAMPLE'>, 'TEMP': <TokenType.TEMPORARY: 'TEMPORARY'>, 'TEMPORARY': <TokenType.TEMPORARY: 'TEMPORARY'>, 'THEN': <TokenType.THEN: 'THEN'>, 'TRUE': <TokenType.TRUE: 'TRUE'>, 'TRUNCATE': <TokenType.TRUNCATE: 'TRUNCATE'>, 'UNION': <TokenType.UNION: 'UNION'>, 'UNKNOWN': <TokenType.UNKNOWN: 'UNKNOWN'>, 'UNNEST': <TokenType.UNNEST: 'UNNEST'>, 'UNPIVOT': <TokenType.UNPIVOT: 'UNPIVOT'>, 'UPDATE': <TokenType.UPDATE: 'UPDATE'>, 'USE': <TokenType.USE: 'USE'>, 'USING': <TokenType.USING: 'USING'>, 'UUID': <TokenType.UUID: 'UUID'>, 'VIEW': <TokenType.VIEW: 'VIEW'>, 'VOLATILE': <TokenType.VOLATILE: 'VOLATILE'>, 'WHEN': <TokenType.WHEN: 'WHEN'>, 'WHERE': <TokenType.WHERE: 'WHERE'>, 'WINDOW': <TokenType.WINDOW: 'WINDOW'>, 'WITH': <TokenType.WITH: 'WITH'>, 'APPLY': <TokenType.APPLY: 'APPLY'>, 'ARRAY': <TokenType.ARRAY: 'ARRAY'>, 'BIT': <TokenType.BIT: 'BIT'>, 'BOOL': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BOOLEAN': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BYTE': <TokenType.TINYINT: 'TINYINT'>, 'MEDIUMINT': <TokenType.MEDIUMINT: 'MEDIUMINT'>, 'INT1': <TokenType.TINYINT: 'TINYINT'>, 'TINYINT': <TokenType.TINYINT: 'TINYINT'>, 'INT16': <TokenType.SMALLINT: 'SMALLINT'>, 'SHORT': <TokenType.SMALLINT: 'SMALLINT'>, 'SMALLINT': <TokenType.SMALLINT: 'SMALLINT'>, 'INT128': <TokenType.INT128: 'INT128'>, 'HUGEINT': <TokenType.INT128: 'INT128'>, 'INT2': <TokenType.SMALLINT: 'SMALLINT'>, 'INTEGER': <TokenType.INT: 'INT'>, 'INT': <TokenType.INT: 'INT'>, 'INT4': <TokenType.INT: 'INT'>, 'INT32': <TokenType.INT: 'INT'>, 'INT64': <TokenType.BIGINT: 'BIGINT'>, 'LONG': <TokenType.BIGINT: 'BIGINT'>, 'BIGINT': <TokenType.BIGINT: 'BIGINT'>, 'INT8': <TokenType.BIGINT: 'BIGINT'>, 'UINT': <TokenType.UINT: 'UINT'>, 'DEC': <TokenType.DECIMAL: 'DECIMAL'>, 'DECIMAL': <TokenType.DECIMAL: 'DECIMAL'>, 'BIGDECIMAL': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'BIGNUMERIC': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'MAP': <TokenType.MAP: 'MAP'>, 'NULLABLE': <TokenType.NULLABLE: 'NULLABLE'>, 'NUMBER': <TokenType.DECIMAL: 'DECIMAL'>, 'NUMERIC': <TokenType.DECIMAL: 'DECIMAL'>, 'FIXED': <TokenType.DECIMAL: 'DECIMAL'>, 'REAL': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT4': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT8': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE PRECISION': <TokenType.DOUBLE: 'DOUBLE'>, 'JSON': <TokenType.JSON: 'JSON'>, 'CHAR': <TokenType.CHAR: 'CHAR'>, 'CHARACTER': <TokenType.CHAR: 'CHAR'>, 'NCHAR': <TokenType.NCHAR: 'NCHAR'>, 'VARCHAR': <TokenType.VARCHAR: 'VARCHAR'>, 'VARCHAR2': <TokenType.VARCHAR: 'VARCHAR'>, 'NVARCHAR': <TokenType.NVARCHAR: 'NVARCHAR'>, 'NVARCHAR2': <TokenType.NVARCHAR: 'NVARCHAR'>, 'BPCHAR': <TokenType.BPCHAR: 'BPCHAR'>, 'STR': <TokenType.TEXT: 'TEXT'>, 'STRING': <TokenType.TEXT: 'TEXT'>, 'TEXT': <TokenType.TEXT: 'TEXT'>, 'LONGTEXT': <TokenType.LONGTEXT: 'LONGTEXT'>, 'MEDIUMTEXT': <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, 'TINYTEXT': <TokenType.TINYTEXT: 'TINYTEXT'>, 'CLOB': <TokenType.TEXT: 'TEXT'>, 'LONGVARCHAR': <TokenType.TEXT: 'TEXT'>, 'BINARY': <TokenType.BINARY: 'BINARY'>, 'BLOB': <TokenType.VARBINARY: 'VARBINARY'>, 'LONGBLOB': <TokenType.LONGBLOB: 'LONGBLOB'>, 'MEDIUMBLOB': <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, 'TINYBLOB': <TokenType.TINYBLOB: 'TINYBLOB'>, 'BYTEA': <TokenType.VARBINARY: 'VARBINARY'>, 'VARBINARY': <TokenType.VARBINARY: 'VARBINARY'>, 'TIME': <TokenType.TIME: 'TIME'>, 'TIMETZ': <TokenType.TIMETZ: 'TIMETZ'>, 'TIMESTAMP': <TokenType.TIMESTAMP: 'TIMESTAMP'>, 'TIMESTAMPTZ': <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, 'TIMESTAMPLTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMP_LTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMPNTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'TIMESTAMP_NTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'DATE': <TokenType.DATE: 'DATE'>, 'DATETIME': <TokenType.DATETIME: 'DATETIME'>, 'INT4RANGE': <TokenType.INT4RANGE: 'INT4RANGE'>, 'INT4MULTIRANGE': <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, 'INT8RANGE': <TokenType.INT8RANGE: 'INT8RANGE'>, 'INT8MULTIRANGE': <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, 'NUMRANGE': <TokenType.NUMRANGE: 'NUMRANGE'>, 'NUMMULTIRANGE': <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, 'TSRANGE': <TokenType.TSRANGE: 'TSRANGE'>, 'TSMULTIRANGE': <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, 'TSTZRANGE': <TokenType.TSTZRANGE: 'TSTZRANGE'>, 'TSTZMULTIRANGE': <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, 'DATERANGE': <TokenType.DATERANGE: 'DATERANGE'>, 'DATEMULTIRANGE': <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, 'UNIQUE': <TokenType.UNIQUE: 'UNIQUE'>, 'STRUCT': <TokenType.STRUCT: 'STRUCT'>, 'SEQUENCE': <TokenType.SEQUENCE: 'SEQUENCE'>, 'VARIANT': <TokenType.VARIANT: 'VARIANT'>, 'ALTER': <TokenType.ALTER: 'ALTER'>, 'ANALYZE': <TokenType.COMMAND: 'COMMAND'>, 'CALL': <TokenType.COMMAND: 'COMMAND'>, 'COMMENT': <TokenType.COMMENT: 'COMMENT'>, 'EXPLAIN': <TokenType.COMMAND: 'COMMAND'>, 'GRANT': <TokenType.COMMAND: 'COMMAND'>, 'OPTIMIZE': <TokenType.COMMAND: 'COMMAND'>, 'PREPARE': <TokenType.COMMAND: 'COMMAND'>, 'VACUUM': <TokenType.COMMAND: 'COMMAND'>, 'USER-DEFINED': <TokenType.USERDEFINED: 'USERDEFINED'>, 'FOR VERSION': <TokenType.VERSION_SNAPSHOT: 'VERSION_SNAPSHOT'>, 'FOR TIMESTAMP': <TokenType.TIMESTAMP_SNAPSHOT: 'TIMESTAMP_SNAPSHOT'>, '~~': <TokenType.LIKE: 'LIKE'>, '~~*': <TokenType.ILIKE: 'ILIKE'>, '~*': <TokenType.IRLIKE: 'IRLIKE'>, '~': <TokenType.RLIKE: 'RLIKE'>, '@@': <TokenType.DAT: 'DAT'>, '@>': <TokenType.AT_GT: 'AT_GT'>, '<@': <TokenType.LT_AT: 'LT_AT'>, '|/': <TokenType.PIPE_SLASH: 'PIPE_SLASH'>, '||/': <TokenType.DPIPE_SLASH: 'DPIPE_SLASH'>, 'BEGIN TRANSACTION': <TokenType.BEGIN: 'BEGIN'>, 'BIGSERIAL': <TokenType.BIGSERIAL: 'BIGSERIAL'>, 'CHARACTER VARYING': <TokenType.VARCHAR: 'VARCHAR'>, 'CONSTRAINT TRIGGER': <TokenType.COMMAND: 'COMMAND'>, 'CSTRING': <TokenType.PSEUDO_TYPE: 'PSEUDO_TYPE'>, 'DECLARE': <TokenType.COMMAND: 'COMMAND'>, 'DO': <TokenType.COMMAND: 'COMMAND'>, 'EXEC': <TokenType.COMMAND: 'COMMAND'>, 'HSTORE': <TokenType.HSTORE: 'HSTORE'>, 'JSONB': <TokenType.JSONB: 'JSONB'>, 'MONEY': <TokenType.MONEY: 'MONEY'>, 'NAME': <TokenType.NAME: 'NAME'>, 'OID': <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, 'ONLY': <TokenType.ONLY: 'ONLY'>, 'OPERATOR': <TokenType.OPERATOR: 'OPERATOR'>, 'REFRESH': <TokenType.COMMAND: 'COMMAND'>, 'REINDEX': <TokenType.COMMAND: 'COMMAND'>, 'RESET': <TokenType.COMMAND: 'COMMAND'>, 'REVOKE': <TokenType.COMMAND: 'COMMAND'>, 'SERIAL': <TokenType.SERIAL: 'SERIAL'>, 'SMALLSERIAL': <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, 'REGCLASS': <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, 'REGCOLLATION': <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, 'REGCONFIG': <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, 'REGDICTIONARY': <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, 'REGNAMESPACE': <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, 'REGOPER': <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, 'REGOPERATOR': <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, 'REGPROC': <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, 'REGPROCEDURE': <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, 'REGROLE': <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, 'REGTYPE': <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, 'HLLSKETCH': <TokenType.HLLSKETCH: 'HLLSKETCH'>, 'SUPER': <TokenType.SUPER: 'SUPER'>, 'TOP': <TokenType.TOP: 'TOP'>, 'UNLOAD': <TokenType.COMMAND: 'COMMAND'>, 'VARBYTE': <TokenType.VARBINARY: 'VARBINARY'>}"}, "sqlglot.dialects.redshift.Redshift.Tokenizer.SINGLE_TOKENS": {"fullname": "sqlglot.dialects.redshift.Redshift.Tokenizer.SINGLE_TOKENS", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Tokenizer.SINGLE_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'(': <TokenType.L_PAREN: 'L_PAREN'>, ')': <TokenType.R_PAREN: 'R_PAREN'>, '[': <TokenType.L_BRACKET: 'L_BRACKET'>, ']': <TokenType.R_BRACKET: 'R_BRACKET'>, '{': <TokenType.L_BRACE: 'L_BRACE'>, '}': <TokenType.R_BRACE: 'R_BRACE'>, '&': <TokenType.AMP: 'AMP'>, '^': <TokenType.CARET: 'CARET'>, ':': <TokenType.COLON: 'COLON'>, ',': <TokenType.COMMA: 'COMMA'>, '.': <TokenType.DOT: 'DOT'>, '-': <TokenType.DASH: 'DASH'>, '=': <TokenType.EQ: 'EQ'>, '>': <TokenType.GT: 'GT'>, '<': <TokenType.LT: 'LT'>, '%': <TokenType.MOD: 'MOD'>, '!': <TokenType.NOT: 'NOT'>, '|': <TokenType.PIPE: 'PIPE'>, '+': <TokenType.PLUS: 'PLUS'>, ';': <TokenType.SEMICOLON: 'SEMICOLON'>, '/': <TokenType.SLASH: 'SLASH'>, '\\\\': <TokenType.BACKSLASH: 'BACKSLASH'>, '*': <TokenType.STAR: 'STAR'>, '~': <TokenType.TILDA: 'TILDA'>, '?': <TokenType.PLACEHOLDER: 'PLACEHOLDER'>, '@': <TokenType.PARAMETER: 'PARAMETER'>, "'": <TokenType.UNKNOWN: 'UNKNOWN'>, '`': <TokenType.UNKNOWN: 'UNKNOWN'>, '"': <TokenType.UNKNOWN: 'UNKNOWN'>, '$': <TokenType.HEREDOC_STRING: 'HEREDOC_STRING'>}"}, "sqlglot.dialects.redshift.Redshift.Generator": {"fullname": "sqlglot.dialects.redshift.Redshift.Generator", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Generator", "kind": "class", "doc": "<p>Generator converts a given syntax tree to the corresponding SQL string.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>pretty:</strong> Whether to format the produced SQL string.\nDefault: False.</li>\n<li><strong>identify:</strong> Determines when an identifier should be quoted. Possible values are:\nFalse (default): Never quote, except in cases where it's mandatory by the dialect.\nTrue or 'always': Always quote.\n'safe': Only quote identifiers that are case insensitive.</li>\n<li><strong>normalize:</strong> Whether to normalize identifiers to lowercase.\nDefault: False.</li>\n<li><strong>pad:</strong> The pad size in a formatted string. For example, this affects the indentation of\na projection in a query, relative to its nesting level.\nDefault: 2.</li>\n<li><strong>indent:</strong> The indentation size in a formatted string. For example, this affects the\nindentation of subqueries and filters under a <code>WHERE</code> clause.\nDefault: 2.</li>\n<li><strong>normalize_functions:</strong> How to normalize function names. Possible values are:\n\"upper\" or True (default): Convert names to uppercase.\n\"lower\": Convert names to lowercase.\nFalse: Disables function name normalization.</li>\n<li><strong>unsupported_level:</strong> Determines the generator's behavior when it encounters unsupported expressions.\nDefault ErrorLevel.WARN.</li>\n<li><strong>max_unsupported:</strong> Maximum number of unsupported messages to include in a raised UnsupportedError.\nThis is only relevant if unsupported_level is ErrorLevel.RAISE.\nDefault: 3</li>\n<li><strong>leading_comma:</strong> Whether the comma is leading or trailing in select expressions.\nThis is only relevant when generating in pretty mode.\nDefault: False</li>\n<li><strong>max_text_width:</strong> The max number of characters in a segment before creating new lines in pretty mode.\nThe default is on the smaller end because the length only represents a segment and not the true\nline length.\nDefault: 80</li>\n<li><strong>comments:</strong> Whether to preserve comments in the output SQL code.\nDefault: True</li>\n</ul>\n", "bases": "sqlglot.dialects.postgres.Postgres.Generator"}, "sqlglot.dialects.redshift.Redshift.Generator.LOCKING_READS_SUPPORTED": {"fullname": "sqlglot.dialects.redshift.Redshift.Generator.LOCKING_READS_SUPPORTED", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Generator.LOCKING_READS_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.redshift.Redshift.Generator.QUERY_HINTS": {"fullname": "sqlglot.dialects.redshift.Redshift.Generator.QUERY_HINTS", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Generator.QUERY_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.redshift.Redshift.Generator.VALUES_AS_TABLE": {"fullname": "sqlglot.dialects.redshift.Redshift.Generator.VALUES_AS_TABLE", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Generator.VALUES_AS_TABLE", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.redshift.Redshift.Generator.TZ_TO_WITH_TIME_ZONE": {"fullname": "sqlglot.dialects.redshift.Redshift.Generator.TZ_TO_WITH_TIME_ZONE", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Generator.TZ_TO_WITH_TIME_ZONE", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.redshift.Redshift.Generator.NVL2_SUPPORTED": {"fullname": "sqlglot.dialects.redshift.Redshift.Generator.NVL2_SUPPORTED", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Generator.NVL2_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.redshift.Redshift.Generator.LAST_DAY_SUPPORTS_DATE_PART": {"fullname": "sqlglot.dialects.redshift.Redshift.Generator.LAST_DAY_SUPPORTS_DATE_PART", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Generator.LAST_DAY_SUPPORTS_DATE_PART", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.redshift.Redshift.Generator.CAN_IMPLEMENT_ARRAY_ANY": {"fullname": "sqlglot.dialects.redshift.Redshift.Generator.CAN_IMPLEMENT_ARRAY_ANY", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Generator.CAN_IMPLEMENT_ARRAY_ANY", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.redshift.Redshift.Generator.MULTI_ARG_DISTINCT": {"fullname": "sqlglot.dialects.redshift.Redshift.Generator.MULTI_ARG_DISTINCT", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Generator.MULTI_ARG_DISTINCT", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.redshift.Redshift.Generator.COPY_PARAMS_ARE_WRAPPED": {"fullname": "sqlglot.dialects.redshift.Redshift.Generator.COPY_PARAMS_ARE_WRAPPED", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Generator.COPY_PARAMS_ARE_WRAPPED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.redshift.Redshift.Generator.HEX_FUNC": {"fullname": "sqlglot.dialects.redshift.Redshift.Generator.HEX_FUNC", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Generator.HEX_FUNC", "kind": "variable", "doc": "<p></p>\n", "default_value": "'TO_HEX'"}, "sqlglot.dialects.redshift.Redshift.Generator.WITH_PROPERTIES_PREFIX": {"fullname": "sqlglot.dialects.redshift.Redshift.Generator.WITH_PROPERTIES_PREFIX", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Generator.WITH_PROPERTIES_PREFIX", "kind": "variable", "doc": "<p></p>\n", "default_value": "' '"}, "sqlglot.dialects.redshift.Redshift.Generator.TYPE_MAPPING": {"fullname": "sqlglot.dialects.redshift.Redshift.Generator.TYPE_MAPPING", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Generator.TYPE_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.NCHAR: 'NCHAR'>: 'CHAR', <Type.NVARCHAR: 'NVARCHAR'>: 'VARCHAR', <Type.MEDIUMTEXT: 'MEDIUMTEXT'>: 'TEXT', <Type.LONGTEXT: 'LONGTEXT'>: 'TEXT', <Type.TINYTEXT: 'TINYTEXT'>: 'TEXT', <Type.MEDIUMBLOB: 'MEDIUMBLOB'>: 'BLOB', <Type.LONGBLOB: 'LONGBLOB'>: 'BLOB', <Type.TINYBLOB: 'TINYBLOB'>: 'BLOB', <Type.INET: 'INET'>: 'INET', <Type.ROWVERSION: 'ROWVERSION'>: 'VARBYTE', <Type.TINYINT: 'TINYINT'>: 'SMALLINT', <Type.FLOAT: 'FLOAT'>: 'REAL', <Type.DOUBLE: 'DOUBLE'>: 'DOUBLE PRECISION', <Type.BINARY: 'BINARY'>: 'VARBYTE', <Type.VARBINARY: 'VARBINARY'>: 'VARBYTE', <Type.DATETIME: 'DATETIME'>: 'TIMESTAMP', <Type.INT: 'INT'>: 'INTEGER', <Type.TIMETZ: 'TIMETZ'>: 'TIME', <Type.TIMESTAMPTZ: 'TIMESTAMPTZ'>: 'TIMESTAMP'}"}, "sqlglot.dialects.redshift.Redshift.Generator.TRANSFORMS": {"fullname": "sqlglot.dialects.redshift.Redshift.Generator.TRANSFORMS", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Generator.TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.JSONPathKey'>: <function json_path_key_only_name>, <class 'sqlglot.expressions.JSONPathRoot'>: <function Postgres.Generator.<lambda>>, <class 'sqlglot.expressions.JSONPathSubscript'>: <function Postgres.Generator.<lambda>>, <class 'sqlglot.expressions.AllowedValuesProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.BackupProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CaseSpecificColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CollateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DateFormatColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DefaultColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EncodeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EphemeralColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExcludeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExternalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.GlobalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.HeapProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IcebergProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InheritsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InlineLengthColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IntervalSpan'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtract'>: <function json_extract_segments.<locals>._json_extract_segments>, <class 'sqlglot.expressions.JSONExtractScalar'>: <function json_extract_segments.<locals>._json_extract_segments>, <class 'sqlglot.expressions.LanguageProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LocationProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LogProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.MaterializedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NonClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NotForReplicationColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnCommitProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnUpdateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OutputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.PathColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ReturnsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SampleProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetConfigProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SettingsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SharingProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlReadWriteProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlSecurityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StabilityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StrictProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TemporaryProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TitleColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.Timestamp'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransformModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransientProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UppercaseColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UnloggedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VarMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VolatileProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithOperator'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.Array'>: <function Postgres.Generator.<lambda>>, <class 'sqlglot.expressions.ArrayConcat'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ArrayContained'>: <function Postgres.Generator.<lambda>>, <class 'sqlglot.expressions.ArrayContains'>: <function Postgres.Generator.<lambda>>, <class 'sqlglot.expressions.ArrayOverlaps'>: <function Postgres.Generator.<lambda>>, <class 'sqlglot.expressions.ArrayFilter'>: <function filter_array_using_unnest>, <class 'sqlglot.expressions.ArraySize'>: <function Postgres.Generator.<lambda>>, <class 'sqlglot.expressions.BitwiseXor'>: <function Postgres.Generator.<lambda>>, <class 'sqlglot.expressions.ColumnDef'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.CurrentDate'>: <function no_paren_current_date_sql>, <class 'sqlglot.expressions.CurrentTimestamp'>: <function Redshift.Generator.<lambda>>, <class 'sqlglot.expressions.CurrentUser'>: <function Postgres.Generator.<lambda>>, <class 'sqlglot.expressions.DateAdd'>: <function date_delta_sql.<locals>._delta_sql>, <class 'sqlglot.expressions.DateDiff'>: <function date_delta_sql.<locals>._delta_sql>, <class 'sqlglot.expressions.DateStrToDate'>: <function datestrtodate_sql>, <class 'sqlglot.expressions.DataType'>: <function _datatype_sql>, <class 'sqlglot.expressions.DateSub'>: <function _date_add_sql.<locals>.func>, <class 'sqlglot.expressions.Explode'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.GroupConcat'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.JSONBExtract'>: <function Postgres.Generator.<lambda>>, <class 'sqlglot.expressions.JSONBExtractScalar'>: <function Postgres.Generator.<lambda>>, <class 'sqlglot.expressions.JSONBContains'>: <function Postgres.Generator.<lambda>>, <class 'sqlglot.expressions.ParseJSON'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.LogicalOr'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.LogicalAnd'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.Max'>: <function max_or_greatest>, <class 'sqlglot.expressions.MapFromEntries'>: <function no_map_from_entries_sql>, <class 'sqlglot.expressions.Min'>: <function min_or_least>, <class 'sqlglot.expressions.Merge'>: <function merge_without_target_sql>, <class 'sqlglot.expressions.PartitionedByProperty'>: <function Postgres.Generator.<lambda>>, <class 'sqlglot.expressions.PercentileCont'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.PercentileDisc'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.Rand'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.RegexpLike'>: <function Postgres.Generator.<lambda>>, <class 'sqlglot.expressions.RegexpILike'>: <function Postgres.Generator.<lambda>>, <class 'sqlglot.expressions.Select'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.StrPosition'>: <function str_position_sql>, <class 'sqlglot.expressions.StrToDate'>: <function Postgres.Generator.<lambda>>, <class 'sqlglot.expressions.StrToTime'>: <function Postgres.Generator.<lambda>>, <class 'sqlglot.expressions.StructExtract'>: <function struct_extract_sql>, <class 'sqlglot.expressions.Substring'>: <function _substring_sql>, <class 'sqlglot.expressions.TimeFromParts'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.TimestampFromParts'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.TimestampTrunc'>: <function timestamptrunc_sql.<locals>._timestamptrunc_sql>, <class 'sqlglot.expressions.TimeStrToTime'>: <function timestrtotime_sql>, <class 'sqlglot.expressions.TimeToStr'>: <function Postgres.Generator.<lambda>>, <class 'sqlglot.expressions.ToChar'>: <function Postgres.Generator.<lambda>>, <class 'sqlglot.expressions.Trim'>: <function trim_sql>, <class 'sqlglot.expressions.TryCast'>: <function no_trycast_sql>, <class 'sqlglot.expressions.TsOrDsAdd'>: <function date_delta_sql.<locals>._delta_sql>, <class 'sqlglot.expressions.TsOrDsDiff'>: <function date_delta_sql.<locals>._delta_sql>, <class 'sqlglot.expressions.UnixToTime'>: <function Redshift.Generator.<lambda>>, <class 'sqlglot.expressions.TimeToUnix'>: <function Postgres.Generator.<lambda>>, <class 'sqlglot.expressions.VariancePop'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.Variance'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.Xor'>: <function bool_xor_sql>, <class 'sqlglot.expressions.Concat'>: <function concat_to_dpipe_sql>, <class 'sqlglot.expressions.ConcatWs'>: <function concat_ws_to_dpipe_sql>, <class 'sqlglot.expressions.ApproxDistinct'>: <function Redshift.Generator.<lambda>>, <class 'sqlglot.expressions.DistKeyProperty'>: <function Redshift.Generator.<lambda>>, <class 'sqlglot.expressions.DistStyleProperty'>: <function Redshift.Generator.<lambda>>, <class 'sqlglot.expressions.FromBase'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.GeneratedAsIdentityColumnConstraint'>: <function generatedasidentitycolumnconstraint_sql>, <class 'sqlglot.expressions.Hex'>: <function Redshift.Generator.<lambda>>, <class 'sqlglot.expressions.SortKeyProperty'>: <function Redshift.Generator.<lambda>>, <class 'sqlglot.expressions.StartsWith'>: <function Redshift.Generator.<lambda>>, <class 'sqlglot.expressions.TableSample'>: <function no_tablesample_sql>}"}, "sqlglot.dialects.redshift.Redshift.Generator.RESERVED_KEYWORDS": {"fullname": "sqlglot.dialects.redshift.Redshift.Generator.RESERVED_KEYWORDS", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Generator.RESERVED_KEYWORDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'similar', 'binary', 'cross', 'wallet', 'false', 'restore', 'aes128', 'analyze', 'timestamp', 'some', 'then', 'unnest', 'lzop', 'for', 'right', 'explicit', 'any', 'all', 'old', 'true', 'isnull', 'union', 'desc', 'emptyasnull', 'pivot', 'offline', 'type', 'encryption', 'create', 'deferrable', 'outer', 'using', 'identity', 'when', 'table', 'analyse', 'off', 'full', 'respect', 'system', 'else', 'leading', 'lun', 'authorization', 'foreign', 'end', 'asc', 'parallel', 'do', 'recover', 'mostly8', 'ilike', 'both', 'new', 'natural', 'check', 'session_user', 'with', 'luns', 'globaldict256', 'interval', 'is', 'verbose', 'current_user_id', 'from', 'bytedict', 'credentials', 'minus', 'resort', 'snapshot', 'aes256', 'and', 'like', 'disable', 'default', 'cast', 'inner', 'initially', 'except', 'nulls', 'localtimestamp', 'unpivot', 'delta32k', 'open', 'lzo', 'without', 'encode', 'mostly16', 'bzip2', 'trailing', 'having', 'permissions', 'join', 'overlaps', 'text32k', 'constraint', 'collate', 'deflate', 'current_date', 'case', 'primary', 'in', 'mostly32', 'percent', 'column', 'sysdate', 'gzip', 'truncatecolumns', 'az64', 'references', 'top', 'localtime', 'or', 'between', 'current_timestamp', 'tag', 'tdes', 'backup', 'current_time', 'blanksasnull', 'intersect', 'distinct', 'globaldict64k', 'on', 'only', 'readratio', 'current_user', 'grant', 'raw', 'not', 'group', 'text255', 'limit', 'into', 'user', 'encrypt ', 'left', 'enable', 'as', 'select', 'partition', 'placing', 'unique', 'offset', 'where', 'array', 'oid', 'null', 'freeze', 'to', 'order', 'delta', 'allowoverwrite', 'ignore', 'notnull', 'defrag', 'rejectlog'}"}, "sqlglot.dialects.redshift.Redshift.Generator.unnest_sql": {"fullname": "sqlglot.dialects.redshift.Redshift.Generator.unnest_sql", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Generator.unnest_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Unnest</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.redshift.Redshift.Generator.cast_sql": {"fullname": "sqlglot.dialects.redshift.Redshift.Generator.cast_sql", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Generator.cast_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Cast</span>,</span><span class=\"param\">\t<span class=\"n\">safe_prefix</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.redshift.Redshift.Generator.datatype_sql": {"fullname": "sqlglot.dialects.redshift.Redshift.Generator.datatype_sql", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Generator.datatype_sql", "kind": "function", "doc": "<p>Redshift converts the <code>TEXT</code> data type to <code>VARCHAR(255)</code> by default when people more generally mean\nVARCHAR of max length which is <code>VARCHAR(max)</code> in Redshift. Therefore if we get a <code>TEXT</code> data type\nwithout precision we convert it to <code>VARCHAR(max)</code> and if it does have precision then we just convert\n<code>TEXT</code> to <code>VARCHAR</code>.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.redshift.Redshift.Generator.alterset_sql": {"fullname": "sqlglot.dialects.redshift.Redshift.Generator.alterset_sql", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Generator.alterset_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">AlterSet</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.redshift.Redshift.Generator.SELECT_KINDS": {"fullname": "sqlglot.dialects.redshift.Redshift.Generator.SELECT_KINDS", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Generator.SELECT_KINDS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Tuple[str, ...]", "default_value": "()"}, "sqlglot.dialects.redshift.Redshift.Generator.TRY_SUPPORTED": {"fullname": "sqlglot.dialects.redshift.Redshift.Generator.TRY_SUPPORTED", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Generator.TRY_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.redshift.Redshift.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS": {"fullname": "sqlglot.dialects.redshift.Redshift.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'qualify': <function Generator.<lambda>>, 'windows': <function Generator.<lambda>>}"}, "sqlglot.dialects.redshift.Redshift.UNESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.redshift.Redshift.UNESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.UNESCAPED_SEQUENCES", "kind": "variable", "doc": "<p>Mapping of an escaped sequence (<code>\\n</code>) to its unescaped version (<code>\n</code>).</p>\n", "annotation": ": Dict[str, str]", "default_value": "{'\\\\a': '\\x07', '\\\\b': '\\x08', '\\\\f': '\\x0c', '\\\\n': '\\n', '\\\\r': '\\r', '\\\\t': '\\t', '\\\\v': '\\x0b', '\\\\\\\\': '\\\\'}"}, "sqlglot.dialects.redshift.Redshift.tokenizer_class": {"fullname": "sqlglot.dialects.redshift.Redshift.tokenizer_class", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.tokenizer_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.redshift.Redshift.Tokenizer'>"}, "sqlglot.dialects.redshift.Redshift.parser_class": {"fullname": "sqlglot.dialects.redshift.Redshift.parser_class", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.parser_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.redshift.Redshift.Parser'>"}, "sqlglot.dialects.redshift.Redshift.generator_class": {"fullname": "sqlglot.dialects.redshift.Redshift.generator_class", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.generator_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.redshift.Redshift.Generator'>"}, "sqlglot.dialects.redshift.Redshift.TIME_TRIE": {"fullname": "sqlglot.dialects.redshift.Redshift.TIME_TRIE", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'A': {'M': {0: True}}, 'P': {'M': {0: True}}, 'D': {0: True, 'D': {0: True, 'D': {0: True}}}, 'F': {'M': {'D': {'D': {0: True, 'D': {0: True}}}, 'H': {'H': {'1': {'2': {0: True}}, '2': {'4': {0: True}}}}, 'M': {'I': {0: True}, 'M': {0: True}}, 'S': {'S': {0: True}}}}, 'H': {'H': {'1': {'2': {0: True}}, '2': {'4': {0: True}}, 0: True}}, 'M': {'I': {0: True}, 'M': {0: True}, 'O': {'N': {0: True}}}, 'O': {'F': {0: True}}, 'S': {'S': {0: True}}, 'T': {'M': {'D': {'a': {'y': {0: True}}, 'y': {0: True}}, 'M': {'o': {'n': {0: True, 't': {'h': {0: True}}}}}}, 'Z': {0: True}}, 'U': {'S': {0: True}}, 'W': {'W': {0: True}}, 'Y': {'Y': {0: True, 'Y': {'Y': {0: True}}}}}"}, "sqlglot.dialects.redshift.Redshift.FORMAT_TRIE": {"fullname": "sqlglot.dialects.redshift.Redshift.FORMAT_TRIE", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.FORMAT_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'A': {'M': {0: True}}, 'P': {'M': {0: True}}, 'D': {0: True, 'D': {0: True, 'D': {0: True}}}, 'F': {'M': {'D': {'D': {0: True, 'D': {0: True}}}, 'H': {'H': {'1': {'2': {0: True}}, '2': {'4': {0: True}}}}, 'M': {'I': {0: True}, 'M': {0: True}}, 'S': {'S': {0: True}}}}, 'H': {'H': {'1': {'2': {0: True}}, '2': {'4': {0: True}}, 0: True}}, 'M': {'I': {0: True}, 'M': {0: True}, 'O': {'N': {0: True}}}, 'O': {'F': {0: True}}, 'S': {'S': {0: True}}, 'T': {'M': {'D': {'a': {'y': {0: True}}, 'y': {0: True}}, 'M': {'o': {'n': {0: True, 't': {'h': {0: True}}}}}}, 'Z': {0: True}}, 'U': {'S': {0: True}}, 'W': {'W': {0: True}}, 'Y': {'Y': {0: True, 'Y': {'Y': {0: True}}}}}"}, "sqlglot.dialects.redshift.Redshift.INVERSE_TIME_MAPPING": {"fullname": "sqlglot.dialects.redshift.Redshift.INVERSE_TIME_MAPPING", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.INVERSE_TIME_MAPPING", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'%p': 'PM', '%u': 'D', '%d': 'DD', '%j': 'DDD', '%-d': 'FMDD', '%-j': 'FMDDD', '%-I': 'FMHH12', '%-H': 'FMHH24', '%-M': 'FMMI', '%-m': 'FMMM', '%-S': 'FMSS', '%I': 'HH12', '%H': 'HH', '%M': 'MI', '%m': 'MM', '%z': 'OF', '%S': 'SS', '%A': 'TMDay', '%a': 'TMDy', '%b': 'MON', '%B': 'TMMonth', '%Z': 'TZ', '%f': 'US', '%U': 'WW', '%y': 'YY', '%Y': 'YYYY'}"}, "sqlglot.dialects.redshift.Redshift.INVERSE_TIME_TRIE": {"fullname": "sqlglot.dialects.redshift.Redshift.INVERSE_TIME_TRIE", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.INVERSE_TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'%': {'p': {0: True}, 'u': {0: True}, 'd': {0: True}, 'j': {0: True}, '-': {'d': {0: True}, 'j': {0: True}, 'I': {0: True}, 'H': {0: True}, 'M': {0: True}, 'm': {0: True}, 'S': {0: True}}, 'I': {0: True}, 'H': {0: True}, 'M': {0: True}, 'm': {0: True}, 'z': {0: True}, 'S': {0: True}, 'A': {0: True}, 'a': {0: True}, 'b': {0: True}, 'B': {0: True}, 'Z': {0: True}, 'f': {0: True}, 'U': {0: True}, 'y': {0: True}, 'Y': {0: True}}}"}, "sqlglot.dialects.redshift.Redshift.ESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.redshift.Redshift.ESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.ESCAPED_SEQUENCES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'\\x07': '\\\\a', '\\x08': '\\\\b', '\\x0c': '\\\\f', '\\n': '\\\\n', '\\r': '\\\\r', '\\t': '\\\\t', '\\x0b': '\\\\v', '\\\\': '\\\\\\\\'}"}, "sqlglot.dialects.redshift.Redshift.QUOTE_START": {"fullname": "sqlglot.dialects.redshift.Redshift.QUOTE_START", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.QUOTE_START", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.redshift.Redshift.QUOTE_END": {"fullname": "sqlglot.dialects.redshift.Redshift.QUOTE_END", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.QUOTE_END", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.redshift.Redshift.IDENTIFIER_START": {"fullname": "sqlglot.dialects.redshift.Redshift.IDENTIFIER_START", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.IDENTIFIER_START", "kind": "variable", "doc": "<p></p>\n", "default_value": "'"'"}, "sqlglot.dialects.redshift.Redshift.IDENTIFIER_END": {"fullname": "sqlglot.dialects.redshift.Redshift.IDENTIFIER_END", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.IDENTIFIER_END", "kind": "variable", "doc": "<p></p>\n", "default_value": "'"'"}, "sqlglot.dialects.redshift.Redshift.BIT_START": {"fullname": "sqlglot.dialects.redshift.Redshift.BIT_START", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.BIT_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.redshift.Redshift.BIT_END": {"fullname": "sqlglot.dialects.redshift.Redshift.BIT_END", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.BIT_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.redshift.Redshift.HEX_START": {"fullname": "sqlglot.dialects.redshift.Redshift.HEX_START", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.HEX_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.redshift.Redshift.HEX_END": {"fullname": "sqlglot.dialects.redshift.Redshift.HEX_END", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.HEX_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.redshift.Redshift.BYTE_START": {"fullname": "sqlglot.dialects.redshift.Redshift.BYTE_START", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.BYTE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""e'""}, "sqlglot.dialects.redshift.Redshift.BYTE_END": {"fullname": "sqlglot.dialects.redshift.Redshift.BYTE_END", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.BYTE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""'""}, "sqlglot.dialects.redshift.Redshift.UNICODE_START": {"fullname": "sqlglot.dialects.redshift.Redshift.UNICODE_START", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.UNICODE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.redshift.Redshift.UNICODE_END": {"fullname": "sqlglot.dialects.redshift.Redshift.UNICODE_END", "modulename": "sqlglot.dialects.redshift", "qualname": "Redshift.UNICODE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.snowflake": {"fullname": "sqlglot.dialects.snowflake", "modulename": "sqlglot.dialects.snowflake", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.dialects.snowflake.DATE_PART_MAPPING": {"fullname": "sqlglot.dialects.snowflake.DATE_PART_MAPPING", "modulename": "sqlglot.dialects.snowflake", "qualname": "DATE_PART_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'Y': 'YEAR', 'YY': 'YEAR', 'YYY': 'YEAR', 'YYYY': 'YEAR', 'YR': 'YEAR', 'YEARS': 'YEAR', 'YRS': 'YEAR', 'MM': 'MONTH', 'MON': 'MONTH', 'MONS': 'MONTH', 'MONTHS': 'MONTH', 'D': 'DAY', 'DD': 'DAY', 'DAYS': 'DAY', 'DAYOFMONTH': 'DAY', 'WEEKDAY': 'DAYOFWEEK', 'DOW': 'DAYOFWEEK', 'DW': 'DAYOFWEEK', 'WEEKDAY_ISO': 'DAYOFWEEKISO', 'DOW_ISO': 'DAYOFWEEKISO', 'DW_ISO': 'DAYOFWEEKISO', 'YEARDAY': 'DAYOFYEAR', 'DOY': 'DAYOFYEAR', 'DY': 'DAYOFYEAR', 'W': 'WEEK', 'WK': 'WEEK', 'WEEKOFYEAR': 'WEEK', 'WOY': 'WEEK', 'WY': 'WEEK', 'WEEK_ISO': 'WEEKISO', 'WEEKOFYEARISO': 'WEEKISO', 'WEEKOFYEAR_ISO': 'WEEKISO', 'Q': 'QUARTER', 'QTR': 'QUARTER', 'QTRS': 'QUARTER', 'QUARTERS': 'QUARTER', 'H': 'HOUR', 'HH': 'HOUR', 'HR': 'HOUR', 'HOURS': 'HOUR', 'HRS': 'HOUR', 'M': 'MINUTE', 'MI': 'MINUTE', 'MIN': 'MINUTE', 'MINUTES': 'MINUTE', 'MINS': 'MINUTE', 'S': 'SECOND', 'SEC': 'SECOND', 'SECONDS': 'SECOND', 'SECS': 'SECOND', 'MS': 'MILLISECOND', 'MSEC': 'MILLISECOND', 'MILLISECONDS': 'MILLISECOND', 'US': 'MICROSECOND', 'USEC': 'MICROSECOND', 'MICROSECONDS': 'MICROSECOND', 'NS': 'NANOSECOND', 'NSEC': 'NANOSECOND', 'NANOSEC': 'NANOSECOND', 'NSECOND': 'NANOSECOND', 'NSECONDS': 'NANOSECOND', 'NANOSECS': 'NANOSECOND', 'EPOCH': 'EPOCH_SECOND', 'EPOCH_SECONDS': 'EPOCH_SECOND', 'EPOCH_MILLISECONDS': 'EPOCH_MILLISECOND', 'EPOCH_MICROSECONDS': 'EPOCH_MICROSECOND', 'EPOCH_NANOSECONDS': 'EPOCH_NANOSECOND', 'TZH': 'TIMEZONE_HOUR', 'TZM': 'TIMEZONE_MINUTE'}"}, "sqlglot.dialects.snowflake.Snowflake": {"fullname": "sqlglot.dialects.snowflake.Snowflake", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.dialect.Dialect"}, "sqlglot.dialects.snowflake.Snowflake.NORMALIZATION_STRATEGY": {"fullname": "sqlglot.dialects.snowflake.Snowflake.NORMALIZATION_STRATEGY", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.NORMALIZATION_STRATEGY", "kind": "variable", "doc": "<p>Specifies the strategy according to which identifiers should be normalized.</p>\n", "default_value": "<NormalizationStrategy.UPPERCASE: 'UPPERCASE'>"}, "sqlglot.dialects.snowflake.Snowflake.NULL_ORDERING": {"fullname": "sqlglot.dialects.snowflake.Snowflake.NULL_ORDERING", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.NULL_ORDERING", "kind": "variable", "doc": "<p>Default <code>NULL</code> ordering method to use if not explicitly set.\nPossible values: <code>\"nulls_are_small\"</code>, <code>\"nulls_are_large\"</code>, <code>\"nulls_are_last\"</code></p>\n", "default_value": "'nulls_are_large'"}, "sqlglot.dialects.snowflake.Snowflake.TIME_FORMAT": {"fullname": "sqlglot.dialects.snowflake.Snowflake.TIME_FORMAT", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.TIME_FORMAT", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'YYYY-MM-DD HH24:MI:SS'""}, "sqlglot.dialects.snowflake.Snowflake.SUPPORTS_USER_DEFINED_TYPES": {"fullname": "sqlglot.dialects.snowflake.Snowflake.SUPPORTS_USER_DEFINED_TYPES", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.SUPPORTS_USER_DEFINED_TYPES", "kind": "variable", "doc": "<p>Whether user-defined data types are supported.</p>\n", "default_value": "False"}, "sqlglot.dialects.snowflake.Snowflake.SUPPORTS_SEMI_ANTI_JOIN": {"fullname": "sqlglot.dialects.snowflake.Snowflake.SUPPORTS_SEMI_ANTI_JOIN", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.SUPPORTS_SEMI_ANTI_JOIN", "kind": "variable", "doc": "<p>Whether <code>SEMI</code> or <code>ANTI</code> joins are supported.</p>\n", "default_value": "False"}, "sqlglot.dialects.snowflake.Snowflake.PREFER_CTE_ALIAS_COLUMN": {"fullname": "sqlglot.dialects.snowflake.Snowflake.PREFER_CTE_ALIAS_COLUMN", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.PREFER_CTE_ALIAS_COLUMN", "kind": "variable", "doc": "<p>Some dialects, such as Snowflake, allow you to reference a CTE column alias in the\nHAVING clause of the CTE. This flag will cause the CTE alias columns to override\nany projection aliases in the subquery.</p>\n\n<p>For example,\n WITH y(c) AS (\n SELECT SUM(a) FROM (SELECT 1 a) AS x HAVING c > 0\n ) SELECT c FROM y;</p>\n\n<pre><code>will be rewritten as\n\nWITH y(c) AS (\n SELECT SUM(a) AS c FROM (SELECT 1 AS a) AS x HAVING c > 0\n) SELECT c FROM y;\n</code></pre>\n", "default_value": "True"}, "sqlglot.dialects.snowflake.Snowflake.TABLESAMPLE_SIZE_IS_PERCENT": {"fullname": "sqlglot.dialects.snowflake.Snowflake.TABLESAMPLE_SIZE_IS_PERCENT", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.TABLESAMPLE_SIZE_IS_PERCENT", "kind": "variable", "doc": "<p>Whether a size in the table sample clause represents percentage.</p>\n", "default_value": "True"}, "sqlglot.dialects.snowflake.Snowflake.COPY_PARAMS_ARE_CSV": {"fullname": "sqlglot.dialects.snowflake.Snowflake.COPY_PARAMS_ARE_CSV", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.COPY_PARAMS_ARE_CSV", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.snowflake.Snowflake.TIME_MAPPING": {"fullname": "sqlglot.dialects.snowflake.Snowflake.TIME_MAPPING", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.TIME_MAPPING", "kind": "variable", "doc": "<p>Associates this dialect's time formats with their equivalent Python <code>strftime</code> formats.</p>\n", "annotation": ": Dict[str, str]", "default_value": "{'YYYY': '%Y', 'yyyy': '%Y', 'YY': '%y', 'yy': '%y', 'MMMM': '%B', 'mmmm': '%B', 'MON': '%b', 'mon': '%b', 'MM': '%m', 'mm': '%m', 'DD': '%d', 'dd': '%-d', 'DY': '%a', 'dy': '%w', 'HH24': '%H', 'hh24': '%H', 'HH12': '%I', 'hh12': '%I', 'MI': '%M', 'mi': '%M', 'SS': '%S', 'ss': '%S', 'FF': '%f', 'ff': '%f', 'FF6': '%f', 'ff6': '%f'}"}, "sqlglot.dialects.snowflake.Snowflake.quote_identifier": {"fullname": "sqlglot.dialects.snowflake.Snowflake.quote_identifier", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.quote_identifier", "kind": "function", "doc": "<p>Adds quotes to a given identifier.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> The expression of interest. If it's not an <code>Identifier</code>, this method is a no-op.</li>\n<li><strong>identify:</strong> If set to <code>False</code>, the quotes will only be added if the identifier is deemed\n\"unsafe\", with respect to its characters and this dialect's normalization strategy.</li>\n</ul>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"o\">~</span><span class=\"n\">E</span>, </span><span class=\"param\"><span class=\"n\">identify</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"o\">~</span><span class=\"n\">E</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.snowflake.Snowflake.Parser": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Parser", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Parser", "kind": "class", "doc": "<p>Parser consumes a list of tokens produced by the Tokenizer and produces a parsed syntax tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>error_level:</strong> The desired error level.\nDefault: ErrorLevel.IMMEDIATE</li>\n<li><strong>error_message_context:</strong> The amount of context to capture from a query string when displaying\nthe error message (in number of characters).\nDefault: 100</li>\n<li><strong>max_errors:</strong> Maximum number of error messages to include in a raised ParseError.\nThis is only relevant if error_level is ErrorLevel.RAISE.\nDefault: 3</li>\n</ul>\n", "bases": "sqlglot.parser.Parser"}, "sqlglot.dialects.snowflake.Snowflake.Parser.IDENTIFY_PIVOT_STRINGS": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Parser.IDENTIFY_PIVOT_STRINGS", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Parser.IDENTIFY_PIVOT_STRINGS", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.snowflake.Snowflake.Parser.DEFAULT_SAMPLING_METHOD": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Parser.DEFAULT_SAMPLING_METHOD", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Parser.DEFAULT_SAMPLING_METHOD", "kind": "variable", "doc": "<p></p>\n", "default_value": "'BERNOULLI'"}, "sqlglot.dialects.snowflake.Snowflake.Parser.COLON_IS_JSON_EXTRACT": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Parser.COLON_IS_JSON_EXTRACT", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Parser.COLON_IS_JSON_EXTRACT", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.snowflake.Snowflake.Parser.ID_VAR_TOKENS": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Parser.ID_VAR_TOKENS", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Parser.ID_VAR_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.KILL: 'KILL'>, <TokenType.MONEY: 'MONEY'>, <TokenType.COPY: 'COPY'>, <TokenType.PERCENT: 'PERCENT'>, <TokenType.TAG: 'TAG'>, <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, <TokenType.VOLATILE: 'VOLATILE'>, <TokenType.IDENTIFIER: 'IDENTIFIER'>, <TokenType.VARBINARY: 'VARBINARY'>, <TokenType.HSTORE: 'HSTORE'>, <TokenType.ASC: 'ASC'>, <TokenType.IPADDRESS: 'IPADDRESS'>, <TokenType.ISNULL: 'ISNULL'>, <TokenType.TEMPORARY: 'TEMPORARY'>, <TokenType.PROCEDURE: 'PROCEDURE'>, <TokenType.SCHEMA: 'SCHEMA'>, <TokenType.NUMRANGE: 'NUMRANGE'>, <TokenType.DATE32: 'DATE32'>, <TokenType.INT8RANGE: 'INT8RANGE'>, <TokenType.AGGREGATEFUNCTION: 'AGGREGATEFUNCTION'>, <TokenType.VIEW: 'VIEW'>, <TokenType.VARCHAR: 'VARCHAR'>, <TokenType.TIMETZ: 'TIMETZ'>, <TokenType.GEOMETRY: 'GEOMETRY'>, <TokenType.BEGIN: 'BEGIN'>, <TokenType.ENUM8: 'ENUM8'>, <TokenType.INDEX: 'INDEX'>, <TokenType.PARTITION: 'PARTITION'>, <TokenType.UINT256: 'UINT256'>, <TokenType.BIGINT: 'BIGINT'>, <TokenType.CACHE: 'CACHE'>, <TokenType.OPERATOR: 'OPERATOR'>, <TokenType.COLUMN: 'COLUMN'>, <TokenType.INT128: 'INT128'>, <TokenType.SMALLMONEY: 'SMALLMONEY'>, <TokenType.HLLSKETCH: 'HLLSKETCH'>, <TokenType.UNPIVOT: 'UNPIVOT'>, <TokenType.SMALLINT: 'SMALLINT'>, <TokenType.INT256: 'INT256'>, <TokenType.FLOAT: 'FLOAT'>, <TokenType.COMMIT: 'COMMIT'>, <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, <TokenType.EXISTS: 'EXISTS'>, <TokenType.NULL: 'NULL'>, <TokenType.RECURSIVE: 'RECURSIVE'>, <TokenType.SET: 'SET'>, <TokenType.NULLABLE: 'NULLABLE'>, <TokenType.REFRESH: 'REFRESH'>, <TokenType.TINYTEXT: 'TINYTEXT'>, <TokenType.SHOW: 'SHOW'>, <TokenType.DEFAULT: 'DEFAULT'>, <TokenType.DATE: 'DATE'>, <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <TokenType.MERGE: 'MERGE'>, <TokenType.FIRST: 'FIRST'>, <TokenType.BINARY: 'BINARY'>, <TokenType.ARRAY: 'ARRAY'>, <TokenType.SERIAL: 'SERIAL'>, <TokenType.EXECUTE: 'EXECUTE'>, <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, <TokenType.INTERVAL: 'INTERVAL'>, <TokenType.PRAGMA: 'PRAGMA'>, <TokenType.APPLY: 'APPLY'>, <TokenType.STORAGE_INTEGRATION: 'STORAGE_INTEGRATION'>, <TokenType.ASOF: 'ASOF'>, <TokenType.WINDOW: 'WINDOW'>, <TokenType.RIGHT: 'RIGHT'>, <TokenType.BPCHAR: 'BPCHAR'>, <TokenType.BIT: 'BIT'>, <TokenType.UINT: 'UINT'>, <TokenType.UUID: 'UUID'>, <TokenType.STRUCT: 'STRUCT'>, <TokenType.FALSE: 'FALSE'>, <TokenType.LEFT: 'LEFT'>, <TokenType.TOP: 'TOP'>, <TokenType.FUNCTION: 'FUNCTION'>, <TokenType.SUPER: 'SUPER'>, <TokenType.CASE: 'CASE'>, <TokenType.IMAGE: 'IMAGE'>, <TokenType.UBIGINT: 'UBIGINT'>, <TokenType.LONGBLOB: 'LONGBLOB'>, <TokenType.ROLLUP: 'ROLLUP'>, <TokenType.VAR: 'VAR'>, <TokenType.COMMAND: 'COMMAND'>, <TokenType.LOAD: 'LOAD'>, <TokenType.TRUNCATE: 'TRUNCATE'>, <TokenType.KEEP: 'KEEP'>, <TokenType.UMEDIUMINT: 'UMEDIUMINT'>, <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, <TokenType.UINT128: 'UINT128'>, <TokenType.END: 'END'>, <TokenType.MAP: 'MAP'>, <TokenType.IPV4: 'IPV4'>, <TokenType.USERDEFINED: 'USERDEFINED'>, <TokenType.REFERENCES: 'REFERENCES'>, <TokenType.REPLACE: 'REPLACE'>, <TokenType.RANGE: 'RANGE'>, <TokenType.NVARCHAR: 'NVARCHAR'>, <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, <TokenType.TRUE: 'TRUE'>, <TokenType.TIMESTAMP_MS: 'TIMESTAMP_MS'>, <TokenType.VARIANT: 'VARIANT'>, <TokenType.ENUM: 'ENUM'>, <TokenType.USE: 'USE'>, <TokenType.USMALLINT: 'USMALLINT'>, <TokenType.OVERLAPS: 'OVERLAPS'>, <TokenType.TIMESTAMP_S: 'TIMESTAMP_S'>, <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, <TokenType.UNIQUE: 'UNIQUE'>, <TokenType.ORDINALITY: 'ORDINALITY'>, <TokenType.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>, <TokenType.TEXT: 'TEXT'>, <TokenType.DATABASE: 'DATABASE'>, <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, <TokenType.PSEUDO_TYPE: 'PSEUDO_TYPE'>, <TokenType.FIXEDSTRING: 'FIXEDSTRING'>, <TokenType.NEXT: 'NEXT'>, <TokenType.INT: 'INT'>, <TokenType.BIGSERIAL: 'BIGSERIAL'>, <TokenType.BOOLEAN: 'BOOLEAN'>, <TokenType.IS: 'IS'>, <TokenType.CONSTRAINT: 'CONSTRAINT'>, <TokenType.FINAL: 'FINAL'>, <TokenType.UNKNOWN: 'UNKNOWN'>, <TokenType.SETTINGS: 'SETTINGS'>, <TokenType.ROWS: 'ROWS'>, <TokenType.TSTZRANGE: 'TSTZRANGE'>, <TokenType.DATETIME64: 'DATETIME64'>, <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, <TokenType.DATETIME: 'DATETIME'>, <TokenType.MEDIUMINT: 'MEDIUMINT'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>, <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, <TokenType.XML: 'XML'>, <TokenType.SEMI: 'SEMI'>, <TokenType.JSON: 'JSON'>, <TokenType.DELETE: 'DELETE'>, <TokenType.UTINYINT: 'UTINYINT'>, <TokenType.TIME: 'TIME'>, <TokenType.UDECIMAL: 'UDECIMAL'>, <TokenType.NESTED: 'NESTED'>, <TokenType.DESC: 'DESC'>, <TokenType.ROWVERSION: 'ROWVERSION'>, <TokenType.OFFSET: 'OFFSET'>, <TokenType.TIMESTAMP_NS: 'TIMESTAMP_NS'>, <TokenType.ANY: 'ANY'>, <TokenType.DIV: 'DIV'>, <TokenType.DICTIONARY: 'DICTIONARY'>, <TokenType.INET: 'INET'>, <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, <TokenType.COMMENT: 'COMMENT'>, <TokenType.CURRENT_USER: 'CURRENT_USER'>, <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>, <TokenType.ALL: 'ALL'>, <TokenType.NAME: 'NAME'>, <TokenType.SOME: 'SOME'>, <TokenType.ENUM16: 'ENUM16'>, <TokenType.YEAR: 'YEAR'>, <TokenType.FULL: 'FULL'>, <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, <TokenType.TINYBLOB: 'TINYBLOB'>, <TokenType.DOUBLE: 'DOUBLE'>, <TokenType.INT4RANGE: 'INT4RANGE'>, <TokenType.FORMAT: 'FORMAT'>, <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, <TokenType.IPPREFIX: 'IPPREFIX'>, <TokenType.OVERWRITE: 'OVERWRITE'>, <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>, <TokenType.COLLATE: 'COLLATE'>, <TokenType.FILTER: 'FILTER'>, <TokenType.JSONB: 'JSONB'>, <TokenType.TDIGEST: 'TDIGEST'>, <TokenType.CHAR: 'CHAR'>, <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.MATCH_CONDITION: 'MATCH_CONDITION'>, <TokenType.ROW: 'ROW'>, <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.TABLE: 'TABLE'>, <TokenType.DATERANGE: 'DATERANGE'>, <TokenType.NATURAL: 'NATURAL'>, <TokenType.TSRANGE: 'TSRANGE'>, <TokenType.ESCAPE: 'ESCAPE'>, <TokenType.PIVOT: 'PIVOT'>, <TokenType.DECIMAL: 'DECIMAL'>, <TokenType.NCHAR: 'NCHAR'>, <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, <TokenType.UPDATE: 'UPDATE'>, <TokenType.MODEL: 'MODEL'>, <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, <TokenType.SEQUENCE: 'SEQUENCE'>, <TokenType.LONGTEXT: 'LONGTEXT'>, <TokenType.DESCRIBE: 'DESCRIBE'>, <TokenType.IPV6: 'IPV6'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, <TokenType.TINYINT: 'TINYINT'>, <TokenType.ANTI: 'ANTI'>}"}, "sqlglot.dialects.snowflake.Snowflake.Parser.TABLE_ALIAS_TOKENS": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Parser.TABLE_ALIAS_TOKENS", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Parser.TABLE_ALIAS_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.KILL: 'KILL'>, <TokenType.MONEY: 'MONEY'>, <TokenType.COPY: 'COPY'>, <TokenType.PERCENT: 'PERCENT'>, <TokenType.TAG: 'TAG'>, <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, <TokenType.VOLATILE: 'VOLATILE'>, <TokenType.IDENTIFIER: 'IDENTIFIER'>, <TokenType.VARBINARY: 'VARBINARY'>, <TokenType.HSTORE: 'HSTORE'>, <TokenType.ASC: 'ASC'>, <TokenType.IPADDRESS: 'IPADDRESS'>, <TokenType.ISNULL: 'ISNULL'>, <TokenType.TEMPORARY: 'TEMPORARY'>, <TokenType.PROCEDURE: 'PROCEDURE'>, <TokenType.SCHEMA: 'SCHEMA'>, <TokenType.NUMRANGE: 'NUMRANGE'>, <TokenType.DATE32: 'DATE32'>, <TokenType.INT8RANGE: 'INT8RANGE'>, <TokenType.ANTI: 'ANTI'>, <TokenType.AGGREGATEFUNCTION: 'AGGREGATEFUNCTION'>, <TokenType.VIEW: 'VIEW'>, <TokenType.VARCHAR: 'VARCHAR'>, <TokenType.TIMETZ: 'TIMETZ'>, <TokenType.GEOMETRY: 'GEOMETRY'>, <TokenType.BEGIN: 'BEGIN'>, <TokenType.ENUM8: 'ENUM8'>, <TokenType.INDEX: 'INDEX'>, <TokenType.PARTITION: 'PARTITION'>, <TokenType.UINT256: 'UINT256'>, <TokenType.BIGINT: 'BIGINT'>, <TokenType.CACHE: 'CACHE'>, <TokenType.OPERATOR: 'OPERATOR'>, <TokenType.COLUMN: 'COLUMN'>, <TokenType.INT128: 'INT128'>, <TokenType.SMALLMONEY: 'SMALLMONEY'>, <TokenType.HLLSKETCH: 'HLLSKETCH'>, <TokenType.UNPIVOT: 'UNPIVOT'>, <TokenType.SMALLINT: 'SMALLINT'>, <TokenType.INT256: 'INT256'>, <TokenType.FLOAT: 'FLOAT'>, <TokenType.COMMIT: 'COMMIT'>, <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, <TokenType.EXISTS: 'EXISTS'>, <TokenType.NULL: 'NULL'>, <TokenType.RECURSIVE: 'RECURSIVE'>, <TokenType.SET: 'SET'>, <TokenType.NULLABLE: 'NULLABLE'>, <TokenType.REFRESH: 'REFRESH'>, <TokenType.TINYTEXT: 'TINYTEXT'>, <TokenType.SHOW: 'SHOW'>, <TokenType.DEFAULT: 'DEFAULT'>, <TokenType.DATE: 'DATE'>, <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <TokenType.MERGE: 'MERGE'>, <TokenType.FIRST: 'FIRST'>, <TokenType.BINARY: 'BINARY'>, <TokenType.ARRAY: 'ARRAY'>, <TokenType.SERIAL: 'SERIAL'>, <TokenType.EXECUTE: 'EXECUTE'>, <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, <TokenType.INTERVAL: 'INTERVAL'>, <TokenType.PRAGMA: 'PRAGMA'>, <TokenType.STORAGE_INTEGRATION: 'STORAGE_INTEGRATION'>, <TokenType.WINDOW: 'WINDOW'>, <TokenType.BPCHAR: 'BPCHAR'>, <TokenType.BIT: 'BIT'>, <TokenType.UINT: 'UINT'>, <TokenType.UUID: 'UUID'>, <TokenType.STRUCT: 'STRUCT'>, <TokenType.FALSE: 'FALSE'>, <TokenType.FUNCTION: 'FUNCTION'>, <TokenType.TOP: 'TOP'>, <TokenType.SUPER: 'SUPER'>, <TokenType.CASE: 'CASE'>, <TokenType.IMAGE: 'IMAGE'>, <TokenType.UBIGINT: 'UBIGINT'>, <TokenType.LONGBLOB: 'LONGBLOB'>, <TokenType.ROLLUP: 'ROLLUP'>, <TokenType.VAR: 'VAR'>, <TokenType.COMMAND: 'COMMAND'>, <TokenType.LOAD: 'LOAD'>, <TokenType.TRUNCATE: 'TRUNCATE'>, <TokenType.KEEP: 'KEEP'>, <TokenType.UMEDIUMINT: 'UMEDIUMINT'>, <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, <TokenType.UINT128: 'UINT128'>, <TokenType.END: 'END'>, <TokenType.MAP: 'MAP'>, <TokenType.IPV4: 'IPV4'>, <TokenType.USERDEFINED: 'USERDEFINED'>, <TokenType.REFERENCES: 'REFERENCES'>, <TokenType.REPLACE: 'REPLACE'>, <TokenType.RANGE: 'RANGE'>, <TokenType.NVARCHAR: 'NVARCHAR'>, <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, <TokenType.TRUE: 'TRUE'>, <TokenType.TIMESTAMP_MS: 'TIMESTAMP_MS'>, <TokenType.VARIANT: 'VARIANT'>, <TokenType.ENUM: 'ENUM'>, <TokenType.USE: 'USE'>, <TokenType.USMALLINT: 'USMALLINT'>, <TokenType.OVERLAPS: 'OVERLAPS'>, <TokenType.TIMESTAMP_S: 'TIMESTAMP_S'>, <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, <TokenType.UNIQUE: 'UNIQUE'>, <TokenType.ORDINALITY: 'ORDINALITY'>, <TokenType.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>, <TokenType.TEXT: 'TEXT'>, <TokenType.DATABASE: 'DATABASE'>, <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, <TokenType.PSEUDO_TYPE: 'PSEUDO_TYPE'>, <TokenType.FIXEDSTRING: 'FIXEDSTRING'>, <TokenType.NEXT: 'NEXT'>, <TokenType.INT: 'INT'>, <TokenType.BIGSERIAL: 'BIGSERIAL'>, <TokenType.BOOLEAN: 'BOOLEAN'>, <TokenType.IS: 'IS'>, <TokenType.CONSTRAINT: 'CONSTRAINT'>, <TokenType.FINAL: 'FINAL'>, <TokenType.UNKNOWN: 'UNKNOWN'>, <TokenType.SETTINGS: 'SETTINGS'>, <TokenType.ROWS: 'ROWS'>, <TokenType.TSTZRANGE: 'TSTZRANGE'>, <TokenType.DATETIME64: 'DATETIME64'>, <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, <TokenType.DATETIME: 'DATETIME'>, <TokenType.MEDIUMINT: 'MEDIUMINT'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>, <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, <TokenType.XML: 'XML'>, <TokenType.JSON: 'JSON'>, <TokenType.UTINYINT: 'UTINYINT'>, <TokenType.DELETE: 'DELETE'>, <TokenType.TIME: 'TIME'>, <TokenType.UDECIMAL: 'UDECIMAL'>, <TokenType.NESTED: 'NESTED'>, <TokenType.SEMI: 'SEMI'>, <TokenType.DESC: 'DESC'>, <TokenType.ROWVERSION: 'ROWVERSION'>, <TokenType.TIMESTAMP_NS: 'TIMESTAMP_NS'>, <TokenType.ANY: 'ANY'>, <TokenType.DIV: 'DIV'>, <TokenType.DICTIONARY: 'DICTIONARY'>, <TokenType.INET: 'INET'>, <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, <TokenType.COMMENT: 'COMMENT'>, <TokenType.CURRENT_USER: 'CURRENT_USER'>, <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>, <TokenType.ALL: 'ALL'>, <TokenType.NAME: 'NAME'>, <TokenType.SOME: 'SOME'>, <TokenType.ENUM16: 'ENUM16'>, <TokenType.YEAR: 'YEAR'>, <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, <TokenType.DOUBLE: 'DOUBLE'>, <TokenType.INT4RANGE: 'INT4RANGE'>, <TokenType.FORMAT: 'FORMAT'>, <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, <TokenType.IPPREFIX: 'IPPREFIX'>, <TokenType.OVERWRITE: 'OVERWRITE'>, <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>, <TokenType.COLLATE: 'COLLATE'>, <TokenType.FILTER: 'FILTER'>, <TokenType.JSONB: 'JSONB'>, <TokenType.TDIGEST: 'TDIGEST'>, <TokenType.CHAR: 'CHAR'>, <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.ROW: 'ROW'>, <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.TABLE: 'TABLE'>, <TokenType.DATERANGE: 'DATERANGE'>, <TokenType.TSRANGE: 'TSRANGE'>, <TokenType.ESCAPE: 'ESCAPE'>, <TokenType.PIVOT: 'PIVOT'>, <TokenType.DECIMAL: 'DECIMAL'>, <TokenType.NCHAR: 'NCHAR'>, <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, <TokenType.UPDATE: 'UPDATE'>, <TokenType.MODEL: 'MODEL'>, <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, <TokenType.SEQUENCE: 'SEQUENCE'>, <TokenType.LONGTEXT: 'LONGTEXT'>, <TokenType.DESCRIBE: 'DESCRIBE'>, <TokenType.IPV6: 'IPV6'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, <TokenType.TINYINT: 'TINYINT'>, <TokenType.TINYBLOB: 'TINYBLOB'>}"}, "sqlglot.dialects.snowflake.Snowflake.Parser.FUNCTIONS": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Parser.FUNCTIONS", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Parser.FUNCTIONS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ABS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Abs'>>, 'ADD_MONTHS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AddMonths'>>, 'ANONYMOUS_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnonymousAggFunc'>>, 'ANY_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnyValue'>>, 'APPROX_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_COUNT_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'APPROX_TOP_K': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxTopK'>>, 'ARG_MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARGMAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'MAX_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARG_MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARGMIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'MIN_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Array'>>, 'ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAgg'>>, 'ARRAY_ALL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAll'>>, 'ARRAY_ANY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAny'>>, 'ARRAY_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CONSTRUCT_COMPACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConstructCompact'>>, 'ARRAY_CONTAINS': <function Snowflake.Parser.<lambda>>, 'FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_OVERLAPS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayOverlaps'>>, 'ARRAY_SIZE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_SORT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySort'>>, 'ARRAY_SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySum'>>, 'ARRAY_TO_STRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_JOIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_UNION_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUnionAgg'>>, 'ARRAY_UNIQUE_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUniqueAgg'>>, 'AVG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Avg'>>, 'CASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Case'>>, 'CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cast'>>, 'CAST_TO_STR_TYPE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CastToStrType'>>, 'CBRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cbrt'>>, 'CEIL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CEILING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CHR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'COALESCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'IFNULL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'NVL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'COLLATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Collate'>>, 'COMBINED_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedAggFunc'>>, 'COMBINED_PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedParameterizedAgg'>>, 'CONCAT': <function Parser.<lambda>>, 'CONCAT_WS': <function Parser.<lambda>>, 'CONNECT_BY_ROOT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ConnectByRoot'>>, 'CONVERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Convert'>>, 'CORR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Corr'>>, 'COUNT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Count'>>, 'COUNT_IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COUNTIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COVAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarPop'>>, 'COVAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarSamp'>>, 'CURRENT_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDate'>>, 'CURRENT_DATETIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDatetime'>>, 'CURRENT_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTime'>>, 'CURRENT_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTimestamp'>>, 'CURRENT_USER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentUser'>>, 'DATE': <function _build_datetime.<locals>._builder>, 'DATE_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateAdd'>>, 'DATEDIFF': <function _build_datediff>, 'DATE_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateDiff'>>, 'DATE_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATE_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateStrToDate'>>, 'DATE_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateSub'>>, 'DATE_TO_DATE_STR': <function Parser.<lambda>>, 'DATE_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateToDi'>>, 'DATE_TRUNC': <function _date_trunc_to_time>, 'DATETIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeAdd'>>, 'DATETIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeDiff'>>, 'DATETIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeSub'>>, 'DATETIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeTrunc'>>, 'DAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Day'>>, 'DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAYOFMONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAY_OF_WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAYOFWEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAY_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DAYOFYEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DECODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Decode'>>, 'DI_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DiToDate'>>, 'ENCODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Encode'>>, 'EXP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Exp'>>, 'EXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Explode'>>, 'EXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ExplodeOuter'>>, 'EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Extract'>>, 'FIRST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.First'>>, 'FIRST_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FirstValue'>>, 'FLATTEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Explode'>>, 'FLOOR': <bound method Func.from_arg_list of <class 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Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'ISINF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'IS_NAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'ISNAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'J_S_O_N_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArray'>>, 'J_S_O_N_ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArrayAgg'>>, 'JSON_ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArrayContains'>>, 'JSONB_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONBExtract'>>, 'JSONB_EXTRACT_SCALAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONBExtractScalar'>>, 'JSON_EXTRACT': <function build_extract_json_with_path.<locals>._builder>, 'JSON_EXTRACT_SCALAR': <function build_extract_json_with_path.<locals>._builder>, 'JSON_FORMAT': 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Func.from_arg_list of <class 'sqlglot.expressions.NextValueFor'>>, 'NTH_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NthValue'>>, 'NULLIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Nullif'>>, 'NUMBER_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NumberToStr'>>, 'NVL2': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Nvl2'>>, 'OPEN_J_S_O_N': <bound method Func.from_arg_list of <class 'sqlglot.expressions.OpenJSON'>>, 'PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParameterizedAgg'>>, 'PARSE_JSON': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParseJSON'>>, 'JSON_PARSE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParseJSON'>>, 'PERCENTILE_CONT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PercentileCont'>>, 'PERCENTILE_DISC': <bound method Func.from_arg_list of <class 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'UNIX_TO_TIME_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTimeStr'>>, 'UPPER': <function build_upper>, 'UCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Upper'>>, 'VAR_MAP': <function build_var_map>, 'VARIANCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'VAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Week'>>, 'WEEK_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.WeekOfYear'>>, 'WEEKOFYEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.WeekOfYear'>>, 'WHEN': <bound 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"<p></p>\n", "default_value": "{<TokenType.TIMETZ: 'TIMETZ'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>, <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>}"}, "sqlglot.dialects.snowflake.Snowflake.Parser.RANGE_PARSERS": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Parser.RANGE_PARSERS", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Parser.RANGE_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.BETWEEN: 'BETWEEN'>: <function Parser.<lambda>>, <TokenType.GLOB: 'GLOB'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.ILIKE: 'ILIKE'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.IN: 'IN'>: <function Parser.<lambda>>, <TokenType.IRLIKE: 'IRLIKE'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.IS: 'IS'>: <function Parser.<lambda>>, <TokenType.LIKE: 'LIKE'>: <function binary_range_parser.<locals>.<lambda>>, <TokenType.OVERLAPS: 'OVERLAPS'>: <function 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'SELECT'>, 'SEMI': <TokenType.SEMI: 'SEMI'>, 'SET': <TokenType.SET: 'SET'>, 'SETTINGS': <TokenType.SETTINGS: 'SETTINGS'>, 'SHOW': <TokenType.SHOW: 'SHOW'>, 'SIMILAR TO': <TokenType.SIMILAR_TO: 'SIMILAR_TO'>, 'SOME': <TokenType.SOME: 'SOME'>, 'SORT BY': <TokenType.SORT_BY: 'SORT_BY'>, 'START WITH': <TokenType.START_WITH: 'START_WITH'>, 'TABLE': <TokenType.TABLE: 'TABLE'>, 'TABLESAMPLE': <TokenType.TABLE_SAMPLE: 'TABLE_SAMPLE'>, 'TEMP': <TokenType.TEMPORARY: 'TEMPORARY'>, 'TEMPORARY': <TokenType.TEMPORARY: 'TEMPORARY'>, 'THEN': <TokenType.THEN: 'THEN'>, 'TRUE': <TokenType.TRUE: 'TRUE'>, 'TRUNCATE': <TokenType.TRUNCATE: 'TRUNCATE'>, 'UNION': <TokenType.UNION: 'UNION'>, 'UNKNOWN': <TokenType.UNKNOWN: 'UNKNOWN'>, 'UNNEST': <TokenType.UNNEST: 'UNNEST'>, 'UNPIVOT': <TokenType.UNPIVOT: 'UNPIVOT'>, 'UPDATE': <TokenType.UPDATE: 'UPDATE'>, 'USE': <TokenType.USE: 'USE'>, 'USING': <TokenType.USING: 'USING'>, 'UUID': <TokenType.UUID: 'UUID'>, 'VALUES': <TokenType.VALUES: 'VALUES'>, 'VIEW': <TokenType.VIEW: 'VIEW'>, 'VOLATILE': <TokenType.VOLATILE: 'VOLATILE'>, 'WHEN': <TokenType.WHEN: 'WHEN'>, 'WHERE': <TokenType.WHERE: 'WHERE'>, 'WINDOW': <TokenType.WINDOW: 'WINDOW'>, 'WITH': <TokenType.WITH: 'WITH'>, 'APPLY': <TokenType.APPLY: 'APPLY'>, 'ARRAY': <TokenType.ARRAY: 'ARRAY'>, 'BIT': <TokenType.BIT: 'BIT'>, 'BOOL': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BOOLEAN': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BYTE': <TokenType.TINYINT: 'TINYINT'>, 'MEDIUMINT': <TokenType.MEDIUMINT: 'MEDIUMINT'>, 'INT1': <TokenType.TINYINT: 'TINYINT'>, 'TINYINT': <TokenType.TINYINT: 'TINYINT'>, 'INT16': <TokenType.SMALLINT: 'SMALLINT'>, 'SHORT': <TokenType.SMALLINT: 'SMALLINT'>, 'SMALLINT': <TokenType.SMALLINT: 'SMALLINT'>, 'INT128': <TokenType.INT128: 'INT128'>, 'HUGEINT': <TokenType.INT128: 'INT128'>, 'INT2': <TokenType.SMALLINT: 'SMALLINT'>, 'INTEGER': <TokenType.INT: 'INT'>, 'INT': <TokenType.INT: 'INT'>, 'INT4': <TokenType.INT: 'INT'>, 'INT32': <TokenType.INT: 'INT'>, 'INT64': <TokenType.BIGINT: 'BIGINT'>, 'LONG': <TokenType.BIGINT: 'BIGINT'>, 'BIGINT': <TokenType.BIGINT: 'BIGINT'>, 'INT8': <TokenType.TINYINT: 'TINYINT'>, 'UINT': <TokenType.UINT: 'UINT'>, 'DEC': <TokenType.DECIMAL: 'DECIMAL'>, 'DECIMAL': <TokenType.DECIMAL: 'DECIMAL'>, 'BIGDECIMAL': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'BIGNUMERIC': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'MAP': <TokenType.MAP: 'MAP'>, 'NULLABLE': <TokenType.NULLABLE: 'NULLABLE'>, 'NUMBER': <TokenType.DECIMAL: 'DECIMAL'>, 'NUMERIC': <TokenType.DECIMAL: 'DECIMAL'>, 'FIXED': <TokenType.DECIMAL: 'DECIMAL'>, 'REAL': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT4': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT8': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE PRECISION': <TokenType.DOUBLE: 'DOUBLE'>, 'JSON': <TokenType.JSON: 'JSON'>, 'CHAR': <TokenType.CHAR: 'CHAR'>, 'CHARACTER': <TokenType.CHAR: 'CHAR'>, 'NCHAR': <TokenType.NCHAR: 'NCHAR'>, 'VARCHAR': <TokenType.VARCHAR: 'VARCHAR'>, 'VARCHAR2': <TokenType.VARCHAR: 'VARCHAR'>, 'NVARCHAR': <TokenType.NVARCHAR: 'NVARCHAR'>, 'NVARCHAR2': <TokenType.NVARCHAR: 'NVARCHAR'>, 'BPCHAR': <TokenType.BPCHAR: 'BPCHAR'>, 'STR': <TokenType.TEXT: 'TEXT'>, 'STRING': <TokenType.TEXT: 'TEXT'>, 'TEXT': <TokenType.TEXT: 'TEXT'>, 'LONGTEXT': <TokenType.LONGTEXT: 'LONGTEXT'>, 'MEDIUMTEXT': <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, 'TINYTEXT': <TokenType.TINYTEXT: 'TINYTEXT'>, 'CLOB': <TokenType.TEXT: 'TEXT'>, 'LONGVARCHAR': <TokenType.TEXT: 'TEXT'>, 'BINARY': <TokenType.BINARY: 'BINARY'>, 'BLOB': <TokenType.VARBINARY: 'VARBINARY'>, 'LONGBLOB': <TokenType.LONGBLOB: 'LONGBLOB'>, 'MEDIUMBLOB': <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, 'TINYBLOB': <TokenType.TINYBLOB: 'TINYBLOB'>, 'BYTEA': <TokenType.VARBINARY: 'VARBINARY'>, 'VARBINARY': <TokenType.VARBINARY: 'VARBINARY'>, 'TIME': <TokenType.TIME: 'TIME'>, 'TIMETZ': <TokenType.TIMETZ: 'TIMETZ'>, 'TIMESTAMP': <TokenType.TIMESTAMP: 'TIMESTAMP'>, 'TIMESTAMPTZ': <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, 'TIMESTAMPLTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMP_LTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMPNTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'TIMESTAMP_NTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'DATE': <TokenType.DATE: 'DATE'>, 'DATETIME': <TokenType.DATETIME: 'DATETIME'>, 'INT4RANGE': <TokenType.INT4RANGE: 'INT4RANGE'>, 'INT4MULTIRANGE': <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, 'INT8RANGE': <TokenType.INT8RANGE: 'INT8RANGE'>, 'INT8MULTIRANGE': <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, 'NUMRANGE': <TokenType.NUMRANGE: 'NUMRANGE'>, 'NUMMULTIRANGE': <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, 'TSRANGE': <TokenType.TSRANGE: 'TSRANGE'>, 'TSMULTIRANGE': <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, 'TSTZRANGE': <TokenType.TSTZRANGE: 'TSTZRANGE'>, 'TSTZMULTIRANGE': <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, 'DATERANGE': <TokenType.DATERANGE: 'DATERANGE'>, 'DATEMULTIRANGE': <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, 'UNIQUE': <TokenType.UNIQUE: 'UNIQUE'>, 'STRUCT': <TokenType.STRUCT: 'STRUCT'>, 'SEQUENCE': <TokenType.SEQUENCE: 'SEQUENCE'>, 'VARIANT': <TokenType.VARIANT: 'VARIANT'>, 'ALTER': <TokenType.ALTER: 'ALTER'>, 'ANALYZE': <TokenType.COMMAND: 'COMMAND'>, 'CALL': <TokenType.COMMAND: 'COMMAND'>, 'COMMENT': <TokenType.COMMENT: 'COMMENT'>, 'EXPLAIN': <TokenType.COMMAND: 'COMMAND'>, 'GRANT': <TokenType.COMMAND: 'COMMAND'>, 'OPTIMIZE': <TokenType.COMMAND: 'COMMAND'>, 'PREPARE': <TokenType.COMMAND: 'COMMAND'>, 'VACUUM': <TokenType.COMMAND: 'COMMAND'>, 'USER-DEFINED': <TokenType.USERDEFINED: 'USERDEFINED'>, 'FOR VERSION': <TokenType.VERSION_SNAPSHOT: 'VERSION_SNAPSHOT'>, 'FOR TIMESTAMP': <TokenType.TIMESTAMP_SNAPSHOT: 'TIMESTAMP_SNAPSHOT'>, 'BYTEINT': <TokenType.INT: 'INT'>, 'CHAR VARYING': <TokenType.VARCHAR: 'VARCHAR'>, 'CHARACTER VARYING': <TokenType.VARCHAR: 'VARCHAR'>, 'EXCLUDE': <TokenType.EXCEPT: 'EXCEPT'>, 'ILIKE ANY': <TokenType.ILIKE_ANY: 'ILIKE_ANY'>, 'LIKE ANY': <TokenType.LIKE_ANY: 'LIKE_ANY'>, 'MATCH_CONDITION': <TokenType.MATCH_CONDITION: 'MATCH_CONDITION'>, 'MATCH_RECOGNIZE': <TokenType.MATCH_RECOGNIZE: 'MATCH_RECOGNIZE'>, 'MINUS': <TokenType.EXCEPT: 'EXCEPT'>, 'NCHAR VARYING': <TokenType.VARCHAR: 'VARCHAR'>, 'PUT': <TokenType.COMMAND: 'COMMAND'>, 'REMOVE': <TokenType.COMMAND: 'COMMAND'>, 'RM': <TokenType.COMMAND: 'COMMAND'>, 'SAMPLE': <TokenType.TABLE_SAMPLE: 'TABLE_SAMPLE'>, 'SQL_DOUBLE': <TokenType.DOUBLE: 'DOUBLE'>, 'SQL_VARCHAR': <TokenType.VARCHAR: 'VARCHAR'>, 'STORAGE INTEGRATION': <TokenType.STORAGE_INTEGRATION: 'STORAGE_INTEGRATION'>, 'TAG': <TokenType.TAG: 'TAG'>, 'TIMESTAMP_TZ': <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, 'TOP': <TokenType.TOP: 'TOP'>}"}, "sqlglot.dialects.snowflake.Snowflake.Tokenizer.SINGLE_TOKENS": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Tokenizer.SINGLE_TOKENS", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Tokenizer.SINGLE_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'(': <TokenType.L_PAREN: 'L_PAREN'>, ')': <TokenType.R_PAREN: 'R_PAREN'>, '[': <TokenType.L_BRACKET: 'L_BRACKET'>, ']': <TokenType.R_BRACKET: 'R_BRACKET'>, '{': <TokenType.L_BRACE: 'L_BRACE'>, '}': <TokenType.R_BRACE: 'R_BRACE'>, '&': <TokenType.AMP: 'AMP'>, '^': <TokenType.CARET: 'CARET'>, ':': <TokenType.COLON: 'COLON'>, ',': <TokenType.COMMA: 'COMMA'>, '.': <TokenType.DOT: 'DOT'>, '-': <TokenType.DASH: 'DASH'>, '=': <TokenType.EQ: 'EQ'>, '>': <TokenType.GT: 'GT'>, '<': <TokenType.LT: 'LT'>, '%': <TokenType.MOD: 'MOD'>, '!': <TokenType.NOT: 'NOT'>, '|': <TokenType.PIPE: 'PIPE'>, '+': <TokenType.PLUS: 'PLUS'>, ';': <TokenType.SEMICOLON: 'SEMICOLON'>, '/': <TokenType.SLASH: 'SLASH'>, '\\\\': <TokenType.BACKSLASH: 'BACKSLASH'>, '*': <TokenType.STAR: 'STAR'>, '~': <TokenType.TILDA: 'TILDA'>, '?': <TokenType.PLACEHOLDER: 'PLACEHOLDER'>, '@': <TokenType.PARAMETER: 'PARAMETER'>, '#': <TokenType.HASH: 'HASH'>, "'": <TokenType.UNKNOWN: 'UNKNOWN'>, '`': <TokenType.UNKNOWN: 'UNKNOWN'>, '"': <TokenType.UNKNOWN: 'UNKNOWN'>, '$': <TokenType.PARAMETER: 'PARAMETER'>}"}, "sqlglot.dialects.snowflake.Snowflake.Tokenizer.VAR_SINGLE_TOKENS": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Tokenizer.VAR_SINGLE_TOKENS", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Tokenizer.VAR_SINGLE_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'$'}"}, "sqlglot.dialects.snowflake.Snowflake.Tokenizer.COMMANDS": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Tokenizer.COMMANDS", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Tokenizer.COMMANDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.EXECUTE: 'EXECUTE'>, <TokenType.FETCH: 'FETCH'>, <TokenType.COMMAND: 'COMMAND'>}"}, "sqlglot.dialects.snowflake.Snowflake.Generator": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator", "kind": "class", "doc": "<p>Generator converts a given syntax tree to the corresponding SQL string.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>pretty:</strong> Whether to format the produced SQL string.\nDefault: False.</li>\n<li><strong>identify:</strong> Determines when an identifier should be quoted. Possible values are:\nFalse (default): Never quote, except in cases where it's mandatory by the dialect.\nTrue or 'always': Always quote.\n'safe': Only quote identifiers that are case insensitive.</li>\n<li><strong>normalize:</strong> Whether to normalize identifiers to lowercase.\nDefault: False.</li>\n<li><strong>pad:</strong> The pad size in a formatted string. For example, this affects the indentation of\na projection in a query, relative to its nesting level.\nDefault: 2.</li>\n<li><strong>indent:</strong> The indentation size in a formatted string. For example, this affects the\nindentation of subqueries and filters under a <code>WHERE</code> clause.\nDefault: 2.</li>\n<li><strong>normalize_functions:</strong> How to normalize function names. Possible values are:\n\"upper\" or True (default): Convert names to uppercase.\n\"lower\": Convert names to lowercase.\nFalse: Disables function name normalization.</li>\n<li><strong>unsupported_level:</strong> Determines the generator's behavior when it encounters unsupported expressions.\nDefault ErrorLevel.WARN.</li>\n<li><strong>max_unsupported:</strong> Maximum number of unsupported messages to include in a raised UnsupportedError.\nThis is only relevant if unsupported_level is ErrorLevel.RAISE.\nDefault: 3</li>\n<li><strong>leading_comma:</strong> Whether the comma is leading or trailing in select expressions.\nThis is only relevant when generating in pretty mode.\nDefault: False</li>\n<li><strong>max_text_width:</strong> The max number of characters in a segment before creating new lines in pretty mode.\nThe default is on the smaller end because the length only represents a segment and not the true\nline length.\nDefault: 80</li>\n<li><strong>comments:</strong> Whether to preserve comments in the output SQL code.\nDefault: True</li>\n</ul>\n", "bases": "sqlglot.generator.Generator"}, "sqlglot.dialects.snowflake.Snowflake.Generator.PARAMETER_TOKEN": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.PARAMETER_TOKEN", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.PARAMETER_TOKEN", "kind": "variable", "doc": "<p></p>\n", "default_value": "'$'"}, "sqlglot.dialects.snowflake.Snowflake.Generator.MATCHED_BY_SOURCE": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.MATCHED_BY_SOURCE", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.MATCHED_BY_SOURCE", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.snowflake.Snowflake.Generator.SINGLE_STRING_INTERVAL": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.SINGLE_STRING_INTERVAL", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.SINGLE_STRING_INTERVAL", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.snowflake.Snowflake.Generator.JOIN_HINTS": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.JOIN_HINTS", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.JOIN_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.snowflake.Snowflake.Generator.TABLE_HINTS": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.TABLE_HINTS", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.TABLE_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.snowflake.Snowflake.Generator.QUERY_HINTS": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.QUERY_HINTS", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.QUERY_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.snowflake.Snowflake.Generator.AGGREGATE_FILTER_SUPPORTED": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.AGGREGATE_FILTER_SUPPORTED", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.AGGREGATE_FILTER_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.snowflake.Snowflake.Generator.SUPPORTS_TABLE_COPY": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.SUPPORTS_TABLE_COPY", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.SUPPORTS_TABLE_COPY", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.snowflake.Snowflake.Generator.COLLATE_IS_FUNC": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.COLLATE_IS_FUNC", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.COLLATE_IS_FUNC", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.snowflake.Snowflake.Generator.LIMIT_ONLY_LITERALS": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.LIMIT_ONLY_LITERALS", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.LIMIT_ONLY_LITERALS", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.snowflake.Snowflake.Generator.JSON_KEY_VALUE_PAIR_SEP": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.JSON_KEY_VALUE_PAIR_SEP", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.JSON_KEY_VALUE_PAIR_SEP", "kind": "variable", "doc": "<p></p>\n", "default_value": "','"}, "sqlglot.dialects.snowflake.Snowflake.Generator.INSERT_OVERWRITE": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.INSERT_OVERWRITE", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.INSERT_OVERWRITE", "kind": "variable", "doc": "<p></p>\n", "default_value": "' OVERWRITE INTO'"}, "sqlglot.dialects.snowflake.Snowflake.Generator.STRUCT_DELIMITER": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.STRUCT_DELIMITER", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.STRUCT_DELIMITER", "kind": "variable", "doc": "<p></p>\n", "default_value": "('(', ')')"}, "sqlglot.dialects.snowflake.Snowflake.Generator.COPY_PARAMS_ARE_WRAPPED": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.COPY_PARAMS_ARE_WRAPPED", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.COPY_PARAMS_ARE_WRAPPED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.snowflake.Snowflake.Generator.COPY_PARAMS_EQ_REQUIRED": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.COPY_PARAMS_EQ_REQUIRED", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.COPY_PARAMS_EQ_REQUIRED", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.snowflake.Snowflake.Generator.STAR_EXCEPT": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.STAR_EXCEPT", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.STAR_EXCEPT", "kind": "variable", "doc": "<p></p>\n", "default_value": "'EXCLUDE'"}, "sqlglot.dialects.snowflake.Snowflake.Generator.TRANSFORMS": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.TRANSFORMS", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.JSONPathKey'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRoot'>: <function Snowflake.Generator.<lambda>>, <class 'sqlglot.expressions.JSONPathSubscript'>: <function <lambda>>, <class 'sqlglot.expressions.AllowedValuesProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.BackupProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CaseSpecificColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CollateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CommentColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DateFormatColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DefaultColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EncodeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EphemeralColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExcludeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExternalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.GlobalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.HeapProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IcebergProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InheritsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InlineLengthColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IntervalSpan'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtract'>: <function Snowflake.Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtractScalar'>: <function Snowflake.Generator.<lambda>>, <class 'sqlglot.expressions.LanguageProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LocationProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LogProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.MaterializedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NonClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NotForReplicationColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnCommitProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnUpdateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OutputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.PathColumnConstraint'>: <function 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"sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.PROPERTIES_LOCATION", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.AllowedValuesProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.AlgorithmProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.AutoIncrementProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.BackupProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.BlockCompressionProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.CharacterSetProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ChecksumProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.CollateProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Cluster'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ClusteredByProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DataBlocksizeProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.DataDeletionProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DefinerProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.DictRange'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DictProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DistKeyProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DistStyleProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.EngineProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ExternalProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.FallbackProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.FileFormatProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.FreespaceProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.GlobalProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.HeapProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.InheritsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.IcebergProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.InputModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.IsolatedLoadingProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.JournalProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.LanguageProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LikeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LocationProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LockProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LockingProperty'>: <Location.POST_ALIAS: 'POST_ALIAS'>, <class 'sqlglot.expressions.LogProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.MaterializedProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.MergeBlockRatioProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.OnProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.OnCommitProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.Order'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 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'sqlglot.expressions.StabilityProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.StrictProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.TemporaryProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.ToTableProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.TransientProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.TransformModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.MergeTreeTTL'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.UnloggedProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.VolatileProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.WithDataProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 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pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">properties</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Properties</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.snowflake.Snowflake.Generator.values_sql": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.values_sql", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.values_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Values</span>,</span><span class=\"param\">\t<span class=\"n\">values_as_table</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.snowflake.Snowflake.Generator.datatype_sql": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.datatype_sql", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.datatype_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.snowflake.Snowflake.Generator.tonumber_sql": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.tonumber_sql", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.tonumber_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ToNumber</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.snowflake.Snowflake.Generator.timestampfromparts_sql": {"fullname": 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class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TryCast</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.snowflake.Snowflake.Generator.log_sql": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.log_sql", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.log_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Log</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.snowflake.Snowflake.Generator.unnest_sql": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.unnest_sql", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.unnest_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Unnest</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.snowflake.Snowflake.Generator.show_sql": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.show_sql", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.show_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Show</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.snowflake.Snowflake.Generator.regexpextract_sql": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.regexpextract_sql", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.regexpextract_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">RegexpExtract</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.snowflake.Snowflake.Generator.except_op": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.except_op", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.except_op", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Except</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.snowflake.Snowflake.Generator.intersect_op": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.intersect_op", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.intersect_op", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Intersect</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.snowflake.Snowflake.Generator.describe_sql": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.describe_sql", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.describe_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Describe</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.snowflake.Snowflake.Generator.generatedasidentitycolumnconstraint_sql": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.generatedasidentitycolumnconstraint_sql", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.generatedasidentitycolumnconstraint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">GeneratedAsIdentityColumnConstraint</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.snowflake.Snowflake.Generator.swaptable_sql": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.swaptable_sql", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.swaptable_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">SwapTable</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.snowflake.Snowflake.Generator.cluster_sql": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.cluster_sql", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.cluster_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Cluster</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.snowflake.Snowflake.Generator.struct_sql": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.struct_sql", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.struct_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Struct</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.snowflake.Snowflake.Generator.approxquantile_sql": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.approxquantile_sql", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.approxquantile_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ApproxQuantile</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.snowflake.Snowflake.Generator.alterset_sql": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.alterset_sql", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.alterset_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">AlterSet</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.snowflake.Snowflake.Generator.SELECT_KINDS": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.SELECT_KINDS", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.SELECT_KINDS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Tuple[str, ...]", "default_value": "()"}, "sqlglot.dialects.snowflake.Snowflake.Generator.TRY_SUPPORTED": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.TRY_SUPPORTED", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.TRY_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.snowflake.Snowflake.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS": {"fullname": "sqlglot.dialects.snowflake.Snowflake.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'qualify': <function Generator.<lambda>>, 'windows': <function Generator.<lambda>>}"}, "sqlglot.dialects.snowflake.Snowflake.UNESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.snowflake.Snowflake.UNESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.UNESCAPED_SEQUENCES", "kind": "variable", "doc": "<p>Mapping of an escaped sequence (<code>\\n</code>) to its unescaped version (<code>\n</code>).</p>\n", "annotation": ": Dict[str, str]", "default_value": "{'\\\\a': '\\x07', '\\\\b': '\\x08', '\\\\f': '\\x0c', '\\\\n': '\\n', '\\\\r': '\\r', '\\\\t': '\\t', '\\\\v': '\\x0b', '\\\\\\\\': '\\\\'}"}, "sqlglot.dialects.snowflake.Snowflake.tokenizer_class": {"fullname": "sqlglot.dialects.snowflake.Snowflake.tokenizer_class", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.tokenizer_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.snowflake.Snowflake.Tokenizer'>"}, "sqlglot.dialects.snowflake.Snowflake.parser_class": {"fullname": "sqlglot.dialects.snowflake.Snowflake.parser_class", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.parser_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.snowflake.Snowflake.Parser'>"}, "sqlglot.dialects.snowflake.Snowflake.generator_class": {"fullname": "sqlglot.dialects.snowflake.Snowflake.generator_class", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.generator_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.snowflake.Snowflake.Generator'>"}, "sqlglot.dialects.snowflake.Snowflake.TIME_TRIE": {"fullname": "sqlglot.dialects.snowflake.Snowflake.TIME_TRIE", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'Y': {'Y': {'Y': {'Y': {0: True}}, 0: True}}, 'y': {'y': {'y': {'y': {0: True}}, 0: True}}, 'M': {'M': {'M': {'M': {0: True}}, 0: True}, 'O': {'N': {0: True}}, 'I': {0: True}}, 'm': {'m': {'m': {'m': {0: True}}, 0: True}, 'o': {'n': {0: True}}, 'i': {0: True}}, 'D': {'D': {0: True}, 'Y': {0: True}}, 'd': {'d': {0: True}, 'y': {0: True}}, 'H': {'H': {'2': {'4': {0: True}}, '1': {'2': {0: True}}}}, 'h': {'h': {'2': {'4': {0: True}}, '1': {'2': {0: True}}}}, 'S': {'S': {0: True}}, 's': {'s': {0: True}}, 'F': {'F': {0: True, '6': {0: True}}}, 'f': {'f': {0: True, '6': {0: True}}}}"}, "sqlglot.dialects.snowflake.Snowflake.FORMAT_TRIE": {"fullname": "sqlglot.dialects.snowflake.Snowflake.FORMAT_TRIE", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.FORMAT_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'Y': {'Y': {'Y': {'Y': {0: True}}, 0: True}}, 'y': {'y': {'y': {'y': {0: True}}, 0: True}}, 'M': {'M': {'M': {'M': {0: True}}, 0: True}, 'O': {'N': {0: True}}, 'I': {0: True}}, 'm': {'m': {'m': {'m': {0: True}}, 0: True}, 'o': {'n': {0: True}}, 'i': {0: True}}, 'D': {'D': {0: True}, 'Y': {0: True}}, 'd': {'d': {0: True}, 'y': {0: True}}, 'H': {'H': {'2': {'4': {0: True}}, '1': {'2': {0: True}}}}, 'h': {'h': {'2': {'4': {0: True}}, '1': {'2': {0: True}}}}, 'S': {'S': {0: True}}, 's': {'s': {0: True}}, 'F': {'F': {0: True, '6': {0: True}}}, 'f': {'f': {0: True, '6': {0: True}}}}"}, "sqlglot.dialects.snowflake.Snowflake.INVERSE_TIME_MAPPING": {"fullname": "sqlglot.dialects.snowflake.Snowflake.INVERSE_TIME_MAPPING", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.INVERSE_TIME_MAPPING", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'%Y': 'yyyy', '%y': 'yy', '%B': 'mmmm', '%b': 'mon', '%m': 'mm', '%d': 'DD', '%-d': 'dd', '%a': 'DY', '%w': 'dy', '%H': 'hh24', '%I': 'hh12', '%M': 'mi', '%S': 'ss', '%f': 'ff6'}"}, "sqlglot.dialects.snowflake.Snowflake.INVERSE_TIME_TRIE": {"fullname": "sqlglot.dialects.snowflake.Snowflake.INVERSE_TIME_TRIE", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.INVERSE_TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'%': {'Y': {0: True}, 'y': {0: True}, 'B': {0: True}, 'b': {0: True}, 'm': {0: True}, 'd': {0: True}, '-': {'d': {0: True}}, 'a': {0: True}, 'w': {0: True}, 'H': {0: True}, 'I': {0: True}, 'M': {0: True}, 'S': {0: True}, 'f': {0: True}}}"}, "sqlglot.dialects.snowflake.Snowflake.ESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.snowflake.Snowflake.ESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.ESCAPED_SEQUENCES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'\\x07': '\\\\a', '\\x08': '\\\\b', '\\x0c': '\\\\f', '\\n': '\\\\n', '\\r': '\\\\r', '\\t': '\\\\t', '\\x0b': '\\\\v', '\\\\': '\\\\\\\\'}"}, "sqlglot.dialects.snowflake.Snowflake.QUOTE_START": {"fullname": "sqlglot.dialects.snowflake.Snowflake.QUOTE_START", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.QUOTE_START", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.snowflake.Snowflake.QUOTE_END": {"fullname": "sqlglot.dialects.snowflake.Snowflake.QUOTE_END", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.QUOTE_END", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.snowflake.Snowflake.IDENTIFIER_START": {"fullname": "sqlglot.dialects.snowflake.Snowflake.IDENTIFIER_START", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.IDENTIFIER_START", "kind": "variable", "doc": "<p></p>\n", "default_value": "'"'"}, "sqlglot.dialects.snowflake.Snowflake.IDENTIFIER_END": {"fullname": "sqlglot.dialects.snowflake.Snowflake.IDENTIFIER_END", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.IDENTIFIER_END", "kind": "variable", "doc": "<p></p>\n", "default_value": "'"'"}, "sqlglot.dialects.snowflake.Snowflake.BIT_START": {"fullname": "sqlglot.dialects.snowflake.Snowflake.BIT_START", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.BIT_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.snowflake.Snowflake.BIT_END": {"fullname": "sqlglot.dialects.snowflake.Snowflake.BIT_END", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.BIT_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.snowflake.Snowflake.HEX_START": {"fullname": "sqlglot.dialects.snowflake.Snowflake.HEX_START", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.HEX_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""x'""}, "sqlglot.dialects.snowflake.Snowflake.HEX_END": {"fullname": "sqlglot.dialects.snowflake.Snowflake.HEX_END", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.HEX_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""'""}, "sqlglot.dialects.snowflake.Snowflake.BYTE_START": {"fullname": "sqlglot.dialects.snowflake.Snowflake.BYTE_START", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.BYTE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.snowflake.Snowflake.BYTE_END": {"fullname": "sqlglot.dialects.snowflake.Snowflake.BYTE_END", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.BYTE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.snowflake.Snowflake.UNICODE_START": {"fullname": "sqlglot.dialects.snowflake.Snowflake.UNICODE_START", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.UNICODE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.snowflake.Snowflake.UNICODE_END": {"fullname": "sqlglot.dialects.snowflake.Snowflake.UNICODE_END", "modulename": "sqlglot.dialects.snowflake", "qualname": "Snowflake.UNICODE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.spark": {"fullname": "sqlglot.dialects.spark", "modulename": "sqlglot.dialects.spark", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.dialects.spark.Spark": {"fullname": "sqlglot.dialects.spark.Spark", "modulename": "sqlglot.dialects.spark", "qualname": "Spark", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.spark2.Spark2"}, "sqlglot.dialects.spark.Spark.Tokenizer": {"fullname": "sqlglot.dialects.spark.Spark.Tokenizer", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.Tokenizer", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.spark2.Spark2.Tokenizer"}, "sqlglot.dialects.spark.Spark.Tokenizer.RAW_STRINGS": {"fullname": "sqlglot.dialects.spark.Spark.Tokenizer.RAW_STRINGS", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.Tokenizer.RAW_STRINGS", "kind": "variable", "doc": "<p></p>\n", "default_value": "[("r'", "'"), ("R'", "'"), ('r"', '"'), ('R"', '"')]"}, "sqlglot.dialects.spark.Spark.Parser": {"fullname": "sqlglot.dialects.spark.Spark.Parser", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.Parser", "kind": "class", "doc": "<p>Parser consumes a list of tokens produced by the Tokenizer and produces a parsed syntax tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>error_level:</strong> The desired error level.\nDefault: ErrorLevel.IMMEDIATE</li>\n<li><strong>error_message_context:</strong> The amount of context to capture from a query string when displaying\nthe error message (in number of characters).\nDefault: 100</li>\n<li><strong>max_errors:</strong> Maximum number of error messages to include in a raised ParseError.\nThis is only relevant if error_level is ErrorLevel.RAISE.\nDefault: 3</li>\n</ul>\n", "bases": "sqlglot.dialects.spark2.Spark2.Parser"}, "sqlglot.dialects.spark.Spark.Parser.FUNCTIONS": {"fullname": "sqlglot.dialects.spark.Spark.Parser.FUNCTIONS", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.Parser.FUNCTIONS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ABS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Abs'>>, 'ADD_MONTHS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AddMonths'>>, 'ANONYMOUS_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnonymousAggFunc'>>, 'ANY_VALUE': <function _build_with_ignore_nulls.<locals>._parse>, 'APPROX_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_COUNT_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'APPROX_TOP_K': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxTopK'>>, 'ARG_MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARGMAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'MAX_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARG_MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARGMIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'MIN_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Array'>>, 'ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAgg'>>, 'ARRAY_ALL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAll'>>, 'ARRAY_ANY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAny'>>, 'ARRAY_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CONSTRUCT_COMPACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConstructCompact'>>, 'ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayContains'>>, 'FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_OVERLAPS': <bound method Func.from_arg_list of <class 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Func.from_arg_list of <class 'sqlglot.expressions.SHA2'>>, 'SAFE_DIVIDE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SafeDivide'>>, 'SIGN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sign'>>, 'SIGNUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sign'>>, 'SORT_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SortArray'>>, 'SPLIT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpSplit'>>, 'SQRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sqrt'>>, 'STANDARD_HASH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StandardHash'>>, 'STAR_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StarMap'>>, 'STARTS_WITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STARTSWITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STDDEV': <bound method Func.from_arg_list of 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'SUBSTRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Substring'>>, 'SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sum'>>, 'TIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeAdd'>>, 'TIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeDiff'>>, 'TIME_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'TIMEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'TIME_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToDate'>>, 'TIME_STR_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToTime'>>, 'TIME_STR_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToUnix'>>, 'TIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeSub'>>, 'TIME_TO_STR': <bound method Func.from_arg_list of <class 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<class 'sqlglot.expressions.TimestampTrunc'>>, 'TO_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToArray'>>, 'TO_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToBase64'>>, 'TO_CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToChar'>>, 'TO_DAYS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToDays'>>, 'TO_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToMap'>>, 'TO_NUMBER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToNumber'>>, 'TRANSFORM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Transform'>>, 'TRIM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Trim'>>, 'TRY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Try'>>, 'TRY_CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TryCast'>>, 'TS_OR_DI_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDiToDi'>>, 'TS_OR_DS_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsAdd'>>, 'TS_OR_DS_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsDiff'>>, 'TS_OR_DS_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToDate'>>, 'TS_OR_DS_TO_DATE_STR': <function Parser.<lambda>>, 'TS_OR_DS_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTime'>>, 'TS_OR_DS_TO_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTimestamp'>>, 'UNHEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Unhex'>>, 'UNIX_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixDate'>>, 'UNIX_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToStr'>>, 'UNIX_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTime'>>, 'UNIX_TO_TIME_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTimeStr'>>, 'UPPER': <function build_upper>, 'UCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Upper'>>, 'VAR_MAP': <function build_var_map>, 'VARIANCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'VAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Week'>>, 'WEEK_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.WeekOfYear'>>, 'WEEKOFYEAR': <function Spark2.Parser.<lambda>>, 'WHEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.When'>>, 'X_M_L_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.XMLTable'>>, 'XOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Xor'>>, 'YEAR': <function Hive.Parser.<lambda>>, 'GLOB': <function Parser.<lambda>>, 'JSON_EXTRACT_PATH_TEXT': <function build_extract_json_with_path.<locals>._builder>, 'LIKE': <function build_like>, 'LOG2': <function Parser.<lambda>>, 'LOG10': <function Parser.<lambda>>, 'MOD': <function build_mod>, 'TO_HEX': <function build_hex>, 'BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToBase64'>>, 'COLLECT_LIST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAgg'>>, 'COLLECT_SET': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUniqueAgg'>>, 'DATE_FORMAT': <function Hive.Parser.<lambda>>, 'FROM_UNIXTIME': <function build_formatted_time.<locals>._builder>, 'GET_JSON_OBJECT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONExtractScalar'>>, 'LOCATE': <function locate_to_strposition>, 'PERCENTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quantile'>>, 'PERCENTILE_APPROX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'SIZE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'TO_DATE': <function build_formatted_time.<locals>._builder>, 'TO_JSON': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONFormat'>>, 'UNBASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase64'>>, 'UNIX_TIMESTAMP': <function Hive.Parser.<lambda>>, 'AGGREGATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Reduce'>>, 'APPROX_PERCENTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'BOOLEAN': <function _build_as_cast.<locals>.<lambda>>, 'DOUBLE': <function _build_as_cast.<locals>.<lambda>>, 'FLOAT': <function _build_as_cast.<locals>.<lambda>>, 'FROM_UTC_TIMESTAMP': <function Spark2.Parser.<lambda>>, 'INT': <function _build_as_cast.<locals>.<lambda>>, 'MAP_FROM_ARRAYS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Map'>>, 'RLIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpLike'>>, 'SHIFTLEFT': <function binary_from_function.<locals>.<lambda>>, 'SHIFTRIGHT': <function binary_from_function.<locals>.<lambda>>, 'STRING': <function _build_as_cast.<locals>.<lambda>>, 'TO_TIMESTAMP': <function Spark2.Parser.<lambda>>, 'TO_UNIX_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToUnix'>>, 'TO_UTC_TIMESTAMP': <function Spark2.Parser.<lambda>>, 'TRUNC': <function Spark2.Parser.<lambda>>, 'TIMESTAMP_LTZ': <function _build_as_cast.<locals>.<lambda>>, 'TIMESTAMP_NTZ': <function _build_as_cast.<locals>.<lambda>>, 'TRY_ELEMENT_AT': <function Spark.Parser.<lambda>>}"}, "sqlglot.dialects.spark.Spark.Parser.SHOW_TRIE": {"fullname": "sqlglot.dialects.spark.Spark.Parser.SHOW_TRIE", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.Parser.SHOW_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.spark.Spark.Parser.SET_TRIE": {"fullname": "sqlglot.dialects.spark.Spark.Parser.SET_TRIE", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.Parser.SET_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'GLOBAL': {0: True}, 'LOCAL': {0: True}, 'SESSION': {0: True}, 'TRANSACTION': {0: True}}"}, "sqlglot.dialects.spark.Spark.Generator": {"fullname": "sqlglot.dialects.spark.Spark.Generator", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.Generator", "kind": "class", "doc": "<p>Generator converts a given syntax tree to the corresponding SQL string.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>pretty:</strong> Whether to format the produced SQL string.\nDefault: False.</li>\n<li><strong>identify:</strong> Determines when an identifier should be quoted. Possible values are:\nFalse (default): Never quote, except in cases where it's mandatory by the dialect.\nTrue or 'always': Always quote.\n'safe': Only quote identifiers that are case insensitive.</li>\n<li><strong>normalize:</strong> Whether to normalize identifiers to lowercase.\nDefault: False.</li>\n<li><strong>pad:</strong> The pad size in a formatted string. For example, this affects the indentation of\na projection in a query, relative to its nesting level.\nDefault: 2.</li>\n<li><strong>indent:</strong> The indentation size in a formatted string. For example, this affects the\nindentation of subqueries and filters under a <code>WHERE</code> clause.\nDefault: 2.</li>\n<li><strong>normalize_functions:</strong> How to normalize function names. Possible values are:\n\"upper\" or True (default): Convert names to uppercase.\n\"lower\": Convert names to lowercase.\nFalse: Disables function name normalization.</li>\n<li><strong>unsupported_level:</strong> Determines the generator's behavior when it encounters unsupported expressions.\nDefault ErrorLevel.WARN.</li>\n<li><strong>max_unsupported:</strong> Maximum number of unsupported messages to include in a raised UnsupportedError.\nThis is only relevant if unsupported_level is ErrorLevel.RAISE.\nDefault: 3</li>\n<li><strong>leading_comma:</strong> Whether the comma is leading or trailing in select expressions.\nThis is only relevant when generating in pretty mode.\nDefault: False</li>\n<li><strong>max_text_width:</strong> The max number of characters in a segment before creating new lines in pretty mode.\nThe default is on the smaller end because the length only represents a segment and not the true\nline length.\nDefault: 80</li>\n<li><strong>comments:</strong> Whether to preserve comments in the output SQL code.\nDefault: True</li>\n</ul>\n", "bases": "sqlglot.dialects.spark2.Spark2.Generator"}, "sqlglot.dialects.spark.Spark.Generator.SUPPORTS_TO_NUMBER": {"fullname": "sqlglot.dialects.spark.Spark.Generator.SUPPORTS_TO_NUMBER", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.Generator.SUPPORTS_TO_NUMBER", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.spark.Spark.Generator.TYPE_MAPPING": {"fullname": "sqlglot.dialects.spark.Spark.Generator.TYPE_MAPPING", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.Generator.TYPE_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.NCHAR: 'NCHAR'>: 'CHAR', <Type.NVARCHAR: 'NVARCHAR'>: 'VARCHAR', <Type.MEDIUMTEXT: 'MEDIUMTEXT'>: 'TEXT', <Type.LONGTEXT: 'LONGTEXT'>: 'TEXT', <Type.TINYTEXT: 'TINYTEXT'>: 'TEXT', <Type.MEDIUMBLOB: 'MEDIUMBLOB'>: 'BLOB', <Type.LONGBLOB: 'LONGBLOB'>: 'BLOB', <Type.TINYBLOB: 'TINYBLOB'>: 'BLOB', <Type.INET: 'INET'>: 'INET', <Type.ROWVERSION: 'ROWVERSION'>: 'BINARY', <Type.BIT: 'BIT'>: 'BOOLEAN', <Type.DATETIME: 'DATETIME'>: 'TIMESTAMP', <Type.TEXT: 'TEXT'>: 'STRING', <Type.TIME: 'TIME'>: 'TIMESTAMP', <Type.TIMESTAMPTZ: 'TIMESTAMPTZ'>: 'TIMESTAMP', <Type.UTINYINT: 'UTINYINT'>: 'SMALLINT', <Type.VARBINARY: 'VARBINARY'>: 'BINARY', <Type.MONEY: 'MONEY'>: 'DECIMAL(15, 4)', <Type.SMALLMONEY: 'SMALLMONEY'>: 'DECIMAL(6, 4)', <Type.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>: 'STRING', <Type.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>: 'TIMESTAMP_LTZ', <Type.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>: 'TIMESTAMP_NTZ'}"}, "sqlglot.dialects.spark.Spark.Generator.TRANSFORMS": {"fullname": "sqlglot.dialects.spark.Spark.Generator.TRANSFORMS", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.Generator.TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.JSONPathKey'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRoot'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSubscript'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathWildcard'>: <function <lambda>>, <class 'sqlglot.expressions.AllowedValuesProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.BackupProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CaseSpecificColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ClusteredColumnConstraint'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.CollateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CommentColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DateFormatColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DefaultColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EncodeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EphemeralColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExcludeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExternalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.GlobalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.HeapProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IcebergProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InheritsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InlineLengthColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IntervalSpan'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtract'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtractScalar'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.LanguageProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LocationProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LogProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.MaterializedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NonClusteredColumnConstraint'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NotForReplicationColumnConstraint'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.OnCommitProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnProperty'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.OnUpdateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OutputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.PathColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ReturnsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SampleProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetConfigProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SettingsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SharingProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlReadWriteProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlSecurityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StabilityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StrictProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TemporaryProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TitleColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.Timestamp'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransformModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransientProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UppercaseColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UnloggedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VarMap'>: <function var_map_sql>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VolatileProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithOperator'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.Select'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.Property'>: <function _property_sql>, <class 'sqlglot.expressions.ApproxDistinct'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ArgMax'>: <function arg_max_or_min_no_count.<locals>._arg_max_or_min_sql>, <class 'sqlglot.expressions.ArgMin'>: <function arg_max_or_min_no_count.<locals>._arg_max_or_min_sql>, <class 'sqlglot.expressions.ArrayConcat'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ArrayToString'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ArraySize'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.With'>: <function no_recursive_cte_sql>, <class 'sqlglot.expressions.DateAdd'>: <function _add_date_sql>, <class 'sqlglot.expressions.DateStrToDate'>: <function datestrtodate_sql>, <class 'sqlglot.expressions.DateSub'>: <function _add_date_sql>, <class 'sqlglot.expressions.DateToDi'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.DiToDate'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.FileFormatProperty'>: <function Spark2.Generator.<lambda>>, <class 'sqlglot.expressions.FromBase64'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.If'>: <function if_sql.<locals>._if_sql>, <class 'sqlglot.expressions.IsNan'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.JSONFormat'>: <function _json_format_sql>, <class 'sqlglot.expressions.Map'>: <function _map_sql>, <class 'sqlglot.expressions.Max'>: <function max_or_greatest>, <class 'sqlglot.expressions.MD5Digest'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.Min'>: <function min_or_least>, <class 'sqlglot.expressions.NotNullColumnConstraint'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.Create'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.Quantile'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ApproxQuantile'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.RegexpExtract'>: <function regexp_extract_sql>, <class 'sqlglot.expressions.RegexpReplace'>: <function Spark2.Generator.<lambda>>, <class 'sqlglot.expressions.RegexpLike'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.RegexpSplit'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.SafeDivide'>: <function no_safe_divide_sql>, <class 'sqlglot.expressions.SchemaCommentProperty'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.ArrayUniqueAgg'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.Split'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.StrPosition'>: <function strposition_to_locate_sql>, <class 'sqlglot.expressions.StrToDate'>: <function _str_to_date>, <class 'sqlglot.expressions.StrToTime'>: <function Spark2.Generator.<lambda>>, <class 'sqlglot.expressions.StrToUnix'>: <function _str_to_unix_sql>, <class 'sqlglot.expressions.StructExtract'>: <function struct_extract_sql>, <class 'sqlglot.expressions.TimeStrToDate'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.TimeStrToTime'>: <function timestrtotime_sql>, <class 'sqlglot.expressions.TimeStrToUnix'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.TimeToStr'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.TimeToUnix'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ToBase64'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.TsOrDiToDi'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.TsOrDsAdd'>: <function _add_date_sql>, <class 'sqlglot.expressions.TsOrDsDiff'>: <function _date_diff_sql>, <class 'sqlglot.expressions.TsOrDsToDate'>: <function _to_date_sql>, <class 'sqlglot.expressions.TryCast'>: <function Spark.Generator.<lambda>>, <class 'sqlglot.expressions.UnixToStr'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.UnixToTime'>: <function _unix_to_time_sql>, <class 'sqlglot.expressions.UnixToTimeStr'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.PartitionedByProperty'>: <function Spark.Generator.<lambda>>, <class 'sqlglot.expressions.NumberToStr'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.National'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.PrimaryKeyColumnConstraint'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.ParseJSON'>: <function Hive.Generator.<lambda>>, <class 'sqlglot.expressions.ArraySum'>: <function Spark2.Generator.<lambda>>, <class 'sqlglot.expressions.AtTimeZone'>: <function Spark2.Generator.<lambda>>, <class 'sqlglot.expressions.BitwiseLeftShift'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.BitwiseRightShift'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.DateFromParts'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.DateTrunc'>: <function Spark2.Generator.<lambda>>, <class 'sqlglot.expressions.DayOfMonth'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.DayOfWeek'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.DayOfYear'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.From'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.FromTimeZone'>: <function Spark2.Generator.<lambda>>, <class 'sqlglot.expressions.LogicalAnd'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.LogicalOr'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.Pivot'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.Reduce'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.TimestampTrunc'>: <function Spark2.Generator.<lambda>>, <class 'sqlglot.expressions.Trim'>: <function trim_sql>, <class 'sqlglot.expressions.VariancePop'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.WeekOfYear'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.WithinGroup'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.ArrayConstructCompact'>: <function Spark.Generator.<lambda>>, <class 'sqlglot.expressions.StartsWith'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.TimestampAdd'>: <function Spark.Generator.<lambda>>}"}, "sqlglot.dialects.spark.Spark.Generator.bracket_sql": {"fullname": "sqlglot.dialects.spark.Spark.Generator.bracket_sql", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.Generator.bracket_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Bracket</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.spark.Spark.Generator.computedcolumnconstraint_sql": {"fullname": "sqlglot.dialects.spark.Spark.Generator.computedcolumnconstraint_sql", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.Generator.computedcolumnconstraint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ComputedColumnConstraint</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.spark.Spark.Generator.anyvalue_sql": {"fullname": "sqlglot.dialects.spark.Spark.Generator.anyvalue_sql", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.Generator.anyvalue_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">AnyValue</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.spark.Spark.Generator.datediff_sql": {"fullname": "sqlglot.dialects.spark.Spark.Generator.datediff_sql", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.Generator.datediff_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DateDiff</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.spark.Spark.Generator.SELECT_KINDS": {"fullname": "sqlglot.dialects.spark.Spark.Generator.SELECT_KINDS", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.Generator.SELECT_KINDS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Tuple[str, ...]", "default_value": "()"}, "sqlglot.dialects.spark.Spark.Generator.TRY_SUPPORTED": {"fullname": "sqlglot.dialects.spark.Spark.Generator.TRY_SUPPORTED", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.Generator.TRY_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.spark.Spark.UNESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.spark.Spark.UNESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.UNESCAPED_SEQUENCES", "kind": "variable", "doc": "<p>Mapping of an escaped sequence (<code>\\n</code>) to its unescaped version (<code>\n</code>).</p>\n", "annotation": ": Dict[str, str]", "default_value": "{'\\\\a': '\\x07', '\\\\b': '\\x08', '\\\\f': '\\x0c', '\\\\n': '\\n', '\\\\r': '\\r', '\\\\t': '\\t', '\\\\v': '\\x0b', '\\\\\\\\': '\\\\'}"}, "sqlglot.dialects.spark.Spark.tokenizer_class": {"fullname": "sqlglot.dialects.spark.Spark.tokenizer_class", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.tokenizer_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.spark.Spark.Tokenizer'>"}, "sqlglot.dialects.spark.Spark.parser_class": {"fullname": "sqlglot.dialects.spark.Spark.parser_class", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.parser_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.spark.Spark.Parser'>"}, "sqlglot.dialects.spark.Spark.generator_class": {"fullname": "sqlglot.dialects.spark.Spark.generator_class", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.generator_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.spark.Spark.Generator'>"}, "sqlglot.dialects.spark.Spark.TIME_TRIE": {"fullname": "sqlglot.dialects.spark.Spark.TIME_TRIE", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'y': {0: True, 'y': {'y': {'y': {0: True}}, 0: True}}, 'Y': {0: True, 'Y': {'Y': {'Y': {0: True}}, 0: True}}, 'M': {'M': {'M': {'M': {0: True}, 0: True}, 0: True}, 0: True}, 'd': {'d': {0: True}, 0: True}, 'H': {'H': {0: True}, 0: True}, 'h': {'h': {0: True}, 0: True}, 'm': {'m': {0: True}, 0: True}, 's': {'s': {0: True}, 0: True}, 'S': {'S': {'S': {'S': {'S': {'S': {0: True}}}}}}, 'a': {0: True}, 'D': {'D': {0: True}, 0: True}, 'E': {0: True, 'E': {0: True, 'E': {0: True, 'E': {0: True}}}}}"}, "sqlglot.dialects.spark.Spark.FORMAT_TRIE": {"fullname": "sqlglot.dialects.spark.Spark.FORMAT_TRIE", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.FORMAT_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'y': {0: True, 'y': {'y': {'y': {0: True}}, 0: True}}, 'Y': {0: True, 'Y': {'Y': {'Y': {0: True}}, 0: True}}, 'M': {'M': {'M': {'M': {0: True}, 0: True}, 0: True}, 0: True}, 'd': {'d': {0: True}, 0: True}, 'H': {'H': {0: True}, 0: True}, 'h': {'h': {0: True}, 0: True}, 'm': {'m': {0: True}, 0: True}, 's': {'s': {0: True}, 0: True}, 'S': {'S': {'S': {'S': {'S': {'S': {0: True}}}}}}, 'a': {0: True}, 'D': {'D': {0: True}, 0: True}, 'E': {0: True, 'E': {0: True, 'E': {0: True, 'E': {0: True}}}}}"}, "sqlglot.dialects.spark.Spark.INVERSE_TIME_MAPPING": {"fullname": "sqlglot.dialects.spark.Spark.INVERSE_TIME_MAPPING", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.INVERSE_TIME_MAPPING", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'%Y': 'yyyy', '%y': 'yy', '%B': 'MMMM', '%b': 'MMM', '%m': 'MM', '%-m': 'M', '%d': 'dd', '%-d': 'd', '%H': 'HH', '%-H': 'H', '%I': 'hh', '%-I': 'h', '%M': 'mm', '%-M': 'm', '%S': 'ss', '%-S': 's', '%f': 'SSSSSS', '%p': 'a', '%j': 'DD', '%-j': 'D', '%a': 'EEE', '%A': 'EEEE'}"}, "sqlglot.dialects.spark.Spark.INVERSE_TIME_TRIE": {"fullname": "sqlglot.dialects.spark.Spark.INVERSE_TIME_TRIE", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.INVERSE_TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'%': {'Y': {0: True}, 'y': {0: True}, 'B': {0: True}, 'b': {0: True}, 'm': {0: True}, '-': {'m': {0: True}, 'd': {0: True}, 'H': {0: True}, 'I': {0: True}, 'M': {0: True}, 'S': {0: True}, 'j': {0: True}}, 'd': {0: True}, 'H': {0: True}, 'I': {0: True}, 'M': {0: True}, 'S': {0: True}, 'f': {0: True}, 'p': {0: True}, 'j': {0: True}, 'a': {0: True}, 'A': {0: True}}}"}, "sqlglot.dialects.spark.Spark.ESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.spark.Spark.ESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.ESCAPED_SEQUENCES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'\\x07': '\\\\a', '\\x08': '\\\\b', '\\x0c': '\\\\f', '\\n': '\\\\n', '\\r': '\\\\r', '\\t': '\\\\t', '\\x0b': '\\\\v', '\\\\': '\\\\\\\\'}"}, "sqlglot.dialects.spark.Spark.QUOTE_START": {"fullname": "sqlglot.dialects.spark.Spark.QUOTE_START", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.QUOTE_START", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.spark.Spark.QUOTE_END": {"fullname": "sqlglot.dialects.spark.Spark.QUOTE_END", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.QUOTE_END", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.spark.Spark.IDENTIFIER_START": {"fullname": "sqlglot.dialects.spark.Spark.IDENTIFIER_START", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.IDENTIFIER_START", "kind": "variable", "doc": "<p></p>\n", "default_value": "'`'"}, "sqlglot.dialects.spark.Spark.IDENTIFIER_END": {"fullname": "sqlglot.dialects.spark.Spark.IDENTIFIER_END", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.IDENTIFIER_END", "kind": "variable", "doc": "<p></p>\n", "default_value": "'`'"}, "sqlglot.dialects.spark.Spark.BIT_START": {"fullname": "sqlglot.dialects.spark.Spark.BIT_START", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.BIT_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.spark.Spark.BIT_END": {"fullname": "sqlglot.dialects.spark.Spark.BIT_END", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.BIT_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.spark.Spark.HEX_START": {"fullname": "sqlglot.dialects.spark.Spark.HEX_START", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.HEX_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""X'""}, "sqlglot.dialects.spark.Spark.HEX_END": {"fullname": "sqlglot.dialects.spark.Spark.HEX_END", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.HEX_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""'""}, "sqlglot.dialects.spark.Spark.BYTE_START": {"fullname": "sqlglot.dialects.spark.Spark.BYTE_START", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.BYTE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.spark.Spark.BYTE_END": {"fullname": "sqlglot.dialects.spark.Spark.BYTE_END", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.BYTE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.spark.Spark.UNICODE_START": {"fullname": "sqlglot.dialects.spark.Spark.UNICODE_START", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.UNICODE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.spark.Spark.UNICODE_END": {"fullname": "sqlglot.dialects.spark.Spark.UNICODE_END", "modulename": "sqlglot.dialects.spark", "qualname": "Spark.UNICODE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.spark2": {"fullname": "sqlglot.dialects.spark2", "modulename": "sqlglot.dialects.spark2", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.dialects.spark2.temporary_storage_provider": {"fullname": "sqlglot.dialects.spark2.temporary_storage_provider", "modulename": "sqlglot.dialects.spark2", "qualname": "temporary_storage_provider", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.spark2.Spark2": {"fullname": "sqlglot.dialects.spark2.Spark2", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.hive.Hive"}, "sqlglot.dialects.spark2.Spark2.Parser": {"fullname": "sqlglot.dialects.spark2.Spark2.Parser", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.Parser", "kind": "class", "doc": "<p>Parser consumes a list of tokens produced by the Tokenizer and produces a parsed syntax tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>error_level:</strong> The desired error level.\nDefault: ErrorLevel.IMMEDIATE</li>\n<li><strong>error_message_context:</strong> The amount of context to capture from a query string when displaying\nthe error message (in number of characters).\nDefault: 100</li>\n<li><strong>max_errors:</strong> Maximum number of error messages to include in a raised ParseError.\nThis is only relevant if error_level is ErrorLevel.RAISE.\nDefault: 3</li>\n</ul>\n", "bases": "sqlglot.dialects.hive.Hive.Parser"}, "sqlglot.dialects.spark2.Spark2.Parser.TRIM_PATTERN_FIRST": {"fullname": "sqlglot.dialects.spark2.Spark2.Parser.TRIM_PATTERN_FIRST", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.Parser.TRIM_PATTERN_FIRST", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.spark2.Spark2.Parser.FUNCTIONS": {"fullname": "sqlglot.dialects.spark2.Spark2.Parser.FUNCTIONS", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.Parser.FUNCTIONS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ABS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Abs'>>, 'ADD_MONTHS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AddMonths'>>, 'ANONYMOUS_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnonymousAggFunc'>>, 'ANY_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnyValue'>>, 'APPROX_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_COUNT_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'APPROX_TOP_K': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxTopK'>>, 'ARG_MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARGMAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'MAX_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARG_MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARGMIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'MIN_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Array'>>, 'ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAgg'>>, 'ARRAY_ALL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAll'>>, 'ARRAY_ANY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAny'>>, 'ARRAY_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CONSTRUCT_COMPACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConstructCompact'>>, 'ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayContains'>>, 'FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_OVERLAPS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayOverlaps'>>, 'ARRAY_SIZE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_SORT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySort'>>, 'ARRAY_SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySum'>>, 'ARRAY_TO_STRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_JOIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_UNION_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUnionAgg'>>, 'ARRAY_UNIQUE_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUniqueAgg'>>, 'AVG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Avg'>>, 'CASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Case'>>, 'CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cast'>>, 'CAST_TO_STR_TYPE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CastToStrType'>>, 'CBRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cbrt'>>, 'CEIL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CEILING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CHR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'COALESCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'IFNULL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'NVL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'COLLATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Collate'>>, 'COMBINED_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedAggFunc'>>, 'COMBINED_PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedParameterizedAgg'>>, 'CONCAT': <function Parser.<lambda>>, 'CONCAT_WS': <function Parser.<lambda>>, 'CONNECT_BY_ROOT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ConnectByRoot'>>, 'CONVERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Convert'>>, 'CORR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Corr'>>, 'COUNT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Count'>>, 'COUNT_IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COUNTIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COVAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarPop'>>, 'COVAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarSamp'>>, 'CURRENT_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDate'>>, 'CURRENT_DATETIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDatetime'>>, 'CURRENT_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTime'>>, 'CURRENT_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTimestamp'>>, 'CURRENT_USER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentUser'>>, 'DATE': <function _build_as_cast.<locals>.<lambda>>, 'DATE_ADD': <function Hive.Parser.<lambda>>, 'DATEDIFF': <function Hive.Parser.<lambda>>, 'DATE_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateDiff'>>, 'DATE_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATE_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateStrToDate'>>, 'DATE_SUB': <function Hive.Parser.<lambda>>, 'DATE_TO_DATE_STR': <function Parser.<lambda>>, 'DATE_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateToDi'>>, 'DATE_TRUNC': <function Spark2.Parser.<lambda>>, 'DATETIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeAdd'>>, 'DATETIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeDiff'>>, 'DATETIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeSub'>>, 'DATETIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeTrunc'>>, 'DAY': <function Hive.Parser.<lambda>>, 'DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAYOFMONTH': <function Spark2.Parser.<lambda>>, 'DAY_OF_WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAYOFWEEK': <function Spark2.Parser.<lambda>>, 'DAY_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DAYOFYEAR': <function Spark2.Parser.<lambda>>, 'DECODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Decode'>>, 'DI_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DiToDate'>>, 'ENCODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Encode'>>, 'EXP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Exp'>>, 'EXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Explode'>>, 'EXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ExplodeOuter'>>, 'EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Extract'>>, 'FIRST': <function _build_with_ignore_nulls.<locals>._parse>, 'FIRST_VALUE': 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'STRUCT_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StructExtract'>>, 'STUFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stuff'>>, 'INSERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stuff'>>, 'SUBSTRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Substring'>>, 'SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sum'>>, 'TIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeAdd'>>, 'TIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeDiff'>>, 'TIME_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'TIMEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'TIME_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToDate'>>, 'TIME_STR_TO_TIME': <bound method Func.from_arg_list of <class 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Func.from_arg_list of <class 'sqlglot.expressions.Trim'>>, 'TRY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Try'>>, 'TRY_CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TryCast'>>, 'TS_OR_DI_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDiToDi'>>, 'TS_OR_DS_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsAdd'>>, 'TS_OR_DS_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsDiff'>>, 'TS_OR_DS_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToDate'>>, 'TS_OR_DS_TO_DATE_STR': <function Parser.<lambda>>, 'TS_OR_DS_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTime'>>, 'TS_OR_DS_TO_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTimestamp'>>, 'UNHEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Unhex'>>, 'UNIX_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixDate'>>, 'UNIX_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToStr'>>, 'UNIX_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTime'>>, 'UNIX_TO_TIME_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTimeStr'>>, 'UPPER': <function build_upper>, 'UCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Upper'>>, 'VAR_MAP': <function build_var_map>, 'VARIANCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'VAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Week'>>, 'WEEK_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.WeekOfYear'>>, 'WEEKOFYEAR': <function Spark2.Parser.<lambda>>, 'WHEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.When'>>, 'X_M_L_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.XMLTable'>>, 'XOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Xor'>>, 'YEAR': <function Hive.Parser.<lambda>>, 'GLOB': <function Parser.<lambda>>, 'JSON_EXTRACT_PATH_TEXT': <function build_extract_json_with_path.<locals>._builder>, 'LIKE': <function build_like>, 'LOG2': <function Parser.<lambda>>, 'LOG10': <function Parser.<lambda>>, 'MOD': <function build_mod>, 'TO_HEX': <function build_hex>, 'BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToBase64'>>, 'COLLECT_LIST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAgg'>>, 'COLLECT_SET': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUniqueAgg'>>, 'DATE_FORMAT': <function Hive.Parser.<lambda>>, 'FROM_UNIXTIME': <function build_formatted_time.<locals>._builder>, 'GET_JSON_OBJECT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONExtractScalar'>>, 'LOCATE': <function locate_to_strposition>, 'PERCENTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quantile'>>, 'PERCENTILE_APPROX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'SIZE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'TO_DATE': <function build_formatted_time.<locals>._builder>, 'TO_JSON': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONFormat'>>, 'UNBASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase64'>>, 'UNIX_TIMESTAMP': <function Hive.Parser.<lambda>>, 'AGGREGATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Reduce'>>, 'APPROX_PERCENTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'BOOLEAN': <function _build_as_cast.<locals>.<lambda>>, 'DOUBLE': <function _build_as_cast.<locals>.<lambda>>, 'FLOAT': <function _build_as_cast.<locals>.<lambda>>, 'FROM_UTC_TIMESTAMP': <function Spark2.Parser.<lambda>>, 'INT': <function _build_as_cast.<locals>.<lambda>>, 'MAP_FROM_ARRAYS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Map'>>, 'RLIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpLike'>>, 'SHIFTLEFT': <function binary_from_function.<locals>.<lambda>>, 'SHIFTRIGHT': <function binary_from_function.<locals>.<lambda>>, 'STRING': <function _build_as_cast.<locals>.<lambda>>, 'TO_TIMESTAMP': <function Spark2.Parser.<lambda>>, 'TO_UNIX_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToUnix'>>, 'TO_UTC_TIMESTAMP': <function Spark2.Parser.<lambda>>, 'TRUNC': <function Spark2.Parser.<lambda>>}"}, "sqlglot.dialects.spark2.Spark2.Parser.FUNCTION_PARSERS": {"fullname": "sqlglot.dialects.spark2.Spark2.Parser.FUNCTION_PARSERS", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.Parser.FUNCTION_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'CAST': <function Parser.<lambda>>, 'CONVERT': <function Parser.<lambda>>, 'DECODE': <function Parser.<lambda>>, 'EXTRACT': <function Parser.<lambda>>, 'JSON_OBJECT': <function Parser.<lambda>>, 'JSON_OBJECTAGG': <function Parser.<lambda>>, 'JSON_TABLE': <function Parser.<lambda>>, 'MATCH': <function Parser.<lambda>>, 'OPENJSON': <function Parser.<lambda>>, 'POSITION': <function Parser.<lambda>>, 'PREDICT': <function Parser.<lambda>>, 'SAFE_CAST': <function Parser.<lambda>>, 'STRING_AGG': <function Parser.<lambda>>, 'SUBSTRING': <function Parser.<lambda>>, 'TRIM': <function Parser.<lambda>>, 'TRY_CAST': <function Parser.<lambda>>, 'TRY_CONVERT': <function Parser.<lambda>>, 'BROADCAST': <function Spark2.Parser.<lambda>>, 'BROADCASTJOIN': <function Spark2.Parser.<lambda>>, 'MAPJOIN': <function Spark2.Parser.<lambda>>, 'MERGE': <function Spark2.Parser.<lambda>>, 'SHUFFLEMERGE': <function Spark2.Parser.<lambda>>, 'MERGEJOIN': <function Spark2.Parser.<lambda>>, 'SHUFFLE_HASH': <function Spark2.Parser.<lambda>>, 'SHUFFLE_REPLICATE_NL': <function Spark2.Parser.<lambda>>}"}, "sqlglot.dialects.spark2.Spark2.Parser.SHOW_TRIE": {"fullname": "sqlglot.dialects.spark2.Spark2.Parser.SHOW_TRIE", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.Parser.SHOW_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.spark2.Spark2.Parser.SET_TRIE": {"fullname": "sqlglot.dialects.spark2.Spark2.Parser.SET_TRIE", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.Parser.SET_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'GLOBAL': {0: True}, 'LOCAL': {0: True}, 'SESSION': {0: True}, 'TRANSACTION': {0: True}}"}, "sqlglot.dialects.spark2.Spark2.Generator": {"fullname": "sqlglot.dialects.spark2.Spark2.Generator", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.Generator", "kind": "class", "doc": "<p>Generator converts a given syntax tree to the corresponding SQL string.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>pretty:</strong> Whether to format the produced SQL string.\nDefault: False.</li>\n<li><strong>identify:</strong> Determines when an identifier should be quoted. Possible values are:\nFalse (default): Never quote, except in cases where it's mandatory by the dialect.\nTrue or 'always': Always quote.\n'safe': Only quote identifiers that are case insensitive.</li>\n<li><strong>normalize:</strong> Whether to normalize identifiers to lowercase.\nDefault: False.</li>\n<li><strong>pad:</strong> The pad size in a formatted string. For example, this affects the indentation of\na projection in a query, relative to its nesting level.\nDefault: 2.</li>\n<li><strong>indent:</strong> The indentation size in a formatted string. For example, this affects the\nindentation of subqueries and filters under a <code>WHERE</code> clause.\nDefault: 2.</li>\n<li><strong>normalize_functions:</strong> How to normalize function names. Possible values are:\n\"upper\" or True (default): Convert names to uppercase.\n\"lower\": Convert names to lowercase.\nFalse: Disables function name normalization.</li>\n<li><strong>unsupported_level:</strong> Determines the generator's behavior when it encounters unsupported expressions.\nDefault ErrorLevel.WARN.</li>\n<li><strong>max_unsupported:</strong> Maximum number of unsupported messages to include in a raised UnsupportedError.\nThis is only relevant if unsupported_level is ErrorLevel.RAISE.\nDefault: 3</li>\n<li><strong>leading_comma:</strong> Whether the comma is leading or trailing in select expressions.\nThis is only relevant when generating in pretty mode.\nDefault: False</li>\n<li><strong>max_text_width:</strong> The max number of characters in a segment before creating new lines in pretty mode.\nThe default is on the smaller end because the length only represents a segment and not the true\nline length.\nDefault: 80</li>\n<li><strong>comments:</strong> Whether to preserve comments in the output SQL code.\nDefault: True</li>\n</ul>\n", "bases": "sqlglot.dialects.hive.Hive.Generator"}, "sqlglot.dialects.spark2.Spark2.Generator.QUERY_HINTS": {"fullname": "sqlglot.dialects.spark2.Spark2.Generator.QUERY_HINTS", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.Generator.QUERY_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.spark2.Spark2.Generator.NVL2_SUPPORTED": {"fullname": "sqlglot.dialects.spark2.Spark2.Generator.NVL2_SUPPORTED", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.Generator.NVL2_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.spark2.Spark2.Generator.CAN_IMPLEMENT_ARRAY_ANY": {"fullname": "sqlglot.dialects.spark2.Spark2.Generator.CAN_IMPLEMENT_ARRAY_ANY", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.Generator.CAN_IMPLEMENT_ARRAY_ANY", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, 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<class 'sqlglot.expressions.ArraySum'>: <function Spark2.Generator.<lambda>>, <class 'sqlglot.expressions.AtTimeZone'>: <function Spark2.Generator.<lambda>>, <class 'sqlglot.expressions.BitwiseLeftShift'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.BitwiseRightShift'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.DateFromParts'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.DateTrunc'>: <function Spark2.Generator.<lambda>>, <class 'sqlglot.expressions.DayOfMonth'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.DayOfWeek'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.DayOfYear'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.From'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.FromTimeZone'>: <function Spark2.Generator.<lambda>>, <class 'sqlglot.expressions.LogicalAnd'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.LogicalOr'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.Pivot'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.Reduce'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.TimestampTrunc'>: <function Spark2.Generator.<lambda>>, <class 'sqlglot.expressions.Trim'>: <function trim_sql>, <class 'sqlglot.expressions.VariancePop'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.WeekOfYear'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.WithinGroup'>: <function preprocess.<locals>._to_sql>}"}, "sqlglot.dialects.spark2.Spark2.Generator.WRAP_DERIVED_VALUES": {"fullname": "sqlglot.dialects.spark2.Spark2.Generator.WRAP_DERIVED_VALUES", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.Generator.WRAP_DERIVED_VALUES", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.spark2.Spark2.Generator.CREATE_FUNCTION_RETURN_AS": {"fullname": "sqlglot.dialects.spark2.Spark2.Generator.CREATE_FUNCTION_RETURN_AS", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.Generator.CREATE_FUNCTION_RETURN_AS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.spark2.Spark2.Generator.struct_sql": {"fullname": "sqlglot.dialects.spark2.Spark2.Generator.struct_sql", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.Generator.struct_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Struct</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.spark2.Spark2.Generator.cast_sql": {"fullname": "sqlglot.dialects.spark2.Spark2.Generator.cast_sql", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.Generator.cast_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Cast</span>,</span><span class=\"param\">\t<span class=\"n\">safe_prefix</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.spark2.Spark2.Generator.columndef_sql": {"fullname": "sqlglot.dialects.spark2.Spark2.Generator.columndef_sql", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.Generator.columndef_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ColumnDef</span>, </span><span class=\"param\"><span class=\"n\">sep</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">' '</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.spark2.Spark2.Generator.SELECT_KINDS": {"fullname": "sqlglot.dialects.spark2.Spark2.Generator.SELECT_KINDS", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.Generator.SELECT_KINDS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Tuple[str, ...]", "default_value": "()"}, "sqlglot.dialects.spark2.Spark2.Generator.TRY_SUPPORTED": {"fullname": "sqlglot.dialects.spark2.Spark2.Generator.TRY_SUPPORTED", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.Generator.TRY_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.spark2.Spark2.Tokenizer": {"fullname": "sqlglot.dialects.spark2.Spark2.Tokenizer", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.Tokenizer", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.hive.Hive.Tokenizer"}, "sqlglot.dialects.spark2.Spark2.Tokenizer.HEX_STRINGS": {"fullname": "sqlglot.dialects.spark2.Spark2.Tokenizer.HEX_STRINGS", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.Tokenizer.HEX_STRINGS", "kind": "variable", "doc": "<p></p>\n", "default_value": "[("X'", "'")]"}, "sqlglot.dialects.spark2.Spark2.UNESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.spark2.Spark2.UNESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.UNESCAPED_SEQUENCES", "kind": "variable", "doc": "<p>Mapping of an escaped sequence (<code>\\n</code>) to its unescaped version (<code>\n</code>).</p>\n", "annotation": ": Dict[str, str]", "default_value": "{'\\\\a': '\\x07', '\\\\b': '\\x08', '\\\\f': '\\x0c', '\\\\n': '\\n', '\\\\r': '\\r', '\\\\t': '\\t', '\\\\v': '\\x0b', '\\\\\\\\': '\\\\'}"}, "sqlglot.dialects.spark2.Spark2.tokenizer_class": {"fullname": "sqlglot.dialects.spark2.Spark2.tokenizer_class", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.tokenizer_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.spark2.Spark2.Tokenizer'>"}, "sqlglot.dialects.spark2.Spark2.parser_class": {"fullname": "sqlglot.dialects.spark2.Spark2.parser_class", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.parser_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.spark2.Spark2.Parser'>"}, "sqlglot.dialects.spark2.Spark2.generator_class": {"fullname": "sqlglot.dialects.spark2.Spark2.generator_class", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.generator_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.spark2.Spark2.Generator'>"}, "sqlglot.dialects.spark2.Spark2.TIME_TRIE": {"fullname": "sqlglot.dialects.spark2.Spark2.TIME_TRIE", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'y': {0: True, 'y': {'y': {'y': {0: True}}, 0: True}}, 'Y': {0: True, 'Y': {'Y': {'Y': {0: True}}, 0: True}}, 'M': {'M': {'M': {'M': {0: True}, 0: True}, 0: True}, 0: True}, 'd': {'d': {0: True}, 0: True}, 'H': {'H': {0: True}, 0: True}, 'h': {'h': {0: True}, 0: True}, 'm': {'m': {0: True}, 0: True}, 's': {'s': {0: True}, 0: True}, 'S': {'S': {'S': {'S': {'S': {'S': {0: True}}}}}}, 'a': {0: True}, 'D': {'D': {0: True}, 0: True}, 'E': {0: True, 'E': {0: True, 'E': {0: True, 'E': {0: True}}}}}"}, "sqlglot.dialects.spark2.Spark2.FORMAT_TRIE": {"fullname": "sqlglot.dialects.spark2.Spark2.FORMAT_TRIE", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.FORMAT_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'y': {0: True, 'y': {'y': {'y': {0: True}}, 0: True}}, 'Y': {0: True, 'Y': {'Y': {'Y': {0: True}}, 0: True}}, 'M': {'M': {'M': {'M': {0: True}, 0: True}, 0: True}, 0: True}, 'd': {'d': {0: True}, 0: True}, 'H': {'H': {0: True}, 0: True}, 'h': {'h': {0: True}, 0: True}, 'm': {'m': {0: True}, 0: True}, 's': {'s': {0: True}, 0: True}, 'S': {'S': {'S': {'S': {'S': {'S': {0: True}}}}}}, 'a': {0: True}, 'D': {'D': {0: True}, 0: True}, 'E': {0: True, 'E': {0: True, 'E': {0: True, 'E': {0: True}}}}}"}, "sqlglot.dialects.spark2.Spark2.INVERSE_TIME_MAPPING": {"fullname": "sqlglot.dialects.spark2.Spark2.INVERSE_TIME_MAPPING", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.INVERSE_TIME_MAPPING", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'%Y': 'yyyy', '%y': 'yy', '%B': 'MMMM', '%b': 'MMM', '%m': 'MM', '%-m': 'M', '%d': 'dd', '%-d': 'd', '%H': 'HH', '%-H': 'H', '%I': 'hh', '%-I': 'h', '%M': 'mm', '%-M': 'm', '%S': 'ss', '%-S': 's', '%f': 'SSSSSS', '%p': 'a', '%j': 'DD', '%-j': 'D', '%a': 'EEE', '%A': 'EEEE'}"}, "sqlglot.dialects.spark2.Spark2.INVERSE_TIME_TRIE": {"fullname": "sqlglot.dialects.spark2.Spark2.INVERSE_TIME_TRIE", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.INVERSE_TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'%': {'Y': {0: True}, 'y': {0: True}, 'B': {0: True}, 'b': {0: True}, 'm': {0: True}, '-': {'m': {0: True}, 'd': {0: True}, 'H': {0: True}, 'I': {0: True}, 'M': {0: True}, 'S': {0: True}, 'j': {0: True}}, 'd': {0: True}, 'H': {0: True}, 'I': {0: True}, 'M': {0: True}, 'S': {0: True}, 'f': {0: True}, 'p': {0: True}, 'j': {0: True}, 'a': {0: True}, 'A': {0: True}}}"}, "sqlglot.dialects.spark2.Spark2.ESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.spark2.Spark2.ESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.ESCAPED_SEQUENCES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'\\x07': '\\\\a', '\\x08': '\\\\b', '\\x0c': '\\\\f', '\\n': '\\\\n', '\\r': '\\\\r', '\\t': '\\\\t', '\\x0b': '\\\\v', '\\\\': '\\\\\\\\'}"}, "sqlglot.dialects.spark2.Spark2.QUOTE_START": {"fullname": "sqlglot.dialects.spark2.Spark2.QUOTE_START", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.QUOTE_START", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.spark2.Spark2.QUOTE_END": {"fullname": "sqlglot.dialects.spark2.Spark2.QUOTE_END", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.QUOTE_END", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.spark2.Spark2.IDENTIFIER_START": {"fullname": "sqlglot.dialects.spark2.Spark2.IDENTIFIER_START", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.IDENTIFIER_START", "kind": "variable", "doc": "<p></p>\n", "default_value": "'`'"}, "sqlglot.dialects.spark2.Spark2.IDENTIFIER_END": {"fullname": "sqlglot.dialects.spark2.Spark2.IDENTIFIER_END", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.IDENTIFIER_END", "kind": "variable", "doc": "<p></p>\n", "default_value": "'`'"}, "sqlglot.dialects.spark2.Spark2.BIT_START": {"fullname": "sqlglot.dialects.spark2.Spark2.BIT_START", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.BIT_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.spark2.Spark2.BIT_END": {"fullname": "sqlglot.dialects.spark2.Spark2.BIT_END", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.BIT_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.spark2.Spark2.HEX_START": {"fullname": "sqlglot.dialects.spark2.Spark2.HEX_START", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.HEX_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""X'""}, "sqlglot.dialects.spark2.Spark2.HEX_END": {"fullname": "sqlglot.dialects.spark2.Spark2.HEX_END", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.HEX_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""'""}, "sqlglot.dialects.spark2.Spark2.BYTE_START": {"fullname": "sqlglot.dialects.spark2.Spark2.BYTE_START", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.BYTE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.spark2.Spark2.BYTE_END": {"fullname": "sqlglot.dialects.spark2.Spark2.BYTE_END", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.BYTE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.spark2.Spark2.UNICODE_START": {"fullname": "sqlglot.dialects.spark2.Spark2.UNICODE_START", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.UNICODE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.spark2.Spark2.UNICODE_END": {"fullname": "sqlglot.dialects.spark2.Spark2.UNICODE_END", "modulename": "sqlglot.dialects.spark2", "qualname": "Spark2.UNICODE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.sqlite": {"fullname": "sqlglot.dialects.sqlite", "modulename": "sqlglot.dialects.sqlite", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.dialects.sqlite.SQLite": {"fullname": "sqlglot.dialects.sqlite.SQLite", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.dialect.Dialect"}, "sqlglot.dialects.sqlite.SQLite.NORMALIZATION_STRATEGY": {"fullname": "sqlglot.dialects.sqlite.SQLite.NORMALIZATION_STRATEGY", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.NORMALIZATION_STRATEGY", "kind": "variable", "doc": "<p>Specifies the strategy according to which identifiers should be normalized.</p>\n", "default_value": "<NormalizationStrategy.CASE_INSENSITIVE: 'CASE_INSENSITIVE'>"}, "sqlglot.dialects.sqlite.SQLite.SUPPORTS_SEMI_ANTI_JOIN": {"fullname": "sqlglot.dialects.sqlite.SQLite.SUPPORTS_SEMI_ANTI_JOIN", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.SUPPORTS_SEMI_ANTI_JOIN", "kind": "variable", "doc": "<p>Whether <code>SEMI</code> or <code>ANTI</code> joins are supported.</p>\n", "default_value": "False"}, "sqlglot.dialects.sqlite.SQLite.TYPED_DIVISION": {"fullname": "sqlglot.dialects.sqlite.SQLite.TYPED_DIVISION", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.TYPED_DIVISION", "kind": "variable", "doc": "<p>Whether the behavior of <code>a / b</code> depends on the types of <code>a</code> and <code>b</code>.\nFalse means <code>a / b</code> is always float division.\nTrue means <code>a / b</code> is integer division if both <code>a</code> and <code>b</code> are integers.</p>\n", "default_value": "True"}, "sqlglot.dialects.sqlite.SQLite.SAFE_DIVISION": {"fullname": "sqlglot.dialects.sqlite.SQLite.SAFE_DIVISION", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.SAFE_DIVISION", "kind": "variable", "doc": "<p>Whether division by zero throws an error (<code>False</code>) or returns NULL (<code>True</code>).</p>\n", "default_value": "True"}, "sqlglot.dialects.sqlite.SQLite.Tokenizer": {"fullname": "sqlglot.dialects.sqlite.SQLite.Tokenizer", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Tokenizer", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.tokens.Tokenizer"}, "sqlglot.dialects.sqlite.SQLite.Tokenizer.IDENTIFIERS": {"fullname": "sqlglot.dialects.sqlite.SQLite.Tokenizer.IDENTIFIERS", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Tokenizer.IDENTIFIERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "['"', ('[', ']'), '`']"}, "sqlglot.dialects.sqlite.SQLite.Tokenizer.HEX_STRINGS": {"fullname": "sqlglot.dialects.sqlite.SQLite.Tokenizer.HEX_STRINGS", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Tokenizer.HEX_STRINGS", "kind": "variable", "doc": "<p></p>\n", "default_value": "[("x'", "'"), ("X'", "'"), ('0x', ''), ('0X', '')]"}, "sqlglot.dialects.sqlite.SQLite.Parser": {"fullname": "sqlglot.dialects.sqlite.SQLite.Parser", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Parser", "kind": "class", "doc": "<p>Parser consumes a list of tokens produced by the Tokenizer and produces a parsed syntax tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>error_level:</strong> The desired error level.\nDefault: ErrorLevel.IMMEDIATE</li>\n<li><strong>error_message_context:</strong> The amount of context to capture from a query string when displaying\nthe error message (in number of characters).\nDefault: 100</li>\n<li><strong>max_errors:</strong> Maximum number of error messages to include in a raised ParseError.\nThis is only relevant if error_level is ErrorLevel.RAISE.\nDefault: 3</li>\n</ul>\n", "bases": "sqlglot.parser.Parser"}, "sqlglot.dialects.sqlite.SQLite.Parser.FUNCTIONS": {"fullname": "sqlglot.dialects.sqlite.SQLite.Parser.FUNCTIONS", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Parser.FUNCTIONS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ABS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Abs'>>, 'ADD_MONTHS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AddMonths'>>, 'ANONYMOUS_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnonymousAggFunc'>>, 'ANY_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnyValue'>>, 'APPROX_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_COUNT_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'APPROX_TOP_K': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxTopK'>>, 'ARG_MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARGMAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'MAX_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARG_MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARGMIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'MIN_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Array'>>, 'ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAgg'>>, 'ARRAY_ALL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAll'>>, 'ARRAY_ANY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAny'>>, 'ARRAY_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CONSTRUCT_COMPACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConstructCompact'>>, 'ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayContains'>>, 'FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_OVERLAPS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayOverlaps'>>, 'ARRAY_SIZE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_SORT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySort'>>, 'ARRAY_SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySum'>>, 'ARRAY_TO_STRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_JOIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_UNION_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUnionAgg'>>, 'ARRAY_UNIQUE_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUniqueAgg'>>, 'AVG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Avg'>>, 'CASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Case'>>, 'CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cast'>>, 'CAST_TO_STR_TYPE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CastToStrType'>>, 'CBRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cbrt'>>, 'CEIL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CEILING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CHR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'COALESCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'IFNULL': <bound method Func.from_arg_list of <class 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method Func.from_arg_list of <class 'sqlglot.expressions.DateDiff'>>, 'DATE_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATE_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateStrToDate'>>, 'DATE_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateSub'>>, 'DATE_TO_DATE_STR': <function Parser.<lambda>>, 'DATE_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateToDi'>>, 'DATE_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateTrunc'>>, 'DATETIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeAdd'>>, 'DATETIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeDiff'>>, 'DATETIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeSub'>>, 'DATETIME_TRUNC': 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method Func.from_arg_list of <class 'sqlglot.expressions.GenerateSeries'>>, 'GREATEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Greatest'>>, 'GROUP_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GroupConcat'>>, 'HEX': <function build_hex>, 'HLL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Hll'>>, 'IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'IIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'INITCAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Initcap'>>, 'IS_INF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'ISINF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'IS_NAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'ISNAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'J_S_O_N_ARRAY': <bound method Func.from_arg_list of 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Func.from_arg_list of <class 'sqlglot.expressions.Ln'>>, 'LOG': <function build_logarithm>, 'LOGICAL_AND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'BOOL_AND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'BOOLAND_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'LOGICAL_OR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'BOOL_OR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'BOOLOR_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'LOWER': <function build_lower>, 'LCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lower'>>, 'LOWER_HEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LowerHex'>>, 'MD5': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MD5'>>, 'MD5_DIGEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MD5Digest'>>, 'MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Map'>>, 'MAP_FROM_ENTRIES': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MapFromEntries'>>, 'MATCH_AGAINST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MatchAgainst'>>, 'MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Max'>>, 'MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Min'>>, 'MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Month'>>, 'MONTHS_BETWEEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MonthsBetween'>>, 'NEXT_VALUE_FOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NextValueFor'>>, 'NTH_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NthValue'>>, 'NULLIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Nullif'>>, 'NUMBER_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NumberToStr'>>, 'NVL2': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Nvl2'>>, 'OPEN_J_S_O_N': <bound method Func.from_arg_list of <class 'sqlglot.expressions.OpenJSON'>>, 'PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParameterizedAgg'>>, 'PARSE_JSON': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParseJSON'>>, 'JSON_PARSE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParseJSON'>>, 'PERCENTILE_CONT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PercentileCont'>>, 'PERCENTILE_DISC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PercentileDisc'>>, 'POSEXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Posexplode'>>, 'POSEXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PosexplodeOuter'>>, 'POWER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Pow'>>, 'POW': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Pow'>>, 'PREDICT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Predict'>>, 'QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quantile'>>, 'QUARTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quarter'>>, 'RAND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'RANDOM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'RANDN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Randn'>>, 'RANGE_N': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RangeN'>>, 'READ_CSV': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ReadCSV'>>, 'REDUCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Reduce'>>, 'REGEXP_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpExtract'>>, 'REGEXP_I_LIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpILike'>>, 'REGEXP_LIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpLike'>>, 'REGEXP_REPLACE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpReplace'>>, 'REGEXP_SPLIT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpSplit'>>, 'REPEAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Repeat'>>, 'RIGHT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Right'>>, 'ROUND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Round'>>, 'ROW_NUMBER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RowNumber'>>, 'SHA': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA'>>, 'SHA1': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA'>>, 'SHA2': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA2'>>, 'SAFE_DIVIDE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SafeDivide'>>, 'SIGN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sign'>>, 'SIGNUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sign'>>, 'SORT_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SortArray'>>, 'SPLIT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Split'>>, 'SQRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sqrt'>>, 'STANDARD_HASH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StandardHash'>>, 'STAR_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StarMap'>>, 'STARTS_WITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STARTSWITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STDDEV': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stddev'>>, 'STDDEV_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StddevPop'>>, 'STDDEV_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StddevSamp'>>, 'STR_POSITION': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrPosition'>>, 'STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToDate'>>, 'STR_TO_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToMap'>>, 'STR_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToTime'>>, 'STR_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToUnix'>>, 'STRUCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Struct'>>, 'STRUCT_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StructExtract'>>, 'STUFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stuff'>>, 'INSERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stuff'>>, 'SUBSTRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Substring'>>, 'SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sum'>>, 'TIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeAdd'>>, 'TIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeDiff'>>, 'TIME_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'TIMEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'TIME_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToDate'>>, 'TIME_STR_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToTime'>>, 'TIME_STR_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToUnix'>>, 'TIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeSub'>>, 'TIME_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeToStr'>>, 'TIME_TO_TIME_STR': <function Parser.<lambda>>, 'TIME_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeToUnix'>>, 'TIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeTrunc'>>, 'TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Timestamp'>>, 'TIMESTAMP_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampAdd'>>, 'TIMESTAMPDIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampDiff'>>, 'TIMESTAMP_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampDiff'>>, 'TIMESTAMP_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampFromParts'>>, 'TIMESTAMPFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampFromParts'>>, 'TIMESTAMP_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampSub'>>, 'TIMESTAMP_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampTrunc'>>, 'TO_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToArray'>>, 'TO_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToBase64'>>, 'TO_CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToChar'>>, 'TO_DAYS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToDays'>>, 'TO_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToMap'>>, 'TO_NUMBER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToNumber'>>, 'TRANSFORM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Transform'>>, 'TRIM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Trim'>>, 'TRY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Try'>>, 'TRY_CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TryCast'>>, 'TS_OR_DI_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDiToDi'>>, 'TS_OR_DS_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsAdd'>>, 'TS_OR_DS_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsDiff'>>, 'TS_OR_DS_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToDate'>>, 'TS_OR_DS_TO_DATE_STR': <function Parser.<lambda>>, 'TS_OR_DS_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTime'>>, 'TS_OR_DS_TO_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTimestamp'>>, 'UNHEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Unhex'>>, 'UNIX_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixDate'>>, 'UNIX_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToStr'>>, 'UNIX_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTime'>>, 'UNIX_TO_TIME_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTimeStr'>>, 'UPPER': <function build_upper>, 'UCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Upper'>>, 'VAR_MAP': <function build_var_map>, 'VARIANCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'VAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Week'>>, 'WEEK_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.WeekOfYear'>>, 'WEEKOFYEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.WeekOfYear'>>, 'WHEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.When'>>, 'X_M_L_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.XMLTable'>>, 'XOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Xor'>>, 'YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Year'>>, 'GLOB': <function Parser.<lambda>>, 'JSON_EXTRACT_PATH_TEXT': <function build_extract_json_with_path.<locals>._builder>, 'LIKE': <function build_like>, 'LOG2': <function Parser.<lambda>>, 'LOG10': <function Parser.<lambda>>, 'MOD': <function build_mod>, 'TO_HEX': <function build_hex>, 'EDITDIST3': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Levenshtein'>>, 'STRFTIME': <function _build_strftime>}"}, "sqlglot.dialects.sqlite.SQLite.Parser.STRING_ALIASES": {"fullname": "sqlglot.dialects.sqlite.SQLite.Parser.STRING_ALIASES", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Parser.STRING_ALIASES", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.sqlite.SQLite.Parser.TABLE_ALIAS_TOKENS": {"fullname": "sqlglot.dialects.sqlite.SQLite.Parser.TABLE_ALIAS_TOKENS", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Parser.TABLE_ALIAS_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.KILL: 'KILL'>, <TokenType.MONEY: 'MONEY'>, <TokenType.COPY: 'COPY'>, <TokenType.PERCENT: 'PERCENT'>, <TokenType.TAG: 'TAG'>, <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, <TokenType.VOLATILE: 'VOLATILE'>, <TokenType.IDENTIFIER: 'IDENTIFIER'>, <TokenType.VARBINARY: 'VARBINARY'>, <TokenType.HSTORE: 'HSTORE'>, <TokenType.ASC: 'ASC'>, <TokenType.IPADDRESS: 'IPADDRESS'>, <TokenType.ISNULL: 'ISNULL'>, <TokenType.TEMPORARY: 'TEMPORARY'>, <TokenType.PROCEDURE: 'PROCEDURE'>, <TokenType.SCHEMA: 'SCHEMA'>, <TokenType.NUMRANGE: 'NUMRANGE'>, <TokenType.DATE32: 'DATE32'>, <TokenType.INT8RANGE: 'INT8RANGE'>, <TokenType.ANTI: 'ANTI'>, <TokenType.AGGREGATEFUNCTION: 'AGGREGATEFUNCTION'>, <TokenType.VIEW: 'VIEW'>, <TokenType.VARCHAR: 'VARCHAR'>, <TokenType.TIMETZ: 'TIMETZ'>, <TokenType.GEOMETRY: 'GEOMETRY'>, <TokenType.BEGIN: 'BEGIN'>, <TokenType.ENUM8: 'ENUM8'>, <TokenType.INDEX: 'INDEX'>, <TokenType.PARTITION: 'PARTITION'>, <TokenType.UINT256: 'UINT256'>, <TokenType.BIGINT: 'BIGINT'>, <TokenType.CACHE: 'CACHE'>, <TokenType.OPERATOR: 'OPERATOR'>, <TokenType.COLUMN: 'COLUMN'>, <TokenType.INT128: 'INT128'>, <TokenType.SMALLMONEY: 'SMALLMONEY'>, <TokenType.HLLSKETCH: 'HLLSKETCH'>, <TokenType.UNPIVOT: 'UNPIVOT'>, <TokenType.SMALLINT: 'SMALLINT'>, <TokenType.INT256: 'INT256'>, <TokenType.FLOAT: 'FLOAT'>, <TokenType.COMMIT: 'COMMIT'>, <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, <TokenType.EXISTS: 'EXISTS'>, <TokenType.NULL: 'NULL'>, <TokenType.RECURSIVE: 'RECURSIVE'>, <TokenType.SET: 'SET'>, <TokenType.NULLABLE: 'NULLABLE'>, <TokenType.REFRESH: 'REFRESH'>, <TokenType.TINYTEXT: 'TINYTEXT'>, <TokenType.SHOW: 'SHOW'>, <TokenType.DEFAULT: 'DEFAULT'>, <TokenType.DATE: 'DATE'>, <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <TokenType.MERGE: 'MERGE'>, <TokenType.FIRST: 'FIRST'>, <TokenType.BINARY: 'BINARY'>, <TokenType.ARRAY: 'ARRAY'>, <TokenType.SERIAL: 'SERIAL'>, <TokenType.EXECUTE: 'EXECUTE'>, <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, <TokenType.INTERVAL: 'INTERVAL'>, <TokenType.PRAGMA: 'PRAGMA'>, <TokenType.STORAGE_INTEGRATION: 'STORAGE_INTEGRATION'>, <TokenType.BPCHAR: 'BPCHAR'>, <TokenType.BIT: 'BIT'>, <TokenType.UINT: 'UINT'>, <TokenType.UUID: 'UUID'>, <TokenType.STRUCT: 'STRUCT'>, <TokenType.FALSE: 'FALSE'>, <TokenType.FUNCTION: 'FUNCTION'>, <TokenType.TOP: 'TOP'>, <TokenType.SUPER: 'SUPER'>, <TokenType.CASE: 'CASE'>, <TokenType.IMAGE: 'IMAGE'>, <TokenType.UBIGINT: 'UBIGINT'>, <TokenType.LONGBLOB: 'LONGBLOB'>, <TokenType.ROLLUP: 'ROLLUP'>, <TokenType.VAR: 'VAR'>, <TokenType.COMMAND: 'COMMAND'>, <TokenType.LOAD: 'LOAD'>, <TokenType.TRUNCATE: 'TRUNCATE'>, <TokenType.KEEP: 'KEEP'>, <TokenType.UMEDIUMINT: 'UMEDIUMINT'>, <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, <TokenType.UINT128: 'UINT128'>, <TokenType.END: 'END'>, <TokenType.MAP: 'MAP'>, <TokenType.IPV4: 'IPV4'>, <TokenType.USERDEFINED: 'USERDEFINED'>, <TokenType.REFERENCES: 'REFERENCES'>, <TokenType.REPLACE: 'REPLACE'>, <TokenType.RANGE: 'RANGE'>, <TokenType.NVARCHAR: 'NVARCHAR'>, <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, <TokenType.TRUE: 'TRUE'>, <TokenType.TIMESTAMP_MS: 'TIMESTAMP_MS'>, <TokenType.VARIANT: 'VARIANT'>, <TokenType.ENUM: 'ENUM'>, <TokenType.USE: 'USE'>, <TokenType.USMALLINT: 'USMALLINT'>, <TokenType.OVERLAPS: 'OVERLAPS'>, <TokenType.TIMESTAMP_S: 'TIMESTAMP_S'>, <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, <TokenType.UNIQUE: 'UNIQUE'>, <TokenType.ORDINALITY: 'ORDINALITY'>, <TokenType.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>, <TokenType.TEXT: 'TEXT'>, <TokenType.DATABASE: 'DATABASE'>, <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, <TokenType.PSEUDO_TYPE: 'PSEUDO_TYPE'>, <TokenType.FIXEDSTRING: 'FIXEDSTRING'>, <TokenType.NEXT: 'NEXT'>, <TokenType.INT: 'INT'>, <TokenType.BIGSERIAL: 'BIGSERIAL'>, <TokenType.BOOLEAN: 'BOOLEAN'>, <TokenType.IS: 'IS'>, <TokenType.CONSTRAINT: 'CONSTRAINT'>, <TokenType.FINAL: 'FINAL'>, <TokenType.UNKNOWN: 'UNKNOWN'>, <TokenType.SETTINGS: 'SETTINGS'>, <TokenType.ROWS: 'ROWS'>, <TokenType.TSTZRANGE: 'TSTZRANGE'>, <TokenType.DATETIME64: 'DATETIME64'>, <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, <TokenType.DATETIME: 'DATETIME'>, <TokenType.MEDIUMINT: 'MEDIUMINT'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>, <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, <TokenType.XML: 'XML'>, <TokenType.JSON: 'JSON'>, <TokenType.UTINYINT: 'UTINYINT'>, <TokenType.DELETE: 'DELETE'>, <TokenType.TIME: 'TIME'>, <TokenType.UDECIMAL: 'UDECIMAL'>, <TokenType.NESTED: 'NESTED'>, <TokenType.SEMI: 'SEMI'>, <TokenType.DESC: 'DESC'>, <TokenType.ROWVERSION: 'ROWVERSION'>, <TokenType.TIMESTAMP_NS: 'TIMESTAMP_NS'>, <TokenType.ANY: 'ANY'>, <TokenType.DIV: 'DIV'>, <TokenType.DICTIONARY: 'DICTIONARY'>, <TokenType.INET: 'INET'>, <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, <TokenType.COMMENT: 'COMMENT'>, <TokenType.CURRENT_USER: 'CURRENT_USER'>, <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>, <TokenType.ALL: 'ALL'>, <TokenType.NAME: 'NAME'>, <TokenType.SOME: 'SOME'>, <TokenType.ENUM16: 'ENUM16'>, <TokenType.YEAR: 'YEAR'>, <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, <TokenType.DOUBLE: 'DOUBLE'>, <TokenType.INT4RANGE: 'INT4RANGE'>, <TokenType.FORMAT: 'FORMAT'>, <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, <TokenType.IPPREFIX: 'IPPREFIX'>, <TokenType.OVERWRITE: 'OVERWRITE'>, <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>, <TokenType.COLLATE: 'COLLATE'>, <TokenType.FILTER: 'FILTER'>, <TokenType.JSONB: 'JSONB'>, <TokenType.TDIGEST: 'TDIGEST'>, <TokenType.CHAR: 'CHAR'>, <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.ROW: 'ROW'>, <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.TABLE: 'TABLE'>, <TokenType.DATERANGE: 'DATERANGE'>, <TokenType.TSRANGE: 'TSRANGE'>, <TokenType.ESCAPE: 'ESCAPE'>, <TokenType.PIVOT: 'PIVOT'>, <TokenType.DECIMAL: 'DECIMAL'>, <TokenType.NCHAR: 'NCHAR'>, <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, <TokenType.UPDATE: 'UPDATE'>, <TokenType.MODEL: 'MODEL'>, <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, <TokenType.SEQUENCE: 'SEQUENCE'>, <TokenType.LONGTEXT: 'LONGTEXT'>, <TokenType.DESCRIBE: 'DESCRIBE'>, <TokenType.IPV6: 'IPV6'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, <TokenType.TINYINT: 'TINYINT'>, <TokenType.TINYBLOB: 'TINYBLOB'>}"}, "sqlglot.dialects.sqlite.SQLite.Parser.SHOW_TRIE": {"fullname": "sqlglot.dialects.sqlite.SQLite.Parser.SHOW_TRIE", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Parser.SHOW_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.sqlite.SQLite.Parser.SET_TRIE": {"fullname": "sqlglot.dialects.sqlite.SQLite.Parser.SET_TRIE", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Parser.SET_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'GLOBAL': {0: True}, 'LOCAL': {0: True}, 'SESSION': {0: True}, 'TRANSACTION': {0: True}}"}, "sqlglot.dialects.sqlite.SQLite.Generator": {"fullname": "sqlglot.dialects.sqlite.SQLite.Generator", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Generator", "kind": "class", "doc": "<p>Generator converts a given syntax tree to the corresponding SQL string.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>pretty:</strong> Whether to format the produced SQL string.\nDefault: False.</li>\n<li><strong>identify:</strong> Determines when an identifier should be quoted. Possible values are:\nFalse (default): Never quote, except in cases where it's mandatory by the dialect.\nTrue or 'always': Always quote.\n'safe': Only quote identifiers that are case insensitive.</li>\n<li><strong>normalize:</strong> Whether to normalize identifiers to lowercase.\nDefault: False.</li>\n<li><strong>pad:</strong> The pad size in a formatted string. For example, this affects the indentation of\na projection in a query, relative to its nesting level.\nDefault: 2.</li>\n<li><strong>indent:</strong> The indentation size in a formatted string. For example, this affects the\nindentation of subqueries and filters under a <code>WHERE</code> clause.\nDefault: 2.</li>\n<li><strong>normalize_functions:</strong> How to normalize function names. Possible values are:\n\"upper\" or True (default): Convert names to uppercase.\n\"lower\": Convert names to lowercase.\nFalse: Disables function name normalization.</li>\n<li><strong>unsupported_level:</strong> Determines the generator's behavior when it encounters unsupported expressions.\nDefault ErrorLevel.WARN.</li>\n<li><strong>max_unsupported:</strong> Maximum number of unsupported messages to include in a raised UnsupportedError.\nThis is only relevant if unsupported_level is ErrorLevel.RAISE.\nDefault: 3</li>\n<li><strong>leading_comma:</strong> Whether the comma is leading or trailing in select expressions.\nThis is only relevant when generating in pretty mode.\nDefault: False</li>\n<li><strong>max_text_width:</strong> The max number of characters in a segment before creating new lines in pretty mode.\nThe default is on the smaller end because the length only represents a segment and not the true\nline length.\nDefault: 80</li>\n<li><strong>comments:</strong> Whether to preserve comments in the output SQL code.\nDefault: True</li>\n</ul>\n", "bases": "sqlglot.generator.Generator"}, "sqlglot.dialects.sqlite.SQLite.Generator.JOIN_HINTS": {"fullname": "sqlglot.dialects.sqlite.SQLite.Generator.JOIN_HINTS", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Generator.JOIN_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.sqlite.SQLite.Generator.TABLE_HINTS": {"fullname": "sqlglot.dialects.sqlite.SQLite.Generator.TABLE_HINTS", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Generator.TABLE_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.sqlite.SQLite.Generator.QUERY_HINTS": {"fullname": "sqlglot.dialects.sqlite.SQLite.Generator.QUERY_HINTS", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Generator.QUERY_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.sqlite.SQLite.Generator.NVL2_SUPPORTED": {"fullname": "sqlglot.dialects.sqlite.SQLite.Generator.NVL2_SUPPORTED", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Generator.NVL2_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.sqlite.SQLite.Generator.JSON_PATH_BRACKETED_KEY_SUPPORTED": {"fullname": "sqlglot.dialects.sqlite.SQLite.Generator.JSON_PATH_BRACKETED_KEY_SUPPORTED", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Generator.JSON_PATH_BRACKETED_KEY_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.sqlite.SQLite.Generator.SUPPORTS_CREATE_TABLE_LIKE": {"fullname": "sqlglot.dialects.sqlite.SQLite.Generator.SUPPORTS_CREATE_TABLE_LIKE", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Generator.SUPPORTS_CREATE_TABLE_LIKE", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.sqlite.SQLite.Generator.SUPPORTS_TABLE_ALIAS_COLUMNS": {"fullname": "sqlglot.dialects.sqlite.SQLite.Generator.SUPPORTS_TABLE_ALIAS_COLUMNS", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Generator.SUPPORTS_TABLE_ALIAS_COLUMNS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.sqlite.SQLite.Generator.SUPPORTS_TO_NUMBER": {"fullname": "sqlglot.dialects.sqlite.SQLite.Generator.SUPPORTS_TO_NUMBER", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Generator.SUPPORTS_TO_NUMBER", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.sqlite.SQLite.Generator.SUPPORTED_JSON_PATH_PARTS": {"fullname": "sqlglot.dialects.sqlite.SQLite.Generator.SUPPORTED_JSON_PATH_PARTS", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Generator.SUPPORTED_JSON_PATH_PARTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.JSONPathSubscript'>, <class 'sqlglot.expressions.JSONPathRoot'>, <class 'sqlglot.expressions.JSONPathKey'>}"}, "sqlglot.dialects.sqlite.SQLite.Generator.TYPE_MAPPING": {"fullname": "sqlglot.dialects.sqlite.SQLite.Generator.TYPE_MAPPING", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Generator.TYPE_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.NCHAR: 'NCHAR'>: 'TEXT', <Type.NVARCHAR: 'NVARCHAR'>: 'TEXT', <Type.MEDIUMTEXT: 'MEDIUMTEXT'>: 'TEXT', <Type.LONGTEXT: 'LONGTEXT'>: 'TEXT', <Type.TINYTEXT: 'TINYTEXT'>: 'TEXT', <Type.MEDIUMBLOB: 'MEDIUMBLOB'>: 'BLOB', <Type.LONGBLOB: 'LONGBLOB'>: 'BLOB', <Type.TINYBLOB: 'TINYBLOB'>: 'BLOB', <Type.INET: 'INET'>: 'INET', <Type.ROWVERSION: 'ROWVERSION'>: 'VARBINARY', <Type.BOOLEAN: 'BOOLEAN'>: 'INTEGER', <Type.TINYINT: 'TINYINT'>: 'INTEGER', <Type.SMALLINT: 'SMALLINT'>: 'INTEGER', <Type.INT: 'INT'>: 'INTEGER', <Type.BIGINT: 'BIGINT'>: 'INTEGER', <Type.FLOAT: 'FLOAT'>: 'REAL', <Type.DOUBLE: 'DOUBLE'>: 'REAL', <Type.DECIMAL: 'DECIMAL'>: 'REAL', <Type.CHAR: 'CHAR'>: 'TEXT', <Type.VARCHAR: 'VARCHAR'>: 'TEXT', <Type.BINARY: 'BINARY'>: 'BLOB', <Type.VARBINARY: 'VARBINARY'>: 'BLOB'}"}, "sqlglot.dialects.sqlite.SQLite.Generator.TOKEN_MAPPING": {"fullname": "sqlglot.dialects.sqlite.SQLite.Generator.TOKEN_MAPPING", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Generator.TOKEN_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>: 'AUTOINCREMENT'}"}, "sqlglot.dialects.sqlite.SQLite.Generator.TRANSFORMS": {"fullname": "sqlglot.dialects.sqlite.SQLite.Generator.TRANSFORMS", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Generator.TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.JSONPathKey'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRoot'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSubscript'>: <function <lambda>>, <class 'sqlglot.expressions.AllowedValuesProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.BackupProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CaseSpecificColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CollateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CommentColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DateFormatColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DefaultColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EncodeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EphemeralColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExcludeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExternalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.GlobalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.HeapProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IcebergProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InheritsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InlineLengthColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IntervalSpan'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtract'>: <function _json_extract_sql>, <class 'sqlglot.expressions.JSONExtractScalar'>: <function arrow_json_extract_sql>, <class 'sqlglot.expressions.LanguageProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LocationProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LogProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.MaterializedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NonClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NotForReplicationColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnCommitProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnUpdateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OutputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.PathColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ReturnsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SampleProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetConfigProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SettingsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SharingProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlReadWriteProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlSecurityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StabilityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StrictProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TemporaryProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TitleColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.Timestamp'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransformModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransientProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UppercaseColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UnloggedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VarMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VolatileProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithOperator'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.AnyValue'>: <function any_value_to_max_sql>, <class 'sqlglot.expressions.Concat'>: <function concat_to_dpipe_sql>, <class 'sqlglot.expressions.CountIf'>: <function count_if_to_sum>, <class 'sqlglot.expressions.Create'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.CurrentDate'>: <function SQLite.Generator.<lambda>>, <class 'sqlglot.expressions.CurrentTime'>: <function SQLite.Generator.<lambda>>, <class 'sqlglot.expressions.CurrentTimestamp'>: <function SQLite.Generator.<lambda>>, <class 'sqlglot.expressions.DateAdd'>: <function _date_add_sql>, <class 'sqlglot.expressions.DateStrToDate'>: <function SQLite.Generator.<lambda>>, <class 'sqlglot.expressions.If'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ILike'>: <function no_ilike_sql>, <class 'sqlglot.expressions.Levenshtein'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.LogicalOr'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.LogicalAnd'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.Pivot'>: <function no_pivot_sql>, <class 'sqlglot.expressions.Rand'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.Select'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.TableSample'>: <function no_tablesample_sql>, <class 'sqlglot.expressions.TimeStrToTime'>: <function SQLite.Generator.<lambda>>, <class 'sqlglot.expressions.TimeToStr'>: <function SQLite.Generator.<lambda>>, <class 'sqlglot.expressions.TryCast'>: <function no_trycast_sql>, <class 'sqlglot.expressions.TsOrDsToTimestamp'>: <function SQLite.Generator.<lambda>>}"}, "sqlglot.dialects.sqlite.SQLite.Generator.PROPERTIES_LOCATION": {"fullname": "sqlglot.dialects.sqlite.SQLite.Generator.PROPERTIES_LOCATION", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Generator.PROPERTIES_LOCATION", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.AllowedValuesProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.AlgorithmProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.AutoIncrementProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.BackupProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.BlockCompressionProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.CharacterSetProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.ChecksumProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.CollateProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.Cluster'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.ClusteredByProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.DataBlocksizeProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.DataDeletionProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.DefinerProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.DictRange'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.DictProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.DistKeyProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.DistStyleProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.EngineProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.ExternalProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.FallbackProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.FileFormatProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.FreespaceProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.GlobalProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.HeapProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.InheritsProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.IcebergProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.InputModelProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.IsolatedLoadingProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.JournalProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.LanguageProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.LikeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LocationProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.LockProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.LockingProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.LogProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.MaterializedProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.MergeBlockRatioProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.OnProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.OnCommitProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.Order'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.OutputModelProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.PartitionedByProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.PartitionedOfProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.PrimaryKey'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.Property'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.ReturnsProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.RowFormatProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.RowFormatDelimitedProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.RowFormatSerdeProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.SampleProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.SchemaCommentProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.SerdeProperties'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.Set'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.SettingsProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.SetProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.SetConfigProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.SharingProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.SequenceProperties'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.SortKeyProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.SqlReadWriteProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.SqlSecurityProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.StabilityProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.StrictProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.TemporaryProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.ToTableProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.TransientProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.TransformModelProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.MergeTreeTTL'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.UnloggedProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.VolatileProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.WithDataProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.WithSystemVersioningProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>}"}, "sqlglot.dialects.sqlite.SQLite.Generator.LIMIT_FETCH": {"fullname": "sqlglot.dialects.sqlite.SQLite.Generator.LIMIT_FETCH", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Generator.LIMIT_FETCH", "kind": "variable", "doc": "<p></p>\n", "default_value": "'LIMIT'"}, "sqlglot.dialects.sqlite.SQLite.Generator.cast_sql": {"fullname": "sqlglot.dialects.sqlite.SQLite.Generator.cast_sql", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Generator.cast_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Cast</span>,</span><span class=\"param\">\t<span class=\"n\">safe_prefix</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.sqlite.SQLite.Generator.generateseries_sql": {"fullname": "sqlglot.dialects.sqlite.SQLite.Generator.generateseries_sql", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Generator.generateseries_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">GenerateSeries</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.sqlite.SQLite.Generator.datediff_sql": {"fullname": "sqlglot.dialects.sqlite.SQLite.Generator.datediff_sql", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Generator.datediff_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DateDiff</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.sqlite.SQLite.Generator.groupconcat_sql": {"fullname": "sqlglot.dialects.sqlite.SQLite.Generator.groupconcat_sql", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Generator.groupconcat_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">GroupConcat</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.sqlite.SQLite.Generator.least_sql": {"fullname": "sqlglot.dialects.sqlite.SQLite.Generator.least_sql", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Generator.least_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Least</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.sqlite.SQLite.Generator.transaction_sql": {"fullname": "sqlglot.dialects.sqlite.SQLite.Generator.transaction_sql", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Generator.transaction_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Transaction</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.sqlite.SQLite.Generator.SELECT_KINDS": {"fullname": "sqlglot.dialects.sqlite.SQLite.Generator.SELECT_KINDS", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Generator.SELECT_KINDS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Tuple[str, ...]", "default_value": "()"}, "sqlglot.dialects.sqlite.SQLite.Generator.TRY_SUPPORTED": {"fullname": "sqlglot.dialects.sqlite.SQLite.Generator.TRY_SUPPORTED", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Generator.TRY_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.sqlite.SQLite.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS": {"fullname": "sqlglot.dialects.sqlite.SQLite.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'qualify': <function Generator.<lambda>>, 'windows': <function Generator.<lambda>>}"}, "sqlglot.dialects.sqlite.SQLite.tokenizer_class": {"fullname": "sqlglot.dialects.sqlite.SQLite.tokenizer_class", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.tokenizer_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.sqlite.SQLite.Tokenizer'>"}, "sqlglot.dialects.sqlite.SQLite.parser_class": {"fullname": "sqlglot.dialects.sqlite.SQLite.parser_class", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.parser_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.sqlite.SQLite.Parser'>"}, "sqlglot.dialects.sqlite.SQLite.generator_class": {"fullname": "sqlglot.dialects.sqlite.SQLite.generator_class", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.generator_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.sqlite.SQLite.Generator'>"}, "sqlglot.dialects.sqlite.SQLite.TIME_TRIE": {"fullname": "sqlglot.dialects.sqlite.SQLite.TIME_TRIE", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.sqlite.SQLite.FORMAT_TRIE": {"fullname": "sqlglot.dialects.sqlite.SQLite.FORMAT_TRIE", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.FORMAT_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.sqlite.SQLite.INVERSE_TIME_MAPPING": {"fullname": "sqlglot.dialects.sqlite.SQLite.INVERSE_TIME_MAPPING", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.INVERSE_TIME_MAPPING", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{}"}, "sqlglot.dialects.sqlite.SQLite.INVERSE_TIME_TRIE": {"fullname": "sqlglot.dialects.sqlite.SQLite.INVERSE_TIME_TRIE", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.INVERSE_TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.sqlite.SQLite.ESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.sqlite.SQLite.ESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.ESCAPED_SEQUENCES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{}"}, "sqlglot.dialects.sqlite.SQLite.QUOTE_START": {"fullname": "sqlglot.dialects.sqlite.SQLite.QUOTE_START", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.QUOTE_START", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.sqlite.SQLite.QUOTE_END": {"fullname": "sqlglot.dialects.sqlite.SQLite.QUOTE_END", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.QUOTE_END", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.sqlite.SQLite.IDENTIFIER_START": {"fullname": "sqlglot.dialects.sqlite.SQLite.IDENTIFIER_START", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.IDENTIFIER_START", "kind": "variable", "doc": "<p></p>\n", "default_value": "'"'"}, "sqlglot.dialects.sqlite.SQLite.IDENTIFIER_END": {"fullname": "sqlglot.dialects.sqlite.SQLite.IDENTIFIER_END", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.IDENTIFIER_END", "kind": "variable", "doc": "<p></p>\n", "default_value": "'"'"}, "sqlglot.dialects.sqlite.SQLite.BIT_START": {"fullname": "sqlglot.dialects.sqlite.SQLite.BIT_START", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.BIT_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.sqlite.SQLite.BIT_END": {"fullname": "sqlglot.dialects.sqlite.SQLite.BIT_END", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.BIT_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.sqlite.SQLite.HEX_START": {"fullname": "sqlglot.dialects.sqlite.SQLite.HEX_START", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.HEX_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""x'""}, "sqlglot.dialects.sqlite.SQLite.HEX_END": {"fullname": "sqlglot.dialects.sqlite.SQLite.HEX_END", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.HEX_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""'""}, "sqlglot.dialects.sqlite.SQLite.BYTE_START": {"fullname": "sqlglot.dialects.sqlite.SQLite.BYTE_START", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.BYTE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.sqlite.SQLite.BYTE_END": {"fullname": "sqlglot.dialects.sqlite.SQLite.BYTE_END", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.BYTE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.sqlite.SQLite.UNICODE_START": {"fullname": "sqlglot.dialects.sqlite.SQLite.UNICODE_START", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.UNICODE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.sqlite.SQLite.UNICODE_END": {"fullname": "sqlglot.dialects.sqlite.SQLite.UNICODE_END", "modulename": "sqlglot.dialects.sqlite", "qualname": "SQLite.UNICODE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.starrocks": {"fullname": "sqlglot.dialects.starrocks", "modulename": "sqlglot.dialects.starrocks", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.dialects.starrocks.StarRocks": {"fullname": "sqlglot.dialects.starrocks.StarRocks", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.mysql.MySQL"}, "sqlglot.dialects.starrocks.StarRocks.Parser": {"fullname": "sqlglot.dialects.starrocks.StarRocks.Parser", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.Parser", "kind": "class", "doc": "<p>Parser consumes a list of tokens produced by the Tokenizer and produces a parsed syntax tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>error_level:</strong> The desired error level.\nDefault: ErrorLevel.IMMEDIATE</li>\n<li><strong>error_message_context:</strong> The amount of context to capture from a query string when displaying\nthe error message (in number of characters).\nDefault: 100</li>\n<li><strong>max_errors:</strong> Maximum number of error messages to include in a raised ParseError.\nThis is only relevant if error_level is ErrorLevel.RAISE.\nDefault: 3</li>\n</ul>\n", "bases": "sqlglot.dialects.mysql.MySQL.Parser"}, "sqlglot.dialects.starrocks.StarRocks.Parser.FUNCTIONS": {"fullname": "sqlglot.dialects.starrocks.StarRocks.Parser.FUNCTIONS", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.Parser.FUNCTIONS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ABS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Abs'>>, 'ADD_MONTHS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AddMonths'>>, 'ANONYMOUS_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnonymousAggFunc'>>, 'ANY_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnyValue'>>, 'APPROX_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_COUNT_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'APPROX_TOP_K': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxTopK'>>, 'ARG_MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARGMAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'MAX_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARG_MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARGMIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'MIN_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Array'>>, 'ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAgg'>>, 'ARRAY_ALL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAll'>>, 'ARRAY_ANY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAny'>>, 'ARRAY_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CONSTRUCT_COMPACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConstructCompact'>>, 'ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayContains'>>, 'FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_OVERLAPS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayOverlaps'>>, 'ARRAY_SIZE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_SORT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySort'>>, 'ARRAY_SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySum'>>, 'ARRAY_TO_STRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_JOIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_UNION_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUnionAgg'>>, 'ARRAY_UNIQUE_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUniqueAgg'>>, 'AVG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Avg'>>, 'CASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Case'>>, 'CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cast'>>, 'CAST_TO_STR_TYPE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CastToStrType'>>, 'CBRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cbrt'>>, 'CEIL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CEILING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CHR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'COALESCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'IFNULL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'NVL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'COLLATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Collate'>>, 'COMBINED_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedAggFunc'>>, 'COMBINED_PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedParameterizedAgg'>>, 'CONCAT': <function Parser.<lambda>>, 'CONCAT_WS': <function Parser.<lambda>>, 'CONNECT_BY_ROOT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ConnectByRoot'>>, 'CONVERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Convert'>>, 'CORR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Corr'>>, 'COUNT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Count'>>, 'COUNT_IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COUNTIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COVAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarPop'>>, 'COVAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarSamp'>>, 'CURRENT_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDate'>>, 'CURRENT_DATETIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDatetime'>>, 'CURRENT_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTime'>>, 'CURRENT_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTimestamp'>>, 'CURRENT_USER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentUser'>>, 'DATE': <function MySQL.Parser.<lambda>>, 'DATE_ADD': <function build_date_delta_with_interval.<locals>._builder>, 'DATEDIFF': <function StarRocks.Parser.<lambda>>, 'DATE_DIFF': <function StarRocks.Parser.<lambda>>, 'DATE_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATE_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateStrToDate'>>, 'DATE_SUB': <function build_date_delta_with_interval.<locals>._builder>, 'DATE_TO_DATE_STR': <function Parser.<lambda>>, 'DATE_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateToDi'>>, 'DATE_TRUNC': <function build_timestamp_trunc>, 'DATETIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeAdd'>>, 'DATETIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeDiff'>>, 'DATETIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeSub'>>, 'DATETIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeTrunc'>>, 'DAY': <function MySQL.Parser.<lambda>>, 'DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAYOFMONTH': <function MySQL.Parser.<lambda>>, 'DAY_OF_WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAYOFWEEK': <function MySQL.Parser.<lambda>>, 'DAY_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DAYOFYEAR': <function MySQL.Parser.<lambda>>, 'DECODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Decode'>>, 'DI_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DiToDate'>>, 'ENCODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Encode'>>, 'EXP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Exp'>>, 'EXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Explode'>>, 'EXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ExplodeOuter'>>, 'EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Extract'>>, 'FIRST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.First'>>, 'FIRST_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FirstValue'>>, 'FLATTEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Flatten'>>, 'FLOOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Floor'>>, 'FROM_BASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase'>>, 'FROM_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase64'>>, 'GENERATE_DATE_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GenerateDateArray'>>, 'GENERATE_SERIES': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GenerateSeries'>>, 'GREATEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Greatest'>>, 'GROUP_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GroupConcat'>>, 'HEX': <function build_hex>, 'HLL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Hll'>>, 'IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'IIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'INITCAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Initcap'>>, 'IS_INF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'ISINF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'IS_NAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'ISNAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'J_S_O_N_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArray'>>, 'J_S_O_N_ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArrayAgg'>>, 'JSON_ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArrayContains'>>, 'JSONB_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONBExtract'>>, 'JSONB_EXTRACT_SCALAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONBExtractScalar'>>, 'JSON_EXTRACT': <function build_extract_json_with_path.<locals>._builder>, 'JSON_EXTRACT_SCALAR': <function build_extract_json_with_path.<locals>._builder>, 'JSON_FORMAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONFormat'>>, 'J_S_O_N_OBJECT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONObject'>>, 'J_S_O_N_OBJECT_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONObjectAgg'>>, 'J_S_O_N_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONTable'>>, 'LAG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lag'>>, 'LAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Last'>>, 'LAST_DAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastDay'>>, 'LAST_DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastDay'>>, 'LAST_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastValue'>>, 'LEAD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lead'>>, 'LEAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Least'>>, 'LEFT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Left'>>, 'LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Length'>>, 'LEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Length'>>, 'LEVENSHTEIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Levenshtein'>>, 'LN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ln'>>, 'LOG': <function build_logarithm>, 'LOGICAL_AND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'BOOL_AND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'BOOLAND_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'LOGICAL_OR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'BOOL_OR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'BOOLOR_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'LOWER': <function build_lower>, 'LCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lower'>>, 'LOWER_HEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LowerHex'>>, 'MD5': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MD5'>>, 'MD5_DIGEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MD5Digest'>>, 'MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Map'>>, 'MAP_FROM_ENTRIES': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MapFromEntries'>>, 'MATCH_AGAINST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MatchAgainst'>>, 'MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Max'>>, 'MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Min'>>, 'MONTH': <function MySQL.Parser.<lambda>>, 'MONTHS_BETWEEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MonthsBetween'>>, 'NEXT_VALUE_FOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NextValueFor'>>, 'NTH_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NthValue'>>, 'NULLIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Nullif'>>, 'NUMBER_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NumberToStr'>>, 'NVL2': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Nvl2'>>, 'OPEN_J_S_O_N': <bound method Func.from_arg_list of <class 'sqlglot.expressions.OpenJSON'>>, 'PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParameterizedAgg'>>, 'PARSE_JSON': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParseJSON'>>, 'JSON_PARSE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParseJSON'>>, 'PERCENTILE_CONT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PercentileCont'>>, 'PERCENTILE_DISC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PercentileDisc'>>, 'POSEXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Posexplode'>>, 'POSEXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PosexplodeOuter'>>, 'POWER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Pow'>>, 'POW': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Pow'>>, 'PREDICT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Predict'>>, 'QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quantile'>>, 'QUARTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quarter'>>, 'RAND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'RANDOM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'RANDN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Randn'>>, 'RANGE_N': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RangeN'>>, 'READ_CSV': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ReadCSV'>>, 'REDUCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Reduce'>>, 'REGEXP_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpExtract'>>, 'REGEXP_I_LIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpILike'>>, 'REGEXP_LIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpLike'>>, 'REGEXP_REPLACE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpReplace'>>, 'REGEXP_SPLIT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpSplit'>>, 'REPEAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Repeat'>>, 'RIGHT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Right'>>, 'ROUND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Round'>>, 'ROW_NUMBER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RowNumber'>>, 'SHA': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA'>>, 'SHA1': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA'>>, 'SHA2': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA2'>>, 'SAFE_DIVIDE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SafeDivide'>>, 'SIGN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sign'>>, 'SIGNUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sign'>>, 'SORT_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SortArray'>>, 'SPLIT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Split'>>, 'SQRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sqrt'>>, 'STANDARD_HASH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StandardHash'>>, 'STAR_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StarMap'>>, 'STARTS_WITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STARTSWITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STDDEV': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stddev'>>, 'STDDEV_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StddevPop'>>, 'STDDEV_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StddevSamp'>>, 'STR_POSITION': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrPosition'>>, 'STR_TO_DATE': <function _str_to_date>, 'STR_TO_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToMap'>>, 'STR_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToTime'>>, 'STR_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToUnix'>>, 'STRUCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Struct'>>, 'STRUCT_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StructExtract'>>, 'STUFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stuff'>>, 'INSERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stuff'>>, 'SUBSTRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Substring'>>, 'SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sum'>>, 'TIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeAdd'>>, 'TIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeDiff'>>, 'TIME_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'TIMEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'TIME_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToDate'>>, 'TIME_STR_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToTime'>>, 'TIME_STR_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToUnix'>>, 'TIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeSub'>>, 'TIME_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeToStr'>>, 'TIME_TO_TIME_STR': <function Parser.<lambda>>, 'TIME_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeToUnix'>>, 'TIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeTrunc'>>, 'TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Timestamp'>>, 'TIMESTAMP_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampAdd'>>, 'TIMESTAMPDIFF': <function build_date_delta.<locals>._builder>, 'TIMESTAMP_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampDiff'>>, 'TIMESTAMP_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampFromParts'>>, 'TIMESTAMPFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampFromParts'>>, 'TIMESTAMP_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampSub'>>, 'TIMESTAMP_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampTrunc'>>, 'TO_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToArray'>>, 'TO_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToBase64'>>, 'TO_CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToChar'>>, 'TO_DAYS': <function MySQL.Parser.<lambda>>, 'TO_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToMap'>>, 'TO_NUMBER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToNumber'>>, 'TRANSFORM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Transform'>>, 'TRIM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Trim'>>, 'TRY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Try'>>, 'TRY_CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TryCast'>>, 'TS_OR_DI_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDiToDi'>>, 'TS_OR_DS_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsAdd'>>, 'TS_OR_DS_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsDiff'>>, 'TS_OR_DS_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToDate'>>, 'TS_OR_DS_TO_DATE_STR': <function Parser.<lambda>>, 'TS_OR_DS_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTime'>>, 'TS_OR_DS_TO_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTimestamp'>>, 'UNHEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Unhex'>>, 'UNIX_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixDate'>>, 'UNIX_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToStr'>>, 'UNIX_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTime'>>, 'UNIX_TO_TIME_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTimeStr'>>, 'UPPER': <function build_upper>, 'UCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Upper'>>, 'VAR_MAP': <function build_var_map>, 'VARIANCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'VAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'WEEK': <function MySQL.Parser.<lambda>>, 'WEEK_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.WeekOfYear'>>, 'WEEKOFYEAR': <function MySQL.Parser.<lambda>>, 'WHEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.When'>>, 'X_M_L_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.XMLTable'>>, 'XOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Xor'>>, 'YEAR': <function MySQL.Parser.<lambda>>, 'GLOB': <function Parser.<lambda>>, 'JSON_EXTRACT_PATH_TEXT': <function build_extract_json_with_path.<locals>._builder>, 'LIKE': <function build_like>, 'LOG2': <function Parser.<lambda>>, 'LOG10': <function Parser.<lambda>>, 'MOD': <function build_mod>, 'TO_HEX': <function build_hex>, 'DATE_FORMAT': <function build_formatted_time.<locals>._builder>, 'INSTR': <function MySQL.Parser.<lambda>>, 'FROM_UNIXTIME': <function build_formatted_time.<locals>._builder>, 'ISNULL': <function isnull_to_is_null>, 'LOCATE': <function locate_to_strposition>, 'MAKETIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'MONTHNAME': <function MySQL.Parser.<lambda>>, 'REGEXP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpLike'>>}"}, "sqlglot.dialects.starrocks.StarRocks.Parser.TABLE_ALIAS_TOKENS": {"fullname": "sqlglot.dialects.starrocks.StarRocks.Parser.TABLE_ALIAS_TOKENS", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.Parser.TABLE_ALIAS_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.KILL: 'KILL'>, <TokenType.MONEY: 'MONEY'>, <TokenType.COPY: 'COPY'>, <TokenType.PERCENT: 'PERCENT'>, <TokenType.TAG: 'TAG'>, <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, <TokenType.VOLATILE: 'VOLATILE'>, <TokenType.IDENTIFIER: 'IDENTIFIER'>, <TokenType.VARBINARY: 'VARBINARY'>, <TokenType.HSTORE: 'HSTORE'>, <TokenType.ASC: 'ASC'>, <TokenType.IPADDRESS: 'IPADDRESS'>, <TokenType.ISNULL: 'ISNULL'>, <TokenType.TEMPORARY: 'TEMPORARY'>, <TokenType.PROCEDURE: 'PROCEDURE'>, <TokenType.SCHEMA: 'SCHEMA'>, <TokenType.NUMRANGE: 'NUMRANGE'>, <TokenType.DATE32: 'DATE32'>, <TokenType.INT8RANGE: 'INT8RANGE'>, <TokenType.ANTI: 'ANTI'>, <TokenType.AGGREGATEFUNCTION: 'AGGREGATEFUNCTION'>, <TokenType.VIEW: 'VIEW'>, <TokenType.VARCHAR: 'VARCHAR'>, <TokenType.TIMETZ: 'TIMETZ'>, <TokenType.GEOMETRY: 'GEOMETRY'>, <TokenType.BEGIN: 'BEGIN'>, <TokenType.ENUM8: 'ENUM8'>, <TokenType.INDEX: 'INDEX'>, <TokenType.PARTITION: 'PARTITION'>, <TokenType.UINT256: 'UINT256'>, <TokenType.BIGINT: 'BIGINT'>, <TokenType.CACHE: 'CACHE'>, <TokenType.OPERATOR: 'OPERATOR'>, <TokenType.COLUMN: 'COLUMN'>, <TokenType.INT128: 'INT128'>, <TokenType.SMALLMONEY: 'SMALLMONEY'>, <TokenType.HLLSKETCH: 'HLLSKETCH'>, <TokenType.UNPIVOT: 'UNPIVOT'>, <TokenType.SMALLINT: 'SMALLINT'>, <TokenType.INT256: 'INT256'>, <TokenType.FLOAT: 'FLOAT'>, <TokenType.COMMIT: 'COMMIT'>, <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, <TokenType.EXISTS: 'EXISTS'>, <TokenType.NULL: 'NULL'>, <TokenType.RECURSIVE: 'RECURSIVE'>, <TokenType.SET: 'SET'>, <TokenType.NULLABLE: 'NULLABLE'>, <TokenType.REFRESH: 'REFRESH'>, <TokenType.TINYTEXT: 'TINYTEXT'>, <TokenType.SHOW: 'SHOW'>, <TokenType.DEFAULT: 'DEFAULT'>, <TokenType.DATE: 'DATE'>, <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <TokenType.MERGE: 'MERGE'>, <TokenType.FIRST: 'FIRST'>, <TokenType.BINARY: 'BINARY'>, <TokenType.ARRAY: 'ARRAY'>, <TokenType.SERIAL: 'SERIAL'>, <TokenType.EXECUTE: 'EXECUTE'>, <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, <TokenType.INTERVAL: 'INTERVAL'>, <TokenType.PRAGMA: 'PRAGMA'>, <TokenType.STORAGE_INTEGRATION: 'STORAGE_INTEGRATION'>, <TokenType.BPCHAR: 'BPCHAR'>, <TokenType.BIT: 'BIT'>, <TokenType.UINT: 'UINT'>, <TokenType.UUID: 'UUID'>, <TokenType.STRUCT: 'STRUCT'>, <TokenType.FALSE: 'FALSE'>, <TokenType.FUNCTION: 'FUNCTION'>, <TokenType.TOP: 'TOP'>, <TokenType.SUPER: 'SUPER'>, <TokenType.CASE: 'CASE'>, <TokenType.IMAGE: 'IMAGE'>, <TokenType.UBIGINT: 'UBIGINT'>, <TokenType.LONGBLOB: 'LONGBLOB'>, <TokenType.ROLLUP: 'ROLLUP'>, <TokenType.VAR: 'VAR'>, <TokenType.COMMAND: 'COMMAND'>, <TokenType.LOAD: 'LOAD'>, <TokenType.TRUNCATE: 'TRUNCATE'>, <TokenType.KEEP: 'KEEP'>, <TokenType.UMEDIUMINT: 'UMEDIUMINT'>, <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, <TokenType.UINT128: 'UINT128'>, <TokenType.END: 'END'>, <TokenType.MAP: 'MAP'>, <TokenType.IPV4: 'IPV4'>, <TokenType.USERDEFINED: 'USERDEFINED'>, <TokenType.REFERENCES: 'REFERENCES'>, <TokenType.REPLACE: 'REPLACE'>, <TokenType.RANGE: 'RANGE'>, <TokenType.NVARCHAR: 'NVARCHAR'>, <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, <TokenType.TRUE: 'TRUE'>, <TokenType.TIMESTAMP_MS: 'TIMESTAMP_MS'>, <TokenType.VARIANT: 'VARIANT'>, <TokenType.ENUM: 'ENUM'>, <TokenType.USMALLINT: 'USMALLINT'>, <TokenType.OVERLAPS: 'OVERLAPS'>, <TokenType.TIMESTAMP_S: 'TIMESTAMP_S'>, <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, <TokenType.UNIQUE: 'UNIQUE'>, <TokenType.ORDINALITY: 'ORDINALITY'>, <TokenType.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>, <TokenType.TEXT: 'TEXT'>, <TokenType.DATABASE: 'DATABASE'>, <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, <TokenType.PSEUDO_TYPE: 'PSEUDO_TYPE'>, <TokenType.FIXEDSTRING: 'FIXEDSTRING'>, <TokenType.NEXT: 'NEXT'>, <TokenType.INT: 'INT'>, <TokenType.BIGSERIAL: 'BIGSERIAL'>, <TokenType.BOOLEAN: 'BOOLEAN'>, <TokenType.IS: 'IS'>, <TokenType.CONSTRAINT: 'CONSTRAINT'>, <TokenType.FINAL: 'FINAL'>, <TokenType.UNKNOWN: 'UNKNOWN'>, <TokenType.SETTINGS: 'SETTINGS'>, <TokenType.ROWS: 'ROWS'>, <TokenType.TSTZRANGE: 'TSTZRANGE'>, <TokenType.DATETIME64: 'DATETIME64'>, <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, <TokenType.DATETIME: 'DATETIME'>, <TokenType.MEDIUMINT: 'MEDIUMINT'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>, <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, <TokenType.XML: 'XML'>, <TokenType.JSON: 'JSON'>, <TokenType.UTINYINT: 'UTINYINT'>, <TokenType.DELETE: 'DELETE'>, <TokenType.TIME: 'TIME'>, <TokenType.UDECIMAL: 'UDECIMAL'>, <TokenType.NESTED: 'NESTED'>, <TokenType.SEMI: 'SEMI'>, <TokenType.DESC: 'DESC'>, <TokenType.ROWVERSION: 'ROWVERSION'>, <TokenType.TIMESTAMP_NS: 'TIMESTAMP_NS'>, <TokenType.ANY: 'ANY'>, <TokenType.DIV: 'DIV'>, <TokenType.DICTIONARY: 'DICTIONARY'>, <TokenType.INET: 'INET'>, <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, <TokenType.COMMENT: 'COMMENT'>, <TokenType.CURRENT_USER: 'CURRENT_USER'>, <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>, <TokenType.ALL: 'ALL'>, <TokenType.NAME: 'NAME'>, <TokenType.SOME: 'SOME'>, <TokenType.ENUM16: 'ENUM16'>, <TokenType.YEAR: 'YEAR'>, <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, <TokenType.DOUBLE: 'DOUBLE'>, <TokenType.INT4RANGE: 'INT4RANGE'>, <TokenType.FORMAT: 'FORMAT'>, <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, <TokenType.IPPREFIX: 'IPPREFIX'>, <TokenType.OVERWRITE: 'OVERWRITE'>, <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>, <TokenType.COLLATE: 'COLLATE'>, <TokenType.FILTER: 'FILTER'>, <TokenType.JSONB: 'JSONB'>, <TokenType.TDIGEST: 'TDIGEST'>, <TokenType.CHAR: 'CHAR'>, <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.ROW: 'ROW'>, <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.TABLE: 'TABLE'>, <TokenType.DATERANGE: 'DATERANGE'>, <TokenType.TSRANGE: 'TSRANGE'>, <TokenType.ESCAPE: 'ESCAPE'>, <TokenType.PIVOT: 'PIVOT'>, <TokenType.DECIMAL: 'DECIMAL'>, <TokenType.NCHAR: 'NCHAR'>, <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, <TokenType.UPDATE: 'UPDATE'>, <TokenType.MODEL: 'MODEL'>, <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, <TokenType.SEQUENCE: 'SEQUENCE'>, <TokenType.LONGTEXT: 'LONGTEXT'>, <TokenType.DESCRIBE: 'DESCRIBE'>, <TokenType.IPV6: 'IPV6'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, <TokenType.TINYINT: 'TINYINT'>, <TokenType.TINYBLOB: 'TINYBLOB'>}"}, "sqlglot.dialects.starrocks.StarRocks.Parser.SHOW_TRIE": {"fullname": "sqlglot.dialects.starrocks.StarRocks.Parser.SHOW_TRIE", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.Parser.SHOW_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'BINARY': {'LOGS': {0: True}}, 'MASTER': {'LOGS': {0: True}, 'STATUS': {0: True}}, 'BINLOG': {'EVENTS': {0: True}}, 'CHARACTER': {'SET': {0: True}}, 'CHARSET': {0: True}, 'COLLATION': {0: True}, 'FULL': {'COLUMNS': {0: True}, 'PROCESSLIST': {0: True}, 'TABLES': {0: True}}, 'COLUMNS': {0: True}, 'CREATE': {'DATABASE': {0: True}, 'EVENT': {0: True}, 'FUNCTION': {0: True}, 'PROCEDURE': {0: True}, 'TABLE': {0: True}, 'TRIGGER': {0: True}, 'VIEW': {0: True}}, 'DATABASES': {0: True}, 'SCHEMAS': {0: True}, 'ENGINE': {0: True}, 'STORAGE': {'ENGINES': {0: True}}, 'ENGINES': {0: True}, 'ERRORS': {0: True}, 'EVENTS': {0: True}, 'FUNCTION': {'CODE': {0: True}, 'STATUS': {0: True}}, 'GRANTS': {0: True}, 'INDEX': {0: True}, 'OPEN': {'TABLES': {0: True}}, 'PLUGINS': {0: True}, 'PROCEDURE': {'CODE': {0: True}, 'STATUS': {0: True}}, 'PRIVILEGES': {0: True}, 'PROCESSLIST': {0: True}, 'PROFILE': {0: True}, 'PROFILES': {0: True}, 'RELAYLOG': {'EVENTS': {0: True}}, 'REPLICAS': {0: True}, 'SLAVE': {'HOSTS': {0: True}, 'STATUS': {0: True}}, 'REPLICA': {'STATUS': {0: True}}, 'GLOBAL': {'STATUS': {0: True}, 'VARIABLES': {0: True}}, 'SESSION': {'STATUS': {0: True}, 'VARIABLES': {0: True}}, 'STATUS': {0: True}, 'TABLE': {'STATUS': {0: True}}, 'TABLES': {0: True}, 'TRIGGERS': {0: True}, 'VARIABLES': {0: True}, 'WARNINGS': {0: True}}"}, "sqlglot.dialects.starrocks.StarRocks.Parser.SET_TRIE": {"fullname": "sqlglot.dialects.starrocks.StarRocks.Parser.SET_TRIE", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.Parser.SET_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'GLOBAL': {0: True}, 'LOCAL': {0: True}, 'SESSION': {0: True}, 'TRANSACTION': {0: True}, 'PERSIST': {0: True}, 'PERSIST_ONLY': {0: True}, 'CHARACTER': {'SET': {0: True}}, 'CHARSET': {0: True}, 'NAMES': {0: True}}"}, "sqlglot.dialects.starrocks.StarRocks.Generator": {"fullname": "sqlglot.dialects.starrocks.StarRocks.Generator", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.Generator", "kind": "class", "doc": "<p>Generator converts a given syntax tree to the corresponding SQL string.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>pretty:</strong> Whether to format the produced SQL string.\nDefault: False.</li>\n<li><strong>identify:</strong> Determines when an identifier should be quoted. Possible values are:\nFalse (default): Never quote, except in cases where it's mandatory by the dialect.\nTrue or 'always': Always quote.\n'safe': Only quote identifiers that are case insensitive.</li>\n<li><strong>normalize:</strong> Whether to normalize identifiers to lowercase.\nDefault: False.</li>\n<li><strong>pad:</strong> The pad size in a formatted string. For example, this affects the indentation of\na projection in a query, relative to its nesting level.\nDefault: 2.</li>\n<li><strong>indent:</strong> The indentation size in a formatted string. For example, this affects the\nindentation of subqueries and filters under a <code>WHERE</code> clause.\nDefault: 2.</li>\n<li><strong>normalize_functions:</strong> How to normalize function names. Possible values are:\n\"upper\" or True (default): Convert names to uppercase.\n\"lower\": Convert names to lowercase.\nFalse: Disables function name normalization.</li>\n<li><strong>unsupported_level:</strong> Determines the generator's behavior when it encounters unsupported expressions.\nDefault ErrorLevel.WARN.</li>\n<li><strong>max_unsupported:</strong> Maximum number of unsupported messages to include in a raised UnsupportedError.\nThis is only relevant if unsupported_level is ErrorLevel.RAISE.\nDefault: 3</li>\n<li><strong>leading_comma:</strong> Whether the comma is leading or trailing in select expressions.\nThis is only relevant when generating in pretty mode.\nDefault: False</li>\n<li><strong>max_text_width:</strong> The max number of characters in a segment before creating new lines in pretty mode.\nThe default is on the smaller end because the length only represents a segment and not the true\nline length.\nDefault: 80</li>\n<li><strong>comments:</strong> Whether to preserve comments in the output SQL code.\nDefault: True</li>\n</ul>\n", "bases": "sqlglot.dialects.mysql.MySQL.Generator"}, "sqlglot.dialects.starrocks.StarRocks.Generator.CAST_MAPPING": {"fullname": "sqlglot.dialects.starrocks.StarRocks.Generator.CAST_MAPPING", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.Generator.CAST_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{}"}, "sqlglot.dialects.starrocks.StarRocks.Generator.TYPE_MAPPING": {"fullname": "sqlglot.dialects.starrocks.StarRocks.Generator.TYPE_MAPPING", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.Generator.TYPE_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.NCHAR: 'NCHAR'>: 'CHAR', <Type.NVARCHAR: 'NVARCHAR'>: 'VARCHAR', <Type.INET: 'INET'>: 'INET', <Type.ROWVERSION: 'ROWVERSION'>: 'VARBINARY', <Type.UBIGINT: 'UBIGINT'>: 'BIGINT', <Type.UINT: 'UINT'>: 'INT', <Type.UMEDIUMINT: 'UMEDIUMINT'>: 'MEDIUMINT', <Type.USMALLINT: 'USMALLINT'>: 'SMALLINT', <Type.UTINYINT: 'UTINYINT'>: 'TINYINT', <Type.UDECIMAL: 'UDECIMAL'>: 'DECIMAL', <Type.TIMESTAMP: 'TIMESTAMP'>: 'DATETIME', <Type.TIMESTAMPTZ: 'TIMESTAMPTZ'>: 'DATETIME', <Type.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>: 'TIMESTAMP', <Type.TEXT: 'TEXT'>: 'STRING'}"}, "sqlglot.dialects.starrocks.StarRocks.Generator.TRANSFORMS": {"fullname": "sqlglot.dialects.starrocks.StarRocks.Generator.TRANSFORMS", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.Generator.TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.JSONPathFilter'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathKey'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRecursive'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRoot'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathScript'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSelector'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSlice'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSubscript'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathUnion'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathWildcard'>: <function <lambda>>, <class 'sqlglot.expressions.AllowedValuesProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.BackupProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CaseSpecificColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CollateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CommentColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DateFormatColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DefaultColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EncodeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EphemeralColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExcludeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExternalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.GlobalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.HeapProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IcebergProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InheritsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InlineLengthColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IntervalSpan'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtract'>: <function arrow_json_extract_sql>, <class 'sqlglot.expressions.JSONExtractScalar'>: <function arrow_json_extract_sql>, <class 'sqlglot.expressions.LanguageProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LocationProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LogProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.MaterializedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NonClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NotForReplicationColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnCommitProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnUpdateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OutputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.PathColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ReturnsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SampleProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetConfigProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SettingsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SharingProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlReadWriteProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlSecurityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StabilityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StrictProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TemporaryProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TitleColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.Timestamp'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransformModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransientProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UppercaseColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UnloggedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VarMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VolatileProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithOperator'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ArrayAgg'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.CurrentDate'>: <function no_paren_current_date_sql>, <class 'sqlglot.expressions.DateDiff'>: <function StarRocks.Generator.<lambda>>, <class 'sqlglot.expressions.DateAdd'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.DateStrToDate'>: <function datestrtodate_sql>, <class 'sqlglot.expressions.DateSub'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.Day'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.DayOfMonth'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.DayOfWeek'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.DayOfYear'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.GroupConcat'>: <function MySQL.Generator.<lambda>>, <class 'sqlglot.expressions.ILike'>: <function no_ilike_sql>, <class 'sqlglot.expressions.Max'>: <function max_or_greatest>, <class 'sqlglot.expressions.Min'>: <function min_or_least>, <class 'sqlglot.expressions.Month'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.NullSafeEQ'>: <function MySQL.Generator.<lambda>>, <class 'sqlglot.expressions.NullSafeNEQ'>: <function MySQL.Generator.<lambda>>, <class 'sqlglot.expressions.ParseJSON'>: <function MySQL.Generator.<lambda>>, <class 'sqlglot.expressions.Pivot'>: <function no_pivot_sql>, <class 'sqlglot.expressions.Select'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.StrPosition'>: <function strposition_to_locate_sql>, <class 'sqlglot.expressions.StrToDate'>: <function _str_to_date_sql>, <class 'sqlglot.expressions.StrToTime'>: <function _str_to_date_sql>, <class 'sqlglot.expressions.Stuff'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.TableSample'>: <function no_tablesample_sql>, <class 'sqlglot.expressions.TimeFromParts'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.TimestampAdd'>: <function date_add_interval_sql.<locals>.func>, <class 'sqlglot.expressions.TimestampDiff'>: <function MySQL.Generator.<lambda>>, <class 'sqlglot.expressions.TimestampSub'>: <function date_add_interval_sql.<locals>.func>, <class 'sqlglot.expressions.TimeStrToUnix'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.TimeStrToTime'>: <function MySQL.Generator.<lambda>>, <class 'sqlglot.expressions.TimeToStr'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.Trim'>: <function _trim_sql>, <class 'sqlglot.expressions.TryCast'>: <function no_trycast_sql>, <class 'sqlglot.expressions.TsOrDsAdd'>: <function date_add_sql.<locals>.func>, <class 'sqlglot.expressions.TsOrDsDiff'>: <function MySQL.Generator.<lambda>>, <class 'sqlglot.expressions.TsOrDsToDate'>: <function _ts_or_ds_to_date_sql>, <class 'sqlglot.expressions.UnixToTime'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.Week'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.WeekOfYear'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.Year'>: <function _remove_ts_or_ds_to_date.<locals>.func>, <class 'sqlglot.expressions.ApproxDistinct'>: <function approx_count_distinct_sql>, <class 'sqlglot.expressions.RegexpLike'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.StrToUnix'>: <function StarRocks.Generator.<lambda>>, <class 'sqlglot.expressions.TimestampTrunc'>: <function StarRocks.Generator.<lambda>>, <class 'sqlglot.expressions.TimeStrToDate'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.UnixToStr'>: <function StarRocks.Generator.<lambda>>}"}, "sqlglot.dialects.starrocks.StarRocks.Generator.SELECT_KINDS": {"fullname": "sqlglot.dialects.starrocks.StarRocks.Generator.SELECT_KINDS", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.Generator.SELECT_KINDS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Tuple[str, ...]", "default_value": "()"}, "sqlglot.dialects.starrocks.StarRocks.Generator.TRY_SUPPORTED": {"fullname": "sqlglot.dialects.starrocks.StarRocks.Generator.TRY_SUPPORTED", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.Generator.TRY_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.starrocks.StarRocks.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS": {"fullname": "sqlglot.dialects.starrocks.StarRocks.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'qualify': <function Generator.<lambda>>, 'windows': <function Generator.<lambda>>}"}, "sqlglot.dialects.starrocks.StarRocks.UNESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.starrocks.StarRocks.UNESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.UNESCAPED_SEQUENCES", "kind": "variable", "doc": "<p>Mapping of an escaped sequence (<code>\\n</code>) to its unescaped version (<code>\n</code>).</p>\n", "annotation": ": Dict[str, str]", "default_value": "{'\\\\a': '\\x07', '\\\\b': '\\x08', '\\\\f': '\\x0c', '\\\\n': '\\n', '\\\\r': '\\r', '\\\\t': '\\t', '\\\\v': '\\x0b', '\\\\\\\\': '\\\\'}"}, "sqlglot.dialects.starrocks.StarRocks.tokenizer_class": {"fullname": "sqlglot.dialects.starrocks.StarRocks.tokenizer_class", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.tokenizer_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.tokens.Tokenizer'>"}, "sqlglot.dialects.starrocks.StarRocks.parser_class": {"fullname": "sqlglot.dialects.starrocks.StarRocks.parser_class", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.parser_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.starrocks.StarRocks.Parser'>"}, "sqlglot.dialects.starrocks.StarRocks.generator_class": {"fullname": "sqlglot.dialects.starrocks.StarRocks.generator_class", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.generator_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.starrocks.StarRocks.Generator'>"}, "sqlglot.dialects.starrocks.StarRocks.TIME_TRIE": {"fullname": "sqlglot.dialects.starrocks.StarRocks.TIME_TRIE", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'%': {'M': {0: True}, 'c': {0: True}, 'e': {0: True}, 'h': {0: True}, 'i': {0: True}, 's': {0: True}, 'u': {0: True}, 'k': {0: True}, 'l': {0: True}, 'T': {0: True}, 'W': {0: True}}}"}, "sqlglot.dialects.starrocks.StarRocks.FORMAT_TRIE": {"fullname": "sqlglot.dialects.starrocks.StarRocks.FORMAT_TRIE", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.FORMAT_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'%': {'M': {0: True}, 'c': {0: True}, 'e': {0: True}, 'h': {0: True}, 'i': {0: True}, 's': {0: True}, 'u': {0: True}, 'k': {0: True}, 'l': {0: True}, 'T': {0: True}, 'W': {0: True}}}"}, "sqlglot.dialects.starrocks.StarRocks.INVERSE_TIME_MAPPING": {"fullname": "sqlglot.dialects.starrocks.StarRocks.INVERSE_TIME_MAPPING", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.INVERSE_TIME_MAPPING", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'%B': '%M', '%-m': '%c', '%-d': '%e', '%I': '%h', '%M': '%i', '%S': '%s', '%W': '%u', '%-H': '%k', '%-I': '%l', '%H:%M:%S': '%T', '%a': '%W'}"}, "sqlglot.dialects.starrocks.StarRocks.INVERSE_TIME_TRIE": {"fullname": "sqlglot.dialects.starrocks.StarRocks.INVERSE_TIME_TRIE", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.INVERSE_TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'%': {'B': {0: True}, '-': {'m': {0: True}, 'd': {0: True}, 'H': {0: True}, 'I': {0: True}}, 'I': {0: True}, 'M': {0: True}, 'S': {0: True}, 'W': {0: True}, 'H': {':': {'%': {'M': {':': {'%': {'S': {0: True}}}}}}}, 'a': {0: True}}}"}, "sqlglot.dialects.starrocks.StarRocks.ESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.starrocks.StarRocks.ESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.ESCAPED_SEQUENCES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'\\x07': '\\\\a', '\\x08': '\\\\b', '\\x0c': '\\\\f', '\\n': '\\\\n', '\\r': '\\\\r', '\\t': '\\\\t', '\\x0b': '\\\\v', '\\\\': '\\\\\\\\'}"}, "sqlglot.dialects.starrocks.StarRocks.QUOTE_START": {"fullname": "sqlglot.dialects.starrocks.StarRocks.QUOTE_START", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.QUOTE_START", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.starrocks.StarRocks.QUOTE_END": {"fullname": "sqlglot.dialects.starrocks.StarRocks.QUOTE_END", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.QUOTE_END", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.starrocks.StarRocks.IDENTIFIER_START": {"fullname": "sqlglot.dialects.starrocks.StarRocks.IDENTIFIER_START", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.IDENTIFIER_START", "kind": "variable", "doc": "<p></p>\n", "default_value": "'`'"}, "sqlglot.dialects.starrocks.StarRocks.IDENTIFIER_END": {"fullname": "sqlglot.dialects.starrocks.StarRocks.IDENTIFIER_END", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.IDENTIFIER_END", "kind": "variable", "doc": "<p></p>\n", "default_value": "'`'"}, "sqlglot.dialects.starrocks.StarRocks.BIT_START": {"fullname": "sqlglot.dialects.starrocks.StarRocks.BIT_START", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.BIT_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""b'""}, "sqlglot.dialects.starrocks.StarRocks.BIT_END": {"fullname": "sqlglot.dialects.starrocks.StarRocks.BIT_END", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.BIT_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""'""}, "sqlglot.dialects.starrocks.StarRocks.HEX_START": {"fullname": "sqlglot.dialects.starrocks.StarRocks.HEX_START", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.HEX_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""x'""}, "sqlglot.dialects.starrocks.StarRocks.HEX_END": {"fullname": "sqlglot.dialects.starrocks.StarRocks.HEX_END", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.HEX_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""'""}, "sqlglot.dialects.starrocks.StarRocks.BYTE_START": {"fullname": "sqlglot.dialects.starrocks.StarRocks.BYTE_START", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.BYTE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.starrocks.StarRocks.BYTE_END": {"fullname": "sqlglot.dialects.starrocks.StarRocks.BYTE_END", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.BYTE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.starrocks.StarRocks.UNICODE_START": {"fullname": "sqlglot.dialects.starrocks.StarRocks.UNICODE_START", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.UNICODE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.starrocks.StarRocks.UNICODE_END": {"fullname": "sqlglot.dialects.starrocks.StarRocks.UNICODE_END", "modulename": "sqlglot.dialects.starrocks", "qualname": "StarRocks.UNICODE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.tableau": {"fullname": "sqlglot.dialects.tableau", "modulename": "sqlglot.dialects.tableau", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.dialects.tableau.Tableau": {"fullname": "sqlglot.dialects.tableau.Tableau", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.dialect.Dialect"}, "sqlglot.dialects.tableau.Tableau.LOG_BASE_FIRST": {"fullname": "sqlglot.dialects.tableau.Tableau.LOG_BASE_FIRST", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.LOG_BASE_FIRST", "kind": "variable", "doc": "<p>Whether the base comes first in the <code>LOG</code> function.\nPossible values: <code>True</code>, <code>False</code>, <code>None</code> (two arguments are not supported by <code>LOG</code>)</p>\n", "annotation": ": Optional[bool]", "default_value": "False"}, "sqlglot.dialects.tableau.Tableau.Tokenizer": {"fullname": "sqlglot.dialects.tableau.Tableau.Tokenizer", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.Tokenizer", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.tokens.Tokenizer"}, "sqlglot.dialects.tableau.Tableau.Tokenizer.IDENTIFIERS": {"fullname": "sqlglot.dialects.tableau.Tableau.Tokenizer.IDENTIFIERS", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.Tokenizer.IDENTIFIERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "[('[', ']')]"}, "sqlglot.dialects.tableau.Tableau.Tokenizer.QUOTES": {"fullname": "sqlglot.dialects.tableau.Tableau.Tokenizer.QUOTES", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.Tokenizer.QUOTES", "kind": "variable", "doc": "<p></p>\n", "default_value": "["'", '"']"}, "sqlglot.dialects.tableau.Tableau.Generator": {"fullname": "sqlglot.dialects.tableau.Tableau.Generator", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.Generator", "kind": "class", "doc": "<p>Generator converts a given syntax tree to the corresponding SQL string.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>pretty:</strong> Whether to format the produced SQL string.\nDefault: False.</li>\n<li><strong>identify:</strong> Determines when an identifier should be quoted. Possible values are:\nFalse (default): Never quote, except in cases where it's mandatory by the dialect.\nTrue or 'always': Always quote.\n'safe': Only quote identifiers that are case insensitive.</li>\n<li><strong>normalize:</strong> Whether to normalize identifiers to lowercase.\nDefault: False.</li>\n<li><strong>pad:</strong> The pad size in a formatted string. For example, this affects the indentation of\na projection in a query, relative to its nesting level.\nDefault: 2.</li>\n<li><strong>indent:</strong> The indentation size in a formatted string. For example, this affects the\nindentation of subqueries and filters under a <code>WHERE</code> clause.\nDefault: 2.</li>\n<li><strong>normalize_functions:</strong> How to normalize function names. Possible values are:\n\"upper\" or True (default): Convert names to uppercase.\n\"lower\": Convert names to lowercase.\nFalse: Disables function name normalization.</li>\n<li><strong>unsupported_level:</strong> Determines the generator's behavior when it encounters unsupported expressions.\nDefault ErrorLevel.WARN.</li>\n<li><strong>max_unsupported:</strong> Maximum number of unsupported messages to include in a raised UnsupportedError.\nThis is only relevant if unsupported_level is ErrorLevel.RAISE.\nDefault: 3</li>\n<li><strong>leading_comma:</strong> Whether the comma is leading or trailing in select expressions.\nThis is only relevant when generating in pretty mode.\nDefault: False</li>\n<li><strong>max_text_width:</strong> The max number of characters in a segment before creating new lines in pretty mode.\nThe default is on the smaller end because the length only represents a segment and not the true\nline length.\nDefault: 80</li>\n<li><strong>comments:</strong> Whether to preserve comments in the output SQL code.\nDefault: True</li>\n</ul>\n", "bases": "sqlglot.generator.Generator"}, "sqlglot.dialects.tableau.Tableau.Generator.JOIN_HINTS": {"fullname": "sqlglot.dialects.tableau.Tableau.Generator.JOIN_HINTS", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.Generator.JOIN_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.tableau.Tableau.Generator.TABLE_HINTS": {"fullname": "sqlglot.dialects.tableau.Tableau.Generator.TABLE_HINTS", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.Generator.TABLE_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.tableau.Tableau.Generator.QUERY_HINTS": {"fullname": "sqlglot.dialects.tableau.Tableau.Generator.QUERY_HINTS", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.Generator.QUERY_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.tableau.Tableau.Generator.TRANSFORMS": {"fullname": "sqlglot.dialects.tableau.Tableau.Generator.TRANSFORMS", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.Generator.TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.JSONPathFilter'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathKey'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRecursive'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRoot'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathScript'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSelector'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSlice'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSubscript'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathUnion'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathWildcard'>: <function <lambda>>, <class 'sqlglot.expressions.AllowedValuesProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.BackupProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CaseSpecificColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CollateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CommentColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DateFormatColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DefaultColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EncodeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EphemeralColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExcludeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExternalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.GlobalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.HeapProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IcebergProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InheritsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InlineLengthColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IntervalSpan'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtract'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtractScalar'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LanguageProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LocationProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LogProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.MaterializedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NonClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NotForReplicationColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnCommitProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnUpdateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OutputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.PathColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ReturnsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SampleProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetConfigProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SettingsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SharingProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlReadWriteProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlSecurityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StabilityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StrictProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TemporaryProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TitleColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.Timestamp'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransformModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransientProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UppercaseColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UnloggedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VarMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VolatileProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithOperator'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.Coalesce'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.Select'>: <function preprocess.<locals>._to_sql>}"}, "sqlglot.dialects.tableau.Tableau.Generator.PROPERTIES_LOCATION": {"fullname": "sqlglot.dialects.tableau.Tableau.Generator.PROPERTIES_LOCATION", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.Generator.PROPERTIES_LOCATION", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.AllowedValuesProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.AlgorithmProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.AutoIncrementProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.BackupProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.BlockCompressionProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.CharacterSetProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ChecksumProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.CollateProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Cluster'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ClusteredByProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DataBlocksizeProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.DataDeletionProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DefinerProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.DictRange'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DictProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DistKeyProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DistStyleProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.EngineProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ExternalProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.FallbackProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.FileFormatProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.FreespaceProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.GlobalProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.HeapProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.InheritsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.IcebergProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.InputModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.IsolatedLoadingProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.JournalProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.LanguageProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LikeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LocationProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LockProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LockingProperty'>: <Location.POST_ALIAS: 'POST_ALIAS'>, <class 'sqlglot.expressions.LogProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.MaterializedProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.MergeBlockRatioProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.OnProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.OnCommitProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.Order'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.OutputModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.PartitionedByProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.PartitionedOfProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.PrimaryKey'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Property'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ReturnsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatDelimitedProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatSerdeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SampleProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SchemaCommentProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SerdeProperties'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Set'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SettingsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SetProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.SetConfigProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SharingProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.SequenceProperties'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.SortKeyProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SqlReadWriteProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SqlSecurityProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.StabilityProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.StrictProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.TemporaryProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.ToTableProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.TransientProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.TransformModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.MergeTreeTTL'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.UnloggedProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.VolatileProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.WithDataProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.WithSystemVersioningProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>}"}, "sqlglot.dialects.tableau.Tableau.Generator.if_sql": {"fullname": "sqlglot.dialects.tableau.Tableau.Generator.if_sql", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.Generator.if_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">If</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tableau.Tableau.Generator.count_sql": {"fullname": "sqlglot.dialects.tableau.Tableau.Generator.count_sql", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.Generator.count_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Count</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tableau.Tableau.Generator.SELECT_KINDS": {"fullname": "sqlglot.dialects.tableau.Tableau.Generator.SELECT_KINDS", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.Generator.SELECT_KINDS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Tuple[str, ...]", "default_value": "()"}, "sqlglot.dialects.tableau.Tableau.Generator.TRY_SUPPORTED": {"fullname": "sqlglot.dialects.tableau.Tableau.Generator.TRY_SUPPORTED", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.Generator.TRY_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.tableau.Tableau.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS": {"fullname": "sqlglot.dialects.tableau.Tableau.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'qualify': <function Generator.<lambda>>, 'windows': <function Generator.<lambda>>}"}, "sqlglot.dialects.tableau.Tableau.Parser": {"fullname": "sqlglot.dialects.tableau.Tableau.Parser", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.Parser", "kind": "class", "doc": "<p>Parser consumes a list of tokens produced by the Tokenizer and produces a parsed syntax tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>error_level:</strong> The desired error level.\nDefault: ErrorLevel.IMMEDIATE</li>\n<li><strong>error_message_context:</strong> The amount of context to capture from a query string when displaying\nthe error message (in number of characters).\nDefault: 100</li>\n<li><strong>max_errors:</strong> Maximum number of error messages to include in a raised ParseError.\nThis is only relevant if error_level is ErrorLevel.RAISE.\nDefault: 3</li>\n</ul>\n", "bases": "sqlglot.parser.Parser"}, "sqlglot.dialects.tableau.Tableau.Parser.FUNCTIONS": {"fullname": "sqlglot.dialects.tableau.Tableau.Parser.FUNCTIONS", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.Parser.FUNCTIONS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ABS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Abs'>>, 'ADD_MONTHS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AddMonths'>>, 'ANONYMOUS_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnonymousAggFunc'>>, 'ANY_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnyValue'>>, 'APPROX_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_COUNT_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'APPROX_TOP_K': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxTopK'>>, 'ARG_MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARGMAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'MAX_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARG_MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARGMIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'MIN_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Array'>>, 'ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAgg'>>, 'ARRAY_ALL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAll'>>, 'ARRAY_ANY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAny'>>, 'ARRAY_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CONSTRUCT_COMPACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConstructCompact'>>, 'ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayContains'>>, 'FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_OVERLAPS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayOverlaps'>>, 'ARRAY_SIZE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_SORT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySort'>>, 'ARRAY_SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySum'>>, 'ARRAY_TO_STRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_JOIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_UNION_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUnionAgg'>>, 'ARRAY_UNIQUE_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUniqueAgg'>>, 'AVG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Avg'>>, 'CASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Case'>>, 'CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cast'>>, 'CAST_TO_STR_TYPE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CastToStrType'>>, 'CBRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cbrt'>>, 'CEIL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CEILING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CHR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'COALESCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'IFNULL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'NVL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'COLLATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Collate'>>, 'COMBINED_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedAggFunc'>>, 'COMBINED_PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedParameterizedAgg'>>, 'CONCAT': <function Parser.<lambda>>, 'CONCAT_WS': <function Parser.<lambda>>, 'CONNECT_BY_ROOT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ConnectByRoot'>>, 'CONVERT': <bound method Func.from_arg_list of <class 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method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STARTSWITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STDDEV': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stddev'>>, 'STDDEV_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StddevPop'>>, 'STDDEV_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StddevSamp'>>, 'STR_POSITION': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrPosition'>>, 'STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToDate'>>, 'STR_TO_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToMap'>>, 'STR_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToTime'>>, 'STR_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToUnix'>>, 'STRUCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Struct'>>, 'STRUCT_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StructExtract'>>, 'STUFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stuff'>>, 'INSERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stuff'>>, 'SUBSTRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Substring'>>, 'SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sum'>>, 'TIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeAdd'>>, 'TIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeDiff'>>, 'TIME_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'TIMEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'TIME_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToDate'>>, 'TIME_STR_TO_TIME': <bound method Func.from_arg_list of <class 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'TRIM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Trim'>>, 'TRY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Try'>>, 'TRY_CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TryCast'>>, 'TS_OR_DI_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDiToDi'>>, 'TS_OR_DS_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsAdd'>>, 'TS_OR_DS_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsDiff'>>, 'TS_OR_DS_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToDate'>>, 'TS_OR_DS_TO_DATE_STR': <function Parser.<lambda>>, 'TS_OR_DS_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTime'>>, 'TS_OR_DS_TO_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTimestamp'>>, 'UNHEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Unhex'>>, 'UNIX_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixDate'>>, 'UNIX_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToStr'>>, 'UNIX_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTime'>>, 'UNIX_TO_TIME_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTimeStr'>>, 'UPPER': <function build_upper>, 'UCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Upper'>>, 'VAR_MAP': <function build_var_map>, 'VARIANCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'VAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Week'>>, 'WEEK_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.WeekOfYear'>>, 'WEEKOFYEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.WeekOfYear'>>, 'WHEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.When'>>, 'X_M_L_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.XMLTable'>>, 'XOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Xor'>>, 'YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Year'>>, 'GLOB': <function Parser.<lambda>>, 'JSON_EXTRACT_PATH_TEXT': <function build_extract_json_with_path.<locals>._builder>, 'LIKE': <function build_like>, 'LOG2': <function Parser.<lambda>>, 'LOG10': <function Parser.<lambda>>, 'MOD': <function build_mod>, 'TO_HEX': <function build_hex>, 'COUNTD': <function Tableau.Parser.<lambda>>}"}, "sqlglot.dialects.tableau.Tableau.Parser.NO_PAREN_IF_COMMANDS": {"fullname": "sqlglot.dialects.tableau.Tableau.Parser.NO_PAREN_IF_COMMANDS", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.Parser.NO_PAREN_IF_COMMANDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.tableau.Tableau.Parser.SHOW_TRIE": {"fullname": "sqlglot.dialects.tableau.Tableau.Parser.SHOW_TRIE", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.Parser.SHOW_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.tableau.Tableau.Parser.SET_TRIE": {"fullname": "sqlglot.dialects.tableau.Tableau.Parser.SET_TRIE", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.Parser.SET_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'GLOBAL': {0: True}, 'LOCAL': {0: True}, 'SESSION': {0: True}, 'TRANSACTION': {0: True}}"}, "sqlglot.dialects.tableau.Tableau.tokenizer_class": {"fullname": "sqlglot.dialects.tableau.Tableau.tokenizer_class", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.tokenizer_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.tableau.Tableau.Tokenizer'>"}, "sqlglot.dialects.tableau.Tableau.parser_class": {"fullname": "sqlglot.dialects.tableau.Tableau.parser_class", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.parser_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.tableau.Tableau.Parser'>"}, "sqlglot.dialects.tableau.Tableau.generator_class": {"fullname": "sqlglot.dialects.tableau.Tableau.generator_class", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.generator_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.tableau.Tableau.Generator'>"}, "sqlglot.dialects.tableau.Tableau.TIME_TRIE": {"fullname": "sqlglot.dialects.tableau.Tableau.TIME_TRIE", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.tableau.Tableau.FORMAT_TRIE": {"fullname": "sqlglot.dialects.tableau.Tableau.FORMAT_TRIE", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.FORMAT_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.tableau.Tableau.INVERSE_TIME_MAPPING": {"fullname": "sqlglot.dialects.tableau.Tableau.INVERSE_TIME_MAPPING", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.INVERSE_TIME_MAPPING", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{}"}, "sqlglot.dialects.tableau.Tableau.INVERSE_TIME_TRIE": {"fullname": "sqlglot.dialects.tableau.Tableau.INVERSE_TIME_TRIE", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.INVERSE_TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.tableau.Tableau.ESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.tableau.Tableau.ESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.ESCAPED_SEQUENCES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{}"}, "sqlglot.dialects.tableau.Tableau.QUOTE_START": {"fullname": "sqlglot.dialects.tableau.Tableau.QUOTE_START", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.QUOTE_START", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.tableau.Tableau.QUOTE_END": {"fullname": "sqlglot.dialects.tableau.Tableau.QUOTE_END", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.QUOTE_END", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.tableau.Tableau.IDENTIFIER_START": {"fullname": "sqlglot.dialects.tableau.Tableau.IDENTIFIER_START", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.IDENTIFIER_START", "kind": "variable", "doc": "<p></p>\n", "default_value": "'['"}, "sqlglot.dialects.tableau.Tableau.IDENTIFIER_END": {"fullname": "sqlglot.dialects.tableau.Tableau.IDENTIFIER_END", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.IDENTIFIER_END", "kind": "variable", "doc": "<p></p>\n", "default_value": "']'"}, "sqlglot.dialects.tableau.Tableau.BIT_START": {"fullname": "sqlglot.dialects.tableau.Tableau.BIT_START", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.BIT_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.tableau.Tableau.BIT_END": {"fullname": "sqlglot.dialects.tableau.Tableau.BIT_END", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.BIT_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.tableau.Tableau.HEX_START": {"fullname": "sqlglot.dialects.tableau.Tableau.HEX_START", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.HEX_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.tableau.Tableau.HEX_END": {"fullname": "sqlglot.dialects.tableau.Tableau.HEX_END", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.HEX_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.tableau.Tableau.BYTE_START": {"fullname": "sqlglot.dialects.tableau.Tableau.BYTE_START", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.BYTE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.tableau.Tableau.BYTE_END": {"fullname": "sqlglot.dialects.tableau.Tableau.BYTE_END", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.BYTE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.tableau.Tableau.UNICODE_START": {"fullname": "sqlglot.dialects.tableau.Tableau.UNICODE_START", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.UNICODE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.tableau.Tableau.UNICODE_END": {"fullname": "sqlglot.dialects.tableau.Tableau.UNICODE_END", "modulename": "sqlglot.dialects.tableau", "qualname": "Tableau.UNICODE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.teradata": {"fullname": "sqlglot.dialects.teradata", "modulename": "sqlglot.dialects.teradata", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.dialects.teradata.Teradata": {"fullname": "sqlglot.dialects.teradata.Teradata", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.dialect.Dialect"}, "sqlglot.dialects.teradata.Teradata.SUPPORTS_SEMI_ANTI_JOIN": {"fullname": "sqlglot.dialects.teradata.Teradata.SUPPORTS_SEMI_ANTI_JOIN", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.SUPPORTS_SEMI_ANTI_JOIN", "kind": "variable", "doc": "<p>Whether <code>SEMI</code> or <code>ANTI</code> joins are supported.</p>\n", "default_value": "False"}, "sqlglot.dialects.teradata.Teradata.TYPED_DIVISION": {"fullname": "sqlglot.dialects.teradata.Teradata.TYPED_DIVISION", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.TYPED_DIVISION", "kind": "variable", "doc": "<p>Whether the behavior of <code>a / b</code> depends on the types of <code>a</code> and <code>b</code>.\nFalse means <code>a / b</code> is always float division.\nTrue means <code>a / b</code> is integer division if both <code>a</code> and <code>b</code> are integers.</p>\n", "default_value": "True"}, "sqlglot.dialects.teradata.Teradata.TIME_MAPPING": {"fullname": "sqlglot.dialects.teradata.Teradata.TIME_MAPPING", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.TIME_MAPPING", "kind": "variable", "doc": "<p>Associates this dialect's time formats with their equivalent Python <code>strftime</code> formats.</p>\n", "annotation": ": Dict[str, str]", "default_value": "{'YY': '%y', 'Y4': '%Y', 'YYYY': '%Y', 'M4': '%B', 'M3': '%b', 'M': '%-M', 'MI': '%M', 'MM': '%m', 'MMM': '%b', 'MMMM': '%B', 'D': '%-d', 'DD': '%d', 'D3': '%j', 'DDD': '%j', 'H': '%-H', 'HH': '%H', 'HH24': '%H', 'S': '%-S', 'SS': '%S', 'SSSSSS': '%f', 'E': '%a', 'EE': '%a', 'E3': '%a', 'E4': '%A', 'EEE': '%a', 'EEEE': '%A'}"}, "sqlglot.dialects.teradata.Teradata.Tokenizer": {"fullname": "sqlglot.dialects.teradata.Teradata.Tokenizer", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Tokenizer", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.tokens.Tokenizer"}, "sqlglot.dialects.teradata.Teradata.Tokenizer.KEYWORDS": {"fullname": "sqlglot.dialects.teradata.Teradata.Tokenizer.KEYWORDS", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Tokenizer.KEYWORDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'{%': <TokenType.BLOCK_START: 'BLOCK_START'>, '{%+': <TokenType.BLOCK_START: 'BLOCK_START'>, '{%-': <TokenType.BLOCK_START: 'BLOCK_START'>, '%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '+%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '-%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '{{+': <TokenType.BLOCK_START: 'BLOCK_START'>, '{{-': <TokenType.BLOCK_START: 'BLOCK_START'>, '+}}': <TokenType.BLOCK_END: 'BLOCK_END'>, '-}}': <TokenType.BLOCK_END: 'BLOCK_END'>, '/*+': <TokenType.HINT: 'HINT'>, '==': <TokenType.EQ: 'EQ'>, '::': <TokenType.DCOLON: 'DCOLON'>, '||': <TokenType.DPIPE: 'DPIPE'>, '>=': <TokenType.GTE: 'GTE'>, '<=': <TokenType.LTE: 'LTE'>, '<>': <TokenType.NEQ: 'NEQ'>, '!=': <TokenType.NEQ: 'NEQ'>, ':=': <TokenType.COLON_EQ: 'COLON_EQ'>, '<=>': <TokenType.NULLSAFE_EQ: 'NULLSAFE_EQ'>, '->': <TokenType.ARROW: 'ARROW'>, '->>': <TokenType.DARROW: 'DARROW'>, '=>': <TokenType.FARROW: 'FARROW'>, '#>': <TokenType.HASH_ARROW: 'HASH_ARROW'>, '#>>': <TokenType.DHASH_ARROW: 'DHASH_ARROW'>, '<->': <TokenType.LR_ARROW: 'LR_ARROW'>, '&&': <TokenType.DAMP: 'DAMP'>, '??': <TokenType.DQMARK: 'DQMARK'>, 'ALL': <TokenType.ALL: 'ALL'>, 'ALWAYS': <TokenType.ALWAYS: 'ALWAYS'>, 'AND': <TokenType.AND: 'AND'>, 'ANTI': <TokenType.ANTI: 'ANTI'>, 'ANY': <TokenType.ANY: 'ANY'>, 'ASC': <TokenType.ASC: 'ASC'>, 'AS': <TokenType.ALIAS: 'ALIAS'>, 'ASOF': <TokenType.ASOF: 'ASOF'>, 'AUTOINCREMENT': <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, 'AUTO_INCREMENT': <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, 'BEGIN': <TokenType.BEGIN: 'BEGIN'>, 'BETWEEN': <TokenType.BETWEEN: 'BETWEEN'>, 'CACHE': <TokenType.CACHE: 'CACHE'>, 'UNCACHE': <TokenType.UNCACHE: 'UNCACHE'>, 'CASE': <TokenType.CASE: 'CASE'>, 'CHARACTER SET': <TokenType.CHARACTER_SET: 'CHARACTER_SET'>, 'CLUSTER BY': <TokenType.CLUSTER_BY: 'CLUSTER_BY'>, 'COLLATE': <TokenType.COLLATE: 'COLLATE'>, 'COLUMN': <TokenType.COLUMN: 'COLUMN'>, 'COMMIT': <TokenType.COMMIT: 'COMMIT'>, 'CONNECT BY': <TokenType.CONNECT_BY: 'CONNECT_BY'>, 'CONSTRAINT': <TokenType.CONSTRAINT: 'CONSTRAINT'>, 'COPY': <TokenType.COPY: 'COPY'>, 'CREATE': <TokenType.CREATE: 'CREATE'>, 'CROSS': <TokenType.CROSS: 'CROSS'>, 'CUBE': <TokenType.CUBE: 'CUBE'>, 'CURRENT_DATE': <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, 'CURRENT_TIME': <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, 'CURRENT_TIMESTAMP': <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, 'CURRENT_USER': <TokenType.CURRENT_USER: 'CURRENT_USER'>, 'DATABASE': <TokenType.DATABASE: 'DATABASE'>, 'DEFAULT': <TokenType.DEFAULT: 'DEFAULT'>, 'DELETE': <TokenType.DELETE: 'DELETE'>, 'DESC': <TokenType.DESC: 'DESC'>, 'DESCRIBE': <TokenType.DESCRIBE: 'DESCRIBE'>, 'DISTINCT': <TokenType.DISTINCT: 'DISTINCT'>, 'DISTRIBUTE BY': <TokenType.DISTRIBUTE_BY: 'DISTRIBUTE_BY'>, 'DIV': <TokenType.DIV: 'DIV'>, 'DROP': <TokenType.DROP: 'DROP'>, 'ELSE': <TokenType.ELSE: 'ELSE'>, 'END': <TokenType.END: 'END'>, 'ENUM': <TokenType.ENUM: 'ENUM'>, 'ESCAPE': <TokenType.ESCAPE: 'ESCAPE'>, 'EXCEPT': <TokenType.EXCEPT: 'EXCEPT'>, 'EXECUTE': <TokenType.EXECUTE: 'EXECUTE'>, 'EXISTS': <TokenType.EXISTS: 'EXISTS'>, 'FALSE': <TokenType.FALSE: 'FALSE'>, 'FETCH': <TokenType.FETCH: 'FETCH'>, 'FILTER': <TokenType.FILTER: 'FILTER'>, 'FIRST': <TokenType.FIRST: 'FIRST'>, 'FULL': <TokenType.FULL: 'FULL'>, 'FUNCTION': <TokenType.FUNCTION: 'FUNCTION'>, 'FOR': <TokenType.FOR: 'FOR'>, 'FOREIGN KEY': <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, 'FORMAT': <TokenType.FORMAT: 'FORMAT'>, 'FROM': <TokenType.FROM: 'FROM'>, 'GEOGRAPHY': <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, 'GEOMETRY': <TokenType.GEOMETRY: 'GEOMETRY'>, 'GLOB': <TokenType.GLOB: 'GLOB'>, 'GROUP BY': <TokenType.GROUP_BY: 'GROUP_BY'>, 'GROUPING SETS': <TokenType.GROUPING_SETS: 'GROUPING_SETS'>, 'HAVING': <TokenType.HAVING: 'HAVING'>, 'ILIKE': <TokenType.ILIKE: 'ILIKE'>, 'IN': <TokenType.IN: 'IN'>, 'INDEX': <TokenType.INDEX: 'INDEX'>, 'INET': <TokenType.INET: 'INET'>, 'INNER': <TokenType.INNER: 'INNER'>, 'INSERT': <TokenType.INSERT: 'INSERT'>, 'INTERVAL': <TokenType.INTERVAL: 'INTERVAL'>, 'INTERSECT': <TokenType.INTERSECT: 'INTERSECT'>, 'INTO': <TokenType.INTO: 'INTO'>, 'IS': <TokenType.IS: 'IS'>, 'ISNULL': <TokenType.ISNULL: 'ISNULL'>, 'JOIN': <TokenType.JOIN: 'JOIN'>, 'KEEP': <TokenType.KEEP: 'KEEP'>, 'KILL': <TokenType.KILL: 'KILL'>, 'LATERAL': <TokenType.LATERAL: 'LATERAL'>, 'LEFT': <TokenType.LEFT: 'LEFT'>, 'LIKE': <TokenType.LIKE: 'LIKE'>, 'LIMIT': <TokenType.LIMIT: 'LIMIT'>, 'LOAD': <TokenType.LOAD: 'LOAD'>, 'LOCK': <TokenType.LOCK: 'LOCK'>, 'MERGE': <TokenType.MERGE: 'MERGE'>, 'NATURAL': <TokenType.NATURAL: 'NATURAL'>, 'NEXT': <TokenType.NEXT: 'NEXT'>, 'NOT': <TokenType.NOT: 'NOT'>, 'NOTNULL': <TokenType.NOTNULL: 'NOTNULL'>, 'NULL': <TokenType.NULL: 'NULL'>, 'OBJECT': <TokenType.OBJECT: 'OBJECT'>, 'OFFSET': <TokenType.OFFSET: 'OFFSET'>, 'ON': <TokenType.ON: 'ON'>, 'OR': <TokenType.OR: 'OR'>, 'XOR': <TokenType.XOR: 'XOR'>, 'ORDER BY': <TokenType.ORDER_BY: 'ORDER_BY'>, 'ORDINALITY': <TokenType.ORDINALITY: 'ORDINALITY'>, 'OUTER': <TokenType.OUTER: 'OUTER'>, 'OVER': <TokenType.OVER: 'OVER'>, 'OVERLAPS': <TokenType.OVERLAPS: 'OVERLAPS'>, 'OVERWRITE': <TokenType.OVERWRITE: 'OVERWRITE'>, 'PARTITION': <TokenType.PARTITION: 'PARTITION'>, 'PARTITION BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PARTITIONED BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PARTITIONED_BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PERCENT': <TokenType.PERCENT: 'PERCENT'>, 'PIVOT': <TokenType.PIVOT: 'PIVOT'>, 'PRAGMA': <TokenType.PRAGMA: 'PRAGMA'>, 'PRIMARY KEY': <TokenType.PRIMARY_KEY: 'PRIMARY_KEY'>, 'PROCEDURE': <TokenType.PROCEDURE: 'PROCEDURE'>, 'QUALIFY': <TokenType.QUALIFY: 'QUALIFY'>, 'RANGE': <TokenType.RANGE: 'RANGE'>, 'RECURSIVE': <TokenType.RECURSIVE: 'RECURSIVE'>, 'REGEXP': <TokenType.RLIKE: 'RLIKE'>, 'REPLACE': <TokenType.REPLACE: 'REPLACE'>, 'RETURNING': <TokenType.RETURNING: 'RETURNING'>, 'REFERENCES': <TokenType.REFERENCES: 'REFERENCES'>, 'RIGHT': <TokenType.RIGHT: 'RIGHT'>, 'RLIKE': <TokenType.RLIKE: 'RLIKE'>, 'ROLLBACK': <TokenType.ROLLBACK: 'ROLLBACK'>, 'ROLLUP': <TokenType.ROLLUP: 'ROLLUP'>, 'ROW': <TokenType.ROW: 'ROW'>, 'ROWS': <TokenType.ROWS: 'ROWS'>, 'SCHEMA': <TokenType.SCHEMA: 'SCHEMA'>, 'SELECT': <TokenType.SELECT: 'SELECT'>, 'SEMI': <TokenType.SEMI: 'SEMI'>, 'SET': <TokenType.SET: 'SET'>, 'SETTINGS': <TokenType.SETTINGS: 'SETTINGS'>, 'SHOW': <TokenType.SHOW: 'SHOW'>, 'SIMILAR TO': <TokenType.SIMILAR_TO: 'SIMILAR_TO'>, 'SOME': <TokenType.SOME: 'SOME'>, 'SORT BY': <TokenType.SORT_BY: 'SORT_BY'>, 'START WITH': <TokenType.START_WITH: 'START_WITH'>, 'TABLE': <TokenType.TABLE: 'TABLE'>, 'TABLESAMPLE': <TokenType.TABLE_SAMPLE: 'TABLE_SAMPLE'>, 'TEMP': <TokenType.TEMPORARY: 'TEMPORARY'>, 'TEMPORARY': <TokenType.TEMPORARY: 'TEMPORARY'>, 'THEN': <TokenType.THEN: 'THEN'>, 'TRUE': <TokenType.TRUE: 'TRUE'>, 'TRUNCATE': <TokenType.TRUNCATE: 'TRUNCATE'>, 'UNION': <TokenType.UNION: 'UNION'>, 'UNKNOWN': <TokenType.UNKNOWN: 'UNKNOWN'>, 'UNNEST': <TokenType.UNNEST: 'UNNEST'>, 'UNPIVOT': <TokenType.UNPIVOT: 'UNPIVOT'>, 'UPDATE': <TokenType.UPDATE: 'UPDATE'>, 'USE': <TokenType.USE: 'USE'>, 'USING': <TokenType.USING: 'USING'>, 'UUID': <TokenType.UUID: 'UUID'>, 'VALUES': <TokenType.VALUES: 'VALUES'>, 'VIEW': <TokenType.VIEW: 'VIEW'>, 'VOLATILE': <TokenType.VOLATILE: 'VOLATILE'>, 'WHEN': <TokenType.WHEN: 'WHEN'>, 'WHERE': <TokenType.WHERE: 'WHERE'>, 'WINDOW': <TokenType.WINDOW: 'WINDOW'>, 'WITH': <TokenType.WITH: 'WITH'>, 'APPLY': <TokenType.APPLY: 'APPLY'>, 'ARRAY': <TokenType.ARRAY: 'ARRAY'>, 'BIT': <TokenType.BIT: 'BIT'>, 'BOOL': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BOOLEAN': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BYTE': <TokenType.TINYINT: 'TINYINT'>, 'MEDIUMINT': <TokenType.MEDIUMINT: 'MEDIUMINT'>, 'INT1': <TokenType.TINYINT: 'TINYINT'>, 'TINYINT': <TokenType.TINYINT: 'TINYINT'>, 'INT16': <TokenType.SMALLINT: 'SMALLINT'>, 'SHORT': <TokenType.SMALLINT: 'SMALLINT'>, 'SMALLINT': <TokenType.SMALLINT: 'SMALLINT'>, 'INT128': <TokenType.INT128: 'INT128'>, 'HUGEINT': <TokenType.INT128: 'INT128'>, 'INT2': <TokenType.SMALLINT: 'SMALLINT'>, 'INTEGER': <TokenType.INT: 'INT'>, 'INT': <TokenType.INT: 'INT'>, 'INT4': <TokenType.INT: 'INT'>, 'INT32': <TokenType.INT: 'INT'>, 'INT64': <TokenType.BIGINT: 'BIGINT'>, 'LONG': <TokenType.BIGINT: 'BIGINT'>, 'BIGINT': <TokenType.BIGINT: 'BIGINT'>, 'INT8': <TokenType.TINYINT: 'TINYINT'>, 'UINT': <TokenType.UINT: 'UINT'>, 'DEC': <TokenType.DECIMAL: 'DECIMAL'>, 'DECIMAL': <TokenType.DECIMAL: 'DECIMAL'>, 'BIGDECIMAL': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'BIGNUMERIC': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'MAP': <TokenType.MAP: 'MAP'>, 'NULLABLE': <TokenType.NULLABLE: 'NULLABLE'>, 'NUMBER': <TokenType.DECIMAL: 'DECIMAL'>, 'NUMERIC': <TokenType.DECIMAL: 'DECIMAL'>, 'FIXED': <TokenType.DECIMAL: 'DECIMAL'>, 'REAL': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT4': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT8': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE PRECISION': <TokenType.DOUBLE: 'DOUBLE'>, 'JSON': <TokenType.JSON: 'JSON'>, 'CHAR': <TokenType.CHAR: 'CHAR'>, 'CHARACTER': <TokenType.CHAR: 'CHAR'>, 'NCHAR': <TokenType.NCHAR: 'NCHAR'>, 'VARCHAR': <TokenType.VARCHAR: 'VARCHAR'>, 'VARCHAR2': <TokenType.VARCHAR: 'VARCHAR'>, 'NVARCHAR': <TokenType.NVARCHAR: 'NVARCHAR'>, 'NVARCHAR2': <TokenType.NVARCHAR: 'NVARCHAR'>, 'BPCHAR': <TokenType.BPCHAR: 'BPCHAR'>, 'STR': <TokenType.TEXT: 'TEXT'>, 'STRING': <TokenType.TEXT: 'TEXT'>, 'TEXT': <TokenType.TEXT: 'TEXT'>, 'LONGTEXT': <TokenType.LONGTEXT: 'LONGTEXT'>, 'MEDIUMTEXT': <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, 'TINYTEXT': <TokenType.TINYTEXT: 'TINYTEXT'>, 'CLOB': <TokenType.TEXT: 'TEXT'>, 'LONGVARCHAR': <TokenType.TEXT: 'TEXT'>, 'BINARY': <TokenType.BINARY: 'BINARY'>, 'BLOB': <TokenType.VARBINARY: 'VARBINARY'>, 'LONGBLOB': <TokenType.LONGBLOB: 'LONGBLOB'>, 'MEDIUMBLOB': <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, 'TINYBLOB': <TokenType.TINYBLOB: 'TINYBLOB'>, 'BYTEA': <TokenType.VARBINARY: 'VARBINARY'>, 'VARBINARY': <TokenType.VARBINARY: 'VARBINARY'>, 'TIME': <TokenType.TIME: 'TIME'>, 'TIMETZ': <TokenType.TIMETZ: 'TIMETZ'>, 'TIMESTAMP': <TokenType.TIMESTAMP: 'TIMESTAMP'>, 'TIMESTAMPTZ': <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, 'TIMESTAMPLTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMP_LTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMPNTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'TIMESTAMP_NTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'DATE': <TokenType.DATE: 'DATE'>, 'DATETIME': <TokenType.DATETIME: 'DATETIME'>, 'INT4RANGE': <TokenType.INT4RANGE: 'INT4RANGE'>, 'INT4MULTIRANGE': <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, 'INT8RANGE': <TokenType.INT8RANGE: 'INT8RANGE'>, 'INT8MULTIRANGE': <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, 'NUMRANGE': <TokenType.NUMRANGE: 'NUMRANGE'>, 'NUMMULTIRANGE': <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, 'TSRANGE': <TokenType.TSRANGE: 'TSRANGE'>, 'TSMULTIRANGE': <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, 'TSTZRANGE': <TokenType.TSTZRANGE: 'TSTZRANGE'>, 'TSTZMULTIRANGE': <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, 'DATERANGE': <TokenType.DATERANGE: 'DATERANGE'>, 'DATEMULTIRANGE': <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, 'UNIQUE': <TokenType.UNIQUE: 'UNIQUE'>, 'STRUCT': <TokenType.STRUCT: 'STRUCT'>, 'SEQUENCE': <TokenType.SEQUENCE: 'SEQUENCE'>, 'VARIANT': <TokenType.VARIANT: 'VARIANT'>, 'ALTER': <TokenType.ALTER: 'ALTER'>, 'ANALYZE': <TokenType.COMMAND: 'COMMAND'>, 'CALL': <TokenType.COMMAND: 'COMMAND'>, 'COMMENT': <TokenType.COMMENT: 'COMMENT'>, 'EXPLAIN': <TokenType.COMMAND: 'COMMAND'>, 'GRANT': <TokenType.COMMAND: 'COMMAND'>, 'OPTIMIZE': <TokenType.COMMAND: 'COMMAND'>, 'PREPARE': <TokenType.COMMAND: 'COMMAND'>, 'VACUUM': <TokenType.COMMAND: 'COMMAND'>, 'USER-DEFINED': <TokenType.USERDEFINED: 'USERDEFINED'>, 'FOR VERSION': <TokenType.VERSION_SNAPSHOT: 'VERSION_SNAPSHOT'>, 'FOR TIMESTAMP': <TokenType.TIMESTAMP_SNAPSHOT: 'TIMESTAMP_SNAPSHOT'>, '**': <TokenType.DSTAR: 'DSTAR'>, '^=': <TokenType.NEQ: 'NEQ'>, 'BYTEINT': <TokenType.SMALLINT: 'SMALLINT'>, 'COLLECT': <TokenType.COMMAND: 'COMMAND'>, 'DEL': <TokenType.DELETE: 'DELETE'>, 'EQ': <TokenType.EQ: 'EQ'>, 'GE': <TokenType.GTE: 'GTE'>, 'GT': <TokenType.GT: 'GT'>, 'HELP': <TokenType.COMMAND: 'COMMAND'>, 'INS': <TokenType.INSERT: 'INSERT'>, 'LE': <TokenType.LTE: 'LTE'>, 'LT': <TokenType.LT: 'LT'>, 'MINUS': <TokenType.EXCEPT: 'EXCEPT'>, 'MOD': <TokenType.MOD: 'MOD'>, 'NE': <TokenType.NEQ: 'NEQ'>, 'NOT=': <TokenType.NEQ: 'NEQ'>, 'SAMPLE': <TokenType.TABLE_SAMPLE: 'TABLE_SAMPLE'>, 'SEL': <TokenType.SELECT: 'SELECT'>, 'ST_GEOMETRY': <TokenType.GEOMETRY: 'GEOMETRY'>, 'TOP': <TokenType.TOP: 'TOP'>, 'UPD': <TokenType.UPDATE: 'UPDATE'>}"}, "sqlglot.dialects.teradata.Teradata.Tokenizer.SINGLE_TOKENS": {"fullname": "sqlglot.dialects.teradata.Teradata.Tokenizer.SINGLE_TOKENS", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Tokenizer.SINGLE_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'(': <TokenType.L_PAREN: 'L_PAREN'>, ')': <TokenType.R_PAREN: 'R_PAREN'>, '[': <TokenType.L_BRACKET: 'L_BRACKET'>, ']': <TokenType.R_BRACKET: 'R_BRACKET'>, '{': <TokenType.L_BRACE: 'L_BRACE'>, '}': <TokenType.R_BRACE: 'R_BRACE'>, '&': <TokenType.AMP: 'AMP'>, '^': <TokenType.CARET: 'CARET'>, ':': <TokenType.COLON: 'COLON'>, ',': <TokenType.COMMA: 'COMMA'>, '.': <TokenType.DOT: 'DOT'>, '-': <TokenType.DASH: 'DASH'>, '=': <TokenType.EQ: 'EQ'>, '>': <TokenType.GT: 'GT'>, '<': <TokenType.LT: 'LT'>, '!': <TokenType.NOT: 'NOT'>, '|': <TokenType.PIPE: 'PIPE'>, '+': <TokenType.PLUS: 'PLUS'>, ';': <TokenType.SEMICOLON: 'SEMICOLON'>, '/': <TokenType.SLASH: 'SLASH'>, '\\\\': <TokenType.BACKSLASH: 'BACKSLASH'>, '*': <TokenType.STAR: 'STAR'>, '~': <TokenType.TILDA: 'TILDA'>, '?': <TokenType.PLACEHOLDER: 'PLACEHOLDER'>, '@': <TokenType.PARAMETER: 'PARAMETER'>, '#': <TokenType.HASH: 'HASH'>, "'": <TokenType.UNKNOWN: 'UNKNOWN'>, '`': <TokenType.UNKNOWN: 'UNKNOWN'>, '"': <TokenType.UNKNOWN: 'UNKNOWN'>}"}, "sqlglot.dialects.teradata.Teradata.Parser": {"fullname": "sqlglot.dialects.teradata.Teradata.Parser", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Parser", "kind": "class", "doc": "<p>Parser consumes a list of tokens produced by the Tokenizer and produces a parsed syntax tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>error_level:</strong> The desired error level.\nDefault: ErrorLevel.IMMEDIATE</li>\n<li><strong>error_message_context:</strong> The amount of context to capture from a query string when displaying\nthe error message (in number of characters).\nDefault: 100</li>\n<li><strong>max_errors:</strong> Maximum number of error messages to include in a raised ParseError.\nThis is only relevant if error_level is ErrorLevel.RAISE.\nDefault: 3</li>\n</ul>\n", "bases": "sqlglot.parser.Parser"}, "sqlglot.dialects.teradata.Teradata.Parser.TABLESAMPLE_CSV": {"fullname": "sqlglot.dialects.teradata.Teradata.Parser.TABLESAMPLE_CSV", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Parser.TABLESAMPLE_CSV", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.teradata.Teradata.Parser.VALUES_FOLLOWED_BY_PAREN": {"fullname": "sqlglot.dialects.teradata.Teradata.Parser.VALUES_FOLLOWED_BY_PAREN", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Parser.VALUES_FOLLOWED_BY_PAREN", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.teradata.Teradata.Parser.CHARSET_TRANSLATORS": {"fullname": "sqlglot.dialects.teradata.Teradata.Parser.CHARSET_TRANSLATORS", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Parser.CHARSET_TRANSLATORS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'UNICODE_TO_UNICODE_FoldSpace', 'UNICODE_TO_UNICODE_Fullwidth', 'KANJI1_KanjiEBCDIC_TO_UNICODE', 'KANJI1_KanjiEUC_TO_UNICODE', 'UNICODE_TO_LOCALE', 'UNICODE_TO_UNICODE_NFKC', 'UNICODE_TO_KANJISJIS', 'KANJISJIS_TO_LATIN', 'GRAPHIC_TO_KANJISJIS', 'KANJISJIS_TO_GRAPHIC', 'UNICODE_TO_KANJI1_KanjiEUC', 'UNICODE_TO_KANJI1_KANJISJIS', 'KANJI1_KANJISJIS_TO_UNICODE', 'GRAPHIC_TO_UNICODE_PadSpace', 'UNICODE_TO_GRAPHIC_PadGraphic', 'UNICODE_TO_GRAPHIC_VarGraphic', 'KANJISJIS_TO_UNICODE', 'LATIN_TO_UNICODE', 'LATIN_TO_GRAPHIC', 'GRAPHIC_TO_UNICODE', 'KANJI1_SBC_TO_UNICODE', 'UNICODE_TO_UNICODE_NFD', 'UNICODE_TO_UNICODE_Halfwidth', 'UNICODE_TO_UNICODE_NFKD', 'UNICODE_TO_KANJI1_KanjiEBCDIC', 'LOCALE_TO_UNICODE', 'LATIN_TO_KANJISJIS', 'UNICODE_TO_GRAPHIC', 'GRAPHIC_TO_LATIN', 'UNICODE_TO_UNICODE_NFC', 'UNICODE_TO_KANJI1_SBC', 'UNICODE_TO_LATIN'}"}, "sqlglot.dialects.teradata.Teradata.Parser.FUNC_TOKENS": {"fullname": "sqlglot.dialects.teradata.Teradata.Parser.FUNC_TOKENS", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Parser.FUNC_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.MONEY: 'MONEY'>, <TokenType.PRIMARY_KEY: 'PRIMARY_KEY'>, <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, <TokenType.IDENTIFIER: 'IDENTIFIER'>, <TokenType.VARBINARY: 'VARBINARY'>, <TokenType.HSTORE: 'HSTORE'>, <TokenType.IPADDRESS: 'IPADDRESS'>, <TokenType.ISNULL: 'ISNULL'>, <TokenType.NUMRANGE: 'NUMRANGE'>, <TokenType.DATE32: 'DATE32'>, <TokenType.INT8RANGE: 'INT8RANGE'>, <TokenType.AGGREGATEFUNCTION: 'AGGREGATEFUNCTION'>, <TokenType.VARCHAR: 'VARCHAR'>, <TokenType.TIMETZ: 'TIMETZ'>, <TokenType.GEOMETRY: 'GEOMETRY'>, <TokenType.ENUM8: 'ENUM8'>, <TokenType.INDEX: 'INDEX'>, <TokenType.UINT256: 'UINT256'>, <TokenType.BIGINT: 'BIGINT'>, <TokenType.INT128: 'INT128'>, <TokenType.SMALLMONEY: 'SMALLMONEY'>, <TokenType.HLLSKETCH: 'HLLSKETCH'>, <TokenType.RLIKE: 'RLIKE'>, <TokenType.SMALLINT: 'SMALLINT'>, <TokenType.INT256: 'INT256'>, <TokenType.GLOB: 'GLOB'>, <TokenType.FLOAT: 'FLOAT'>, <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, <TokenType.UNNEST: 'UNNEST'>, <TokenType.EXISTS: 'EXISTS'>, <TokenType.NULL: 'NULL'>, <TokenType.XOR: 'XOR'>, <TokenType.NULLABLE: 'NULLABLE'>, <TokenType.TINYTEXT: 'TINYTEXT'>, <TokenType.DATE: 'DATE'>, <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <TokenType.MERGE: 'MERGE'>, <TokenType.FIRST: 'FIRST'>, <TokenType.BINARY: 'BINARY'>, <TokenType.ARRAY: 'ARRAY'>, <TokenType.SERIAL: 'SERIAL'>, <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, <TokenType.INTERVAL: 'INTERVAL'>, <TokenType.WINDOW: 'WINDOW'>, <TokenType.RIGHT: 'RIGHT'>, <TokenType.BPCHAR: 'BPCHAR'>, <TokenType.BIT: 'BIT'>, <TokenType.UINT: 'UINT'>, <TokenType.ILIKE: 'ILIKE'>, <TokenType.UUID: 'UUID'>, <TokenType.STRUCT: 'STRUCT'>, <TokenType.LEFT: 'LEFT'>, <TokenType.SUPER: 'SUPER'>, <TokenType.IMAGE: 'IMAGE'>, <TokenType.UBIGINT: 'UBIGINT'>, <TokenType.LONGBLOB: 'LONGBLOB'>, <TokenType.VAR: 'VAR'>, <TokenType.COMMAND: 'COMMAND'>, <TokenType.TRUNCATE: 'TRUNCATE'>, <TokenType.UMEDIUMINT: 'UMEDIUMINT'>, <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, <TokenType.UINT128: 'UINT128'>, <TokenType.MAP: 'MAP'>, <TokenType.IPV4: 'IPV4'>, <TokenType.USERDEFINED: 'USERDEFINED'>, <TokenType.RANGE: 'RANGE'>, <TokenType.NVARCHAR: 'NVARCHAR'>, <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, <TokenType.TIMESTAMP_MS: 'TIMESTAMP_MS'>, <TokenType.VARIANT: 'VARIANT'>, <TokenType.ENUM: 'ENUM'>, <TokenType.USMALLINT: 'USMALLINT'>, <TokenType.TIMESTAMP_S: 'TIMESTAMP_S'>, <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, <TokenType.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>, <TokenType.TEXT: 'TEXT'>, <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, <TokenType.PSEUDO_TYPE: 'PSEUDO_TYPE'>, <TokenType.FIXEDSTRING: 'FIXEDSTRING'>, <TokenType.INT: 'INT'>, <TokenType.BIGSERIAL: 'BIGSERIAL'>, <TokenType.BOOLEAN: 'BOOLEAN'>, <TokenType.UNKNOWN: 'UNKNOWN'>, <TokenType.TSTZRANGE: 'TSTZRANGE'>, <TokenType.DATETIME64: 'DATETIME64'>, <TokenType.DATETIME: 'DATETIME'>, <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, <TokenType.MEDIUMINT: 'MEDIUMINT'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>, <TokenType.LIKE: 'LIKE'>, <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, <TokenType.XML: 'XML'>, <TokenType.JSON: 'JSON'>, <TokenType.UTINYINT: 'UTINYINT'>, <TokenType.TIME: 'TIME'>, <TokenType.UDECIMAL: 'UDECIMAL'>, <TokenType.NESTED: 'NESTED'>, <TokenType.ROWVERSION: 'ROWVERSION'>, <TokenType.OFFSET: 'OFFSET'>, <TokenType.INSERT: 'INSERT'>, <TokenType.TIMESTAMP_NS: 'TIMESTAMP_NS'>, <TokenType.ANY: 'ANY'>, <TokenType.INET: 'INET'>, <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, <TokenType.CURRENT_USER: 'CURRENT_USER'>, <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>, <TokenType.ALL: 'ALL'>, <TokenType.NAME: 'NAME'>, <TokenType.SOME: 'SOME'>, <TokenType.ENUM16: 'ENUM16'>, <TokenType.YEAR: 'YEAR'>, <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, <TokenType.DOUBLE: 'DOUBLE'>, <TokenType.INT4RANGE: 'INT4RANGE'>, <TokenType.FORMAT: 'FORMAT'>, <TokenType.IPPREFIX: 'IPPREFIX'>, <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>, <TokenType.COLLATE: 'COLLATE'>, <TokenType.FILTER: 'FILTER'>, <TokenType.JSONB: 'JSONB'>, <TokenType.TDIGEST: 'TDIGEST'>, <TokenType.CHAR: 'CHAR'>, <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.ROW: 'ROW'>, <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.TABLE: 'TABLE'>, <TokenType.DATERANGE: 'DATERANGE'>, <TokenType.TSRANGE: 'TSRANGE'>, <TokenType.DECIMAL: 'DECIMAL'>, <TokenType.NCHAR: 'NCHAR'>, <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, <TokenType.SEQUENCE: 'SEQUENCE'>, <TokenType.LONGTEXT: 'LONGTEXT'>, <TokenType.IPV6: 'IPV6'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, <TokenType.TINYINT: 'TINYINT'>, <TokenType.TINYBLOB: 'TINYBLOB'>}"}, "sqlglot.dialects.teradata.Teradata.Parser.STATEMENT_PARSERS": {"fullname": "sqlglot.dialects.teradata.Teradata.Parser.STATEMENT_PARSERS", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Parser.STATEMENT_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.ALTER: 'ALTER'>: <function Parser.<lambda>>, <TokenType.BEGIN: 'BEGIN'>: <function Parser.<lambda>>, <TokenType.CACHE: 'CACHE'>: <function Parser.<lambda>>, <TokenType.COMMENT: 'COMMENT'>: <function Parser.<lambda>>, <TokenType.COMMIT: 'COMMIT'>: <function Parser.<lambda>>, <TokenType.COPY: 'COPY'>: <function Parser.<lambda>>, <TokenType.CREATE: 'CREATE'>: <function Parser.<lambda>>, <TokenType.DELETE: 'DELETE'>: <function Parser.<lambda>>, <TokenType.DESC: 'DESC'>: <function Parser.<lambda>>, <TokenType.DESCRIBE: 'DESCRIBE'>: <function Parser.<lambda>>, <TokenType.DROP: 'DROP'>: <function Parser.<lambda>>, <TokenType.INSERT: 'INSERT'>: <function Parser.<lambda>>, <TokenType.KILL: 'KILL'>: <function Parser.<lambda>>, <TokenType.LOAD: 'LOAD'>: <function Parser.<lambda>>, <TokenType.MERGE: 'MERGE'>: <function Parser.<lambda>>, <TokenType.PIVOT: 'PIVOT'>: <function Parser.<lambda>>, <TokenType.PRAGMA: 'PRAGMA'>: <function Parser.<lambda>>, <TokenType.REFRESH: 'REFRESH'>: <function Parser.<lambda>>, <TokenType.ROLLBACK: 'ROLLBACK'>: <function Parser.<lambda>>, <TokenType.SET: 'SET'>: <function Parser.<lambda>>, <TokenType.TRUNCATE: 'TRUNCATE'>: <function Parser.<lambda>>, <TokenType.UNCACHE: 'UNCACHE'>: <function Parser.<lambda>>, <TokenType.UPDATE: 'UPDATE'>: <function Parser.<lambda>>, <TokenType.USE: 'USE'>: <function Parser.<lambda>>, <TokenType.SEMICOLON: 'SEMICOLON'>: <function Parser.<lambda>>, <TokenType.DATABASE: 'DATABASE'>: <function Teradata.Parser.<lambda>>, <TokenType.REPLACE: 'REPLACE'>: <function Teradata.Parser.<lambda>>}"}, "sqlglot.dialects.teradata.Teradata.Parser.FUNCTION_PARSERS": {"fullname": "sqlglot.dialects.teradata.Teradata.Parser.FUNCTION_PARSERS", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Parser.FUNCTION_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'CAST': <function Parser.<lambda>>, 'CONVERT': <function Parser.<lambda>>, 'DECODE': <function Parser.<lambda>>, 'EXTRACT': <function Parser.<lambda>>, 'JSON_OBJECT': <function Parser.<lambda>>, 'JSON_OBJECTAGG': <function Parser.<lambda>>, 'JSON_TABLE': <function Parser.<lambda>>, 'MATCH': <function Parser.<lambda>>, 'OPENJSON': <function Parser.<lambda>>, 'POSITION': <function Parser.<lambda>>, 'PREDICT': <function Parser.<lambda>>, 'SAFE_CAST': <function Parser.<lambda>>, 'STRING_AGG': <function Parser.<lambda>>, 'SUBSTRING': <function Parser.<lambda>>, 'TRIM': <function Parser.<lambda>>, 'TRY_CAST': <function Parser.<lambda>>, 'TRY_CONVERT': <function Parser.<lambda>>, 'TRYCAST': <function Parser.<lambda>>, 'RANGE_N': <function Teradata.Parser.<lambda>>, 'TRANSLATE': <function Teradata.Parser.<lambda>>}"}, "sqlglot.dialects.teradata.Teradata.Parser.EXPONENT": {"fullname": "sqlglot.dialects.teradata.Teradata.Parser.EXPONENT", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Parser.EXPONENT", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.DSTAR: 'DSTAR'>: <class 'sqlglot.expressions.Pow'>}"}, "sqlglot.dialects.teradata.Teradata.Parser.TABLE_ALIAS_TOKENS": {"fullname": "sqlglot.dialects.teradata.Teradata.Parser.TABLE_ALIAS_TOKENS", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Parser.TABLE_ALIAS_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.KILL: 'KILL'>, <TokenType.MONEY: 'MONEY'>, <TokenType.COPY: 'COPY'>, <TokenType.PERCENT: 'PERCENT'>, <TokenType.TAG: 'TAG'>, <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, <TokenType.VOLATILE: 'VOLATILE'>, <TokenType.IDENTIFIER: 'IDENTIFIER'>, <TokenType.VARBINARY: 'VARBINARY'>, <TokenType.HSTORE: 'HSTORE'>, <TokenType.ASC: 'ASC'>, <TokenType.IPADDRESS: 'IPADDRESS'>, <TokenType.ISNULL: 'ISNULL'>, <TokenType.TEMPORARY: 'TEMPORARY'>, <TokenType.PROCEDURE: 'PROCEDURE'>, <TokenType.SCHEMA: 'SCHEMA'>, <TokenType.NUMRANGE: 'NUMRANGE'>, <TokenType.DATE32: 'DATE32'>, <TokenType.INT8RANGE: 'INT8RANGE'>, <TokenType.ANTI: 'ANTI'>, <TokenType.AGGREGATEFUNCTION: 'AGGREGATEFUNCTION'>, <TokenType.VIEW: 'VIEW'>, <TokenType.VARCHAR: 'VARCHAR'>, <TokenType.TIMETZ: 'TIMETZ'>, <TokenType.GEOMETRY: 'GEOMETRY'>, <TokenType.BEGIN: 'BEGIN'>, <TokenType.ENUM8: 'ENUM8'>, <TokenType.INDEX: 'INDEX'>, <TokenType.PARTITION: 'PARTITION'>, <TokenType.UINT256: 'UINT256'>, <TokenType.BIGINT: 'BIGINT'>, <TokenType.CACHE: 'CACHE'>, <TokenType.OPERATOR: 'OPERATOR'>, <TokenType.COLUMN: 'COLUMN'>, <TokenType.INT128: 'INT128'>, <TokenType.SMALLMONEY: 'SMALLMONEY'>, <TokenType.HLLSKETCH: 'HLLSKETCH'>, <TokenType.UNPIVOT: 'UNPIVOT'>, <TokenType.SMALLINT: 'SMALLINT'>, <TokenType.INT256: 'INT256'>, <TokenType.FLOAT: 'FLOAT'>, <TokenType.COMMIT: 'COMMIT'>, <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, <TokenType.EXISTS: 'EXISTS'>, <TokenType.NULL: 'NULL'>, <TokenType.RECURSIVE: 'RECURSIVE'>, <TokenType.SET: 'SET'>, <TokenType.NULLABLE: 'NULLABLE'>, <TokenType.REFRESH: 'REFRESH'>, <TokenType.TINYTEXT: 'TINYTEXT'>, <TokenType.SHOW: 'SHOW'>, <TokenType.DEFAULT: 'DEFAULT'>, <TokenType.DATE: 'DATE'>, <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <TokenType.MERGE: 'MERGE'>, <TokenType.FIRST: 'FIRST'>, <TokenType.BINARY: 'BINARY'>, <TokenType.ARRAY: 'ARRAY'>, <TokenType.SERIAL: 'SERIAL'>, <TokenType.EXECUTE: 'EXECUTE'>, <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, <TokenType.INTERVAL: 'INTERVAL'>, <TokenType.PRAGMA: 'PRAGMA'>, <TokenType.STORAGE_INTEGRATION: 'STORAGE_INTEGRATION'>, <TokenType.BPCHAR: 'BPCHAR'>, <TokenType.BIT: 'BIT'>, <TokenType.UINT: 'UINT'>, <TokenType.UUID: 'UUID'>, <TokenType.STRUCT: 'STRUCT'>, <TokenType.FALSE: 'FALSE'>, <TokenType.FUNCTION: 'FUNCTION'>, <TokenType.TOP: 'TOP'>, <TokenType.SUPER: 'SUPER'>, <TokenType.CASE: 'CASE'>, <TokenType.IMAGE: 'IMAGE'>, <TokenType.UBIGINT: 'UBIGINT'>, <TokenType.LONGBLOB: 'LONGBLOB'>, <TokenType.ROLLUP: 'ROLLUP'>, <TokenType.VAR: 'VAR'>, <TokenType.COMMAND: 'COMMAND'>, <TokenType.LOAD: 'LOAD'>, <TokenType.TRUNCATE: 'TRUNCATE'>, <TokenType.KEEP: 'KEEP'>, <TokenType.UMEDIUMINT: 'UMEDIUMINT'>, <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, <TokenType.UINT128: 'UINT128'>, <TokenType.END: 'END'>, <TokenType.MAP: 'MAP'>, <TokenType.IPV4: 'IPV4'>, <TokenType.USERDEFINED: 'USERDEFINED'>, <TokenType.REFERENCES: 'REFERENCES'>, <TokenType.REPLACE: 'REPLACE'>, <TokenType.RANGE: 'RANGE'>, <TokenType.NVARCHAR: 'NVARCHAR'>, <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, <TokenType.TRUE: 'TRUE'>, <TokenType.TIMESTAMP_MS: 'TIMESTAMP_MS'>, <TokenType.VARIANT: 'VARIANT'>, <TokenType.ENUM: 'ENUM'>, <TokenType.USE: 'USE'>, <TokenType.USMALLINT: 'USMALLINT'>, <TokenType.OVERLAPS: 'OVERLAPS'>, <TokenType.TIMESTAMP_S: 'TIMESTAMP_S'>, <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, <TokenType.UNIQUE: 'UNIQUE'>, <TokenType.ORDINALITY: 'ORDINALITY'>, <TokenType.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>, <TokenType.TEXT: 'TEXT'>, <TokenType.DATABASE: 'DATABASE'>, <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, <TokenType.PSEUDO_TYPE: 'PSEUDO_TYPE'>, <TokenType.FIXEDSTRING: 'FIXEDSTRING'>, <TokenType.NEXT: 'NEXT'>, <TokenType.INT: 'INT'>, <TokenType.BIGSERIAL: 'BIGSERIAL'>, <TokenType.BOOLEAN: 'BOOLEAN'>, <TokenType.IS: 'IS'>, <TokenType.CONSTRAINT: 'CONSTRAINT'>, <TokenType.FINAL: 'FINAL'>, <TokenType.UNKNOWN: 'UNKNOWN'>, <TokenType.SETTINGS: 'SETTINGS'>, <TokenType.ROWS: 'ROWS'>, <TokenType.TSTZRANGE: 'TSTZRANGE'>, <TokenType.DATETIME64: 'DATETIME64'>, <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, <TokenType.DATETIME: 'DATETIME'>, <TokenType.MEDIUMINT: 'MEDIUMINT'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>, <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, <TokenType.XML: 'XML'>, <TokenType.JSON: 'JSON'>, <TokenType.UTINYINT: 'UTINYINT'>, <TokenType.DELETE: 'DELETE'>, <TokenType.TIME: 'TIME'>, <TokenType.UDECIMAL: 'UDECIMAL'>, <TokenType.NESTED: 'NESTED'>, <TokenType.SEMI: 'SEMI'>, <TokenType.DESC: 'DESC'>, <TokenType.ROWVERSION: 'ROWVERSION'>, <TokenType.TIMESTAMP_NS: 'TIMESTAMP_NS'>, <TokenType.ANY: 'ANY'>, <TokenType.DIV: 'DIV'>, <TokenType.DICTIONARY: 'DICTIONARY'>, <TokenType.INET: 'INET'>, <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, <TokenType.COMMENT: 'COMMENT'>, <TokenType.CURRENT_USER: 'CURRENT_USER'>, <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>, <TokenType.ALL: 'ALL'>, <TokenType.NAME: 'NAME'>, <TokenType.SOME: 'SOME'>, <TokenType.ENUM16: 'ENUM16'>, <TokenType.YEAR: 'YEAR'>, <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, <TokenType.DOUBLE: 'DOUBLE'>, <TokenType.INT4RANGE: 'INT4RANGE'>, <TokenType.FORMAT: 'FORMAT'>, <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, <TokenType.IPPREFIX: 'IPPREFIX'>, <TokenType.OVERWRITE: 'OVERWRITE'>, <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>, <TokenType.COLLATE: 'COLLATE'>, <TokenType.FILTER: 'FILTER'>, <TokenType.JSONB: 'JSONB'>, <TokenType.TDIGEST: 'TDIGEST'>, <TokenType.CHAR: 'CHAR'>, <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.ROW: 'ROW'>, <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.TABLE: 'TABLE'>, <TokenType.DATERANGE: 'DATERANGE'>, <TokenType.TSRANGE: 'TSRANGE'>, <TokenType.ESCAPE: 'ESCAPE'>, <TokenType.PIVOT: 'PIVOT'>, <TokenType.DECIMAL: 'DECIMAL'>, <TokenType.NCHAR: 'NCHAR'>, <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, <TokenType.UPDATE: 'UPDATE'>, <TokenType.MODEL: 'MODEL'>, <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, <TokenType.SEQUENCE: 'SEQUENCE'>, <TokenType.LONGTEXT: 'LONGTEXT'>, <TokenType.DESCRIBE: 'DESCRIBE'>, <TokenType.IPV6: 'IPV6'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, <TokenType.TINYINT: 'TINYINT'>, <TokenType.TINYBLOB: 'TINYBLOB'>}"}, "sqlglot.dialects.teradata.Teradata.Parser.SHOW_TRIE": {"fullname": "sqlglot.dialects.teradata.Teradata.Parser.SHOW_TRIE", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Parser.SHOW_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.teradata.Teradata.Parser.SET_TRIE": {"fullname": "sqlglot.dialects.teradata.Teradata.Parser.SET_TRIE", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Parser.SET_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'GLOBAL': {0: True}, 'LOCAL': {0: True}, 'SESSION': {0: True}, 'TRANSACTION': {0: True}}"}, "sqlglot.dialects.teradata.Teradata.Generator": {"fullname": "sqlglot.dialects.teradata.Teradata.Generator", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Generator", "kind": "class", "doc": "<p>Generator converts a given syntax tree to the corresponding SQL string.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>pretty:</strong> Whether to format the produced SQL string.\nDefault: False.</li>\n<li><strong>identify:</strong> Determines when an identifier should be quoted. Possible values are:\nFalse (default): Never quote, except in cases where it's mandatory by the dialect.\nTrue or 'always': Always quote.\n'safe': Only quote identifiers that are case insensitive.</li>\n<li><strong>normalize:</strong> Whether to normalize identifiers to lowercase.\nDefault: False.</li>\n<li><strong>pad:</strong> The pad size in a formatted string. For example, this affects the indentation of\na projection in a query, relative to its nesting level.\nDefault: 2.</li>\n<li><strong>indent:</strong> The indentation size in a formatted string. For example, this affects the\nindentation of subqueries and filters under a <code>WHERE</code> clause.\nDefault: 2.</li>\n<li><strong>normalize_functions:</strong> How to normalize function names. Possible values are:\n\"upper\" or True (default): Convert names to uppercase.\n\"lower\": Convert names to lowercase.\nFalse: Disables function name normalization.</li>\n<li><strong>unsupported_level:</strong> Determines the generator's behavior when it encounters unsupported expressions.\nDefault ErrorLevel.WARN.</li>\n<li><strong>max_unsupported:</strong> Maximum number of unsupported messages to include in a raised UnsupportedError.\nThis is only relevant if unsupported_level is ErrorLevel.RAISE.\nDefault: 3</li>\n<li><strong>leading_comma:</strong> Whether the comma is leading or trailing in select expressions.\nThis is only relevant when generating in pretty mode.\nDefault: False</li>\n<li><strong>max_text_width:</strong> The max number of characters in a segment before creating new lines in pretty mode.\nThe default is on the smaller end because the length only represents a segment and not the true\nline length.\nDefault: 80</li>\n<li><strong>comments:</strong> Whether to preserve comments in the output SQL code.\nDefault: True</li>\n</ul>\n", "bases": "sqlglot.generator.Generator"}, "sqlglot.dialects.teradata.Teradata.Generator.LIMIT_IS_TOP": {"fullname": "sqlglot.dialects.teradata.Teradata.Generator.LIMIT_IS_TOP", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Generator.LIMIT_IS_TOP", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.teradata.Teradata.Generator.JOIN_HINTS": {"fullname": "sqlglot.dialects.teradata.Teradata.Generator.JOIN_HINTS", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Generator.JOIN_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.teradata.Teradata.Generator.TABLE_HINTS": {"fullname": "sqlglot.dialects.teradata.Teradata.Generator.TABLE_HINTS", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Generator.TABLE_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.teradata.Teradata.Generator.QUERY_HINTS": {"fullname": "sqlglot.dialects.teradata.Teradata.Generator.QUERY_HINTS", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Generator.QUERY_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.teradata.Teradata.Generator.TABLESAMPLE_KEYWORDS": {"fullname": "sqlglot.dialects.teradata.Teradata.Generator.TABLESAMPLE_KEYWORDS", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Generator.TABLESAMPLE_KEYWORDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "'SAMPLE'"}, "sqlglot.dialects.teradata.Teradata.Generator.LAST_DAY_SUPPORTS_DATE_PART": {"fullname": "sqlglot.dialects.teradata.Teradata.Generator.LAST_DAY_SUPPORTS_DATE_PART", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Generator.LAST_DAY_SUPPORTS_DATE_PART", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.teradata.Teradata.Generator.CAN_IMPLEMENT_ARRAY_ANY": {"fullname": "sqlglot.dialects.teradata.Teradata.Generator.CAN_IMPLEMENT_ARRAY_ANY", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Generator.CAN_IMPLEMENT_ARRAY_ANY", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.teradata.Teradata.Generator.TYPE_MAPPING": {"fullname": "sqlglot.dialects.teradata.Teradata.Generator.TYPE_MAPPING", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Generator.TYPE_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.NCHAR: 'NCHAR'>: 'CHAR', <Type.NVARCHAR: 'NVARCHAR'>: 'VARCHAR', <Type.MEDIUMTEXT: 'MEDIUMTEXT'>: 'TEXT', <Type.LONGTEXT: 'LONGTEXT'>: 'TEXT', <Type.TINYTEXT: 'TINYTEXT'>: 'TEXT', <Type.MEDIUMBLOB: 'MEDIUMBLOB'>: 'BLOB', <Type.LONGBLOB: 'LONGBLOB'>: 'BLOB', <Type.TINYBLOB: 'TINYBLOB'>: 'BLOB', <Type.INET: 'INET'>: 'INET', <Type.ROWVERSION: 'ROWVERSION'>: 'VARBINARY', <Type.GEOMETRY: 'GEOMETRY'>: 'ST_GEOMETRY', <Type.DOUBLE: 'DOUBLE'>: 'DOUBLE PRECISION'}"}, "sqlglot.dialects.teradata.Teradata.Generator.PROPERTIES_LOCATION": {"fullname": "sqlglot.dialects.teradata.Teradata.Generator.PROPERTIES_LOCATION", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Generator.PROPERTIES_LOCATION", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.AllowedValuesProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.AlgorithmProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.AutoIncrementProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.BackupProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.BlockCompressionProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.CharacterSetProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ChecksumProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.CollateProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Cluster'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ClusteredByProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DataBlocksizeProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.DataDeletionProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DefinerProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.DictRange'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DictProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DistKeyProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DistStyleProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.EngineProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ExternalProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.FallbackProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.FileFormatProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.FreespaceProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.GlobalProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.HeapProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.InheritsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.IcebergProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.InputModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.IsolatedLoadingProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.JournalProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.LanguageProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LikeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LocationProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LockProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LockingProperty'>: <Location.POST_ALIAS: 'POST_ALIAS'>, <class 'sqlglot.expressions.LogProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.MaterializedProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.MergeBlockRatioProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.OnProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.OnCommitProperty'>: <Location.POST_INDEX: 'POST_INDEX'>, <class 'sqlglot.expressions.Order'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.OutputModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.PartitionedByProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.PartitionedOfProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.PrimaryKey'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Property'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ReturnsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatDelimitedProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatSerdeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SampleProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SchemaCommentProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SerdeProperties'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Set'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SettingsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SetProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.SetConfigProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SharingProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.SequenceProperties'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.SortKeyProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SqlReadWriteProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SqlSecurityProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.StabilityProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.StrictProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.TemporaryProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.ToTableProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.TransientProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.TransformModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.MergeTreeTTL'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.UnloggedProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.VolatileProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.WithDataProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.WithSystemVersioningProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>}"}, "sqlglot.dialects.teradata.Teradata.Generator.TRANSFORMS": {"fullname": "sqlglot.dialects.teradata.Teradata.Generator.TRANSFORMS", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Generator.TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.JSONPathFilter'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathKey'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRecursive'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRoot'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathScript'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSelector'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSlice'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSubscript'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathUnion'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathWildcard'>: <function <lambda>>, <class 'sqlglot.expressions.AllowedValuesProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.BackupProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CaseSpecificColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CollateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CommentColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DateFormatColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DefaultColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EncodeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EphemeralColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExcludeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExternalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.GlobalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.HeapProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IcebergProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InheritsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InlineLengthColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IntervalSpan'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtract'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtractScalar'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LanguageProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LocationProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LogProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.MaterializedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NonClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NotForReplicationColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnCommitProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnUpdateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OutputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.PathColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ReturnsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SampleProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetConfigProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SettingsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SharingProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlReadWriteProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlSecurityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StabilityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StrictProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TemporaryProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TitleColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.Timestamp'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransformModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransientProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UppercaseColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UnloggedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VarMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VolatileProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithOperator'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ArgMax'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ArgMin'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ArraySize'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.Max'>: <function max_or_greatest>, <class 'sqlglot.expressions.Min'>: <function min_or_least>, <class 'sqlglot.expressions.Pow'>: <function Teradata.Generator.<lambda>>, <class 'sqlglot.expressions.Select'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.StrToDate'>: <function Teradata.Generator.<lambda>>, <class 'sqlglot.expressions.ToChar'>: <function Teradata.Generator.<lambda>>, <class 'sqlglot.expressions.ToNumber'>: <function to_number_with_nls_param>, <class 'sqlglot.expressions.Use'>: <function Teradata.Generator.<lambda>>, <class 'sqlglot.expressions.CurrentTimestamp'>: <function Teradata.Generator.<lambda>>, <class 'sqlglot.expressions.DateAdd'>: <function _date_add_sql.<locals>.func>, <class 'sqlglot.expressions.DateSub'>: <function _date_add_sql.<locals>.func>, <class 'sqlglot.expressions.Quarter'>: <function Teradata.Generator.<lambda>>}"}, "sqlglot.dialects.teradata.Teradata.Generator.cast_sql": {"fullname": "sqlglot.dialects.teradata.Teradata.Generator.cast_sql", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Generator.cast_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Cast</span>,</span><span class=\"param\">\t<span class=\"n\">safe_prefix</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.teradata.Teradata.Generator.trycast_sql": {"fullname": "sqlglot.dialects.teradata.Teradata.Generator.trycast_sql", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Generator.trycast_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TryCast</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.teradata.Teradata.Generator.tablesample_sql": {"fullname": "sqlglot.dialects.teradata.Teradata.Generator.tablesample_sql", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Generator.tablesample_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TableSample</span>,</span><span class=\"param\">\t<span class=\"n\">sep</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">' AS '</span>,</span><span class=\"param\">\t<span class=\"n\">tablesample_keyword</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.teradata.Teradata.Generator.partitionedbyproperty_sql": {"fullname": "sqlglot.dialects.teradata.Teradata.Generator.partitionedbyproperty_sql", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Generator.partitionedbyproperty_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">PartitionedByProperty</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.teradata.Teradata.Generator.update_sql": {"fullname": "sqlglot.dialects.teradata.Teradata.Generator.update_sql", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Generator.update_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Update</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.teradata.Teradata.Generator.mod_sql": {"fullname": "sqlglot.dialects.teradata.Teradata.Generator.mod_sql", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Generator.mod_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Mod</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.teradata.Teradata.Generator.datatype_sql": {"fullname": "sqlglot.dialects.teradata.Teradata.Generator.datatype_sql", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Generator.datatype_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.teradata.Teradata.Generator.rangen_sql": {"fullname": "sqlglot.dialects.teradata.Teradata.Generator.rangen_sql", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Generator.rangen_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">RangeN</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.teradata.Teradata.Generator.createable_sql": {"fullname": "sqlglot.dialects.teradata.Teradata.Generator.createable_sql", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Generator.createable_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Create</span>,</span><span class=\"param\">\t<span class=\"n\">locations</span><span class=\"p\">:</span> <span class=\"n\">DefaultDict</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.teradata.Teradata.Generator.extract_sql": {"fullname": "sqlglot.dialects.teradata.Teradata.Generator.extract_sql", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Generator.extract_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Extract</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.teradata.Teradata.Generator.interval_sql": {"fullname": "sqlglot.dialects.teradata.Teradata.Generator.interval_sql", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Generator.interval_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Interval</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.teradata.Teradata.Generator.SELECT_KINDS": {"fullname": "sqlglot.dialects.teradata.Teradata.Generator.SELECT_KINDS", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Generator.SELECT_KINDS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Tuple[str, ...]", "default_value": "()"}, "sqlglot.dialects.teradata.Teradata.Generator.TRY_SUPPORTED": {"fullname": "sqlglot.dialects.teradata.Teradata.Generator.TRY_SUPPORTED", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Generator.TRY_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.teradata.Teradata.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS": {"fullname": "sqlglot.dialects.teradata.Teradata.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'qualify': <function Generator.<lambda>>, 'windows': <function Generator.<lambda>>}"}, "sqlglot.dialects.teradata.Teradata.tokenizer_class": {"fullname": "sqlglot.dialects.teradata.Teradata.tokenizer_class", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.tokenizer_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.teradata.Teradata.Tokenizer'>"}, "sqlglot.dialects.teradata.Teradata.parser_class": {"fullname": "sqlglot.dialects.teradata.Teradata.parser_class", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.parser_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.teradata.Teradata.Parser'>"}, "sqlglot.dialects.teradata.Teradata.generator_class": {"fullname": "sqlglot.dialects.teradata.Teradata.generator_class", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.generator_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.teradata.Teradata.Generator'>"}, "sqlglot.dialects.teradata.Teradata.TIME_TRIE": {"fullname": "sqlglot.dialects.teradata.Teradata.TIME_TRIE", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'Y': {'Y': {0: True, 'Y': {'Y': {0: True}}}, '4': {0: True}}, 'M': {'4': {0: True}, '3': {0: True}, 0: True, 'I': {0: True}, 'M': {0: True, 'M': {0: True, 'M': {0: True}}}}, 'D': {0: True, 'D': {0: True, 'D': {0: True}}, '3': {0: True}}, 'H': {0: True, 'H': {0: True, '2': {'4': {0: True}}}}, 'S': {0: True, 'S': {0: True, 'S': {'S': {'S': {'S': {0: True}}}}}}, 'E': {0: True, 'E': {0: True, 'E': {0: True, 'E': {0: True}}}, '3': {0: True}, '4': {0: True}}}"}, "sqlglot.dialects.teradata.Teradata.FORMAT_TRIE": {"fullname": "sqlglot.dialects.teradata.Teradata.FORMAT_TRIE", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.FORMAT_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'Y': {'Y': {0: True, 'Y': {'Y': {0: True}}}, '4': {0: True}}, 'M': {'4': {0: True}, '3': {0: True}, 0: True, 'I': {0: True}, 'M': {0: True, 'M': {0: True, 'M': {0: True}}}}, 'D': {0: True, 'D': {0: True, 'D': {0: True}}, '3': {0: True}}, 'H': {0: True, 'H': {0: True, '2': {'4': {0: True}}}}, 'S': {0: True, 'S': {0: True, 'S': {'S': {'S': {'S': {0: True}}}}}}, 'E': {0: True, 'E': {0: True, 'E': {0: True, 'E': {0: True}}}, '3': {0: True}, '4': {0: True}}}"}, "sqlglot.dialects.teradata.Teradata.INVERSE_TIME_MAPPING": {"fullname": "sqlglot.dialects.teradata.Teradata.INVERSE_TIME_MAPPING", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.INVERSE_TIME_MAPPING", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'%y': 'YY', '%Y': 'YYYY', '%B': 'MMMM', '%b': 'MMM', '%-M': 'M', '%M': 'MI', '%m': 'MM', '%-d': 'D', '%d': 'DD', '%j': 'DDD', '%-H': 'H', '%H': 'HH24', '%-S': 'S', '%S': 'SS', '%f': 'SSSSSS', '%a': 'EEE', '%A': 'EEEE'}"}, "sqlglot.dialects.teradata.Teradata.INVERSE_TIME_TRIE": {"fullname": "sqlglot.dialects.teradata.Teradata.INVERSE_TIME_TRIE", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.INVERSE_TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'%': {'y': {0: True}, 'Y': {0: True}, 'B': {0: True}, 'b': {0: True}, '-': {'M': {0: True}, 'd': {0: True}, 'H': {0: True}, 'S': {0: True}}, 'M': {0: True}, 'm': {0: True}, 'd': {0: True}, 'j': {0: True}, 'H': {0: True}, 'S': {0: True}, 'f': {0: True}, 'a': {0: True}, 'A': {0: True}}}"}, "sqlglot.dialects.teradata.Teradata.ESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.teradata.Teradata.ESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.ESCAPED_SEQUENCES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{}"}, "sqlglot.dialects.teradata.Teradata.QUOTE_START": {"fullname": "sqlglot.dialects.teradata.Teradata.QUOTE_START", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.QUOTE_START", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.teradata.Teradata.QUOTE_END": {"fullname": "sqlglot.dialects.teradata.Teradata.QUOTE_END", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.QUOTE_END", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.teradata.Teradata.IDENTIFIER_START": {"fullname": "sqlglot.dialects.teradata.Teradata.IDENTIFIER_START", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.IDENTIFIER_START", "kind": "variable", "doc": "<p></p>\n", "default_value": "'"'"}, "sqlglot.dialects.teradata.Teradata.IDENTIFIER_END": {"fullname": "sqlglot.dialects.teradata.Teradata.IDENTIFIER_END", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.IDENTIFIER_END", "kind": "variable", "doc": "<p></p>\n", "default_value": "'"'"}, "sqlglot.dialects.teradata.Teradata.BIT_START": {"fullname": "sqlglot.dialects.teradata.Teradata.BIT_START", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.BIT_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.teradata.Teradata.BIT_END": {"fullname": "sqlglot.dialects.teradata.Teradata.BIT_END", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.BIT_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.teradata.Teradata.HEX_START": {"fullname": "sqlglot.dialects.teradata.Teradata.HEX_START", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.HEX_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.teradata.Teradata.HEX_END": {"fullname": "sqlglot.dialects.teradata.Teradata.HEX_END", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.HEX_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.teradata.Teradata.BYTE_START": {"fullname": "sqlglot.dialects.teradata.Teradata.BYTE_START", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.BYTE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.teradata.Teradata.BYTE_END": {"fullname": "sqlglot.dialects.teradata.Teradata.BYTE_END", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.BYTE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.teradata.Teradata.UNICODE_START": {"fullname": "sqlglot.dialects.teradata.Teradata.UNICODE_START", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.UNICODE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.teradata.Teradata.UNICODE_END": {"fullname": "sqlglot.dialects.teradata.Teradata.UNICODE_END", "modulename": "sqlglot.dialects.teradata", "qualname": "Teradata.UNICODE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.trino": {"fullname": "sqlglot.dialects.trino", "modulename": "sqlglot.dialects.trino", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.dialects.trino.Trino": {"fullname": "sqlglot.dialects.trino.Trino", "modulename": "sqlglot.dialects.trino", "qualname": "Trino", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.presto.Presto"}, "sqlglot.dialects.trino.Trino.SUPPORTS_USER_DEFINED_TYPES": {"fullname": "sqlglot.dialects.trino.Trino.SUPPORTS_USER_DEFINED_TYPES", "modulename": "sqlglot.dialects.trino", "qualname": "Trino.SUPPORTS_USER_DEFINED_TYPES", "kind": "variable", "doc": "<p>Whether user-defined data types are supported.</p>\n", "default_value": "False"}, "sqlglot.dialects.trino.Trino.LOG_BASE_FIRST": {"fullname": "sqlglot.dialects.trino.Trino.LOG_BASE_FIRST", "modulename": "sqlglot.dialects.trino", "qualname": "Trino.LOG_BASE_FIRST", "kind": "variable", "doc": "<p>Whether the base comes first in the <code>LOG</code> function.\nPossible values: <code>True</code>, <code>False</code>, <code>None</code> (two arguments are not supported by <code>LOG</code>)</p>\n", "annotation": ": Optional[bool]", "default_value": "True"}, "sqlglot.dialects.trino.Trino.Parser": {"fullname": "sqlglot.dialects.trino.Trino.Parser", "modulename": "sqlglot.dialects.trino", "qualname": "Trino.Parser", "kind": "class", "doc": "<p>Parser consumes a list of tokens produced by the Tokenizer and produces a parsed syntax tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>error_level:</strong> The desired error level.\nDefault: ErrorLevel.IMMEDIATE</li>\n<li><strong>error_message_context:</strong> The amount of context to capture from a query string when displaying\nthe error message (in number of characters).\nDefault: 100</li>\n<li><strong>max_errors:</strong> Maximum number of error messages to include in a raised ParseError.\nThis is only relevant if error_level is ErrorLevel.RAISE.\nDefault: 3</li>\n</ul>\n", "bases": "sqlglot.dialects.presto.Presto.Parser"}, "sqlglot.dialects.trino.Trino.Parser.FUNCTION_PARSERS": {"fullname": "sqlglot.dialects.trino.Trino.Parser.FUNCTION_PARSERS", "modulename": "sqlglot.dialects.trino", "qualname": "Trino.Parser.FUNCTION_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'CAST': <function Parser.<lambda>>, 'CONVERT': <function Parser.<lambda>>, 'DECODE': <function Parser.<lambda>>, 'EXTRACT': <function Parser.<lambda>>, 'JSON_OBJECT': <function Parser.<lambda>>, 'JSON_OBJECTAGG': <function Parser.<lambda>>, 'JSON_TABLE': <function Parser.<lambda>>, 'MATCH': <function Parser.<lambda>>, 'OPENJSON': <function Parser.<lambda>>, 'POSITION': <function Parser.<lambda>>, 'PREDICT': <function Parser.<lambda>>, 'SAFE_CAST': <function Parser.<lambda>>, 'STRING_AGG': <function Parser.<lambda>>, 'SUBSTRING': <function Parser.<lambda>>, 'TRY_CAST': <function Parser.<lambda>>, 'TRY_CONVERT': <function Parser.<lambda>>, 'TRIM': <function Trino.Parser.<lambda>>}"}, "sqlglot.dialects.trino.Trino.Parser.TABLE_ALIAS_TOKENS": {"fullname": "sqlglot.dialects.trino.Trino.Parser.TABLE_ALIAS_TOKENS", "modulename": "sqlglot.dialects.trino", "qualname": "Trino.Parser.TABLE_ALIAS_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.KILL: 'KILL'>, <TokenType.MONEY: 'MONEY'>, <TokenType.COPY: 'COPY'>, <TokenType.PERCENT: 'PERCENT'>, <TokenType.TAG: 'TAG'>, <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, <TokenType.VOLATILE: 'VOLATILE'>, <TokenType.IDENTIFIER: 'IDENTIFIER'>, <TokenType.VARBINARY: 'VARBINARY'>, <TokenType.HSTORE: 'HSTORE'>, <TokenType.ASC: 'ASC'>, <TokenType.IPADDRESS: 'IPADDRESS'>, <TokenType.ISNULL: 'ISNULL'>, <TokenType.TEMPORARY: 'TEMPORARY'>, <TokenType.PROCEDURE: 'PROCEDURE'>, <TokenType.SCHEMA: 'SCHEMA'>, <TokenType.NUMRANGE: 'NUMRANGE'>, <TokenType.DATE32: 'DATE32'>, <TokenType.INT8RANGE: 'INT8RANGE'>, <TokenType.ANTI: 'ANTI'>, <TokenType.AGGREGATEFUNCTION: 'AGGREGATEFUNCTION'>, <TokenType.VIEW: 'VIEW'>, <TokenType.VARCHAR: 'VARCHAR'>, <TokenType.TIMETZ: 'TIMETZ'>, <TokenType.GEOMETRY: 'GEOMETRY'>, <TokenType.BEGIN: 'BEGIN'>, <TokenType.ENUM8: 'ENUM8'>, <TokenType.INDEX: 'INDEX'>, <TokenType.PARTITION: 'PARTITION'>, <TokenType.UINT256: 'UINT256'>, <TokenType.BIGINT: 'BIGINT'>, <TokenType.CACHE: 'CACHE'>, <TokenType.OPERATOR: 'OPERATOR'>, <TokenType.COLUMN: 'COLUMN'>, <TokenType.INT128: 'INT128'>, <TokenType.SMALLMONEY: 'SMALLMONEY'>, <TokenType.HLLSKETCH: 'HLLSKETCH'>, <TokenType.UNPIVOT: 'UNPIVOT'>, <TokenType.SMALLINT: 'SMALLINT'>, <TokenType.INT256: 'INT256'>, <TokenType.FLOAT: 'FLOAT'>, <TokenType.COMMIT: 'COMMIT'>, <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, <TokenType.EXISTS: 'EXISTS'>, <TokenType.NULL: 'NULL'>, <TokenType.RECURSIVE: 'RECURSIVE'>, <TokenType.SET: 'SET'>, <TokenType.NULLABLE: 'NULLABLE'>, <TokenType.REFRESH: 'REFRESH'>, <TokenType.TINYTEXT: 'TINYTEXT'>, <TokenType.SHOW: 'SHOW'>, <TokenType.DEFAULT: 'DEFAULT'>, <TokenType.DATE: 'DATE'>, <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <TokenType.MERGE: 'MERGE'>, <TokenType.FIRST: 'FIRST'>, <TokenType.BINARY: 'BINARY'>, <TokenType.ARRAY: 'ARRAY'>, <TokenType.SERIAL: 'SERIAL'>, <TokenType.EXECUTE: 'EXECUTE'>, <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, <TokenType.INTERVAL: 'INTERVAL'>, <TokenType.PRAGMA: 'PRAGMA'>, <TokenType.STORAGE_INTEGRATION: 'STORAGE_INTEGRATION'>, <TokenType.BPCHAR: 'BPCHAR'>, <TokenType.BIT: 'BIT'>, <TokenType.UINT: 'UINT'>, <TokenType.UUID: 'UUID'>, <TokenType.STRUCT: 'STRUCT'>, <TokenType.FALSE: 'FALSE'>, <TokenType.FUNCTION: 'FUNCTION'>, <TokenType.TOP: 'TOP'>, <TokenType.SUPER: 'SUPER'>, <TokenType.CASE: 'CASE'>, <TokenType.IMAGE: 'IMAGE'>, <TokenType.UBIGINT: 'UBIGINT'>, <TokenType.LONGBLOB: 'LONGBLOB'>, <TokenType.ROLLUP: 'ROLLUP'>, <TokenType.VAR: 'VAR'>, <TokenType.COMMAND: 'COMMAND'>, <TokenType.LOAD: 'LOAD'>, <TokenType.TRUNCATE: 'TRUNCATE'>, <TokenType.KEEP: 'KEEP'>, <TokenType.UMEDIUMINT: 'UMEDIUMINT'>, <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, <TokenType.UINT128: 'UINT128'>, <TokenType.END: 'END'>, <TokenType.MAP: 'MAP'>, <TokenType.IPV4: 'IPV4'>, <TokenType.USERDEFINED: 'USERDEFINED'>, <TokenType.REFERENCES: 'REFERENCES'>, <TokenType.REPLACE: 'REPLACE'>, <TokenType.RANGE: 'RANGE'>, <TokenType.NVARCHAR: 'NVARCHAR'>, <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, <TokenType.TRUE: 'TRUE'>, <TokenType.TIMESTAMP_MS: 'TIMESTAMP_MS'>, <TokenType.VARIANT: 'VARIANT'>, <TokenType.ENUM: 'ENUM'>, <TokenType.USE: 'USE'>, <TokenType.USMALLINT: 'USMALLINT'>, <TokenType.OVERLAPS: 'OVERLAPS'>, <TokenType.TIMESTAMP_S: 'TIMESTAMP_S'>, <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, <TokenType.UNIQUE: 'UNIQUE'>, <TokenType.ORDINALITY: 'ORDINALITY'>, <TokenType.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>, <TokenType.TEXT: 'TEXT'>, <TokenType.DATABASE: 'DATABASE'>, <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, <TokenType.PSEUDO_TYPE: 'PSEUDO_TYPE'>, <TokenType.FIXEDSTRING: 'FIXEDSTRING'>, <TokenType.NEXT: 'NEXT'>, <TokenType.INT: 'INT'>, <TokenType.BIGSERIAL: 'BIGSERIAL'>, <TokenType.BOOLEAN: 'BOOLEAN'>, <TokenType.IS: 'IS'>, <TokenType.CONSTRAINT: 'CONSTRAINT'>, <TokenType.FINAL: 'FINAL'>, <TokenType.UNKNOWN: 'UNKNOWN'>, <TokenType.SETTINGS: 'SETTINGS'>, <TokenType.ROWS: 'ROWS'>, <TokenType.TSTZRANGE: 'TSTZRANGE'>, <TokenType.DATETIME64: 'DATETIME64'>, <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, <TokenType.DATETIME: 'DATETIME'>, <TokenType.MEDIUMINT: 'MEDIUMINT'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>, <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, <TokenType.XML: 'XML'>, <TokenType.JSON: 'JSON'>, <TokenType.UTINYINT: 'UTINYINT'>, <TokenType.DELETE: 'DELETE'>, <TokenType.TIME: 'TIME'>, <TokenType.UDECIMAL: 'UDECIMAL'>, <TokenType.NESTED: 'NESTED'>, <TokenType.SEMI: 'SEMI'>, <TokenType.DESC: 'DESC'>, <TokenType.ROWVERSION: 'ROWVERSION'>, <TokenType.TIMESTAMP_NS: 'TIMESTAMP_NS'>, <TokenType.ANY: 'ANY'>, <TokenType.DIV: 'DIV'>, <TokenType.DICTIONARY: 'DICTIONARY'>, <TokenType.INET: 'INET'>, <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, <TokenType.COMMENT: 'COMMENT'>, <TokenType.CURRENT_USER: 'CURRENT_USER'>, <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>, <TokenType.ALL: 'ALL'>, <TokenType.NAME: 'NAME'>, <TokenType.SOME: 'SOME'>, <TokenType.ENUM16: 'ENUM16'>, <TokenType.YEAR: 'YEAR'>, <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, <TokenType.DOUBLE: 'DOUBLE'>, <TokenType.INT4RANGE: 'INT4RANGE'>, <TokenType.FORMAT: 'FORMAT'>, <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, <TokenType.IPPREFIX: 'IPPREFIX'>, <TokenType.OVERWRITE: 'OVERWRITE'>, <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>, <TokenType.COLLATE: 'COLLATE'>, <TokenType.FILTER: 'FILTER'>, <TokenType.JSONB: 'JSONB'>, <TokenType.TDIGEST: 'TDIGEST'>, <TokenType.CHAR: 'CHAR'>, <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.ROW: 'ROW'>, <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.TABLE: 'TABLE'>, <TokenType.DATERANGE: 'DATERANGE'>, <TokenType.TSRANGE: 'TSRANGE'>, <TokenType.ESCAPE: 'ESCAPE'>, <TokenType.PIVOT: 'PIVOT'>, <TokenType.DECIMAL: 'DECIMAL'>, <TokenType.NCHAR: 'NCHAR'>, <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, <TokenType.UPDATE: 'UPDATE'>, <TokenType.MODEL: 'MODEL'>, <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, <TokenType.SEQUENCE: 'SEQUENCE'>, <TokenType.LONGTEXT: 'LONGTEXT'>, <TokenType.DESCRIBE: 'DESCRIBE'>, <TokenType.IPV6: 'IPV6'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, <TokenType.TINYINT: 'TINYINT'>, <TokenType.TINYBLOB: 'TINYBLOB'>}"}, "sqlglot.dialects.trino.Trino.Parser.SHOW_TRIE": {"fullname": "sqlglot.dialects.trino.Trino.Parser.SHOW_TRIE", "modulename": "sqlglot.dialects.trino", "qualname": "Trino.Parser.SHOW_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.trino.Trino.Parser.SET_TRIE": {"fullname": "sqlglot.dialects.trino.Trino.Parser.SET_TRIE", "modulename": "sqlglot.dialects.trino", "qualname": "Trino.Parser.SET_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'GLOBAL': {0: True}, 'LOCAL': {0: True}, 'SESSION': {0: True}, 'TRANSACTION': {0: True}}"}, "sqlglot.dialects.trino.Trino.Generator": {"fullname": "sqlglot.dialects.trino.Trino.Generator", "modulename": "sqlglot.dialects.trino", "qualname": "Trino.Generator", "kind": "class", "doc": "<p>Generator converts a given syntax tree to the corresponding SQL string.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>pretty:</strong> Whether to format the produced SQL string.\nDefault: False.</li>\n<li><strong>identify:</strong> Determines when an identifier should be quoted. Possible values are:\nFalse (default): Never quote, except in cases where it's mandatory by the dialect.\nTrue or 'always': Always quote.\n'safe': Only quote identifiers that are case insensitive.</li>\n<li><strong>normalize:</strong> Whether to normalize identifiers to lowercase.\nDefault: False.</li>\n<li><strong>pad:</strong> The pad size in a formatted string. For example, this affects the indentation of\na projection in a query, relative to its nesting level.\nDefault: 2.</li>\n<li><strong>indent:</strong> The indentation size in a formatted string. For example, this affects the\nindentation of subqueries and filters under a <code>WHERE</code> clause.\nDefault: 2.</li>\n<li><strong>normalize_functions:</strong> How to normalize function names. Possible values are:\n\"upper\" or True (default): Convert names to uppercase.\n\"lower\": Convert names to lowercase.\nFalse: Disables function name normalization.</li>\n<li><strong>unsupported_level:</strong> Determines the generator's behavior when it encounters unsupported expressions.\nDefault ErrorLevel.WARN.</li>\n<li><strong>max_unsupported:</strong> Maximum number of unsupported messages to include in a raised UnsupportedError.\nThis is only relevant if unsupported_level is ErrorLevel.RAISE.\nDefault: 3</li>\n<li><strong>leading_comma:</strong> Whether the comma is leading or trailing in select expressions.\nThis is only relevant when generating in pretty mode.\nDefault: False</li>\n<li><strong>max_text_width:</strong> The max number of characters in a segment before creating new lines in pretty mode.\nThe default is on the smaller end because the length only represents a segment and not the true\nline length.\nDefault: 80</li>\n<li><strong>comments:</strong> Whether to preserve comments in the output SQL code.\nDefault: True</li>\n</ul>\n", "bases": "sqlglot.dialects.presto.Presto.Generator"}, "sqlglot.dialects.trino.Trino.Generator.TRANSFORMS": {"fullname": "sqlglot.dialects.trino.Trino.Generator.TRANSFORMS", "modulename": "sqlglot.dialects.trino", "qualname": "Trino.Generator.TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.JSONPathKey'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRoot'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSubscript'>: <function <lambda>>, <class 'sqlglot.expressions.AllowedValuesProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.BackupProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CaseSpecificColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CollateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CommentColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DateFormatColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DefaultColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EncodeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EphemeralColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExcludeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExternalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.GlobalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.HeapProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IcebergProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InheritsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InlineLengthColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IntervalSpan'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtract'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtractScalar'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LanguageProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LocationProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LogProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.MaterializedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NonClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NotForReplicationColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnCommitProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnUpdateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OutputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.PathColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ReturnsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SampleProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetConfigProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SettingsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SharingProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlReadWriteProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlSecurityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StabilityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StrictProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TemporaryProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TitleColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.Timestamp'>: <function no_timestamp_sql>, <class 'sqlglot.expressions.ToMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransformModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransientProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UppercaseColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UnloggedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VarMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VolatileProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithOperator'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.AnyValue'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.ApproxDistinct'>: <function Presto.Generator.<lambda>>, <class 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"annotation": ": Dict", "default_value": "{'%': {'B': {0: True}, '-': {'m': {0: True}, 'd': {0: True}, 'H': {0: True}, 'I': {0: True}}, 'I': {0: True}, 'M': {0: True}, 'S': {0: True}, 'W': {0: True}, 'H': {':': {'%': {'M': {':': {'%': {'S': {0: True}}}}}}}, 'a': {0: True}}}"}, "sqlglot.dialects.trino.Trino.ESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.trino.Trino.ESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.trino", "qualname": "Trino.ESCAPED_SEQUENCES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{}"}, "sqlglot.dialects.trino.Trino.QUOTE_START": {"fullname": "sqlglot.dialects.trino.Trino.QUOTE_START", "modulename": "sqlglot.dialects.trino", "qualname": "Trino.QUOTE_START", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.trino.Trino.QUOTE_END": {"fullname": "sqlglot.dialects.trino.Trino.QUOTE_END", "modulename": "sqlglot.dialects.trino", "qualname": "Trino.QUOTE_END", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.trino.Trino.IDENTIFIER_START": {"fullname": "sqlglot.dialects.trino.Trino.IDENTIFIER_START", "modulename": "sqlglot.dialects.trino", "qualname": "Trino.IDENTIFIER_START", "kind": "variable", "doc": "<p></p>\n", "default_value": "'"'"}, "sqlglot.dialects.trino.Trino.IDENTIFIER_END": {"fullname": "sqlglot.dialects.trino.Trino.IDENTIFIER_END", "modulename": "sqlglot.dialects.trino", "qualname": "Trino.IDENTIFIER_END", "kind": "variable", "doc": "<p></p>\n", "default_value": "'"'"}, "sqlglot.dialects.trino.Trino.BIT_START": {"fullname": "sqlglot.dialects.trino.Trino.BIT_START", "modulename": "sqlglot.dialects.trino", "qualname": "Trino.BIT_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.trino.Trino.BIT_END": {"fullname": "sqlglot.dialects.trino.Trino.BIT_END", "modulename": "sqlglot.dialects.trino", "qualname": "Trino.BIT_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.trino.Trino.HEX_START": {"fullname": "sqlglot.dialects.trino.Trino.HEX_START", "modulename": "sqlglot.dialects.trino", "qualname": "Trino.HEX_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""X'""}, "sqlglot.dialects.trino.Trino.HEX_END": {"fullname": "sqlglot.dialects.trino.Trino.HEX_END", "modulename": "sqlglot.dialects.trino", "qualname": "Trino.HEX_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": ""'""}, "sqlglot.dialects.trino.Trino.BYTE_START": {"fullname": "sqlglot.dialects.trino.Trino.BYTE_START", "modulename": "sqlglot.dialects.trino", "qualname": "Trino.BYTE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.trino.Trino.BYTE_END": {"fullname": "sqlglot.dialects.trino.Trino.BYTE_END", "modulename": 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"qualname": "FULL_FORMAT_TIME_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'weekday': '%A', 'dw': '%A', 'w': '%A', 'month': '%B', 'mm': '%B', 'm': '%B'}"}, "sqlglot.dialects.tsql.DATE_DELTA_INTERVAL": {"fullname": "sqlglot.dialects.tsql.DATE_DELTA_INTERVAL", "modulename": "sqlglot.dialects.tsql", "qualname": "DATE_DELTA_INTERVAL", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'year': 'year', 'yyyy': 'year', 'yy': 'year', 'quarter': 'quarter', 'qq': 'quarter', 'q': 'quarter', 'month': 'month', 'mm': 'month', 'm': 'month', 'week': 'week', 'ww': 'week', 'wk': 'week', 'day': 'day', 'dd': 'day', 'd': 'day'}"}, "sqlglot.dialects.tsql.DATE_FMT_RE": {"fullname": "sqlglot.dialects.tsql.DATE_FMT_RE", "modulename": "sqlglot.dialects.tsql", "qualname": "DATE_FMT_RE", "kind": "variable", "doc": "<p></p>\n", "default_value": "re.compile('([dD]{1,2})|([mM]{1,2})|([yY]{1,4})|([hH]{1,2})|([sS]{1,2})')"}, "sqlglot.dialects.tsql.TRANSPILE_SAFE_NUMBER_FMT": {"fullname": "sqlglot.dialects.tsql.TRANSPILE_SAFE_NUMBER_FMT", "modulename": "sqlglot.dialects.tsql", "qualname": "TRANSPILE_SAFE_NUMBER_FMT", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'C', 'N'}"}, "sqlglot.dialects.tsql.DEFAULT_START_DATE": {"fullname": "sqlglot.dialects.tsql.DEFAULT_START_DATE", "modulename": "sqlglot.dialects.tsql", "qualname": "DEFAULT_START_DATE", "kind": "variable", "doc": "<p></p>\n", "default_value": "datetime.date(1900, 1, 1)"}, "sqlglot.dialects.tsql.BIT_TYPES": {"fullname": "sqlglot.dialects.tsql.BIT_TYPES", "modulename": "sqlglot.dialects.tsql", "qualname": "BIT_TYPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.Alias'>, <class 'sqlglot.expressions.Select'>, <class 'sqlglot.expressions.EQ'>, <class 'sqlglot.expressions.Is'>, <class 'sqlglot.expressions.In'>, <class 'sqlglot.expressions.NEQ'>}"}, "sqlglot.dialects.tsql.OPTIONS": {"fullname": "sqlglot.dialects.tsql.OPTIONS", "modulename": "sqlglot.dialects.tsql", "qualname": "OPTIONS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, Sequence[Union[Sequence[str], str]]]", "default_value": "{'DISABLE_OPTIMIZED_PLAN_FORCING': (), 'FAST': (), 'IGNORE_NONCLUSTERED_COLUMNSTORE_INDEX': (), 'LABEL': (), 'MAXDOP': (), 'MAXRECURSION': (), 'MAX_GRANT_PERCENT': (), 'MIN_GRANT_PERCENT': (), 'NO_PERFORMANCE_SPOOL': (), 'QUERYTRACEON': (), 'RECOMPILE': (), 'CONCAT': ('UNION',), 'DISABLE': ('EXTERNALPUSHDOWN', 'SCALEOUTEXECUTION'), 'EXPAND': ('VIEWS',), 'FORCE': ('EXTERNALPUSHDOWN', 'ORDER', 'SCALEOUTEXECUTION'), 'HASH': ('GROUP', 'JOIN', 'UNION'), 'KEEP': ('PLAN',), 'KEEPFIXED': ('PLAN',), 'LOOP': ('JOIN',), 'MERGE': ('JOIN', 'UNION'), 'OPTIMIZE': (('FOR', 'UNKNOWN'),), 'ORDER': ('GROUP',), 'PARAMETERIZATION': ('FORCED', 'SIMPLE'), 'ROBUST': ('PLAN',), 'USE': ('PLAN',)}"}, "sqlglot.dialects.tsql.OPTIONS_THAT_REQUIRE_EQUAL": {"fullname": "sqlglot.dialects.tsql.OPTIONS_THAT_REQUIRE_EQUAL", "modulename": "sqlglot.dialects.tsql", "qualname": "OPTIONS_THAT_REQUIRE_EQUAL", "kind": "variable", "doc": "<p></p>\n", "default_value": "('MAX_GRANT_PERCENT', 'MIN_GRANT_PERCENT', 'LABEL')"}, "sqlglot.dialects.tsql.DATEPART_ONLY_FORMATS": {"fullname": "sqlglot.dialects.tsql.DATEPART_ONLY_FORMATS", "modulename": "sqlglot.dialects.tsql", "qualname": "DATEPART_ONLY_FORMATS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'HOUR', 'DW', 'QUARTER'}"}, "sqlglot.dialects.tsql.qualify_derived_table_outputs": {"fullname": "sqlglot.dialects.tsql.qualify_derived_table_outputs", "modulename": "sqlglot.dialects.tsql", "qualname": "qualify_derived_table_outputs", "kind": "function", "doc": "<p>Ensures all (unnamed) output columns are aliased for CTEs and Subqueries.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL": {"fullname": "sqlglot.dialects.tsql.TSQL", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.dialect.Dialect"}, "sqlglot.dialects.tsql.TSQL.NORMALIZATION_STRATEGY": {"fullname": "sqlglot.dialects.tsql.TSQL.NORMALIZATION_STRATEGY", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.NORMALIZATION_STRATEGY", "kind": "variable", "doc": "<p>Specifies the strategy according to which identifiers should be normalized.</p>\n", "default_value": "<NormalizationStrategy.CASE_INSENSITIVE: 'CASE_INSENSITIVE'>"}, "sqlglot.dialects.tsql.TSQL.TIME_FORMAT": {"fullname": "sqlglot.dialects.tsql.TSQL.TIME_FORMAT", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.TIME_FORMAT", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'yyyy-mm-dd hh:mm:ss'""}, "sqlglot.dialects.tsql.TSQL.SUPPORTS_SEMI_ANTI_JOIN": {"fullname": "sqlglot.dialects.tsql.TSQL.SUPPORTS_SEMI_ANTI_JOIN", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.SUPPORTS_SEMI_ANTI_JOIN", "kind": "variable", "doc": "<p>Whether <code>SEMI</code> or <code>ANTI</code> joins are supported.</p>\n", "default_value": "False"}, "sqlglot.dialects.tsql.TSQL.LOG_BASE_FIRST": {"fullname": "sqlglot.dialects.tsql.TSQL.LOG_BASE_FIRST", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.LOG_BASE_FIRST", "kind": "variable", "doc": "<p>Whether the base comes first in the <code>LOG</code> function.\nPossible values: <code>True</code>, <code>False</code>, <code>None</code> (two arguments are not supported by <code>LOG</code>)</p>\n", "annotation": ": Optional[bool]", "default_value": "False"}, "sqlglot.dialects.tsql.TSQL.TYPED_DIVISION": {"fullname": "sqlglot.dialects.tsql.TSQL.TYPED_DIVISION", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.TYPED_DIVISION", "kind": "variable", "doc": "<p>Whether the behavior of <code>a / b</code> depends on the types of <code>a</code> and <code>b</code>.\nFalse means <code>a / b</code> is always float division.\nTrue means <code>a / b</code> is integer division if both <code>a</code> and <code>b</code> are integers.</p>\n", "default_value": "True"}, "sqlglot.dialects.tsql.TSQL.CONCAT_COALESCE": {"fullname": "sqlglot.dialects.tsql.TSQL.CONCAT_COALESCE", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.CONCAT_COALESCE", "kind": "variable", "doc": "<p>A <code>NULL</code> arg in <code>CONCAT</code> yields <code>NULL</code> by default, but in some dialects it yields an empty string.</p>\n", "default_value": "True"}, "sqlglot.dialects.tsql.TSQL.TIME_MAPPING": {"fullname": "sqlglot.dialects.tsql.TSQL.TIME_MAPPING", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.TIME_MAPPING", "kind": "variable", "doc": "<p>Associates this dialect's time formats with their equivalent Python <code>strftime</code> formats.</p>\n", "annotation": ": Dict[str, str]", "default_value": "{'year': '%Y', 'dayofyear': '%j', 'day': '%d', 'dy': '%d', 'y': '%Y', 'week': '%W', 'ww': '%W', 'wk': '%W', 'hour': '%h', 'hh': '%I', 'minute': '%M', 'mi': '%M', 'n': '%M', 'second': '%S', 'ss': '%S', 's': '%-S', 'millisecond': '%f', 'ms': '%f', 'weekday': '%W', 'dw': '%W', 'month': '%m', 'mm': '%M', 'm': '%-M', 'Y': '%Y', 'YYYY': '%Y', 'YY': '%y', 'MMMM': '%B', 'MMM': '%b', 'MM': '%m', 'M': '%-m', 'dddd': '%A', 'dd': '%d', 'd': '%-d', 'HH': '%H', 'H': '%-H', 'h': '%-I', 'S': '%f', 'yyyy': '%Y', 'yy': '%y'}"}, "sqlglot.dialects.tsql.TSQL.CONVERT_FORMAT_MAPPING": {"fullname": "sqlglot.dialects.tsql.TSQL.CONVERT_FORMAT_MAPPING", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.CONVERT_FORMAT_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'0': '%b %d %Y %-I:%M%p', '1': '%m/%d/%y', '2': '%y.%m.%d', '3': '%d/%m/%y', '4': '%d.%m.%y', '5': '%d-%m-%y', '6': '%d %b %y', '7': '%b %d, %y', '8': '%H:%M:%S', '9': '%b %d %Y %-I:%M:%S:%f%p', '10': 'mm-dd-yy', '11': 'yy/mm/dd', '12': 'yymmdd', '13': '%d %b %Y %H:%M:ss:%f', '14': '%H:%M:%S:%f', '20': '%Y-%m-%d %H:%M:%S', '21': '%Y-%m-%d %H:%M:%S.%f', '22': '%m/%d/%y %-I:%M:%S %p', '23': '%Y-%m-%d', '24': '%H:%M:%S', '25': '%Y-%m-%d %H:%M:%S.%f', '100': '%b %d %Y %-I:%M%p', '101': '%m/%d/%Y', '102': '%Y.%m.%d', '103': '%d/%m/%Y', '104': '%d.%m.%Y', '105': '%d-%m-%Y', '106': '%d %b %Y', '107': '%b %d, %Y', '108': '%H:%M:%S', '109': '%b %d %Y %-I:%M:%S:%f%p', '110': '%m-%d-%Y', '111': '%Y/%m/%d', '112': '%Y%m%d', '113': '%d %b %Y %H:%M:%S:%f', '114': '%H:%M:%S:%f', '120': '%Y-%m-%d %H:%M:%S', '121': '%Y-%m-%d %H:%M:%S.%f'}"}, "sqlglot.dialects.tsql.TSQL.FORMAT_TIME_MAPPING": {"fullname": "sqlglot.dialects.tsql.TSQL.FORMAT_TIME_MAPPING", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.FORMAT_TIME_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'y': '%B %Y', 'd': '%m/%d/%Y', 'H': '%-H', 'h': '%-I', 's': '%Y-%m-%d %H:%M:%S', 'D': '%A,%B,%Y', 'f': '%A,%B,%Y %-I:%M %p', 'F': '%A,%B,%Y %-I:%M:%S %p', 'g': '%m/%d/%Y %-I:%M %p', 'G': '%m/%d/%Y %-I:%M:%S %p', 'M': '%B %-d', 'm': '%B %-d', 'O': '%Y-%m-%dT%H:%M:%S', 'u': '%Y-%M-%D %H:%M:%S%z', 'U': '%A, %B %D, %Y %H:%M:%S%z', 'T': '%-I:%M:%S %p', 't': '%-I:%M', 'Y': '%a %Y'}"}, "sqlglot.dialects.tsql.TSQL.Tokenizer": {"fullname": "sqlglot.dialects.tsql.TSQL.Tokenizer", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Tokenizer", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.tokens.Tokenizer"}, "sqlglot.dialects.tsql.TSQL.Tokenizer.IDENTIFIERS": {"fullname": "sqlglot.dialects.tsql.TSQL.Tokenizer.IDENTIFIERS", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Tokenizer.IDENTIFIERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "[('[', ']'), '"']"}, "sqlglot.dialects.tsql.TSQL.Tokenizer.QUOTES": {"fullname": "sqlglot.dialects.tsql.TSQL.Tokenizer.QUOTES", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Tokenizer.QUOTES", "kind": "variable", "doc": "<p></p>\n", "default_value": "["'", '"']"}, "sqlglot.dialects.tsql.TSQL.Tokenizer.HEX_STRINGS": {"fullname": "sqlglot.dialects.tsql.TSQL.Tokenizer.HEX_STRINGS", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Tokenizer.HEX_STRINGS", "kind": "variable", "doc": "<p></p>\n", "default_value": "[('0x', ''), ('0X', '')]"}, "sqlglot.dialects.tsql.TSQL.Tokenizer.VAR_SINGLE_TOKENS": {"fullname": "sqlglot.dialects.tsql.TSQL.Tokenizer.VAR_SINGLE_TOKENS", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Tokenizer.VAR_SINGLE_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'$', '@', '#'}"}, "sqlglot.dialects.tsql.TSQL.Tokenizer.KEYWORDS": {"fullname": "sqlglot.dialects.tsql.TSQL.Tokenizer.KEYWORDS", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Tokenizer.KEYWORDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'{%': <TokenType.BLOCK_START: 'BLOCK_START'>, '{%+': <TokenType.BLOCK_START: 'BLOCK_START'>, '{%-': <TokenType.BLOCK_START: 'BLOCK_START'>, '%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '+%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '-%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '{{+': <TokenType.BLOCK_START: 'BLOCK_START'>, '{{-': <TokenType.BLOCK_START: 'BLOCK_START'>, '+}}': <TokenType.BLOCK_END: 'BLOCK_END'>, '-}}': <TokenType.BLOCK_END: 'BLOCK_END'>, '/*+': <TokenType.HINT: 'HINT'>, '==': <TokenType.EQ: 'EQ'>, '::': <TokenType.DCOLON: 'DCOLON'>, '||': <TokenType.DPIPE: 'DPIPE'>, '>=': <TokenType.GTE: 'GTE'>, '<=': <TokenType.LTE: 'LTE'>, '<>': <TokenType.NEQ: 'NEQ'>, '!=': <TokenType.NEQ: 'NEQ'>, ':=': <TokenType.COLON_EQ: 'COLON_EQ'>, '<=>': <TokenType.NULLSAFE_EQ: 'NULLSAFE_EQ'>, '->': <TokenType.ARROW: 'ARROW'>, '->>': <TokenType.DARROW: 'DARROW'>, '=>': <TokenType.FARROW: 'FARROW'>, '#>': <TokenType.HASH_ARROW: 'HASH_ARROW'>, '#>>': <TokenType.DHASH_ARROW: 'DHASH_ARROW'>, '<->': <TokenType.LR_ARROW: 'LR_ARROW'>, '&&': <TokenType.DAMP: 'DAMP'>, '??': <TokenType.DQMARK: 'DQMARK'>, 'ALL': <TokenType.ALL: 'ALL'>, 'ALWAYS': <TokenType.ALWAYS: 'ALWAYS'>, 'AND': <TokenType.AND: 'AND'>, 'ANTI': <TokenType.ANTI: 'ANTI'>, 'ANY': <TokenType.ANY: 'ANY'>, 'ASC': <TokenType.ASC: 'ASC'>, 'AS': <TokenType.ALIAS: 'ALIAS'>, 'ASOF': <TokenType.ASOF: 'ASOF'>, 'AUTOINCREMENT': <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, 'AUTO_INCREMENT': <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, 'BEGIN': <TokenType.BEGIN: 'BEGIN'>, 'BETWEEN': <TokenType.BETWEEN: 'BETWEEN'>, 'CACHE': <TokenType.CACHE: 'CACHE'>, 'UNCACHE': <TokenType.UNCACHE: 'UNCACHE'>, 'CASE': <TokenType.CASE: 'CASE'>, 'CHARACTER SET': <TokenType.CHARACTER_SET: 'CHARACTER_SET'>, 'CLUSTER BY': <TokenType.CLUSTER_BY: 'CLUSTER_BY'>, 'COLLATE': <TokenType.COLLATE: 'COLLATE'>, 'COLUMN': <TokenType.COLUMN: 'COLUMN'>, 'COMMIT': <TokenType.COMMIT: 'COMMIT'>, 'CONNECT BY': <TokenType.CONNECT_BY: 'CONNECT_BY'>, 'CONSTRAINT': <TokenType.CONSTRAINT: 'CONSTRAINT'>, 'COPY': <TokenType.COPY: 'COPY'>, 'CREATE': <TokenType.CREATE: 'CREATE'>, 'CROSS': <TokenType.CROSS: 'CROSS'>, 'CUBE': <TokenType.CUBE: 'CUBE'>, 'CURRENT_DATE': <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, 'CURRENT_TIME': <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, 'CURRENT_TIMESTAMP': <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, 'CURRENT_USER': <TokenType.CURRENT_USER: 'CURRENT_USER'>, 'DATABASE': <TokenType.DATABASE: 'DATABASE'>, 'DEFAULT': <TokenType.DEFAULT: 'DEFAULT'>, 'DELETE': <TokenType.DELETE: 'DELETE'>, 'DESC': <TokenType.DESC: 'DESC'>, 'DESCRIBE': <TokenType.DESCRIBE: 'DESCRIBE'>, 'DISTINCT': <TokenType.DISTINCT: 'DISTINCT'>, 'DISTRIBUTE BY': <TokenType.DISTRIBUTE_BY: 'DISTRIBUTE_BY'>, 'DIV': <TokenType.DIV: 'DIV'>, 'DROP': <TokenType.DROP: 'DROP'>, 'ELSE': <TokenType.ELSE: 'ELSE'>, 'END': <TokenType.END: 'END'>, 'ENUM': <TokenType.ENUM: 'ENUM'>, 'ESCAPE': <TokenType.ESCAPE: 'ESCAPE'>, 'EXCEPT': <TokenType.EXCEPT: 'EXCEPT'>, 'EXECUTE': <TokenType.EXECUTE: 'EXECUTE'>, 'EXISTS': <TokenType.EXISTS: 'EXISTS'>, 'FALSE': <TokenType.FALSE: 'FALSE'>, 'FETCH': <TokenType.FETCH: 'FETCH'>, 'FILTER': <TokenType.FILTER: 'FILTER'>, 'FIRST': <TokenType.FIRST: 'FIRST'>, 'FULL': <TokenType.FULL: 'FULL'>, 'FUNCTION': <TokenType.FUNCTION: 'FUNCTION'>, 'FOR': <TokenType.FOR: 'FOR'>, 'FOREIGN KEY': <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, 'FORMAT': <TokenType.FORMAT: 'FORMAT'>, 'FROM': <TokenType.FROM: 'FROM'>, 'GEOGRAPHY': <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, 'GEOMETRY': <TokenType.GEOMETRY: 'GEOMETRY'>, 'GLOB': <TokenType.GLOB: 'GLOB'>, 'GROUP BY': <TokenType.GROUP_BY: 'GROUP_BY'>, 'GROUPING SETS': <TokenType.GROUPING_SETS: 'GROUPING_SETS'>, 'HAVING': <TokenType.HAVING: 'HAVING'>, 'ILIKE': <TokenType.ILIKE: 'ILIKE'>, 'IN': <TokenType.IN: 'IN'>, 'INDEX': <TokenType.INDEX: 'INDEX'>, 'INET': <TokenType.INET: 'INET'>, 'INNER': <TokenType.INNER: 'INNER'>, 'INSERT': <TokenType.INSERT: 'INSERT'>, 'INTERVAL': <TokenType.INTERVAL: 'INTERVAL'>, 'INTERSECT': <TokenType.INTERSECT: 'INTERSECT'>, 'INTO': <TokenType.INTO: 'INTO'>, 'IS': <TokenType.IS: 'IS'>, 'ISNULL': <TokenType.ISNULL: 'ISNULL'>, 'JOIN': <TokenType.JOIN: 'JOIN'>, 'KEEP': <TokenType.KEEP: 'KEEP'>, 'KILL': <TokenType.KILL: 'KILL'>, 'LATERAL': <TokenType.LATERAL: 'LATERAL'>, 'LEFT': <TokenType.LEFT: 'LEFT'>, 'LIKE': <TokenType.LIKE: 'LIKE'>, 'LIMIT': <TokenType.LIMIT: 'LIMIT'>, 'LOAD': <TokenType.LOAD: 'LOAD'>, 'LOCK': <TokenType.LOCK: 'LOCK'>, 'MERGE': <TokenType.MERGE: 'MERGE'>, 'NATURAL': <TokenType.NATURAL: 'NATURAL'>, 'NEXT': <TokenType.NEXT: 'NEXT'>, 'NOT': <TokenType.NOT: 'NOT'>, 'NOTNULL': <TokenType.NOTNULL: 'NOTNULL'>, 'NULL': <TokenType.NULL: 'NULL'>, 'OBJECT': <TokenType.OBJECT: 'OBJECT'>, 'OFFSET': <TokenType.OFFSET: 'OFFSET'>, 'ON': <TokenType.ON: 'ON'>, 'OR': <TokenType.OR: 'OR'>, 'XOR': <TokenType.XOR: 'XOR'>, 'ORDER BY': <TokenType.ORDER_BY: 'ORDER_BY'>, 'ORDINALITY': <TokenType.ORDINALITY: 'ORDINALITY'>, 'OUTER': <TokenType.OUTER: 'OUTER'>, 'OVER': <TokenType.OVER: 'OVER'>, 'OVERLAPS': <TokenType.OVERLAPS: 'OVERLAPS'>, 'OVERWRITE': <TokenType.OVERWRITE: 'OVERWRITE'>, 'PARTITION': <TokenType.PARTITION: 'PARTITION'>, 'PARTITION BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PARTITIONED BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PARTITIONED_BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PERCENT': <TokenType.PERCENT: 'PERCENT'>, 'PIVOT': <TokenType.PIVOT: 'PIVOT'>, 'PRAGMA': <TokenType.PRAGMA: 'PRAGMA'>, 'PRIMARY KEY': <TokenType.PRIMARY_KEY: 'PRIMARY_KEY'>, 'PROCEDURE': <TokenType.PROCEDURE: 'PROCEDURE'>, 'QUALIFY': <TokenType.QUALIFY: 'QUALIFY'>, 'RANGE': <TokenType.RANGE: 'RANGE'>, 'RECURSIVE': <TokenType.RECURSIVE: 'RECURSIVE'>, 'REGEXP': <TokenType.RLIKE: 'RLIKE'>, 'REPLACE': <TokenType.REPLACE: 'REPLACE'>, 'RETURNING': <TokenType.RETURNING: 'RETURNING'>, 'REFERENCES': <TokenType.REFERENCES: 'REFERENCES'>, 'RIGHT': <TokenType.RIGHT: 'RIGHT'>, 'RLIKE': <TokenType.RLIKE: 'RLIKE'>, 'ROLLBACK': <TokenType.ROLLBACK: 'ROLLBACK'>, 'ROLLUP': <TokenType.ROLLUP: 'ROLLUP'>, 'ROW': <TokenType.ROW: 'ROW'>, 'ROWS': <TokenType.ROWS: 'ROWS'>, 'SCHEMA': <TokenType.SCHEMA: 'SCHEMA'>, 'SELECT': <TokenType.SELECT: 'SELECT'>, 'SEMI': <TokenType.SEMI: 'SEMI'>, 'SET': <TokenType.SET: 'SET'>, 'SETTINGS': <TokenType.SETTINGS: 'SETTINGS'>, 'SHOW': <TokenType.SHOW: 'SHOW'>, 'SIMILAR TO': <TokenType.SIMILAR_TO: 'SIMILAR_TO'>, 'SOME': <TokenType.SOME: 'SOME'>, 'SORT BY': <TokenType.SORT_BY: 'SORT_BY'>, 'START WITH': <TokenType.START_WITH: 'START_WITH'>, 'TABLE': <TokenType.TABLE: 'TABLE'>, 'TABLESAMPLE': <TokenType.TABLE_SAMPLE: 'TABLE_SAMPLE'>, 'TEMP': <TokenType.TEMPORARY: 'TEMPORARY'>, 'TEMPORARY': <TokenType.TEMPORARY: 'TEMPORARY'>, 'THEN': <TokenType.THEN: 'THEN'>, 'TRUE': <TokenType.TRUE: 'TRUE'>, 'TRUNCATE': <TokenType.TRUNCATE: 'TRUNCATE'>, 'UNION': <TokenType.UNION: 'UNION'>, 'UNKNOWN': <TokenType.UNKNOWN: 'UNKNOWN'>, 'UNNEST': <TokenType.UNNEST: 'UNNEST'>, 'UNPIVOT': <TokenType.UNPIVOT: 'UNPIVOT'>, 'UPDATE': <TokenType.UPDATE: 'UPDATE'>, 'USE': <TokenType.USE: 'USE'>, 'USING': <TokenType.USING: 'USING'>, 'UUID': <TokenType.UUID: 'UUID'>, 'VALUES': <TokenType.VALUES: 'VALUES'>, 'VIEW': <TokenType.VIEW: 'VIEW'>, 'VOLATILE': <TokenType.VOLATILE: 'VOLATILE'>, 'WHEN': <TokenType.WHEN: 'WHEN'>, 'WHERE': <TokenType.WHERE: 'WHERE'>, 'WINDOW': <TokenType.WINDOW: 'WINDOW'>, 'WITH': <TokenType.WITH: 'WITH'>, 'APPLY': <TokenType.APPLY: 'APPLY'>, 'ARRAY': <TokenType.ARRAY: 'ARRAY'>, 'BIT': <TokenType.BIT: 'BIT'>, 'BOOL': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BOOLEAN': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BYTE': <TokenType.TINYINT: 'TINYINT'>, 'MEDIUMINT': <TokenType.MEDIUMINT: 'MEDIUMINT'>, 'INT1': <TokenType.TINYINT: 'TINYINT'>, 'TINYINT': <TokenType.UTINYINT: 'UTINYINT'>, 'INT16': <TokenType.SMALLINT: 'SMALLINT'>, 'SHORT': <TokenType.SMALLINT: 'SMALLINT'>, 'SMALLINT': <TokenType.SMALLINT: 'SMALLINT'>, 'INT128': <TokenType.INT128: 'INT128'>, 'HUGEINT': <TokenType.INT128: 'INT128'>, 'INT2': <TokenType.SMALLINT: 'SMALLINT'>, 'INTEGER': <TokenType.INT: 'INT'>, 'INT': <TokenType.INT: 'INT'>, 'INT4': <TokenType.INT: 'INT'>, 'INT32': <TokenType.INT: 'INT'>, 'INT64': <TokenType.BIGINT: 'BIGINT'>, 'LONG': <TokenType.BIGINT: 'BIGINT'>, 'BIGINT': <TokenType.BIGINT: 'BIGINT'>, 'INT8': <TokenType.TINYINT: 'TINYINT'>, 'UINT': <TokenType.UINT: 'UINT'>, 'DEC': <TokenType.DECIMAL: 'DECIMAL'>, 'DECIMAL': <TokenType.DECIMAL: 'DECIMAL'>, 'BIGDECIMAL': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'BIGNUMERIC': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'MAP': <TokenType.MAP: 'MAP'>, 'NULLABLE': <TokenType.NULLABLE: 'NULLABLE'>, 'NUMBER': <TokenType.DECIMAL: 'DECIMAL'>, 'NUMERIC': <TokenType.DECIMAL: 'DECIMAL'>, 'FIXED': <TokenType.DECIMAL: 'DECIMAL'>, 'REAL': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT4': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT8': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE PRECISION': <TokenType.DOUBLE: 'DOUBLE'>, 'JSON': <TokenType.JSON: 'JSON'>, 'CHAR': <TokenType.CHAR: 'CHAR'>, 'CHARACTER': <TokenType.CHAR: 'CHAR'>, 'NCHAR': <TokenType.NCHAR: 'NCHAR'>, 'VARCHAR': <TokenType.VARCHAR: 'VARCHAR'>, 'VARCHAR2': <TokenType.VARCHAR: 'VARCHAR'>, 'NVARCHAR': <TokenType.NVARCHAR: 'NVARCHAR'>, 'NVARCHAR2': <TokenType.NVARCHAR: 'NVARCHAR'>, 'BPCHAR': <TokenType.BPCHAR: 'BPCHAR'>, 'STR': <TokenType.TEXT: 'TEXT'>, 'STRING': <TokenType.TEXT: 'TEXT'>, 'TEXT': <TokenType.TEXT: 'TEXT'>, 'LONGTEXT': <TokenType.LONGTEXT: 'LONGTEXT'>, 'MEDIUMTEXT': <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, 'TINYTEXT': <TokenType.TINYTEXT: 'TINYTEXT'>, 'CLOB': <TokenType.TEXT: 'TEXT'>, 'LONGVARCHAR': <TokenType.TEXT: 'TEXT'>, 'BINARY': <TokenType.BINARY: 'BINARY'>, 'BLOB': <TokenType.VARBINARY: 'VARBINARY'>, 'LONGBLOB': <TokenType.LONGBLOB: 'LONGBLOB'>, 'MEDIUMBLOB': <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, 'TINYBLOB': <TokenType.TINYBLOB: 'TINYBLOB'>, 'BYTEA': <TokenType.VARBINARY: 'VARBINARY'>, 'VARBINARY': <TokenType.VARBINARY: 'VARBINARY'>, 'TIME': <TokenType.TIME: 'TIME'>, 'TIMETZ': <TokenType.TIMETZ: 'TIMETZ'>, 'TIMESTAMP': <TokenType.ROWVERSION: 'ROWVERSION'>, 'TIMESTAMPTZ': <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, 'TIMESTAMPLTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMP_LTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMPNTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'TIMESTAMP_NTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'DATE': <TokenType.DATE: 'DATE'>, 'DATETIME': <TokenType.DATETIME: 'DATETIME'>, 'INT4RANGE': <TokenType.INT4RANGE: 'INT4RANGE'>, 'INT4MULTIRANGE': <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, 'INT8RANGE': <TokenType.INT8RANGE: 'INT8RANGE'>, 'INT8MULTIRANGE': <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, 'NUMRANGE': <TokenType.NUMRANGE: 'NUMRANGE'>, 'NUMMULTIRANGE': <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, 'TSRANGE': <TokenType.TSRANGE: 'TSRANGE'>, 'TSMULTIRANGE': <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, 'TSTZRANGE': <TokenType.TSTZRANGE: 'TSTZRANGE'>, 'TSTZMULTIRANGE': <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, 'DATERANGE': <TokenType.DATERANGE: 'DATERANGE'>, 'DATEMULTIRANGE': <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, 'UNIQUE': <TokenType.UNIQUE: 'UNIQUE'>, 'STRUCT': <TokenType.STRUCT: 'STRUCT'>, 'SEQUENCE': <TokenType.SEQUENCE: 'SEQUENCE'>, 'VARIANT': <TokenType.VARIANT: 'VARIANT'>, 'ALTER': <TokenType.ALTER: 'ALTER'>, 'ANALYZE': <TokenType.COMMAND: 'COMMAND'>, 'CALL': <TokenType.COMMAND: 'COMMAND'>, 'COMMENT': <TokenType.COMMENT: 'COMMENT'>, 'EXPLAIN': <TokenType.COMMAND: 'COMMAND'>, 'GRANT': <TokenType.COMMAND: 'COMMAND'>, 'OPTIMIZE': <TokenType.COMMAND: 'COMMAND'>, 'PREPARE': <TokenType.COMMAND: 'COMMAND'>, 'VACUUM': <TokenType.COMMAND: 'COMMAND'>, 'USER-DEFINED': <TokenType.USERDEFINED: 'USERDEFINED'>, 'FOR VERSION': <TokenType.VERSION_SNAPSHOT: 'VERSION_SNAPSHOT'>, 'FOR TIMESTAMP': <TokenType.TIMESTAMP_SNAPSHOT: 'TIMESTAMP_SNAPSHOT'>, 'DATETIME2': <TokenType.DATETIME: 'DATETIME'>, 'DATETIMEOFFSET': <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, 'DECLARE': <TokenType.DECLARE: 'DECLARE'>, 'EXEC': <TokenType.COMMAND: 'COMMAND'>, 'FOR SYSTEM_TIME': <TokenType.TIMESTAMP_SNAPSHOT: 'TIMESTAMP_SNAPSHOT'>, 'IMAGE': <TokenType.IMAGE: 'IMAGE'>, 'MONEY': <TokenType.MONEY: 'MONEY'>, 'NTEXT': <TokenType.TEXT: 'TEXT'>, 'OPTION': <TokenType.OPTION: 'OPTION'>, 'OUTPUT': <TokenType.RETURNING: 'RETURNING'>, 'PRINT': <TokenType.COMMAND: 'COMMAND'>, 'PROC': <TokenType.PROCEDURE: 'PROCEDURE'>, 'ROWVERSION': <TokenType.ROWVERSION: 'ROWVERSION'>, 'SMALLDATETIME': <TokenType.DATETIME: 'DATETIME'>, 'SMALLMONEY': <TokenType.SMALLMONEY: 'SMALLMONEY'>, 'SQL_VARIANT': <TokenType.VARIANT: 'VARIANT'>, 'SYSTEM_USER': <TokenType.CURRENT_USER: 'CURRENT_USER'>, 'TOP': <TokenType.TOP: 'TOP'>, 'UNIQUEIDENTIFIER': <TokenType.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>, 'UPDATE STATISTICS': <TokenType.COMMAND: 'COMMAND'>, 'XML': <TokenType.XML: 'XML'>}"}, "sqlglot.dialects.tsql.TSQL.Tokenizer.COMMANDS": {"fullname": "sqlglot.dialects.tsql.TSQL.Tokenizer.COMMANDS", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Tokenizer.COMMANDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.FETCH: 'FETCH'>, <TokenType.END: 'END'>, <TokenType.EXECUTE: 'EXECUTE'>, <TokenType.COMMAND: 'COMMAND'>, <TokenType.SHOW: 'SHOW'>}"}, "sqlglot.dialects.tsql.TSQL.Parser": {"fullname": "sqlglot.dialects.tsql.TSQL.Parser", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Parser", "kind": "class", "doc": "<p>Parser consumes a list of tokens produced by the Tokenizer and produces a parsed syntax tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>error_level:</strong> The desired error level.\nDefault: ErrorLevel.IMMEDIATE</li>\n<li><strong>error_message_context:</strong> The amount of context to capture from a query string when displaying\nthe error message (in number of characters).\nDefault: 100</li>\n<li><strong>max_errors:</strong> Maximum number of error messages to include in a raised ParseError.\nThis is only relevant if error_level is ErrorLevel.RAISE.\nDefault: 3</li>\n</ul>\n", "bases": "sqlglot.parser.Parser"}, "sqlglot.dialects.tsql.TSQL.Parser.SET_REQUIRES_ASSIGNMENT_DELIMITER": {"fullname": "sqlglot.dialects.tsql.TSQL.Parser.SET_REQUIRES_ASSIGNMENT_DELIMITER", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Parser.SET_REQUIRES_ASSIGNMENT_DELIMITER", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.tsql.TSQL.Parser.LOG_DEFAULTS_TO_LN": {"fullname": "sqlglot.dialects.tsql.TSQL.Parser.LOG_DEFAULTS_TO_LN", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Parser.LOG_DEFAULTS_TO_LN", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.tsql.TSQL.Parser.ALTER_TABLE_ADD_REQUIRED_FOR_EACH_COLUMN": {"fullname": "sqlglot.dialects.tsql.TSQL.Parser.ALTER_TABLE_ADD_REQUIRED_FOR_EACH_COLUMN", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Parser.ALTER_TABLE_ADD_REQUIRED_FOR_EACH_COLUMN", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.tsql.TSQL.Parser.STRING_ALIASES": {"fullname": "sqlglot.dialects.tsql.TSQL.Parser.STRING_ALIASES", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Parser.STRING_ALIASES", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.tsql.TSQL.Parser.NO_PAREN_IF_COMMANDS": {"fullname": "sqlglot.dialects.tsql.TSQL.Parser.NO_PAREN_IF_COMMANDS", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Parser.NO_PAREN_IF_COMMANDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.tsql.TSQL.Parser.QUERY_MODIFIER_PARSERS": {"fullname": "sqlglot.dialects.tsql.TSQL.Parser.QUERY_MODIFIER_PARSERS", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Parser.QUERY_MODIFIER_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.MATCH_RECOGNIZE: 'MATCH_RECOGNIZE'>: <function Parser.<lambda>>, <TokenType.PREWHERE: 'PREWHERE'>: <function Parser.<lambda>>, <TokenType.WHERE: 'WHERE'>: <function Parser.<lambda>>, <TokenType.GROUP_BY: 'GROUP_BY'>: <function Parser.<lambda>>, <TokenType.HAVING: 'HAVING'>: <function Parser.<lambda>>, <TokenType.QUALIFY: 'QUALIFY'>: <function Parser.<lambda>>, <TokenType.WINDOW: 'WINDOW'>: <function Parser.<lambda>>, <TokenType.ORDER_BY: 'ORDER_BY'>: <function Parser.<lambda>>, <TokenType.LIMIT: 'LIMIT'>: <function Parser.<lambda>>, <TokenType.FETCH: 'FETCH'>: <function Parser.<lambda>>, <TokenType.OFFSET: 'OFFSET'>: <function Parser.<lambda>>, <TokenType.FOR: 'FOR'>: <function Parser.<lambda>>, <TokenType.LOCK: 'LOCK'>: <function Parser.<lambda>>, <TokenType.TABLE_SAMPLE: 'TABLE_SAMPLE'>: <function Parser.<lambda>>, <TokenType.USING: 'USING'>: <function Parser.<lambda>>, <TokenType.CLUSTER_BY: 'CLUSTER_BY'>: <function Parser.<lambda>>, <TokenType.DISTRIBUTE_BY: 'DISTRIBUTE_BY'>: <function Parser.<lambda>>, <TokenType.SORT_BY: 'SORT_BY'>: <function Parser.<lambda>>, <TokenType.CONNECT_BY: 'CONNECT_BY'>: <function Parser.<lambda>>, <TokenType.START_WITH: 'START_WITH'>: <function Parser.<lambda>>, <TokenType.OPTION: 'OPTION'>: <function TSQL.Parser.<lambda>>}"}, "sqlglot.dialects.tsql.TSQL.Parser.FUNCTIONS": {"fullname": "sqlglot.dialects.tsql.TSQL.Parser.FUNCTIONS", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Parser.FUNCTIONS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ABS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Abs'>>, 'ADD_MONTHS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AddMonths'>>, 'ANONYMOUS_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnonymousAggFunc'>>, 'ANY_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnyValue'>>, 'APPROX_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_COUNT_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'APPROX_TOP_K': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxTopK'>>, 'ARG_MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARGMAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'MAX_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARG_MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARGMIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'MIN_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Array'>>, 'ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAgg'>>, 'ARRAY_ALL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAll'>>, 'ARRAY_ANY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAny'>>, 'ARRAY_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CONSTRUCT_COMPACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConstructCompact'>>, 'ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayContains'>>, 'FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_OVERLAPS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayOverlaps'>>, 'ARRAY_SIZE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_SORT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySort'>>, 'ARRAY_SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySum'>>, 'ARRAY_TO_STRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_JOIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_UNION_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUnionAgg'>>, 'ARRAY_UNIQUE_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUniqueAgg'>>, 'AVG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Avg'>>, 'CASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Case'>>, 'CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cast'>>, 'CAST_TO_STR_TYPE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CastToStrType'>>, 'CBRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cbrt'>>, 'CEIL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CEILING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CHR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'COALESCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'IFNULL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'NVL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'COLLATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Collate'>>, 'COMBINED_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedAggFunc'>>, 'COMBINED_PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedParameterizedAgg'>>, 'CONCAT': <function Parser.<lambda>>, 'CONCAT_WS': <function Parser.<lambda>>, 'CONNECT_BY_ROOT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ConnectByRoot'>>, 'CONVERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Convert'>>, 'CORR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Corr'>>, 'COUNT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Count'>>, 'COUNT_IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COUNTIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COVAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarPop'>>, 'COVAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarSamp'>>, 'CURRENT_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDate'>>, 'CURRENT_DATETIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDatetime'>>, 'CURRENT_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTime'>>, 'CURRENT_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTimestamp'>>, 'CURRENT_USER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentUser'>>, 'DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Date'>>, 'DATE_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateAdd'>>, 'DATEDIFF': <function _build_date_delta.<locals>._builder>, 'DATE_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateDiff'>>, 'DATE_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATE_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateStrToDate'>>, 'DATE_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateSub'>>, 'DATE_TO_DATE_STR': <function Parser.<lambda>>, 'DATE_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateToDi'>>, 'DATE_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateTrunc'>>, 'DATETIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeAdd'>>, 'DATETIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeDiff'>>, 'DATETIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeSub'>>, 'DATETIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeTrunc'>>, 'DAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Day'>>, 'DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAYOFMONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAY_OF_WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAYOFWEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAY_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DAYOFYEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DECODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Decode'>>, 'DI_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DiToDate'>>, 'ENCODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Encode'>>, 'EXP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Exp'>>, 'EXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Explode'>>, 'EXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ExplodeOuter'>>, 'EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Extract'>>, 'FIRST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.First'>>, 'FIRST_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FirstValue'>>, 'FLATTEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Flatten'>>, 'FLOOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Floor'>>, 'FROM_BASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase'>>, 'FROM_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase64'>>, 'GENERATE_DATE_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GenerateDateArray'>>, 'GENERATE_SERIES': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GenerateSeries'>>, 'GREATEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Greatest'>>, 'GROUP_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GroupConcat'>>, 'HEX': <function build_hex>, 'HLL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Hll'>>, 'IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'IIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'INITCAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Initcap'>>, 'IS_INF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'ISINF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'IS_NAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'ISNAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'J_S_O_N_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArray'>>, 'J_S_O_N_ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArrayAgg'>>, 'JSON_ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArrayContains'>>, 'JSONB_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONBExtract'>>, 'JSONB_EXTRACT_SCALAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONBExtractScalar'>>, 'JSON_EXTRACT': <function build_extract_json_with_path.<locals>._builder>, 'JSON_EXTRACT_SCALAR': <function build_extract_json_with_path.<locals>._builder>, 'JSON_FORMAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONFormat'>>, 'J_S_O_N_OBJECT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONObject'>>, 'J_S_O_N_OBJECT_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONObjectAgg'>>, 'J_S_O_N_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONTable'>>, 'LAG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lag'>>, 'LAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Last'>>, 'LAST_DAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastDay'>>, 'LAST_DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastDay'>>, 'LAST_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastValue'>>, 'LEAD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lead'>>, 'LEAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Least'>>, 'LEFT': <function _build_with_arg_as_text.<locals>._parse>, 'LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Length'>>, 'LEN': <function _build_with_arg_as_text.<locals>._parse>, 'LEVENSHTEIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Levenshtein'>>, 'LN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ln'>>, 'LOG': <function build_logarithm>, 'LOGICAL_AND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'BOOL_AND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'BOOLAND_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'LOGICAL_OR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'BOOL_OR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'BOOLOR_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalOr'>>, 'LOWER': <function build_lower>, 'LCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lower'>>, 'LOWER_HEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LowerHex'>>, 'MD5': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MD5'>>, 'MD5_DIGEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MD5Digest'>>, 'MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Map'>>, 'MAP_FROM_ENTRIES': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MapFromEntries'>>, 'MATCH_AGAINST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MatchAgainst'>>, 'MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Max'>>, 'MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Min'>>, 'MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Month'>>, 'MONTHS_BETWEEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.MonthsBetween'>>, 'NEXT_VALUE_FOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NextValueFor'>>, 'NTH_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NthValue'>>, 'NULLIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Nullif'>>, 'NUMBER_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.NumberToStr'>>, 'NVL2': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Nvl2'>>, 'OPEN_J_S_O_N': <bound method Func.from_arg_list of <class 'sqlglot.expressions.OpenJSON'>>, 'PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParameterizedAgg'>>, 'PARSE_JSON': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParseJSON'>>, 'JSON_PARSE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ParseJSON'>>, 'PERCENTILE_CONT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PercentileCont'>>, 'PERCENTILE_DISC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PercentileDisc'>>, 'POSEXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Posexplode'>>, 'POSEXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.PosexplodeOuter'>>, 'POWER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Pow'>>, 'POW': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Pow'>>, 'PREDICT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Predict'>>, 'QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quantile'>>, 'QUARTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Quarter'>>, 'RAND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'RANDOM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'RANDN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Randn'>>, 'RANGE_N': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RangeN'>>, 'READ_CSV': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ReadCSV'>>, 'REDUCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Reduce'>>, 'REGEXP_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpExtract'>>, 'REGEXP_I_LIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpILike'>>, 'REGEXP_LIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpLike'>>, 'REGEXP_REPLACE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpReplace'>>, 'REGEXP_SPLIT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpSplit'>>, 'REPEAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Repeat'>>, 'RIGHT': <function _build_with_arg_as_text.<locals>._parse>, 'ROUND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Round'>>, 'ROW_NUMBER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RowNumber'>>, 'SHA': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA'>>, 'SHA1': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA'>>, 'SHA2': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SHA2'>>, 'SAFE_DIVIDE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SafeDivide'>>, 'SIGN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sign'>>, 'SIGNUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sign'>>, 'SORT_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.SortArray'>>, 'SPLIT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Split'>>, 'SQRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sqrt'>>, 'STANDARD_HASH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StandardHash'>>, 'STAR_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StarMap'>>, 'STARTS_WITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STARTSWITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STDDEV': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stddev'>>, 'STDDEV_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StddevPop'>>, 'STDDEV_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StddevSamp'>>, 'STR_POSITION': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrPosition'>>, 'STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToDate'>>, 'STR_TO_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToMap'>>, 'STR_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToTime'>>, 'STR_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToUnix'>>, 'STRUCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Struct'>>, 'STRUCT_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StructExtract'>>, 'STUFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stuff'>>, 'INSERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stuff'>>, 'SUBSTRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Substring'>>, 'SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sum'>>, 'TIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeAdd'>>, 'TIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeDiff'>>, 'TIME_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeFromParts'>>, 'TIMEFROMPARTS': <function _build_timefromparts>, 'TIME_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToDate'>>, 'TIME_STR_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToTime'>>, 'TIME_STR_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeStrToUnix'>>, 'TIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeSub'>>, 'TIME_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeToStr'>>, 'TIME_TO_TIME_STR': <function Parser.<lambda>>, 'TIME_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeToUnix'>>, 'TIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeTrunc'>>, 'TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Timestamp'>>, 'TIMESTAMP_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampAdd'>>, 'TIMESTAMPDIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampDiff'>>, 'TIMESTAMP_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampDiff'>>, 'TIMESTAMP_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampFromParts'>>, 'TIMESTAMPFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampFromParts'>>, 'TIMESTAMP_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampSub'>>, 'TIMESTAMP_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampTrunc'>>, 'TO_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToArray'>>, 'TO_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToBase64'>>, 'TO_CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToChar'>>, 'TO_DAYS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToDays'>>, 'TO_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToMap'>>, 'TO_NUMBER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToNumber'>>, 'TRANSFORM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Transform'>>, 'TRIM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Trim'>>, 'TRY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Try'>>, 'TRY_CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TryCast'>>, 'TS_OR_DI_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDiToDi'>>, 'TS_OR_DS_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsAdd'>>, 'TS_OR_DS_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsDiff'>>, 'TS_OR_DS_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToDate'>>, 'TS_OR_DS_TO_DATE_STR': <function Parser.<lambda>>, 'TS_OR_DS_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTime'>>, 'TS_OR_DS_TO_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTimestamp'>>, 'UNHEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Unhex'>>, 'UNIX_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixDate'>>, 'UNIX_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToStr'>>, 'UNIX_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTime'>>, 'UNIX_TO_TIME_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTimeStr'>>, 'UPPER': <function build_upper>, 'UCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Upper'>>, 'VAR_MAP': <function build_var_map>, 'VARIANCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'VAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Week'>>, 'WEEK_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.WeekOfYear'>>, 'WEEKOFYEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.WeekOfYear'>>, 'WHEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.When'>>, 'X_M_L_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.XMLTable'>>, 'XOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Xor'>>, 'YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Year'>>, 'GLOB': <function Parser.<lambda>>, 'JSON_EXTRACT_PATH_TEXT': <function build_extract_json_with_path.<locals>._builder>, 'LIKE': <function build_like>, 'LOG2': <function Parser.<lambda>>, 'LOG10': <function Parser.<lambda>>, 'MOD': <function build_mod>, 'TO_HEX': <function build_hex>, 'CHARINDEX': <function TSQL.Parser.<lambda>>, 'DATEADD': <function build_date_delta.<locals>._builder>, 'DATENAME': <function _build_formatted_time.<locals>._builder>, 'DATEPART': <function _build_formatted_time.<locals>._builder>, 'DATETIMEFROMPARTS': <function _build_datetimefromparts>, 'EOMONTH': <function _build_eomonth>, 'FORMAT': <function _build_format>, 'GETDATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTimestamp'>>, 'HASHBYTES': <function _build_hashbytes>, 'ISNULL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'JSON_QUERY': <function build_extract_json_with_path.<locals>._builder>, 'JSON_VALUE': <function build_extract_json_with_path.<locals>._builder>, 'REPLICATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Repeat'>>, 'SQUARE': <function TSQL.Parser.<lambda>>, 'SYSDATETIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTimestamp'>>, 'SUSER_NAME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentUser'>>, 'SUSER_SNAME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentUser'>>, 'SYSTEM_USER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentUser'>>}"}, "sqlglot.dialects.tsql.TSQL.Parser.JOIN_HINTS": {"fullname": "sqlglot.dialects.tsql.TSQL.Parser.JOIN_HINTS", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Parser.JOIN_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'LOOP', 'MERGE', 'HASH', 'REMOTE'}"}, "sqlglot.dialects.tsql.TSQL.Parser.RETURNS_TABLE_TOKENS": {"fullname": "sqlglot.dialects.tsql.TSQL.Parser.RETURNS_TABLE_TOKENS", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Parser.RETURNS_TABLE_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.KILL: 'KILL'>, <TokenType.COPY: 'COPY'>, <TokenType.PERCENT: 'PERCENT'>, <TokenType.TAG: 'TAG'>, <TokenType.VOLATILE: 'VOLATILE'>, <TokenType.IDENTIFIER: 'IDENTIFIER'>, <TokenType.ASC: 'ASC'>, <TokenType.ISNULL: 'ISNULL'>, <TokenType.TEMPORARY: 'TEMPORARY'>, <TokenType.PROCEDURE: 'PROCEDURE'>, <TokenType.SCHEMA: 'SCHEMA'>, <TokenType.VIEW: 'VIEW'>, <TokenType.BEGIN: 'BEGIN'>, <TokenType.INDEX: 'INDEX'>, <TokenType.PARTITION: 'PARTITION'>, <TokenType.CACHE: 'CACHE'>, <TokenType.OPERATOR: 'OPERATOR'>, <TokenType.COLUMN: 'COLUMN'>, <TokenType.UNPIVOT: 'UNPIVOT'>, <TokenType.COMMIT: 'COMMIT'>, <TokenType.EXISTS: 'EXISTS'>, <TokenType.RECURSIVE: 'RECURSIVE'>, <TokenType.SET: 'SET'>, <TokenType.REFRESH: 'REFRESH'>, <TokenType.SHOW: 'SHOW'>, <TokenType.DEFAULT: 'DEFAULT'>, <TokenType.MERGE: 'MERGE'>, <TokenType.FIRST: 'FIRST'>, <TokenType.EXECUTE: 'EXECUTE'>, <TokenType.PRAGMA: 'PRAGMA'>, <TokenType.APPLY: 'APPLY'>, <TokenType.STORAGE_INTEGRATION: 'STORAGE_INTEGRATION'>, <TokenType.ASOF: 'ASOF'>, <TokenType.WINDOW: 'WINDOW'>, <TokenType.RIGHT: 'RIGHT'>, <TokenType.FALSE: 'FALSE'>, <TokenType.LEFT: 'LEFT'>, <TokenType.TOP: 'TOP'>, <TokenType.FUNCTION: 'FUNCTION'>, <TokenType.CASE: 'CASE'>, <TokenType.ROLLUP: 'ROLLUP'>, <TokenType.VAR: 'VAR'>, <TokenType.COMMAND: 'COMMAND'>, <TokenType.LOAD: 'LOAD'>, <TokenType.TRUNCATE: 'TRUNCATE'>, <TokenType.KEEP: 'KEEP'>, <TokenType.END: 'END'>, <TokenType.REFERENCES: 'REFERENCES'>, <TokenType.REPLACE: 'REPLACE'>, <TokenType.RANGE: 'RANGE'>, <TokenType.TRUE: 'TRUE'>, <TokenType.USE: 'USE'>, <TokenType.OVERLAPS: 'OVERLAPS'>, <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, <TokenType.UNIQUE: 'UNIQUE'>, <TokenType.ORDINALITY: 'ORDINALITY'>, <TokenType.DATABASE: 'DATABASE'>, <TokenType.NEXT: 'NEXT'>, <TokenType.IS: 'IS'>, <TokenType.CONSTRAINT: 'CONSTRAINT'>, <TokenType.FINAL: 'FINAL'>, <TokenType.SETTINGS: 'SETTINGS'>, <TokenType.ROWS: 'ROWS'>, <TokenType.SEMI: 'SEMI'>, <TokenType.DELETE: 'DELETE'>, <TokenType.DESC: 'DESC'>, <TokenType.OFFSET: 'OFFSET'>, <TokenType.ANY: 'ANY'>, <TokenType.DICTIONARY: 'DICTIONARY'>, <TokenType.DIV: 'DIV'>, <TokenType.COMMENT: 'COMMENT'>, <TokenType.CURRENT_USER: 'CURRENT_USER'>, <TokenType.ALL: 'ALL'>, <TokenType.SOME: 'SOME'>, <TokenType.FULL: 'FULL'>, <TokenType.FORMAT: 'FORMAT'>, <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, <TokenType.OVERWRITE: 'OVERWRITE'>, <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>, <TokenType.COLLATE: 'COLLATE'>, <TokenType.FILTER: 'FILTER'>, <TokenType.ROW: 'ROW'>, <TokenType.NATURAL: 'NATURAL'>, <TokenType.ESCAPE: 'ESCAPE'>, <TokenType.PIVOT: 'PIVOT'>, <TokenType.UPDATE: 'UPDATE'>, <TokenType.MODEL: 'MODEL'>, <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, <TokenType.SEQUENCE: 'SEQUENCE'>, <TokenType.DESCRIBE: 'DESCRIBE'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, <TokenType.ANTI: 'ANTI'>}"}, "sqlglot.dialects.tsql.TSQL.Parser.STATEMENT_PARSERS": {"fullname": "sqlglot.dialects.tsql.TSQL.Parser.STATEMENT_PARSERS", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Parser.STATEMENT_PARSERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.ALTER: 'ALTER'>: <function Parser.<lambda>>, <TokenType.BEGIN: 'BEGIN'>: <function Parser.<lambda>>, <TokenType.CACHE: 'CACHE'>: <function Parser.<lambda>>, <TokenType.COMMENT: 'COMMENT'>: <function Parser.<lambda>>, <TokenType.COMMIT: 'COMMIT'>: <function Parser.<lambda>>, <TokenType.COPY: 'COPY'>: <function Parser.<lambda>>, <TokenType.CREATE: 'CREATE'>: <function Parser.<lambda>>, <TokenType.DELETE: 'DELETE'>: <function Parser.<lambda>>, <TokenType.DESC: 'DESC'>: <function Parser.<lambda>>, <TokenType.DESCRIBE: 'DESCRIBE'>: <function Parser.<lambda>>, <TokenType.DROP: 'DROP'>: <function Parser.<lambda>>, <TokenType.INSERT: 'INSERT'>: <function Parser.<lambda>>, <TokenType.KILL: 'KILL'>: <function Parser.<lambda>>, <TokenType.LOAD: 'LOAD'>: <function Parser.<lambda>>, <TokenType.MERGE: 'MERGE'>: <function Parser.<lambda>>, <TokenType.PIVOT: 'PIVOT'>: <function Parser.<lambda>>, <TokenType.PRAGMA: 'PRAGMA'>: <function Parser.<lambda>>, <TokenType.REFRESH: 'REFRESH'>: <function Parser.<lambda>>, <TokenType.ROLLBACK: 'ROLLBACK'>: <function Parser.<lambda>>, <TokenType.SET: 'SET'>: <function Parser.<lambda>>, <TokenType.TRUNCATE: 'TRUNCATE'>: <function Parser.<lambda>>, <TokenType.UNCACHE: 'UNCACHE'>: <function Parser.<lambda>>, <TokenType.UPDATE: 'UPDATE'>: <function Parser.<lambda>>, <TokenType.USE: 'USE'>: <function Parser.<lambda>>, <TokenType.SEMICOLON: 'SEMICOLON'>: <function Parser.<lambda>>, <TokenType.DECLARE: 'DECLARE'>: <function TSQL.Parser.<lambda>>}"}, "sqlglot.dialects.tsql.TSQL.Parser.TABLE_ALIAS_TOKENS": {"fullname": "sqlglot.dialects.tsql.TSQL.Parser.TABLE_ALIAS_TOKENS", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Parser.TABLE_ALIAS_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.KILL: 'KILL'>, <TokenType.MONEY: 'MONEY'>, <TokenType.COPY: 'COPY'>, <TokenType.PERCENT: 'PERCENT'>, <TokenType.TAG: 'TAG'>, <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, <TokenType.VOLATILE: 'VOLATILE'>, <TokenType.IDENTIFIER: 'IDENTIFIER'>, <TokenType.VARBINARY: 'VARBINARY'>, <TokenType.HSTORE: 'HSTORE'>, <TokenType.ASC: 'ASC'>, <TokenType.IPADDRESS: 'IPADDRESS'>, <TokenType.ISNULL: 'ISNULL'>, <TokenType.TEMPORARY: 'TEMPORARY'>, <TokenType.PROCEDURE: 'PROCEDURE'>, <TokenType.SCHEMA: 'SCHEMA'>, <TokenType.NUMRANGE: 'NUMRANGE'>, <TokenType.DATE32: 'DATE32'>, <TokenType.INT8RANGE: 'INT8RANGE'>, <TokenType.ANTI: 'ANTI'>, <TokenType.AGGREGATEFUNCTION: 'AGGREGATEFUNCTION'>, <TokenType.VIEW: 'VIEW'>, <TokenType.VARCHAR: 'VARCHAR'>, <TokenType.TIMETZ: 'TIMETZ'>, <TokenType.GEOMETRY: 'GEOMETRY'>, <TokenType.BEGIN: 'BEGIN'>, <TokenType.ENUM8: 'ENUM8'>, <TokenType.INDEX: 'INDEX'>, <TokenType.PARTITION: 'PARTITION'>, <TokenType.UINT256: 'UINT256'>, <TokenType.BIGINT: 'BIGINT'>, <TokenType.CACHE: 'CACHE'>, <TokenType.OPERATOR: 'OPERATOR'>, <TokenType.COLUMN: 'COLUMN'>, <TokenType.INT128: 'INT128'>, <TokenType.SMALLMONEY: 'SMALLMONEY'>, <TokenType.HLLSKETCH: 'HLLSKETCH'>, <TokenType.UNPIVOT: 'UNPIVOT'>, <TokenType.SMALLINT: 'SMALLINT'>, <TokenType.INT256: 'INT256'>, <TokenType.FLOAT: 'FLOAT'>, <TokenType.COMMIT: 'COMMIT'>, <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, <TokenType.EXISTS: 'EXISTS'>, <TokenType.NULL: 'NULL'>, <TokenType.RECURSIVE: 'RECURSIVE'>, <TokenType.SET: 'SET'>, <TokenType.NULLABLE: 'NULLABLE'>, <TokenType.REFRESH: 'REFRESH'>, <TokenType.TINYTEXT: 'TINYTEXT'>, <TokenType.SHOW: 'SHOW'>, <TokenType.DEFAULT: 'DEFAULT'>, <TokenType.DATE: 'DATE'>, <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <TokenType.MERGE: 'MERGE'>, <TokenType.FIRST: 'FIRST'>, <TokenType.BINARY: 'BINARY'>, <TokenType.ARRAY: 'ARRAY'>, <TokenType.SERIAL: 'SERIAL'>, <TokenType.EXECUTE: 'EXECUTE'>, <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, <TokenType.INTERVAL: 'INTERVAL'>, <TokenType.PRAGMA: 'PRAGMA'>, <TokenType.STORAGE_INTEGRATION: 'STORAGE_INTEGRATION'>, <TokenType.BPCHAR: 'BPCHAR'>, <TokenType.BIT: 'BIT'>, <TokenType.UINT: 'UINT'>, <TokenType.UUID: 'UUID'>, <TokenType.STRUCT: 'STRUCT'>, <TokenType.FALSE: 'FALSE'>, <TokenType.FUNCTION: 'FUNCTION'>, <TokenType.TOP: 'TOP'>, <TokenType.SUPER: 'SUPER'>, <TokenType.CASE: 'CASE'>, <TokenType.IMAGE: 'IMAGE'>, <TokenType.UBIGINT: 'UBIGINT'>, <TokenType.LONGBLOB: 'LONGBLOB'>, <TokenType.ROLLUP: 'ROLLUP'>, <TokenType.VAR: 'VAR'>, <TokenType.COMMAND: 'COMMAND'>, <TokenType.LOAD: 'LOAD'>, <TokenType.TRUNCATE: 'TRUNCATE'>, <TokenType.KEEP: 'KEEP'>, <TokenType.UMEDIUMINT: 'UMEDIUMINT'>, <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, <TokenType.UINT128: 'UINT128'>, <TokenType.END: 'END'>, <TokenType.MAP: 'MAP'>, <TokenType.IPV4: 'IPV4'>, <TokenType.USERDEFINED: 'USERDEFINED'>, <TokenType.REFERENCES: 'REFERENCES'>, <TokenType.REPLACE: 'REPLACE'>, <TokenType.RANGE: 'RANGE'>, <TokenType.NVARCHAR: 'NVARCHAR'>, <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, <TokenType.TRUE: 'TRUE'>, <TokenType.TIMESTAMP_MS: 'TIMESTAMP_MS'>, <TokenType.VARIANT: 'VARIANT'>, <TokenType.ENUM: 'ENUM'>, <TokenType.USE: 'USE'>, <TokenType.USMALLINT: 'USMALLINT'>, <TokenType.OVERLAPS: 'OVERLAPS'>, <TokenType.TIMESTAMP_S: 'TIMESTAMP_S'>, <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, <TokenType.UNIQUE: 'UNIQUE'>, <TokenType.ORDINALITY: 'ORDINALITY'>, <TokenType.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>, <TokenType.TEXT: 'TEXT'>, <TokenType.DATABASE: 'DATABASE'>, <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, <TokenType.PSEUDO_TYPE: 'PSEUDO_TYPE'>, <TokenType.FIXEDSTRING: 'FIXEDSTRING'>, <TokenType.NEXT: 'NEXT'>, <TokenType.INT: 'INT'>, <TokenType.BIGSERIAL: 'BIGSERIAL'>, <TokenType.BOOLEAN: 'BOOLEAN'>, <TokenType.IS: 'IS'>, <TokenType.CONSTRAINT: 'CONSTRAINT'>, <TokenType.FINAL: 'FINAL'>, <TokenType.UNKNOWN: 'UNKNOWN'>, <TokenType.SETTINGS: 'SETTINGS'>, <TokenType.ROWS: 'ROWS'>, <TokenType.TSTZRANGE: 'TSTZRANGE'>, <TokenType.DATETIME64: 'DATETIME64'>, <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, <TokenType.DATETIME: 'DATETIME'>, <TokenType.MEDIUMINT: 'MEDIUMINT'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>, <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, <TokenType.XML: 'XML'>, <TokenType.JSON: 'JSON'>, <TokenType.UTINYINT: 'UTINYINT'>, <TokenType.DELETE: 'DELETE'>, <TokenType.TIME: 'TIME'>, <TokenType.UDECIMAL: 'UDECIMAL'>, <TokenType.NESTED: 'NESTED'>, <TokenType.SEMI: 'SEMI'>, <TokenType.DESC: 'DESC'>, <TokenType.ROWVERSION: 'ROWVERSION'>, <TokenType.TIMESTAMP_NS: 'TIMESTAMP_NS'>, <TokenType.ANY: 'ANY'>, <TokenType.DIV: 'DIV'>, <TokenType.DICTIONARY: 'DICTIONARY'>, <TokenType.INET: 'INET'>, <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, <TokenType.COMMENT: 'COMMENT'>, <TokenType.CURRENT_USER: 'CURRENT_USER'>, <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>, <TokenType.ALL: 'ALL'>, <TokenType.NAME: 'NAME'>, <TokenType.SOME: 'SOME'>, <TokenType.ENUM16: 'ENUM16'>, <TokenType.YEAR: 'YEAR'>, <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, <TokenType.DOUBLE: 'DOUBLE'>, <TokenType.INT4RANGE: 'INT4RANGE'>, <TokenType.FORMAT: 'FORMAT'>, <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, <TokenType.IPPREFIX: 'IPPREFIX'>, <TokenType.OVERWRITE: 'OVERWRITE'>, <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>, <TokenType.COLLATE: 'COLLATE'>, <TokenType.FILTER: 'FILTER'>, <TokenType.JSONB: 'JSONB'>, <TokenType.TDIGEST: 'TDIGEST'>, <TokenType.CHAR: 'CHAR'>, <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.ROW: 'ROW'>, <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.TABLE: 'TABLE'>, <TokenType.DATERANGE: 'DATERANGE'>, <TokenType.TSRANGE: 'TSRANGE'>, <TokenType.ESCAPE: 'ESCAPE'>, <TokenType.PIVOT: 'PIVOT'>, <TokenType.DECIMAL: 'DECIMAL'>, <TokenType.NCHAR: 'NCHAR'>, <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, <TokenType.UPDATE: 'UPDATE'>, <TokenType.MODEL: 'MODEL'>, <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, <TokenType.SEQUENCE: 'SEQUENCE'>, <TokenType.LONGTEXT: 'LONGTEXT'>, <TokenType.DESCRIBE: 'DESCRIBE'>, <TokenType.IPV6: 'IPV6'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, <TokenType.TINYINT: 'TINYINT'>, <TokenType.TINYBLOB: 'TINYBLOB'>}"}, "sqlglot.dialects.tsql.TSQL.Parser.SHOW_TRIE": {"fullname": "sqlglot.dialects.tsql.TSQL.Parser.SHOW_TRIE", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Parser.SHOW_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.dialects.tsql.TSQL.Parser.SET_TRIE": {"fullname": "sqlglot.dialects.tsql.TSQL.Parser.SET_TRIE", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Parser.SET_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'GLOBAL': {0: True}, 'LOCAL': {0: True}, 'SESSION': {0: True}, 'TRANSACTION': {0: True}}"}, "sqlglot.dialects.tsql.TSQL.Generator": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator", "kind": "class", "doc": "<p>Generator converts a given syntax tree to the corresponding SQL string.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>pretty:</strong> Whether to format the produced SQL string.\nDefault: False.</li>\n<li><strong>identify:</strong> Determines when an identifier should be quoted. Possible values are:\nFalse (default): Never quote, except in cases where it's mandatory by the dialect.\nTrue or 'always': Always quote.\n'safe': Only quote identifiers that are case insensitive.</li>\n<li><strong>normalize:</strong> Whether to normalize identifiers to lowercase.\nDefault: False.</li>\n<li><strong>pad:</strong> The pad size in a formatted string. For example, this affects the indentation of\na projection in a query, relative to its nesting level.\nDefault: 2.</li>\n<li><strong>indent:</strong> The indentation size in a formatted string. For example, this affects the\nindentation of subqueries and filters under a <code>WHERE</code> clause.\nDefault: 2.</li>\n<li><strong>normalize_functions:</strong> How to normalize function names. Possible values are:\n\"upper\" or True (default): Convert names to uppercase.\n\"lower\": Convert names to lowercase.\nFalse: Disables function name normalization.</li>\n<li><strong>unsupported_level:</strong> Determines the generator's behavior when it encounters unsupported expressions.\nDefault ErrorLevel.WARN.</li>\n<li><strong>max_unsupported:</strong> Maximum number of unsupported messages to include in a raised UnsupportedError.\nThis is only relevant if unsupported_level is ErrorLevel.RAISE.\nDefault: 3</li>\n<li><strong>leading_comma:</strong> Whether the comma is leading or trailing in select expressions.\nThis is only relevant when generating in pretty mode.\nDefault: False</li>\n<li><strong>max_text_width:</strong> The max number of characters in a segment before creating new lines in pretty mode.\nThe default is on the smaller end because the length only represents a segment and not the true\nline length.\nDefault: 80</li>\n<li><strong>comments:</strong> Whether to preserve comments in the output SQL code.\nDefault: True</li>\n</ul>\n", "bases": "sqlglot.generator.Generator"}, "sqlglot.dialects.tsql.TSQL.Generator.LIMIT_IS_TOP": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.LIMIT_IS_TOP", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.LIMIT_IS_TOP", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.tsql.TSQL.Generator.QUERY_HINTS": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.QUERY_HINTS", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.QUERY_HINTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.tsql.TSQL.Generator.RETURNING_END": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.RETURNING_END", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.RETURNING_END", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.tsql.TSQL.Generator.NVL2_SUPPORTED": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.NVL2_SUPPORTED", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.NVL2_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.tsql.TSQL.Generator.ALTER_TABLE_INCLUDE_COLUMN_KEYWORD": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.ALTER_TABLE_INCLUDE_COLUMN_KEYWORD", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.ALTER_TABLE_INCLUDE_COLUMN_KEYWORD", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.tsql.TSQL.Generator.LIMIT_FETCH": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.LIMIT_FETCH", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.LIMIT_FETCH", "kind": "variable", "doc": "<p></p>\n", "default_value": "'FETCH'"}, "sqlglot.dialects.tsql.TSQL.Generator.COMPUTED_COLUMN_WITH_TYPE": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.COMPUTED_COLUMN_WITH_TYPE", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.COMPUTED_COLUMN_WITH_TYPE", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.tsql.TSQL.Generator.CTE_RECURSIVE_KEYWORD_REQUIRED": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.CTE_RECURSIVE_KEYWORD_REQUIRED", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.CTE_RECURSIVE_KEYWORD_REQUIRED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.tsql.TSQL.Generator.ENSURE_BOOLS": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.ENSURE_BOOLS", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.ENSURE_BOOLS", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.tsql.TSQL.Generator.NULL_ORDERING_SUPPORTED": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.NULL_ORDERING_SUPPORTED", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.NULL_ORDERING_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "None"}, "sqlglot.dialects.tsql.TSQL.Generator.SUPPORTS_SINGLE_ARG_CONCAT": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.SUPPORTS_SINGLE_ARG_CONCAT", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.SUPPORTS_SINGLE_ARG_CONCAT", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.tsql.TSQL.Generator.TABLESAMPLE_SEED_KEYWORD": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.TABLESAMPLE_SEED_KEYWORD", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.TABLESAMPLE_SEED_KEYWORD", "kind": "variable", "doc": "<p></p>\n", "default_value": "'REPEATABLE'"}, "sqlglot.dialects.tsql.TSQL.Generator.SUPPORTS_SELECT_INTO": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.SUPPORTS_SELECT_INTO", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.SUPPORTS_SELECT_INTO", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.tsql.TSQL.Generator.JSON_PATH_BRACKETED_KEY_SUPPORTED": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.JSON_PATH_BRACKETED_KEY_SUPPORTED", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.JSON_PATH_BRACKETED_KEY_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.tsql.TSQL.Generator.SUPPORTS_TO_NUMBER": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.SUPPORTS_TO_NUMBER", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.SUPPORTS_TO_NUMBER", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.tsql.TSQL.Generator.OUTER_UNION_MODIFIERS": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.OUTER_UNION_MODIFIERS", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.OUTER_UNION_MODIFIERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.tsql.TSQL.Generator.COPY_PARAMS_EQ_REQUIRED": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.COPY_PARAMS_EQ_REQUIRED", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.COPY_PARAMS_EQ_REQUIRED", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.dialects.tsql.TSQL.Generator.EXPRESSIONS_WITHOUT_NESTED_CTES": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.EXPRESSIONS_WITHOUT_NESTED_CTES", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.EXPRESSIONS_WITHOUT_NESTED_CTES", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.Select'>, <class 'sqlglot.expressions.Insert'>, <class 'sqlglot.expressions.Union'>, <class 'sqlglot.expressions.Subquery'>, <class 'sqlglot.expressions.Merge'>, <class 'sqlglot.expressions.Update'>, <class 'sqlglot.expressions.Delete'>}"}, "sqlglot.dialects.tsql.TSQL.Generator.SUPPORTED_JSON_PATH_PARTS": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.SUPPORTED_JSON_PATH_PARTS", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.SUPPORTED_JSON_PATH_PARTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.JSONPathSubscript'>, <class 'sqlglot.expressions.JSONPathRoot'>, <class 'sqlglot.expressions.JSONPathKey'>}"}, "sqlglot.dialects.tsql.TSQL.Generator.TYPE_MAPPING": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.TYPE_MAPPING", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.TYPE_MAPPING", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.MEDIUMTEXT: 'MEDIUMTEXT'>: 'TEXT', <Type.LONGTEXT: 'LONGTEXT'>: 'TEXT', <Type.TINYTEXT: 'TINYTEXT'>: 'TEXT', <Type.MEDIUMBLOB: 'MEDIUMBLOB'>: 'BLOB', <Type.LONGBLOB: 'LONGBLOB'>: 'BLOB', <Type.TINYBLOB: 'TINYBLOB'>: 'BLOB', <Type.INET: 'INET'>: 'INET', <Type.ROWVERSION: 'ROWVERSION'>: 'ROWVERSION', <Type.BOOLEAN: 'BOOLEAN'>: 'BIT', <Type.DECIMAL: 'DECIMAL'>: 'NUMERIC', <Type.DATETIME: 'DATETIME'>: 'DATETIME2', <Type.DOUBLE: 'DOUBLE'>: 'FLOAT', <Type.INT: 'INT'>: 'INTEGER', <Type.TEXT: 'TEXT'>: 'VARCHAR(MAX)', <Type.TIMESTAMP: 'TIMESTAMP'>: 'DATETIME2', <Type.TIMESTAMPTZ: 'TIMESTAMPTZ'>: 'DATETIMEOFFSET', <Type.UTINYINT: 'UTINYINT'>: 'TINYINT', <Type.VARIANT: 'VARIANT'>: 'SQL_VARIANT'}"}, "sqlglot.dialects.tsql.TSQL.Generator.TRANSFORMS": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.TRANSFORMS", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.JSONPathKey'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRoot'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSubscript'>: <function <lambda>>, <class 'sqlglot.expressions.AllowedValuesProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.BackupProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CaseSpecificColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CollateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CommentColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DateFormatColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DefaultColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EncodeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EphemeralColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExcludeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExternalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.GlobalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.HeapProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IcebergProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InheritsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InlineLengthColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IntervalSpan'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtract'>: <function _json_extract_sql>, <class 'sqlglot.expressions.JSONExtractScalar'>: <function _json_extract_sql>, <class 'sqlglot.expressions.LanguageProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LocationProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LogProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.MaterializedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NonClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NotForReplicationColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnCommitProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnUpdateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OutputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.PathColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SampleProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetConfigProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SettingsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SharingProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlReadWriteProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.SqlSecurityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StabilityProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.StrictProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TemporaryProperty'>: <function TSQL.Generator.<lambda>>, <class 'sqlglot.expressions.TitleColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.Timestamp'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransformModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransientProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UppercaseColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UnloggedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VarMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VolatileProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithOperator'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.AnyValue'>: <function any_value_to_max_sql>, <class 'sqlglot.expressions.ArrayToString'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.AutoIncrementColumnConstraint'>: <function TSQL.Generator.<lambda>>, <class 'sqlglot.expressions.DateAdd'>: <function date_delta_sql.<locals>._delta_sql>, <class 'sqlglot.expressions.DateDiff'>: <function date_delta_sql.<locals>._delta_sql>, <class 'sqlglot.expressions.CTE'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.CurrentDate'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.CurrentTimestamp'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.DateStrToDate'>: <function datestrtodate_sql>, <class 'sqlglot.expressions.Extract'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.GeneratedAsIdentityColumnConstraint'>: <function generatedasidentitycolumnconstraint_sql>, <class 'sqlglot.expressions.GroupConcat'>: <function _string_agg_sql>, <class 'sqlglot.expressions.If'>: <function rename_func.<locals>.<lambda>>, <class 'sqlglot.expressions.LastDay'>: <function TSQL.Generator.<lambda>>, <class 'sqlglot.expressions.Max'>: <function max_or_greatest>, <class 'sqlglot.expressions.MD5'>: <function TSQL.Generator.<lambda>>, <class 'sqlglot.expressions.Min'>: <function min_or_least>, <class 'sqlglot.expressions.NumberToStr'>: <function _format_sql>, <class 'sqlglot.expressions.ParseJSON'>: <function TSQL.Generator.<lambda>>, <class 'sqlglot.expressions.Select'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.StrPosition'>: <function TSQL.Generator.<lambda>>, <class 'sqlglot.expressions.Subquery'>: <function preprocess.<locals>._to_sql>, <class 'sqlglot.expressions.SHA'>: <function TSQL.Generator.<lambda>>, <class 'sqlglot.expressions.SHA2'>: <function TSQL.Generator.<lambda>>, <class 'sqlglot.expressions.TimeStrToTime'>: <function timestrtotime_sql>, <class 'sqlglot.expressions.TimeToStr'>: <function _format_sql>, <class 'sqlglot.expressions.Trim'>: <function trim_sql>, <class 'sqlglot.expressions.TsOrDsAdd'>: <function date_delta_sql.<locals>._delta_sql>, <class 'sqlglot.expressions.TsOrDsDiff'>: <function date_delta_sql.<locals>._delta_sql>}"}, "sqlglot.dialects.tsql.TSQL.Generator.PROPERTIES_LOCATION": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.PROPERTIES_LOCATION", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.PROPERTIES_LOCATION", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.AllowedValuesProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.AlgorithmProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.AutoIncrementProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.BackupProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.BlockCompressionProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.CharacterSetProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ChecksumProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.CollateProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Cluster'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ClusteredByProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DataBlocksizeProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.DataDeletionProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DefinerProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.DictRange'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DictProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DistKeyProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DistStyleProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.EngineProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ExternalProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.FallbackProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.FileFormatProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.FreespaceProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.GlobalProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.HeapProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.InheritsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.IcebergProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.InputModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.IsolatedLoadingProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.JournalProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.LanguageProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LikeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LocationProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LockProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LockingProperty'>: <Location.POST_ALIAS: 'POST_ALIAS'>, <class 'sqlglot.expressions.LogProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.MaterializedProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.MergeBlockRatioProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.OnProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.OnCommitProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.Order'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.OutputModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.PartitionedByProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.PartitionedOfProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.PrimaryKey'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Property'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ReturnsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatDelimitedProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatSerdeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SampleProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SchemaCommentProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SerdeProperties'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Set'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SettingsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SetProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.SetConfigProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SharingProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.SequenceProperties'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.SortKeyProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SqlReadWriteProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SqlSecurityProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.StabilityProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.StrictProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.TemporaryProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.ToTableProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.TransientProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.TransformModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.MergeTreeTTL'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.UnloggedProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.VolatileProperty'>: <Location.UNSUPPORTED: 'UNSUPPORTED'>, <class 'sqlglot.expressions.WithDataProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.WithSystemVersioningProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>}"}, "sqlglot.dialects.tsql.TSQL.Generator.select_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.select_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.select_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Select</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.convert_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.convert_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.convert_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Convert</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.queryoption_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.queryoption_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.queryoption_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">QueryOption</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.lateral_op": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.lateral_op", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.lateral_op", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Lateral</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.timefromparts_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.timefromparts_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.timefromparts_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TimeFromParts</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.timestampfromparts_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.timestampfromparts_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.timestampfromparts_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TimestampFromParts</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.setitem_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.setitem_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.setitem_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">SetItem</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.boolean_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.boolean_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.boolean_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Boolean</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.is_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.is_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.is_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Is</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.createable_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.createable_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.createable_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Create</span>,</span><span class=\"param\">\t<span class=\"n\">locations</span><span class=\"p\">:</span> <span class=\"n\">DefaultDict</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.create_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.create_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.create_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Create</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.offset_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.offset_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.offset_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Offset</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.version_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.version_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.version_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Version</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.returnsproperty_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.returnsproperty_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.returnsproperty_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ReturnsProperty</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.returning_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.returning_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.returning_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Returning</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.transaction_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.transaction_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.transaction_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Transaction</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.commit_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.commit_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.commit_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Commit</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.rollback_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.rollback_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.rollback_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Rollback</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.identifier_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.identifier_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.identifier_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Identifier</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.constraint_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.constraint_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.constraint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Constraint</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.length_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.length_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.length_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Length</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.right_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.right_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.right_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Right</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.left_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.left_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.left_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Left</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.partition_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.partition_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.partition_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Partition</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.altertable_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.altertable_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.altertable_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">AlterTable</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.drop_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.drop_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.drop_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Drop</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.declare_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.declare_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.declare_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Declare</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.declareitem_sql": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.declareitem_sql", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.declareitem_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DeclareItem</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.dialects.tsql.TSQL.Generator.SELECT_KINDS": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.SELECT_KINDS", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.SELECT_KINDS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Tuple[str, ...]", "default_value": "()"}, "sqlglot.dialects.tsql.TSQL.Generator.TRY_SUPPORTED": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.TRY_SUPPORTED", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.TRY_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.dialects.tsql.TSQL.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS": {"fullname": "sqlglot.dialects.tsql.TSQL.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'qualify': <function Generator.<lambda>>, 'windows': <function Generator.<lambda>>}"}, "sqlglot.dialects.tsql.TSQL.tokenizer_class": {"fullname": "sqlglot.dialects.tsql.TSQL.tokenizer_class", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.tokenizer_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.tsql.TSQL.Tokenizer'>"}, "sqlglot.dialects.tsql.TSQL.parser_class": {"fullname": "sqlglot.dialects.tsql.TSQL.parser_class", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.parser_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.tsql.TSQL.Parser'>"}, "sqlglot.dialects.tsql.TSQL.generator_class": {"fullname": "sqlglot.dialects.tsql.TSQL.generator_class", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.generator_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.dialects.tsql.TSQL.Generator'>"}, "sqlglot.dialects.tsql.TSQL.TIME_TRIE": {"fullname": "sqlglot.dialects.tsql.TSQL.TIME_TRIE", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'y': {'e': {'a': {'r': {0: True}}}, 0: True, 'y': {'y': {'y': {0: True}}, 0: True}}, 'd': {'a': {'y': {'o': {'f': {'y': {'e': {'a': {'r': {0: True}}}}}}, 0: True}}, 'y': {0: True}, 'w': {0: True}, 'd': {'d': {'d': {0: True}}, 0: True}, 0: True}, 'w': {'e': {'e': {'k': {0: True, 'd': {'a': {'y': {0: True}}}}}}, 'w': {0: True}, 'k': {0: True}}, 'h': {'o': {'u': {'r': {0: True}}}, 'h': {0: True}, 0: True}, 'm': {'i': {'n': {'u': {'t': {'e': {0: True}}}}, 0: True, 'l': {'l': {'i': {'s': {'e': {'c': {'o': {'n': {'d': {0: True}}}}}}}}}}, 's': {0: True}, 'o': {'n': {'t': {'h': {0: True}}}}, 'm': {0: True}, 0: True}, 'n': {0: True}, 's': {'e': {'c': {'o': {'n': {'d': {0: True}}}}}, 's': {0: True}, 0: True}, 'Y': {0: True, 'Y': {'Y': {'Y': {0: True}}, 0: True}}, 'M': {'M': {'M': {'M': {0: True}, 0: True}, 0: True}, 0: True}, 'H': {'H': {0: True}, 0: True}, 'S': {0: True}}"}, "sqlglot.dialects.tsql.TSQL.FORMAT_TRIE": {"fullname": "sqlglot.dialects.tsql.TSQL.FORMAT_TRIE", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.FORMAT_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'y': {'e': {'a': {'r': {0: True}}}, 0: True, 'y': {'y': {'y': {0: True}}, 0: True}}, 'd': {'a': {'y': {'o': {'f': {'y': {'e': {'a': {'r': {0: True}}}}}}, 0: True}}, 'y': {0: True}, 'w': {0: True}, 'd': {'d': {'d': {0: True}}, 0: True}, 0: True}, 'w': {'e': {'e': {'k': {0: True, 'd': {'a': {'y': {0: True}}}}}}, 'w': {0: True}, 'k': {0: True}}, 'h': {'o': {'u': {'r': {0: True}}}, 'h': {0: True}, 0: True}, 'm': {'i': {'n': {'u': {'t': {'e': {0: True}}}}, 0: True, 'l': {'l': {'i': {'s': {'e': {'c': {'o': {'n': {'d': {0: True}}}}}}}}}}, 's': {0: True}, 'o': {'n': {'t': {'h': {0: True}}}}, 'm': {0: True}, 0: True}, 'n': {0: True}, 's': {'e': {'c': {'o': {'n': {'d': {0: True}}}}}, 's': {0: True}, 0: True}, 'Y': {0: True, 'Y': {'Y': {'Y': {0: True}}, 0: True}}, 'M': {'M': {'M': {'M': {0: True}, 0: True}, 0: True}, 0: True}, 'H': {'H': {0: True}, 0: True}, 'S': {0: True}}"}, "sqlglot.dialects.tsql.TSQL.INVERSE_TIME_MAPPING": {"fullname": "sqlglot.dialects.tsql.TSQL.INVERSE_TIME_MAPPING", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.INVERSE_TIME_MAPPING", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'%Y': 'yyyy', '%j': 'dayofyear', '%d': 'dd', '%W': 'dw', '%h': 'hour', '%I': 'hh', '%M': 'mm', '%S': 'ss', '%-S': 's', '%f': 'S', '%m': 'MM', '%-M': 'm', '%y': 'yy', '%B': 'MMMM', '%b': 'MMM', '%-m': 'M', '%A': 'dddd', '%-d': 'd', '%H': 'HH', '%-H': 'H', '%-I': 'h'}"}, "sqlglot.dialects.tsql.TSQL.INVERSE_TIME_TRIE": {"fullname": "sqlglot.dialects.tsql.TSQL.INVERSE_TIME_TRIE", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.INVERSE_TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'%': {'Y': {0: True}, 'j': {0: True}, 'd': {0: True}, 'W': {0: True}, 'h': {0: True}, 'I': {0: True}, 'M': {0: True}, 'S': {0: True}, '-': {'S': {0: True}, 'M': {0: True}, 'm': {0: True}, 'd': {0: True}, 'H': {0: True}, 'I': {0: True}}, 'f': {0: True}, 'm': {0: True}, 'y': {0: True}, 'B': {0: True}, 'b': {0: True}, 'A': {0: True}, 'H': {0: True}}}"}, "sqlglot.dialects.tsql.TSQL.ESCAPED_SEQUENCES": {"fullname": "sqlglot.dialects.tsql.TSQL.ESCAPED_SEQUENCES", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.ESCAPED_SEQUENCES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{}"}, "sqlglot.dialects.tsql.TSQL.QUOTE_START": {"fullname": "sqlglot.dialects.tsql.TSQL.QUOTE_START", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.QUOTE_START", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.tsql.TSQL.QUOTE_END": {"fullname": "sqlglot.dialects.tsql.TSQL.QUOTE_END", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.QUOTE_END", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.dialects.tsql.TSQL.IDENTIFIER_START": {"fullname": "sqlglot.dialects.tsql.TSQL.IDENTIFIER_START", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.IDENTIFIER_START", "kind": "variable", "doc": "<p></p>\n", "default_value": "'['"}, "sqlglot.dialects.tsql.TSQL.IDENTIFIER_END": {"fullname": "sqlglot.dialects.tsql.TSQL.IDENTIFIER_END", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.IDENTIFIER_END", "kind": "variable", "doc": "<p></p>\n", "default_value": "']'"}, "sqlglot.dialects.tsql.TSQL.BIT_START": {"fullname": "sqlglot.dialects.tsql.TSQL.BIT_START", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.BIT_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.tsql.TSQL.BIT_END": {"fullname": "sqlglot.dialects.tsql.TSQL.BIT_END", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.BIT_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.tsql.TSQL.HEX_START": {"fullname": "sqlglot.dialects.tsql.TSQL.HEX_START", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.HEX_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "'0x'"}, "sqlglot.dialects.tsql.TSQL.HEX_END": {"fullname": "sqlglot.dialects.tsql.TSQL.HEX_END", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.HEX_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "''"}, "sqlglot.dialects.tsql.TSQL.BYTE_START": {"fullname": "sqlglot.dialects.tsql.TSQL.BYTE_START", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.BYTE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.tsql.TSQL.BYTE_END": {"fullname": "sqlglot.dialects.tsql.TSQL.BYTE_END", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.BYTE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.tsql.TSQL.UNICODE_START": {"fullname": "sqlglot.dialects.tsql.TSQL.UNICODE_START", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.UNICODE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.dialects.tsql.TSQL.UNICODE_END": {"fullname": "sqlglot.dialects.tsql.TSQL.UNICODE_END", "modulename": "sqlglot.dialects.tsql", "qualname": "TSQL.UNICODE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.diff": {"fullname": "sqlglot.diff", "modulename": "sqlglot.diff", "kind": "module", "doc": "<h1 id=\"semantic-diff-for-sql\">Semantic Diff for SQL</h1>\n\n<p><em>by <a href=\"https://github.com/izeigerman\">Iaroslav Zeigerman</a></em></p>\n\n<h2 id=\"motivation\">Motivation</h2>\n\n<p>Software is constantly changing and evolving, and identifying what has changed and reviewing those changes is an integral part of the development process. SQL code is no exception to this.</p>\n\n<p>Text-based diff tools such as <code>git diff</code>, when applied to a code base, have certain limitations. First, they can only detect insertions and deletions, not movements or updates of individual pieces of code. Second, such tools can only detect changes between lines of text, which is too coarse for something as granular and detailed as source code. Additionally, the outcome of such a diff is dependent on the underlying code formatting, and yields different results if the formatting should change.</p>\n\n<p>Consider the following diff generated by Git:</p>\n\n<p><img src=\"data:image/png;base64,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\" alt=\"Git diff output\" /></p>\n\n<p>Semantically the query hasn\u2019t changed. The two arguments <code>b</code> and <code>c</code> have been swapped (moved), posing no impact on the output of the query. Yet Git replaced the whole affected expression alongside a bulk of unrelated elements.</p>\n\n<p>The alternative to text-based diffing is to compare Abstract Syntax Trees (AST) instead. The main advantage of ASTs are that they are a direct product of code parsing, which represents the underlying code structure at any desired level of granularity. Comparing ASTs may yield extremely precise diffs; changes such as code movements and updates can also be detected. Even more importantly, this approach facilitates additional use cases beyond eyeballing two versions of source code side by side.</p>\n\n<p>The use cases I had in mind for SQL when I decided to embark on this journey of semantic diffing were the following:</p>\n\n<ul>\n<li><strong>Query similarity score.</strong> Identifying which parts the two queries have in common to automatically suggest opportunities for consolidation, creation of intermediate/staging tables, and so on.</li>\n<li><strong>Differentiating between cosmetic / structural changes and functional ones.</strong> For example when a nested query is refactored into a common table expression (CTE), this kind of change doesn\u2019t have any functional impact on either a query or its outcome.</li>\n<li><strong>Automatic suggestions about the need to retroactively backfill data.</strong> This is especially important for pipelines that populate very large tables for which restatement is a runtime-intensive procedure. The ability to discern between simple code movements and actual modifications can help assess the impact of a change and make suggestions accordingly.</li>\n</ul>\n\n<p>The implementation discussed in this post is now a part of the <a href=\"https://github.com/tobymao/sqlglot/\">SQLGlot</a> library. You can find a complete source code in the <a href=\"https://github.com/tobymao/sqlglot/blob/main/sqlglot/diff.py\">diff.py</a> module. The choice of SQLglot was an obvious one due to its simple but powerful API, lack of external dependencies and, more importantly, extensive list of supported SQL dialects.</p>\n\n<h2 id=\"the-search-for-a-solution\">The Search for a Solution</h2>\n\n<p>When it comes to any diffing tool (not just a semantic one), the primary challenge is to match as many elements of compared entities as possible. Once such a set of matching elements is available, deriving a sequence of changes becomes an easy task.</p>\n\n<p>If our elements have unique identifiers associated with them (for example, an element\u2019s ID in DOM), the matching problem is trivial. However, the SQL syntax trees that we are comparing have neither unique keys nor object identifiers that can be used for the purposes of matching. So, how do we suppose to find pairs of nodes that are related?</p>\n\n<p>To better illustrate the problem, consider comparing the following SQL expressions: <code>SELECT a + b + c, d, e</code> and <code>SELECT a - b + c, e, f</code>. Matching individual nodes from respective syntax trees can be visualized as follows:</p>\n\n<p><img src=\"data:image/png;base64,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\" alt=\"Figure 1: Example of node matching for two SQL expression trees\" />\n<em>Figure 1: Example of node matching for two SQL expression trees.</em></p>\n\n<p>By looking at the figure of node matching for two SQL expression trees above, we conclude that the following changes should be captured by our solution:</p>\n\n<ul>\n<li>Inserted nodes: <code>Sub</code> and <code>f</code>. These are the nodes from the target AST which do not have a matching node in the source AST.</li>\n<li>Removed nodes: <code>Add</code> and <code>d</code>. These are the nodes from the source AST which do not have a counterpart in the target AST.</li>\n<li>Remaining nodes must be identified as unchanged.</li>\n</ul>\n\n<p>It should be clear at this point that if we manage to match nodes in the source tree with their counterparts in the target tree, then computing the diff becomes a trivial matter.</p>\n\n<h3 id=\"naive-brute-force\">Na\u00efve Brute-Force</h3>\n\n<p>The na\u00efve solution would be to try all different permutations of node pair combinations, and see which set of pairs performs the best based on some type of heuristics. The runtime cost of such a solution quickly reaches the escape velocity; if both trees had only 10 nodes each, the number of such sets would approximately be 10! ^ 2 = 3.6M ^ 2 ~= 13 * 10^12. This is a very bad case of factorial complexity (to be precise, it\u2019s actually much worse - O(n! ^ 2) - but I couldn\u2019t come up with a name for it), so there is little need to explore this approach any further.</p>\n\n<h3 id=\"myers-algorithm\">Myers Algorithm</h3>\n\n<p>After the na\u00efve approach was proven to be infeasible, the next question I asked myself was \u201chow does git diff work?\u201d. This question led me to discover the Myers diff algorithm [1]. This algorithm has been designed to compare sequences of strings. At its core, it\u2019s looking for the shortest path on a graph of possible edits that transform the first sequence into the second one, while heavily rewarding those paths that lead to longest subsequences of unchanged elements. There\u2019s a lot of material out there describing this algorithm in greater detail. I found James Coglan\u2019s series of <a href=\"https://blog.jcoglan.com/2017/02/12/the-myers-diff-algorithm-part-1/\">blog posts</a> to be the most comprehensive.</p>\n\n<p>Therefore, I had this \u201cbrilliant\u201d (actually not) idea to transform trees into sequences by traversing them in topological order, and then applying the Myers algorithm on resulting sequences while using a custom heuristics when checking the equality of two nodes. Unsurprisingly, comparing sequences of strings is quite different from comparing hierarchical tree structures, and by flattening trees into sequences, we lose a lot of relevant context. This resulted in a terrible performance of this algorithm on ASTs. It often matched completely unrelated nodes, even when the two trees were mostly the same, and produced extremely inaccurate lists of changes overall. After playing around with it a little and tweaking my equality heuristics to improve accuracy, I ultimately scrapped the whole implementation and went back to the drawing board.</p>\n\n<h2 id=\"change-distiller\">Change Distiller</h2>\n\n<p>The algorithm I settled on at the end was Change Distiller, created by Fluri et al. [2], which in turn is an improvement over the core idea described by Chawathe et al. [3].</p>\n\n<p>The algorithm consists of two high-level steps:</p>\n\n<ol>\n<li><strong>Finding appropriate matchings between pairs of nodes that are part of compared ASTs.</strong> Identifying what is meant by \u201cappropriate\u201d matching is also a part of this step.</li>\n<li><strong>Generating the so-called \u201cedit script\u201d from the matching set built in the 1st step.</strong> The edit script is a sequence of edit operations (for example, insert, remove, update, etc.) on individual tree nodes, such that when applied as transformations on the source AST, it eventually becomes the target AST. In general, the shorter the sequence, the better. The length of the edit script can be used to compare the performance of different algorithms, though this is not the only metric that matters.</li>\n</ol>\n\n<p>The rest of this section is dedicated to the Python implementation of the steps above using the AST implementation provided by the SQLGlot library.</p>\n\n<h3 id=\"building-the-matching-set\">Building the Matching Set</h3>\n\n<h4 id=\"matching-leaves\">Matching Leaves</h4>\n\n<p>We begin composing the matching set by matching the leaf nodes. Leaf nodes are the nodes that do not have any children nodes (such as literals, identifiers, etc.). In order to match them, we gather all the leaf nodes from the source tree and generate a cartesian product with all the leaves from the target tree, while comparing pairs created this way and assigning them a similarity score. During this stage, we also exclude pairs that don\u2019t pass basic matching criteria. Then, we pick pairs that scored the highest while making sure that each node is matched no more than once.</p>\n\n<p>Using the example provided at the beginning of the post, the process of building an initial set of candidate matchings can be seen on Figure 2.</p>\n\n<p><img 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\" alt=\"Figure 2: Building a set of candidate matchings between leaf nodes. The third item in each triplet represents a similarity score between two nodes.\" />\n<em>Figure 2: Building a set of candidate matchings between leaf nodes. The third item in each triplet represents a similarity score between two nodes.</em></p>\n\n<p>First, let\u2019s analyze the similarity score. Then, we\u2019ll discuss matching criteria.</p>\n\n<p>The similarity score proposed by Fluri et al. [2] is a <a href=\"https://en.wikipedia.org/wiki/S%C3%B8rensen%E2%80%93Dice_coefficient\">dice coefficient </a>applied to <a href=\"https://en.wikipedia.org/wiki/Bigram\">bigrams</a> of respective node values. A bigram is a sequence of two adjacent elements from a string computed in a sliding window fashion:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"k\">def</span> <span class=\"nf\">bigram</span><span class=\"p\">(</span><span class=\"n\">string</span><span class=\"p\">):</span>\n <span class=\"n\">count</span> <span class=\"o\">=</span> <span class=\"nb\">max</span><span class=\"p\">(</span><span class=\"mi\">0</span><span class=\"p\">,</span> <span class=\"nb\">len</span><span class=\"p\">(</span><span class=\"n\">string</span><span class=\"p\">)</span> <span class=\"o\">-</span> <span class=\"mi\">1</span><span class=\"p\">)</span>\n <span class=\"k\">return</span> <span class=\"p\">[</span><span class=\"n\">string</span><span class=\"p\">[</span><span class=\"n\">i</span> <span class=\"p\">:</span> <span class=\"n\">i</span> <span class=\"o\">+</span> <span class=\"mi\">2</span><span class=\"p\">]</span> <span class=\"k\">for</span> <span class=\"n\">i</span> <span class=\"ow\">in</span> <span class=\"nb\">range</span><span class=\"p\">(</span><span class=\"n\">count</span><span class=\"p\">)]</span>\n</code></pre>\n</div>\n\n<p>For reasons that will become clear shortly, we actually need to compute bigram histograms rather than just sequences:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"kn\">from</span> <span class=\"nn\">collections</span> <span class=\"kn\">import</span> <span class=\"n\">defaultdict</span>\n\n<span class=\"k\">def</span> <span class=\"nf\">bigram_histo</span><span class=\"p\">(</span><span class=\"n\">string</span><span class=\"p\">):</span>\n <span class=\"n\">count</span> <span class=\"o\">=</span> <span class=\"nb\">max</span><span class=\"p\">(</span><span class=\"mi\">0</span><span class=\"p\">,</span> <span class=\"nb\">len</span><span class=\"p\">(</span><span class=\"n\">string</span><span class=\"p\">)</span> <span class=\"o\">-</span> <span class=\"mi\">1</span><span class=\"p\">)</span>\n <span class=\"n\">bigram_histo</span> <span class=\"o\">=</span> <span class=\"n\">defaultdict</span><span class=\"p\">(</span><span class=\"nb\">int</span><span class=\"p\">)</span>\n <span class=\"k\">for</span> <span class=\"n\">i</span> <span class=\"ow\">in</span> <span class=\"nb\">range</span><span class=\"p\">(</span><span class=\"n\">count</span><span class=\"p\">):</span>\n <span class=\"n\">bigram_histo</span><span class=\"p\">[</span><span class=\"n\">string</span><span class=\"p\">[</span><span class=\"n\">i</span> <span class=\"p\">:</span> <span class=\"n\">i</span> <span class=\"o\">+</span> <span class=\"mi\">2</span><span class=\"p\">]]</span> <span class=\"o\">+=</span> <span class=\"mi\">1</span>\n <span class=\"k\">return</span> <span class=\"n\">bigram_histo</span>\n</code></pre>\n</div>\n\n<p>The dice coefficient formula looks like following:</p>\n\n<p><img src=\"data:image/png;base64,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\" alt=\"Dice Coefficient\" /></p>\n\n<p>Where X is a bigram of the source node and Y is a bigram of the second one. What this essentially does is count the number of bigram elements the two nodes have in common, multiply it by 2, and then divide by the total number of elements in both bigrams. This is where bigram histograms come in handy:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"k\">def</span> <span class=\"nf\">dice_coefficient</span><span class=\"p\">(</span><span class=\"n\">source</span><span class=\"p\">,</span> <span class=\"n\">target</span><span class=\"p\">):</span>\n <span class=\"n\">source_histo</span> <span class=\"o\">=</span> <span class=\"n\">bigram_histo</span><span class=\"p\">(</span><span class=\"n\">source</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">())</span>\n <span class=\"n\">target_histo</span> <span class=\"o\">=</span> <span class=\"n\">bigram_histo</span><span class=\"p\">(</span><span class=\"n\">target</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">())</span>\n\n <span class=\"n\">total_grams</span> <span class=\"o\">=</span> <span class=\"p\">(</span>\n <span class=\"nb\">sum</span><span class=\"p\">(</span><span class=\"n\">source_histo</span><span class=\"o\">.</span><span class=\"n\">values</span><span class=\"p\">())</span> <span class=\"o\">+</span> <span class=\"nb\">sum</span><span class=\"p\">(</span><span class=\"n\">target_histo</span><span class=\"o\">.</span><span class=\"n\">values</span><span class=\"p\">())</span>\n <span class=\"p\">)</span>\n <span class=\"k\">if</span> <span class=\"ow\">not</span> <span class=\"n\">total_grams</span><span class=\"p\">:</span>\n <span class=\"k\">return</span> <span class=\"mf\">1.0</span> <span class=\"k\">if</span> <span class=\"n\">source</span> <span class=\"o\">==</span> <span class=\"n\">target</span> <span class=\"k\">else</span> <span class=\"mf\">0.0</span>\n\n <span class=\"n\">overlap_len</span> <span class=\"o\">=</span> <span class=\"mi\">0</span>\n <span class=\"n\">overlapping_grams</span> <span class=\"o\">=</span> <span class=\"nb\">set</span><span class=\"p\">(</span><span class=\"n\">source_histo</span><span class=\"p\">)</span> <span class=\"o\">&</span> <span class=\"nb\">set</span><span class=\"p\">(</span><span class=\"n\">target_histo</span><span class=\"p\">)</span>\n <span class=\"k\">for</span> <span class=\"n\">g</span> <span class=\"ow\">in</span> <span class=\"n\">overlapping_grams</span><span class=\"p\">:</span>\n <span class=\"n\">overlap_len</span> <span class=\"o\">+=</span> <span class=\"nb\">min</span><span class=\"p\">(</span><span class=\"n\">source_histo</span><span class=\"p\">[</span><span class=\"n\">g</span><span class=\"p\">],</span> <span class=\"n\">target_histo</span><span class=\"p\">[</span><span class=\"n\">g</span><span class=\"p\">])</span>\n\n <span class=\"k\">return</span> <span class=\"mi\">2</span> <span class=\"o\">*</span> <span class=\"n\">overlap_len</span> <span class=\"o\">/</span> <span class=\"n\">total_grams</span>\n</code></pre>\n</div>\n\n<p>To compute a bigram given a tree node, we first transform the node into its canonical SQL representation,so that the <code>Literal(123)</code> node becomes just \u201c123\u201d and the <code>Identifier(\u201ca\u201d)</code> node becomes just \u201ca\u201d. We also handle a scenario when strings are too short to derive bigrams. In this case, we fallback to checking the two nodes for equality.</p>\n\n<p>Now when we know how to compute the similarity score, we can take care of the matching criteria for leaf nodes. In the original paper [2], the matching criteria is formalized as follows:</p>\n\n<p><img src=\"data:image/png;base64,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\" alt=\"Matching criteria for leaf nodes\" /></p>\n\n<p>The two nodes are matched if two conditions are met:</p>\n\n<ol>\n<li>The node labels match (in our case labels are just node types).</li>\n<li>The similarity score for node values is greater than or equal to some threshold \u201cf\u201d. The authors of the paper recommend setting the value of \u201cf\u201d to 0.6.</li>\n</ol>\n\n<p>With building blocks in place, we can now build a matching set for leaf nodes. First, we generate a list of candidates for matching:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"kn\">from</span> <span class=\"nn\">heapq</span> <span class=\"kn\">import</span> <span class=\"n\">heappush</span><span class=\"p\">,</span> <span class=\"n\">heappop</span>\n\n<span class=\"n\">candidate_matchings</span> <span class=\"o\">=</span> <span class=\"p\">[]</span>\n<span class=\"n\">source_leaves</span> <span class=\"o\">=</span> <span class=\"n\">_get_leaves</span><span class=\"p\">(</span><span class=\"bp\">self</span><span class=\"o\">.</span><span class=\"n\">_source</span><span class=\"p\">)</span>\n<span class=\"n\">target_leaves</span> <span class=\"o\">=</span> <span class=\"n\">_get_leaves</span><span class=\"p\">(</span><span class=\"bp\">self</span><span class=\"o\">.</span><span class=\"n\">_target</span><span class=\"p\">)</span>\n<span class=\"k\">for</span> <span class=\"n\">source_leaf</span> <span class=\"ow\">in</span> <span class=\"n\">source_leaves</span><span class=\"p\">:</span>\n <span class=\"k\">for</span> <span class=\"n\">target_leaf</span> <span class=\"ow\">in</span> <span class=\"n\">target_leaves</span><span class=\"p\">:</span>\n <span class=\"k\">if</span> <span class=\"n\">_is_same_type</span><span class=\"p\">(</span><span class=\"n\">source_leaf</span><span class=\"p\">,</span> <span class=\"n\">target_leaf</span><span class=\"p\">):</span>\n <span class=\"n\">similarity_score</span> <span class=\"o\">=</span> <span class=\"n\">dice_coefficient</span><span class=\"p\">(</span>\n <span class=\"n\">source_leaf</span><span class=\"p\">,</span> <span class=\"n\">target_leaf</span>\n <span class=\"p\">)</span>\n <span class=\"k\">if</span> <span class=\"n\">similarity_score</span> <span class=\"o\">>=</span> <span class=\"mf\">0.6</span><span class=\"p\">:</span>\n <span class=\"n\">heappush</span><span class=\"p\">(</span>\n <span class=\"n\">candidate_matchings</span><span class=\"p\">,</span>\n <span class=\"p\">(</span>\n <span class=\"o\">-</span><span class=\"n\">similarity_score</span><span class=\"p\">,</span>\n <span class=\"nb\">len</span><span class=\"p\">(</span><span class=\"n\">candidate_matchings</span><span class=\"p\">),</span>\n <span class=\"n\">source_leaf</span><span class=\"p\">,</span>\n <span class=\"n\">target_leaf</span><span class=\"p\">,</span>\n <span class=\"p\">),</span>\n <span class=\"p\">)</span>\n</code></pre>\n</div>\n\n<p>In the implementation above, we push each matching pair onto the heap to automatically maintain the correct order based on the assigned similarity score.</p>\n\n<p>Finally, we build the initial matching set by picking leaf pairs with the highest score:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"n\">matching_set</span> <span class=\"o\">=</span> <span class=\"nb\">set</span><span class=\"p\">()</span>\n<span class=\"k\">while</span> <span class=\"n\">candidate_matchings</span><span class=\"p\">:</span>\n <span class=\"n\">_</span><span class=\"p\">,</span> <span class=\"n\">_</span><span class=\"p\">,</span> <span class=\"n\">source_leaf</span><span class=\"p\">,</span> <span class=\"n\">target_leaf</span> <span class=\"o\">=</span> <span class=\"n\">heappop</span><span class=\"p\">(</span><span class=\"n\">candidate_matchings</span><span class=\"p\">)</span>\n <span class=\"k\">if</span> <span class=\"p\">(</span>\n <span class=\"n\">source_leaf</span> <span class=\"ow\">in</span> <span class=\"n\">unmatched_source_nodes</span>\n <span class=\"ow\">and</span> <span class=\"n\">target_leaf</span> <span class=\"ow\">in</span> <span class=\"n\">unmatched_target_nodes</span>\n <span class=\"p\">):</span>\n <span class=\"n\">matching_set</span><span class=\"o\">.</span><span class=\"n\">add</span><span class=\"p\">((</span><span class=\"n\">source_leaf</span><span class=\"p\">,</span> <span class=\"n\">target_leaf</span><span class=\"p\">))</span>\n <span class=\"n\">unmatched_source_nodes</span><span class=\"o\">.</span><span class=\"n\">remove</span><span class=\"p\">(</span><span class=\"n\">source_leaf</span><span class=\"p\">)</span>\n <span class=\"n\">unmatched_target_nodes</span><span class=\"o\">.</span><span class=\"n\">remove</span><span class=\"p\">(</span><span class=\"n\">target_leaf</span><span class=\"p\">)</span>\n</code></pre>\n</div>\n\n<p>To finalize the matching set, we should now proceed with matching inner nodes.</p>\n\n<h4 id=\"matching-inner-nodes\">Matching Inner Nodes</h4>\n\n<p>Matching inner nodes is quite similar to matching leaf nodes, with the following two distinctions:</p>\n\n<ul>\n<li>Rather than ranking a set of possible candidates, we pick the first node pair that passes the matching criteria.</li>\n<li>The matching criteria itself has been extended to account for the number of leaf nodes the pair of inner nodes have in common.</li>\n</ul>\n\n<p><img src=\"data:image/gif;base64,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\" alt=\"Figure 3: Matching inner nodes based on their type as well as how many of their leaf nodes have been previously matched.\" />\n<em>Figure 3: Matching inner nodes based on their type as well as how many of their leaf nodes have been previously matched.</em></p>\n\n<p>Let\u2019s start with the matching criteria. The criteria is formalized as follows:</p>\n\n<p><img 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\" alt=\"Matching criteria for inner nodes\" /></p>\n\n<p>Alongside already familiar similarity score and node type criteria, there is a new one in the middle: the ratio of leaf nodes that the two nodes have in common must exceed some threshold \u201ct\u201d. The recommended value for \u201ct\u201d is also 0.6. Counting the number of common leaf nodes is pretty straightforward, since we already have the complete matching set for leaves. All we need to do is count how many matching pairs do leaf nodes from the two compared inner nodes form.</p>\n\n<p>There are two additional heuristics associated with this matching criteria:</p>\n\n<ul>\n<li>Inner node similarity weighting: if the similarity score between the node values doesn\u2019t pass the threshold \u201cf\u201d but the ratio of common leaf nodes (\u201ct\u201d) is greater than or equal to 0.8, then the matching is considered successful.</li>\n<li>The threshold \u201ct\u201d is reduced to 0.4 for inner nodes with the number of leaf nodes equal to 4 or less, in order to decrease the false negative rate for small subtrees.</li>\n</ul>\n\n<p>We now only have to iterate through the remaining unmatched nodes and form matching pairs based on the outlined criteria:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"n\">leaves_matching_set</span> <span class=\"o\">=</span> <span class=\"n\">matching_set</span><span class=\"o\">.</span><span class=\"n\">copy</span><span class=\"p\">()</span>\n\n<span class=\"k\">for</span> <span class=\"n\">source_node</span> <span class=\"ow\">in</span> <span class=\"n\">unmatched_source_nodes</span><span class=\"o\">.</span><span class=\"n\">copy</span><span class=\"p\">():</span>\n <span class=\"k\">for</span> <span class=\"n\">target_node</span> <span class=\"ow\">in</span> <span class=\"n\">unmatched_target_nodes</span><span class=\"p\">:</span>\n <span class=\"k\">if</span> <span class=\"n\">_is_same_type</span><span class=\"p\">(</span><span class=\"n\">source_node</span><span class=\"p\">,</span> <span class=\"n\">target_node</span><span class=\"p\">):</span>\n <span class=\"n\">source_leaves</span> <span class=\"o\">=</span> <span class=\"nb\">set</span><span class=\"p\">(</span><span class=\"n\">_get_leaves</span><span class=\"p\">(</span><span class=\"n\">source_node</span><span class=\"p\">))</span>\n <span class=\"n\">target_leaves</span> <span class=\"o\">=</span> <span class=\"nb\">set</span><span class=\"p\">(</span><span class=\"n\">_get_leaves</span><span class=\"p\">(</span><span class=\"n\">target_node</span><span class=\"p\">))</span>\n\n <span class=\"n\">max_leaves_num</span> <span class=\"o\">=</span> <span class=\"nb\">max</span><span class=\"p\">(</span><span class=\"nb\">len</span><span class=\"p\">(</span><span class=\"n\">source_leaves</span><span class=\"p\">),</span> <span class=\"nb\">len</span><span class=\"p\">(</span><span class=\"n\">target_leaves</span><span class=\"p\">))</span>\n <span class=\"k\">if</span> <span class=\"n\">max_leaves_num</span><span class=\"p\">:</span>\n <span class=\"n\">common_leaves_num</span> <span class=\"o\">=</span> <span class=\"nb\">sum</span><span class=\"p\">(</span>\n <span class=\"mi\">1</span> <span class=\"k\">if</span> <span class=\"n\">s</span> <span class=\"ow\">in</span> <span class=\"n\">source_leaves</span> <span class=\"ow\">and</span> <span class=\"n\">t</span> <span class=\"ow\">in</span> <span class=\"n\">target_leaves</span> <span class=\"k\">else</span> <span class=\"mi\">0</span>\n <span class=\"k\">for</span> <span class=\"n\">s</span><span class=\"p\">,</span> <span class=\"n\">t</span> <span class=\"ow\">in</span> <span class=\"n\">leaves_matching_set</span>\n <span class=\"p\">)</span>\n <span class=\"n\">leaf_similarity_score</span> <span class=\"o\">=</span> <span class=\"n\">common_leaves_num</span> <span class=\"o\">/</span> <span class=\"n\">max_leaves_num</span>\n <span class=\"k\">else</span><span class=\"p\">:</span>\n <span class=\"n\">leaf_similarity_score</span> <span class=\"o\">=</span> <span class=\"mf\">0.0</span>\n\n <span class=\"n\">adjusted_t</span> <span class=\"o\">=</span> <span class=\"p\">(</span>\n <span class=\"mf\">0.6</span>\n <span class=\"k\">if</span> <span class=\"nb\">min</span><span class=\"p\">(</span><span class=\"nb\">len</span><span class=\"p\">(</span><span class=\"n\">source_leaves</span><span class=\"p\">),</span> <span class=\"nb\">len</span><span class=\"p\">(</span><span class=\"n\">target_leaves</span><span class=\"p\">))</span> <span class=\"o\">></span> <span class=\"mi\">4</span>\n <span class=\"k\">else</span> <span class=\"mf\">0.4</span>\n <span class=\"p\">)</span>\n\n <span class=\"k\">if</span> <span class=\"n\">leaf_similarity_score</span> <span class=\"o\">>=</span> <span class=\"mf\">0.8</span> <span class=\"ow\">or</span> <span class=\"p\">(</span>\n <span class=\"n\">leaf_similarity_score</span> <span class=\"o\">>=</span> <span class=\"n\">adjusted_t</span>\n <span class=\"ow\">and</span> <span class=\"n\">dice_coefficient</span><span class=\"p\">(</span><span class=\"n\">source_node</span><span class=\"p\">,</span> <span class=\"n\">target_node</span><span class=\"p\">)</span> <span class=\"o\">>=</span> <span class=\"mf\">0.6</span>\n <span class=\"p\">):</span>\n <span class=\"n\">matching_set</span><span class=\"o\">.</span><span class=\"n\">add</span><span class=\"p\">((</span><span class=\"n\">source_node</span><span class=\"p\">,</span> <span class=\"n\">target_node</span><span class=\"p\">))</span>\n <span class=\"n\">unmatched_source_nodes</span><span class=\"o\">.</span><span class=\"n\">remove</span><span class=\"p\">(</span><span class=\"n\">source_node</span><span class=\"p\">)</span>\n <span class=\"n\">unmatched_target_nodes</span><span class=\"o\">.</span><span class=\"n\">remove</span><span class=\"p\">(</span><span class=\"n\">target_node</span><span class=\"p\">)</span>\n <span class=\"k\">break</span>\n</code></pre>\n</div>\n\n<p>After the matching set is formed, we can proceed with generation of the edit script, which will be the algorithm\u2019s output.</p>\n\n<h3 id=\"generating-the-edit-script\">Generating the Edit Script</h3>\n\n<p>At this point, we should have the following 3 sets at our disposal:</p>\n\n<ul>\n<li>The set of matched node pairs.</li>\n<li>The set of remaining unmatched nodes from the source tree.</li>\n<li>The set of remaining unmatched nodes from the target tree.</li>\n</ul>\n\n<p>We can derive 3 kinds of edits from the matching set: either the node\u2019s value was updated (<strong>Update</strong>), the node was moved to a different position within the tree (<strong>Move</strong>), or the node remained unchanged (<strong>Keep</strong>). Note that the <strong>Move</strong> case is not mutually exclusive with the other two. The node could have been updated or could have remained the same while at the same time its position within its parent node or the parent node itself could have changed. All unmatched nodes from the source tree are the ones that were removed (<strong>Remove</strong>), while unmatched nodes from the target tree are the ones that were inserted (<strong>Insert</strong>).</p>\n\n<p>The latter two cases are pretty straightforward to implement:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"n\">edit_script</span> <span class=\"o\">=</span> <span class=\"p\">[]</span>\n\n<span class=\"k\">for</span> <span class=\"n\">removed_node</span> <span class=\"ow\">in</span> <span class=\"n\">unmatched_source_nodes</span><span class=\"p\">:</span>\n <span class=\"n\">edit_script</span><span class=\"o\">.</span><span class=\"n\">append</span><span class=\"p\">(</span><span class=\"n\">Remove</span><span class=\"p\">(</span><span class=\"n\">removed_node</span><span class=\"p\">))</span>\n<span class=\"k\">for</span> <span class=\"n\">inserted_node</span> <span class=\"ow\">in</span> <span class=\"n\">unmatched_target_nodes</span><span class=\"p\">:</span>\n <span class=\"n\">edit_script</span><span class=\"o\">.</span><span class=\"n\">append</span><span class=\"p\">(</span><span class=\"n\">Insert</span><span class=\"p\">(</span><span class=\"n\">inserted_node</span><span class=\"p\">))</span>\n</code></pre>\n</div>\n\n<p>Traversing the matching set requires a little more thought:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"k\">for</span> <span class=\"n\">source_node</span><span class=\"p\">,</span> <span class=\"n\">target_node</span> <span class=\"ow\">in</span> <span class=\"n\">matching_set</span><span class=\"p\">:</span>\n <span class=\"k\">if</span> <span class=\"p\">(</span>\n <span class=\"ow\">not</span> <span class=\"nb\">isinstance</span><span class=\"p\">(</span><span class=\"n\">source_node</span><span class=\"p\">,</span> <span class=\"n\">LEAF_EXPRESSION_TYPES</span><span class=\"p\">)</span>\n <span class=\"ow\">or</span> <span class=\"n\">source_node</span> <span class=\"o\">==</span> <span class=\"n\">target_node</span>\n <span class=\"p\">):</span>\n <span class=\"n\">move_edits</span> <span class=\"o\">=</span> <span class=\"n\">generate_move_edits</span><span class=\"p\">(</span>\n <span class=\"n\">source_node</span><span class=\"p\">,</span> <span class=\"n\">target_node</span><span class=\"p\">,</span> <span class=\"n\">matching_set</span>\n <span class=\"p\">)</span>\n <span class=\"n\">edit_script</span><span class=\"o\">.</span><span class=\"n\">extend</span><span class=\"p\">(</span><span class=\"n\">move_edits</span><span class=\"p\">)</span>\n <span class=\"n\">edit_script</span><span class=\"o\">.</span><span class=\"n\">append</span><span class=\"p\">(</span><span class=\"n\">Keep</span><span class=\"p\">(</span><span class=\"n\">source_node</span><span class=\"p\">,</span> <span class=\"n\">target_node</span><span class=\"p\">))</span>\n <span class=\"k\">else</span><span class=\"p\">:</span>\n <span class=\"n\">edit_script</span><span class=\"o\">.</span><span class=\"n\">append</span><span class=\"p\">(</span><span class=\"n\">Update</span><span class=\"p\">(</span><span class=\"n\">source_node</span><span class=\"p\">,</span> <span class=\"n\">target_node</span><span class=\"p\">))</span>\n</code></pre>\n</div>\n\n<p>If a matching pair represents a pair of leaf nodes, we check if they are the same to decide whether an update took place. For inner node pairs, we also need to compare the positions of their respective children to detect node movements. Chawathe et al. [3] suggest applying the <a href=\"https://en.wikipedia.org/wiki/Longest_common_subsequence_problem\">longest common subsequence </a>(LCS) algorithm which, no surprise here, was described by Myers himself [1]. There is a small catch, however: instead of checking the equality of two children nodes, we need to check whether the two nodes form a pair that is a part of our matching set.</p>\n\n<p>Now with this knowledge, the implementation becomes straightforward:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"k\">def</span> <span class=\"nf\">generate_move_edits</span><span class=\"p\">(</span><span class=\"n\">source</span><span class=\"p\">,</span> <span class=\"n\">target</span><span class=\"p\">,</span> <span class=\"n\">matching_set</span><span class=\"p\">):</span>\n <span class=\"n\">source_children</span> <span class=\"o\">=</span> <span class=\"n\">_get_child_nodes</span><span class=\"p\">(</span><span class=\"n\">source</span><span class=\"p\">)</span>\n <span class=\"n\">target_children</span> <span class=\"o\">=</span> <span class=\"n\">_get_child_nodes</span><span class=\"p\">(</span><span class=\"n\">target</span><span class=\"p\">)</span>\n\n <span class=\"n\">lcs</span> <span class=\"o\">=</span> <span class=\"nb\">set</span><span class=\"p\">(</span>\n <span class=\"n\">_longest_common_subsequence</span><span class=\"p\">(</span>\n <span class=\"n\">source_children</span><span class=\"p\">,</span>\n <span class=\"n\">target_children</span><span class=\"p\">,</span>\n <span class=\"k\">lambda</span> <span class=\"n\">l</span><span class=\"p\">,</span> <span class=\"n\">r</span><span class=\"p\">:</span> <span class=\"p\">(</span><span class=\"n\">l</span><span class=\"p\">,</span> <span class=\"n\">r</span><span class=\"p\">)</span> <span class=\"ow\">in</span> <span class=\"n\">matching_set</span>\n <span class=\"p\">)</span>\n <span class=\"p\">)</span>\n\n <span class=\"n\">move_edits</span> <span class=\"o\">=</span> <span class=\"p\">[]</span>\n <span class=\"k\">for</span> <span class=\"n\">node</span> <span class=\"ow\">in</span> <span class=\"n\">source_children</span><span class=\"p\">:</span>\n <span class=\"k\">if</span> <span class=\"n\">node</span> <span class=\"ow\">not</span> <span class=\"ow\">in</span> <span class=\"n\">lcs</span> <span class=\"ow\">and</span> <span class=\"n\">node</span> <span class=\"ow\">not</span> <span class=\"ow\">in</span> <span class=\"n\">unmatched_source_nodes</span><span class=\"p\">:</span>\n <span class=\"n\">move_edits</span><span class=\"o\">.</span><span class=\"n\">append</span><span class=\"p\">(</span><span class=\"n\">Move</span><span class=\"p\">(</span><span class=\"n\">node</span><span class=\"p\">))</span>\n\n <span class=\"k\">return</span> <span class=\"n\">move_edits</span>\n</code></pre>\n</div>\n\n<p>I left out the implementation of the LCS algorithm itself here, but there are plenty of implementation choices out there that can be easily looked up.</p>\n\n<h3 id=\"output\">Output</h3>\n\n<p>The implemented algorithm produces the output that resembles the following:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"o\">>>></span> <span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">parse_one</span><span class=\"p\">,</span> <span class=\"n\">diff</span>\n<span class=\"o\">>>></span> <span class=\"n\">diff</span><span class=\"p\">(</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT a + b + c, d, e"</span><span class=\"p\">),</span> <span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT a - b + c, e, f"</span><span class=\"p\">))</span>\n\n<span class=\"n\">Remove</span><span class=\"p\">(</span><span class=\"n\">Add</span><span class=\"p\">)</span>\n<span class=\"n\">Remove</span><span class=\"p\">(</span><span class=\"n\">Column</span><span class=\"p\">(</span><span class=\"n\">d</span><span class=\"p\">))</span>\n<span class=\"n\">Remove</span><span class=\"p\">(</span><span class=\"n\">Identifier</span><span class=\"p\">(</span><span class=\"n\">d</span><span class=\"p\">))</span>\n<span class=\"n\">Insert</span><span class=\"p\">(</span><span class=\"n\">Sub</span><span class=\"p\">)</span>\n<span class=\"n\">Insert</span><span class=\"p\">(</span><span class=\"n\">Column</span><span class=\"p\">(</span><span class=\"n\">f</span><span class=\"p\">))</span>\n<span class=\"n\">Insert</span><span class=\"p\">(</span><span class=\"n\">Identifier</span><span class=\"p\">(</span><span class=\"n\">f</span><span class=\"p\">))</span>\n<span class=\"n\">Keep</span><span class=\"p\">(</span><span class=\"n\">Select</span><span class=\"p\">,</span> <span class=\"n\">Select</span><span class=\"p\">)</span>\n<span class=\"n\">Keep</span><span class=\"p\">(</span><span class=\"n\">Add</span><span class=\"p\">,</span> <span class=\"n\">Add</span><span class=\"p\">)</span>\n<span class=\"n\">Keep</span><span class=\"p\">(</span><span class=\"n\">Column</span><span class=\"p\">(</span><span class=\"n\">a</span><span class=\"p\">),</span> <span class=\"n\">Column</span><span class=\"p\">(</span><span class=\"n\">a</span><span class=\"p\">))</span>\n<span class=\"n\">Keep</span><span class=\"p\">(</span><span class=\"n\">Identifier</span><span class=\"p\">(</span><span class=\"n\">a</span><span class=\"p\">),</span> <span class=\"n\">Identifier</span><span class=\"p\">(</span><span class=\"n\">a</span><span class=\"p\">))</span>\n<span class=\"n\">Keep</span><span class=\"p\">(</span><span class=\"n\">Column</span><span class=\"p\">(</span><span class=\"n\">b</span><span class=\"p\">),</span> <span class=\"n\">Column</span><span class=\"p\">(</span><span class=\"n\">b</span><span class=\"p\">))</span>\n<span class=\"n\">Keep</span><span class=\"p\">(</span><span class=\"n\">Identifier</span><span class=\"p\">(</span><span class=\"n\">b</span><span class=\"p\">),</span> <span class=\"n\">Identifier</span><span class=\"p\">(</span><span class=\"n\">b</span><span class=\"p\">))</span>\n<span class=\"n\">Keep</span><span class=\"p\">(</span><span class=\"n\">Column</span><span class=\"p\">(</span><span class=\"n\">c</span><span class=\"p\">),</span> <span class=\"n\">Column</span><span class=\"p\">(</span><span class=\"n\">c</span><span class=\"p\">))</span>\n<span class=\"n\">Keep</span><span class=\"p\">(</span><span class=\"n\">Identifier</span><span class=\"p\">(</span><span class=\"n\">c</span><span class=\"p\">),</span> <span class=\"n\">Identifier</span><span class=\"p\">(</span><span class=\"n\">c</span><span class=\"p\">))</span>\n<span class=\"n\">Keep</span><span class=\"p\">(</span><span class=\"n\">Column</span><span class=\"p\">(</span><span class=\"n\">e</span><span class=\"p\">),</span> <span class=\"n\">Column</span><span class=\"p\">(</span><span class=\"n\">e</span><span class=\"p\">))</span>\n<span class=\"n\">Keep</span><span class=\"p\">(</span><span class=\"n\">Identifier</span><span class=\"p\">(</span><span class=\"n\">e</span><span class=\"p\">),</span> <span class=\"n\">Identifier</span><span class=\"p\">(</span><span class=\"n\">e</span><span class=\"p\">))</span>\n</code></pre>\n</div>\n\n<p>Note that the output above is abbreviated. The string representation of actual AST nodes is significantly more verbose.</p>\n\n<p>The implementation works especially well when coupled with the SQLGlot\u2019s query optimizer which can be used to produce canonical representations of compared queries:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"o\">>>></span> <span class=\"n\">schema</span><span class=\"o\">=</span><span class=\"p\">{</span><span class=\"s2\">"t"</span><span class=\"p\">:</span> <span class=\"p\">{</span><span class=\"s2\">"a"</span><span class=\"p\">:</span> <span class=\"s2\">"INT"</span><span class=\"p\">,</span> <span class=\"s2\">"b"</span><span class=\"p\">:</span> <span class=\"s2\">"INT"</span><span class=\"p\">,</span> <span class=\"s2\">"c"</span><span class=\"p\">:</span> <span class=\"s2\">"INT"</span><span class=\"p\">,</span> <span class=\"s2\">"d"</span><span class=\"p\">:</span> <span class=\"s2\">"INT"</span><span class=\"p\">}}</span>\n<span class=\"o\">>>></span> <span class=\"n\">source</span> <span class=\"o\">=</span> <span class=\"s2\">"""</span>\n<span class=\"s2\">... SELECT 1 + 1 + a</span>\n<span class=\"s2\">... FROM t</span>\n<span class=\"s2\">... WHERE b = 1 OR (c = 2 AND d = 3)</span>\n<span class=\"s2\">... """</span>\n<span class=\"o\">>>></span> <span class=\"n\">target</span> <span class=\"o\">=</span> <span class=\"s2\">"""</span>\n<span class=\"s2\">... SELECT 2 + a</span>\n<span class=\"s2\">... FROM t</span>\n<span class=\"s2\">... WHERE (b = 1 OR c = 2) AND (b = 1 OR d = 3)</span>\n<span class=\"s2\">... """</span>\n<span class=\"o\">>>></span> <span class=\"n\">optimized_source</span> <span class=\"o\">=</span> <span class=\"n\">optimize</span><span class=\"p\">(</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"n\">source</span><span class=\"p\">),</span> <span class=\"n\">schema</span><span class=\"o\">=</span><span class=\"n\">schema</span><span class=\"p\">)</span>\n<span class=\"o\">>>></span> <span class=\"n\">optimized_target</span> <span class=\"o\">=</span> <span class=\"n\">optimize</span><span class=\"p\">(</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"n\">target</span><span class=\"p\">),</span> <span class=\"n\">schema</span><span class=\"o\">=</span><span class=\"n\">schema</span><span class=\"p\">)</span>\n<span class=\"o\">>>></span> <span class=\"n\">edit_script</span> <span class=\"o\">=</span> <span class=\"n\">diff</span><span class=\"p\">(</span><span class=\"n\">optimized_source</span><span class=\"p\">,</span> <span class=\"n\">optimized_target</span><span class=\"p\">)</span>\n<span class=\"o\">>>></span> <span class=\"nb\">sum</span><span class=\"p\">(</span><span class=\"mi\">0</span> <span class=\"k\">if</span> <span class=\"nb\">isinstance</span><span class=\"p\">(</span><span class=\"n\">e</span><span class=\"p\">,</span> <span class=\"n\">Keep</span><span class=\"p\">)</span> <span class=\"k\">else</span> <span class=\"mi\">1</span> <span class=\"k\">for</span> <span class=\"n\">e</span> <span class=\"ow\">in</span> <span class=\"n\">edit_script</span><span class=\"p\">)</span>\n<span class=\"mi\">0</span>\n</code></pre>\n</div>\n\n<h3 id=\"optimizations\">Optimizations</h3>\n\n<p>The worst case runtime complexity of this algorithm is not exactly stellar: O(n^2 * log n^2). This is because of the leaf matching process, which involves ranking a cartesian product between all leaf nodes of compared trees. Unsurprisingly, the algorithm takes a considerable time to finish for bigger queries.</p>\n\n<p>There are still a few basic things we can do in our implementation to help improve performance:</p>\n\n<ul>\n<li>Refer to individual node objects using their identifiers (Python\u2019s <a href=\"https://docs.python.org/3/library/functions.html#id\">id()</a>) instead of direct references in sets. This helps avoid costly recursive hash calculations and equality checks.</li>\n<li>Cache bigram histograms to avoid computing them more than once for the same node.</li>\n<li>Compute the canonical SQL string representation for each tree once while caching string representations of all inner nodes. This prevents redundant tree traversals when bigrams are computed.</li>\n</ul>\n\n<p>At the time of writing only the first two optimizations have been implemented, so there is an opportunity to contribute for anyone who\u2019s interested.</p>\n\n<h2 id=\"alternative-solutions\">Alternative Solutions</h2>\n\n<p>This section is dedicated to solutions that I\u2019ve investigated, but haven\u2019t tried.</p>\n\n<p>First, this section wouldn\u2019t be complete without Tristan Hume\u2019s <a href=\"https://thume.ca/2017/06/17/tree-diffing/\">blog post</a>. Tristan\u2019s solution has a lot in common with the Myers algorithm plus heuristics that is much more clever than what I came up with. The implementation relies on a combination of <a href=\"https://en.wikipedia.org/wiki/Dynamic_programming\">dynamic programming</a> and <a href=\"https://en.wikipedia.org/wiki/A*_search_algorithm\">A* search algorithm</a> to explore the space of possible matchings and pick the best ones. It seemed to have worked well for Tistan\u2019s specific use case, but after my negative experience with the Myers algorithm, I decided to try something different.</p>\n\n<p>Another notable approach is the Gumtree algorithm by Falleri et al. [4]. I discovered this paper after I\u2019d already implemented the algorithm that is the main focus of this post. In sections 5.2 and 5.3 of their paper, the authors compare the two algorithms side by side and claim that Gumtree is significantly better in terms of both runtime performance and accuracy when evaluated on 12 792 pairs of Java source files. This doesn\u2019t surprise me, as the algorithm takes the height of subtrees into account. In my tests, I definitely saw scenarios in which this context would have helped. On top of that, the authors promise O(n^2) runtime complexity in the worst case which, given the Change Distiller's O(n^2 * log n^2), looks particularly tempting. I hope to try this algorithm out at some point, and there is a good chance you see me writing about it in my future posts.</p>\n\n<h2 id=\"conclusion\">Conclusion</h2>\n\n<p>The Change Distiller algorithm yielded quite satisfactory results in most of my tests. The scenarios in which it fell short mostly concerned identical (or very similar) subtrees located in different parts of the AST. In those cases, node mismatches were frequent and, as a result, edit scripts were somewhat suboptimal.</p>\n\n<p>Additionally, the runtime performance of the algorithm leaves a lot to be desired. On trees with 1000 leaf nodes each, the algorithm takes a little under 2 seconds to complete. My implementation still has room for improvement, but this should give you a rough idea of what to expect. It appears that the Gumtree algorithm [4] can help address both of these points. I hope to find bandwidth to work on it soon and then compare the two algorithms side-by-side to find out which one performs better on SQL specifically. In the meantime, Change Distiller definitely gets the job done, and I can now proceed with applying it to some of the use cases I mentioned at the beginning of this post.</p>\n\n<p>I\u2019m also curious to learn whether other folks in the industry faced a similar problem, and how they approached it. If you did something similar, I\u2019m interested to hear about your experience.</p>\n\n<h2 id=\"references\">References</h2>\n\n<p>[1] Eugene W. Myers. <a href=\"http://www.xmailserver.org/diff2.pdf\">An O(ND) Difference Algorithm and Its Variations</a>. Algorithmica 1(2): 251-266 (1986)</p>\n\n<p>[2] B. Fluri, M. Wursch, M. Pinzger, and H. Gall. <a href=\"https://www.researchgate.net/publication/3189787_Change_DistillingTree_Differencing_for_Fine-Grained_Source_Code_Change_Extraction\">Change Distilling: Tree differencing for fine-grained source code change extraction</a>. IEEE Trans. Software Eng., 33(11):725\u2013743, 2007.</p>\n\n<p>[3] S.S. Chawathe, A. Rajaraman, H. Garcia-Molina, and J. Widom. <a href=\"http://ilpubs.stanford.edu:8090/115/1/1995-46.pdf\">Change Detection in Hierarchically Structured Information</a>. Proc. ACM Sigmod Int\u2019l Conf. Management of Data, pp. 493-504, June 1996</p>\n\n<p>[4] Jean-R\u00e9my Falleri, Flor\u00e9al Morandat, Xavier Blanc, Matias Martinez, Martin Monperrus. <a href=\"https://hal.archives-ouvertes.fr/hal-01054552/document\">Fine-grained and Accurate Source Code Differencing</a>. Proceedings of the International Conference on Automated Software Engineering, 2014, V\u00e4steras, Sweden. pp.313-324, 10.1145/2642937.2642982. hal-01054552</p>\n\n<hr />\n"}, "sqlglot.diff.Insert": {"fullname": "sqlglot.diff.Insert", "modulename": "sqlglot.diff", "qualname": "Insert", "kind": "class", "doc": "<p>Indicates that a new node has been inserted</p>\n"}, "sqlglot.diff.Insert.__init__": {"fullname": "sqlglot.diff.Insert.__init__", "modulename": "sqlglot.diff", "qualname": "Insert.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span>)</span>"}, "sqlglot.diff.Insert.expression": {"fullname": "sqlglot.diff.Insert.expression", "modulename": "sqlglot.diff", "qualname": "Insert.expression", "kind": "variable", "doc": "<p></p>\n", "annotation": ": sqlglot.expressions.Expression"}, "sqlglot.diff.Remove": {"fullname": "sqlglot.diff.Remove", "modulename": "sqlglot.diff", "qualname": "Remove", "kind": "class", "doc": "<p>Indicates that an existing node has been removed</p>\n"}, "sqlglot.diff.Remove.__init__": {"fullname": "sqlglot.diff.Remove.__init__", "modulename": "sqlglot.diff", "qualname": "Remove.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span>)</span>"}, "sqlglot.diff.Remove.expression": {"fullname": "sqlglot.diff.Remove.expression", "modulename": "sqlglot.diff", "qualname": "Remove.expression", "kind": "variable", "doc": "<p></p>\n", "annotation": ": sqlglot.expressions.Expression"}, "sqlglot.diff.Move": {"fullname": "sqlglot.diff.Move", "modulename": "sqlglot.diff", "qualname": "Move", "kind": "class", "doc": "<p>Indicates that an existing node's position within the tree has changed</p>\n"}, "sqlglot.diff.Move.__init__": {"fullname": "sqlglot.diff.Move.__init__", "modulename": "sqlglot.diff", "qualname": "Move.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span>)</span>"}, "sqlglot.diff.Move.expression": {"fullname": "sqlglot.diff.Move.expression", "modulename": "sqlglot.diff", "qualname": "Move.expression", "kind": "variable", "doc": "<p></p>\n", "annotation": ": sqlglot.expressions.Expression"}, "sqlglot.diff.Update": {"fullname": "sqlglot.diff.Update", "modulename": "sqlglot.diff", "qualname": "Update", "kind": "class", "doc": "<p>Indicates that an existing node has been updated</p>\n"}, "sqlglot.diff.Update.__init__": {"fullname": "sqlglot.diff.Update.__init__", "modulename": "sqlglot.diff", "qualname": "Update.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">source</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">target</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span>)</span>"}, "sqlglot.diff.Update.source": {"fullname": "sqlglot.diff.Update.source", "modulename": "sqlglot.diff", "qualname": "Update.source", "kind": "variable", "doc": "<p></p>\n", "annotation": ": sqlglot.expressions.Expression"}, "sqlglot.diff.Update.target": {"fullname": "sqlglot.diff.Update.target", "modulename": "sqlglot.diff", "qualname": "Update.target", "kind": "variable", "doc": "<p></p>\n", "annotation": ": sqlglot.expressions.Expression"}, "sqlglot.diff.Keep": {"fullname": "sqlglot.diff.Keep", "modulename": "sqlglot.diff", "qualname": "Keep", "kind": "class", "doc": "<p>Indicates that an existing node hasn't been changed</p>\n"}, "sqlglot.diff.Keep.__init__": {"fullname": "sqlglot.diff.Keep.__init__", "modulename": "sqlglot.diff", "qualname": "Keep.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">source</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">target</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span>)</span>"}, "sqlglot.diff.Keep.source": {"fullname": "sqlglot.diff.Keep.source", "modulename": "sqlglot.diff", "qualname": "Keep.source", "kind": "variable", "doc": "<p></p>\n", "annotation": ": sqlglot.expressions.Expression"}, "sqlglot.diff.Keep.target": {"fullname": "sqlglot.diff.Keep.target", "modulename": "sqlglot.diff", "qualname": "Keep.target", "kind": "variable", "doc": "<p></p>\n", "annotation": ": sqlglot.expressions.Expression"}, "sqlglot.diff.diff": {"fullname": "sqlglot.diff.diff", "modulename": "sqlglot.diff", "qualname": "diff", "kind": "function", "doc": "<p>Returns the list of changes between the source and the target expressions.</p>\n\n<h6 id=\"examples\">Examples:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">diff</span><span class=\"p\">(</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"a + b"</span><span class=\"p\">),</span> <span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"a + c"</span><span class=\"p\">))</span>\n<span class=\"go\">[</span>\n<span class=\"go\"> Remove(expression=(COLUMN this: (IDENTIFIER this: b, quoted: False))),</span>\n<span class=\"go\"> Insert(expression=(COLUMN this: (IDENTIFIER this: c, quoted: False))),</span>\n<span class=\"go\"> Keep(</span>\n<span class=\"go\"> source=(ADD this: ...),</span>\n<span class=\"go\"> target=(ADD this: ...)</span>\n<span class=\"go\"> ),</span>\n<span class=\"go\"> Keep(</span>\n<span class=\"go\"> source=(COLUMN this: (IDENTIFIER this: a, quoted: False)),</span>\n<span class=\"go\"> target=(COLUMN this: (IDENTIFIER this: a, quoted: False))</span>\n<span class=\"go\"> ),</span>\n<span class=\"go\">]</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>source:</strong> the source expression.</li>\n<li><strong>target:</strong> the target expression against which the diff should be calculated.</li>\n<li><strong>matchings:</strong> the list of pre-matched node pairs which is used to help the algorithm's\nheuristics produce better results for subtrees that are known by a caller to be matching.\nNote: expression references in this list must refer to the same node objects that are\nreferenced in source / target trees.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>the list of Insert, Remove, Move, Update and Keep objects for each node in the source and the\n target expression trees. This list represents a sequence of steps needed to transform the source\n expression tree into the target one.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">source</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">target</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">matchings</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">Tuple</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">kwargs</span><span class=\"p\">:</span> <span class=\"n\">Any</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">diff</span><span class=\"o\">.</span><span class=\"n\">Insert</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">diff</span><span class=\"o\">.</span><span class=\"n\">Remove</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">diff</span><span class=\"o\">.</span><span class=\"n\">Move</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">diff</span><span class=\"o\">.</span><span class=\"n\">Update</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">diff</span><span class=\"o\">.</span><span class=\"n\">Keep</span><span class=\"p\">]]</span>:</span></span>", "funcdef": "def"}, "sqlglot.diff.UPDATABLE_EXPRESSION_TYPES": {"fullname": "sqlglot.diff.UPDATABLE_EXPRESSION_TYPES", "modulename": "sqlglot.diff", "qualname": "UPDATABLE_EXPRESSION_TYPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "(<class 'sqlglot.expressions.Boolean'>, <class 'sqlglot.expressions.DataType'>, <class 'sqlglot.expressions.Literal'>, <class 'sqlglot.expressions.Table'>, <class 'sqlglot.expressions.Column'>, <class 'sqlglot.expressions.Lambda'>)"}, "sqlglot.diff.IGNORED_LEAF_EXPRESSION_TYPES": {"fullname": "sqlglot.diff.IGNORED_LEAF_EXPRESSION_TYPES", "modulename": "sqlglot.diff", "qualname": "IGNORED_LEAF_EXPRESSION_TYPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "(<class 'sqlglot.expressions.Identifier'>,)"}, "sqlglot.diff.ChangeDistiller": {"fullname": "sqlglot.diff.ChangeDistiller", "modulename": "sqlglot.diff", "qualname": "ChangeDistiller", "kind": "class", "doc": "<p>The implementation of the Change Distiller algorithm described by Beat Fluri and Martin Pinzger in\ntheir paper <a href=\"https://ieeexplore.ieee.org/document/4339230\">https://ieeexplore.ieee.org/document/4339230</a>, which in turn is based on the algorithm by\nChawathe et al. described in <a href=\"http://ilpubs.stanford.edu:8090/115/1/1995-46.pdf\">http://ilpubs.stanford.edu:8090/115/1/1995-46.pdf</a>.</p>\n"}, "sqlglot.diff.ChangeDistiller.__init__": {"fullname": "sqlglot.diff.ChangeDistiller.__init__", "modulename": "sqlglot.diff", "qualname": "ChangeDistiller.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">f</span><span class=\"p\">:</span> <span class=\"nb\">float</span> <span class=\"o\">=</span> <span class=\"mf\">0.6</span>, </span><span class=\"param\"><span class=\"n\">t</span><span class=\"p\">:</span> <span class=\"nb\">float</span> <span class=\"o\">=</span> <span class=\"mf\">0.6</span></span>)</span>"}, "sqlglot.diff.ChangeDistiller.f": {"fullname": "sqlglot.diff.ChangeDistiller.f", "modulename": "sqlglot.diff", "qualname": "ChangeDistiller.f", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.diff.ChangeDistiller.t": {"fullname": "sqlglot.diff.ChangeDistiller.t", "modulename": "sqlglot.diff", "qualname": "ChangeDistiller.t", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.diff.ChangeDistiller.diff": {"fullname": "sqlglot.diff.ChangeDistiller.diff", "modulename": "sqlglot.diff", "qualname": "ChangeDistiller.diff", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">source</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">target</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">matchings</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">Tuple</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">diff</span><span class=\"o\">.</span><span class=\"n\">Insert</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">diff</span><span class=\"o\">.</span><span class=\"n\">Remove</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">diff</span><span class=\"o\">.</span><span class=\"n\">Move</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">diff</span><span class=\"o\">.</span><span class=\"n\">Update</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">diff</span><span class=\"o\">.</span><span class=\"n\">Keep</span><span class=\"p\">]]</span>:</span></span>", "funcdef": "def"}, "sqlglot.errors": {"fullname": "sqlglot.errors", "modulename": "sqlglot.errors", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.errors.ErrorLevel": {"fullname": "sqlglot.errors.ErrorLevel", "modulename": "sqlglot.errors", "qualname": "ErrorLevel", "kind": "class", "doc": "<p>An enumeration.</p>\n", "bases": "sqlglot.helper.AutoName"}, "sqlglot.errors.ErrorLevel.IGNORE": {"fullname": "sqlglot.errors.ErrorLevel.IGNORE", "modulename": "sqlglot.errors", "qualname": "ErrorLevel.IGNORE", "kind": "variable", "doc": "<p>Ignore all errors.</p>\n", "default_value": "<ErrorLevel.IGNORE: 'IGNORE'>"}, "sqlglot.errors.ErrorLevel.WARN": {"fullname": "sqlglot.errors.ErrorLevel.WARN", "modulename": "sqlglot.errors", "qualname": "ErrorLevel.WARN", "kind": "variable", "doc": "<p>Log all errors.</p>\n", "default_value": "<ErrorLevel.WARN: 'WARN'>"}, "sqlglot.errors.ErrorLevel.RAISE": {"fullname": "sqlglot.errors.ErrorLevel.RAISE", "modulename": "sqlglot.errors", "qualname": "ErrorLevel.RAISE", "kind": "variable", "doc": "<p>Collect all errors and raise a single exception.</p>\n", "default_value": "<ErrorLevel.RAISE: 'RAISE'>"}, "sqlglot.errors.ErrorLevel.IMMEDIATE": {"fullname": "sqlglot.errors.ErrorLevel.IMMEDIATE", "modulename": "sqlglot.errors", "qualname": "ErrorLevel.IMMEDIATE", "kind": "variable", "doc": "<p>Immediately raise an exception on the first error found.</p>\n", "default_value": "<ErrorLevel.IMMEDIATE: 'IMMEDIATE'>"}, "sqlglot.errors.SqlglotError": {"fullname": "sqlglot.errors.SqlglotError", "modulename": "sqlglot.errors", "qualname": "SqlglotError", "kind": "class", "doc": "<p>Common base class for all non-exit exceptions.</p>\n", "bases": "builtins.Exception"}, "sqlglot.errors.UnsupportedError": {"fullname": "sqlglot.errors.UnsupportedError", "modulename": "sqlglot.errors", "qualname": "UnsupportedError", "kind": "class", "doc": "<p>Common base class for all non-exit exceptions.</p>\n", "bases": "SqlglotError"}, "sqlglot.errors.ParseError": {"fullname": "sqlglot.errors.ParseError", "modulename": "sqlglot.errors", "qualname": "ParseError", "kind": "class", "doc": "<p>Common base class for all non-exit exceptions.</p>\n", "bases": "SqlglotError"}, "sqlglot.errors.ParseError.__init__": {"fullname": "sqlglot.errors.ParseError.__init__", "modulename": "sqlglot.errors", "qualname": "ParseError.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">message</span><span class=\"p\">:</span> <span class=\"nb\">str</span>, </span><span class=\"param\"><span class=\"n\">errors</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">Any</span><span class=\"p\">]]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span>)</span>"}, "sqlglot.errors.ParseError.errors": {"fullname": "sqlglot.errors.ParseError.errors", "modulename": "sqlglot.errors", "qualname": "ParseError.errors", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.errors.ParseError.new": {"fullname": "sqlglot.errors.ParseError.new", "modulename": "sqlglot.errors", "qualname": "ParseError.new", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">cls</span>,</span><span class=\"param\">\t<span class=\"n\">message</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">description</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">line</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">int</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">col</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">int</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">start_context</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">highlight</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">end_context</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">into_expression</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">errors</span><span class=\"o\">.</span><span class=\"n\">ParseError</span>:</span></span>", "funcdef": "def"}, "sqlglot.errors.TokenError": {"fullname": "sqlglot.errors.TokenError", "modulename": "sqlglot.errors", "qualname": "TokenError", "kind": "class", "doc": "<p>Common base class for all non-exit exceptions.</p>\n", "bases": "SqlglotError"}, "sqlglot.errors.OptimizeError": {"fullname": "sqlglot.errors.OptimizeError", "modulename": "sqlglot.errors", "qualname": "OptimizeError", "kind": "class", "doc": "<p>Common base class for all non-exit exceptions.</p>\n", "bases": "SqlglotError"}, "sqlglot.errors.SchemaError": {"fullname": "sqlglot.errors.SchemaError", "modulename": "sqlglot.errors", "qualname": "SchemaError", "kind": "class", "doc": "<p>Common base class for all non-exit exceptions.</p>\n", "bases": "SqlglotError"}, "sqlglot.errors.ExecuteError": {"fullname": "sqlglot.errors.ExecuteError", "modulename": "sqlglot.errors", "qualname": "ExecuteError", "kind": "class", "doc": "<p>Common base class for all non-exit exceptions.</p>\n", "bases": "SqlglotError"}, "sqlglot.errors.concat_messages": {"fullname": "sqlglot.errors.concat_messages", "modulename": "sqlglot.errors", "qualname": "concat_messages", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">errors</span><span class=\"p\">:</span> <span class=\"n\">Sequence</span><span class=\"p\">[</span><span class=\"n\">Any</span><span class=\"p\">]</span>, </span><span class=\"param\"><span class=\"n\">maximum</span><span class=\"p\">:</span> <span class=\"nb\">int</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.errors.merge_errors": {"fullname": "sqlglot.errors.merge_errors", "modulename": "sqlglot.errors", "qualname": "merge_errors", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">errors</span><span class=\"p\">:</span> <span class=\"n\">Sequence</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">errors</span><span class=\"o\">.</span><span class=\"n\">ParseError</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">Any</span><span class=\"p\">]]</span>:</span></span>", "funcdef": "def"}, "sqlglot.executor": {"fullname": "sqlglot.executor", "modulename": "sqlglot.executor", "kind": "module", "doc": "<h1 id=\"writing-a-python-sql-engine-from-scratch\">Writing a Python SQL engine from scratch</h1>\n\n<p><a href=\"https://www.linkedin.com/in/toby-mao/\">Toby Mao</a></p>\n\n<h2 id=\"introduction\">Introduction</h2>\n\n<p>When I first started writing SQLGlot in early 2021, my goal was just to translate SQL queries from SparkSQL to Presto and vice versa. However, over the last year and a half, I've ended up with a full-fledged SQL engine. SQLGlot can now parse and transpile between <a href=\"https://github.com/tobymao/sqlglot/blob/main/sqlglot/dialects/__init__.py\">18 SQL dialects</a> and can execute all 24 <a href=\"https://www.tpc.org/tpch/\">TPC-H</a> SQL queries. The parser and engine are all written from scratch using Python.</p>\n\n<p>This post will cover <a href=\"#why\">why</a> I went through the effort of creating a Python SQL engine and <a href=\"#how\">how</a> a simple query goes from a string to actually transforming data. The following steps are briefly summarized:</p>\n\n<ul>\n<li><a href=\"#tokenizing\">Tokenizing</a></li>\n<li><a href=\"#parsing\">Parsing</a></li>\n<li><a href=\"#optimizing\">Optimizing</a></li>\n<li><a href=\"#planning\">Planning</a></li>\n<li><a href=\"#executing\">Executing</a></li>\n</ul>\n\n<h2 id=\"why\">Why?</h2>\n\n<p>I started working on SQLGlot because of my work on the <a href=\"https://netflixtechblog.com/reimagining-experimentation-analysis-at-netflix-71356393af21\">experimentation and metrics platform</a> at Netflix, where I built tools that allowed data scientists to define and compute SQL-based metrics. Netflix relied on multiple engines to query data (Spark, Presto, and Druid), so my team built the metrics platform around <a href=\"https://github.com/kayak/pypika\">PyPika</a>, a Python SQL query builder. This way, definitions could be reused across multiple engines. However, it became quickly apparent that writing python code to programmatically generate SQL was challenging for data scientists, especially those with academic backgrounds, since they were mostly familiar with R and SQL. At the time, the only Python SQL parser was <a href=\"[https://github.com/andialbrecht/sqlparse\">sqlparse</a>, which is not actually a parser but a tokenizer, so having users write raw SQL into the platform wasn't really an option. Some time later, I randomly stumbled across <a href=\"https://craftinginterpreters.com/\">Crafting Interpreters</a> and realized that I could use it as a guide towards creating my own SQL parser/transpiler.</p>\n\n<p>Why did I do this? Isn't a Python SQL engine going to be extremely slow?</p>\n\n<p>The main reason why I ended up building a SQL engine was...just for <strong>entertainment</strong>. It's been fun learning about all the things required to actually run a SQL query, and seeing it actually work is extremely rewarding. Before SQLGlot, I had zero experience with lexers, parsers, or compilers.</p>\n\n<p>In terms of practical use cases, I planned to use the Python SQL engine for unit testing SQL pipelines. Big data pipelines are tough to test because many of the engines are not open source and cannot be run locally. With SQLGlot, you can take a SQL query targeting a warehouse such as <a href=\"https://www.snowflake.com/en/\">Snowflake</a> and seamlessly run it in CI on mock Python data. It's easy to mock data and create arbitrary <a href=\"https://en.wikipedia.org/wiki/User-defined_function\">UDFs</a> because everything is just Python. Although the implementation is slow and unsuitable for large amounts of data (> 1 million rows), there's very little overhead/startup and you can run queries on test data in a couple of milliseconds.</p>\n\n<p>Finally, the components that have been built to support execution can be used as a <strong>foundation</strong> for a faster engine. I'm inspired by what <a href=\"https://github.com/apache/calcite\">Apache Calcite</a> has done for the JVM world. Even though Python is commonly used for data, there hasn't been a Calcite for Python. So, you could say that SQLGlot aims to be that framework. For example, it wouldn't take much work to replace the Python execution engine with numpy/pandas/arrow to become a respectably-performing query engine. The implementation would be able to leverage the parser, optimizer, and logical planner, only needing to implement physical execution. There is a lot of work in the Python ecosystem around high performance vectorized computation, which I think could benefit from a pure Python-based <a href=\"https://en.wikipedia.org/wiki/Abstract_syntax_tree\">AST</a>/<a href=\"https://en.wikipedia.org/wiki/Query_plan\">plan</a>. Parsing and planning doesn't have to be fast when the bottleneck of running queries is processing terabytes of data. So, having a Python-based ecosystem around SQL is beneficial given the ease of development in Python, despite not having bare metal performance.</p>\n\n<p>Parts of SQLGlot's toolkit are being used today by the following:</p>\n\n<ul>\n<li><a href=\"https://github.com/ibis-project/ibis\">Ibis</a>: A Python library that provides a lightweight, universal interface for data wrangling.\n<ul>\n<li>Uses the Python SQL expression builder and leverages the optimizer/planner to convert SQL into dataframe operations.</li>\n</ul></li>\n<li><a href=\"https://github.com/kelsin/mysql-mimic\">mysql-mimic</a>: Pure-Python implementation of the MySQL server wire protocol\n<ul>\n<li>Parses / transforms SQL and executes INFORMATION_SCHEMA queries.</li>\n</ul></li>\n<li><a href=\"https://github.com/marsupialtail/quokka\">Quokka</a>: Push-based vectorized query engine\n<ul>\n<li>Parse and optimizes SQL.</li>\n</ul></li>\n<li><a href=\"https://github.com/moj-analytical-services/splink\">Splink</a>: Fast, accurate and scalable probabilistic data linkage using your choice of SQL backend.\n<ul>\n<li>Transpiles queries.</li>\n</ul></li>\n</ul>\n\n<h2 id=\"how\">How?</h2>\n\n<p>There are many steps involved with actually running a simple query like:</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"k\">SELECT</span>\n<span class=\"w\"> </span><span class=\"n\">bar</span><span class=\"p\">.</span><span class=\"n\">a</span><span class=\"p\">,</span>\n<span class=\"w\"> </span><span class=\"n\">b</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"w\"> </span><span class=\"k\">AS</span><span class=\"w\"> </span><span class=\"n\">b</span>\n<span class=\"k\">FROM</span><span class=\"w\"> </span><span class=\"n\">bar</span>\n<span class=\"k\">JOIN</span><span class=\"w\"> </span><span class=\"n\">baz</span>\n<span class=\"w\"> </span><span class=\"k\">ON</span><span class=\"w\"> </span><span class=\"n\">bar</span><span class=\"p\">.</span><span class=\"n\">a</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"n\">baz</span><span class=\"p\">.</span><span class=\"n\">a</span>\n<span class=\"k\">WHERE</span><span class=\"w\"> </span><span class=\"n\">bar</span><span class=\"p\">.</span><span class=\"n\">a</span><span class=\"w\"> </span><span class=\"o\">></span><span class=\"w\"> </span><span class=\"mi\">1</span>\n</code></pre>\n</div>\n\n<p>In this post, I'll walk through all the steps SQLGlot takes to run this query over Python objects.</p>\n\n<h2 id=\"tokenizing\">Tokenizing</h2>\n\n<p>The first step is to convert the sql string into a list of tokens. SQLGlot's tokenizer is quite simple and can be found <a href=\"https://github.com/tobymao/sqlglot/blob/main/sqlglot/tokens.py\">here</a>. In a while loop, it checks each character and either appends the character to the current token, or makes a new token.</p>\n\n<p>Running the SQLGlot tokenizer shows the output.</p>\n\n<p><img src=\"data:image/png;base64,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\" alt=\"Tokenizer Output\" /></p>\n\n<p>Each keyword has been converted to a SQLGlot Token object. Each token has some metadata associated with it, like line/column information for error messages. Comments are also a part of the token, so that comments can be preserved.</p>\n\n<h2 id=\"parsing\">Parsing</h2>\n\n<p>Once a SQL statement is tokenized, we don't need to worry about white space and other formatting, so it's easier to work with. We can now convert the list of tokens into an AST. The SQLGlot <a href=\"https://github.com/tobymao/sqlglot/blob/main/sqlglot/parser.py\">parser</a> is a handwritten <a href=\"https://en.wikipedia.org/wiki/Recursive_descent_parser\">recursive descent</a> parser.</p>\n\n<p>Similar to the tokenizer, it consumes the tokens sequentially, but it instead uses a recursive algorithm. The tokens are converted into a single AST node that presents the SQL query. The SQLGlot parser was designed to support various dialects, so it contains many options for overriding parsing functionality.</p>\n\n<p><img src=\"data:image/png;base64,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\" alt=\"Parser Output\" /></p>\n\n<p>The AST is a generic representation of a given SQL query. Each dialect can override or implement its own generator, which can convert an AST object into syntatically-correct SQL.</p>\n\n<h2 id=\"optimizing\">Optimizing</h2>\n\n<p>Once we have our AST, we can transform it into an equivalent query that produces the same results more efficiently. When optimizing queries, most engines first convert the AST into a logical plan and then optimize the plan. However, I chose to <strong>optimize the AST directly</strong> for the following reasons:</p>\n\n<ol>\n<li><p>It's easier to debug and <a href=\"https://github.com/tobymao/sqlglot/blob/main/tests/fixtures/optimizer\">validate</a> the optimizations when the input and output are both SQL.</p></li>\n<li><p>Rules can be applied a la carte to transform SQL into a more desirable form.</p></li>\n<li><p>I wanted a way to generate 'canonical sql'. Having a canonical representation of SQL is useful for understanding if two queries are semantically equivalent (e.g. <code>SELECT 1 + 1</code> and <code>SELECT 2</code>).</p></li>\n</ol>\n\n<p>I've yet to find another engine that takes this approach, but I'm quite happy with this decision. The optimizer currently does not perform any \"physical optimizations\" such as join reordering. Those are left to the execution layer, as additional statistics and information could become relevant.</p>\n\n<p><img 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\" alt=\"Optimizer Output\" /></p>\n\n<p>The optimizer currently has <a href=\"https://github.com/tobymao/sqlglot/tree/main/sqlglot/optimizer\">17 rules</a>. Each of these rules is applied, transforming the AST in place. The combination of these rules creates \"canonical\" sql that can then be more easily converted into a logical plan and executed.</p>\n\n<p>Some example rules are:</p>\n\n<h3 id=\"qualify_tables-and-qualify_columns\">qualify_tables and qualify_columns</h3>\n\n<ul>\n<li>Adds all db/catalog qualifiers to tables and forces an alias.</li>\n<li>Ensure each column is unambiguous and expand stars.</li>\n</ul>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"k\">SELECT</span><span class=\"w\"> </span><span class=\"o\">*</span><span class=\"w\"> </span><span class=\"k\">FROM</span><span class=\"w\"> </span><span class=\"n\">x</span><span class=\"p\">;</span>\n\n<span class=\"k\">SELECT</span><span class=\"w\"> </span><span class=\"ss\">"db"</span><span class=\"p\">.</span><span class=\"ss\">"x"</span><span class=\"w\"> </span><span class=\"k\">AS</span><span class=\"w\"> </span><span class=\"ss\">"x"</span><span class=\"p\">;</span>\n</code></pre>\n</div>\n\n<h3 id=\"simplify\">simplify</h3>\n\n<p>Boolean and math simplification. Check out all the <a href=\"https://github.com/tobymao/sqlglot/blob/main/tests/fixtures/optimizer/simplify.sql\">test cases</a>.</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"p\">((</span><span class=\"k\">NOT</span><span class=\"w\"> </span><span class=\"k\">FALSE</span><span class=\"p\">)</span><span class=\"w\"> </span><span class=\"k\">AND</span><span class=\"w\"> </span><span class=\"p\">(</span><span class=\"n\">x</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"n\">x</span><span class=\"p\">))</span><span class=\"w\"> </span><span class=\"k\">AND</span><span class=\"w\"> </span><span class=\"p\">(</span><span class=\"k\">TRUE</span><span class=\"w\"> </span><span class=\"k\">OR</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"w\"> </span><span class=\"o\"><></span><span class=\"w\"> </span><span class=\"mi\">3</span><span class=\"p\">);</span>\n<span class=\"n\">x</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"n\">x</span><span class=\"p\">;</span>\n\n<span class=\"mi\">1</span><span class=\"w\"> </span><span class=\"o\">+</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"p\">;</span>\n<span class=\"mi\">2</span><span class=\"p\">;</span>\n</code></pre>\n</div>\n\n<h3 id=\"normalize\">normalize</h3>\n\n<p>Attempts to convert all predicates into <a href=\"https://en.wikipedia.org/wiki/Conjunctive_normal_form\">conjunctive normal form</a>.</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"c1\">-- DNF</span>\n<span class=\"p\">(</span><span class=\"n\">A</span><span class=\"w\"> </span><span class=\"k\">AND</span><span class=\"w\"> </span><span class=\"n\">B</span><span class=\"p\">)</span><span class=\"w\"> </span><span class=\"k\">OR</span><span class=\"w\"> </span><span class=\"p\">(</span><span class=\"n\">B</span><span class=\"w\"> </span><span class=\"k\">AND</span><span class=\"w\"> </span><span class=\"k\">C</span><span class=\"w\"> </span><span class=\"k\">AND</span><span class=\"w\"> </span><span class=\"n\">D</span><span class=\"p\">);</span>\n\n<span class=\"c1\">-- CNF</span>\n<span class=\"p\">(</span><span class=\"n\">A</span><span class=\"w\"> </span><span class=\"k\">OR</span><span class=\"w\"> </span><span class=\"k\">C</span><span class=\"p\">)</span><span class=\"w\"> </span><span class=\"k\">AND</span><span class=\"w\"> </span><span class=\"p\">(</span><span class=\"n\">A</span><span class=\"w\"> </span><span class=\"k\">OR</span><span class=\"w\"> </span><span class=\"n\">D</span><span class=\"p\">)</span><span class=\"w\"> </span><span class=\"k\">AND</span><span class=\"w\"> </span><span class=\"n\">B</span><span class=\"p\">;</span>\n</code></pre>\n</div>\n\n<h3 id=\"unnest_subqueries\">unnest_subqueries</h3>\n\n<p>Converts subqueries in predicates into joins.</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"c1\">-- The subquery can be converted into a left join</span>\n<span class=\"k\">SELECT</span><span class=\"w\"> </span><span class=\"o\">*</span>\n<span class=\"k\">FROM</span><span class=\"w\"> </span><span class=\"n\">x</span><span class=\"w\"> </span><span class=\"k\">AS</span><span class=\"w\"> </span><span class=\"n\">x</span>\n<span class=\"k\">WHERE</span><span class=\"w\"> </span><span class=\"p\">(</span>\n<span class=\"w\"> </span><span class=\"k\">SELECT</span><span class=\"w\"> </span><span class=\"n\">y</span><span class=\"p\">.</span><span class=\"n\">a</span><span class=\"w\"> </span><span class=\"k\">AS</span><span class=\"w\"> </span><span class=\"n\">a</span>\n<span class=\"w\"> </span><span class=\"k\">FROM</span><span class=\"w\"> </span><span class=\"n\">y</span><span class=\"w\"> </span><span class=\"k\">AS</span><span class=\"w\"> </span><span class=\"n\">y</span>\n<span class=\"w\"> </span><span class=\"k\">WHERE</span><span class=\"w\"> </span><span class=\"n\">x</span><span class=\"p\">.</span><span class=\"n\">a</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"n\">y</span><span class=\"p\">.</span><span class=\"n\">a</span>\n<span class=\"p\">)</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"p\">;</span>\n\n<span class=\"k\">SELECT</span><span class=\"w\"> </span><span class=\"o\">*</span>\n<span class=\"k\">FROM</span><span class=\"w\"> </span><span class=\"n\">x</span><span class=\"w\"> </span><span class=\"k\">AS</span><span class=\"w\"> </span><span class=\"n\">x</span>\n<span class=\"k\">LEFT</span><span class=\"w\"> </span><span class=\"k\">JOIN</span><span class=\"w\"> </span><span class=\"p\">(</span>\n<span class=\"w\"> </span><span class=\"k\">SELECT</span><span class=\"w\"> </span><span class=\"n\">y</span><span class=\"p\">.</span><span class=\"n\">a</span><span class=\"w\"> </span><span class=\"k\">AS</span><span class=\"w\"> </span><span class=\"n\">a</span>\n<span class=\"w\"> </span><span class=\"k\">FROM</span><span class=\"w\"> </span><span class=\"n\">y</span><span class=\"w\"> </span><span class=\"k\">AS</span><span class=\"w\"> </span><span class=\"n\">y</span>\n<span class=\"w\"> </span><span class=\"k\">WHERE</span><span class=\"w\"> </span><span class=\"k\">TRUE</span>\n<span class=\"w\"> </span><span class=\"k\">GROUP</span><span class=\"w\"> </span><span class=\"k\">BY</span><span class=\"w\"> </span><span class=\"n\">y</span><span class=\"p\">.</span><span class=\"n\">a</span>\n<span class=\"p\">)</span><span class=\"w\"> </span><span class=\"k\">AS</span><span class=\"w\"> </span><span class=\"ss\">"_u_0"</span>\n<span class=\"w\"> </span><span class=\"k\">ON</span><span class=\"w\"> </span><span class=\"n\">x</span><span class=\"p\">.</span><span class=\"n\">a</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"ss\">"_u_0"</span><span class=\"p\">.</span><span class=\"n\">a</span>\n<span class=\"k\">WHERE</span><span class=\"w\"> </span><span class=\"p\">(</span><span class=\"ss\">"_u_0"</span><span class=\"p\">.</span><span class=\"n\">a</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"w\"> </span><span class=\"k\">AND</span><span class=\"w\"> </span><span class=\"k\">NOT</span><span class=\"w\"> </span><span class=\"ss\">"_u_0"</span><span class=\"p\">.</span><span class=\"n\">a</span><span class=\"w\"> </span><span class=\"k\">IS</span><span class=\"w\"> </span><span class=\"k\">NULL</span><span class=\"p\">)</span>\n</code></pre>\n</div>\n\n<h3 id=\"pushdown_predicates\">pushdown_predicates</h3>\n\n<p>Push down filters into the innermost query.</p>\n\n<div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"k\">SELECT</span><span class=\"w\"> </span><span class=\"o\">*</span>\n<span class=\"k\">FROM</span><span class=\"w\"> </span><span class=\"p\">(</span>\n<span class=\"w\"> </span><span class=\"k\">SELECT</span><span class=\"w\"> </span><span class=\"o\">*</span>\n<span class=\"w\"> </span><span class=\"k\">FROM</span><span class=\"w\"> </span><span class=\"n\">x</span><span class=\"w\"> </span><span class=\"k\">AS</span><span class=\"w\"> </span><span class=\"n\">x</span>\n<span class=\"p\">)</span><span class=\"w\"> </span><span class=\"k\">AS</span><span class=\"w\"> </span><span class=\"n\">y</span>\n<span class=\"k\">WHERE</span><span class=\"w\"> </span><span class=\"n\">y</span><span class=\"p\">.</span><span class=\"n\">a</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"mi\">1</span><span class=\"p\">;</span>\n\n<span class=\"k\">SELECT</span><span class=\"w\"> </span><span class=\"o\">*</span>\n<span class=\"k\">FROM</span><span class=\"w\"> </span><span class=\"p\">(</span>\n<span class=\"w\"> </span><span class=\"k\">SELECT</span><span class=\"w\"> </span><span class=\"o\">*</span>\n<span class=\"w\"> </span><span class=\"k\">FROM</span><span class=\"w\"> </span><span class=\"n\">x</span><span class=\"w\"> </span><span class=\"k\">AS</span><span class=\"w\"> </span><span class=\"n\">x</span>\n<span class=\"w\"> </span><span class=\"k\">WHERE</span><span class=\"w\"> </span><span class=\"n\">y</span><span class=\"p\">.</span><span class=\"n\">a</span><span class=\"w\"> </span><span class=\"o\">=</span><span class=\"w\"> </span><span class=\"mi\">1</span>\n<span class=\"p\">)</span><span class=\"w\"> </span><span class=\"k\">AS</span><span class=\"w\"> </span><span class=\"n\">y</span><span class=\"w\"> </span><span class=\"k\">WHERE</span><span class=\"w\"> </span><span class=\"k\">TRUE</span>\n</code></pre>\n</div>\n\n<h3 id=\"annotate_types\">annotate_types</h3>\n\n<p>Infer all types throughout the AST given schema information and function type definitions.</p>\n\n<h2 id=\"planning\">Planning</h2>\n\n<p>After the SQL AST has been \"optimized\", it's much easier to <a href=\"https://github.com/tobymao/sqlglot/blob/main/sqlglot/planner.py\">convert into a logical plan</a>. The AST is traversed and converted into a <a href=\"https://en.wikipedia.org/wiki/Directed_acyclic_graph\">DAG</a> consisting of one of five steps. The different steps are:</p>\n\n<h3 id=\"scan\">Scan</h3>\n\n<p>Selects columns from a table, applies projections, and finally filters the table.</p>\n\n<h3 id=\"sort\">Sort</h3>\n\n<p>Sorts a table for order by expressions.</p>\n\n<h3 id=\"set\">Set</h3>\n\n<p>Applies the operators union/union all/except/intersect.</p>\n\n<h3 id=\"aggregate\">Aggregate</h3>\n\n<p>Applies an aggregation/group by.</p>\n\n<h3 id=\"join\">Join</h3>\n\n<p>Joins multiple tables together.</p>\n\n<p><img src=\"data:image/png;base64,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\" alt=\"Planner Output\" /></p>\n\n<p>The logical plan is quite simple and contains the information required to convert it into a physical plan (execution).</p>\n\n<h2 id=\"executing\">Executing</h2>\n\n<p>Finally, we can actually execute the SQL query. The <a href=\"https://github.com/tobymao/sqlglot/blob/main/sqlglot/executor/python.py\">Python engine</a> is not fast, but it's very small (~400 LOC)! It iterates the DAG with a queue and runs each step, passing each intermediary table to the next step.</p>\n\n<p>In order to keep things simple, it evaluates expressions with <code>eval</code>. Because SQLGlot was built primarily to be a transpiler, it was simple to create a \"Python SQL\" dialect. So a SQL expression <code>x + 1</code> can just be converted into <code>scope['x'] + 1</code>.</p>\n\n<p><img 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\" alt=\"Executor Output\" /></p>\n\n<h2 id=\"whats-next\">What's next</h2>\n\n<p>SQLGlot's main focus will always be on parsing/transpiling, but I plan to continue development on the execution engine. I'd like to pass <a href=\"https://www.tpc.org/tpcds/\">TPC-DS</a>. If someone doesn't beat me to it, I may even take a stab at writing a Pandas/Arrow execution engine.</p>\n\n<p>I'm hoping that over time, SQLGlot will spark the Python SQL ecosystem just like Calcite has for Java.</p>\n\n<h2 id=\"special-thanks\">Special thanks</h2>\n\n<p>SQLGlot would not be what it is without it's core contributors. In particular, the execution engine would not exist without <a href=\"https://github.com/barakalon\">Barak Alon</a> and <a href=\"https://github.com/GeorgeSittas\">George Sittas</a>.</p>\n\n<h2 id=\"get-in-touch\">Get in touch</h2>\n\n<p>If you'd like to chat more about SQLGlot, please join my <a href=\"https://tobikodata.com/slack\">Slack Channel</a>!</p>\n\n<hr />\n"}, "sqlglot.executor.logger": {"fullname": "sqlglot.executor.logger", "modulename": "sqlglot.executor", "qualname": "logger", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Logger sqlglot (WARNING)>"}, "sqlglot.executor.execute": {"fullname": "sqlglot.executor.execute", "modulename": "sqlglot.executor", "qualname": "execute", "kind": "function", "doc": "<p>Run a sql query against data.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>sql:</strong> a sql statement.</li>\n<li><strong>schema:</strong> database schema.\nThis can either be an instance of <code>Schema</code> or a mapping in one of the following forms:\n<ol>\n<li>{table: {col: type}}</li>\n<li>{db: {table: {col: type}}}</li>\n<li>{catalog: {db: {table: {col: type}}}}</li>\n</ol></li>\n<li><strong>read:</strong> the SQL dialect to apply during parsing (eg. \"spark\", \"hive\", \"presto\", \"mysql\").</li>\n<li><strong>dialect:</strong> the SQL dialect (alias for read).</li>\n<li><strong>tables:</strong> additional tables to register.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>Simple columnar data structure.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">sql</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">schema</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">schema</span><span class=\"o\">.</span><span class=\"n\">Schema</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">read</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">tables</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">executor</span><span class=\"o\">.</span><span class=\"n\">table</span><span class=\"o\">.</span><span class=\"n\">Table</span>:</span></span>", "funcdef": "def"}, "sqlglot.executor.context": {"fullname": "sqlglot.executor.context", "modulename": "sqlglot.executor.context", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.executor.context.Context": {"fullname": "sqlglot.executor.context.Context", "modulename": "sqlglot.executor.context", "qualname": "Context", "kind": "class", "doc": "<p>Execution context for sql expressions.</p>\n\n<p>Context is used to hold relevant data tables which can then be queried on with eval.</p>\n\n<p>References to columns can either be scalar or vectors. When set_row is used, column references\nevaluate to scalars while set_range evaluates to vectors. This allows convenient and efficient\nevaluation of aggregation functions.</p>\n"}, "sqlglot.executor.context.Context.__init__": {"fullname": "sqlglot.executor.context.Context.__init__", "modulename": "sqlglot.executor.context", "qualname": "Context.__init__", "kind": "function", "doc": "<p>Args\n tables: representing the scope of the current execution context.\n env: dictionary of functions within the execution context.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">tables</span><span class=\"p\">:</span> <span class=\"n\">Dict</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">executor</span><span class=\"o\">.</span><span class=\"n\">table</span><span class=\"o\">.</span><span class=\"n\">Table</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">env</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span>)</span>"}, "sqlglot.executor.context.Context.tables": {"fullname": "sqlglot.executor.context.Context.tables", "modulename": "sqlglot.executor.context", "qualname": "Context.tables", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.executor.context.Context.range_readers": {"fullname": "sqlglot.executor.context.Context.range_readers", "modulename": "sqlglot.executor.context", "qualname": "Context.range_readers", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.executor.context.Context.row_readers": {"fullname": "sqlglot.executor.context.Context.row_readers", "modulename": "sqlglot.executor.context", "qualname": "Context.row_readers", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.executor.context.Context.env": {"fullname": "sqlglot.executor.context.Context.env", "modulename": "sqlglot.executor.context", "qualname": "Context.env", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.executor.context.Context.eval": {"fullname": "sqlglot.executor.context.Context.eval", "modulename": "sqlglot.executor.context", "qualname": "Context.eval", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">code</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.context.Context.eval_tuple": {"fullname": "sqlglot.executor.context.Context.eval_tuple", "modulename": "sqlglot.executor.context", "qualname": "Context.eval_tuple", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">codes</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.context.Context.table": {"fullname": "sqlglot.executor.context.Context.table", "modulename": "sqlglot.executor.context", "qualname": "Context.table", "kind": "variable", "doc": "<p></p>\n", "annotation": ": sqlglot.executor.table.Table"}, "sqlglot.executor.context.Context.add_columns": {"fullname": "sqlglot.executor.context.Context.add_columns", "modulename": "sqlglot.executor.context", "qualname": "Context.add_columns", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">*</span><span class=\"n\">columns</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.executor.context.Context.columns": {"fullname": "sqlglot.executor.context.Context.columns", "modulename": "sqlglot.executor.context", "qualname": "Context.columns", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Tuple"}, "sqlglot.executor.context.Context.table_iter": {"fullname": "sqlglot.executor.context.Context.table_iter", "modulename": "sqlglot.executor.context", "qualname": "Context.table_iter", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">table</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">executor</span><span class=\"o\">.</span><span class=\"n\">table</span><span class=\"o\">.</span><span class=\"n\">TableIter</span>:</span></span>", "funcdef": "def"}, "sqlglot.executor.context.Context.filter": {"fullname": "sqlglot.executor.context.Context.filter", "modulename": "sqlglot.executor.context", "qualname": "Context.filter", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">condition</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.executor.context.Context.sort": {"fullname": "sqlglot.executor.context.Context.sort", "modulename": "sqlglot.executor.context", "qualname": "Context.sort", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">key</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.executor.context.Context.set_row": {"fullname": "sqlglot.executor.context.Context.set_row", "modulename": "sqlglot.executor.context", "qualname": "Context.set_row", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">row</span><span class=\"p\">:</span> <span class=\"n\">Tuple</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.executor.context.Context.set_index": {"fullname": "sqlglot.executor.context.Context.set_index", "modulename": "sqlglot.executor.context", "qualname": "Context.set_index", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">index</span><span class=\"p\">:</span> <span class=\"nb\">int</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.executor.context.Context.set_range": {"fullname": "sqlglot.executor.context.Context.set_range", "modulename": "sqlglot.executor.context", "qualname": "Context.set_range", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">start</span><span class=\"p\">:</span> <span class=\"nb\">int</span>, </span><span class=\"param\"><span class=\"n\">end</span><span class=\"p\">:</span> <span class=\"nb\">int</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.executor.env": {"fullname": "sqlglot.executor.env", "modulename": "sqlglot.executor.env", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.executor.env.reverse_key": {"fullname": "sqlglot.executor.env.reverse_key", "modulename": "sqlglot.executor.env", "qualname": "reverse_key", "kind": "class", "doc": "<p></p>\n"}, "sqlglot.executor.env.reverse_key.__init__": {"fullname": "sqlglot.executor.env.reverse_key.__init__", "modulename": "sqlglot.executor.env", "qualname": "reverse_key.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">obj</span></span>)</span>"}, "sqlglot.executor.env.reverse_key.obj": {"fullname": "sqlglot.executor.env.reverse_key.obj", "modulename": "sqlglot.executor.env", "qualname": "reverse_key.obj", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.executor.env.filter_nulls": {"fullname": "sqlglot.executor.env.filter_nulls", "modulename": "sqlglot.executor.env", "qualname": "filter_nulls", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">func</span>, </span><span class=\"param\"><span class=\"n\">empty_null</span><span class=\"o\">=</span><span class=\"kc\">True</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.env.null_if_any": {"fullname": "sqlglot.executor.env.null_if_any", "modulename": "sqlglot.executor.env", "qualname": "null_if_any", "kind": "function", "doc": "<p>Decorator that makes a function return <code>None</code> if any of the <code>required</code> arguments are <code>None</code>.</p>\n\n<p>This also supports decoration with no arguments, e.g.:</p>\n\n<pre><code>@null_if_any\ndef foo(a, b): ...\n</code></pre>\n\n<p>In which case all arguments are required.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"o\">*</span><span class=\"n\">required</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.env.str_position": {"fullname": "sqlglot.executor.env.str_position", "modulename": "sqlglot.executor.env", "qualname": "str_position", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">substr</span>, </span><span class=\"param\"><span class=\"n\">this</span>, </span><span class=\"param\"><span class=\"n\">position</span><span class=\"o\">=</span><span class=\"kc\">None</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.env.substring": {"fullname": "sqlglot.executor.env.substring", "modulename": "sqlglot.executor.env", "qualname": "substring", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">this</span>, </span><span class=\"param\"><span class=\"n\">start</span><span class=\"o\">=</span><span class=\"kc\">None</span>, </span><span class=\"param\"><span class=\"n\">length</span><span class=\"o\">=</span><span class=\"kc\">None</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.env.cast": {"fullname": "sqlglot.executor.env.cast", "modulename": "sqlglot.executor.env", "qualname": "cast", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">this</span>, </span><span class=\"param\"><span class=\"n\">to</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.env.ordered": {"fullname": "sqlglot.executor.env.ordered", "modulename": "sqlglot.executor.env", "qualname": "ordered", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">this</span>, </span><span class=\"param\"><span class=\"n\">desc</span>, </span><span class=\"param\"><span class=\"n\">nulls_first</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.env.interval": {"fullname": "sqlglot.executor.env.interval", "modulename": "sqlglot.executor.env", "qualname": "interval", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">this</span>, </span><span class=\"param\"><span class=\"n\">unit</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.env.arraytostring": {"fullname": "sqlglot.executor.env.arraytostring", "modulename": "sqlglot.executor.env", "qualname": "arraytostring", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">this</span>, </span><span class=\"param\"><span class=\"n\">expression</span>, </span><span class=\"param\"><span class=\"n\">null</span><span class=\"o\">=</span><span class=\"kc\">None</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.env.jsonextract": {"fullname": "sqlglot.executor.env.jsonextract", "modulename": "sqlglot.executor.env", "qualname": "jsonextract", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">this</span>, </span><span class=\"param\"><span class=\"n\">expression</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.env.ENV": {"fullname": "sqlglot.executor.env.ENV", "modulename": "sqlglot.executor.env", "qualname": "ENV", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'exp': <module 'sqlglot.expressions' from '/home/runner/work/sqlglot/sqlglot/sqlglot/expressions.py'>, 'ARRAYAGG': <class 'list'>, 'ARRAYUNIQUEAGG': <function <lambda>>, 'AVG': <function fmean>, 'COUNT': <function <lambda>>, 'MAX': <function max>, 'MIN': <function min>, 'SUM': <function sum>, 'ABS': <function <lambda>>, 'ADD': <function <lambda>>, 'ARRAYANY': <function <lambda>>, 'ARRAYTOSTRING': <function arraytostring>, 'BETWEEN': <function <lambda>>, 'BITWISEAND': <function <lambda>>, 'BITWISELEFTSHIFT': <function <lambda>>, 'BITWISEOR': <function <lambda>>, 'BITWISERIGHTSHIFT': <function <lambda>>, 'BITWISEXOR': <function <lambda>>, 'CAST': <function cast>, 'COALESCE': <function <lambda>>, 'CONCAT': <function <lambda>>, 'SAFECONCAT': <function <lambda>>, 'CONCATWS': <function <lambda>>, 'DATEDIFF': <function <lambda>>, 'DATESTRTODATE': <function <lambda>>, 'DIV': <function <lambda>>, 'DOT': <function <lambda>>, 'EQ': <function <lambda>>, 'EXTRACT': <function <lambda>>, 'GT': <function <lambda>>, 'GTE': <function <lambda>>, 'IF': <function <lambda>>, 'INTDIV': <function <lambda>>, 'INTERVAL': <function interval>, 'JSONEXTRACT': <function jsonextract>, 'LEFT': <function <lambda>>, 'LIKE': <function <lambda>>, 'LOWER': <function <lambda>>, 'LT': <function <lambda>>, 'LTE': <function <lambda>>, 'MAP': <function <lambda>>, 'MOD': <function <lambda>>, 'MUL': <function <lambda>>, 'NEQ': <function <lambda>>, 'ORD': <function ord>, 'ORDERED': <function ordered>, 'POW': <built-in function pow>, 'RIGHT': <function <lambda>>, 'ROUND': <function <lambda>>, 'STRPOSITION': <function str_position>, 'SUB': <function <lambda>>, 'SUBSTRING': <function substring>, 'TIMESTRTOTIME': <function <lambda>>, 'UPPER': <function <lambda>>, 'YEAR': <function <lambda>>, 'MONTH': <function <lambda>>, 'DAY': <function <lambda>>, 'CURRENTDATETIME': <built-in method now of type object>, 'CURRENTTIMESTAMP': <built-in method now of type object>, 'CURRENTTIME': <built-in method now of type object>, 'CURRENTDATE': <built-in method today of type object>, 'STRFTIME': <function <lambda>>, 'STRTOTIME': <function <lambda>>, 'TRIM': <function <lambda>>, 'STRUCT': <function <lambda>>, 'UNIXTOTIME': <function <lambda>>}"}, "sqlglot.executor.python": {"fullname": "sqlglot.executor.python", "modulename": "sqlglot.executor.python", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.executor.python.PythonExecutor": {"fullname": "sqlglot.executor.python.PythonExecutor", "modulename": "sqlglot.executor.python", "qualname": "PythonExecutor", "kind": "class", "doc": "<p></p>\n"}, "sqlglot.executor.python.PythonExecutor.__init__": {"fullname": "sqlglot.executor.python.PythonExecutor.__init__", "modulename": "sqlglot.executor.python", "qualname": "PythonExecutor.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">env</span><span class=\"o\">=</span><span class=\"kc\">None</span>, </span><span class=\"param\"><span class=\"n\">tables</span><span class=\"o\">=</span><span class=\"kc\">None</span></span>)</span>"}, "sqlglot.executor.python.PythonExecutor.generator": {"fullname": "sqlglot.executor.python.PythonExecutor.generator", "modulename": "sqlglot.executor.python", "qualname": "PythonExecutor.generator", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.executor.python.PythonExecutor.env": {"fullname": "sqlglot.executor.python.PythonExecutor.env", "modulename": "sqlglot.executor.python", "qualname": "PythonExecutor.env", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.executor.python.PythonExecutor.tables": {"fullname": "sqlglot.executor.python.PythonExecutor.tables", "modulename": "sqlglot.executor.python", "qualname": "PythonExecutor.tables", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.executor.python.PythonExecutor.execute": {"fullname": "sqlglot.executor.python.PythonExecutor.execute", "modulename": "sqlglot.executor.python", "qualname": "PythonExecutor.execute", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">plan</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.python.PythonExecutor.generate": {"fullname": "sqlglot.executor.python.PythonExecutor.generate", "modulename": "sqlglot.executor.python", "qualname": "PythonExecutor.generate", "kind": "function", "doc": "<p>Convert a SQL expression into literal Python code and compile it into bytecode.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.python.PythonExecutor.generate_tuple": {"fullname": "sqlglot.executor.python.PythonExecutor.generate_tuple", "modulename": "sqlglot.executor.python", "qualname": "PythonExecutor.generate_tuple", "kind": "function", "doc": "<p>Convert an array of SQL expressions into tuple of Python byte code.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expressions</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.python.PythonExecutor.context": {"fullname": "sqlglot.executor.python.PythonExecutor.context", "modulename": "sqlglot.executor.python", "qualname": "PythonExecutor.context", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">tables</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.python.PythonExecutor.table": {"fullname": "sqlglot.executor.python.PythonExecutor.table", "modulename": "sqlglot.executor.python", "qualname": "PythonExecutor.table", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expressions</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.python.PythonExecutor.scan": {"fullname": "sqlglot.executor.python.PythonExecutor.scan", "modulename": "sqlglot.executor.python", "qualname": "PythonExecutor.scan", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">step</span>, </span><span class=\"param\"><span class=\"n\">context</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.python.PythonExecutor.static": {"fullname": "sqlglot.executor.python.PythonExecutor.static", "modulename": "sqlglot.executor.python", "qualname": "PythonExecutor.static", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.python.PythonExecutor.scan_table": {"fullname": "sqlglot.executor.python.PythonExecutor.scan_table", "modulename": "sqlglot.executor.python", "qualname": "PythonExecutor.scan_table", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">step</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.python.PythonExecutor.scan_csv": {"fullname": "sqlglot.executor.python.PythonExecutor.scan_csv", "modulename": "sqlglot.executor.python", "qualname": "PythonExecutor.scan_csv", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">step</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.python.PythonExecutor.join": {"fullname": "sqlglot.executor.python.PythonExecutor.join", "modulename": "sqlglot.executor.python", "qualname": "PythonExecutor.join", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">step</span>, </span><span class=\"param\"><span class=\"n\">context</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.python.PythonExecutor.nested_loop_join": {"fullname": "sqlglot.executor.python.PythonExecutor.nested_loop_join", "modulename": "sqlglot.executor.python", "qualname": "PythonExecutor.nested_loop_join", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">_join</span>, </span><span class=\"param\"><span class=\"n\">source_context</span>, </span><span class=\"param\"><span class=\"n\">join_context</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.python.PythonExecutor.hash_join": {"fullname": "sqlglot.executor.python.PythonExecutor.hash_join", "modulename": "sqlglot.executor.python", "qualname": "PythonExecutor.hash_join", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">join</span>, </span><span class=\"param\"><span class=\"n\">source_context</span>, </span><span class=\"param\"><span class=\"n\">join_context</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.python.PythonExecutor.aggregate": {"fullname": "sqlglot.executor.python.PythonExecutor.aggregate", "modulename": "sqlglot.executor.python", "qualname": "PythonExecutor.aggregate", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">step</span>, </span><span class=\"param\"><span class=\"n\">context</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.python.PythonExecutor.sort": {"fullname": "sqlglot.executor.python.PythonExecutor.sort", "modulename": "sqlglot.executor.python", "qualname": "PythonExecutor.sort", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">step</span>, </span><span class=\"param\"><span class=\"n\">context</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.python.PythonExecutor.set_operation": {"fullname": "sqlglot.executor.python.PythonExecutor.set_operation", "modulename": "sqlglot.executor.python", "qualname": "PythonExecutor.set_operation", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">step</span>, </span><span class=\"param\"><span class=\"n\">context</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.python.Python": {"fullname": "sqlglot.executor.python.Python", "modulename": "sqlglot.executor.python", "qualname": "Python", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.dialects.dialect.Dialect"}, "sqlglot.executor.python.Python.Tokenizer": {"fullname": "sqlglot.executor.python.Python.Tokenizer", "modulename": "sqlglot.executor.python", "qualname": "Python.Tokenizer", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.tokens.Tokenizer"}, "sqlglot.executor.python.Python.Tokenizer.STRING_ESCAPES": {"fullname": "sqlglot.executor.python.Python.Tokenizer.STRING_ESCAPES", "modulename": "sqlglot.executor.python", "qualname": "Python.Tokenizer.STRING_ESCAPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "['\\\\']"}, "sqlglot.executor.python.Python.Generator": {"fullname": "sqlglot.executor.python.Python.Generator", "modulename": "sqlglot.executor.python", "qualname": "Python.Generator", "kind": "class", "doc": "<p>Generator converts a given syntax tree to the corresponding SQL string.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>pretty:</strong> Whether to format the produced SQL string.\nDefault: False.</li>\n<li><strong>identify:</strong> Determines when an identifier should be quoted. Possible values are:\nFalse (default): Never quote, except in cases where it's mandatory by the dialect.\nTrue or 'always': Always quote.\n'safe': Only quote identifiers that are case insensitive.</li>\n<li><strong>normalize:</strong> Whether to normalize identifiers to lowercase.\nDefault: False.</li>\n<li><strong>pad:</strong> The pad size in a formatted string. For example, this affects the indentation of\na projection in a query, relative to its nesting level.\nDefault: 2.</li>\n<li><strong>indent:</strong> The indentation size in a formatted string. For example, this affects the\nindentation of subqueries and filters under a <code>WHERE</code> clause.\nDefault: 2.</li>\n<li><strong>normalize_functions:</strong> How to normalize function names. Possible values are:\n\"upper\" or True (default): Convert names to uppercase.\n\"lower\": Convert names to lowercase.\nFalse: Disables function name normalization.</li>\n<li><strong>unsupported_level:</strong> Determines the generator's behavior when it encounters unsupported expressions.\nDefault ErrorLevel.WARN.</li>\n<li><strong>max_unsupported:</strong> Maximum number of unsupported messages to include in a raised UnsupportedError.\nThis is only relevant if unsupported_level is ErrorLevel.RAISE.\nDefault: 3</li>\n<li><strong>leading_comma:</strong> Whether the comma is leading or trailing in select expressions.\nThis is only relevant when generating in pretty mode.\nDefault: False</li>\n<li><strong>max_text_width:</strong> The max number of characters in a segment before creating new lines in pretty mode.\nThe default is on the smaller end because the length only represents a segment and not the true\nline length.\nDefault: 80</li>\n<li><strong>comments:</strong> Whether to preserve comments in the output SQL code.\nDefault: True</li>\n</ul>\n", "bases": "sqlglot.generator.Generator"}, "sqlglot.executor.python.Python.Generator.TRANSFORMS": {"fullname": "sqlglot.executor.python.Python.Generator.TRANSFORMS", "modulename": "sqlglot.executor.python", "qualname": "Python.Generator.TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.Add'>: <function _rename>, <class 'sqlglot.expressions.And'>: <function Python.Generator.<lambda>>, <class 'sqlglot.expressions.ArrayContained'>: <function _rename>, <class 'sqlglot.expressions.ArrayContains'>: <function _rename>, <class 'sqlglot.expressions.ArrayOverlaps'>: <function _rename>, <class 'sqlglot.expressions.Binary'>: <function _rename>, <class 'sqlglot.expressions.BitwiseAnd'>: <function _rename>, <class 'sqlglot.expressions.BitwiseLeftShift'>: <function _rename>, <class 'sqlglot.expressions.BitwiseOr'>: <function _rename>, <class 'sqlglot.expressions.BitwiseRightShift'>: <function _rename>, <class 'sqlglot.expressions.BitwiseXor'>: <function _rename>, <class 'sqlglot.expressions.Collate'>: <function _rename>, <class 'sqlglot.expressions.Connector'>: <function _rename>, <class 'sqlglot.expressions.Corr'>: <function _rename>, <class 'sqlglot.expressions.CovarPop'>: <function _rename>, <class 'sqlglot.expressions.CovarSamp'>: <function _rename>, <class 'sqlglot.expressions.DPipe'>: <function _rename>, <class 'sqlglot.expressions.Distance'>: <function _rename>, <class 'sqlglot.expressions.Div'>: <function _div_sql>, <class 'sqlglot.expressions.Dot'>: <function _rename>, <class 'sqlglot.expressions.EQ'>: <function _rename>, <class 'sqlglot.expressions.Escape'>: <function _rename>, <class 'sqlglot.expressions.GT'>: <function _rename>, <class 'sqlglot.expressions.GTE'>: <function _rename>, <class 'sqlglot.expressions.Glob'>: <function _rename>, <class 'sqlglot.expressions.ILike'>: <function _rename>, <class 'sqlglot.expressions.ILikeAny'>: <function _rename>, <class 'sqlglot.expressions.IntDiv'>: <function _rename>, <class 'sqlglot.expressions.Is'>: <function Python.Generator.<lambda>>, <class 'sqlglot.expressions.JSONArrayContains'>: <function _rename>, <class 'sqlglot.expressions.JSONBContains'>: <function _rename>, <class 'sqlglot.expressions.JSONBExtract'>: <function _rename>, <class 'sqlglot.expressions.JSONBExtractScalar'>: <function _rename>, <class 'sqlglot.expressions.JSONExtract'>: <function _rename>, <class 'sqlglot.expressions.JSONExtractScalar'>: <function _rename>, <class 'sqlglot.expressions.Kwarg'>: <function _rename>, <class 'sqlglot.expressions.LT'>: <function _rename>, <class 'sqlglot.expressions.LTE'>: <function _rename>, <class 'sqlglot.expressions.Like'>: <function _rename>, <class 'sqlglot.expressions.LikeAny'>: <function _rename>, <class 'sqlglot.expressions.Mod'>: <function _rename>, <class 'sqlglot.expressions.Mul'>: <function _rename>, <class 'sqlglot.expressions.NEQ'>: <function _rename>, <class 'sqlglot.expressions.NullSafeEQ'>: <function _rename>, <class 'sqlglot.expressions.NullSafeNEQ'>: <function _rename>, <class 'sqlglot.expressions.Operator'>: <function _rename>, <class 'sqlglot.expressions.Or'>: <function Python.Generator.<lambda>>, <class 'sqlglot.expressions.Overlaps'>: <function _rename>, <class 'sqlglot.expressions.Pow'>: <function _rename>, <class 'sqlglot.expressions.PropertyEQ'>: <function _rename>, <class 'sqlglot.expressions.RegexpILike'>: <function _rename>, <class 'sqlglot.expressions.RegexpLike'>: <function _rename>, <class 'sqlglot.expressions.SimilarTo'>: <function _rename>, <class 'sqlglot.expressions.Slice'>: <function _rename>, <class 'sqlglot.expressions.Sub'>: <function _rename>, <class 'sqlglot.expressions.Xor'>: <function _rename>, <class 'sqlglot.expressions.Abs'>: <function _rename>, <class 'sqlglot.expressions.AddMonths'>: <function _rename>, <class 'sqlglot.expressions.AnonymousAggFunc'>: <function _rename>, <class 'sqlglot.expressions.AnyValue'>: <function _rename>, <class 'sqlglot.expressions.ApproxDistinct'>: <function _rename>, <class 'sqlglot.expressions.ApproxQuantile'>: <function _rename>, <class 'sqlglot.expressions.ApproxTopK'>: <function _rename>, <class 'sqlglot.expressions.ArgMax'>: <function _rename>, <class 'sqlglot.expressions.ArgMin'>: <function _rename>, <class 'sqlglot.expressions.Array'>: <function inline_array_sql>, <class 'sqlglot.expressions.ArrayAgg'>: <function _rename>, <class 'sqlglot.expressions.ArrayAll'>: <function _rename>, <class 'sqlglot.expressions.ArrayAny'>: <function _rename>, <class 'sqlglot.expressions.ArrayConcat'>: <function _rename>, <class 'sqlglot.expressions.ArrayConstructCompact'>: <function _rename>, <class 'sqlglot.expressions.ArrayFilter'>: <function _rename>, <class 'sqlglot.expressions.ArraySize'>: <function _rename>, <class 'sqlglot.expressions.ArraySort'>: <function _rename>, <class 'sqlglot.expressions.ArraySum'>: <function _rename>, <class 'sqlglot.expressions.ArrayToString'>: <function _rename>, <class 'sqlglot.expressions.ArrayUnionAgg'>: <function _rename>, <class 'sqlglot.expressions.ArrayUniqueAgg'>: <function _rename>, <class 'sqlglot.expressions.Avg'>: <function _rename>, <class 'sqlglot.expressions.Case'>: <function _case_sql>, <class 'sqlglot.expressions.Cast'>: <function Python.Generator.<lambda>>, <class 'sqlglot.expressions.CastToStrType'>: <function _rename>, <class 'sqlglot.expressions.Cbrt'>: <function _rename>, <class 'sqlglot.expressions.Ceil'>: <function _rename>, <class 'sqlglot.expressions.Chr'>: <function _rename>, <class 'sqlglot.expressions.Coalesce'>: <function _rename>, <class 'sqlglot.expressions.CombinedAggFunc'>: <function _rename>, <class 'sqlglot.expressions.CombinedParameterizedAgg'>: <function _rename>, <class 'sqlglot.expressions.Concat'>: <function Python.Generator.<lambda>>, <class 'sqlglot.expressions.ConcatWs'>: <function _rename>, <class 'sqlglot.expressions.ConnectByRoot'>: <function _rename>, <class 'sqlglot.expressions.Convert'>: <function _rename>, <class 'sqlglot.expressions.Count'>: <function _rename>, <class 'sqlglot.expressions.CountIf'>: <function _rename>, <class 'sqlglot.expressions.CurrentDate'>: <function _rename>, <class 'sqlglot.expressions.CurrentDatetime'>: <function _rename>, <class 'sqlglot.expressions.CurrentTime'>: <function _rename>, <class 'sqlglot.expressions.CurrentTimestamp'>: <function _rename>, <class 'sqlglot.expressions.CurrentUser'>: <function _rename>, <class 'sqlglot.expressions.Date'>: <function _rename>, <class 'sqlglot.expressions.DateAdd'>: <function _rename>, <class 'sqlglot.expressions.DateDiff'>: <function _rename>, <class 'sqlglot.expressions.DateFromParts'>: <function _rename>, <class 'sqlglot.expressions.DateStrToDate'>: <function _rename>, <class 'sqlglot.expressions.DateSub'>: <function _rename>, <class 'sqlglot.expressions.DateToDateStr'>: <function _rename>, <class 'sqlglot.expressions.DateToDi'>: <function _rename>, <class 'sqlglot.expressions.DateTrunc'>: <function _rename>, <class 'sqlglot.expressions.DatetimeAdd'>: <function _rename>, <class 'sqlglot.expressions.DatetimeDiff'>: <function _rename>, <class 'sqlglot.expressions.DatetimeSub'>: <function _rename>, <class 'sqlglot.expressions.DatetimeTrunc'>: <function _rename>, <class 'sqlglot.expressions.Day'>: <function _rename>, <class 'sqlglot.expressions.DayOfMonth'>: <function _rename>, <class 'sqlglot.expressions.DayOfWeek'>: <function _rename>, <class 'sqlglot.expressions.DayOfYear'>: <function _rename>, <class 'sqlglot.expressions.Decode'>: <function _rename>, <class 'sqlglot.expressions.DiToDate'>: <function _rename>, <class 'sqlglot.expressions.Encode'>: <function _rename>, <class 'sqlglot.expressions.Exp'>: <function _rename>, <class 'sqlglot.expressions.Explode'>: <function _rename>, <class 'sqlglot.expressions.ExplodeOuter'>: <function _rename>, <class 'sqlglot.expressions.Extract'>: <function Python.Generator.<lambda>>, <class 'sqlglot.expressions.First'>: <function _rename>, <class 'sqlglot.expressions.FirstValue'>: <function _rename>, <class 'sqlglot.expressions.Flatten'>: <function _rename>, <class 'sqlglot.expressions.Floor'>: <function _rename>, <class 'sqlglot.expressions.FromBase'>: <function _rename>, <class 'sqlglot.expressions.FromBase64'>: <function _rename>, <class 'sqlglot.expressions.GenerateDateArray'>: <function _rename>, <class 'sqlglot.expressions.GenerateSeries'>: <function _rename>, <class 'sqlglot.expressions.Greatest'>: <function _rename>, <class 'sqlglot.expressions.GroupConcat'>: <function _rename>, <class 'sqlglot.expressions.Hex'>: <function _rename>, <class 'sqlglot.expressions.Hll'>: <function _rename>, <class 'sqlglot.expressions.If'>: <function _rename>, <class 'sqlglot.expressions.Initcap'>: <function _rename>, <class 'sqlglot.expressions.IsInf'>: <function _rename>, <class 'sqlglot.expressions.IsNan'>: <function _rename>, <class 'sqlglot.expressions.JSONArray'>: <function _rename>, <class 'sqlglot.expressions.JSONArrayAgg'>: <function _rename>, <class 'sqlglot.expressions.JSONFormat'>: <function _rename>, <class 'sqlglot.expressions.JSONObject'>: <function _rename>, <class 'sqlglot.expressions.JSONObjectAgg'>: <function _rename>, <class 'sqlglot.expressions.JSONTable'>: <function _rename>, <class 'sqlglot.expressions.Lag'>: <function _rename>, <class 'sqlglot.expressions.Last'>: <function _rename>, <class 'sqlglot.expressions.LastDay'>: <function _rename>, <class 'sqlglot.expressions.LastValue'>: <function _rename>, <class 'sqlglot.expressions.Lead'>: <function _rename>, <class 'sqlglot.expressions.Least'>: <function _rename>, <class 'sqlglot.expressions.Left'>: <function _rename>, <class 'sqlglot.expressions.Length'>: <function _rename>, <class 'sqlglot.expressions.Levenshtein'>: <function _rename>, <class 'sqlglot.expressions.Ln'>: <function _rename>, <class 'sqlglot.expressions.Log'>: <function _rename>, <class 'sqlglot.expressions.LogicalAnd'>: <function _rename>, <class 'sqlglot.expressions.LogicalOr'>: <function _rename>, <class 'sqlglot.expressions.Lower'>: <function _rename>, <class 'sqlglot.expressions.LowerHex'>: <function _rename>, <class 'sqlglot.expressions.MD5'>: <function _rename>, <class 'sqlglot.expressions.MD5Digest'>: <function _rename>, <class 'sqlglot.expressions.Map'>: <function _rename>, <class 'sqlglot.expressions.MapFromEntries'>: <function _rename>, <class 'sqlglot.expressions.MatchAgainst'>: <function _rename>, <class 'sqlglot.expressions.Max'>: <function _rename>, <class 'sqlglot.expressions.Min'>: <function _rename>, <class 'sqlglot.expressions.Month'>: <function _rename>, <class 'sqlglot.expressions.MonthsBetween'>: <function _rename>, <class 'sqlglot.expressions.NextValueFor'>: <function _rename>, <class 'sqlglot.expressions.NthValue'>: <function _rename>, <class 'sqlglot.expressions.Nullif'>: <function _rename>, <class 'sqlglot.expressions.NumberToStr'>: <function _rename>, <class 'sqlglot.expressions.Nvl2'>: <function _rename>, <class 'sqlglot.expressions.OpenJSON'>: <function _rename>, <class 'sqlglot.expressions.ParameterizedAgg'>: <function _rename>, <class 'sqlglot.expressions.ParseJSON'>: <function _rename>, <class 'sqlglot.expressions.PercentileCont'>: <function _rename>, <class 'sqlglot.expressions.PercentileDisc'>: <function _rename>, <class 'sqlglot.expressions.Posexplode'>: <function _rename>, <class 'sqlglot.expressions.PosexplodeOuter'>: <function _rename>, <class 'sqlglot.expressions.Predict'>: <function _rename>, <class 'sqlglot.expressions.Quantile'>: <function _rename>, <class 'sqlglot.expressions.Quarter'>: <function _rename>, <class 'sqlglot.expressions.Rand'>: <function _rename>, <class 'sqlglot.expressions.Randn'>: <function _rename>, <class 'sqlglot.expressions.RangeN'>: <function _rename>, <class 'sqlglot.expressions.ReadCSV'>: <function _rename>, <class 'sqlglot.expressions.Reduce'>: <function _rename>, <class 'sqlglot.expressions.RegexpExtract'>: <function _rename>, <class 'sqlglot.expressions.RegexpReplace'>: <function _rename>, <class 'sqlglot.expressions.RegexpSplit'>: <function _rename>, <class 'sqlglot.expressions.Repeat'>: <function _rename>, <class 'sqlglot.expressions.Right'>: <function _rename>, <class 'sqlglot.expressions.Round'>: <function _rename>, <class 'sqlglot.expressions.RowNumber'>: <function _rename>, <class 'sqlglot.expressions.SHA'>: <function _rename>, <class 'sqlglot.expressions.SHA2'>: <function _rename>, <class 'sqlglot.expressions.SafeDivide'>: <function _rename>, <class 'sqlglot.expressions.Sign'>: <function _rename>, <class 'sqlglot.expressions.SortArray'>: <function _rename>, <class 'sqlglot.expressions.Split'>: <function _rename>, <class 'sqlglot.expressions.Sqrt'>: <function _rename>, <class 'sqlglot.expressions.StandardHash'>: <function _rename>, <class 'sqlglot.expressions.StarMap'>: <function _rename>, <class 'sqlglot.expressions.StartsWith'>: <function _rename>, <class 'sqlglot.expressions.Stddev'>: <function _rename>, <class 'sqlglot.expressions.StddevPop'>: <function _rename>, <class 'sqlglot.expressions.StddevSamp'>: <function _rename>, <class 'sqlglot.expressions.StrPosition'>: <function _rename>, <class 'sqlglot.expressions.StrToDate'>: <function _rename>, <class 'sqlglot.expressions.StrToMap'>: <function _rename>, <class 'sqlglot.expressions.StrToTime'>: <function _rename>, <class 'sqlglot.expressions.StrToUnix'>: <function _rename>, <class 'sqlglot.expressions.Struct'>: <function _rename>, <class 'sqlglot.expressions.StructExtract'>: <function _rename>, <class 'sqlglot.expressions.Stuff'>: <function _rename>, <class 'sqlglot.expressions.Substring'>: <function _rename>, <class 'sqlglot.expressions.Sum'>: <function _rename>, <class 'sqlglot.expressions.TimeAdd'>: <function _rename>, <class 'sqlglot.expressions.TimeDiff'>: <function _rename>, <class 'sqlglot.expressions.TimeFromParts'>: <function _rename>, <class 'sqlglot.expressions.TimeStrToDate'>: <function _rename>, <class 'sqlglot.expressions.TimeStrToTime'>: <function _rename>, <class 'sqlglot.expressions.TimeStrToUnix'>: <function _rename>, <class 'sqlglot.expressions.TimeSub'>: <function _rename>, <class 'sqlglot.expressions.TimeToStr'>: <function _rename>, <class 'sqlglot.expressions.TimeToTimeStr'>: <function _rename>, <class 'sqlglot.expressions.TimeToUnix'>: <function _rename>, <class 'sqlglot.expressions.TimeTrunc'>: <function _rename>, <class 'sqlglot.expressions.Timestamp'>: <function _rename>, <class 'sqlglot.expressions.TimestampAdd'>: <function _rename>, <class 'sqlglot.expressions.TimestampDiff'>: <function _rename>, <class 'sqlglot.expressions.TimestampFromParts'>: <function _rename>, <class 'sqlglot.expressions.TimestampSub'>: <function _rename>, <class 'sqlglot.expressions.TimestampTrunc'>: <function _rename>, <class 'sqlglot.expressions.ToArray'>: <function _rename>, <class 'sqlglot.expressions.ToBase64'>: <function _rename>, <class 'sqlglot.expressions.ToChar'>: <function _rename>, <class 'sqlglot.expressions.ToDays'>: <function _rename>, <class 'sqlglot.expressions.ToMap'>: <function _rename>, <class 'sqlglot.expressions.ToNumber'>: <function _rename>, <class 'sqlglot.expressions.Transform'>: <function _rename>, <class 'sqlglot.expressions.Trim'>: <function _rename>, <class 'sqlglot.expressions.Try'>: <function _rename>, <class 'sqlglot.expressions.TryCast'>: <function _rename>, <class 'sqlglot.expressions.TsOrDiToDi'>: <function _rename>, <class 'sqlglot.expressions.TsOrDsAdd'>: <function _rename>, <class 'sqlglot.expressions.TsOrDsDiff'>: <function _rename>, <class 'sqlglot.expressions.TsOrDsToDate'>: <function _rename>, <class 'sqlglot.expressions.TsOrDsToDateStr'>: <function _rename>, <class 'sqlglot.expressions.TsOrDsToTime'>: <function _rename>, <class 'sqlglot.expressions.TsOrDsToTimestamp'>: <function _rename>, <class 'sqlglot.expressions.Unhex'>: <function _rename>, <class 'sqlglot.expressions.UnixDate'>: <function _rename>, <class 'sqlglot.expressions.UnixToStr'>: <function _rename>, <class 'sqlglot.expressions.UnixToTime'>: <function _rename>, <class 'sqlglot.expressions.UnixToTimeStr'>: <function _rename>, <class 'sqlglot.expressions.Upper'>: <function _rename>, <class 'sqlglot.expressions.VarMap'>: <function _rename>, <class 'sqlglot.expressions.Variance'>: <function _rename>, <class 'sqlglot.expressions.VariancePop'>: <function _rename>, <class 'sqlglot.expressions.Week'>: <function _rename>, <class 'sqlglot.expressions.WeekOfYear'>: <function _rename>, <class 'sqlglot.expressions.When'>: <function _rename>, <class 'sqlglot.expressions.XMLTable'>: <function _rename>, <class 'sqlglot.expressions.Year'>: <function _rename>, <class 'sqlglot.expressions.Alias'>: <function Python.Generator.<lambda>>, <class 'sqlglot.expressions.Between'>: <function _rename>, <class 'sqlglot.expressions.Boolean'>: <function Python.Generator.<lambda>>, <class 'sqlglot.expressions.Column'>: <function Python.Generator.<lambda>>, <class 'sqlglot.expressions.Distinct'>: <function Python.Generator.<lambda>>, <class 'sqlglot.expressions.In'>: <function Python.Generator.<lambda>>, <class 'sqlglot.expressions.Interval'>: <function Python.Generator.<lambda>>, <class 'sqlglot.expressions.JSONPath'>: <function Python.Generator.<lambda>>, <class 'sqlglot.expressions.JSONPathKey'>: <function Python.Generator.<lambda>>, <class 'sqlglot.expressions.JSONPathSubscript'>: <function Python.Generator.<lambda>>, <class 'sqlglot.expressions.Lambda'>: <function _lambda_sql>, <class 'sqlglot.expressions.Not'>: <function Python.Generator.<lambda>>, <class 'sqlglot.expressions.Null'>: <function Python.Generator.<lambda>>, <class 'sqlglot.expressions.Ordered'>: <function _ordered_py>, <class 'sqlglot.expressions.Star'>: <function Python.Generator.<lambda>>}"}, "sqlglot.executor.python.Python.Generator.SELECT_KINDS": {"fullname": "sqlglot.executor.python.Python.Generator.SELECT_KINDS", "modulename": "sqlglot.executor.python", "qualname": "Python.Generator.SELECT_KINDS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Tuple[str, ...]", "default_value": "()"}, "sqlglot.executor.python.Python.Generator.TRY_SUPPORTED": {"fullname": "sqlglot.executor.python.Python.Generator.TRY_SUPPORTED", "modulename": "sqlglot.executor.python", "qualname": "Python.Generator.TRY_SUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.executor.python.Python.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS": {"fullname": "sqlglot.executor.python.Python.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "modulename": "sqlglot.executor.python", "qualname": "Python.Generator.AFTER_HAVING_MODIFIER_TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'qualify': <function Generator.<lambda>>, 'windows': <function Generator.<lambda>>}"}, "sqlglot.executor.python.Python.UNESCAPED_SEQUENCES": {"fullname": "sqlglot.executor.python.Python.UNESCAPED_SEQUENCES", "modulename": "sqlglot.executor.python", "qualname": "Python.UNESCAPED_SEQUENCES", "kind": "variable", "doc": "<p>Mapping of an escaped sequence (<code>\\n</code>) to its unescaped version (<code>\n</code>).</p>\n", "annotation": ": Dict[str, str]", "default_value": "{'\\\\a': '\\x07', '\\\\b': '\\x08', '\\\\f': '\\x0c', '\\\\n': '\\n', '\\\\r': '\\r', '\\\\t': '\\t', '\\\\v': '\\x0b', '\\\\\\\\': '\\\\'}"}, "sqlglot.executor.python.Python.tokenizer_class": {"fullname": "sqlglot.executor.python.Python.tokenizer_class", "modulename": "sqlglot.executor.python", "qualname": "Python.tokenizer_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.executor.python.Python.Tokenizer'>"}, "sqlglot.executor.python.Python.parser_class": {"fullname": "sqlglot.executor.python.Python.parser_class", "modulename": "sqlglot.executor.python", "qualname": "Python.parser_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.parser.Parser'>"}, "sqlglot.executor.python.Python.generator_class": {"fullname": "sqlglot.executor.python.Python.generator_class", "modulename": "sqlglot.executor.python", "qualname": "Python.generator_class", "kind": "variable", "doc": "<p></p>\n", "default_value": "<class 'sqlglot.executor.python.Python.Generator'>"}, "sqlglot.executor.python.Python.TIME_TRIE": {"fullname": "sqlglot.executor.python.Python.TIME_TRIE", "modulename": "sqlglot.executor.python", "qualname": "Python.TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.executor.python.Python.FORMAT_TRIE": {"fullname": "sqlglot.executor.python.Python.FORMAT_TRIE", "modulename": "sqlglot.executor.python", "qualname": "Python.FORMAT_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.executor.python.Python.INVERSE_TIME_MAPPING": {"fullname": "sqlglot.executor.python.Python.INVERSE_TIME_MAPPING", "modulename": "sqlglot.executor.python", "qualname": "Python.INVERSE_TIME_MAPPING", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{}"}, "sqlglot.executor.python.Python.INVERSE_TIME_TRIE": {"fullname": "sqlglot.executor.python.Python.INVERSE_TIME_TRIE", "modulename": "sqlglot.executor.python", "qualname": "Python.INVERSE_TIME_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.executor.python.Python.ESCAPED_SEQUENCES": {"fullname": "sqlglot.executor.python.Python.ESCAPED_SEQUENCES", "modulename": "sqlglot.executor.python", "qualname": "Python.ESCAPED_SEQUENCES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{'\\x07': '\\\\a', '\\x08': '\\\\b', '\\x0c': '\\\\f', '\\n': '\\\\n', '\\r': '\\\\r', '\\t': '\\\\t', '\\x0b': '\\\\v', '\\\\': '\\\\\\\\'}"}, "sqlglot.executor.python.Python.QUOTE_START": {"fullname": "sqlglot.executor.python.Python.QUOTE_START", "modulename": "sqlglot.executor.python", "qualname": "Python.QUOTE_START", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.executor.python.Python.QUOTE_END": {"fullname": "sqlglot.executor.python.Python.QUOTE_END", "modulename": "sqlglot.executor.python", "qualname": "Python.QUOTE_END", "kind": "variable", "doc": "<p></p>\n", "default_value": ""'""}, "sqlglot.executor.python.Python.IDENTIFIER_START": {"fullname": "sqlglot.executor.python.Python.IDENTIFIER_START", "modulename": "sqlglot.executor.python", "qualname": "Python.IDENTIFIER_START", "kind": "variable", "doc": "<p></p>\n", "default_value": "'"'"}, "sqlglot.executor.python.Python.IDENTIFIER_END": {"fullname": "sqlglot.executor.python.Python.IDENTIFIER_END", "modulename": "sqlglot.executor.python", "qualname": "Python.IDENTIFIER_END", "kind": "variable", "doc": "<p></p>\n", "default_value": "'"'"}, "sqlglot.executor.python.Python.BIT_START": {"fullname": "sqlglot.executor.python.Python.BIT_START", "modulename": "sqlglot.executor.python", "qualname": "Python.BIT_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.executor.python.Python.BIT_END": {"fullname": "sqlglot.executor.python.Python.BIT_END", "modulename": "sqlglot.executor.python", "qualname": "Python.BIT_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.executor.python.Python.HEX_START": {"fullname": "sqlglot.executor.python.Python.HEX_START", "modulename": "sqlglot.executor.python", "qualname": "Python.HEX_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.executor.python.Python.HEX_END": {"fullname": "sqlglot.executor.python.Python.HEX_END", "modulename": "sqlglot.executor.python", "qualname": "Python.HEX_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.executor.python.Python.BYTE_START": {"fullname": "sqlglot.executor.python.Python.BYTE_START", "modulename": "sqlglot.executor.python", "qualname": "Python.BYTE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.executor.python.Python.BYTE_END": {"fullname": "sqlglot.executor.python.Python.BYTE_END", "modulename": "sqlglot.executor.python", "qualname": "Python.BYTE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.executor.python.Python.UNICODE_START": {"fullname": "sqlglot.executor.python.Python.UNICODE_START", "modulename": "sqlglot.executor.python", "qualname": "Python.UNICODE_START", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.executor.python.Python.UNICODE_END": {"fullname": "sqlglot.executor.python.Python.UNICODE_END", "modulename": "sqlglot.executor.python", "qualname": "Python.UNICODE_END", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.executor.table": {"fullname": "sqlglot.executor.table", "modulename": "sqlglot.executor.table", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.executor.table.Table": {"fullname": "sqlglot.executor.table.Table", "modulename": "sqlglot.executor.table", "qualname": "Table", "kind": "class", "doc": "<p></p>\n"}, "sqlglot.executor.table.Table.__init__": {"fullname": "sqlglot.executor.table.Table.__init__", "modulename": "sqlglot.executor.table", "qualname": "Table.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">columns</span>, </span><span class=\"param\"><span class=\"n\">rows</span><span class=\"o\">=</span><span class=\"kc\">None</span>, </span><span class=\"param\"><span class=\"n\">column_range</span><span class=\"o\">=</span><span class=\"kc\">None</span></span>)</span>"}, "sqlglot.executor.table.Table.columns": {"fullname": "sqlglot.executor.table.Table.columns", "modulename": "sqlglot.executor.table", "qualname": "Table.columns", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.executor.table.Table.column_range": {"fullname": "sqlglot.executor.table.Table.column_range", "modulename": "sqlglot.executor.table", "qualname": "Table.column_range", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.executor.table.Table.reader": {"fullname": "sqlglot.executor.table.Table.reader", "modulename": "sqlglot.executor.table", "qualname": "Table.reader", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.executor.table.Table.rows": {"fullname": "sqlglot.executor.table.Table.rows", "modulename": "sqlglot.executor.table", "qualname": "Table.rows", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.executor.table.Table.range_reader": {"fullname": "sqlglot.executor.table.Table.range_reader", "modulename": "sqlglot.executor.table", "qualname": "Table.range_reader", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.executor.table.Table.add_columns": {"fullname": "sqlglot.executor.table.Table.add_columns", "modulename": "sqlglot.executor.table", "qualname": "Table.add_columns", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">*</span><span class=\"n\">columns</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.executor.table.Table.append": {"fullname": "sqlglot.executor.table.Table.append", "modulename": "sqlglot.executor.table", "qualname": "Table.append", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">row</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.table.Table.pop": {"fullname": "sqlglot.executor.table.Table.pop", "modulename": "sqlglot.executor.table", "qualname": "Table.pop", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.executor.table.Table.width": {"fullname": "sqlglot.executor.table.Table.width", "modulename": "sqlglot.executor.table", "qualname": "Table.width", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.executor.table.TableIter": {"fullname": "sqlglot.executor.table.TableIter", "modulename": "sqlglot.executor.table", "qualname": "TableIter", "kind": "class", "doc": "<p></p>\n"}, "sqlglot.executor.table.TableIter.__init__": {"fullname": "sqlglot.executor.table.TableIter.__init__", "modulename": "sqlglot.executor.table", "qualname": "TableIter.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">table</span></span>)</span>"}, "sqlglot.executor.table.TableIter.table": {"fullname": "sqlglot.executor.table.TableIter.table", "modulename": "sqlglot.executor.table", "qualname": "TableIter.table", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.executor.table.TableIter.index": {"fullname": "sqlglot.executor.table.TableIter.index", "modulename": "sqlglot.executor.table", "qualname": "TableIter.index", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.executor.table.RangeReader": {"fullname": "sqlglot.executor.table.RangeReader", "modulename": "sqlglot.executor.table", "qualname": "RangeReader", "kind": "class", "doc": "<p></p>\n"}, "sqlglot.executor.table.RangeReader.__init__": {"fullname": "sqlglot.executor.table.RangeReader.__init__", "modulename": "sqlglot.executor.table", "qualname": "RangeReader.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">table</span></span>)</span>"}, "sqlglot.executor.table.RangeReader.table": {"fullname": "sqlglot.executor.table.RangeReader.table", "modulename": "sqlglot.executor.table", "qualname": "RangeReader.table", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.executor.table.RangeReader.range": {"fullname": "sqlglot.executor.table.RangeReader.range", "modulename": "sqlglot.executor.table", "qualname": "RangeReader.range", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.executor.table.RowReader": {"fullname": "sqlglot.executor.table.RowReader", "modulename": "sqlglot.executor.table", "qualname": "RowReader", "kind": "class", "doc": "<p></p>\n"}, "sqlglot.executor.table.RowReader.__init__": {"fullname": "sqlglot.executor.table.RowReader.__init__", "modulename": "sqlglot.executor.table", "qualname": "RowReader.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">columns</span>, </span><span class=\"param\"><span class=\"n\">column_range</span><span class=\"o\">=</span><span class=\"kc\">None</span></span>)</span>"}, "sqlglot.executor.table.RowReader.columns": {"fullname": "sqlglot.executor.table.RowReader.columns", "modulename": "sqlglot.executor.table", "qualname": "RowReader.columns", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.executor.table.RowReader.row": {"fullname": "sqlglot.executor.table.RowReader.row", "modulename": "sqlglot.executor.table", "qualname": "RowReader.row", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.executor.table.Tables": {"fullname": "sqlglot.executor.table.Tables", "modulename": "sqlglot.executor.table", "qualname": "Tables", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.schema.AbstractMappingSchema"}, "sqlglot.executor.table.ensure_tables": {"fullname": "sqlglot.executor.table.ensure_tables", "modulename": "sqlglot.executor.table", "qualname": "ensure_tables", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">d</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">executor</span><span class=\"o\">.</span><span class=\"n\">table</span><span class=\"o\">.</span><span class=\"n\">Tables</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions": {"fullname": "sqlglot.expressions", "modulename": "sqlglot.expressions", "kind": "module", "doc": "<h2 id=\"expressions\">Expressions</h2>\n\n<p>Every AST node in SQLGlot is represented by a subclass of <code>Expression</code>.</p>\n\n<p>This module contains the implementation of all supported <code>Expression</code> types. Additionally,\nit exposes a number of helper functions, which are mainly used to programmatically build\nSQL expressions, such as <code>sqlglot.expressions.select</code>.</p>\n\n<hr />\n"}, "sqlglot.expressions.SQLGLOT_META": {"fullname": "sqlglot.expressions.SQLGLOT_META", "modulename": "sqlglot.expressions", "qualname": "SQLGLOT_META", "kind": "variable", "doc": "<p></p>\n", "default_value": "'sqlglot.meta'"}, "sqlglot.expressions.TABLE_PARTS": {"fullname": "sqlglot.expressions.TABLE_PARTS", "modulename": "sqlglot.expressions", "qualname": "TABLE_PARTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "('this', 'db', 'catalog')"}, "sqlglot.expressions.COLUMN_PARTS": {"fullname": "sqlglot.expressions.COLUMN_PARTS", "modulename": "sqlglot.expressions", "qualname": "COLUMN_PARTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "('this', 'table', 'db', 'catalog')"}, "sqlglot.expressions.Expression": {"fullname": "sqlglot.expressions.Expression", "modulename": "sqlglot.expressions", "qualname": "Expression", "kind": "class", "doc": "<p>The base class for all expressions in a syntax tree. Each Expression encapsulates any necessary\ncontext, such as its child expressions, their names (arg keys), and whether a given child expression\nis optional or not.</p>\n\n<h6 id=\"attributes\">Attributes:</h6>\n\n<ul>\n<li><strong>key:</strong> a unique key for each class in the Expression hierarchy. This is useful for hashing\nand representing expressions as strings.</li>\n<li><strong>arg_types:</strong> determines the arguments (child nodes) supported by an expression. It maps\narg keys to booleans that indicate whether the corresponding args are optional.</li>\n<li><strong>parent:</strong> a reference to the parent expression (or None, in case of root expressions).</li>\n<li><strong>arg_key:</strong> the arg key an expression is associated with, i.e. the name its parent expression\nuses to refer to it.</li>\n<li><strong>index:</strong> the index of an expression if it is inside of a list argument in its parent.</li>\n<li><strong>comments:</strong> a list of comments that are associated with a given expression. This is used in\norder to preserve comments when transpiling SQL code.</li>\n<li><strong>type:</strong> the <code>sqlglot.expressions.DataType</code> type of an expression. This is inferred by the\noptimizer, in order to enable some transformations that require type information.</li>\n<li><strong>meta:</strong> a dictionary that can be used to store useful metadata for a given expression.</li>\n</ul>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"k\">class</span> <span class=\"nc\">Foo</span><span class=\"p\">(</span><span class=\"n\">Expression</span><span class=\"p\">):</span>\n<span class=\"gp\">... </span> <span class=\"n\">arg_types</span> <span class=\"o\">=</span> <span class=\"p\">{</span><span class=\"s2\">"this"</span><span class=\"p\">:</span> <span class=\"kc\">True</span><span class=\"p\">,</span> <span class=\"s2\">"expression"</span><span class=\"p\">:</span> <span class=\"kc\">False</span><span class=\"p\">}</span>\n</code></pre>\n </div>\n \n <p>The above definition informs us that Foo is an Expression that requires an argument called\n \"this\" and may also optionally receive an argument called \"expression\".</p>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>args:</strong> a mapping used for retrieving the arguments of an expression, given their arg keys.</li>\n</ul>\n"}, "sqlglot.expressions.Expression.__init__": {"fullname": "sqlglot.expressions.Expression.__init__", "modulename": "sqlglot.expressions", "qualname": "Expression.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"o\">**</span><span class=\"n\">args</span><span class=\"p\">:</span> <span class=\"n\">Any</span></span>)</span>"}, "sqlglot.expressions.Expression.key": {"fullname": "sqlglot.expressions.Expression.key", "modulename": "sqlglot.expressions", "qualname": "Expression.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'expression'"}, "sqlglot.expressions.Expression.arg_types": {"fullname": "sqlglot.expressions.Expression.arg_types", "modulename": "sqlglot.expressions", "qualname": "Expression.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True}"}, "sqlglot.expressions.Expression.args": {"fullname": "sqlglot.expressions.Expression.args", "modulename": "sqlglot.expressions", "qualname": "Expression.args", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, Any]"}, "sqlglot.expressions.Expression.parent": {"fullname": "sqlglot.expressions.Expression.parent", "modulename": "sqlglot.expressions", "qualname": "Expression.parent", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[sqlglot.expressions.Expression]"}, "sqlglot.expressions.Expression.arg_key": {"fullname": "sqlglot.expressions.Expression.arg_key", "modulename": "sqlglot.expressions", "qualname": "Expression.arg_key", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]"}, "sqlglot.expressions.Expression.index": {"fullname": "sqlglot.expressions.Expression.index", "modulename": "sqlglot.expressions", "qualname": "Expression.index", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[int]"}, "sqlglot.expressions.Expression.comments": {"fullname": "sqlglot.expressions.Expression.comments", "modulename": "sqlglot.expressions", "qualname": "Expression.comments", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[List[str]]"}, "sqlglot.expressions.Expression.hashable_args": {"fullname": "sqlglot.expressions.Expression.hashable_args", "modulename": "sqlglot.expressions", "qualname": "Expression.hashable_args", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Any"}, "sqlglot.expressions.Expression.this": {"fullname": "sqlglot.expressions.Expression.this", "modulename": "sqlglot.expressions", "qualname": "Expression.this", "kind": "variable", "doc": "<p>Retrieves the argument with key \"this\".</p>\n", "annotation": ": Any"}, "sqlglot.expressions.Expression.expression": {"fullname": "sqlglot.expressions.Expression.expression", "modulename": "sqlglot.expressions", "qualname": "Expression.expression", "kind": "variable", "doc": "<p>Retrieves the argument with key \"expression\".</p>\n", "annotation": ": Any"}, "sqlglot.expressions.Expression.expressions": {"fullname": "sqlglot.expressions.Expression.expressions", "modulename": "sqlglot.expressions", "qualname": "Expression.expressions", "kind": "variable", "doc": "<p>Retrieves the argument with key \"expressions\".</p>\n", "annotation": ": List[Any]"}, "sqlglot.expressions.Expression.text": {"fullname": "sqlglot.expressions.Expression.text", "modulename": "sqlglot.expressions", "qualname": "Expression.text", "kind": "function", "doc": "<p>Returns a textual representation of the argument corresponding to \"key\". This can only be used\nfor args that are strings or leaf Expression instances, such as identifiers and literals.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">key</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.is_string": {"fullname": "sqlglot.expressions.Expression.is_string", "modulename": "sqlglot.expressions", "qualname": "Expression.is_string", "kind": "variable", "doc": "<p>Checks whether a Literal expression is a string.</p>\n", "annotation": ": bool"}, "sqlglot.expressions.Expression.is_number": {"fullname": "sqlglot.expressions.Expression.is_number", "modulename": "sqlglot.expressions", "qualname": "Expression.is_number", "kind": "variable", "doc": "<p>Checks whether a Literal expression is a number.</p>\n", "annotation": ": bool"}, "sqlglot.expressions.Expression.is_negative": {"fullname": "sqlglot.expressions.Expression.is_negative", "modulename": "sqlglot.expressions", "qualname": "Expression.is_negative", "kind": "variable", "doc": "<p>Checks whether an expression is negative.</p>\n\n<p>Handles both exp.Neg and Literal numbers with \"-\" which come from optimizer.simplify.</p>\n", "annotation": ": bool"}, "sqlglot.expressions.Expression.is_int": {"fullname": "sqlglot.expressions.Expression.is_int", "modulename": "sqlglot.expressions", "qualname": "Expression.is_int", "kind": "variable", "doc": "<p>Checks whether a Literal expression is an integer.</p>\n", "annotation": ": bool"}, "sqlglot.expressions.Expression.is_star": {"fullname": "sqlglot.expressions.Expression.is_star", "modulename": "sqlglot.expressions", "qualname": "Expression.is_star", "kind": "variable", "doc": "<p>Checks whether an expression is a star.</p>\n", "annotation": ": bool"}, "sqlglot.expressions.Expression.alias": {"fullname": "sqlglot.expressions.Expression.alias", "modulename": "sqlglot.expressions", "qualname": "Expression.alias", "kind": "variable", "doc": "<p>Returns the alias of the expression, or an empty string if it's not aliased.</p>\n", "annotation": ": str"}, "sqlglot.expressions.Expression.alias_column_names": {"fullname": "sqlglot.expressions.Expression.alias_column_names", "modulename": "sqlglot.expressions", "qualname": "Expression.alias_column_names", "kind": "variable", "doc": "<p></p>\n", "annotation": ": List[str]"}, "sqlglot.expressions.Expression.name": {"fullname": "sqlglot.expressions.Expression.name", "modulename": "sqlglot.expressions", "qualname": "Expression.name", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.expressions.Expression.alias_or_name": {"fullname": "sqlglot.expressions.Expression.alias_or_name", "modulename": "sqlglot.expressions", "qualname": "Expression.alias_or_name", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.expressions.Expression.output_name": {"fullname": "sqlglot.expressions.Expression.output_name", "modulename": "sqlglot.expressions", "qualname": "Expression.output_name", "kind": "variable", "doc": "<p>Name of the output column if this expression is a selection.</p>\n\n<p>If the Expression has no output name, an empty string is returned.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">parse_one</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT a"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'a'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT b AS c"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'c'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT 1 + 2"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">''</span>\n</code></pre>\n </div>\n</blockquote>\n", "annotation": ": str"}, "sqlglot.expressions.Expression.type": {"fullname": "sqlglot.expressions.Expression.type", "modulename": "sqlglot.expressions", "qualname": "Expression.type", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[sqlglot.expressions.DataType]"}, "sqlglot.expressions.Expression.is_type": {"fullname": "sqlglot.expressions.Expression.is_type", "modulename": "sqlglot.expressions", "qualname": "Expression.is_type", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">*</span><span class=\"n\">dtypes</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">bool</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.is_leaf": {"fullname": "sqlglot.expressions.Expression.is_leaf", "modulename": "sqlglot.expressions", "qualname": "Expression.is_leaf", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">bool</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.meta": {"fullname": "sqlglot.expressions.Expression.meta", "modulename": "sqlglot.expressions", "qualname": "Expression.meta", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, Any]"}, "sqlglot.expressions.Expression.copy": {"fullname": "sqlglot.expressions.Expression.copy", "modulename": "sqlglot.expressions", "qualname": "Expression.copy", "kind": "function", "doc": "<p>Returns a deep copy of the expression.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.add_comments": {"fullname": "sqlglot.expressions.Expression.add_comments", "modulename": "sqlglot.expressions", "qualname": "Expression.add_comments", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">comments</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.pop_comments": {"fullname": "sqlglot.expressions.Expression.pop_comments", "modulename": "sqlglot.expressions", "qualname": "Expression.pop_comments", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.append": {"fullname": "sqlglot.expressions.Expression.append", "modulename": "sqlglot.expressions", "qualname": "Expression.append", "kind": "function", "doc": "<p>Appends value to arg_key if it's a list or sets it as a new list.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>arg_key (str):</strong> name of the list expression arg</li>\n<li><strong>value (Any):</strong> value to append to the list</li>\n</ul>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">arg_key</span><span class=\"p\">:</span> <span class=\"nb\">str</span>, </span><span class=\"param\"><span class=\"n\">value</span><span class=\"p\">:</span> <span class=\"n\">Any</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.set": {"fullname": "sqlglot.expressions.Expression.set", "modulename": "sqlglot.expressions", "qualname": "Expression.set", "kind": "function", "doc": "<p>Sets arg_key to value.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>arg_key:</strong> name of the expression arg.</li>\n<li><strong>value:</strong> value to set the arg to.</li>\n<li><strong>index:</strong> if the arg is a list, this specifies what position to add the value in it.</li>\n</ul>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">arg_key</span><span class=\"p\">:</span> <span class=\"nb\">str</span>, </span><span class=\"param\"><span class=\"n\">value</span><span class=\"p\">:</span> <span class=\"n\">Any</span>, </span><span class=\"param\"><span class=\"n\">index</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">int</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.depth": {"fullname": "sqlglot.expressions.Expression.depth", "modulename": "sqlglot.expressions", "qualname": "Expression.depth", "kind": "variable", "doc": "<p>Returns the depth of this tree.</p>\n", "annotation": ": int"}, "sqlglot.expressions.Expression.iter_expressions": {"fullname": "sqlglot.expressions.Expression.iter_expressions", "modulename": "sqlglot.expressions", "qualname": "Expression.iter_expressions", "kind": "function", "doc": "<p>Yields the key and expression for all arguments, exploding list args.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">reverse</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Iterator</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.find": {"fullname": "sqlglot.expressions.Expression.find", "modulename": "sqlglot.expressions", "qualname": "Expression.find", "kind": "function", "doc": "<p>Returns the first node in this tree which matches at least one of\nthe specified types.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression_types:</strong> the expression type(s) to match.</li>\n<li><strong>bfs:</strong> whether to search the AST using the BFS algorithm (DFS is used if false).</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The node which matches the criteria or None if no such node was found.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">*</span><span class=\"n\">expression_types</span><span class=\"p\">:</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">E</span><span class=\"p\">]</span>, </span><span class=\"param\"><span class=\"n\">bfs</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">E</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.find_all": {"fullname": "sqlglot.expressions.Expression.find_all", "modulename": "sqlglot.expressions", "qualname": "Expression.find_all", "kind": "function", "doc": "<p>Returns a generator object which visits all nodes in this tree and only\nyields those that match at least one of the specified expression types.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression_types:</strong> the expression type(s) to match.</li>\n<li><strong>bfs:</strong> whether to search the AST using the BFS algorithm (DFS is used if false).</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The generator object.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">*</span><span class=\"n\">expression_types</span><span class=\"p\">:</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">E</span><span class=\"p\">]</span>, </span><span class=\"param\"><span class=\"n\">bfs</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Iterator</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">E</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.find_ancestor": {"fullname": "sqlglot.expressions.Expression.find_ancestor", "modulename": "sqlglot.expressions", "qualname": "Expression.find_ancestor", "kind": "function", "doc": "<p>Returns a nearest parent matching expression_types.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression_types:</strong> the expression type(s) to match.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The parent node.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">*</span><span class=\"n\">expression_types</span><span class=\"p\">:</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">E</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">E</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.parent_select": {"fullname": "sqlglot.expressions.Expression.parent_select", "modulename": "sqlglot.expressions", "qualname": "Expression.parent_select", "kind": "variable", "doc": "<p>Returns the parent select statement.</p>\n", "annotation": ": Optional[sqlglot.expressions.Select]"}, "sqlglot.expressions.Expression.same_parent": {"fullname": "sqlglot.expressions.Expression.same_parent", "modulename": "sqlglot.expressions", "qualname": "Expression.same_parent", "kind": "variable", "doc": "<p>Returns if the parent is the same class as itself.</p>\n", "annotation": ": bool"}, "sqlglot.expressions.Expression.root": {"fullname": "sqlglot.expressions.Expression.root", "modulename": "sqlglot.expressions", "qualname": "Expression.root", "kind": "function", "doc": "<p>Returns the root expression of this tree.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.walk": {"fullname": "sqlglot.expressions.Expression.walk", "modulename": "sqlglot.expressions", "qualname": "Expression.walk", "kind": "function", "doc": "<p>Returns a generator object which visits all nodes in this tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>bfs:</strong> if set to True the BFS traversal order will be applied,\notherwise the DFS traversal will be used instead.</li>\n<li><strong>prune:</strong> callable that returns True if the generator should stop traversing\nthis branch of the tree.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>the generator object.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">bfs</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">prune</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">],</span> <span class=\"nb\">bool</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Iterator</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.dfs": {"fullname": "sqlglot.expressions.Expression.dfs", "modulename": "sqlglot.expressions", "qualname": "Expression.dfs", "kind": "function", "doc": "<p>Returns a generator object which visits all nodes in this tree in\nthe DFS (Depth-first) order.</p>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The generator object.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">prune</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">],</span> <span class=\"nb\">bool</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Iterator</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.bfs": {"fullname": "sqlglot.expressions.Expression.bfs", "modulename": "sqlglot.expressions", "qualname": "Expression.bfs", "kind": "function", "doc": "<p>Returns a generator object which visits all nodes in this tree in\nthe BFS (Breadth-first) order.</p>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The generator object.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">prune</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">],</span> <span class=\"nb\">bool</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Iterator</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.unnest": {"fullname": "sqlglot.expressions.Expression.unnest", "modulename": "sqlglot.expressions", "qualname": "Expression.unnest", "kind": "function", "doc": "<p>Returns the first non parenthesis child or self.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.unalias": {"fullname": "sqlglot.expressions.Expression.unalias", "modulename": "sqlglot.expressions", "qualname": "Expression.unalias", "kind": "function", "doc": "<p>Returns the inner expression if this is an Alias.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.unnest_operands": {"fullname": "sqlglot.expressions.Expression.unnest_operands", "modulename": "sqlglot.expressions", "qualname": "Expression.unnest_operands", "kind": "function", "doc": "<p>Returns unnested operands as a tuple.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.flatten": {"fullname": "sqlglot.expressions.Expression.flatten", "modulename": "sqlglot.expressions", "qualname": "Expression.flatten", "kind": "function", "doc": "<p>Returns a generator which yields child nodes whose parents are the same class.</p>\n\n<p>A AND B AND C -> [A, B, C]</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">unnest</span><span class=\"o\">=</span><span class=\"kc\">True</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.to_s": {"fullname": "sqlglot.expressions.Expression.to_s", "modulename": "sqlglot.expressions", "qualname": "Expression.to_s", "kind": "function", "doc": "<p>Same as __repr__, but includes additional information which can be useful\nfor debugging, like empty or missing args and the AST nodes' object IDs.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.sql": {"fullname": "sqlglot.expressions.Expression.sql", "modulename": "sqlglot.expressions", "qualname": "Expression.sql", "kind": "function", "doc": "<p>Returns SQL string representation of this tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>dialect:</strong> the dialect of the output SQL string (eg. \"spark\", \"hive\", \"presto\", \"mysql\").</li>\n<li><strong>opts:</strong> other <code>sqlglot.generator.Generator</code> options.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The SQL string.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.transform": {"fullname": "sqlglot.expressions.Expression.transform", "modulename": "sqlglot.expressions", "qualname": "Expression.transform", "kind": "function", "doc": "<p>Visits all tree nodes (excluding already transformed ones)\nand applies the given transformation function to each node.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>fun:</strong> a function which takes a node as an argument and returns a\nnew transformed node or the same node without modifications. If the function\nreturns None, then the corresponding node will be removed from the syntax tree.</li>\n<li><strong>copy:</strong> if set to True a new tree instance is constructed, otherwise the tree is\nmodified in place.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The transformed tree.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">fun</span><span class=\"p\">:</span> <span class=\"n\">Callable</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">args</span><span class=\"p\">:</span> <span class=\"n\">Any</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.replace": {"fullname": "sqlglot.expressions.Expression.replace", "modulename": "sqlglot.expressions", "qualname": "Expression.replace", "kind": "function", "doc": "<p>Swap out this expression with a new expression.</p>\n\n<p>For example::</p>\n\n<pre><code>>>> tree = Select().select(\"x\").from_(\"tbl\")\n>>> tree.find(Column).replace(column(\"y\"))\nColumn(\n this=Identifier(this=y, quoted=False))\n>>> tree.sql()\n'SELECT y FROM tbl'\n</code></pre>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> new node</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The new expression or expressions.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.pop": {"fullname": "sqlglot.expressions.Expression.pop", "modulename": "sqlglot.expressions", "qualname": "Expression.pop", "kind": "function", "doc": "<p>Remove this expression from its AST.</p>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The popped expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"o\">~</span><span class=\"n\">E</span></span><span class=\"return-annotation\">) -> <span class=\"o\">~</span><span class=\"n\">E</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.assert_is": {"fullname": "sqlglot.expressions.Expression.assert_is", "modulename": "sqlglot.expressions", "qualname": "Expression.assert_is", "kind": "function", "doc": "<p>Assert that this <code>Expression</code> is an instance of <code>type_</code>.</p>\n\n<p>If it is NOT an instance of <code>type_</code>, this raises an assertion error.\nOtherwise, this returns this expression.</p>\n\n<h6 id=\"examples\">Examples:</h6>\n\n<blockquote>\n <p>This is useful for type security in chained expressions:</p>\n \n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"gp\">>>> </span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT x from y"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">assert_is</span><span class=\"p\">(</span><span class=\"n\">Select</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"z"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT x, z FROM y'</span>\n</code></pre>\n </div>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">type_</span><span class=\"p\">:</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">E</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"o\">~</span><span class=\"n\">E</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.error_messages": {"fullname": "sqlglot.expressions.Expression.error_messages", "modulename": "sqlglot.expressions", "qualname": "Expression.error_messages", "kind": "function", "doc": "<p>Checks if this expression is valid (e.g. all mandatory args are set).</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>args:</strong> a sequence of values that were used to instantiate a Func expression. This is used\nto check that the provided arguments don't exceed the function argument limit.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>A list of error messages for all possible errors that were found.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">args</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Sequence</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.dump": {"fullname": "sqlglot.expressions.Expression.dump", "modulename": "sqlglot.expressions", "qualname": "Expression.dump", "kind": "function", "doc": "<p>Dump this Expression to a JSON-serializable dict.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.load": {"fullname": "sqlglot.expressions.Expression.load", "modulename": "sqlglot.expressions", "qualname": "Expression.load", "kind": "function", "doc": "<p>Load a dict (as returned by <code>Expression.dump</code>) into an Expression instance.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">cls</span>, </span><span class=\"param\"><span class=\"n\">obj</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.and_": {"fullname": "sqlglot.expressions.Expression.and_", "modulename": "sqlglot.expressions", "qualname": "Expression.and_", "kind": "function", "doc": "<p>AND this condition with one or multiple expressions.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">condition</span><span class=\"p\">(</span><span class=\"s2\">"x=1"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">and_</span><span class=\"p\">(</span><span class=\"s2\">"y=1"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'x = 1 AND y = 1'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>*expressions:</strong> the SQL code strings to parse.\nIf an <code>Expression</code> instance is passed, it will be used as-is.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expression.</li>\n<li><strong>copy:</strong> whether to copy the involved expressions (only applies to Expressions).</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The new And condition.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Condition</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.or_": {"fullname": "sqlglot.expressions.Expression.or_", "modulename": "sqlglot.expressions", "qualname": "Expression.or_", "kind": "function", "doc": "<p>OR this condition with one or multiple expressions.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">condition</span><span class=\"p\">(</span><span class=\"s2\">"x=1"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">or_</span><span class=\"p\">(</span><span class=\"s2\">"y=1"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'x = 1 OR y = 1'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>*expressions:</strong> the SQL code strings to parse.\nIf an <code>Expression</code> instance is passed, it will be used as-is.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expression.</li>\n<li><strong>copy:</strong> whether to copy the involved expressions (only applies to Expressions).</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The new Or condition.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Condition</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.not_": {"fullname": "sqlglot.expressions.Expression.not_", "modulename": "sqlglot.expressions", "qualname": "Expression.not_", "kind": "function", "doc": "<p>Wrap this condition with NOT.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">condition</span><span class=\"p\">(</span><span class=\"s2\">"x=1"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">not_</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'NOT x = 1'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>copy:</strong> whether to copy this object.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The new Not instance.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.as_": {"fullname": "sqlglot.expressions.Expression.as_", "modulename": "sqlglot.expressions", "qualname": "Expression.as_", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">alias</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Identifier</span>,</span><span class=\"param\">\t<span class=\"n\">quoted</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">bool</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Alias</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.isin": {"fullname": "sqlglot.expressions.Expression.isin", "modulename": "sqlglot.expressions", "qualname": "Expression.isin", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Any</span>,</span><span class=\"param\">\t<span class=\"n\">query</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">unnest</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">,</span> <span class=\"n\">Collection</span><span class=\"p\">[</span><span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">In</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.between": {"fullname": "sqlglot.expressions.Expression.between", "modulename": "sqlglot.expressions", "qualname": "Expression.between", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">low</span><span class=\"p\">:</span> <span class=\"n\">Any</span>,</span><span class=\"param\">\t<span class=\"n\">high</span><span class=\"p\">:</span> <span class=\"n\">Any</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Between</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.is_": {"fullname": "sqlglot.expressions.Expression.is_", "modulename": "sqlglot.expressions", "qualname": "Expression.is_", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">other</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Is</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.like": {"fullname": "sqlglot.expressions.Expression.like", "modulename": "sqlglot.expressions", "qualname": "Expression.like", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">other</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Like</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.ilike": {"fullname": "sqlglot.expressions.Expression.ilike", "modulename": "sqlglot.expressions", "qualname": "Expression.ilike", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">other</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ILike</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.eq": {"fullname": "sqlglot.expressions.Expression.eq", "modulename": "sqlglot.expressions", "qualname": "Expression.eq", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">other</span><span class=\"p\">:</span> <span class=\"n\">Any</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">EQ</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.neq": {"fullname": "sqlglot.expressions.Expression.neq", "modulename": "sqlglot.expressions", "qualname": "Expression.neq", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">other</span><span class=\"p\">:</span> <span class=\"n\">Any</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">NEQ</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.rlike": {"fullname": "sqlglot.expressions.Expression.rlike", "modulename": "sqlglot.expressions", "qualname": "Expression.rlike", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">other</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">RegexpLike</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.div": {"fullname": "sqlglot.expressions.Expression.div", "modulename": "sqlglot.expressions", "qualname": "Expression.div", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">other</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">typed</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span>,</span><span class=\"param\">\t<span class=\"n\">safe</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Div</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.asc": {"fullname": "sqlglot.expressions.Expression.asc", "modulename": "sqlglot.expressions", "qualname": "Expression.asc", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">nulls_first</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Ordered</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Expression.desc": {"fullname": "sqlglot.expressions.Expression.desc", "modulename": "sqlglot.expressions", "qualname": "Expression.desc", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">nulls_first</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Ordered</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.IntoType": {"fullname": "sqlglot.expressions.IntoType", "modulename": "sqlglot.expressions", "qualname": "IntoType", "kind": "variable", "doc": "<p></p>\n", "default_value": "typing.Union[str, typing.Type[sqlglot.expressions.Expression], typing.Collection[typing.Union[str, typing.Type[sqlglot.expressions.Expression]]]]"}, "sqlglot.expressions.ExpOrStr": {"fullname": "sqlglot.expressions.ExpOrStr", "modulename": "sqlglot.expressions", "qualname": "ExpOrStr", "kind": "variable", "doc": "<p></p>\n", "default_value": "typing.Union[str, sqlglot.expressions.Expression]"}, "sqlglot.expressions.Condition": {"fullname": "sqlglot.expressions.Condition", "modulename": "sqlglot.expressions", "qualname": "Condition", "kind": "class", "doc": "<p>Logical conditions like x AND y, or simply x</p>\n", "bases": "Expression"}, "sqlglot.expressions.Condition.key": {"fullname": "sqlglot.expressions.Condition.key", "modulename": "sqlglot.expressions", "qualname": "Condition.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'condition'"}, "sqlglot.expressions.Predicate": {"fullname": "sqlglot.expressions.Predicate", "modulename": "sqlglot.expressions", "qualname": "Predicate", "kind": "class", "doc": "<p>Relationships like x = y, x > 1, x >= y.</p>\n", "bases": "Condition"}, "sqlglot.expressions.Predicate.key": {"fullname": "sqlglot.expressions.Predicate.key", "modulename": "sqlglot.expressions", "qualname": "Predicate.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'predicate'"}, "sqlglot.expressions.DerivedTable": {"fullname": "sqlglot.expressions.DerivedTable", "modulename": "sqlglot.expressions", "qualname": "DerivedTable", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.DerivedTable.selects": {"fullname": "sqlglot.expressions.DerivedTable.selects", "modulename": "sqlglot.expressions", "qualname": "DerivedTable.selects", "kind": "variable", "doc": "<p></p>\n", "annotation": ": List[sqlglot.expressions.Expression]"}, "sqlglot.expressions.DerivedTable.named_selects": {"fullname": "sqlglot.expressions.DerivedTable.named_selects", "modulename": "sqlglot.expressions", "qualname": "DerivedTable.named_selects", "kind": "variable", "doc": "<p></p>\n", "annotation": ": List[str]"}, "sqlglot.expressions.DerivedTable.key": {"fullname": "sqlglot.expressions.DerivedTable.key", "modulename": "sqlglot.expressions", "qualname": "DerivedTable.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'derivedtable'"}, "sqlglot.expressions.Query": {"fullname": "sqlglot.expressions.Query", "modulename": "sqlglot.expressions", "qualname": "Query", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Query.subquery": {"fullname": "sqlglot.expressions.Query.subquery", "modulename": "sqlglot.expressions", "qualname": "Query.subquery", "kind": "function", "doc": "<p>Returns a <code>Subquery</code> that wraps around this query.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">subquery</span> <span class=\"o\">=</span> <span class=\"n\">Select</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"x"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">from_</span><span class=\"p\">(</span><span class=\"s2\">"tbl"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">subquery</span><span class=\"p\">()</span>\n<span class=\"gp\">>>> </span><span class=\"n\">Select</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"x"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">from_</span><span class=\"p\">(</span><span class=\"n\">subquery</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT x FROM (SELECT x FROM tbl)'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>alias:</strong> an optional alias for the subquery.</li>\n<li><strong>copy:</strong> if <code>False</code>, modify this expression instance in-place.</li>\n</ul>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">alias</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Subquery</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Query.limit": {"fullname": "sqlglot.expressions.Query.limit", "modulename": "sqlglot.expressions", "qualname": "Query.limit", "kind": "function", "doc": "<p>Adds a LIMIT clause to this query.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"1"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">union</span><span class=\"p\">(</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"1"</span><span class=\"p\">))</span><span class=\"o\">.</span><span class=\"n\">limit</span><span class=\"p\">(</span><span class=\"mi\">1</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT 1 UNION SELECT 1 LIMIT 1'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> the SQL code string to parse.\nThis can also be an integer.\nIf a <code>Limit</code> instance is passed, it will be used as-is.\nIf another <code>Expression</code> instance is passed, it will be wrapped in a <code>Limit</code>.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expression.</li>\n<li><strong>copy:</strong> if <code>False</code>, modify this expression instance in-place.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>A limited Select expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"o\">~</span><span class=\"n\">Q</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"nb\">int</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"o\">~</span><span class=\"n\">Q</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Query.offset": {"fullname": "sqlglot.expressions.Query.offset", "modulename": "sqlglot.expressions", "qualname": "Query.offset", "kind": "function", "doc": "<p>Set the OFFSET expression.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">Select</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">from_</span><span class=\"p\">(</span><span class=\"s2\">"tbl"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"x"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">offset</span><span class=\"p\">(</span><span class=\"mi\">10</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT x FROM tbl OFFSET 10'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> the SQL code string to parse.\nThis can also be an integer.\nIf a <code>Offset</code> instance is passed, this is used as-is.\nIf another <code>Expression</code> instance is passed, it will be wrapped in a <code>Offset</code>.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expression.</li>\n<li><strong>copy:</strong> if <code>False</code>, modify this expression instance in-place.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The modified Select expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"o\">~</span><span class=\"n\">Q</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"nb\">int</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"o\">~</span><span class=\"n\">Q</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Query.order_by": {"fullname": "sqlglot.expressions.Query.order_by", "modulename": "sqlglot.expressions", "qualname": "Query.order_by", "kind": "function", "doc": "<p>Set the ORDER BY expression.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">Select</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">from_</span><span class=\"p\">(</span><span class=\"s2\">"tbl"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"x"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">order_by</span><span class=\"p\">(</span><span class=\"s2\">"x DESC"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT x FROM tbl ORDER BY x DESC'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>*expressions:</strong> the SQL code strings to parse.\nIf a <code>Group</code> instance is passed, this is used as-is.\nIf another <code>Expression</code> instance is passed, it will be wrapped in a <code>Order</code>.</li>\n<li><strong>append:</strong> if <code>True</code>, add to any existing expressions.\nOtherwise, this flattens all the <code>Order</code> expression into a single expression.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expression.</li>\n<li><strong>copy:</strong> if <code>False</code>, modify this expression instance in-place.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The modified Select expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"o\">~</span><span class=\"n\">Q</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">append</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"o\">~</span><span class=\"n\">Q</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Query.ctes": {"fullname": "sqlglot.expressions.Query.ctes", "modulename": "sqlglot.expressions", "qualname": "Query.ctes", "kind": "variable", "doc": "<p>Returns a list of all the CTEs attached to this query.</p>\n", "annotation": ": List[sqlglot.expressions.CTE]"}, "sqlglot.expressions.Query.selects": {"fullname": "sqlglot.expressions.Query.selects", "modulename": "sqlglot.expressions", "qualname": "Query.selects", "kind": "variable", "doc": "<p>Returns the query's projections.</p>\n", "annotation": ": List[sqlglot.expressions.Expression]"}, "sqlglot.expressions.Query.named_selects": {"fullname": "sqlglot.expressions.Query.named_selects", "modulename": "sqlglot.expressions", "qualname": "Query.named_selects", "kind": "variable", "doc": "<p>Returns the output names of the query's projections.</p>\n", "annotation": ": List[str]"}, "sqlglot.expressions.Query.select": {"fullname": "sqlglot.expressions.Query.select", "modulename": "sqlglot.expressions", "qualname": "Query.select", "kind": "function", "doc": "<p>Append to or set the SELECT expressions.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">Select</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"x"</span><span class=\"p\">,</span> <span class=\"s2\">"y"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT x, y'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>*expressions:</strong> the SQL code strings to parse.\nIf an <code>Expression</code> instance is passed, it will be used as-is.</li>\n<li><strong>append:</strong> if <code>True</code>, add to any existing expressions.\nOtherwise, this resets the expressions.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expressions.</li>\n<li><strong>copy:</strong> if <code>False</code>, modify this expression instance in-place.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The modified Query expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"o\">~</span><span class=\"n\">Q</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">append</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"o\">~</span><span class=\"n\">Q</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Query.with_": {"fullname": "sqlglot.expressions.Query.with_", "modulename": "sqlglot.expressions", "qualname": "Query.with_", "kind": "function", "doc": "<p>Append to or set the common table expressions.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">Select</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">with_</span><span class=\"p\">(</span><span class=\"s2\">"tbl2"</span><span class=\"p\">,</span> <span class=\"n\">as_</span><span class=\"o\">=</span><span class=\"s2\">"SELECT * FROM tbl"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"x"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">from_</span><span class=\"p\">(</span><span class=\"s2\">"tbl2"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'WITH tbl2 AS (SELECT * FROM tbl) SELECT x FROM tbl2'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>alias:</strong> the SQL code string to parse as the table name.\nIf an <code>Expression</code> instance is passed, this is used as-is.</li>\n<li><strong>as_:</strong> the SQL code string to parse as the table expression.\nIf an <code>Expression</code> instance is passed, it will be used as-is.</li>\n<li><strong>recursive:</strong> set the RECURSIVE part of the expression. Defaults to <code>False</code>.</li>\n<li><strong>append:</strong> if <code>True</code>, add to any existing expressions.\nOtherwise, this resets the expressions.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expression.</li>\n<li><strong>copy:</strong> if <code>False</code>, modify this expression instance in-place.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The modified expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span><span class=\"p\">:</span> <span class=\"o\">~</span><span class=\"n\">Q</span>,</span><span class=\"param\">\t<span class=\"n\">alias</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">as_</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">recursive</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">bool</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">append</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"o\">~</span><span class=\"n\">Q</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Query.union": {"fullname": "sqlglot.expressions.Query.union", "modulename": "sqlglot.expressions", "qualname": "Query.union", "kind": "function", "doc": "<p>Builds a UNION expression.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"gp\">>>> </span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT * FROM foo"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">union</span><span class=\"p\">(</span><span class=\"s2\">"SELECT * FROM bla"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT * FROM foo UNION SELECT * FROM bla'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> the SQL code string.\nIf an <code>Expression</code> instance is passed, it will be used as-is.</li>\n<li><strong>distinct:</strong> set the DISTINCT flag if and only if this is true.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expression.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The new Union expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">distinct</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Union</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Query.intersect": {"fullname": "sqlglot.expressions.Query.intersect", "modulename": "sqlglot.expressions", "qualname": "Query.intersect", "kind": "function", "doc": "<p>Builds an INTERSECT expression.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"gp\">>>> </span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT * FROM foo"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">intersect</span><span class=\"p\">(</span><span class=\"s2\">"SELECT * FROM bla"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT * FROM foo INTERSECT SELECT * FROM bla'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> the SQL code string.\nIf an <code>Expression</code> instance is passed, it will be used as-is.</li>\n<li><strong>distinct:</strong> set the DISTINCT flag if and only if this is true.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expression.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The new Intersect expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">distinct</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Intersect</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Query.except_": {"fullname": "sqlglot.expressions.Query.except_", "modulename": "sqlglot.expressions", "qualname": "Query.except_", "kind": "function", "doc": "<p>Builds an EXCEPT expression.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"gp\">>>> </span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT * FROM foo"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">except_</span><span class=\"p\">(</span><span class=\"s2\">"SELECT * FROM bla"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT * FROM foo EXCEPT SELECT * FROM bla'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> the SQL code string.\nIf an <code>Expression</code> instance is passed, it will be used as-is.</li>\n<li><strong>distinct:</strong> set the DISTINCT flag if and only if this is true.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expression.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The new Except expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">distinct</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Except</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Query.key": {"fullname": "sqlglot.expressions.Query.key", "modulename": "sqlglot.expressions", "qualname": "Query.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'query'"}, "sqlglot.expressions.UDTF": {"fullname": "sqlglot.expressions.UDTF", "modulename": "sqlglot.expressions", "qualname": "UDTF", "kind": "class", "doc": "<p></p>\n", "bases": "DerivedTable"}, "sqlglot.expressions.UDTF.selects": {"fullname": "sqlglot.expressions.UDTF.selects", "modulename": "sqlglot.expressions", "qualname": "UDTF.selects", "kind": "variable", "doc": "<p></p>\n", "annotation": ": List[sqlglot.expressions.Expression]"}, "sqlglot.expressions.UDTF.key": {"fullname": "sqlglot.expressions.UDTF.key", "modulename": "sqlglot.expressions", "qualname": "UDTF.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'udtf'"}, "sqlglot.expressions.Cache": {"fullname": "sqlglot.expressions.Cache", "modulename": "sqlglot.expressions", "qualname": "Cache", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Cache.arg_types": {"fullname": "sqlglot.expressions.Cache.arg_types", "modulename": "sqlglot.expressions", "qualname": "Cache.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'lazy': False, 'options': False, 'expression': False}"}, "sqlglot.expressions.Cache.key": {"fullname": "sqlglot.expressions.Cache.key", "modulename": "sqlglot.expressions", "qualname": "Cache.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'cache'"}, "sqlglot.expressions.Uncache": {"fullname": "sqlglot.expressions.Uncache", "modulename": "sqlglot.expressions", "qualname": "Uncache", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Uncache.arg_types": {"fullname": "sqlglot.expressions.Uncache.arg_types", "modulename": "sqlglot.expressions", "qualname": "Uncache.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'exists': False}"}, "sqlglot.expressions.Uncache.key": {"fullname": "sqlglot.expressions.Uncache.key", "modulename": "sqlglot.expressions", "qualname": "Uncache.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'uncache'"}, "sqlglot.expressions.Refresh": {"fullname": "sqlglot.expressions.Refresh", "modulename": "sqlglot.expressions", "qualname": "Refresh", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Refresh.key": {"fullname": "sqlglot.expressions.Refresh.key", "modulename": "sqlglot.expressions", "qualname": "Refresh.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'refresh'"}, "sqlglot.expressions.DDL": {"fullname": "sqlglot.expressions.DDL", "modulename": "sqlglot.expressions", "qualname": "DDL", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.DDL.ctes": {"fullname": "sqlglot.expressions.DDL.ctes", "modulename": "sqlglot.expressions", "qualname": "DDL.ctes", "kind": "variable", "doc": "<p>Returns a list of all the CTEs attached to this statement.</p>\n", "annotation": ": List[sqlglot.expressions.CTE]"}, "sqlglot.expressions.DDL.selects": {"fullname": "sqlglot.expressions.DDL.selects", "modulename": "sqlglot.expressions", "qualname": "DDL.selects", "kind": "variable", "doc": "<p>If this statement contains a query (e.g. a CTAS), this returns the query's projections.</p>\n", "annotation": ": List[sqlglot.expressions.Expression]"}, "sqlglot.expressions.DDL.named_selects": {"fullname": "sqlglot.expressions.DDL.named_selects", "modulename": "sqlglot.expressions", "qualname": "DDL.named_selects", "kind": "variable", "doc": "<p>If this statement contains a query (e.g. a CTAS), this returns the output\nnames of the query's projections.</p>\n", "annotation": ": List[str]"}, "sqlglot.expressions.DDL.key": {"fullname": "sqlglot.expressions.DDL.key", "modulename": "sqlglot.expressions", "qualname": "DDL.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'ddl'"}, "sqlglot.expressions.DML": {"fullname": "sqlglot.expressions.DML", "modulename": "sqlglot.expressions", "qualname": "DML", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.DML.returning": {"fullname": "sqlglot.expressions.DML.returning", "modulename": "sqlglot.expressions", "qualname": "DML.returning", "kind": "function", "doc": "<p>Set the RETURNING expression. Not supported by all dialects.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">delete</span><span class=\"p\">(</span><span class=\"s2\">"tbl"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">returning</span><span class=\"p\">(</span><span class=\"s2\">"*"</span><span class=\"p\">,</span> <span class=\"n\">dialect</span><span class=\"o\">=</span><span class=\"s2\">"postgres"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'DELETE FROM tbl RETURNING *'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> the SQL code strings to parse.\nIf an <code>Expression</code> instance is passed, it will be used as-is.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expressions.</li>\n<li><strong>copy:</strong> if <code>False</code>, modify this expression instance in-place.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>Delete: the modified expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DML</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.DML.key": {"fullname": "sqlglot.expressions.DML.key", "modulename": "sqlglot.expressions", "qualname": "DML.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'dml'"}, "sqlglot.expressions.Create": {"fullname": "sqlglot.expressions.Create", "modulename": "sqlglot.expressions", "qualname": "Create", "kind": "class", "doc": "<p></p>\n", "bases": "DDL"}, "sqlglot.expressions.Create.arg_types": {"fullname": "sqlglot.expressions.Create.arg_types", "modulename": "sqlglot.expressions", "qualname": "Create.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'with': False, 'this': True, 'kind': True, 'expression': False, 'exists': False, 'properties': False, 'replace': False, 'unique': False, 'indexes': False, 'no_schema_binding': False, 'begin': False, 'end': False, 'clone': False}"}, "sqlglot.expressions.Create.kind": {"fullname": "sqlglot.expressions.Create.kind", "modulename": "sqlglot.expressions", "qualname": "Create.kind", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]"}, "sqlglot.expressions.Create.key": {"fullname": "sqlglot.expressions.Create.key", "modulename": "sqlglot.expressions", "qualname": "Create.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'create'"}, "sqlglot.expressions.SequenceProperties": {"fullname": "sqlglot.expressions.SequenceProperties", "modulename": "sqlglot.expressions", "qualname": "SequenceProperties", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.SequenceProperties.arg_types": {"fullname": "sqlglot.expressions.SequenceProperties.arg_types", "modulename": "sqlglot.expressions", "qualname": "SequenceProperties.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'increment': False, 'minvalue': False, 'maxvalue': False, 'cache': False, 'start': False, 'owned': False, 'options': False}"}, "sqlglot.expressions.SequenceProperties.key": {"fullname": "sqlglot.expressions.SequenceProperties.key", "modulename": "sqlglot.expressions", "qualname": "SequenceProperties.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'sequenceproperties'"}, "sqlglot.expressions.TruncateTable": {"fullname": "sqlglot.expressions.TruncateTable", "modulename": "sqlglot.expressions", "qualname": "TruncateTable", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.TruncateTable.arg_types": {"fullname": "sqlglot.expressions.TruncateTable.arg_types", "modulename": "sqlglot.expressions", "qualname": "TruncateTable.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'expressions': True, 'is_database': False, 'exists': False, 'only': False, 'cluster': False, 'identity': False, 'option': False, 'partition': False}"}, "sqlglot.expressions.TruncateTable.key": {"fullname": "sqlglot.expressions.TruncateTable.key", "modulename": "sqlglot.expressions", "qualname": "TruncateTable.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'truncatetable'"}, "sqlglot.expressions.Clone": {"fullname": "sqlglot.expressions.Clone", "modulename": "sqlglot.expressions", "qualname": "Clone", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Clone.arg_types": {"fullname": "sqlglot.expressions.Clone.arg_types", "modulename": "sqlglot.expressions", "qualname": "Clone.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'shallow': False, 'copy': False}"}, "sqlglot.expressions.Clone.key": {"fullname": "sqlglot.expressions.Clone.key", "modulename": "sqlglot.expressions", "qualname": "Clone.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'clone'"}, "sqlglot.expressions.Describe": {"fullname": "sqlglot.expressions.Describe", "modulename": "sqlglot.expressions", "qualname": "Describe", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Describe.arg_types": {"fullname": "sqlglot.expressions.Describe.arg_types", "modulename": "sqlglot.expressions", "qualname": "Describe.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'style': False, 'kind': False, 'expressions': False}"}, "sqlglot.expressions.Describe.key": {"fullname": "sqlglot.expressions.Describe.key", "modulename": "sqlglot.expressions", "qualname": "Describe.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'describe'"}, "sqlglot.expressions.Kill": {"fullname": "sqlglot.expressions.Kill", "modulename": "sqlglot.expressions", "qualname": "Kill", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Kill.arg_types": {"fullname": "sqlglot.expressions.Kill.arg_types", "modulename": "sqlglot.expressions", "qualname": "Kill.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'kind': False}"}, "sqlglot.expressions.Kill.key": {"fullname": "sqlglot.expressions.Kill.key", "modulename": "sqlglot.expressions", "qualname": "Kill.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'kill'"}, "sqlglot.expressions.Pragma": {"fullname": "sqlglot.expressions.Pragma", "modulename": "sqlglot.expressions", "qualname": "Pragma", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Pragma.key": {"fullname": "sqlglot.expressions.Pragma.key", "modulename": "sqlglot.expressions", "qualname": "Pragma.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'pragma'"}, "sqlglot.expressions.Declare": {"fullname": "sqlglot.expressions.Declare", "modulename": "sqlglot.expressions", "qualname": "Declare", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Declare.arg_types": {"fullname": "sqlglot.expressions.Declare.arg_types", "modulename": "sqlglot.expressions", "qualname": "Declare.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'expressions': True}"}, "sqlglot.expressions.Declare.key": {"fullname": "sqlglot.expressions.Declare.key", "modulename": "sqlglot.expressions", "qualname": "Declare.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'declare'"}, "sqlglot.expressions.DeclareItem": {"fullname": "sqlglot.expressions.DeclareItem", "modulename": "sqlglot.expressions", "qualname": "DeclareItem", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.DeclareItem.arg_types": {"fullname": "sqlglot.expressions.DeclareItem.arg_types", "modulename": "sqlglot.expressions", "qualname": "DeclareItem.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'kind': True, 'default': False}"}, "sqlglot.expressions.DeclareItem.key": {"fullname": "sqlglot.expressions.DeclareItem.key", "modulename": "sqlglot.expressions", "qualname": "DeclareItem.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'declareitem'"}, "sqlglot.expressions.Set": {"fullname": "sqlglot.expressions.Set", "modulename": "sqlglot.expressions", "qualname": "Set", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Set.arg_types": {"fullname": "sqlglot.expressions.Set.arg_types", "modulename": "sqlglot.expressions", "qualname": "Set.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'expressions': False, 'unset': False, 'tag': False}"}, "sqlglot.expressions.Set.key": {"fullname": "sqlglot.expressions.Set.key", "modulename": "sqlglot.expressions", "qualname": "Set.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'set'"}, "sqlglot.expressions.Heredoc": {"fullname": "sqlglot.expressions.Heredoc", "modulename": "sqlglot.expressions", "qualname": "Heredoc", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Heredoc.arg_types": {"fullname": "sqlglot.expressions.Heredoc.arg_types", "modulename": "sqlglot.expressions", "qualname": "Heredoc.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'tag': False}"}, "sqlglot.expressions.Heredoc.key": {"fullname": "sqlglot.expressions.Heredoc.key", "modulename": "sqlglot.expressions", "qualname": "Heredoc.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'heredoc'"}, "sqlglot.expressions.SetItem": {"fullname": "sqlglot.expressions.SetItem", "modulename": "sqlglot.expressions", "qualname": "SetItem", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.SetItem.arg_types": {"fullname": "sqlglot.expressions.SetItem.arg_types", "modulename": "sqlglot.expressions", "qualname": "SetItem.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False, 'expressions': False, 'kind': False, 'collate': False, 'global': False}"}, "sqlglot.expressions.SetItem.key": {"fullname": "sqlglot.expressions.SetItem.key", "modulename": "sqlglot.expressions", "qualname": "SetItem.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'setitem'"}, "sqlglot.expressions.Show": {"fullname": "sqlglot.expressions.Show", "modulename": "sqlglot.expressions", "qualname": "Show", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Show.arg_types": {"fullname": "sqlglot.expressions.Show.arg_types", "modulename": "sqlglot.expressions", "qualname": "Show.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'history': False, 'terse': False, 'target': False, 'offset': False, 'starts_with': False, 'limit': False, 'from': False, 'like': False, 'where': False, 'db': False, 'scope': False, 'scope_kind': False, 'full': False, 'mutex': False, 'query': False, 'channel': False, 'global': False, 'log': False, 'position': False, 'types': False}"}, "sqlglot.expressions.Show.key": {"fullname": "sqlglot.expressions.Show.key", "modulename": "sqlglot.expressions", "qualname": "Show.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'show'"}, "sqlglot.expressions.UserDefinedFunction": {"fullname": "sqlglot.expressions.UserDefinedFunction", "modulename": "sqlglot.expressions", "qualname": "UserDefinedFunction", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.UserDefinedFunction.arg_types": {"fullname": "sqlglot.expressions.UserDefinedFunction.arg_types", "modulename": "sqlglot.expressions", "qualname": "UserDefinedFunction.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expressions': False, 'wrapped': False}"}, "sqlglot.expressions.UserDefinedFunction.key": {"fullname": "sqlglot.expressions.UserDefinedFunction.key", "modulename": "sqlglot.expressions", "qualname": "UserDefinedFunction.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'userdefinedfunction'"}, "sqlglot.expressions.CharacterSet": {"fullname": "sqlglot.expressions.CharacterSet", "modulename": "sqlglot.expressions", "qualname": "CharacterSet", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.CharacterSet.arg_types": {"fullname": "sqlglot.expressions.CharacterSet.arg_types", "modulename": "sqlglot.expressions", "qualname": "CharacterSet.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'default': False}"}, "sqlglot.expressions.CharacterSet.key": {"fullname": "sqlglot.expressions.CharacterSet.key", "modulename": "sqlglot.expressions", "qualname": "CharacterSet.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'characterset'"}, "sqlglot.expressions.With": {"fullname": "sqlglot.expressions.With", "modulename": "sqlglot.expressions", "qualname": "With", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.With.arg_types": {"fullname": "sqlglot.expressions.With.arg_types", "modulename": "sqlglot.expressions", "qualname": "With.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'expressions': True, 'recursive': False}"}, "sqlglot.expressions.With.recursive": {"fullname": "sqlglot.expressions.With.recursive", "modulename": "sqlglot.expressions", "qualname": "With.recursive", "kind": "variable", "doc": "<p></p>\n", "annotation": ": bool"}, "sqlglot.expressions.With.key": {"fullname": "sqlglot.expressions.With.key", "modulename": "sqlglot.expressions", "qualname": "With.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'with'"}, "sqlglot.expressions.WithinGroup": {"fullname": "sqlglot.expressions.WithinGroup", "modulename": "sqlglot.expressions", "qualname": "WithinGroup", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.WithinGroup.arg_types": {"fullname": "sqlglot.expressions.WithinGroup.arg_types", "modulename": "sqlglot.expressions", "qualname": "WithinGroup.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': False}"}, "sqlglot.expressions.WithinGroup.key": {"fullname": "sqlglot.expressions.WithinGroup.key", "modulename": "sqlglot.expressions", "qualname": "WithinGroup.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'withingroup'"}, "sqlglot.expressions.CTE": {"fullname": "sqlglot.expressions.CTE", "modulename": "sqlglot.expressions", "qualname": "CTE", "kind": "class", "doc": "<p></p>\n", "bases": "DerivedTable"}, "sqlglot.expressions.CTE.arg_types": {"fullname": "sqlglot.expressions.CTE.arg_types", "modulename": "sqlglot.expressions", "qualname": "CTE.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'alias': True, 'scalar': False, 'materialized': False}"}, "sqlglot.expressions.CTE.key": {"fullname": "sqlglot.expressions.CTE.key", "modulename": "sqlglot.expressions", "qualname": "CTE.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'cte'"}, "sqlglot.expressions.ProjectionDef": {"fullname": "sqlglot.expressions.ProjectionDef", "modulename": "sqlglot.expressions", "qualname": "ProjectionDef", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.ProjectionDef.arg_types": {"fullname": "sqlglot.expressions.ProjectionDef.arg_types", "modulename": "sqlglot.expressions", "qualname": "ProjectionDef.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': True}"}, "sqlglot.expressions.ProjectionDef.key": {"fullname": "sqlglot.expressions.ProjectionDef.key", "modulename": "sqlglot.expressions", "qualname": "ProjectionDef.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'projectiondef'"}, "sqlglot.expressions.TableAlias": {"fullname": "sqlglot.expressions.TableAlias", "modulename": "sqlglot.expressions", "qualname": "TableAlias", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.TableAlias.arg_types": {"fullname": "sqlglot.expressions.TableAlias.arg_types", "modulename": "sqlglot.expressions", "qualname": "TableAlias.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False, 'columns': False}"}, "sqlglot.expressions.TableAlias.columns": {"fullname": "sqlglot.expressions.TableAlias.columns", "modulename": "sqlglot.expressions", "qualname": "TableAlias.columns", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.expressions.TableAlias.key": {"fullname": "sqlglot.expressions.TableAlias.key", "modulename": "sqlglot.expressions", "qualname": "TableAlias.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'tablealias'"}, "sqlglot.expressions.BitString": {"fullname": "sqlglot.expressions.BitString", "modulename": "sqlglot.expressions", "qualname": "BitString", "kind": "class", "doc": "<p></p>\n", "bases": "Condition"}, "sqlglot.expressions.BitString.key": {"fullname": "sqlglot.expressions.BitString.key", "modulename": "sqlglot.expressions", "qualname": "BitString.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'bitstring'"}, "sqlglot.expressions.HexString": {"fullname": "sqlglot.expressions.HexString", "modulename": "sqlglot.expressions", "qualname": "HexString", "kind": "class", "doc": "<p></p>\n", "bases": "Condition"}, "sqlglot.expressions.HexString.key": {"fullname": "sqlglot.expressions.HexString.key", "modulename": "sqlglot.expressions", "qualname": "HexString.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'hexstring'"}, "sqlglot.expressions.ByteString": {"fullname": "sqlglot.expressions.ByteString", "modulename": "sqlglot.expressions", "qualname": "ByteString", "kind": "class", "doc": "<p></p>\n", "bases": "Condition"}, "sqlglot.expressions.ByteString.key": {"fullname": "sqlglot.expressions.ByteString.key", "modulename": "sqlglot.expressions", "qualname": "ByteString.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'bytestring'"}, "sqlglot.expressions.RawString": {"fullname": "sqlglot.expressions.RawString", "modulename": "sqlglot.expressions", "qualname": "RawString", "kind": "class", "doc": "<p></p>\n", "bases": "Condition"}, "sqlglot.expressions.RawString.key": {"fullname": "sqlglot.expressions.RawString.key", "modulename": "sqlglot.expressions", "qualname": "RawString.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'rawstring'"}, "sqlglot.expressions.UnicodeString": {"fullname": "sqlglot.expressions.UnicodeString", "modulename": "sqlglot.expressions", "qualname": "UnicodeString", "kind": "class", "doc": "<p></p>\n", "bases": "Condition"}, "sqlglot.expressions.UnicodeString.arg_types": {"fullname": "sqlglot.expressions.UnicodeString.arg_types", "modulename": "sqlglot.expressions", "qualname": "UnicodeString.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'escape': False}"}, "sqlglot.expressions.UnicodeString.key": {"fullname": "sqlglot.expressions.UnicodeString.key", "modulename": "sqlglot.expressions", "qualname": "UnicodeString.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'unicodestring'"}, "sqlglot.expressions.Column": {"fullname": "sqlglot.expressions.Column", "modulename": "sqlglot.expressions", "qualname": "Column", "kind": "class", "doc": "<p></p>\n", "bases": "Condition"}, "sqlglot.expressions.Column.arg_types": {"fullname": "sqlglot.expressions.Column.arg_types", "modulename": "sqlglot.expressions", "qualname": "Column.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'table': False, 'db': False, 'catalog': False, 'join_mark': False}"}, "sqlglot.expressions.Column.table": {"fullname": "sqlglot.expressions.Column.table", "modulename": "sqlglot.expressions", "qualname": "Column.table", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.expressions.Column.db": {"fullname": "sqlglot.expressions.Column.db", "modulename": "sqlglot.expressions", "qualname": "Column.db", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.expressions.Column.catalog": {"fullname": "sqlglot.expressions.Column.catalog", "modulename": "sqlglot.expressions", "qualname": "Column.catalog", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.expressions.Column.output_name": {"fullname": "sqlglot.expressions.Column.output_name", "modulename": "sqlglot.expressions", "qualname": "Column.output_name", "kind": "variable", "doc": "<p>Name of the output column if this expression is a selection.</p>\n\n<p>If the Expression has no output name, an empty string is returned.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">parse_one</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT a"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'a'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT b AS c"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'c'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT 1 + 2"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">''</span>\n</code></pre>\n </div>\n</blockquote>\n", "annotation": ": str"}, "sqlglot.expressions.Column.parts": {"fullname": "sqlglot.expressions.Column.parts", "modulename": "sqlglot.expressions", "qualname": "Column.parts", "kind": "variable", "doc": "<p>Return the parts of a column in order catalog, db, table, name.</p>\n", "annotation": ": List[sqlglot.expressions.Identifier]"}, "sqlglot.expressions.Column.to_dot": {"fullname": "sqlglot.expressions.Column.to_dot", "modulename": "sqlglot.expressions", "qualname": "Column.to_dot", "kind": "function", "doc": "<p>Converts the column into a dot expression.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Dot</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Identifier</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Column.key": {"fullname": "sqlglot.expressions.Column.key", "modulename": "sqlglot.expressions", "qualname": "Column.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'column'"}, "sqlglot.expressions.ColumnPosition": {"fullname": "sqlglot.expressions.ColumnPosition", "modulename": "sqlglot.expressions", "qualname": "ColumnPosition", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.ColumnPosition.arg_types": {"fullname": "sqlglot.expressions.ColumnPosition.arg_types", "modulename": "sqlglot.expressions", "qualname": "ColumnPosition.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False, 'position': True}"}, "sqlglot.expressions.ColumnPosition.key": {"fullname": "sqlglot.expressions.ColumnPosition.key", "modulename": "sqlglot.expressions", "qualname": "ColumnPosition.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'columnposition'"}, "sqlglot.expressions.ColumnDef": {"fullname": "sqlglot.expressions.ColumnDef", "modulename": "sqlglot.expressions", "qualname": "ColumnDef", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.ColumnDef.arg_types": {"fullname": "sqlglot.expressions.ColumnDef.arg_types", "modulename": "sqlglot.expressions", "qualname": "ColumnDef.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'kind': False, 'constraints': False, 'exists': False, 'position': False}"}, "sqlglot.expressions.ColumnDef.constraints": {"fullname": "sqlglot.expressions.ColumnDef.constraints", "modulename": "sqlglot.expressions", "qualname": "ColumnDef.constraints", "kind": "variable", "doc": "<p></p>\n", "annotation": ": List[sqlglot.expressions.ColumnConstraint]"}, "sqlglot.expressions.ColumnDef.kind": {"fullname": "sqlglot.expressions.ColumnDef.kind", "modulename": "sqlglot.expressions", "qualname": "ColumnDef.kind", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[sqlglot.expressions.DataType]"}, "sqlglot.expressions.ColumnDef.key": {"fullname": "sqlglot.expressions.ColumnDef.key", "modulename": "sqlglot.expressions", "qualname": "ColumnDef.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'columndef'"}, "sqlglot.expressions.AlterColumn": {"fullname": "sqlglot.expressions.AlterColumn", "modulename": "sqlglot.expressions", "qualname": "AlterColumn", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.AlterColumn.arg_types": {"fullname": "sqlglot.expressions.AlterColumn.arg_types", "modulename": "sqlglot.expressions", "qualname": "AlterColumn.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'dtype': False, 'collate': False, 'using': False, 'default': False, 'drop': False, 'comment': False}"}, "sqlglot.expressions.AlterColumn.key": {"fullname": "sqlglot.expressions.AlterColumn.key", "modulename": "sqlglot.expressions", "qualname": "AlterColumn.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'altercolumn'"}, "sqlglot.expressions.AlterDistStyle": {"fullname": "sqlglot.expressions.AlterDistStyle", "modulename": "sqlglot.expressions", "qualname": "AlterDistStyle", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.AlterDistStyle.key": {"fullname": "sqlglot.expressions.AlterDistStyle.key", "modulename": "sqlglot.expressions", "qualname": "AlterDistStyle.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'alterdiststyle'"}, "sqlglot.expressions.AlterSortKey": {"fullname": "sqlglot.expressions.AlterSortKey", "modulename": "sqlglot.expressions", "qualname": "AlterSortKey", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.AlterSortKey.arg_types": {"fullname": 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{"fullname": "sqlglot.expressions.NotNullColumnConstraint", "modulename": "sqlglot.expressions", "qualname": "NotNullColumnConstraint", "kind": "class", "doc": "<p></p>\n", "bases": "ColumnConstraintKind"}, "sqlglot.expressions.NotNullColumnConstraint.arg_types": {"fullname": "sqlglot.expressions.NotNullColumnConstraint.arg_types", "modulename": "sqlglot.expressions", "qualname": "NotNullColumnConstraint.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'allow_null': False}"}, "sqlglot.expressions.NotNullColumnConstraint.key": {"fullname": "sqlglot.expressions.NotNullColumnConstraint.key", "modulename": "sqlglot.expressions", "qualname": "NotNullColumnConstraint.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'notnullcolumnconstraint'"}, "sqlglot.expressions.OnUpdateColumnConstraint": {"fullname": "sqlglot.expressions.OnUpdateColumnConstraint", "modulename": "sqlglot.expressions", "qualname": "OnUpdateColumnConstraint", "kind": "class", "doc": "<p></p>\n", "bases": "ColumnConstraintKind"}, "sqlglot.expressions.OnUpdateColumnConstraint.key": {"fullname": "sqlglot.expressions.OnUpdateColumnConstraint.key", "modulename": "sqlglot.expressions", "qualname": "OnUpdateColumnConstraint.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'onupdatecolumnconstraint'"}, "sqlglot.expressions.TransformColumnConstraint": {"fullname": "sqlglot.expressions.TransformColumnConstraint", "modulename": "sqlglot.expressions", "qualname": "TransformColumnConstraint", "kind": "class", "doc": "<p></p>\n", "bases": "ColumnConstraintKind"}, "sqlglot.expressions.TransformColumnConstraint.key": {"fullname": "sqlglot.expressions.TransformColumnConstraint.key", "modulename": "sqlglot.expressions", "qualname": "TransformColumnConstraint.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'transformcolumnconstraint'"}, "sqlglot.expressions.PrimaryKeyColumnConstraint": {"fullname": "sqlglot.expressions.PrimaryKeyColumnConstraint", "modulename": "sqlglot.expressions", "qualname": "PrimaryKeyColumnConstraint", "kind": "class", "doc": "<p></p>\n", "bases": "ColumnConstraintKind"}, "sqlglot.expressions.PrimaryKeyColumnConstraint.arg_types": {"fullname": "sqlglot.expressions.PrimaryKeyColumnConstraint.arg_types", "modulename": "sqlglot.expressions", "qualname": "PrimaryKeyColumnConstraint.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'desc': False}"}, "sqlglot.expressions.PrimaryKeyColumnConstraint.key": {"fullname": "sqlglot.expressions.PrimaryKeyColumnConstraint.key", "modulename": "sqlglot.expressions", "qualname": "PrimaryKeyColumnConstraint.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'primarykeycolumnconstraint'"}, "sqlglot.expressions.TitleColumnConstraint": {"fullname": "sqlglot.expressions.TitleColumnConstraint", "modulename": "sqlglot.expressions", "qualname": "TitleColumnConstraint", "kind": "class", "doc": "<p></p>\n", "bases": "ColumnConstraintKind"}, "sqlglot.expressions.TitleColumnConstraint.key": {"fullname": "sqlglot.expressions.TitleColumnConstraint.key", "modulename": "sqlglot.expressions", "qualname": "TitleColumnConstraint.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'titlecolumnconstraint'"}, "sqlglot.expressions.UniqueColumnConstraint": {"fullname": "sqlglot.expressions.UniqueColumnConstraint", "modulename": "sqlglot.expressions", "qualname": "UniqueColumnConstraint", "kind": "class", "doc": "<p></p>\n", "bases": "ColumnConstraintKind"}, "sqlglot.expressions.UniqueColumnConstraint.arg_types": {"fullname": "sqlglot.expressions.UniqueColumnConstraint.arg_types", "modulename": "sqlglot.expressions", "qualname": "UniqueColumnConstraint.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False, 'index_type': False, 'on_conflict': False}"}, "sqlglot.expressions.UniqueColumnConstraint.key": {"fullname": "sqlglot.expressions.UniqueColumnConstraint.key", "modulename": "sqlglot.expressions", "qualname": "UniqueColumnConstraint.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'uniquecolumnconstraint'"}, "sqlglot.expressions.UppercaseColumnConstraint": {"fullname": "sqlglot.expressions.UppercaseColumnConstraint", "modulename": "sqlglot.expressions", "qualname": "UppercaseColumnConstraint", "kind": "class", "doc": "<p></p>\n", "bases": "ColumnConstraintKind"}, "sqlglot.expressions.UppercaseColumnConstraint.arg_types": {"fullname": "sqlglot.expressions.UppercaseColumnConstraint.arg_types", "modulename": "sqlglot.expressions", "qualname": "UppercaseColumnConstraint.arg_types", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, Any]", "default_value": "{}"}, "sqlglot.expressions.UppercaseColumnConstraint.key": {"fullname": "sqlglot.expressions.UppercaseColumnConstraint.key", "modulename": "sqlglot.expressions", "qualname": "UppercaseColumnConstraint.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'uppercasecolumnconstraint'"}, "sqlglot.expressions.PathColumnConstraint": {"fullname": "sqlglot.expressions.PathColumnConstraint", "modulename": "sqlglot.expressions", "qualname": "PathColumnConstraint", "kind": "class", "doc": "<p></p>\n", "bases": "ColumnConstraintKind"}, "sqlglot.expressions.PathColumnConstraint.key": {"fullname": "sqlglot.expressions.PathColumnConstraint.key", "modulename": "sqlglot.expressions", "qualname": "PathColumnConstraint.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'pathcolumnconstraint'"}, "sqlglot.expressions.ComputedColumnConstraint": {"fullname": "sqlglot.expressions.ComputedColumnConstraint", "modulename": "sqlglot.expressions", "qualname": "ComputedColumnConstraint", "kind": "class", "doc": "<p></p>\n", "bases": "ColumnConstraintKind"}, "sqlglot.expressions.ComputedColumnConstraint.arg_types": {"fullname": "sqlglot.expressions.ComputedColumnConstraint.arg_types", "modulename": "sqlglot.expressions", "qualname": "ComputedColumnConstraint.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'persisted': False, 'not_null': False}"}, "sqlglot.expressions.ComputedColumnConstraint.key": {"fullname": "sqlglot.expressions.ComputedColumnConstraint.key", "modulename": "sqlglot.expressions", "qualname": "ComputedColumnConstraint.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'computedcolumnconstraint'"}, "sqlglot.expressions.Constraint": {"fullname": "sqlglot.expressions.Constraint", "modulename": "sqlglot.expressions", "qualname": "Constraint", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Constraint.arg_types": {"fullname": "sqlglot.expressions.Constraint.arg_types", "modulename": "sqlglot.expressions", "qualname": "Constraint.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expressions': True}"}, "sqlglot.expressions.Constraint.key": {"fullname": "sqlglot.expressions.Constraint.key", "modulename": "sqlglot.expressions", "qualname": "Constraint.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'constraint'"}, "sqlglot.expressions.Delete": {"fullname": "sqlglot.expressions.Delete", "modulename": "sqlglot.expressions", "qualname": "Delete", "kind": "class", "doc": "<p></p>\n", "bases": "DML"}, "sqlglot.expressions.Delete.arg_types": {"fullname": "sqlglot.expressions.Delete.arg_types", "modulename": "sqlglot.expressions", "qualname": "Delete.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'with': False, 'this': False, 'using': False, 'where': False, 'returning': False, 'limit': False, 'tables': False}"}, "sqlglot.expressions.Delete.delete": {"fullname": "sqlglot.expressions.Delete.delete", "modulename": "sqlglot.expressions", "qualname": "Delete.delete", "kind": "function", "doc": "<p>Create a DELETE expression or replace the table on an existing DELETE expression.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">delete</span><span class=\"p\">(</span><span class=\"s2\">"tbl"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'DELETE FROM tbl'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>table:</strong> the table from which to delete.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expression.</li>\n<li><strong>copy:</strong> if <code>False</code>, modify this expression instance in-place.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>Delete: the modified expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">table</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Delete</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Delete.where": {"fullname": "sqlglot.expressions.Delete.where", "modulename": "sqlglot.expressions", "qualname": "Delete.where", "kind": "function", "doc": "<p>Append to or set the WHERE expressions.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">delete</span><span class=\"p\">(</span><span class=\"s2\">"tbl"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">where</span><span class=\"p\">(</span><span class=\"s2\">"x = 'a' OR x < 'b'"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">"DELETE FROM tbl WHERE x = 'a' OR x < 'b'"</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>*expressions:</strong> the SQL code strings to parse.\nIf an <code>Expression</code> instance is passed, it will be used as-is.\nMultiple expressions are combined with an AND operator.</li>\n<li><strong>append:</strong> if <code>True</code>, AND the new expressions to any existing expression.\nOtherwise, this resets the expression.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expressions.</li>\n<li><strong>copy:</strong> if <code>False</code>, modify this expression instance in-place.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>Delete: the modified expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">append</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Delete</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Delete.key": {"fullname": "sqlglot.expressions.Delete.key", "modulename": "sqlglot.expressions", "qualname": "Delete.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'delete'"}, "sqlglot.expressions.Drop": {"fullname": "sqlglot.expressions.Drop", "modulename": "sqlglot.expressions", "qualname": "Drop", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Drop.arg_types": {"fullname": "sqlglot.expressions.Drop.arg_types", "modulename": "sqlglot.expressions", "qualname": "Drop.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False, 'kind': False, 'expressions': False, 'exists': False, 'temporary': False, 'materialized': False, 'cascade': False, 'constraints': False, 'purge': False, 'cluster': False}"}, "sqlglot.expressions.Drop.key": {"fullname": "sqlglot.expressions.Drop.key", "modulename": "sqlglot.expressions", "qualname": "Drop.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'drop'"}, "sqlglot.expressions.Filter": {"fullname": "sqlglot.expressions.Filter", "modulename": "sqlglot.expressions", "qualname": "Filter", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Filter.arg_types": {"fullname": "sqlglot.expressions.Filter.arg_types", "modulename": "sqlglot.expressions", "qualname": "Filter.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': True}"}, "sqlglot.expressions.Filter.key": {"fullname": "sqlglot.expressions.Filter.key", "modulename": "sqlglot.expressions", "qualname": "Filter.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'filter'"}, "sqlglot.expressions.Check": {"fullname": "sqlglot.expressions.Check", "modulename": "sqlglot.expressions", "qualname": "Check", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Check.key": {"fullname": "sqlglot.expressions.Check.key", "modulename": "sqlglot.expressions", "qualname": "Check.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'check'"}, "sqlglot.expressions.Connect": {"fullname": "sqlglot.expressions.Connect", "modulename": "sqlglot.expressions", "qualname": "Connect", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Connect.arg_types": {"fullname": "sqlglot.expressions.Connect.arg_types", "modulename": "sqlglot.expressions", "qualname": "Connect.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'start': False, 'connect': True, 'nocycle': False}"}, "sqlglot.expressions.Connect.key": {"fullname": "sqlglot.expressions.Connect.key", "modulename": "sqlglot.expressions", "qualname": "Connect.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'connect'"}, "sqlglot.expressions.CopyParameter": {"fullname": "sqlglot.expressions.CopyParameter", "modulename": "sqlglot.expressions", "qualname": "CopyParameter", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.CopyParameter.arg_types": {"fullname": "sqlglot.expressions.CopyParameter.arg_types", "modulename": "sqlglot.expressions", "qualname": "CopyParameter.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': False}"}, "sqlglot.expressions.CopyParameter.key": {"fullname": "sqlglot.expressions.CopyParameter.key", "modulename": "sqlglot.expressions", "qualname": "CopyParameter.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'copyparameter'"}, "sqlglot.expressions.Copy": {"fullname": "sqlglot.expressions.Copy", "modulename": "sqlglot.expressions", "qualname": "Copy", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Copy.arg_types": {"fullname": "sqlglot.expressions.Copy.arg_types", "modulename": "sqlglot.expressions", "qualname": "Copy.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'kind': True, 'files': True, 'credentials': False, 'format': False, 'params': False}"}, "sqlglot.expressions.Copy.key": {"fullname": "sqlglot.expressions.Copy.key", "modulename": "sqlglot.expressions", "qualname": "Copy.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'copy'"}, "sqlglot.expressions.Credentials": {"fullname": "sqlglot.expressions.Credentials", "modulename": "sqlglot.expressions", "qualname": "Credentials", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Credentials.arg_types": {"fullname": "sqlglot.expressions.Credentials.arg_types", "modulename": "sqlglot.expressions", "qualname": "Credentials.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'credentials': False, 'encryption': False, 'storage': False, 'iam_role': False, 'region': False}"}, "sqlglot.expressions.Credentials.key": {"fullname": "sqlglot.expressions.Credentials.key", "modulename": "sqlglot.expressions", "qualname": "Credentials.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'credentials'"}, "sqlglot.expressions.Prior": {"fullname": "sqlglot.expressions.Prior", "modulename": "sqlglot.expressions", "qualname": "Prior", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Prior.key": {"fullname": "sqlglot.expressions.Prior.key", "modulename": "sqlglot.expressions", "qualname": "Prior.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'prior'"}, "sqlglot.expressions.Directory": {"fullname": "sqlglot.expressions.Directory", "modulename": "sqlglot.expressions", "qualname": "Directory", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Directory.arg_types": {"fullname": "sqlglot.expressions.Directory.arg_types", "modulename": "sqlglot.expressions", "qualname": "Directory.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'local': False, 'row_format': False}"}, "sqlglot.expressions.Directory.key": {"fullname": "sqlglot.expressions.Directory.key", "modulename": "sqlglot.expressions", "qualname": "Directory.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'directory'"}, "sqlglot.expressions.ForeignKey": {"fullname": "sqlglot.expressions.ForeignKey", "modulename": "sqlglot.expressions", "qualname": "ForeignKey", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.ForeignKey.arg_types": {"fullname": "sqlglot.expressions.ForeignKey.arg_types", "modulename": "sqlglot.expressions", "qualname": "ForeignKey.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'expressions': True, 'reference': False, 'delete': False, 'update': False}"}, "sqlglot.expressions.ForeignKey.key": {"fullname": "sqlglot.expressions.ForeignKey.key", "modulename": "sqlglot.expressions", "qualname": "ForeignKey.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'foreignkey'"}, "sqlglot.expressions.ColumnPrefix": {"fullname": "sqlglot.expressions.ColumnPrefix", "modulename": "sqlglot.expressions", "qualname": "ColumnPrefix", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.ColumnPrefix.arg_types": {"fullname": "sqlglot.expressions.ColumnPrefix.arg_types", "modulename": "sqlglot.expressions", "qualname": "ColumnPrefix.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': True}"}, "sqlglot.expressions.ColumnPrefix.key": {"fullname": "sqlglot.expressions.ColumnPrefix.key", "modulename": "sqlglot.expressions", "qualname": "ColumnPrefix.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'columnprefix'"}, "sqlglot.expressions.PrimaryKey": {"fullname": "sqlglot.expressions.PrimaryKey", "modulename": "sqlglot.expressions", "qualname": "PrimaryKey", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.PrimaryKey.arg_types": {"fullname": "sqlglot.expressions.PrimaryKey.arg_types", "modulename": "sqlglot.expressions", "qualname": "PrimaryKey.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'expressions': True, 'options': False}"}, "sqlglot.expressions.PrimaryKey.key": {"fullname": "sqlglot.expressions.PrimaryKey.key", "modulename": "sqlglot.expressions", "qualname": "PrimaryKey.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'primarykey'"}, "sqlglot.expressions.Into": {"fullname": "sqlglot.expressions.Into", "modulename": "sqlglot.expressions", "qualname": "Into", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Into.arg_types": {"fullname": "sqlglot.expressions.Into.arg_types", "modulename": "sqlglot.expressions", "qualname": "Into.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'temporary': False, 'unlogged': False}"}, "sqlglot.expressions.Into.key": {"fullname": "sqlglot.expressions.Into.key", "modulename": "sqlglot.expressions", "qualname": "Into.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'into'"}, "sqlglot.expressions.From": {"fullname": "sqlglot.expressions.From", "modulename": "sqlglot.expressions", "qualname": "From", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.From.name": {"fullname": "sqlglot.expressions.From.name", "modulename": "sqlglot.expressions", "qualname": "From.name", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.expressions.From.alias_or_name": {"fullname": "sqlglot.expressions.From.alias_or_name", "modulename": "sqlglot.expressions", "qualname": "From.alias_or_name", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.expressions.From.key": {"fullname": "sqlglot.expressions.From.key", "modulename": "sqlglot.expressions", "qualname": "From.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'from'"}, "sqlglot.expressions.Having": {"fullname": "sqlglot.expressions.Having", "modulename": "sqlglot.expressions", "qualname": "Having", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Having.key": {"fullname": "sqlglot.expressions.Having.key", "modulename": "sqlglot.expressions", "qualname": "Having.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'having'"}, "sqlglot.expressions.Hint": {"fullname": "sqlglot.expressions.Hint", "modulename": "sqlglot.expressions", "qualname": "Hint", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Hint.arg_types": {"fullname": "sqlglot.expressions.Hint.arg_types", "modulename": "sqlglot.expressions", "qualname": "Hint.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'expressions': True}"}, "sqlglot.expressions.Hint.key": {"fullname": "sqlglot.expressions.Hint.key", "modulename": "sqlglot.expressions", "qualname": "Hint.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'hint'"}, "sqlglot.expressions.JoinHint": {"fullname": "sqlglot.expressions.JoinHint", "modulename": "sqlglot.expressions", "qualname": "JoinHint", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.JoinHint.arg_types": {"fullname": "sqlglot.expressions.JoinHint.arg_types", "modulename": "sqlglot.expressions", "qualname": "JoinHint.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expressions': True}"}, "sqlglot.expressions.JoinHint.key": {"fullname": "sqlglot.expressions.JoinHint.key", "modulename": "sqlglot.expressions", "qualname": "JoinHint.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'joinhint'"}, "sqlglot.expressions.Identifier": {"fullname": "sqlglot.expressions.Identifier", "modulename": "sqlglot.expressions", "qualname": "Identifier", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Identifier.arg_types": {"fullname": "sqlglot.expressions.Identifier.arg_types", "modulename": "sqlglot.expressions", "qualname": "Identifier.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'quoted': False, 'global': False, 'temporary': False}"}, "sqlglot.expressions.Identifier.quoted": {"fullname": "sqlglot.expressions.Identifier.quoted", "modulename": "sqlglot.expressions", "qualname": "Identifier.quoted", "kind": "variable", "doc": "<p></p>\n", "annotation": ": bool"}, "sqlglot.expressions.Identifier.hashable_args": {"fullname": "sqlglot.expressions.Identifier.hashable_args", "modulename": "sqlglot.expressions", "qualname": "Identifier.hashable_args", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Any"}, "sqlglot.expressions.Identifier.output_name": {"fullname": "sqlglot.expressions.Identifier.output_name", "modulename": "sqlglot.expressions", "qualname": "Identifier.output_name", "kind": "variable", "doc": "<p>Name of the output column if this expression is a selection.</p>\n\n<p>If the Expression has no output name, an empty string is returned.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">parse_one</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT a"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'a'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT b AS c"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'c'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT 1 + 2"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">''</span>\n</code></pre>\n </div>\n</blockquote>\n", "annotation": ": str"}, "sqlglot.expressions.Identifier.key": {"fullname": "sqlglot.expressions.Identifier.key", "modulename": "sqlglot.expressions", "qualname": "Identifier.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'identifier'"}, "sqlglot.expressions.Opclass": {"fullname": "sqlglot.expressions.Opclass", "modulename": "sqlglot.expressions", "qualname": "Opclass", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Opclass.arg_types": {"fullname": "sqlglot.expressions.Opclass.arg_types", "modulename": "sqlglot.expressions", "qualname": "Opclass.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': True}"}, "sqlglot.expressions.Opclass.key": {"fullname": "sqlglot.expressions.Opclass.key", "modulename": "sqlglot.expressions", "qualname": "Opclass.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'opclass'"}, "sqlglot.expressions.Index": {"fullname": "sqlglot.expressions.Index", "modulename": "sqlglot.expressions", "qualname": "Index", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Index.arg_types": {"fullname": "sqlglot.expressions.Index.arg_types", "modulename": "sqlglot.expressions", "qualname": "Index.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False, 'table': False, 'unique': False, 'primary': False, 'amp': False, 'params': False}"}, "sqlglot.expressions.Index.key": {"fullname": "sqlglot.expressions.Index.key", "modulename": "sqlglot.expressions", "qualname": "Index.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'index'"}, "sqlglot.expressions.IndexParameters": {"fullname": "sqlglot.expressions.IndexParameters", "modulename": "sqlglot.expressions", "qualname": "IndexParameters", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.IndexParameters.arg_types": {"fullname": "sqlglot.expressions.IndexParameters.arg_types", "modulename": "sqlglot.expressions", "qualname": "IndexParameters.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'using': False, 'include': False, 'columns': False, 'with_storage': False, 'partition_by': False, 'tablespace': False, 'where': False}"}, "sqlglot.expressions.IndexParameters.key": {"fullname": "sqlglot.expressions.IndexParameters.key", "modulename": "sqlglot.expressions", "qualname": "IndexParameters.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'indexparameters'"}, "sqlglot.expressions.Insert": {"fullname": "sqlglot.expressions.Insert", "modulename": "sqlglot.expressions", "qualname": "Insert", "kind": "class", "doc": "<p></p>\n", "bases": "DDL, DML"}, "sqlglot.expressions.Insert.arg_types": {"fullname": "sqlglot.expressions.Insert.arg_types", "modulename": "sqlglot.expressions", "qualname": "Insert.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'hint': False, 'with': False, 'is_function': False, 'this': False, 'expression': False, 'conflict': False, 'returning': False, 'overwrite': False, 'exists': False, 'alternative': False, 'where': False, 'ignore': False, 'by_name': False, 'stored': False}"}, "sqlglot.expressions.Insert.with_": {"fullname": "sqlglot.expressions.Insert.with_", "modulename": "sqlglot.expressions", "qualname": "Insert.with_", "kind": "function", "doc": "<p>Append to or set the common table expressions.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">insert</span><span class=\"p\">(</span><span class=\"s2\">"SELECT x FROM cte"</span><span class=\"p\">,</span> <span class=\"s2\">"t"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">with_</span><span class=\"p\">(</span><span class=\"s2\">"cte"</span><span class=\"p\">,</span> <span class=\"n\">as_</span><span class=\"o\">=</span><span class=\"s2\">"SELECT * FROM tbl"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'WITH cte AS (SELECT * FROM tbl) INSERT INTO t SELECT x FROM cte'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>alias:</strong> the SQL code string to parse as the table name.\nIf an <code>Expression</code> instance is passed, this is used as-is.</li>\n<li><strong>as_:</strong> the SQL code string to parse as the table expression.\nIf an <code>Expression</code> instance is passed, it will be used as-is.</li>\n<li><strong>recursive:</strong> set the RECURSIVE part of the expression. Defaults to <code>False</code>.</li>\n<li><strong>append:</strong> if <code>True</code>, add to any existing expressions.\nOtherwise, this resets the expressions.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expression.</li>\n<li><strong>copy:</strong> if <code>False</code>, modify this expression instance in-place.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The modified expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">alias</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">as_</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">recursive</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">bool</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">append</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Insert</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Insert.key": {"fullname": "sqlglot.expressions.Insert.key", "modulename": "sqlglot.expressions", "qualname": "Insert.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'insert'"}, "sqlglot.expressions.OnConflict": {"fullname": "sqlglot.expressions.OnConflict", "modulename": "sqlglot.expressions", "qualname": "OnConflict", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.OnConflict.arg_types": {"fullname": "sqlglot.expressions.OnConflict.arg_types", "modulename": "sqlglot.expressions", "qualname": "OnConflict.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'duplicate': False, 'expressions': False, 'action': False, 'conflict_keys': False, 'constraint': False}"}, "sqlglot.expressions.OnConflict.key": {"fullname": "sqlglot.expressions.OnConflict.key", "modulename": "sqlglot.expressions", "qualname": "OnConflict.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'onconflict'"}, "sqlglot.expressions.Returning": {"fullname": "sqlglot.expressions.Returning", "modulename": "sqlglot.expressions", "qualname": "Returning", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Returning.arg_types": {"fullname": "sqlglot.expressions.Returning.arg_types", "modulename": "sqlglot.expressions", "qualname": "Returning.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'expressions': True, 'into': False}"}, "sqlglot.expressions.Returning.key": {"fullname": "sqlglot.expressions.Returning.key", "modulename": "sqlglot.expressions", "qualname": "Returning.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'returning'"}, "sqlglot.expressions.Introducer": {"fullname": "sqlglot.expressions.Introducer", "modulename": "sqlglot.expressions", "qualname": "Introducer", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Introducer.arg_types": {"fullname": "sqlglot.expressions.Introducer.arg_types", "modulename": "sqlglot.expressions", "qualname": "Introducer.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': True}"}, "sqlglot.expressions.Introducer.key": {"fullname": "sqlglot.expressions.Introducer.key", "modulename": "sqlglot.expressions", "qualname": "Introducer.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'introducer'"}, "sqlglot.expressions.National": {"fullname": "sqlglot.expressions.National", "modulename": "sqlglot.expressions", "qualname": "National", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.National.key": {"fullname": "sqlglot.expressions.National.key", "modulename": "sqlglot.expressions", "qualname": "National.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'national'"}, "sqlglot.expressions.LoadData": {"fullname": "sqlglot.expressions.LoadData", "modulename": "sqlglot.expressions", "qualname": "LoadData", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.LoadData.arg_types": {"fullname": "sqlglot.expressions.LoadData.arg_types", "modulename": "sqlglot.expressions", "qualname": "LoadData.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'local': False, 'overwrite': False, 'inpath': True, 'partition': False, 'input_format': False, 'serde': False}"}, "sqlglot.expressions.LoadData.key": {"fullname": "sqlglot.expressions.LoadData.key", "modulename": "sqlglot.expressions", "qualname": "LoadData.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'loaddata'"}, "sqlglot.expressions.Partition": {"fullname": "sqlglot.expressions.Partition", "modulename": "sqlglot.expressions", "qualname": "Partition", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Partition.arg_types": {"fullname": "sqlglot.expressions.Partition.arg_types", "modulename": "sqlglot.expressions", "qualname": "Partition.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'expressions': True}"}, "sqlglot.expressions.Partition.key": {"fullname": "sqlglot.expressions.Partition.key", "modulename": "sqlglot.expressions", "qualname": "Partition.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'partition'"}, "sqlglot.expressions.PartitionRange": {"fullname": "sqlglot.expressions.PartitionRange", "modulename": "sqlglot.expressions", "qualname": "PartitionRange", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.PartitionRange.arg_types": {"fullname": "sqlglot.expressions.PartitionRange.arg_types", "modulename": "sqlglot.expressions", "qualname": "PartitionRange.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': True}"}, "sqlglot.expressions.PartitionRange.key": {"fullname": "sqlglot.expressions.PartitionRange.key", "modulename": "sqlglot.expressions", "qualname": "PartitionRange.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'partitionrange'"}, "sqlglot.expressions.PartitionId": {"fullname": "sqlglot.expressions.PartitionId", "modulename": "sqlglot.expressions", "qualname": "PartitionId", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.PartitionId.key": {"fullname": "sqlglot.expressions.PartitionId.key", "modulename": "sqlglot.expressions", "qualname": "PartitionId.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'partitionid'"}, "sqlglot.expressions.Fetch": {"fullname": "sqlglot.expressions.Fetch", "modulename": "sqlglot.expressions", "qualname": "Fetch", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Fetch.arg_types": {"fullname": "sqlglot.expressions.Fetch.arg_types", "modulename": "sqlglot.expressions", "qualname": "Fetch.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'direction': False, 'count': False, 'percent': False, 'with_ties': False}"}, "sqlglot.expressions.Fetch.key": {"fullname": "sqlglot.expressions.Fetch.key", "modulename": "sqlglot.expressions", "qualname": "Fetch.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'fetch'"}, "sqlglot.expressions.Group": {"fullname": "sqlglot.expressions.Group", "modulename": "sqlglot.expressions", "qualname": "Group", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Group.arg_types": {"fullname": "sqlglot.expressions.Group.arg_types", "modulename": "sqlglot.expressions", "qualname": "Group.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'expressions': False, 'grouping_sets': False, 'cube': False, 'rollup': False, 'totals': False, 'all': False}"}, "sqlglot.expressions.Group.key": {"fullname": "sqlglot.expressions.Group.key", "modulename": "sqlglot.expressions", "qualname": "Group.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'group'"}, "sqlglot.expressions.Lambda": {"fullname": "sqlglot.expressions.Lambda", "modulename": "sqlglot.expressions", "qualname": "Lambda", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Lambda.arg_types": {"fullname": "sqlglot.expressions.Lambda.arg_types", "modulename": "sqlglot.expressions", "qualname": "Lambda.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expressions': True}"}, "sqlglot.expressions.Lambda.key": {"fullname": "sqlglot.expressions.Lambda.key", "modulename": "sqlglot.expressions", "qualname": "Lambda.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'lambda'"}, "sqlglot.expressions.Limit": {"fullname": "sqlglot.expressions.Limit", "modulename": "sqlglot.expressions", "qualname": "Limit", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Limit.arg_types": {"fullname": "sqlglot.expressions.Limit.arg_types", "modulename": "sqlglot.expressions", "qualname": "Limit.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False, 'expression': True, 'offset': False, 'expressions': False}"}, "sqlglot.expressions.Limit.key": {"fullname": "sqlglot.expressions.Limit.key", "modulename": "sqlglot.expressions", "qualname": "Limit.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'limit'"}, "sqlglot.expressions.Literal": {"fullname": "sqlglot.expressions.Literal", "modulename": "sqlglot.expressions", "qualname": "Literal", "kind": "class", "doc": "<p></p>\n", "bases": "Condition"}, "sqlglot.expressions.Literal.arg_types": {"fullname": "sqlglot.expressions.Literal.arg_types", "modulename": "sqlglot.expressions", "qualname": "Literal.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'is_string': True}"}, "sqlglot.expressions.Literal.hashable_args": {"fullname": "sqlglot.expressions.Literal.hashable_args", "modulename": "sqlglot.expressions", "qualname": "Literal.hashable_args", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Any"}, "sqlglot.expressions.Literal.number": {"fullname": "sqlglot.expressions.Literal.number", "modulename": "sqlglot.expressions", "qualname": "Literal.number", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">cls</span>, </span><span class=\"param\"><span class=\"n\">number</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Literal</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Literal.string": {"fullname": "sqlglot.expressions.Literal.string", "modulename": "sqlglot.expressions", "qualname": "Literal.string", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">cls</span>, </span><span class=\"param\"><span class=\"n\">string</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Literal</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Literal.output_name": {"fullname": "sqlglot.expressions.Literal.output_name", "modulename": "sqlglot.expressions", "qualname": "Literal.output_name", "kind": "variable", "doc": "<p>Name of the output column if this expression is a selection.</p>\n\n<p>If the Expression has no output name, an empty string is returned.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">parse_one</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT a"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'a'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT b AS c"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'c'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT 1 + 2"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">''</span>\n</code></pre>\n </div>\n</blockquote>\n", "annotation": ": str"}, "sqlglot.expressions.Literal.key": {"fullname": "sqlglot.expressions.Literal.key", "modulename": "sqlglot.expressions", "qualname": "Literal.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'literal'"}, "sqlglot.expressions.Join": {"fullname": "sqlglot.expressions.Join", "modulename": "sqlglot.expressions", "qualname": "Join", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Join.arg_types": {"fullname": "sqlglot.expressions.Join.arg_types", "modulename": "sqlglot.expressions", "qualname": "Join.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'on': False, 'side': False, 'kind': False, 'using': False, 'method': False, 'global': False, 'hint': False, 'match_condition': False}"}, "sqlglot.expressions.Join.method": {"fullname": "sqlglot.expressions.Join.method", "modulename": "sqlglot.expressions", "qualname": "Join.method", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.expressions.Join.kind": {"fullname": "sqlglot.expressions.Join.kind", "modulename": "sqlglot.expressions", "qualname": "Join.kind", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.expressions.Join.side": {"fullname": "sqlglot.expressions.Join.side", "modulename": "sqlglot.expressions", "qualname": "Join.side", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.expressions.Join.hint": {"fullname": "sqlglot.expressions.Join.hint", "modulename": "sqlglot.expressions", "qualname": "Join.hint", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.expressions.Join.alias_or_name": {"fullname": "sqlglot.expressions.Join.alias_or_name", "modulename": "sqlglot.expressions", "qualname": "Join.alias_or_name", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.expressions.Join.on": {"fullname": "sqlglot.expressions.Join.on", "modulename": "sqlglot.expressions", "qualname": "Join.on", "kind": "function", "doc": "<p>Append to or set the ON expressions.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"gp\">>>> </span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"JOIN x"</span><span class=\"p\">,</span> <span class=\"n\">into</span><span class=\"o\">=</span><span class=\"n\">Join</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">on</span><span class=\"p\">(</span><span class=\"s2\">"y = 1"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'JOIN x ON y = 1'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>*expressions:</strong> the SQL code strings to parse.\nIf an <code>Expression</code> instance is passed, it will be used as-is.\nMultiple expressions are combined with an AND operator.</li>\n<li><strong>append:</strong> if <code>True</code>, AND the new expressions to any existing expression.\nOtherwise, this resets the expression.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expressions.</li>\n<li><strong>copy:</strong> if <code>False</code>, modify this expression instance in-place.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The modified Join expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">append</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Join</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Join.using": {"fullname": "sqlglot.expressions.Join.using", "modulename": "sqlglot.expressions", "qualname": "Join.using", "kind": "function", "doc": "<p>Append to or set the USING expressions.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"gp\">>>> </span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"JOIN x"</span><span class=\"p\">,</span> <span class=\"n\">into</span><span class=\"o\">=</span><span class=\"n\">Join</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">using</span><span class=\"p\">(</span><span class=\"s2\">"foo"</span><span class=\"p\">,</span> <span class=\"s2\">"bla"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'JOIN x USING (foo, bla)'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>*expressions:</strong> the SQL code strings to parse.\nIf an <code>Expression</code> instance is passed, it will be used as-is.</li>\n<li><strong>append:</strong> if <code>True</code>, concatenate the new expressions to the existing \"using\" list.\nOtherwise, this resets the expression.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expressions.</li>\n<li><strong>copy:</strong> if <code>False</code>, modify this expression instance in-place.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The modified Join expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">append</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Join</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Join.key": {"fullname": "sqlglot.expressions.Join.key", "modulename": "sqlglot.expressions", "qualname": "Join.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'join'"}, "sqlglot.expressions.Lateral": {"fullname": "sqlglot.expressions.Lateral", "modulename": "sqlglot.expressions", "qualname": "Lateral", "kind": "class", "doc": "<p></p>\n", "bases": "UDTF"}, "sqlglot.expressions.Lateral.arg_types": {"fullname": "sqlglot.expressions.Lateral.arg_types", "modulename": "sqlglot.expressions", "qualname": "Lateral.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'view': False, 'outer': False, 'alias': False, 'cross_apply': False}"}, "sqlglot.expressions.Lateral.key": {"fullname": "sqlglot.expressions.Lateral.key", "modulename": "sqlglot.expressions", "qualname": "Lateral.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'lateral'"}, "sqlglot.expressions.MatchRecognizeMeasure": {"fullname": "sqlglot.expressions.MatchRecognizeMeasure", "modulename": "sqlglot.expressions", "qualname": "MatchRecognizeMeasure", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.MatchRecognizeMeasure.arg_types": {"fullname": "sqlglot.expressions.MatchRecognizeMeasure.arg_types", "modulename": "sqlglot.expressions", "qualname": "MatchRecognizeMeasure.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'window_frame': False}"}, "sqlglot.expressions.MatchRecognizeMeasure.key": {"fullname": "sqlglot.expressions.MatchRecognizeMeasure.key", "modulename": "sqlglot.expressions", "qualname": "MatchRecognizeMeasure.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'matchrecognizemeasure'"}, "sqlglot.expressions.MatchRecognize": {"fullname": "sqlglot.expressions.MatchRecognize", "modulename": "sqlglot.expressions", "qualname": "MatchRecognize", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.MatchRecognize.arg_types": {"fullname": "sqlglot.expressions.MatchRecognize.arg_types", "modulename": "sqlglot.expressions", "qualname": "MatchRecognize.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'partition_by': False, 'order': False, 'measures': False, 'rows': False, 'after': False, 'pattern': False, 'define': False, 'alias': False}"}, "sqlglot.expressions.MatchRecognize.key": {"fullname": "sqlglot.expressions.MatchRecognize.key", "modulename": "sqlglot.expressions", "qualname": "MatchRecognize.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'matchrecognize'"}, "sqlglot.expressions.Final": {"fullname": "sqlglot.expressions.Final", "modulename": "sqlglot.expressions", "qualname": "Final", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Final.key": {"fullname": "sqlglot.expressions.Final.key", "modulename": "sqlglot.expressions", "qualname": "Final.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'final'"}, "sqlglot.expressions.Offset": {"fullname": "sqlglot.expressions.Offset", "modulename": "sqlglot.expressions", "qualname": "Offset", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Offset.arg_types": {"fullname": "sqlglot.expressions.Offset.arg_types", "modulename": "sqlglot.expressions", "qualname": "Offset.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False, 'expression': True, 'expressions': False}"}, "sqlglot.expressions.Offset.key": {"fullname": "sqlglot.expressions.Offset.key", "modulename": "sqlglot.expressions", "qualname": "Offset.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'offset'"}, "sqlglot.expressions.Order": {"fullname": "sqlglot.expressions.Order", "modulename": "sqlglot.expressions", "qualname": "Order", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Order.arg_types": {"fullname": "sqlglot.expressions.Order.arg_types", "modulename": "sqlglot.expressions", "qualname": "Order.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False, 'expressions': True, 'interpolate': False, 'siblings': False}"}, "sqlglot.expressions.Order.key": {"fullname": "sqlglot.expressions.Order.key", "modulename": "sqlglot.expressions", "qualname": "Order.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'order'"}, "sqlglot.expressions.WithFill": {"fullname": "sqlglot.expressions.WithFill", "modulename": "sqlglot.expressions", "qualname": "WithFill", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.WithFill.arg_types": {"fullname": "sqlglot.expressions.WithFill.arg_types", "modulename": "sqlglot.expressions", "qualname": "WithFill.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'from': False, 'to': False, 'step': False}"}, "sqlglot.expressions.WithFill.key": {"fullname": "sqlglot.expressions.WithFill.key", "modulename": "sqlglot.expressions", "qualname": "WithFill.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'withfill'"}, "sqlglot.expressions.Cluster": {"fullname": "sqlglot.expressions.Cluster", "modulename": "sqlglot.expressions", "qualname": "Cluster", "kind": "class", "doc": "<p></p>\n", "bases": "Order"}, "sqlglot.expressions.Cluster.key": {"fullname": "sqlglot.expressions.Cluster.key", "modulename": "sqlglot.expressions", "qualname": "Cluster.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'cluster'"}, "sqlglot.expressions.Distribute": {"fullname": "sqlglot.expressions.Distribute", "modulename": "sqlglot.expressions", "qualname": "Distribute", "kind": "class", "doc": "<p></p>\n", "bases": "Order"}, "sqlglot.expressions.Distribute.key": {"fullname": "sqlglot.expressions.Distribute.key", "modulename": "sqlglot.expressions", "qualname": "Distribute.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'distribute'"}, "sqlglot.expressions.Sort": {"fullname": "sqlglot.expressions.Sort", "modulename": "sqlglot.expressions", "qualname": "Sort", "kind": "class", "doc": "<p></p>\n", "bases": "Order"}, "sqlglot.expressions.Sort.key": {"fullname": "sqlglot.expressions.Sort.key", "modulename": "sqlglot.expressions", "qualname": "Sort.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'sort'"}, "sqlglot.expressions.Ordered": {"fullname": "sqlglot.expressions.Ordered", "modulename": "sqlglot.expressions", "qualname": "Ordered", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Ordered.arg_types": {"fullname": "sqlglot.expressions.Ordered.arg_types", "modulename": "sqlglot.expressions", "qualname": "Ordered.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'desc': False, 'nulls_first': True, 'with_fill': False}"}, "sqlglot.expressions.Ordered.key": {"fullname": "sqlglot.expressions.Ordered.key", "modulename": "sqlglot.expressions", "qualname": "Ordered.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'ordered'"}, "sqlglot.expressions.Property": {"fullname": "sqlglot.expressions.Property", "modulename": "sqlglot.expressions", "qualname": "Property", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Property.arg_types": {"fullname": "sqlglot.expressions.Property.arg_types", "modulename": "sqlglot.expressions", "qualname": "Property.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'value': True}"}, "sqlglot.expressions.Property.key": {"fullname": "sqlglot.expressions.Property.key", "modulename": "sqlglot.expressions", "qualname": "Property.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'property'"}, 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"sqlglot.expressions.TransientProperty.key", "modulename": "sqlglot.expressions", "qualname": "TransientProperty.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'transientproperty'"}, "sqlglot.expressions.UnloggedProperty": {"fullname": "sqlglot.expressions.UnloggedProperty", "modulename": "sqlglot.expressions", "qualname": "UnloggedProperty", "kind": "class", "doc": "<p></p>\n", "bases": "Property"}, "sqlglot.expressions.UnloggedProperty.arg_types": {"fullname": "sqlglot.expressions.UnloggedProperty.arg_types", "modulename": "sqlglot.expressions", "qualname": "UnloggedProperty.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{}"}, "sqlglot.expressions.UnloggedProperty.key": {"fullname": "sqlglot.expressions.UnloggedProperty.key", "modulename": "sqlglot.expressions", "qualname": "UnloggedProperty.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'unloggedproperty'"}, "sqlglot.expressions.ViewAttributeProperty": {"fullname": "sqlglot.expressions.ViewAttributeProperty", "modulename": "sqlglot.expressions", "qualname": "ViewAttributeProperty", "kind": "class", "doc": "<p></p>\n", "bases": "Property"}, "sqlglot.expressions.ViewAttributeProperty.arg_types": {"fullname": "sqlglot.expressions.ViewAttributeProperty.arg_types", "modulename": "sqlglot.expressions", "qualname": "ViewAttributeProperty.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True}"}, "sqlglot.expressions.ViewAttributeProperty.key": {"fullname": "sqlglot.expressions.ViewAttributeProperty.key", "modulename": "sqlglot.expressions", "qualname": "ViewAttributeProperty.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'viewattributeproperty'"}, "sqlglot.expressions.VolatileProperty": {"fullname": "sqlglot.expressions.VolatileProperty", "modulename": "sqlglot.expressions", "qualname": "VolatileProperty", "kind": "class", "doc": "<p></p>\n", "bases": "Property"}, "sqlglot.expressions.VolatileProperty.arg_types": {"fullname": "sqlglot.expressions.VolatileProperty.arg_types", "modulename": "sqlglot.expressions", "qualname": "VolatileProperty.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False}"}, "sqlglot.expressions.VolatileProperty.key": {"fullname": "sqlglot.expressions.VolatileProperty.key", "modulename": "sqlglot.expressions", "qualname": "VolatileProperty.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'volatileproperty'"}, "sqlglot.expressions.WithDataProperty": {"fullname": "sqlglot.expressions.WithDataProperty", "modulename": "sqlglot.expressions", "qualname": "WithDataProperty", "kind": "class", "doc": "<p></p>\n", "bases": "Property"}, "sqlglot.expressions.WithDataProperty.arg_types": {"fullname": "sqlglot.expressions.WithDataProperty.arg_types", "modulename": "sqlglot.expressions", "qualname": "WithDataProperty.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'no': True, 'statistics': False}"}, "sqlglot.expressions.WithDataProperty.key": {"fullname": "sqlglot.expressions.WithDataProperty.key", "modulename": "sqlglot.expressions", "qualname": "WithDataProperty.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'withdataproperty'"}, "sqlglot.expressions.WithJournalTableProperty": {"fullname": "sqlglot.expressions.WithJournalTableProperty", "modulename": "sqlglot.expressions", "qualname": "WithJournalTableProperty", "kind": "class", "doc": "<p></p>\n", "bases": "Property"}, "sqlglot.expressions.WithJournalTableProperty.arg_types": {"fullname": "sqlglot.expressions.WithJournalTableProperty.arg_types", "modulename": "sqlglot.expressions", "qualname": "WithJournalTableProperty.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True}"}, "sqlglot.expressions.WithJournalTableProperty.key": {"fullname": "sqlglot.expressions.WithJournalTableProperty.key", "modulename": "sqlglot.expressions", "qualname": 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<class 'sqlglot.expressions.ClusteredByProperty'>, 'COLLATE': <class 'sqlglot.expressions.CollateProperty'>, 'COMMENT': <class 'sqlglot.expressions.SchemaCommentProperty'>, 'DEFINER': <class 'sqlglot.expressions.DefinerProperty'>, 'DISTKEY': <class 'sqlglot.expressions.DistKeyProperty'>, 'DISTSTYLE': <class 'sqlglot.expressions.DistStyleProperty'>, 'ENGINE': <class 'sqlglot.expressions.EngineProperty'>, 'EXECUTE AS': <class 'sqlglot.expressions.ExecuteAsProperty'>, 'FORMAT': <class 'sqlglot.expressions.FileFormatProperty'>, 'LANGUAGE': <class 'sqlglot.expressions.LanguageProperty'>, 'LOCATION': <class 'sqlglot.expressions.LocationProperty'>, 'LOCK': <class 'sqlglot.expressions.LockProperty'>, 'PARTITIONED_BY': <class 'sqlglot.expressions.PartitionedByProperty'>, 'RETURNS': <class 'sqlglot.expressions.ReturnsProperty'>, 'ROW_FORMAT': <class 'sqlglot.expressions.RowFormatProperty'>, 'SORTKEY': <class 'sqlglot.expressions.SortKeyProperty'>}"}, "sqlglot.expressions.Properties.PROPERTY_TO_NAME": {"fullname": "sqlglot.expressions.Properties.PROPERTY_TO_NAME", "modulename": "sqlglot.expressions", "qualname": "Properties.PROPERTY_TO_NAME", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.AlgorithmProperty'>: 'ALGORITHM', <class 'sqlglot.expressions.AutoIncrementProperty'>: 'AUTO_INCREMENT', <class 'sqlglot.expressions.CharacterSetProperty'>: 'CHARACTER SET', <class 'sqlglot.expressions.ClusteredByProperty'>: 'CLUSTERED_BY', <class 'sqlglot.expressions.CollateProperty'>: 'COLLATE', <class 'sqlglot.expressions.SchemaCommentProperty'>: 'COMMENT', <class 'sqlglot.expressions.DefinerProperty'>: 'DEFINER', <class 'sqlglot.expressions.DistKeyProperty'>: 'DISTKEY', <class 'sqlglot.expressions.DistStyleProperty'>: 'DISTSTYLE', <class 'sqlglot.expressions.EngineProperty'>: 'ENGINE', <class 'sqlglot.expressions.ExecuteAsProperty'>: 'EXECUTE AS', <class 'sqlglot.expressions.FileFormatProperty'>: 'FORMAT', <class 'sqlglot.expressions.LanguageProperty'>: 'LANGUAGE', <class 'sqlglot.expressions.LocationProperty'>: 'LOCATION', <class 'sqlglot.expressions.LockProperty'>: 'LOCK', <class 'sqlglot.expressions.PartitionedByProperty'>: 'PARTITIONED_BY', <class 'sqlglot.expressions.ReturnsProperty'>: 'RETURNS', <class 'sqlglot.expressions.RowFormatProperty'>: 'ROW_FORMAT', <class 'sqlglot.expressions.SortKeyProperty'>: 'SORTKEY'}"}, "sqlglot.expressions.Properties.Location": {"fullname": "sqlglot.expressions.Properties.Location", "modulename": "sqlglot.expressions", "qualname": "Properties.Location", "kind": "class", "doc": "<p>An enumeration.</p>\n", "bases": "sqlglot.helper.AutoName"}, "sqlglot.expressions.Properties.Location.POST_CREATE": {"fullname": "sqlglot.expressions.Properties.Location.POST_CREATE", "modulename": "sqlglot.expressions", "qualname": "Properties.Location.POST_CREATE", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Location.POST_CREATE: 'POST_CREATE'>"}, "sqlglot.expressions.Properties.Location.POST_NAME": {"fullname": "sqlglot.expressions.Properties.Location.POST_NAME", "modulename": "sqlglot.expressions", "qualname": "Properties.Location.POST_NAME", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Location.POST_NAME: 'POST_NAME'>"}, "sqlglot.expressions.Properties.Location.POST_SCHEMA": {"fullname": "sqlglot.expressions.Properties.Location.POST_SCHEMA", "modulename": "sqlglot.expressions", "qualname": "Properties.Location.POST_SCHEMA", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Location.POST_SCHEMA: 'POST_SCHEMA'>"}, "sqlglot.expressions.Properties.Location.POST_WITH": {"fullname": "sqlglot.expressions.Properties.Location.POST_WITH", "modulename": "sqlglot.expressions", "qualname": "Properties.Location.POST_WITH", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Location.POST_WITH: 'POST_WITH'>"}, "sqlglot.expressions.Properties.Location.POST_ALIAS": {"fullname": "sqlglot.expressions.Properties.Location.POST_ALIAS", "modulename": "sqlglot.expressions", "qualname": "Properties.Location.POST_ALIAS", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Location.POST_ALIAS: 'POST_ALIAS'>"}, "sqlglot.expressions.Properties.Location.POST_EXPRESSION": {"fullname": "sqlglot.expressions.Properties.Location.POST_EXPRESSION", "modulename": "sqlglot.expressions", "qualname": "Properties.Location.POST_EXPRESSION", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Location.POST_EXPRESSION: 'POST_EXPRESSION'>"}, "sqlglot.expressions.Properties.Location.POST_INDEX": {"fullname": "sqlglot.expressions.Properties.Location.POST_INDEX", "modulename": "sqlglot.expressions", "qualname": "Properties.Location.POST_INDEX", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Location.POST_INDEX: 'POST_INDEX'>"}, "sqlglot.expressions.Properties.Location.UNSUPPORTED": {"fullname": "sqlglot.expressions.Properties.Location.UNSUPPORTED", "modulename": "sqlglot.expressions", "qualname": "Properties.Location.UNSUPPORTED", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Location.UNSUPPORTED: 'UNSUPPORTED'>"}, "sqlglot.expressions.Properties.from_dict": {"fullname": "sqlglot.expressions.Properties.from_dict", "modulename": "sqlglot.expressions", "qualname": "Properties.from_dict", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">cls</span>, </span><span class=\"param\"><span class=\"n\">properties_dict</span><span class=\"p\">:</span> <span class=\"n\">Dict</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Properties</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Properties.key": {"fullname": "sqlglot.expressions.Properties.key", "modulename": "sqlglot.expressions", "qualname": "Properties.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'properties'"}, "sqlglot.expressions.Qualify": {"fullname": "sqlglot.expressions.Qualify", "modulename": "sqlglot.expressions", "qualname": "Qualify", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Qualify.key": {"fullname": "sqlglot.expressions.Qualify.key", "modulename": "sqlglot.expressions", "qualname": "Qualify.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'qualify'"}, "sqlglot.expressions.InputOutputFormat": {"fullname": "sqlglot.expressions.InputOutputFormat", "modulename": "sqlglot.expressions", "qualname": "InputOutputFormat", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.InputOutputFormat.arg_types": {"fullname": "sqlglot.expressions.InputOutputFormat.arg_types", "modulename": "sqlglot.expressions", "qualname": "InputOutputFormat.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'input_format': False, 'output_format': False}"}, "sqlglot.expressions.InputOutputFormat.key": {"fullname": "sqlglot.expressions.InputOutputFormat.key", "modulename": "sqlglot.expressions", "qualname": "InputOutputFormat.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'inputoutputformat'"}, "sqlglot.expressions.Return": {"fullname": "sqlglot.expressions.Return", "modulename": "sqlglot.expressions", "qualname": "Return", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Return.key": {"fullname": "sqlglot.expressions.Return.key", "modulename": "sqlglot.expressions", "qualname": "Return.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'return'"}, "sqlglot.expressions.Reference": {"fullname": "sqlglot.expressions.Reference", "modulename": "sqlglot.expressions", "qualname": "Reference", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Reference.arg_types": {"fullname": "sqlglot.expressions.Reference.arg_types", "modulename": "sqlglot.expressions", "qualname": "Reference.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expressions': False, 'options': False}"}, "sqlglot.expressions.Reference.key": {"fullname": "sqlglot.expressions.Reference.key", "modulename": "sqlglot.expressions", "qualname": "Reference.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'reference'"}, "sqlglot.expressions.Tuple": {"fullname": "sqlglot.expressions.Tuple", "modulename": "sqlglot.expressions", "qualname": "Tuple", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Tuple.arg_types": {"fullname": "sqlglot.expressions.Tuple.arg_types", "modulename": "sqlglot.expressions", "qualname": "Tuple.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'expressions': False}"}, "sqlglot.expressions.Tuple.isin": {"fullname": "sqlglot.expressions.Tuple.isin", "modulename": "sqlglot.expressions", "qualname": "Tuple.isin", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Any</span>,</span><span class=\"param\">\t<span class=\"n\">query</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">unnest</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">,</span> <span class=\"n\">Collection</span><span class=\"p\">[</span><span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">In</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Tuple.key": {"fullname": "sqlglot.expressions.Tuple.key", "modulename": "sqlglot.expressions", "qualname": "Tuple.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'tuple'"}, "sqlglot.expressions.QUERY_MODIFIERS": {"fullname": "sqlglot.expressions.QUERY_MODIFIERS", "modulename": "sqlglot.expressions", "qualname": "QUERY_MODIFIERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'match': False, 'laterals': False, 'joins': False, 'connect': False, 'pivots': False, 'prewhere': False, 'where': False, 'group': False, 'having': False, 'qualify': False, 'windows': False, 'distribute': False, 'sort': False, 'cluster': False, 'order': False, 'limit': False, 'offset': False, 'locks': False, 'sample': False, 'settings': False, 'format': False, 'options': False}"}, "sqlglot.expressions.QueryOption": {"fullname": "sqlglot.expressions.QueryOption", "modulename": "sqlglot.expressions", "qualname": "QueryOption", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.QueryOption.arg_types": {"fullname": "sqlglot.expressions.QueryOption.arg_types", "modulename": "sqlglot.expressions", "qualname": "QueryOption.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': False}"}, "sqlglot.expressions.QueryOption.key": {"fullname": "sqlglot.expressions.QueryOption.key", "modulename": "sqlglot.expressions", "qualname": "QueryOption.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'queryoption'"}, "sqlglot.expressions.WithTableHint": {"fullname": "sqlglot.expressions.WithTableHint", "modulename": "sqlglot.expressions", "qualname": "WithTableHint", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.WithTableHint.arg_types": {"fullname": "sqlglot.expressions.WithTableHint.arg_types", "modulename": "sqlglot.expressions", "qualname": "WithTableHint.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'expressions': True}"}, "sqlglot.expressions.WithTableHint.key": {"fullname": "sqlglot.expressions.WithTableHint.key", "modulename": "sqlglot.expressions", "qualname": "WithTableHint.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'withtablehint'"}, "sqlglot.expressions.IndexTableHint": {"fullname": "sqlglot.expressions.IndexTableHint", "modulename": "sqlglot.expressions", "qualname": "IndexTableHint", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.IndexTableHint.arg_types": {"fullname": "sqlglot.expressions.IndexTableHint.arg_types", "modulename": "sqlglot.expressions", "qualname": "IndexTableHint.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expressions': False, 'target': False}"}, "sqlglot.expressions.IndexTableHint.key": {"fullname": "sqlglot.expressions.IndexTableHint.key", "modulename": "sqlglot.expressions", "qualname": "IndexTableHint.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'indextablehint'"}, "sqlglot.expressions.HistoricalData": {"fullname": "sqlglot.expressions.HistoricalData", "modulename": "sqlglot.expressions", "qualname": "HistoricalData", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.HistoricalData.arg_types": {"fullname": "sqlglot.expressions.HistoricalData.arg_types", "modulename": "sqlglot.expressions", "qualname": "HistoricalData.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'kind': True, 'expression': True}"}, "sqlglot.expressions.HistoricalData.key": {"fullname": "sqlglot.expressions.HistoricalData.key", "modulename": "sqlglot.expressions", "qualname": "HistoricalData.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'historicaldata'"}, "sqlglot.expressions.Table": {"fullname": "sqlglot.expressions.Table", "modulename": "sqlglot.expressions", "qualname": "Table", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Table.arg_types": {"fullname": "sqlglot.expressions.Table.arg_types", "modulename": "sqlglot.expressions", "qualname": "Table.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False, 'alias': False, 'db': False, 'catalog': False, 'laterals': False, 'joins': False, 'pivots': False, 'hints': False, 'system_time': False, 'version': False, 'format': False, 'pattern': False, 'ordinality': False, 'when': False, 'only': False, 'partition': False}"}, "sqlglot.expressions.Table.name": {"fullname": "sqlglot.expressions.Table.name", "modulename": "sqlglot.expressions", "qualname": "Table.name", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.expressions.Table.db": {"fullname": "sqlglot.expressions.Table.db", "modulename": "sqlglot.expressions", "qualname": "Table.db", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.expressions.Table.catalog": {"fullname": "sqlglot.expressions.Table.catalog", "modulename": "sqlglot.expressions", "qualname": "Table.catalog", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.expressions.Table.selects": {"fullname": "sqlglot.expressions.Table.selects", "modulename": "sqlglot.expressions", "qualname": "Table.selects", "kind": "variable", "doc": "<p></p>\n", "annotation": ": List[sqlglot.expressions.Expression]"}, "sqlglot.expressions.Table.named_selects": {"fullname": "sqlglot.expressions.Table.named_selects", "modulename": "sqlglot.expressions", "qualname": "Table.named_selects", "kind": "variable", "doc": "<p></p>\n", "annotation": ": List[str]"}, "sqlglot.expressions.Table.parts": {"fullname": "sqlglot.expressions.Table.parts", "modulename": "sqlglot.expressions", "qualname": "Table.parts", "kind": "variable", "doc": "<p>Return the parts of a table in order catalog, db, table.</p>\n", "annotation": ": List[sqlglot.expressions.Expression]"}, "sqlglot.expressions.Table.to_column": {"fullname": "sqlglot.expressions.Table.to_column", "modulename": "sqlglot.expressions", "qualname": "Table.to_column", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Alias</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Column</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Dot</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Table.key": {"fullname": "sqlglot.expressions.Table.key", "modulename": "sqlglot.expressions", "qualname": "Table.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'table'"}, "sqlglot.expressions.Union": {"fullname": "sqlglot.expressions.Union", "modulename": "sqlglot.expressions", "qualname": "Union", "kind": "class", "doc": "<p></p>\n", "bases": "Query"}, "sqlglot.expressions.Union.arg_types": {"fullname": "sqlglot.expressions.Union.arg_types", "modulename": "sqlglot.expressions", "qualname": "Union.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'with': False, 'this': True, 'expression': True, 'distinct': False, 'by_name': False, 'match': False, 'laterals': False, 'joins': False, 'connect': False, 'pivots': False, 'prewhere': False, 'where': False, 'group': False, 'having': False, 'qualify': False, 'windows': False, 'distribute': False, 'sort': False, 'cluster': False, 'order': False, 'limit': False, 'offset': False, 'locks': False, 'sample': False, 'settings': False, 'format': False, 'options': False}"}, "sqlglot.expressions.Union.select": {"fullname": "sqlglot.expressions.Union.select", "modulename": "sqlglot.expressions", "qualname": "Union.select", "kind": "function", "doc": "<p>Append to or set the SELECT expressions.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">Select</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"x"</span><span class=\"p\">,</span> <span class=\"s2\">"y"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT x, y'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>*expressions:</strong> the SQL code strings to parse.\nIf an <code>Expression</code> instance is passed, it will be used as-is.</li>\n<li><strong>append:</strong> if <code>True</code>, add to any existing expressions.\nOtherwise, this resets the expressions.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expressions.</li>\n<li><strong>copy:</strong> if <code>False</code>, modify this expression instance in-place.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The modified Query expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">append</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Union</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Union.named_selects": {"fullname": "sqlglot.expressions.Union.named_selects", "modulename": "sqlglot.expressions", "qualname": "Union.named_selects", "kind": "variable", "doc": "<p>Returns the output names of the query's projections.</p>\n", "annotation": ": List[str]"}, "sqlglot.expressions.Union.is_star": {"fullname": "sqlglot.expressions.Union.is_star", "modulename": "sqlglot.expressions", "qualname": "Union.is_star", "kind": "variable", "doc": "<p>Checks whether an expression is a star.</p>\n", "annotation": ": bool"}, "sqlglot.expressions.Union.selects": {"fullname": "sqlglot.expressions.Union.selects", "modulename": "sqlglot.expressions", "qualname": "Union.selects", "kind": "variable", "doc": "<p>Returns the query's projections.</p>\n", "annotation": ": List[sqlglot.expressions.Expression]"}, "sqlglot.expressions.Union.left": {"fullname": "sqlglot.expressions.Union.left", "modulename": "sqlglot.expressions", "qualname": "Union.left", "kind": "variable", "doc": "<p></p>\n", "annotation": ": sqlglot.expressions.Expression"}, "sqlglot.expressions.Union.right": {"fullname": "sqlglot.expressions.Union.right", "modulename": "sqlglot.expressions", "qualname": "Union.right", "kind": "variable", "doc": "<p></p>\n", "annotation": ": sqlglot.expressions.Expression"}, "sqlglot.expressions.Union.key": {"fullname": "sqlglot.expressions.Union.key", "modulename": "sqlglot.expressions", "qualname": "Union.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'union'"}, "sqlglot.expressions.Except": {"fullname": "sqlglot.expressions.Except", "modulename": "sqlglot.expressions", "qualname": "Except", "kind": "class", "doc": "<p></p>\n", "bases": "Union"}, "sqlglot.expressions.Except.key": {"fullname": "sqlglot.expressions.Except.key", "modulename": "sqlglot.expressions", "qualname": "Except.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'except'"}, "sqlglot.expressions.Intersect": {"fullname": "sqlglot.expressions.Intersect", "modulename": "sqlglot.expressions", "qualname": "Intersect", "kind": "class", "doc": "<p></p>\n", "bases": "Union"}, "sqlglot.expressions.Intersect.key": {"fullname": "sqlglot.expressions.Intersect.key", "modulename": "sqlglot.expressions", "qualname": "Intersect.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'intersect'"}, "sqlglot.expressions.Unnest": {"fullname": "sqlglot.expressions.Unnest", "modulename": "sqlglot.expressions", "qualname": "Unnest", "kind": "class", "doc": "<p></p>\n", "bases": "UDTF"}, "sqlglot.expressions.Unnest.arg_types": {"fullname": "sqlglot.expressions.Unnest.arg_types", "modulename": "sqlglot.expressions", "qualname": "Unnest.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'expressions': True, 'alias': False, 'offset': False}"}, "sqlglot.expressions.Unnest.selects": {"fullname": "sqlglot.expressions.Unnest.selects", "modulename": "sqlglot.expressions", "qualname": "Unnest.selects", "kind": "variable", "doc": "<p></p>\n", "annotation": ": List[sqlglot.expressions.Expression]"}, "sqlglot.expressions.Unnest.key": {"fullname": "sqlglot.expressions.Unnest.key", "modulename": "sqlglot.expressions", "qualname": "Unnest.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'unnest'"}, "sqlglot.expressions.Update": {"fullname": "sqlglot.expressions.Update", "modulename": "sqlglot.expressions", "qualname": "Update", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Update.arg_types": {"fullname": "sqlglot.expressions.Update.arg_types", "modulename": "sqlglot.expressions", "qualname": "Update.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'with': False, 'this': False, 'expressions': True, 'from': False, 'where': False, 'returning': False, 'order': False, 'limit': False}"}, "sqlglot.expressions.Update.key": {"fullname": "sqlglot.expressions.Update.key", "modulename": "sqlglot.expressions", "qualname": "Update.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'update'"}, "sqlglot.expressions.Values": {"fullname": "sqlglot.expressions.Values", "modulename": "sqlglot.expressions", "qualname": "Values", "kind": "class", "doc": "<p></p>\n", "bases": "UDTF"}, "sqlglot.expressions.Values.arg_types": {"fullname": "sqlglot.expressions.Values.arg_types", "modulename": "sqlglot.expressions", "qualname": "Values.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'expressions': True, 'alias': False}"}, "sqlglot.expressions.Values.key": {"fullname": "sqlglot.expressions.Values.key", "modulename": "sqlglot.expressions", "qualname": "Values.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'values'"}, "sqlglot.expressions.Var": {"fullname": "sqlglot.expressions.Var", "modulename": "sqlglot.expressions", "qualname": "Var", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Var.key": {"fullname": "sqlglot.expressions.Var.key", "modulename": "sqlglot.expressions", "qualname": "Var.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'var'"}, "sqlglot.expressions.Version": {"fullname": "sqlglot.expressions.Version", "modulename": "sqlglot.expressions", "qualname": "Version", "kind": "class", "doc": "<p>Time travel, iceberg, bigquery etc\n<a href=\"https://trino.io/docs/current/connector/iceberg.html?highlight=snapshot#using-snapshots\">https://trino.io/docs/current/connector/iceberg.html?highlight=snapshot#using-snapshots</a>\n<a href=\"https://www.databricks.com/blog/2019/02/04/introducing-delta-time-travel-for-large-scale-data-lakes.html\">https://www.databricks.com/blog/2019/02/04/introducing-delta-time-travel-for-large-scale-data-lakes.html</a>\n<a href=\"https://cloud.google.com/bigquery/docs/reference/standard-sql/query-syntax#for_system_time_as_of\">https://cloud.google.com/bigquery/docs/reference/standard-sql/query-syntax#for_system_time_as_of</a>\n<a href=\"https://learn.microsoft.com/en-us/sql/relational-databases/tables/querying-data-in-a-system-versioned-temporal-table?view=sql-server-ver16\">https://learn.microsoft.com/en-us/sql/relational-databases/tables/querying-data-in-a-system-versioned-temporal-table?view=sql-server-ver16</a>\nthis is either TIMESTAMP or VERSION\nkind is (\"AS OF\", \"BETWEEN\")</p>\n", "bases": "Expression"}, "sqlglot.expressions.Version.arg_types": {"fullname": "sqlglot.expressions.Version.arg_types", "modulename": "sqlglot.expressions", "qualname": "Version.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'kind': True, 'expression': False}"}, "sqlglot.expressions.Version.key": {"fullname": "sqlglot.expressions.Version.key", "modulename": "sqlglot.expressions", "qualname": "Version.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'version'"}, "sqlglot.expressions.Schema": {"fullname": "sqlglot.expressions.Schema", "modulename": "sqlglot.expressions", "qualname": "Schema", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Schema.arg_types": {"fullname": "sqlglot.expressions.Schema.arg_types", "modulename": "sqlglot.expressions", "qualname": "Schema.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False, 'expressions': False}"}, "sqlglot.expressions.Schema.key": {"fullname": "sqlglot.expressions.Schema.key", "modulename": "sqlglot.expressions", "qualname": "Schema.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'schema'"}, "sqlglot.expressions.Lock": {"fullname": "sqlglot.expressions.Lock", "modulename": "sqlglot.expressions", "qualname": "Lock", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Lock.arg_types": {"fullname": "sqlglot.expressions.Lock.arg_types", "modulename": "sqlglot.expressions", "qualname": "Lock.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'update': True, 'expressions': False, 'wait': False}"}, "sqlglot.expressions.Lock.key": {"fullname": "sqlglot.expressions.Lock.key", "modulename": "sqlglot.expressions", "qualname": "Lock.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'lock'"}, "sqlglot.expressions.Select": {"fullname": "sqlglot.expressions.Select", "modulename": "sqlglot.expressions", "qualname": "Select", "kind": "class", "doc": "<p></p>\n", "bases": "Query"}, "sqlglot.expressions.Select.arg_types": {"fullname": "sqlglot.expressions.Select.arg_types", "modulename": "sqlglot.expressions", "qualname": "Select.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'with': False, 'kind': False, 'expressions': False, 'hint': False, 'distinct': False, 'into': False, 'from': False, 'match': False, 'laterals': False, 'joins': False, 'connect': False, 'pivots': False, 'prewhere': False, 'where': False, 'group': False, 'having': False, 'qualify': False, 'windows': False, 'distribute': False, 'sort': False, 'cluster': False, 'order': False, 'limit': False, 'offset': False, 'locks': False, 'sample': False, 'settings': False, 'format': False, 'options': False}"}, "sqlglot.expressions.Select.from_": {"fullname": "sqlglot.expressions.Select.from_", "modulename": "sqlglot.expressions", "qualname": "Select.from_", "kind": "function", "doc": "<p>Set the FROM expression.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">Select</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">from_</span><span class=\"p\">(</span><span class=\"s2\">"tbl"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"x"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT x FROM tbl'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression :</strong> the SQL code strings to parse.\nIf a <code>From</code> instance is passed, this is used as-is.\nIf another <code>Expression</code> instance is passed, it will be wrapped in a <code>From</code>.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expression.</li>\n<li><strong>copy:</strong> if <code>False</code>, modify this expression instance in-place.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The modified Select expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Select</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Select.group_by": {"fullname": "sqlglot.expressions.Select.group_by", "modulename": "sqlglot.expressions", "qualname": "Select.group_by", "kind": "function", "doc": "<p>Set the GROUP BY expression.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">Select</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">from_</span><span class=\"p\">(</span><span class=\"s2\">"tbl"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"x"</span><span class=\"p\">,</span> <span class=\"s2\">"COUNT(1)"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">group_by</span><span class=\"p\">(</span><span class=\"s2\">"x"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT x, COUNT(1) FROM tbl GROUP BY x'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>*expressions:</strong> the SQL code strings to parse.\nIf a <code>Group</code> instance is passed, this is used as-is.\nIf another <code>Expression</code> instance is passed, it will be wrapped in a <code>Group</code>.\nIf nothing is passed in then a group by is not applied to the expression</li>\n<li><strong>append:</strong> if <code>True</code>, add to any existing expressions.\nOtherwise, this flattens all the <code>Group</code> expression into a single expression.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expression.</li>\n<li><strong>copy:</strong> if <code>False</code>, modify this expression instance in-place.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The modified Select expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">append</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Select</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Select.sort_by": {"fullname": "sqlglot.expressions.Select.sort_by", "modulename": "sqlglot.expressions", "qualname": "Select.sort_by", "kind": "function", "doc": "<p>Set the SORT BY expression.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">Select</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">from_</span><span class=\"p\">(</span><span class=\"s2\">"tbl"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"x"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sort_by</span><span class=\"p\">(</span><span class=\"s2\">"x DESC"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">(</span><span class=\"n\">dialect</span><span class=\"o\">=</span><span class=\"s2\">"hive"</span><span class=\"p\">)</span>\n<span class=\"go\">'SELECT x FROM tbl SORT BY x DESC'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>*expressions:</strong> the SQL code strings to parse.\nIf a <code>Group</code> instance is passed, this is used as-is.\nIf another <code>Expression</code> instance is passed, it will be wrapped in a <code>SORT</code>.</li>\n<li><strong>append:</strong> if <code>True</code>, add to any existing expressions.\nOtherwise, this flattens all the <code>Order</code> expression into a single expression.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expression.</li>\n<li><strong>copy:</strong> if <code>False</code>, modify this expression instance in-place.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The modified Select expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">append</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Select</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Select.cluster_by": {"fullname": "sqlglot.expressions.Select.cluster_by", "modulename": "sqlglot.expressions", "qualname": "Select.cluster_by", "kind": "function", "doc": "<p>Set the CLUSTER BY expression.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">Select</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">from_</span><span class=\"p\">(</span><span class=\"s2\">"tbl"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"x"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">cluster_by</span><span class=\"p\">(</span><span class=\"s2\">"x DESC"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">(</span><span class=\"n\">dialect</span><span class=\"o\">=</span><span class=\"s2\">"hive"</span><span class=\"p\">)</span>\n<span class=\"go\">'SELECT x FROM tbl CLUSTER BY x DESC'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>*expressions:</strong> the SQL code strings to parse.\nIf a <code>Group</code> instance is passed, this is used as-is.\nIf another <code>Expression</code> instance is passed, it will be wrapped in a <code>Cluster</code>.</li>\n<li><strong>append:</strong> if <code>True</code>, add to any existing expressions.\nOtherwise, this flattens all the <code>Order</code> expression into a single expression.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expression.</li>\n<li><strong>copy:</strong> if <code>False</code>, modify this expression instance in-place.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The modified Select expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">append</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Select</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Select.select": {"fullname": "sqlglot.expressions.Select.select", "modulename": "sqlglot.expressions", "qualname": "Select.select", "kind": "function", "doc": "<p>Append to or set the SELECT expressions.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">Select</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"x"</span><span class=\"p\">,</span> <span class=\"s2\">"y"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT x, y'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>*expressions:</strong> the SQL code strings to parse.\nIf an <code>Expression</code> instance is passed, it will be used as-is.</li>\n<li><strong>append:</strong> if <code>True</code>, add to any existing expressions.\nOtherwise, this resets the expressions.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expressions.</li>\n<li><strong>copy:</strong> if <code>False</code>, modify this expression instance in-place.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The modified Query expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">append</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Select</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Select.lateral": {"fullname": "sqlglot.expressions.Select.lateral", "modulename": "sqlglot.expressions", "qualname": "Select.lateral", "kind": "function", "doc": "<p>Append to or set the LATERAL expressions.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">Select</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"x"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">lateral</span><span class=\"p\">(</span><span class=\"s2\">"OUTER explode(y) tbl2 AS z"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">from_</span><span class=\"p\">(</span><span class=\"s2\">"tbl"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT x FROM tbl LATERAL VIEW OUTER EXPLODE(y) tbl2 AS z'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>*expressions:</strong> the SQL code strings to parse.\nIf an <code>Expression</code> instance is passed, it will be used as-is.</li>\n<li><strong>append:</strong> if <code>True</code>, add to any existing expressions.\nOtherwise, this resets the expressions.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expressions.</li>\n<li><strong>copy:</strong> if <code>False</code>, modify this expression instance in-place.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The modified Select expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">append</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Select</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Select.join": {"fullname": "sqlglot.expressions.Select.join", "modulename": "sqlglot.expressions", "qualname": "Select.join", "kind": "function", "doc": "<p>Append to or set the JOIN expressions.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">Select</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"*"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">from_</span><span class=\"p\">(</span><span class=\"s2\">"tbl"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">join</span><span class=\"p\">(</span><span class=\"s2\">"tbl2"</span><span class=\"p\">,</span> <span class=\"n\">on</span><span class=\"o\">=</span><span class=\"s2\">"tbl1.y = tbl2.y"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT * FROM tbl JOIN tbl2 ON tbl1.y = tbl2.y'</span>\n</code></pre>\n </div>\n \n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">Select</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"1"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">from_</span><span class=\"p\">(</span><span class=\"s2\">"a"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">join</span><span class=\"p\">(</span><span class=\"s2\">"b"</span><span class=\"p\">,</span> <span class=\"n\">using</span><span class=\"o\">=</span><span class=\"p\">[</span><span class=\"s2\">"x"</span><span class=\"p\">,</span> <span class=\"s2\">"y"</span><span class=\"p\">,</span> <span class=\"s2\">"z"</span><span class=\"p\">])</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT 1 FROM a JOIN b USING (x, y, z)'</span>\n</code></pre>\n </div>\n \n <p>Use <code>join_type</code> to change the type of join:</p>\n \n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">Select</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"*"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">from_</span><span class=\"p\">(</span><span class=\"s2\">"tbl"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">join</span><span class=\"p\">(</span><span class=\"s2\">"tbl2"</span><span class=\"p\">,</span> <span class=\"n\">on</span><span class=\"o\">=</span><span class=\"s2\">"tbl1.y = tbl2.y"</span><span class=\"p\">,</span> <span class=\"n\">join_type</span><span class=\"o\">=</span><span class=\"s2\">"left outer"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT * FROM tbl LEFT OUTER JOIN tbl2 ON tbl1.y = tbl2.y'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> the SQL code string to parse.\nIf an <code>Expression</code> instance is passed, it will be used as-is.</li>\n<li><strong>on:</strong> optionally specify the join \"on\" criteria as a SQL string.\nIf an <code>Expression</code> instance is passed, it will be used as-is.</li>\n<li><strong>using:</strong> optionally specify the join \"using\" criteria as a SQL string.\nIf an <code>Expression</code> instance is passed, it will be used as-is.</li>\n<li><strong>append:</strong> if <code>True</code>, add to any existing expressions.\nOtherwise, this resets the expressions.</li>\n<li><strong>join_type:</strong> if set, alter the parsed join type.</li>\n<li><strong>join_alias:</strong> an optional alias for the joined source.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expressions.</li>\n<li><strong>copy:</strong> if <code>False</code>, modify this expression instance in-place.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>Select: the modified expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">on</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">using</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">Collection</span><span class=\"p\">[</span><span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">append</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">join_type</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">join_alias</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Identifier</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Select</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Select.where": {"fullname": "sqlglot.expressions.Select.where", "modulename": "sqlglot.expressions", "qualname": "Select.where", "kind": "function", "doc": "<p>Append to or set the WHERE expressions.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">Select</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"x"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">from_</span><span class=\"p\">(</span><span class=\"s2\">"tbl"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">where</span><span class=\"p\">(</span><span class=\"s2\">"x = 'a' OR x < 'b'"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">"SELECT x FROM tbl WHERE x = 'a' OR x < 'b'"</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>*expressions:</strong> the SQL code strings to parse.\nIf an <code>Expression</code> instance is passed, it will be used as-is.\nMultiple expressions are combined with an AND operator.</li>\n<li><strong>append:</strong> if <code>True</code>, AND the new expressions to any existing expression.\nOtherwise, this resets the expression.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expressions.</li>\n<li><strong>copy:</strong> if <code>False</code>, modify this expression instance in-place.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>Select: the modified expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">append</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Select</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Select.having": {"fullname": "sqlglot.expressions.Select.having", "modulename": "sqlglot.expressions", "qualname": "Select.having", "kind": "function", "doc": "<p>Append to or set the HAVING expressions.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">Select</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"x"</span><span class=\"p\">,</span> <span class=\"s2\">"COUNT(y)"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">from_</span><span class=\"p\">(</span><span class=\"s2\">"tbl"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">group_by</span><span class=\"p\">(</span><span class=\"s2\">"x"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">having</span><span class=\"p\">(</span><span class=\"s2\">"COUNT(y) > 3"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT x, COUNT(y) FROM tbl GROUP BY x HAVING COUNT(y) > 3'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>*expressions:</strong> the SQL code strings to parse.\nIf an <code>Expression</code> instance is passed, it will be used as-is.\nMultiple expressions are combined with an AND operator.</li>\n<li><strong>append:</strong> if <code>True</code>, AND the new expressions to any existing expression.\nOtherwise, this resets the expression.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expressions.</li>\n<li><strong>copy:</strong> if <code>False</code>, modify this expression instance in-place.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The modified Select expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">append</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Select</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Select.window": {"fullname": "sqlglot.expressions.Select.window", "modulename": "sqlglot.expressions", "qualname": "Select.window", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">append</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Select</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Select.qualify": {"fullname": "sqlglot.expressions.Select.qualify", "modulename": "sqlglot.expressions", "qualname": "Select.qualify", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">append</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Select</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Select.distinct": {"fullname": "sqlglot.expressions.Select.distinct", "modulename": "sqlglot.expressions", "qualname": "Select.distinct", "kind": "function", "doc": "<p>Set the OFFSET expression.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">Select</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">from_</span><span class=\"p\">(</span><span class=\"s2\">"tbl"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"x"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">distinct</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT DISTINCT x FROM tbl'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>ons:</strong> the expressions to distinct on</li>\n<li><strong>distinct:</strong> whether the Select should be distinct</li>\n<li><strong>copy:</strong> if <code>False</code>, modify this expression instance in-place.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>Select: the modified expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">ons</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">distinct</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Select</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Select.ctas": {"fullname": "sqlglot.expressions.Select.ctas", "modulename": "sqlglot.expressions", "qualname": "Select.ctas", "kind": "function", "doc": "<p>Convert this expression to a CREATE TABLE AS statement.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">Select</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"*"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">from_</span><span class=\"p\">(</span><span class=\"s2\">"tbl"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">ctas</span><span class=\"p\">(</span><span class=\"s2\">"x"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'CREATE TABLE x AS SELECT * FROM tbl'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>table:</strong> the SQL code string to parse as the table name.\nIf another <code>Expression</code> instance is passed, it will be used as-is.</li>\n<li><strong>properties:</strong> an optional mapping of table properties</li>\n<li><strong>dialect:</strong> the dialect used to parse the input table.</li>\n<li><strong>copy:</strong> if <code>False</code>, modify this expression instance in-place.</li>\n<li><strong>opts:</strong> other options to use to parse the input table.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The new Create expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">table</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">properties</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Create</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Select.lock": {"fullname": "sqlglot.expressions.Select.lock", "modulename": "sqlglot.expressions", "qualname": "Select.lock", "kind": "function", "doc": "<p>Set the locking read mode for this expression.</p>\n\n<h6 id=\"examples\">Examples:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">Select</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"x"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">from_</span><span class=\"p\">(</span><span class=\"s2\">"tbl"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">where</span><span class=\"p\">(</span><span class=\"s2\">"x = 'a'"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">lock</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">(</span><span class=\"s2\">"mysql"</span><span class=\"p\">)</span>\n<span class=\"go\">"SELECT x FROM tbl WHERE x = 'a' FOR UPDATE"</span>\n</code></pre>\n </div>\n \n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">Select</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"x"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">from_</span><span class=\"p\">(</span><span class=\"s2\">"tbl"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">where</span><span class=\"p\">(</span><span class=\"s2\">"x = 'a'"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">lock</span><span class=\"p\">(</span><span class=\"n\">update</span><span class=\"o\">=</span><span class=\"kc\">False</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">(</span><span class=\"s2\">"mysql"</span><span class=\"p\">)</span>\n<span class=\"go\">"SELECT x FROM tbl WHERE x = 'a' FOR SHARE"</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>update:</strong> if <code>True</code>, the locking type will be <code>FOR UPDATE</code>, else it will be <code>FOR SHARE</code>.</li>\n<li><strong>copy:</strong> if <code>False</code>, modify this expression instance in-place.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The modified expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">update</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Select</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Select.hint": {"fullname": "sqlglot.expressions.Select.hint", "modulename": "sqlglot.expressions", "qualname": "Select.hint", "kind": "function", "doc": "<p>Set hints for this expression.</p>\n\n<h6 id=\"examples\">Examples:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">Select</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"x"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">from_</span><span class=\"p\">(</span><span class=\"s2\">"tbl"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">hint</span><span class=\"p\">(</span><span class=\"s2\">"BROADCAST(y)"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">(</span><span class=\"n\">dialect</span><span class=\"o\">=</span><span class=\"s2\">"spark"</span><span class=\"p\">)</span>\n<span class=\"go\">'SELECT /*+ BROADCAST(y) */ x FROM tbl'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>hints:</strong> The SQL code strings to parse as the hints.\nIf an <code>Expression</code> instance is passed, it will be used as-is.</li>\n<li><strong>dialect:</strong> The dialect used to parse the hints.</li>\n<li><strong>copy:</strong> If <code>False</code>, modify this expression instance in-place.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The modified expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">hints</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Select</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Select.named_selects": {"fullname": "sqlglot.expressions.Select.named_selects", "modulename": "sqlglot.expressions", "qualname": "Select.named_selects", "kind": "variable", "doc": "<p>Returns the output names of the query's projections.</p>\n", "annotation": ": List[str]"}, "sqlglot.expressions.Select.is_star": {"fullname": "sqlglot.expressions.Select.is_star", "modulename": "sqlglot.expressions", "qualname": "Select.is_star", "kind": "variable", "doc": "<p>Checks whether an expression is a star.</p>\n", "annotation": ": bool"}, "sqlglot.expressions.Select.selects": {"fullname": "sqlglot.expressions.Select.selects", "modulename": "sqlglot.expressions", "qualname": "Select.selects", "kind": "variable", "doc": "<p>Returns the query's projections.</p>\n", "annotation": ": List[sqlglot.expressions.Expression]"}, "sqlglot.expressions.Select.key": {"fullname": "sqlglot.expressions.Select.key", "modulename": "sqlglot.expressions", "qualname": "Select.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'select'"}, "sqlglot.expressions.UNWRAPPED_QUERIES": {"fullname": "sqlglot.expressions.UNWRAPPED_QUERIES", "modulename": "sqlglot.expressions", "qualname": "UNWRAPPED_QUERIES", "kind": "variable", "doc": "<p></p>\n", "default_value": "(<class 'sqlglot.expressions.Select'>, <class 'sqlglot.expressions.Union'>)"}, "sqlglot.expressions.Subquery": {"fullname": "sqlglot.expressions.Subquery", "modulename": "sqlglot.expressions", "qualname": "Subquery", "kind": "class", "doc": "<p></p>\n", "bases": "DerivedTable, Query"}, "sqlglot.expressions.Subquery.arg_types": {"fullname": "sqlglot.expressions.Subquery.arg_types", "modulename": "sqlglot.expressions", "qualname": "Subquery.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'alias': False, 'with': False, 'match': False, 'laterals': False, 'joins': False, 'connect': False, 'pivots': False, 'prewhere': False, 'where': False, 'group': False, 'having': False, 'qualify': False, 'windows': False, 'distribute': False, 'sort': False, 'cluster': False, 'order': False, 'limit': False, 'offset': False, 'locks': False, 'sample': False, 'settings': False, 'format': False, 'options': False}"}, "sqlglot.expressions.Subquery.unnest": {"fullname": "sqlglot.expressions.Subquery.unnest", "modulename": "sqlglot.expressions", "qualname": "Subquery.unnest", "kind": "function", "doc": "<p>Returns the first non subquery.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.expressions.Subquery.unwrap": {"fullname": "sqlglot.expressions.Subquery.unwrap", "modulename": "sqlglot.expressions", "qualname": "Subquery.unwrap", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Subquery</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Subquery.select": {"fullname": "sqlglot.expressions.Subquery.select", "modulename": "sqlglot.expressions", "qualname": "Subquery.select", "kind": "function", "doc": "<p>Append to or set the SELECT expressions.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">Select</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"x"</span><span class=\"p\">,</span> <span class=\"s2\">"y"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT x, y'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>*expressions:</strong> the SQL code strings to parse.\nIf an <code>Expression</code> instance is passed, it will be used as-is.</li>\n<li><strong>append:</strong> if <code>True</code>, add to any existing expressions.\nOtherwise, this resets the expressions.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expressions.</li>\n<li><strong>copy:</strong> if <code>False</code>, modify this expression instance in-place.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The modified Query expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">append</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Subquery</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Subquery.is_wrapper": {"fullname": "sqlglot.expressions.Subquery.is_wrapper", "modulename": "sqlglot.expressions", "qualname": "Subquery.is_wrapper", "kind": "variable", "doc": "<p>Whether this Subquery acts as a simple wrapper around another expression.</p>\n\n<p>SELECT * FROM (((SELECT * FROM t)))\n ^\n This corresponds to a \"wrapper\" Subquery node</p>\n", "annotation": ": bool"}, "sqlglot.expressions.Subquery.is_star": {"fullname": "sqlglot.expressions.Subquery.is_star", "modulename": "sqlglot.expressions", "qualname": "Subquery.is_star", "kind": "variable", "doc": "<p>Checks whether an expression is a star.</p>\n", "annotation": ": bool"}, "sqlglot.expressions.Subquery.output_name": {"fullname": "sqlglot.expressions.Subquery.output_name", "modulename": "sqlglot.expressions", "qualname": "Subquery.output_name", "kind": "variable", "doc": "<p>Name of the output column if this expression is a selection.</p>\n\n<p>If the Expression has no output name, an empty string is returned.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">parse_one</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT a"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'a'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT b AS c"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'c'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT 1 + 2"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">''</span>\n</code></pre>\n </div>\n</blockquote>\n", "annotation": ": str"}, "sqlglot.expressions.Subquery.key": {"fullname": "sqlglot.expressions.Subquery.key", "modulename": "sqlglot.expressions", "qualname": "Subquery.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'subquery'"}, "sqlglot.expressions.TableSample": {"fullname": "sqlglot.expressions.TableSample", "modulename": "sqlglot.expressions", "qualname": "TableSample", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.TableSample.arg_types": {"fullname": "sqlglot.expressions.TableSample.arg_types", "modulename": "sqlglot.expressions", "qualname": "TableSample.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False, 'expressions': False, 'method': False, 'bucket_numerator': False, 'bucket_denominator': False, 'bucket_field': False, 'percent': False, 'rows': False, 'size': False, 'seed': False}"}, "sqlglot.expressions.TableSample.key": {"fullname": "sqlglot.expressions.TableSample.key", "modulename": "sqlglot.expressions", "qualname": "TableSample.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'tablesample'"}, "sqlglot.expressions.Tag": {"fullname": "sqlglot.expressions.Tag", "modulename": "sqlglot.expressions", "qualname": "Tag", "kind": "class", "doc": "<p>Tags are used for generating arbitrary sql like SELECT <span>x</span>.</p>\n", "bases": "Expression"}, "sqlglot.expressions.Tag.arg_types": {"fullname": "sqlglot.expressions.Tag.arg_types", "modulename": "sqlglot.expressions", "qualname": "Tag.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False, 'prefix': False, 'postfix': False}"}, "sqlglot.expressions.Tag.key": {"fullname": "sqlglot.expressions.Tag.key", "modulename": "sqlglot.expressions", "qualname": "Tag.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'tag'"}, "sqlglot.expressions.Pivot": {"fullname": "sqlglot.expressions.Pivot", "modulename": "sqlglot.expressions", "qualname": "Pivot", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Pivot.arg_types": {"fullname": "sqlglot.expressions.Pivot.arg_types", "modulename": "sqlglot.expressions", "qualname": "Pivot.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False, 'alias': False, 'expressions': False, 'field': False, 'unpivot': False, 'using': False, 'group': False, 'columns': False, 'include_nulls': False}"}, "sqlglot.expressions.Pivot.unpivot": {"fullname": "sqlglot.expressions.Pivot.unpivot", "modulename": "sqlglot.expressions", "qualname": "Pivot.unpivot", "kind": "variable", "doc": "<p></p>\n", "annotation": ": bool"}, "sqlglot.expressions.Pivot.key": {"fullname": "sqlglot.expressions.Pivot.key", "modulename": "sqlglot.expressions", "qualname": "Pivot.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'pivot'"}, "sqlglot.expressions.Window": {"fullname": "sqlglot.expressions.Window", "modulename": "sqlglot.expressions", "qualname": "Window", "kind": "class", "doc": "<p></p>\n", "bases": "Condition"}, "sqlglot.expressions.Window.arg_types": {"fullname": "sqlglot.expressions.Window.arg_types", "modulename": "sqlglot.expressions", "qualname": "Window.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'partition_by': False, 'order': False, 'spec': False, 'alias': False, 'over': False, 'first': False}"}, "sqlglot.expressions.Window.key": {"fullname": "sqlglot.expressions.Window.key", "modulename": "sqlglot.expressions", "qualname": "Window.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'window'"}, "sqlglot.expressions.WindowSpec": {"fullname": "sqlglot.expressions.WindowSpec", "modulename": "sqlglot.expressions", "qualname": "WindowSpec", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.WindowSpec.arg_types": {"fullname": "sqlglot.expressions.WindowSpec.arg_types", "modulename": "sqlglot.expressions", "qualname": "WindowSpec.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'kind': False, 'start': False, 'start_side': False, 'end': False, 'end_side': False}"}, "sqlglot.expressions.WindowSpec.key": {"fullname": "sqlglot.expressions.WindowSpec.key", "modulename": "sqlglot.expressions", "qualname": "WindowSpec.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'windowspec'"}, "sqlglot.expressions.PreWhere": {"fullname": "sqlglot.expressions.PreWhere", "modulename": "sqlglot.expressions", "qualname": "PreWhere", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.PreWhere.key": {"fullname": "sqlglot.expressions.PreWhere.key", "modulename": "sqlglot.expressions", "qualname": "PreWhere.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'prewhere'"}, "sqlglot.expressions.Where": {"fullname": "sqlglot.expressions.Where", "modulename": "sqlglot.expressions", "qualname": "Where", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Where.key": {"fullname": "sqlglot.expressions.Where.key", "modulename": "sqlglot.expressions", "qualname": "Where.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'where'"}, "sqlglot.expressions.Star": {"fullname": "sqlglot.expressions.Star", "modulename": "sqlglot.expressions", "qualname": "Star", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Star.arg_types": {"fullname": "sqlglot.expressions.Star.arg_types", "modulename": "sqlglot.expressions", "qualname": "Star.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'except': False, 'replace': False, 'rename': False}"}, "sqlglot.expressions.Star.name": {"fullname": "sqlglot.expressions.Star.name", "modulename": "sqlglot.expressions", "qualname": "Star.name", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.expressions.Star.output_name": {"fullname": "sqlglot.expressions.Star.output_name", "modulename": "sqlglot.expressions", "qualname": "Star.output_name", "kind": "variable", "doc": "<p>Name of the output column if this expression is a selection.</p>\n\n<p>If the Expression has no output name, an empty string is returned.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">parse_one</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT a"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'a'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT b AS c"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'c'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT 1 + 2"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">''</span>\n</code></pre>\n </div>\n</blockquote>\n", "annotation": ": str"}, "sqlglot.expressions.Star.key": {"fullname": "sqlglot.expressions.Star.key", "modulename": "sqlglot.expressions", "qualname": "Star.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'star'"}, "sqlglot.expressions.Parameter": {"fullname": "sqlglot.expressions.Parameter", "modulename": "sqlglot.expressions", "qualname": "Parameter", "kind": "class", "doc": "<p></p>\n", "bases": "Condition"}, "sqlglot.expressions.Parameter.arg_types": {"fullname": "sqlglot.expressions.Parameter.arg_types", "modulename": "sqlglot.expressions", "qualname": "Parameter.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': False}"}, "sqlglot.expressions.Parameter.key": {"fullname": "sqlglot.expressions.Parameter.key", "modulename": "sqlglot.expressions", "qualname": "Parameter.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'parameter'"}, "sqlglot.expressions.SessionParameter": {"fullname": "sqlglot.expressions.SessionParameter", "modulename": "sqlglot.expressions", "qualname": "SessionParameter", "kind": "class", "doc": "<p></p>\n", "bases": "Condition"}, "sqlglot.expressions.SessionParameter.arg_types": {"fullname": "sqlglot.expressions.SessionParameter.arg_types", "modulename": "sqlglot.expressions", "qualname": "SessionParameter.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'kind': False}"}, "sqlglot.expressions.SessionParameter.key": {"fullname": "sqlglot.expressions.SessionParameter.key", "modulename": "sqlglot.expressions", "qualname": "SessionParameter.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'sessionparameter'"}, "sqlglot.expressions.Placeholder": {"fullname": "sqlglot.expressions.Placeholder", "modulename": "sqlglot.expressions", "qualname": "Placeholder", "kind": "class", "doc": "<p></p>\n", "bases": "Condition"}, "sqlglot.expressions.Placeholder.arg_types": {"fullname": "sqlglot.expressions.Placeholder.arg_types", "modulename": "sqlglot.expressions", "qualname": "Placeholder.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False, 'kind': False}"}, "sqlglot.expressions.Placeholder.name": {"fullname": "sqlglot.expressions.Placeholder.name", "modulename": "sqlglot.expressions", "qualname": "Placeholder.name", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.expressions.Placeholder.key": {"fullname": "sqlglot.expressions.Placeholder.key", "modulename": "sqlglot.expressions", "qualname": "Placeholder.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'placeholder'"}, "sqlglot.expressions.Null": {"fullname": "sqlglot.expressions.Null", "modulename": "sqlglot.expressions", "qualname": "Null", "kind": "class", "doc": "<p></p>\n", "bases": "Condition"}, "sqlglot.expressions.Null.arg_types": {"fullname": "sqlglot.expressions.Null.arg_types", "modulename": "sqlglot.expressions", "qualname": "Null.arg_types", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, Any]", "default_value": "{}"}, "sqlglot.expressions.Null.name": {"fullname": "sqlglot.expressions.Null.name", "modulename": "sqlglot.expressions", "qualname": "Null.name", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.expressions.Null.key": {"fullname": "sqlglot.expressions.Null.key", "modulename": "sqlglot.expressions", "qualname": "Null.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'null'"}, "sqlglot.expressions.Boolean": {"fullname": "sqlglot.expressions.Boolean", "modulename": "sqlglot.expressions", "qualname": "Boolean", "kind": "class", "doc": "<p></p>\n", "bases": "Condition"}, "sqlglot.expressions.Boolean.key": {"fullname": "sqlglot.expressions.Boolean.key", "modulename": "sqlglot.expressions", "qualname": "Boolean.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'boolean'"}, "sqlglot.expressions.DataTypeParam": {"fullname": "sqlglot.expressions.DataTypeParam", "modulename": "sqlglot.expressions", "qualname": "DataTypeParam", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.DataTypeParam.arg_types": {"fullname": "sqlglot.expressions.DataTypeParam.arg_types", "modulename": "sqlglot.expressions", "qualname": "DataTypeParam.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': False}"}, "sqlglot.expressions.DataTypeParam.name": {"fullname": "sqlglot.expressions.DataTypeParam.name", "modulename": "sqlglot.expressions", "qualname": "DataTypeParam.name", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.expressions.DataTypeParam.key": {"fullname": "sqlglot.expressions.DataTypeParam.key", "modulename": "sqlglot.expressions", "qualname": "DataTypeParam.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'datatypeparam'"}, "sqlglot.expressions.DataType": {"fullname": "sqlglot.expressions.DataType", "modulename": "sqlglot.expressions", "qualname": "DataType", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.DataType.arg_types": {"fullname": "sqlglot.expressions.DataType.arg_types", "modulename": "sqlglot.expressions", "qualname": "DataType.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expressions': False, 'nested': False, 'values': False, 'prefix': False, 'kind': 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"doc": "<p></p>\n", "default_value": "<Type.SMALLMONEY: 'SMALLMONEY'>"}, "sqlglot.expressions.DataType.Type.SMALLSERIAL": {"fullname": "sqlglot.expressions.DataType.Type.SMALLSERIAL", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.SMALLSERIAL", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.SMALLSERIAL: 'SMALLSERIAL'>"}, "sqlglot.expressions.DataType.Type.STRUCT": {"fullname": "sqlglot.expressions.DataType.Type.STRUCT", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.STRUCT", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.STRUCT: 'STRUCT'>"}, "sqlglot.expressions.DataType.Type.SUPER": {"fullname": "sqlglot.expressions.DataType.Type.SUPER", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.SUPER", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.SUPER: 'SUPER'>"}, "sqlglot.expressions.DataType.Type.TEXT": {"fullname": "sqlglot.expressions.DataType.Type.TEXT", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.TEXT", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.TEXT: 'TEXT'>"}, "sqlglot.expressions.DataType.Type.TINYBLOB": {"fullname": "sqlglot.expressions.DataType.Type.TINYBLOB", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.TINYBLOB", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.TINYBLOB: 'TINYBLOB'>"}, "sqlglot.expressions.DataType.Type.TINYTEXT": {"fullname": "sqlglot.expressions.DataType.Type.TINYTEXT", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.TINYTEXT", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.TINYTEXT: 'TINYTEXT'>"}, "sqlglot.expressions.DataType.Type.TIME": {"fullname": "sqlglot.expressions.DataType.Type.TIME", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.TIME", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.TIME: 'TIME'>"}, "sqlglot.expressions.DataType.Type.TIMETZ": {"fullname": "sqlglot.expressions.DataType.Type.TIMETZ", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.TIMETZ", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.TIMETZ: 'TIMETZ'>"}, "sqlglot.expressions.DataType.Type.TIMESTAMP": {"fullname": "sqlglot.expressions.DataType.Type.TIMESTAMP", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.TIMESTAMP", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.TIMESTAMP: 'TIMESTAMP'>"}, "sqlglot.expressions.DataType.Type.TIMESTAMPNTZ": {"fullname": "sqlglot.expressions.DataType.Type.TIMESTAMPNTZ", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.TIMESTAMPNTZ", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>"}, "sqlglot.expressions.DataType.Type.TIMESTAMPLTZ": {"fullname": "sqlglot.expressions.DataType.Type.TIMESTAMPLTZ", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.TIMESTAMPLTZ", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>"}, "sqlglot.expressions.DataType.Type.TIMESTAMPTZ": {"fullname": "sqlglot.expressions.DataType.Type.TIMESTAMPTZ", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.TIMESTAMPTZ", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.TIMESTAMPTZ: 'TIMESTAMPTZ'>"}, "sqlglot.expressions.DataType.Type.TIMESTAMP_S": {"fullname": "sqlglot.expressions.DataType.Type.TIMESTAMP_S", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.TIMESTAMP_S", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.TIMESTAMP_S: 'TIMESTAMP_S'>"}, "sqlglot.expressions.DataType.Type.TIMESTAMP_MS": {"fullname": "sqlglot.expressions.DataType.Type.TIMESTAMP_MS", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.TIMESTAMP_MS", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.TIMESTAMP_MS: 'TIMESTAMP_MS'>"}, "sqlglot.expressions.DataType.Type.TIMESTAMP_NS": {"fullname": "sqlglot.expressions.DataType.Type.TIMESTAMP_NS", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.TIMESTAMP_NS", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.TIMESTAMP_NS: 'TIMESTAMP_NS'>"}, "sqlglot.expressions.DataType.Type.TINYINT": {"fullname": "sqlglot.expressions.DataType.Type.TINYINT", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.TINYINT", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.TINYINT: 'TINYINT'>"}, "sqlglot.expressions.DataType.Type.TSMULTIRANGE": {"fullname": "sqlglot.expressions.DataType.Type.TSMULTIRANGE", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.TSMULTIRANGE", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.TSMULTIRANGE: 'TSMULTIRANGE'>"}, "sqlglot.expressions.DataType.Type.TSRANGE": {"fullname": "sqlglot.expressions.DataType.Type.TSRANGE", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.TSRANGE", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.TSRANGE: 'TSRANGE'>"}, "sqlglot.expressions.DataType.Type.TSTZMULTIRANGE": {"fullname": "sqlglot.expressions.DataType.Type.TSTZMULTIRANGE", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.TSTZMULTIRANGE", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>"}, "sqlglot.expressions.DataType.Type.TSTZRANGE": {"fullname": "sqlglot.expressions.DataType.Type.TSTZRANGE", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.TSTZRANGE", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.TSTZRANGE: 'TSTZRANGE'>"}, "sqlglot.expressions.DataType.Type.UBIGINT": {"fullname": "sqlglot.expressions.DataType.Type.UBIGINT", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.UBIGINT", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.UBIGINT: 'UBIGINT'>"}, "sqlglot.expressions.DataType.Type.UINT": {"fullname": "sqlglot.expressions.DataType.Type.UINT", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.UINT", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.UINT: 'UINT'>"}, "sqlglot.expressions.DataType.Type.UINT128": {"fullname": "sqlglot.expressions.DataType.Type.UINT128", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.UINT128", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.UINT128: 'UINT128'>"}, "sqlglot.expressions.DataType.Type.UINT256": {"fullname": "sqlglot.expressions.DataType.Type.UINT256", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.UINT256", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.UINT256: 'UINT256'>"}, "sqlglot.expressions.DataType.Type.UMEDIUMINT": {"fullname": "sqlglot.expressions.DataType.Type.UMEDIUMINT", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.UMEDIUMINT", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.UMEDIUMINT: 'UMEDIUMINT'>"}, "sqlglot.expressions.DataType.Type.UDECIMAL": {"fullname": "sqlglot.expressions.DataType.Type.UDECIMAL", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.UDECIMAL", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.UDECIMAL: 'UDECIMAL'>"}, "sqlglot.expressions.DataType.Type.UNIQUEIDENTIFIER": {"fullname": "sqlglot.expressions.DataType.Type.UNIQUEIDENTIFIER", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.UNIQUEIDENTIFIER", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>"}, "sqlglot.expressions.DataType.Type.UNKNOWN": {"fullname": "sqlglot.expressions.DataType.Type.UNKNOWN", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.UNKNOWN", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.UNKNOWN: 'UNKNOWN'>"}, "sqlglot.expressions.DataType.Type.USERDEFINED": {"fullname": "sqlglot.expressions.DataType.Type.USERDEFINED", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.USERDEFINED", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.USERDEFINED: 'USER-DEFINED'>"}, "sqlglot.expressions.DataType.Type.USMALLINT": {"fullname": "sqlglot.expressions.DataType.Type.USMALLINT", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.USMALLINT", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.USMALLINT: 'USMALLINT'>"}, "sqlglot.expressions.DataType.Type.UTINYINT": {"fullname": "sqlglot.expressions.DataType.Type.UTINYINT", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.UTINYINT", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.UTINYINT: 'UTINYINT'>"}, "sqlglot.expressions.DataType.Type.UUID": {"fullname": "sqlglot.expressions.DataType.Type.UUID", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.UUID", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.UUID: 'UUID'>"}, "sqlglot.expressions.DataType.Type.VARBINARY": {"fullname": "sqlglot.expressions.DataType.Type.VARBINARY", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.VARBINARY", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.VARBINARY: 'VARBINARY'>"}, "sqlglot.expressions.DataType.Type.VARCHAR": {"fullname": "sqlglot.expressions.DataType.Type.VARCHAR", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.VARCHAR", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.VARCHAR: 'VARCHAR'>"}, "sqlglot.expressions.DataType.Type.VARIANT": {"fullname": "sqlglot.expressions.DataType.Type.VARIANT", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.VARIANT", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.VARIANT: 'VARIANT'>"}, "sqlglot.expressions.DataType.Type.XML": {"fullname": "sqlglot.expressions.DataType.Type.XML", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.XML", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.XML: 'XML'>"}, "sqlglot.expressions.DataType.Type.YEAR": {"fullname": "sqlglot.expressions.DataType.Type.YEAR", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.YEAR", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.YEAR: 'YEAR'>"}, "sqlglot.expressions.DataType.Type.TDIGEST": {"fullname": "sqlglot.expressions.DataType.Type.TDIGEST", "modulename": "sqlglot.expressions", "qualname": "DataType.Type.TDIGEST", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Type.TDIGEST: 'TDIGEST'>"}, "sqlglot.expressions.DataType.STRUCT_TYPES": {"fullname": "sqlglot.expressions.DataType.STRUCT_TYPES", "modulename": "sqlglot.expressions", "qualname": "DataType.STRUCT_TYPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.NESTED: 'NESTED'>, <Type.OBJECT: 'OBJECT'>, <Type.STRUCT: 'STRUCT'>}"}, "sqlglot.expressions.DataType.NESTED_TYPES": {"fullname": "sqlglot.expressions.DataType.NESTED_TYPES", "modulename": "sqlglot.expressions", "qualname": "DataType.NESTED_TYPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.NESTED: 'NESTED'>, <Type.MAP: 'MAP'>, <Type.OBJECT: 'OBJECT'>, <Type.ARRAY: 'ARRAY'>, <Type.STRUCT: 'STRUCT'>}"}, "sqlglot.expressions.DataType.TEXT_TYPES": {"fullname": "sqlglot.expressions.DataType.TEXT_TYPES", "modulename": "sqlglot.expressions", "qualname": "DataType.TEXT_TYPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.CHAR: 'CHAR'>, <Type.NCHAR: 'NCHAR'>, <Type.NAME: 'NAME'>, <Type.VARCHAR: 'VARCHAR'>, <Type.NVARCHAR: 'NVARCHAR'>, <Type.TEXT: 'TEXT'>}"}, "sqlglot.expressions.DataType.SIGNED_INTEGER_TYPES": {"fullname": "sqlglot.expressions.DataType.SIGNED_INTEGER_TYPES", "modulename": "sqlglot.expressions", "qualname": "DataType.SIGNED_INTEGER_TYPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.BIGINT: 'BIGINT'>, <Type.INT128: 'INT128'>, <Type.TINYINT: 'TINYINT'>, <Type.SMALLINT: 'SMALLINT'>, <Type.INT256: 'INT256'>, <Type.INT: 'INT'>, <Type.MEDIUMINT: 'MEDIUMINT'>}"}, "sqlglot.expressions.DataType.UNSIGNED_INTEGER_TYPES": {"fullname": "sqlglot.expressions.DataType.UNSIGNED_INTEGER_TYPES", "modulename": "sqlglot.expressions", "qualname": "DataType.UNSIGNED_INTEGER_TYPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.UINT128: 'UINT128'>, <Type.UINT256: 'UINT256'>, <Type.USMALLINT: 'USMALLINT'>, <Type.UBIGINT: 'UBIGINT'>, <Type.UINT: 'UINT'>, <Type.UMEDIUMINT: 'UMEDIUMINT'>, <Type.UTINYINT: 'UTINYINT'>}"}, "sqlglot.expressions.DataType.INTEGER_TYPES": {"fullname": "sqlglot.expressions.DataType.INTEGER_TYPES", "modulename": "sqlglot.expressions", "qualname": "DataType.INTEGER_TYPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.UINT128: 'UINT128'>, <Type.BIGINT: 'BIGINT'>, <Type.INT128: 'INT128'>, <Type.UINT256: 'UINT256'>, <Type.USMALLINT: 'USMALLINT'>, <Type.MEDIUMINT: 'MEDIUMINT'>, <Type.UBIGINT: 'UBIGINT'>, <Type.TINYINT: 'TINYINT'>, <Type.BIT: 'BIT'>, <Type.SMALLINT: 'SMALLINT'>, <Type.UINT: 'UINT'>, <Type.INT256: 'INT256'>, <Type.INT: 'INT'>, <Type.UMEDIUMINT: 'UMEDIUMINT'>, <Type.UTINYINT: 'UTINYINT'>}"}, "sqlglot.expressions.DataType.FLOAT_TYPES": {"fullname": "sqlglot.expressions.DataType.FLOAT_TYPES", "modulename": "sqlglot.expressions", "qualname": "DataType.FLOAT_TYPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.DOUBLE: 'DOUBLE'>, <Type.FLOAT: 'FLOAT'>}"}, "sqlglot.expressions.DataType.REAL_TYPES": {"fullname": "sqlglot.expressions.DataType.REAL_TYPES", "modulename": "sqlglot.expressions", "qualname": "DataType.REAL_TYPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.MONEY: 'MONEY'>, <Type.DOUBLE: 'DOUBLE'>, <Type.DECIMAL: 'DECIMAL'>, <Type.SMALLMONEY: 'SMALLMONEY'>, <Type.BIGDECIMAL: 'BIGDECIMAL'>, <Type.FLOAT: 'FLOAT'>, <Type.UDECIMAL: 'UDECIMAL'>}"}, "sqlglot.expressions.DataType.NUMERIC_TYPES": {"fullname": "sqlglot.expressions.DataType.NUMERIC_TYPES", "modulename": "sqlglot.expressions", "qualname": "DataType.NUMERIC_TYPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.UINT256: 'UINT256'>, <Type.BIGINT: 'BIGINT'>, <Type.INT128: 'INT128'>, <Type.MONEY: 'MONEY'>, <Type.USMALLINT: 'USMALLINT'>, <Type.SMALLMONEY: 'SMALLMONEY'>, <Type.UBIGINT: 'UBIGINT'>, <Type.SMALLINT: 'SMALLINT'>, <Type.INT256: 'INT256'>, <Type.FLOAT: 'FLOAT'>, <Type.MEDIUMINT: 'MEDIUMINT'>, <Type.UMEDIUMINT: 'UMEDIUMINT'>, <Type.UTINYINT: 'UTINYINT'>, <Type.UINT128: 'UINT128'>, <Type.UDECIMAL: 'UDECIMAL'>, <Type.DOUBLE: 'DOUBLE'>, <Type.DECIMAL: 'DECIMAL'>, <Type.BIGDECIMAL: 'BIGDECIMAL'>, <Type.BIT: 'BIT'>, <Type.UINT: 'UINT'>, <Type.INT: 'INT'>, <Type.TINYINT: 'TINYINT'>}"}, "sqlglot.expressions.DataType.TEMPORAL_TYPES": {"fullname": "sqlglot.expressions.DataType.TEMPORAL_TYPES", "modulename": "sqlglot.expressions", "qualname": "DataType.TEMPORAL_TYPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.TIME: 'TIME'>, <Type.DATE: 'DATE'>, <Type.TIMESTAMP_MS: 'TIMESTAMP_MS'>, <Type.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <Type.DATE32: 'DATE32'>, <Type.TIMESTAMP_S: 'TIMESTAMP_S'>, <Type.TIMESTAMP_NS: 'TIMESTAMP_NS'>, <Type.DATETIME64: 'DATETIME64'>, <Type.DATETIME: 'DATETIME'>, <Type.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <Type.TIMETZ: 'TIMETZ'>, <Type.TIMESTAMP: 'TIMESTAMP'>, <Type.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>}"}, "sqlglot.expressions.DataType.build": {"fullname": "sqlglot.expressions.DataType.build", "modulename": "sqlglot.expressions", "qualname": "DataType.build", "kind": "function", "doc": "<p>Constructs a DataType object.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>dtype:</strong> the data type of interest.</li>\n<li><strong>dialect:</strong> the dialect to use for parsing <code>dtype</code>, in case it's a string.</li>\n<li><strong>udt:</strong> when set to True, <code>dtype</code> will be used as-is if it can't be parsed into a\nDataType, thus creating a user-defined type.</li>\n<li><strong>copy:</strong> whether to copy the data type.</li>\n<li><strong>kwargs:</strong> additional arguments to pass in the constructor of DataType.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The constructed DataType object.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">cls</span>,</span><span class=\"param\">\t<span class=\"n\">dtype</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">udt</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.DataType.is_type": {"fullname": "sqlglot.expressions.DataType.is_type", "modulename": "sqlglot.expressions", "qualname": "DataType.is_type", "kind": "function", "doc": "<p>Checks whether this DataType matches one of the provided data types. Nested types or precision\nwill be compared using \"structural equivalence\" semantics, so e.g. array<int> != array<float>.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>dtypes:</strong> the data types to compare this DataType to.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>True, if and only if there is a type in <code>dtypes</code> which is equal to this DataType.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">dtypes</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">bool</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.DataType.key": {"fullname": "sqlglot.expressions.DataType.key", "modulename": "sqlglot.expressions", "qualname": "DataType.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'datatype'"}, "sqlglot.expressions.DATA_TYPE": {"fullname": "sqlglot.expressions.DATA_TYPE", "modulename": "sqlglot.expressions", "qualname": "DATA_TYPE", "kind": "variable", "doc": "<p></p>\n", "default_value": "typing.Union[str, sqlglot.expressions.DataType, sqlglot.expressions.DataType.Type]"}, "sqlglot.expressions.PseudoType": {"fullname": "sqlglot.expressions.PseudoType", "modulename": "sqlglot.expressions", "qualname": "PseudoType", "kind": "class", "doc": "<p></p>\n", "bases": "DataType"}, "sqlglot.expressions.PseudoType.arg_types": {"fullname": "sqlglot.expressions.PseudoType.arg_types", "modulename": "sqlglot.expressions", "qualname": "PseudoType.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True}"}, "sqlglot.expressions.PseudoType.key": {"fullname": "sqlglot.expressions.PseudoType.key", "modulename": "sqlglot.expressions", "qualname": "PseudoType.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'pseudotype'"}, "sqlglot.expressions.ObjectIdentifier": {"fullname": "sqlglot.expressions.ObjectIdentifier", "modulename": "sqlglot.expressions", "qualname": "ObjectIdentifier", "kind": "class", "doc": "<p></p>\n", "bases": "DataType"}, "sqlglot.expressions.ObjectIdentifier.arg_types": {"fullname": "sqlglot.expressions.ObjectIdentifier.arg_types", "modulename": "sqlglot.expressions", "qualname": "ObjectIdentifier.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True}"}, "sqlglot.expressions.ObjectIdentifier.key": {"fullname": "sqlglot.expressions.ObjectIdentifier.key", "modulename": "sqlglot.expressions", "qualname": "ObjectIdentifier.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'objectidentifier'"}, "sqlglot.expressions.SubqueryPredicate": {"fullname": "sqlglot.expressions.SubqueryPredicate", "modulename": "sqlglot.expressions", "qualname": "SubqueryPredicate", "kind": "class", "doc": "<p></p>\n", "bases": "Predicate"}, "sqlglot.expressions.SubqueryPredicate.key": {"fullname": "sqlglot.expressions.SubqueryPredicate.key", "modulename": "sqlglot.expressions", "qualname": "SubqueryPredicate.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'subquerypredicate'"}, "sqlglot.expressions.All": {"fullname": "sqlglot.expressions.All", "modulename": "sqlglot.expressions", "qualname": "All", "kind": "class", "doc": "<p></p>\n", "bases": "SubqueryPredicate"}, "sqlglot.expressions.All.key": {"fullname": "sqlglot.expressions.All.key", "modulename": "sqlglot.expressions", "qualname": "All.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'all'"}, "sqlglot.expressions.Any": {"fullname": "sqlglot.expressions.Any", "modulename": "sqlglot.expressions", "qualname": "Any", "kind": "class", "doc": "<p></p>\n", "bases": "SubqueryPredicate"}, "sqlglot.expressions.Any.key": {"fullname": "sqlglot.expressions.Any.key", "modulename": "sqlglot.expressions", "qualname": "Any.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'any'"}, "sqlglot.expressions.Exists": {"fullname": "sqlglot.expressions.Exists", "modulename": "sqlglot.expressions", "qualname": "Exists", "kind": "class", "doc": "<p></p>\n", "bases": "SubqueryPredicate"}, "sqlglot.expressions.Exists.key": {"fullname": "sqlglot.expressions.Exists.key", "modulename": "sqlglot.expressions", "qualname": "Exists.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'exists'"}, "sqlglot.expressions.Command": {"fullname": "sqlglot.expressions.Command", "modulename": "sqlglot.expressions", "qualname": "Command", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Command.arg_types": {"fullname": "sqlglot.expressions.Command.arg_types", "modulename": "sqlglot.expressions", "qualname": "Command.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': False}"}, "sqlglot.expressions.Command.key": {"fullname": "sqlglot.expressions.Command.key", "modulename": "sqlglot.expressions", "qualname": "Command.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'command'"}, "sqlglot.expressions.Transaction": {"fullname": "sqlglot.expressions.Transaction", "modulename": "sqlglot.expressions", "qualname": "Transaction", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Transaction.arg_types": {"fullname": "sqlglot.expressions.Transaction.arg_types", "modulename": "sqlglot.expressions", "qualname": "Transaction.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False, 'modes': False, 'mark': False}"}, "sqlglot.expressions.Transaction.key": {"fullname": "sqlglot.expressions.Transaction.key", "modulename": "sqlglot.expressions", "qualname": "Transaction.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'transaction'"}, "sqlglot.expressions.Commit": {"fullname": "sqlglot.expressions.Commit", "modulename": "sqlglot.expressions", "qualname": "Commit", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Commit.arg_types": {"fullname": "sqlglot.expressions.Commit.arg_types", "modulename": "sqlglot.expressions", "qualname": "Commit.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'chain': False, 'this': False, 'durability': False}"}, "sqlglot.expressions.Commit.key": {"fullname": "sqlglot.expressions.Commit.key", "modulename": "sqlglot.expressions", "qualname": "Commit.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'commit'"}, "sqlglot.expressions.Rollback": {"fullname": "sqlglot.expressions.Rollback", "modulename": "sqlglot.expressions", "qualname": "Rollback", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Rollback.arg_types": {"fullname": "sqlglot.expressions.Rollback.arg_types", "modulename": "sqlglot.expressions", "qualname": "Rollback.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'savepoint': False, 'this': False}"}, "sqlglot.expressions.Rollback.key": {"fullname": "sqlglot.expressions.Rollback.key", "modulename": "sqlglot.expressions", "qualname": "Rollback.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'rollback'"}, "sqlglot.expressions.AlterTable": {"fullname": "sqlglot.expressions.AlterTable", "modulename": "sqlglot.expressions", "qualname": "AlterTable", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.AlterTable.arg_types": {"fullname": "sqlglot.expressions.AlterTable.arg_types", "modulename": "sqlglot.expressions", "qualname": "AlterTable.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'actions': True, 'exists': False, 'only': False, 'options': False, 'cluster': False}"}, "sqlglot.expressions.AlterTable.key": {"fullname": "sqlglot.expressions.AlterTable.key", "modulename": "sqlglot.expressions", "qualname": "AlterTable.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'altertable'"}, "sqlglot.expressions.AddConstraint": {"fullname": "sqlglot.expressions.AddConstraint", "modulename": "sqlglot.expressions", "qualname": "AddConstraint", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.AddConstraint.arg_types": {"fullname": "sqlglot.expressions.AddConstraint.arg_types", "modulename": "sqlglot.expressions", "qualname": "AddConstraint.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'expressions': True}"}, "sqlglot.expressions.AddConstraint.key": {"fullname": "sqlglot.expressions.AddConstraint.key", "modulename": "sqlglot.expressions", "qualname": "AddConstraint.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'addconstraint'"}, "sqlglot.expressions.DropPartition": {"fullname": "sqlglot.expressions.DropPartition", "modulename": "sqlglot.expressions", "qualname": "DropPartition", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.DropPartition.arg_types": {"fullname": "sqlglot.expressions.DropPartition.arg_types", "modulename": "sqlglot.expressions", "qualname": "DropPartition.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'expressions': True, 'exists': False}"}, "sqlglot.expressions.DropPartition.key": {"fullname": "sqlglot.expressions.DropPartition.key", "modulename": "sqlglot.expressions", "qualname": "DropPartition.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'droppartition'"}, "sqlglot.expressions.ReplacePartition": {"fullname": "sqlglot.expressions.ReplacePartition", "modulename": "sqlglot.expressions", "qualname": "ReplacePartition", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.ReplacePartition.arg_types": {"fullname": "sqlglot.expressions.ReplacePartition.arg_types", "modulename": "sqlglot.expressions", "qualname": "ReplacePartition.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'expression': True, 'source': True}"}, "sqlglot.expressions.ReplacePartition.key": {"fullname": "sqlglot.expressions.ReplacePartition.key", "modulename": "sqlglot.expressions", "qualname": "ReplacePartition.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'replacepartition'"}, "sqlglot.expressions.Binary": {"fullname": "sqlglot.expressions.Binary", "modulename": "sqlglot.expressions", "qualname": "Binary", "kind": "class", "doc": "<p></p>\n", "bases": "Condition"}, "sqlglot.expressions.Binary.arg_types": {"fullname": "sqlglot.expressions.Binary.arg_types", "modulename": "sqlglot.expressions", "qualname": "Binary.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': True}"}, "sqlglot.expressions.Binary.left": {"fullname": "sqlglot.expressions.Binary.left", "modulename": "sqlglot.expressions", "qualname": "Binary.left", "kind": "variable", "doc": "<p></p>\n", "annotation": ": sqlglot.expressions.Expression"}, "sqlglot.expressions.Binary.right": {"fullname": "sqlglot.expressions.Binary.right", "modulename": "sqlglot.expressions", "qualname": "Binary.right", "kind": "variable", "doc": "<p></p>\n", "annotation": ": sqlglot.expressions.Expression"}, "sqlglot.expressions.Binary.key": {"fullname": "sqlglot.expressions.Binary.key", "modulename": "sqlglot.expressions", "qualname": "Binary.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'binary'"}, "sqlglot.expressions.Add": {"fullname": "sqlglot.expressions.Add", "modulename": "sqlglot.expressions", "qualname": "Add", "kind": "class", "doc": "<p></p>\n", "bases": "Binary"}, "sqlglot.expressions.Add.key": {"fullname": "sqlglot.expressions.Add.key", "modulename": "sqlglot.expressions", "qualname": "Add.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'add'"}, "sqlglot.expressions.Connector": {"fullname": "sqlglot.expressions.Connector", "modulename": "sqlglot.expressions", "qualname": "Connector", "kind": "class", "doc": "<p></p>\n", "bases": "Binary"}, "sqlglot.expressions.Connector.key": {"fullname": "sqlglot.expressions.Connector.key", "modulename": "sqlglot.expressions", "qualname": "Connector.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'connector'"}, "sqlglot.expressions.And": {"fullname": "sqlglot.expressions.And", "modulename": "sqlglot.expressions", "qualname": "And", "kind": "class", "doc": "<p></p>\n", "bases": "Connector"}, "sqlglot.expressions.And.key": {"fullname": "sqlglot.expressions.And.key", "modulename": "sqlglot.expressions", "qualname": "And.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'and'"}, "sqlglot.expressions.Or": {"fullname": "sqlglot.expressions.Or", "modulename": "sqlglot.expressions", "qualname": "Or", "kind": "class", "doc": "<p></p>\n", "bases": "Connector"}, "sqlglot.expressions.Or.key": {"fullname": "sqlglot.expressions.Or.key", "modulename": "sqlglot.expressions", "qualname": "Or.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'or'"}, "sqlglot.expressions.BitwiseAnd": {"fullname": "sqlglot.expressions.BitwiseAnd", "modulename": "sqlglot.expressions", "qualname": "BitwiseAnd", "kind": "class", "doc": "<p></p>\n", "bases": "Binary"}, "sqlglot.expressions.BitwiseAnd.key": {"fullname": "sqlglot.expressions.BitwiseAnd.key", "modulename": "sqlglot.expressions", "qualname": "BitwiseAnd.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'bitwiseand'"}, "sqlglot.expressions.BitwiseLeftShift": {"fullname": "sqlglot.expressions.BitwiseLeftShift", "modulename": "sqlglot.expressions", "qualname": "BitwiseLeftShift", "kind": "class", "doc": "<p></p>\n", "bases": "Binary"}, "sqlglot.expressions.BitwiseLeftShift.key": {"fullname": "sqlglot.expressions.BitwiseLeftShift.key", "modulename": "sqlglot.expressions", "qualname": "BitwiseLeftShift.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'bitwiseleftshift'"}, "sqlglot.expressions.BitwiseOr": {"fullname": "sqlglot.expressions.BitwiseOr", "modulename": "sqlglot.expressions", "qualname": "BitwiseOr", "kind": "class", "doc": "<p></p>\n", "bases": "Binary"}, "sqlglot.expressions.BitwiseOr.key": {"fullname": "sqlglot.expressions.BitwiseOr.key", "modulename": "sqlglot.expressions", "qualname": "BitwiseOr.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'bitwiseor'"}, "sqlglot.expressions.BitwiseRightShift": {"fullname": "sqlglot.expressions.BitwiseRightShift", "modulename": "sqlglot.expressions", "qualname": "BitwiseRightShift", "kind": "class", "doc": "<p></p>\n", "bases": "Binary"}, "sqlglot.expressions.BitwiseRightShift.key": {"fullname": "sqlglot.expressions.BitwiseRightShift.key", "modulename": "sqlglot.expressions", "qualname": "BitwiseRightShift.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'bitwiserightshift'"}, "sqlglot.expressions.BitwiseXor": {"fullname": "sqlglot.expressions.BitwiseXor", "modulename": "sqlglot.expressions", "qualname": "BitwiseXor", "kind": "class", "doc": "<p></p>\n", "bases": "Binary"}, "sqlglot.expressions.BitwiseXor.key": {"fullname": "sqlglot.expressions.BitwiseXor.key", "modulename": "sqlglot.expressions", "qualname": "BitwiseXor.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'bitwisexor'"}, "sqlglot.expressions.Div": {"fullname": "sqlglot.expressions.Div", "modulename": "sqlglot.expressions", "qualname": "Div", "kind": "class", "doc": "<p></p>\n", "bases": "Binary"}, "sqlglot.expressions.Div.arg_types": {"fullname": "sqlglot.expressions.Div.arg_types", "modulename": "sqlglot.expressions", "qualname": "Div.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': True, 'typed': False, 'safe': False}"}, "sqlglot.expressions.Div.key": {"fullname": "sqlglot.expressions.Div.key", "modulename": "sqlglot.expressions", "qualname": "Div.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'div'"}, "sqlglot.expressions.Overlaps": {"fullname": "sqlglot.expressions.Overlaps", "modulename": "sqlglot.expressions", "qualname": "Overlaps", "kind": "class", "doc": "<p></p>\n", "bases": "Binary"}, "sqlglot.expressions.Overlaps.key": {"fullname": "sqlglot.expressions.Overlaps.key", "modulename": "sqlglot.expressions", "qualname": "Overlaps.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'overlaps'"}, "sqlglot.expressions.Dot": {"fullname": "sqlglot.expressions.Dot", "modulename": "sqlglot.expressions", "qualname": "Dot", "kind": "class", "doc": "<p></p>\n", "bases": "Binary"}, "sqlglot.expressions.Dot.is_star": {"fullname": "sqlglot.expressions.Dot.is_star", "modulename": "sqlglot.expressions", "qualname": "Dot.is_star", "kind": "variable", "doc": "<p>Checks whether an expression is a star.</p>\n", "annotation": ": bool"}, "sqlglot.expressions.Dot.name": {"fullname": "sqlglot.expressions.Dot.name", "modulename": "sqlglot.expressions", "qualname": "Dot.name", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.expressions.Dot.output_name": {"fullname": "sqlglot.expressions.Dot.output_name", "modulename": "sqlglot.expressions", "qualname": "Dot.output_name", "kind": "variable", "doc": "<p>Name of the output column if this expression is a selection.</p>\n\n<p>If the Expression has no output name, an empty string is returned.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">parse_one</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT a"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'a'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT b AS c"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'c'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT 1 + 2"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">''</span>\n</code></pre>\n </div>\n</blockquote>\n", "annotation": ": str"}, "sqlglot.expressions.Dot.build": {"fullname": "sqlglot.expressions.Dot.build", "modulename": "sqlglot.expressions", "qualname": "Dot.build", "kind": "function", "doc": "<p>Build a Dot object with a sequence of expressions.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Sequence</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Dot</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Dot.parts": {"fullname": "sqlglot.expressions.Dot.parts", "modulename": "sqlglot.expressions", "qualname": "Dot.parts", "kind": "variable", "doc": "<p>Return the parts of a table / column in order catalog, db, table.</p>\n", "annotation": ": List[sqlglot.expressions.Expression]"}, "sqlglot.expressions.Dot.key": {"fullname": "sqlglot.expressions.Dot.key", "modulename": "sqlglot.expressions", "qualname": "Dot.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'dot'"}, "sqlglot.expressions.DPipe": {"fullname": "sqlglot.expressions.DPipe", "modulename": "sqlglot.expressions", "qualname": "DPipe", "kind": "class", "doc": "<p></p>\n", "bases": "Binary"}, "sqlglot.expressions.DPipe.arg_types": {"fullname": "sqlglot.expressions.DPipe.arg_types", "modulename": "sqlglot.expressions", "qualname": "DPipe.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': True, 'safe': False}"}, "sqlglot.expressions.DPipe.key": {"fullname": "sqlglot.expressions.DPipe.key", "modulename": "sqlglot.expressions", "qualname": "DPipe.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'dpipe'"}, "sqlglot.expressions.EQ": {"fullname": "sqlglot.expressions.EQ", "modulename": "sqlglot.expressions", "qualname": "EQ", "kind": "class", "doc": "<p></p>\n", "bases": "Binary, Predicate"}, "sqlglot.expressions.EQ.key": {"fullname": "sqlglot.expressions.EQ.key", "modulename": "sqlglot.expressions", "qualname": "EQ.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'eq'"}, "sqlglot.expressions.NullSafeEQ": {"fullname": "sqlglot.expressions.NullSafeEQ", "modulename": "sqlglot.expressions", "qualname": "NullSafeEQ", "kind": "class", "doc": "<p></p>\n", "bases": "Binary, Predicate"}, "sqlglot.expressions.NullSafeEQ.key": {"fullname": "sqlglot.expressions.NullSafeEQ.key", "modulename": "sqlglot.expressions", "qualname": "NullSafeEQ.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'nullsafeeq'"}, "sqlglot.expressions.NullSafeNEQ": {"fullname": "sqlglot.expressions.NullSafeNEQ", "modulename": "sqlglot.expressions", "qualname": "NullSafeNEQ", "kind": "class", "doc": "<p></p>\n", "bases": "Binary, Predicate"}, "sqlglot.expressions.NullSafeNEQ.key": {"fullname": "sqlglot.expressions.NullSafeNEQ.key", "modulename": "sqlglot.expressions", "qualname": "NullSafeNEQ.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'nullsafeneq'"}, "sqlglot.expressions.PropertyEQ": {"fullname": "sqlglot.expressions.PropertyEQ", "modulename": "sqlglot.expressions", "qualname": "PropertyEQ", "kind": "class", "doc": "<p></p>\n", "bases": "Binary"}, "sqlglot.expressions.PropertyEQ.key": {"fullname": "sqlglot.expressions.PropertyEQ.key", "modulename": "sqlglot.expressions", "qualname": "PropertyEQ.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'propertyeq'"}, "sqlglot.expressions.Distance": {"fullname": "sqlglot.expressions.Distance", "modulename": "sqlglot.expressions", "qualname": "Distance", "kind": "class", "doc": "<p></p>\n", "bases": "Binary"}, "sqlglot.expressions.Distance.key": {"fullname": "sqlglot.expressions.Distance.key", "modulename": "sqlglot.expressions", "qualname": "Distance.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'distance'"}, "sqlglot.expressions.Escape": {"fullname": "sqlglot.expressions.Escape", "modulename": "sqlglot.expressions", "qualname": "Escape", "kind": "class", "doc": "<p></p>\n", "bases": "Binary"}, "sqlglot.expressions.Escape.key": {"fullname": "sqlglot.expressions.Escape.key", "modulename": "sqlglot.expressions", "qualname": "Escape.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'escape'"}, "sqlglot.expressions.Glob": {"fullname": "sqlglot.expressions.Glob", "modulename": "sqlglot.expressions", "qualname": "Glob", "kind": "class", "doc": "<p></p>\n", "bases": "Binary, Predicate"}, "sqlglot.expressions.Glob.key": {"fullname": "sqlglot.expressions.Glob.key", "modulename": "sqlglot.expressions", "qualname": "Glob.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'glob'"}, "sqlglot.expressions.GT": {"fullname": "sqlglot.expressions.GT", "modulename": "sqlglot.expressions", "qualname": "GT", "kind": "class", "doc": "<p></p>\n", "bases": "Binary, Predicate"}, "sqlglot.expressions.GT.key": {"fullname": "sqlglot.expressions.GT.key", "modulename": "sqlglot.expressions", "qualname": "GT.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'gt'"}, "sqlglot.expressions.GTE": {"fullname": "sqlglot.expressions.GTE", "modulename": "sqlglot.expressions", "qualname": "GTE", "kind": "class", "doc": "<p></p>\n", "bases": "Binary, Predicate"}, "sqlglot.expressions.GTE.key": {"fullname": "sqlglot.expressions.GTE.key", "modulename": "sqlglot.expressions", "qualname": "GTE.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'gte'"}, "sqlglot.expressions.ILike": {"fullname": "sqlglot.expressions.ILike", "modulename": "sqlglot.expressions", "qualname": "ILike", "kind": "class", "doc": "<p></p>\n", "bases": "Binary, Predicate"}, "sqlglot.expressions.ILike.key": {"fullname": "sqlglot.expressions.ILike.key", "modulename": "sqlglot.expressions", "qualname": "ILike.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'ilike'"}, "sqlglot.expressions.ILikeAny": {"fullname": "sqlglot.expressions.ILikeAny", "modulename": "sqlglot.expressions", "qualname": "ILikeAny", "kind": "class", "doc": "<p></p>\n", "bases": "Binary, Predicate"}, "sqlglot.expressions.ILikeAny.key": {"fullname": "sqlglot.expressions.ILikeAny.key", "modulename": "sqlglot.expressions", "qualname": "ILikeAny.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'ilikeany'"}, "sqlglot.expressions.IntDiv": {"fullname": "sqlglot.expressions.IntDiv", "modulename": "sqlglot.expressions", "qualname": "IntDiv", "kind": "class", "doc": "<p></p>\n", "bases": "Binary"}, "sqlglot.expressions.IntDiv.key": {"fullname": "sqlglot.expressions.IntDiv.key", "modulename": "sqlglot.expressions", "qualname": "IntDiv.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'intdiv'"}, "sqlglot.expressions.Is": {"fullname": "sqlglot.expressions.Is", "modulename": "sqlglot.expressions", "qualname": "Is", "kind": "class", "doc": "<p></p>\n", "bases": "Binary, Predicate"}, "sqlglot.expressions.Is.key": {"fullname": "sqlglot.expressions.Is.key", "modulename": "sqlglot.expressions", "qualname": "Is.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'is'"}, "sqlglot.expressions.Kwarg": {"fullname": "sqlglot.expressions.Kwarg", "modulename": "sqlglot.expressions", "qualname": "Kwarg", "kind": "class", "doc": "<p>Kwarg in special functions like func(kwarg => y).</p>\n", "bases": "Binary"}, "sqlglot.expressions.Kwarg.key": {"fullname": "sqlglot.expressions.Kwarg.key", "modulename": "sqlglot.expressions", "qualname": "Kwarg.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'kwarg'"}, "sqlglot.expressions.Like": {"fullname": "sqlglot.expressions.Like", "modulename": "sqlglot.expressions", "qualname": "Like", "kind": "class", "doc": "<p></p>\n", "bases": "Binary, Predicate"}, "sqlglot.expressions.Like.key": {"fullname": "sqlglot.expressions.Like.key", "modulename": "sqlglot.expressions", "qualname": "Like.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'like'"}, "sqlglot.expressions.LikeAny": {"fullname": "sqlglot.expressions.LikeAny", "modulename": "sqlglot.expressions", "qualname": "LikeAny", "kind": "class", "doc": "<p></p>\n", "bases": "Binary, Predicate"}, "sqlglot.expressions.LikeAny.key": {"fullname": "sqlglot.expressions.LikeAny.key", "modulename": "sqlglot.expressions", "qualname": "LikeAny.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'likeany'"}, "sqlglot.expressions.LT": {"fullname": "sqlglot.expressions.LT", "modulename": "sqlglot.expressions", "qualname": "LT", "kind": "class", "doc": "<p></p>\n", "bases": "Binary, Predicate"}, "sqlglot.expressions.LT.key": {"fullname": "sqlglot.expressions.LT.key", "modulename": "sqlglot.expressions", "qualname": "LT.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'lt'"}, "sqlglot.expressions.LTE": {"fullname": "sqlglot.expressions.LTE", "modulename": "sqlglot.expressions", "qualname": "LTE", "kind": "class", "doc": "<p></p>\n", "bases": "Binary, Predicate"}, "sqlglot.expressions.LTE.key": {"fullname": "sqlglot.expressions.LTE.key", "modulename": "sqlglot.expressions", "qualname": "LTE.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'lte'"}, "sqlglot.expressions.Mod": {"fullname": "sqlglot.expressions.Mod", "modulename": "sqlglot.expressions", "qualname": "Mod", "kind": "class", "doc": "<p></p>\n", "bases": "Binary"}, "sqlglot.expressions.Mod.key": {"fullname": "sqlglot.expressions.Mod.key", "modulename": "sqlglot.expressions", "qualname": "Mod.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'mod'"}, "sqlglot.expressions.Mul": {"fullname": "sqlglot.expressions.Mul", "modulename": "sqlglot.expressions", "qualname": "Mul", "kind": "class", "doc": "<p></p>\n", "bases": "Binary"}, "sqlglot.expressions.Mul.key": {"fullname": "sqlglot.expressions.Mul.key", "modulename": "sqlglot.expressions", "qualname": "Mul.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'mul'"}, "sqlglot.expressions.NEQ": {"fullname": "sqlglot.expressions.NEQ", "modulename": "sqlglot.expressions", "qualname": "NEQ", "kind": "class", "doc": "<p></p>\n", "bases": "Binary, Predicate"}, "sqlglot.expressions.NEQ.key": {"fullname": "sqlglot.expressions.NEQ.key", "modulename": "sqlglot.expressions", "qualname": "NEQ.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'neq'"}, "sqlglot.expressions.Operator": {"fullname": "sqlglot.expressions.Operator", "modulename": "sqlglot.expressions", "qualname": "Operator", "kind": "class", "doc": "<p></p>\n", "bases": "Binary"}, "sqlglot.expressions.Operator.arg_types": {"fullname": "sqlglot.expressions.Operator.arg_types", "modulename": "sqlglot.expressions", "qualname": "Operator.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'operator': True, 'expression': True}"}, "sqlglot.expressions.Operator.key": {"fullname": "sqlglot.expressions.Operator.key", "modulename": "sqlglot.expressions", "qualname": "Operator.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'operator'"}, "sqlglot.expressions.SimilarTo": {"fullname": "sqlglot.expressions.SimilarTo", "modulename": "sqlglot.expressions", "qualname": "SimilarTo", "kind": "class", "doc": "<p></p>\n", "bases": "Binary, Predicate"}, "sqlglot.expressions.SimilarTo.key": {"fullname": "sqlglot.expressions.SimilarTo.key", "modulename": "sqlglot.expressions", "qualname": "SimilarTo.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'similarto'"}, "sqlglot.expressions.Slice": {"fullname": "sqlglot.expressions.Slice", "modulename": "sqlglot.expressions", "qualname": "Slice", "kind": "class", "doc": "<p></p>\n", "bases": "Binary"}, "sqlglot.expressions.Slice.arg_types": {"fullname": "sqlglot.expressions.Slice.arg_types", "modulename": "sqlglot.expressions", "qualname": "Slice.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False, 'expression': False}"}, "sqlglot.expressions.Slice.key": {"fullname": "sqlglot.expressions.Slice.key", "modulename": "sqlglot.expressions", "qualname": "Slice.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'slice'"}, "sqlglot.expressions.Sub": {"fullname": "sqlglot.expressions.Sub", "modulename": "sqlglot.expressions", "qualname": "Sub", "kind": "class", "doc": "<p></p>\n", "bases": "Binary"}, "sqlglot.expressions.Sub.key": {"fullname": "sqlglot.expressions.Sub.key", "modulename": "sqlglot.expressions", "qualname": "Sub.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'sub'"}, "sqlglot.expressions.Unary": {"fullname": "sqlglot.expressions.Unary", "modulename": "sqlglot.expressions", "qualname": "Unary", "kind": "class", "doc": "<p></p>\n", "bases": "Condition"}, "sqlglot.expressions.Unary.key": {"fullname": "sqlglot.expressions.Unary.key", "modulename": "sqlglot.expressions", "qualname": "Unary.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'unary'"}, "sqlglot.expressions.BitwiseNot": {"fullname": "sqlglot.expressions.BitwiseNot", "modulename": "sqlglot.expressions", "qualname": "BitwiseNot", "kind": "class", "doc": "<p></p>\n", "bases": "Unary"}, "sqlglot.expressions.BitwiseNot.key": {"fullname": "sqlglot.expressions.BitwiseNot.key", "modulename": "sqlglot.expressions", "qualname": "BitwiseNot.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'bitwisenot'"}, "sqlglot.expressions.Not": {"fullname": "sqlglot.expressions.Not", "modulename": "sqlglot.expressions", "qualname": "Not", "kind": "class", "doc": "<p></p>\n", "bases": "Unary"}, "sqlglot.expressions.Not.key": {"fullname": "sqlglot.expressions.Not.key", "modulename": "sqlglot.expressions", "qualname": "Not.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'not'"}, "sqlglot.expressions.Paren": {"fullname": "sqlglot.expressions.Paren", "modulename": "sqlglot.expressions", "qualname": "Paren", "kind": "class", "doc": "<p></p>\n", "bases": "Unary"}, "sqlglot.expressions.Paren.output_name": {"fullname": "sqlglot.expressions.Paren.output_name", "modulename": "sqlglot.expressions", "qualname": "Paren.output_name", "kind": "variable", "doc": "<p>Name of the output column if this expression is a selection.</p>\n\n<p>If the Expression has no output name, an empty string is returned.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">parse_one</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT a"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'a'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT b AS c"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'c'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT 1 + 2"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">''</span>\n</code></pre>\n </div>\n</blockquote>\n", "annotation": ": str"}, "sqlglot.expressions.Paren.key": {"fullname": "sqlglot.expressions.Paren.key", "modulename": "sqlglot.expressions", "qualname": "Paren.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'paren'"}, "sqlglot.expressions.Neg": {"fullname": "sqlglot.expressions.Neg", "modulename": "sqlglot.expressions", "qualname": "Neg", "kind": "class", "doc": "<p></p>\n", "bases": "Unary"}, "sqlglot.expressions.Neg.key": {"fullname": "sqlglot.expressions.Neg.key", "modulename": "sqlglot.expressions", "qualname": "Neg.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'neg'"}, "sqlglot.expressions.Alias": {"fullname": "sqlglot.expressions.Alias", "modulename": "sqlglot.expressions", "qualname": "Alias", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Alias.arg_types": {"fullname": "sqlglot.expressions.Alias.arg_types", "modulename": "sqlglot.expressions", "qualname": "Alias.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'alias': False}"}, "sqlglot.expressions.Alias.output_name": {"fullname": "sqlglot.expressions.Alias.output_name", "modulename": "sqlglot.expressions", "qualname": "Alias.output_name", "kind": "variable", "doc": "<p>Name of the output column if this expression is a selection.</p>\n\n<p>If the Expression has no output name, an empty string is returned.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">parse_one</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT a"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'a'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT b AS c"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'c'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT 1 + 2"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">''</span>\n</code></pre>\n </div>\n</blockquote>\n", "annotation": ": str"}, "sqlglot.expressions.Alias.key": {"fullname": "sqlglot.expressions.Alias.key", "modulename": "sqlglot.expressions", "qualname": "Alias.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'alias'"}, "sqlglot.expressions.PivotAlias": {"fullname": "sqlglot.expressions.PivotAlias", "modulename": "sqlglot.expressions", "qualname": "PivotAlias", "kind": "class", "doc": "<p></p>\n", "bases": "Alias"}, "sqlglot.expressions.PivotAlias.key": {"fullname": "sqlglot.expressions.PivotAlias.key", "modulename": "sqlglot.expressions", "qualname": "PivotAlias.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'pivotalias'"}, "sqlglot.expressions.Aliases": {"fullname": "sqlglot.expressions.Aliases", "modulename": "sqlglot.expressions", "qualname": "Aliases", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Aliases.arg_types": {"fullname": "sqlglot.expressions.Aliases.arg_types", "modulename": "sqlglot.expressions", "qualname": "Aliases.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expressions': True}"}, "sqlglot.expressions.Aliases.aliases": {"fullname": "sqlglot.expressions.Aliases.aliases", "modulename": "sqlglot.expressions", "qualname": "Aliases.aliases", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.expressions.Aliases.key": {"fullname": "sqlglot.expressions.Aliases.key", "modulename": "sqlglot.expressions", "qualname": "Aliases.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'aliases'"}, "sqlglot.expressions.AtIndex": {"fullname": "sqlglot.expressions.AtIndex", "modulename": "sqlglot.expressions", "qualname": "AtIndex", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.AtIndex.arg_types": {"fullname": "sqlglot.expressions.AtIndex.arg_types", "modulename": "sqlglot.expressions", "qualname": "AtIndex.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': True}"}, "sqlglot.expressions.AtIndex.key": {"fullname": "sqlglot.expressions.AtIndex.key", "modulename": "sqlglot.expressions", "qualname": "AtIndex.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'atindex'"}, "sqlglot.expressions.AtTimeZone": {"fullname": "sqlglot.expressions.AtTimeZone", "modulename": "sqlglot.expressions", "qualname": "AtTimeZone", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.AtTimeZone.arg_types": {"fullname": "sqlglot.expressions.AtTimeZone.arg_types", "modulename": "sqlglot.expressions", "qualname": "AtTimeZone.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'zone': True}"}, "sqlglot.expressions.AtTimeZone.key": {"fullname": "sqlglot.expressions.AtTimeZone.key", "modulename": "sqlglot.expressions", "qualname": "AtTimeZone.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'attimezone'"}, "sqlglot.expressions.FromTimeZone": {"fullname": "sqlglot.expressions.FromTimeZone", "modulename": "sqlglot.expressions", "qualname": "FromTimeZone", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.FromTimeZone.arg_types": {"fullname": "sqlglot.expressions.FromTimeZone.arg_types", "modulename": "sqlglot.expressions", "qualname": "FromTimeZone.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'zone': True}"}, "sqlglot.expressions.FromTimeZone.key": {"fullname": "sqlglot.expressions.FromTimeZone.key", "modulename": "sqlglot.expressions", "qualname": "FromTimeZone.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'fromtimezone'"}, "sqlglot.expressions.Between": {"fullname": "sqlglot.expressions.Between", "modulename": "sqlglot.expressions", "qualname": "Between", "kind": "class", "doc": "<p></p>\n", "bases": "Predicate"}, "sqlglot.expressions.Between.arg_types": {"fullname": "sqlglot.expressions.Between.arg_types", "modulename": "sqlglot.expressions", "qualname": "Between.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'low': True, 'high': True}"}, "sqlglot.expressions.Between.key": {"fullname": "sqlglot.expressions.Between.key", "modulename": "sqlglot.expressions", "qualname": "Between.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'between'"}, "sqlglot.expressions.Bracket": {"fullname": "sqlglot.expressions.Bracket", "modulename": "sqlglot.expressions", "qualname": "Bracket", "kind": "class", "doc": "<p></p>\n", "bases": "Condition"}, "sqlglot.expressions.Bracket.arg_types": {"fullname": "sqlglot.expressions.Bracket.arg_types", "modulename": "sqlglot.expressions", "qualname": "Bracket.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expressions': True, 'offset': False, 'safe': False, 'returns_list_for_maps': False}"}, "sqlglot.expressions.Bracket.output_name": {"fullname": "sqlglot.expressions.Bracket.output_name", "modulename": "sqlglot.expressions", "qualname": "Bracket.output_name", "kind": "variable", "doc": "<p>Name of the output column if this expression is a selection.</p>\n\n<p>If the Expression has no output name, an empty string is returned.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">parse_one</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT a"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'a'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT b AS c"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'c'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT 1 + 2"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">''</span>\n</code></pre>\n </div>\n</blockquote>\n", "annotation": ": str"}, "sqlglot.expressions.Bracket.key": {"fullname": "sqlglot.expressions.Bracket.key", "modulename": "sqlglot.expressions", "qualname": "Bracket.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'bracket'"}, "sqlglot.expressions.Distinct": {"fullname": "sqlglot.expressions.Distinct", "modulename": "sqlglot.expressions", "qualname": "Distinct", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Distinct.arg_types": {"fullname": "sqlglot.expressions.Distinct.arg_types", "modulename": "sqlglot.expressions", "qualname": "Distinct.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'expressions': False, 'on': False}"}, "sqlglot.expressions.Distinct.key": {"fullname": "sqlglot.expressions.Distinct.key", "modulename": "sqlglot.expressions", "qualname": "Distinct.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'distinct'"}, "sqlglot.expressions.In": {"fullname": "sqlglot.expressions.In", "modulename": "sqlglot.expressions", "qualname": "In", "kind": "class", "doc": "<p></p>\n", "bases": "Predicate"}, "sqlglot.expressions.In.arg_types": {"fullname": "sqlglot.expressions.In.arg_types", "modulename": "sqlglot.expressions", "qualname": "In.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expressions': False, 'query': False, 'unnest': False, 'field': False, 'is_global': False}"}, "sqlglot.expressions.In.key": {"fullname": "sqlglot.expressions.In.key", "modulename": "sqlglot.expressions", "qualname": "In.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'in'"}, "sqlglot.expressions.ForIn": {"fullname": "sqlglot.expressions.ForIn", "modulename": "sqlglot.expressions", "qualname": "ForIn", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.ForIn.arg_types": {"fullname": "sqlglot.expressions.ForIn.arg_types", "modulename": "sqlglot.expressions", "qualname": "ForIn.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': True}"}, "sqlglot.expressions.ForIn.key": {"fullname": "sqlglot.expressions.ForIn.key", "modulename": "sqlglot.expressions", "qualname": "ForIn.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'forin'"}, "sqlglot.expressions.TimeUnit": {"fullname": "sqlglot.expressions.TimeUnit", "modulename": "sqlglot.expressions", "qualname": "TimeUnit", "kind": "class", "doc": "<p>Automatically converts unit arg into a var.</p>\n", "bases": "Expression"}, "sqlglot.expressions.TimeUnit.__init__": {"fullname": "sqlglot.expressions.TimeUnit.__init__", "modulename": "sqlglot.expressions", "qualname": "TimeUnit.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"o\">**</span><span class=\"n\">args</span></span>)</span>"}, "sqlglot.expressions.TimeUnit.arg_types": {"fullname": "sqlglot.expressions.TimeUnit.arg_types", "modulename": "sqlglot.expressions", "qualname": "TimeUnit.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'unit': False}"}, "sqlglot.expressions.TimeUnit.UNABBREVIATED_UNIT_NAME": {"fullname": "sqlglot.expressions.TimeUnit.UNABBREVIATED_UNIT_NAME", "modulename": "sqlglot.expressions", "qualname": "TimeUnit.UNABBREVIATED_UNIT_NAME", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'D': 'DAY', 'H': 'HOUR', 'M': 'MINUTE', 'MS': 'MILLISECOND', 'NS': 'NANOSECOND', 'Q': 'QUARTER', 'S': 'SECOND', 'US': 'MICROSECOND', 'W': 'WEEK', 'Y': 'YEAR'}"}, "sqlglot.expressions.TimeUnit.VAR_LIKE": {"fullname": "sqlglot.expressions.TimeUnit.VAR_LIKE", "modulename": "sqlglot.expressions", "qualname": "TimeUnit.VAR_LIKE", "kind": "variable", "doc": "<p></p>\n", "default_value": "(<class 'sqlglot.expressions.Column'>, <class 'sqlglot.expressions.Literal'>, <class 'sqlglot.expressions.Var'>)"}, "sqlglot.expressions.TimeUnit.unit": {"fullname": "sqlglot.expressions.TimeUnit.unit", "modulename": "sqlglot.expressions", "qualname": "TimeUnit.unit", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Union[sqlglot.expressions.Var, sqlglot.expressions.IntervalSpan, NoneType]"}, "sqlglot.expressions.TimeUnit.key": {"fullname": "sqlglot.expressions.TimeUnit.key", "modulename": "sqlglot.expressions", "qualname": "TimeUnit.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'timeunit'"}, "sqlglot.expressions.IntervalOp": {"fullname": "sqlglot.expressions.IntervalOp", "modulename": "sqlglot.expressions", "qualname": "IntervalOp", "kind": "class", "doc": "<p></p>\n", "bases": "TimeUnit"}, "sqlglot.expressions.IntervalOp.arg_types": {"fullname": "sqlglot.expressions.IntervalOp.arg_types", "modulename": "sqlglot.expressions", "qualname": "IntervalOp.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'unit': True, 'expression': True}"}, "sqlglot.expressions.IntervalOp.interval": {"fullname": "sqlglot.expressions.IntervalOp.interval", "modulename": "sqlglot.expressions", "qualname": "IntervalOp.interval", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.expressions.IntervalOp.key": {"fullname": "sqlglot.expressions.IntervalOp.key", "modulename": "sqlglot.expressions", "qualname": "IntervalOp.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'intervalop'"}, "sqlglot.expressions.IntervalSpan": {"fullname": "sqlglot.expressions.IntervalSpan", "modulename": "sqlglot.expressions", "qualname": "IntervalSpan", "kind": "class", "doc": "<p></p>\n", "bases": "DataType"}, "sqlglot.expressions.IntervalSpan.arg_types": {"fullname": "sqlglot.expressions.IntervalSpan.arg_types", "modulename": "sqlglot.expressions", "qualname": "IntervalSpan.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': True}"}, "sqlglot.expressions.IntervalSpan.key": {"fullname": "sqlglot.expressions.IntervalSpan.key", "modulename": "sqlglot.expressions", "qualname": "IntervalSpan.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'intervalspan'"}, "sqlglot.expressions.Interval": {"fullname": "sqlglot.expressions.Interval", "modulename": "sqlglot.expressions", "qualname": "Interval", "kind": "class", "doc": "<p></p>\n", "bases": "TimeUnit"}, "sqlglot.expressions.Interval.arg_types": {"fullname": "sqlglot.expressions.Interval.arg_types", "modulename": "sqlglot.expressions", "qualname": "Interval.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False, 'unit': False}"}, "sqlglot.expressions.Interval.key": {"fullname": "sqlglot.expressions.Interval.key", "modulename": "sqlglot.expressions", "qualname": "Interval.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'interval'"}, "sqlglot.expressions.IgnoreNulls": {"fullname": "sqlglot.expressions.IgnoreNulls", "modulename": "sqlglot.expressions", "qualname": "IgnoreNulls", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.IgnoreNulls.key": {"fullname": "sqlglot.expressions.IgnoreNulls.key", "modulename": "sqlglot.expressions", "qualname": "IgnoreNulls.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'ignorenulls'"}, "sqlglot.expressions.RespectNulls": {"fullname": "sqlglot.expressions.RespectNulls", "modulename": "sqlglot.expressions", "qualname": "RespectNulls", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.RespectNulls.key": {"fullname": "sqlglot.expressions.RespectNulls.key", "modulename": "sqlglot.expressions", "qualname": "RespectNulls.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'respectnulls'"}, "sqlglot.expressions.HavingMax": {"fullname": "sqlglot.expressions.HavingMax", "modulename": "sqlglot.expressions", "qualname": "HavingMax", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.HavingMax.arg_types": {"fullname": "sqlglot.expressions.HavingMax.arg_types", "modulename": "sqlglot.expressions", "qualname": "HavingMax.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': True, 'max': True}"}, "sqlglot.expressions.HavingMax.key": {"fullname": "sqlglot.expressions.HavingMax.key", "modulename": "sqlglot.expressions", "qualname": "HavingMax.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'havingmax'"}, "sqlglot.expressions.Func": {"fullname": "sqlglot.expressions.Func", "modulename": "sqlglot.expressions", "qualname": "Func", "kind": "class", "doc": "<p>The base class for all function expressions.</p>\n\n<h6 id=\"attributes\">Attributes:</h6>\n\n<ul>\n<li><strong>is_var_len_args (bool):</strong> if set to True the last argument defined in arg_types will be\ntreated as a variable length argument and the argument's value will be stored as a list.</li>\n<li><strong>_sql_names (list):</strong> the SQL name (1st item in the list) and aliases (subsequent items) for this\nfunction expression. These values are used to map this node to a name during parsing as\nwell as to provide the function's name during SQL string generation. By default the SQL\nname is set to the expression's class name transformed to snake case.</li>\n</ul>\n", "bases": "Condition"}, "sqlglot.expressions.Func.is_var_len_args": {"fullname": "sqlglot.expressions.Func.is_var_len_args", "modulename": "sqlglot.expressions", "qualname": "Func.is_var_len_args", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.expressions.Func.from_arg_list": {"fullname": "sqlglot.expressions.Func.from_arg_list", "modulename": "sqlglot.expressions", "qualname": "Func.from_arg_list", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">cls</span>, </span><span class=\"param\"><span class=\"n\">args</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.expressions.Func.sql_names": {"fullname": "sqlglot.expressions.Func.sql_names", "modulename": "sqlglot.expressions", "qualname": "Func.sql_names", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">cls</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.expressions.Func.sql_name": {"fullname": "sqlglot.expressions.Func.sql_name", "modulename": "sqlglot.expressions", "qualname": "Func.sql_name", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">cls</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.expressions.Func.default_parser_mappings": {"fullname": "sqlglot.expressions.Func.default_parser_mappings", "modulename": "sqlglot.expressions", "qualname": "Func.default_parser_mappings", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">cls</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.expressions.Func.key": {"fullname": "sqlglot.expressions.Func.key", "modulename": "sqlglot.expressions", "qualname": "Func.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'func'"}, "sqlglot.expressions.AggFunc": {"fullname": "sqlglot.expressions.AggFunc", "modulename": "sqlglot.expressions", "qualname": "AggFunc", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.AggFunc.key": {"fullname": "sqlglot.expressions.AggFunc.key", "modulename": "sqlglot.expressions", "qualname": "AggFunc.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'aggfunc'"}, "sqlglot.expressions.ParameterizedAgg": {"fullname": "sqlglot.expressions.ParameterizedAgg", "modulename": "sqlglot.expressions", "qualname": "ParameterizedAgg", "kind": "class", "doc": "<p></p>\n", "bases": "AggFunc"}, "sqlglot.expressions.ParameterizedAgg.arg_types": {"fullname": "sqlglot.expressions.ParameterizedAgg.arg_types", "modulename": "sqlglot.expressions", "qualname": "ParameterizedAgg.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expressions': True, 'params': True}"}, "sqlglot.expressions.ParameterizedAgg.key": {"fullname": "sqlglot.expressions.ParameterizedAgg.key", "modulename": "sqlglot.expressions", "qualname": "ParameterizedAgg.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'parameterizedagg'"}, "sqlglot.expressions.Abs": {"fullname": "sqlglot.expressions.Abs", "modulename": "sqlglot.expressions", "qualname": "Abs", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.Abs.key": {"fullname": "sqlglot.expressions.Abs.key", "modulename": "sqlglot.expressions", "qualname": "Abs.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'abs'"}, "sqlglot.expressions.ArgMax": {"fullname": "sqlglot.expressions.ArgMax", "modulename": "sqlglot.expressions", "qualname": "ArgMax", "kind": "class", "doc": "<p></p>\n", "bases": "AggFunc"}, "sqlglot.expressions.ArgMax.arg_types": {"fullname": "sqlglot.expressions.ArgMax.arg_types", "modulename": "sqlglot.expressions", "qualname": "ArgMax.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': True, 'count': False}"}, "sqlglot.expressions.ArgMax.key": {"fullname": "sqlglot.expressions.ArgMax.key", "modulename": "sqlglot.expressions", "qualname": "ArgMax.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'argmax'"}, "sqlglot.expressions.ArgMin": {"fullname": "sqlglot.expressions.ArgMin", "modulename": "sqlglot.expressions", "qualname": "ArgMin", "kind": "class", "doc": "<p></p>\n", "bases": "AggFunc"}, "sqlglot.expressions.ArgMin.arg_types": {"fullname": "sqlglot.expressions.ArgMin.arg_types", "modulename": "sqlglot.expressions", "qualname": "ArgMin.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': True, 'count': False}"}, "sqlglot.expressions.ArgMin.key": {"fullname": "sqlglot.expressions.ArgMin.key", "modulename": "sqlglot.expressions", "qualname": "ArgMin.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'argmin'"}, "sqlglot.expressions.ApproxTopK": {"fullname": "sqlglot.expressions.ApproxTopK", "modulename": "sqlglot.expressions", "qualname": "ApproxTopK", "kind": "class", "doc": "<p></p>\n", "bases": "AggFunc"}, "sqlglot.expressions.ApproxTopK.arg_types": {"fullname": "sqlglot.expressions.ApproxTopK.arg_types", "modulename": "sqlglot.expressions", "qualname": "ApproxTopK.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': False, 'counters': False}"}, "sqlglot.expressions.ApproxTopK.key": {"fullname": "sqlglot.expressions.ApproxTopK.key", "modulename": "sqlglot.expressions", "qualname": "ApproxTopK.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'approxtopk'"}, "sqlglot.expressions.Flatten": {"fullname": "sqlglot.expressions.Flatten", "modulename": "sqlglot.expressions", "qualname": "Flatten", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.Flatten.key": {"fullname": "sqlglot.expressions.Flatten.key", "modulename": "sqlglot.expressions", "qualname": "Flatten.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'flatten'"}, "sqlglot.expressions.Transform": {"fullname": "sqlglot.expressions.Transform", "modulename": "sqlglot.expressions", "qualname": "Transform", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.Transform.arg_types": {"fullname": "sqlglot.expressions.Transform.arg_types", "modulename": "sqlglot.expressions", "qualname": "Transform.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': True}"}, "sqlglot.expressions.Transform.key": {"fullname": "sqlglot.expressions.Transform.key", "modulename": "sqlglot.expressions", "qualname": "Transform.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'transform'"}, "sqlglot.expressions.Anonymous": {"fullname": "sqlglot.expressions.Anonymous", "modulename": "sqlglot.expressions", "qualname": "Anonymous", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.Anonymous.arg_types": {"fullname": "sqlglot.expressions.Anonymous.arg_types", "modulename": "sqlglot.expressions", "qualname": "Anonymous.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expressions': False}"}, "sqlglot.expressions.Anonymous.is_var_len_args": {"fullname": "sqlglot.expressions.Anonymous.is_var_len_args", "modulename": "sqlglot.expressions", "qualname": "Anonymous.is_var_len_args", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.expressions.Anonymous.name": {"fullname": "sqlglot.expressions.Anonymous.name", "modulename": "sqlglot.expressions", "qualname": "Anonymous.name", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.expressions.Anonymous.key": {"fullname": "sqlglot.expressions.Anonymous.key", "modulename": "sqlglot.expressions", "qualname": "Anonymous.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'anonymous'"}, "sqlglot.expressions.AnonymousAggFunc": {"fullname": "sqlglot.expressions.AnonymousAggFunc", "modulename": "sqlglot.expressions", "qualname": "AnonymousAggFunc", "kind": "class", "doc": "<p></p>\n", "bases": "AggFunc"}, "sqlglot.expressions.AnonymousAggFunc.arg_types": {"fullname": "sqlglot.expressions.AnonymousAggFunc.arg_types", "modulename": "sqlglot.expressions", "qualname": "AnonymousAggFunc.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expressions': False}"}, "sqlglot.expressions.AnonymousAggFunc.is_var_len_args": {"fullname": "sqlglot.expressions.AnonymousAggFunc.is_var_len_args", "modulename": "sqlglot.expressions", "qualname": "AnonymousAggFunc.is_var_len_args", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.expressions.AnonymousAggFunc.key": {"fullname": "sqlglot.expressions.AnonymousAggFunc.key", "modulename": "sqlglot.expressions", "qualname": "AnonymousAggFunc.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'anonymousaggfunc'"}, "sqlglot.expressions.CombinedAggFunc": {"fullname": "sqlglot.expressions.CombinedAggFunc", "modulename": "sqlglot.expressions", "qualname": "CombinedAggFunc", "kind": "class", "doc": "<p></p>\n", "bases": "AnonymousAggFunc"}, "sqlglot.expressions.CombinedAggFunc.arg_types": {"fullname": "sqlglot.expressions.CombinedAggFunc.arg_types", "modulename": "sqlglot.expressions", "qualname": "CombinedAggFunc.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expressions': False, 'parts': True}"}, "sqlglot.expressions.CombinedAggFunc.key": {"fullname": "sqlglot.expressions.CombinedAggFunc.key", "modulename": "sqlglot.expressions", "qualname": "CombinedAggFunc.key", "kind": "variable", 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"qualname": "LastValue", "kind": "class", "doc": "<p></p>\n", "bases": "AggFunc"}, "sqlglot.expressions.LastValue.key": {"fullname": "sqlglot.expressions.LastValue.key", "modulename": "sqlglot.expressions", "qualname": "LastValue.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'lastvalue'"}, "sqlglot.expressions.NthValue": {"fullname": "sqlglot.expressions.NthValue", "modulename": "sqlglot.expressions", "qualname": "NthValue", "kind": "class", "doc": "<p></p>\n", "bases": "AggFunc"}, "sqlglot.expressions.NthValue.arg_types": {"fullname": "sqlglot.expressions.NthValue.arg_types", "modulename": "sqlglot.expressions", "qualname": "NthValue.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'offset': True}"}, "sqlglot.expressions.NthValue.key": {"fullname": "sqlglot.expressions.NthValue.key", "modulename": "sqlglot.expressions", "qualname": "NthValue.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'nthvalue'"}, "sqlglot.expressions.Case": {"fullname": "sqlglot.expressions.Case", "modulename": "sqlglot.expressions", "qualname": "Case", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.Case.arg_types": {"fullname": "sqlglot.expressions.Case.arg_types", "modulename": "sqlglot.expressions", "qualname": "Case.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False, 'ifs': True, 'default': False}"}, "sqlglot.expressions.Case.when": {"fullname": "sqlglot.expressions.Case.when", "modulename": "sqlglot.expressions", "qualname": "Case.when", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">condition</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">then</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Case</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Case.else_": {"fullname": "sqlglot.expressions.Case.else_", "modulename": "sqlglot.expressions", "qualname": "Case.else_", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">condition</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Case</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Case.key": {"fullname": "sqlglot.expressions.Case.key", "modulename": "sqlglot.expressions", "qualname": "Case.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'case'"}, "sqlglot.expressions.Cast": {"fullname": "sqlglot.expressions.Cast", "modulename": "sqlglot.expressions", "qualname": "Cast", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.Cast.arg_types": {"fullname": "sqlglot.expressions.Cast.arg_types", "modulename": "sqlglot.expressions", "qualname": "Cast.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'to': True, 'format': False, 'safe': False, 'action': False}"}, "sqlglot.expressions.Cast.name": {"fullname": "sqlglot.expressions.Cast.name", "modulename": "sqlglot.expressions", "qualname": "Cast.name", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.expressions.Cast.to": {"fullname": "sqlglot.expressions.Cast.to", "modulename": "sqlglot.expressions", "qualname": "Cast.to", "kind": "variable", "doc": "<p></p>\n", "annotation": ": sqlglot.expressions.DataType"}, "sqlglot.expressions.Cast.output_name": {"fullname": "sqlglot.expressions.Cast.output_name", "modulename": "sqlglot.expressions", "qualname": "Cast.output_name", "kind": "variable", "doc": "<p>Name of the output column if this expression is a selection.</p>\n\n<p>If the Expression has no output name, an empty string is returned.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">parse_one</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT a"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'a'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT b AS c"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'c'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT 1 + 2"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">''</span>\n</code></pre>\n </div>\n</blockquote>\n", "annotation": ": str"}, "sqlglot.expressions.Cast.is_type": {"fullname": "sqlglot.expressions.Cast.is_type", "modulename": "sqlglot.expressions", "qualname": "Cast.is_type", "kind": "function", "doc": "<p>Checks whether this Cast's DataType matches one of the provided data types. Nested types\nlike arrays or structs will be compared using \"structural equivalence\" semantics, so e.g.\narray<int> != array<float>.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>dtypes:</strong> the data types to compare this Cast's DataType to.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>True, if and only if there is a type in <code>dtypes</code> which is equal to this Cast's DataType.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">dtypes</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">bool</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.Cast.key": {"fullname": "sqlglot.expressions.Cast.key", "modulename": "sqlglot.expressions", "qualname": "Cast.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'cast'"}, "sqlglot.expressions.TryCast": {"fullname": "sqlglot.expressions.TryCast", "modulename": "sqlglot.expressions", "qualname": "TryCast", "kind": "class", "doc": "<p></p>\n", "bases": "Cast"}, "sqlglot.expressions.TryCast.key": {"fullname": "sqlglot.expressions.TryCast.key", "modulename": "sqlglot.expressions", "qualname": "TryCast.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'trycast'"}, "sqlglot.expressions.Try": {"fullname": "sqlglot.expressions.Try", "modulename": "sqlglot.expressions", "qualname": "Try", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.Try.key": {"fullname": "sqlglot.expressions.Try.key", "modulename": "sqlglot.expressions", "qualname": "Try.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'try'"}, "sqlglot.expressions.CastToStrType": {"fullname": "sqlglot.expressions.CastToStrType", "modulename": "sqlglot.expressions", "qualname": "CastToStrType", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.CastToStrType.arg_types": {"fullname": "sqlglot.expressions.CastToStrType.arg_types", "modulename": "sqlglot.expressions", "qualname": "CastToStrType.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'to': True}"}, "sqlglot.expressions.CastToStrType.key": {"fullname": "sqlglot.expressions.CastToStrType.key", "modulename": "sqlglot.expressions", "qualname": "CastToStrType.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'casttostrtype'"}, "sqlglot.expressions.Collate": {"fullname": "sqlglot.expressions.Collate", "modulename": "sqlglot.expressions", "qualname": "Collate", "kind": "class", "doc": "<p></p>\n", "bases": "Binary, Func"}, "sqlglot.expressions.Collate.key": {"fullname": "sqlglot.expressions.Collate.key", "modulename": "sqlglot.expressions", "qualname": "Collate.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'collate'"}, "sqlglot.expressions.Ceil": {"fullname": "sqlglot.expressions.Ceil", "modulename": "sqlglot.expressions", "qualname": "Ceil", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.Ceil.arg_types": {"fullname": "sqlglot.expressions.Ceil.arg_types", "modulename": "sqlglot.expressions", "qualname": "Ceil.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'decimals': False}"}, "sqlglot.expressions.Ceil.key": {"fullname": "sqlglot.expressions.Ceil.key", "modulename": "sqlglot.expressions", "qualname": "Ceil.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'ceil'"}, "sqlglot.expressions.Coalesce": {"fullname": "sqlglot.expressions.Coalesce", "modulename": "sqlglot.expressions", "qualname": "Coalesce", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.Coalesce.arg_types": {"fullname": "sqlglot.expressions.Coalesce.arg_types", "modulename": "sqlglot.expressions", "qualname": "Coalesce.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expressions': False}"}, "sqlglot.expressions.Coalesce.is_var_len_args": {"fullname": "sqlglot.expressions.Coalesce.is_var_len_args", "modulename": "sqlglot.expressions", "qualname": "Coalesce.is_var_len_args", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.expressions.Coalesce.key": {"fullname": "sqlglot.expressions.Coalesce.key", "modulename": "sqlglot.expressions", "qualname": "Coalesce.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'coalesce'"}, "sqlglot.expressions.Chr": {"fullname": "sqlglot.expressions.Chr", "modulename": "sqlglot.expressions", "qualname": "Chr", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.Chr.arg_types": {"fullname": "sqlglot.expressions.Chr.arg_types", "modulename": "sqlglot.expressions", "qualname": "Chr.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'charset': False, 'expressions': False}"}, "sqlglot.expressions.Chr.is_var_len_args": {"fullname": "sqlglot.expressions.Chr.is_var_len_args", "modulename": "sqlglot.expressions", "qualname": "Chr.is_var_len_args", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.expressions.Chr.key": {"fullname": "sqlglot.expressions.Chr.key", "modulename": "sqlglot.expressions", "qualname": "Chr.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'chr'"}, "sqlglot.expressions.Concat": {"fullname": "sqlglot.expressions.Concat", "modulename": "sqlglot.expressions", "qualname": "Concat", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.Concat.arg_types": {"fullname": "sqlglot.expressions.Concat.arg_types", "modulename": "sqlglot.expressions", "qualname": "Concat.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'expressions': True, 'safe': False, 'coalesce': False}"}, "sqlglot.expressions.Concat.is_var_len_args": {"fullname": "sqlglot.expressions.Concat.is_var_len_args", "modulename": "sqlglot.expressions", "qualname": "Concat.is_var_len_args", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.expressions.Concat.key": {"fullname": "sqlglot.expressions.Concat.key", "modulename": "sqlglot.expressions", "qualname": "Concat.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'concat'"}, "sqlglot.expressions.ConcatWs": {"fullname": "sqlglot.expressions.ConcatWs", "modulename": "sqlglot.expressions", "qualname": "ConcatWs", "kind": "class", "doc": "<p></p>\n", "bases": "Concat"}, "sqlglot.expressions.ConcatWs.key": {"fullname": "sqlglot.expressions.ConcatWs.key", "modulename": "sqlglot.expressions", "qualname": "ConcatWs.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'concatws'"}, "sqlglot.expressions.ConnectByRoot": {"fullname": "sqlglot.expressions.ConnectByRoot", "modulename": "sqlglot.expressions", "qualname": "ConnectByRoot", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.ConnectByRoot.key": {"fullname": "sqlglot.expressions.ConnectByRoot.key", "modulename": "sqlglot.expressions", "qualname": "ConnectByRoot.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'connectbyroot'"}, "sqlglot.expressions.Count": {"fullname": "sqlglot.expressions.Count", "modulename": "sqlglot.expressions", "qualname": "Count", "kind": "class", "doc": "<p></p>\n", "bases": "AggFunc"}, "sqlglot.expressions.Count.arg_types": {"fullname": "sqlglot.expressions.Count.arg_types", "modulename": "sqlglot.expressions", "qualname": "Count.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False, 'expressions': False}"}, "sqlglot.expressions.Count.is_var_len_args": {"fullname": "sqlglot.expressions.Count.is_var_len_args", "modulename": "sqlglot.expressions", "qualname": "Count.is_var_len_args", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.expressions.Count.key": {"fullname": "sqlglot.expressions.Count.key", "modulename": "sqlglot.expressions", "qualname": "Count.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'count'"}, "sqlglot.expressions.CountIf": {"fullname": "sqlglot.expressions.CountIf", "modulename": "sqlglot.expressions", "qualname": "CountIf", "kind": "class", "doc": "<p></p>\n", "bases": "AggFunc"}, "sqlglot.expressions.CountIf.key": {"fullname": "sqlglot.expressions.CountIf.key", "modulename": "sqlglot.expressions", "qualname": "CountIf.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'countif'"}, "sqlglot.expressions.Cbrt": {"fullname": "sqlglot.expressions.Cbrt", "modulename": "sqlglot.expressions", "qualname": "Cbrt", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.Cbrt.key": {"fullname": "sqlglot.expressions.Cbrt.key", "modulename": "sqlglot.expressions", "qualname": "Cbrt.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'cbrt'"}, "sqlglot.expressions.CurrentDate": {"fullname": "sqlglot.expressions.CurrentDate", "modulename": "sqlglot.expressions", "qualname": "CurrentDate", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.CurrentDate.arg_types": {"fullname": "sqlglot.expressions.CurrentDate.arg_types", "modulename": "sqlglot.expressions", "qualname": "CurrentDate.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False}"}, "sqlglot.expressions.CurrentDate.key": {"fullname": "sqlglot.expressions.CurrentDate.key", "modulename": "sqlglot.expressions", "qualname": "CurrentDate.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'currentdate'"}, "sqlglot.expressions.CurrentDatetime": {"fullname": "sqlglot.expressions.CurrentDatetime", "modulename": "sqlglot.expressions", "qualname": "CurrentDatetime", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.CurrentDatetime.arg_types": {"fullname": "sqlglot.expressions.CurrentDatetime.arg_types", "modulename": "sqlglot.expressions", "qualname": "CurrentDatetime.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False}"}, "sqlglot.expressions.CurrentDatetime.key": {"fullname": "sqlglot.expressions.CurrentDatetime.key", "modulename": "sqlglot.expressions", "qualname": "CurrentDatetime.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'currentdatetime'"}, "sqlglot.expressions.CurrentTime": {"fullname": "sqlglot.expressions.CurrentTime", "modulename": "sqlglot.expressions", "qualname": "CurrentTime", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.CurrentTime.arg_types": {"fullname": "sqlglot.expressions.CurrentTime.arg_types", "modulename": "sqlglot.expressions", "qualname": "CurrentTime.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False}"}, "sqlglot.expressions.CurrentTime.key": {"fullname": "sqlglot.expressions.CurrentTime.key", "modulename": "sqlglot.expressions", "qualname": "CurrentTime.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'currenttime'"}, "sqlglot.expressions.CurrentTimestamp": {"fullname": "sqlglot.expressions.CurrentTimestamp", "modulename": "sqlglot.expressions", "qualname": "CurrentTimestamp", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.CurrentTimestamp.arg_types": {"fullname": "sqlglot.expressions.CurrentTimestamp.arg_types", "modulename": "sqlglot.expressions", "qualname": "CurrentTimestamp.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False, 'transaction': False}"}, "sqlglot.expressions.CurrentTimestamp.key": {"fullname": "sqlglot.expressions.CurrentTimestamp.key", "modulename": "sqlglot.expressions", "qualname": "CurrentTimestamp.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'currenttimestamp'"}, "sqlglot.expressions.CurrentUser": {"fullname": "sqlglot.expressions.CurrentUser", "modulename": "sqlglot.expressions", "qualname": "CurrentUser", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.CurrentUser.arg_types": {"fullname": "sqlglot.expressions.CurrentUser.arg_types", "modulename": "sqlglot.expressions", "qualname": "CurrentUser.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False}"}, "sqlglot.expressions.CurrentUser.key": {"fullname": "sqlglot.expressions.CurrentUser.key", "modulename": "sqlglot.expressions", "qualname": "CurrentUser.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'currentuser'"}, "sqlglot.expressions.DateAdd": {"fullname": "sqlglot.expressions.DateAdd", "modulename": "sqlglot.expressions", "qualname": "DateAdd", "kind": "class", "doc": "<p></p>\n", "bases": "Func, IntervalOp"}, "sqlglot.expressions.DateAdd.arg_types": {"fullname": "sqlglot.expressions.DateAdd.arg_types", "modulename": "sqlglot.expressions", "qualname": "DateAdd.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': True, 'unit': False}"}, "sqlglot.expressions.DateAdd.key": {"fullname": "sqlglot.expressions.DateAdd.key", "modulename": "sqlglot.expressions", "qualname": "DateAdd.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'dateadd'"}, "sqlglot.expressions.DateSub": {"fullname": "sqlglot.expressions.DateSub", "modulename": "sqlglot.expressions", "qualname": "DateSub", "kind": "class", "doc": "<p></p>\n", "bases": "Func, IntervalOp"}, "sqlglot.expressions.DateSub.arg_types": {"fullname": "sqlglot.expressions.DateSub.arg_types", "modulename": "sqlglot.expressions", "qualname": "DateSub.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': True, 'unit': False}"}, "sqlglot.expressions.DateSub.key": {"fullname": "sqlglot.expressions.DateSub.key", "modulename": "sqlglot.expressions", "qualname": "DateSub.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'datesub'"}, "sqlglot.expressions.DateDiff": {"fullname": "sqlglot.expressions.DateDiff", "modulename": "sqlglot.expressions", "qualname": "DateDiff", "kind": "class", "doc": "<p></p>\n", "bases": "Func, TimeUnit"}, "sqlglot.expressions.DateDiff.arg_types": {"fullname": "sqlglot.expressions.DateDiff.arg_types", "modulename": "sqlglot.expressions", "qualname": "DateDiff.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': True, 'unit': False}"}, 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"doc": "<p></p>\n", "default_value": "{'this': True, 'charset': True}"}, "sqlglot.expressions.Encode.key": {"fullname": "sqlglot.expressions.Encode.key", "modulename": "sqlglot.expressions", "qualname": "Encode.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'encode'"}, "sqlglot.expressions.Exp": {"fullname": "sqlglot.expressions.Exp", "modulename": "sqlglot.expressions", "qualname": "Exp", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.Exp.key": {"fullname": "sqlglot.expressions.Exp.key", "modulename": "sqlglot.expressions", "qualname": "Exp.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'exp'"}, "sqlglot.expressions.Explode": {"fullname": "sqlglot.expressions.Explode", "modulename": "sqlglot.expressions", "qualname": "Explode", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.Explode.arg_types": {"fullname": "sqlglot.expressions.Explode.arg_types", "modulename": "sqlglot.expressions", "qualname": "Explode.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expressions': False}"}, "sqlglot.expressions.Explode.is_var_len_args": {"fullname": "sqlglot.expressions.Explode.is_var_len_args", "modulename": "sqlglot.expressions", "qualname": "Explode.is_var_len_args", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.expressions.Explode.key": {"fullname": "sqlglot.expressions.Explode.key", "modulename": "sqlglot.expressions", "qualname": "Explode.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'explode'"}, "sqlglot.expressions.ExplodeOuter": {"fullname": "sqlglot.expressions.ExplodeOuter", "modulename": "sqlglot.expressions", "qualname": "ExplodeOuter", "kind": "class", "doc": "<p></p>\n", "bases": "Explode"}, "sqlglot.expressions.ExplodeOuter.key": {"fullname": "sqlglot.expressions.ExplodeOuter.key", "modulename": "sqlglot.expressions", "qualname": "ExplodeOuter.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'explodeouter'"}, "sqlglot.expressions.Posexplode": {"fullname": "sqlglot.expressions.Posexplode", "modulename": "sqlglot.expressions", "qualname": "Posexplode", "kind": "class", "doc": "<p></p>\n", "bases": "Explode"}, "sqlglot.expressions.Posexplode.key": {"fullname": "sqlglot.expressions.Posexplode.key", "modulename": "sqlglot.expressions", "qualname": "Posexplode.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'posexplode'"}, "sqlglot.expressions.PosexplodeOuter": {"fullname": "sqlglot.expressions.PosexplodeOuter", "modulename": "sqlglot.expressions", "qualname": "PosexplodeOuter", "kind": "class", "doc": "<p></p>\n", "bases": "Posexplode, ExplodeOuter"}, "sqlglot.expressions.PosexplodeOuter.key": {"fullname": "sqlglot.expressions.PosexplodeOuter.key", "modulename": "sqlglot.expressions", "qualname": "PosexplodeOuter.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'posexplodeouter'"}, "sqlglot.expressions.Floor": {"fullname": "sqlglot.expressions.Floor", "modulename": "sqlglot.expressions", "qualname": "Floor", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.Floor.arg_types": {"fullname": "sqlglot.expressions.Floor.arg_types", "modulename": "sqlglot.expressions", "qualname": "Floor.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'decimals': False}"}, "sqlglot.expressions.Floor.key": {"fullname": "sqlglot.expressions.Floor.key", "modulename": "sqlglot.expressions", "qualname": "Floor.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'floor'"}, "sqlglot.expressions.FromBase64": {"fullname": "sqlglot.expressions.FromBase64", "modulename": "sqlglot.expressions", "qualname": "FromBase64", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.FromBase64.key": {"fullname": "sqlglot.expressions.FromBase64.key", "modulename": "sqlglot.expressions", "qualname": "FromBase64.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'frombase64'"}, "sqlglot.expressions.ToBase64": {"fullname": "sqlglot.expressions.ToBase64", "modulename": "sqlglot.expressions", "qualname": "ToBase64", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.ToBase64.key": {"fullname": "sqlglot.expressions.ToBase64.key", "modulename": "sqlglot.expressions", "qualname": "ToBase64.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'tobase64'"}, "sqlglot.expressions.GenerateDateArray": {"fullname": "sqlglot.expressions.GenerateDateArray", "modulename": "sqlglot.expressions", "qualname": "GenerateDateArray", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.GenerateDateArray.arg_types": {"fullname": "sqlglot.expressions.GenerateDateArray.arg_types", "modulename": "sqlglot.expressions", "qualname": "GenerateDateArray.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'start': True, 'end': True, 'interval': False}"}, "sqlglot.expressions.GenerateDateArray.key": {"fullname": "sqlglot.expressions.GenerateDateArray.key", "modulename": "sqlglot.expressions", "qualname": "GenerateDateArray.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'generatedatearray'"}, "sqlglot.expressions.Greatest": {"fullname": "sqlglot.expressions.Greatest", "modulename": "sqlglot.expressions", "qualname": "Greatest", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.Greatest.arg_types": {"fullname": "sqlglot.expressions.Greatest.arg_types", "modulename": "sqlglot.expressions", "qualname": "Greatest.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expressions': False}"}, "sqlglot.expressions.Greatest.is_var_len_args": {"fullname": "sqlglot.expressions.Greatest.is_var_len_args", "modulename": "sqlglot.expressions", "qualname": "Greatest.is_var_len_args", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.expressions.Greatest.key": {"fullname": "sqlglot.expressions.Greatest.key", "modulename": "sqlglot.expressions", "qualname": "Greatest.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'greatest'"}, "sqlglot.expressions.GroupConcat": {"fullname": "sqlglot.expressions.GroupConcat", "modulename": "sqlglot.expressions", "qualname": "GroupConcat", "kind": "class", "doc": "<p></p>\n", "bases": "AggFunc"}, "sqlglot.expressions.GroupConcat.arg_types": {"fullname": "sqlglot.expressions.GroupConcat.arg_types", "modulename": "sqlglot.expressions", "qualname": "GroupConcat.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'separator': False}"}, "sqlglot.expressions.GroupConcat.key": {"fullname": "sqlglot.expressions.GroupConcat.key", "modulename": "sqlglot.expressions", "qualname": "GroupConcat.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'groupconcat'"}, "sqlglot.expressions.Hex": {"fullname": "sqlglot.expressions.Hex", "modulename": "sqlglot.expressions", "qualname": "Hex", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.Hex.key": {"fullname": "sqlglot.expressions.Hex.key", "modulename": "sqlglot.expressions", "qualname": "Hex.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'hex'"}, "sqlglot.expressions.LowerHex": {"fullname": "sqlglot.expressions.LowerHex", "modulename": "sqlglot.expressions", "qualname": "LowerHex", "kind": "class", "doc": "<p></p>\n", "bases": "Hex"}, "sqlglot.expressions.LowerHex.key": {"fullname": "sqlglot.expressions.LowerHex.key", "modulename": "sqlglot.expressions", "qualname": "LowerHex.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'lowerhex'"}, "sqlglot.expressions.Xor": {"fullname": "sqlglot.expressions.Xor", "modulename": "sqlglot.expressions", "qualname": "Xor", "kind": "class", "doc": "<p></p>\n", "bases": "Connector, Func"}, "sqlglot.expressions.Xor.arg_types": {"fullname": "sqlglot.expressions.Xor.arg_types", "modulename": "sqlglot.expressions", "qualname": "Xor.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False, 'expression': False, 'expressions': False}"}, "sqlglot.expressions.Xor.key": {"fullname": "sqlglot.expressions.Xor.key", "modulename": "sqlglot.expressions", "qualname": "Xor.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'xor'"}, "sqlglot.expressions.If": {"fullname": "sqlglot.expressions.If", "modulename": "sqlglot.expressions", "qualname": "If", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.If.arg_types": {"fullname": "sqlglot.expressions.If.arg_types", "modulename": "sqlglot.expressions", "qualname": "If.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'true': True, 'false': False}"}, "sqlglot.expressions.If.key": {"fullname": "sqlglot.expressions.If.key", "modulename": "sqlglot.expressions", "qualname": "If.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'if'"}, "sqlglot.expressions.Nullif": {"fullname": "sqlglot.expressions.Nullif", "modulename": "sqlglot.expressions", "qualname": "Nullif", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.Nullif.arg_types": {"fullname": "sqlglot.expressions.Nullif.arg_types", "modulename": "sqlglot.expressions", "qualname": "Nullif.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': True}"}, "sqlglot.expressions.Nullif.key": {"fullname": "sqlglot.expressions.Nullif.key", "modulename": "sqlglot.expressions", "qualname": "Nullif.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'nullif'"}, "sqlglot.expressions.Initcap": {"fullname": "sqlglot.expressions.Initcap", "modulename": "sqlglot.expressions", "qualname": "Initcap", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.Initcap.arg_types": {"fullname": "sqlglot.expressions.Initcap.arg_types", "modulename": "sqlglot.expressions", "qualname": "Initcap.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': False}"}, "sqlglot.expressions.Initcap.key": {"fullname": "sqlglot.expressions.Initcap.key", "modulename": "sqlglot.expressions", "qualname": "Initcap.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'initcap'"}, "sqlglot.expressions.IsNan": {"fullname": "sqlglot.expressions.IsNan", "modulename": "sqlglot.expressions", "qualname": "IsNan", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.IsNan.key": {"fullname": "sqlglot.expressions.IsNan.key", "modulename": "sqlglot.expressions", "qualname": "IsNan.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'isnan'"}, "sqlglot.expressions.IsInf": {"fullname": "sqlglot.expressions.IsInf", "modulename": "sqlglot.expressions", "qualname": "IsInf", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.IsInf.key": {"fullname": "sqlglot.expressions.IsInf.key", "modulename": "sqlglot.expressions", "qualname": "IsInf.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'isinf'"}, "sqlglot.expressions.JSONPath": {"fullname": "sqlglot.expressions.JSONPath", "modulename": "sqlglot.expressions", "qualname": "JSONPath", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.JSONPath.arg_types": {"fullname": "sqlglot.expressions.JSONPath.arg_types", "modulename": "sqlglot.expressions", "qualname": "JSONPath.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'expressions': True}"}, "sqlglot.expressions.JSONPath.output_name": {"fullname": "sqlglot.expressions.JSONPath.output_name", "modulename": "sqlglot.expressions", "qualname": "JSONPath.output_name", "kind": "variable", "doc": "<p>Name of the output column if this expression is a selection.</p>\n\n<p>If the Expression has no output name, an empty string is returned.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">parse_one</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT a"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'a'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT b AS c"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'c'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT 1 + 2"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">''</span>\n</code></pre>\n </div>\n</blockquote>\n", "annotation": ": str"}, "sqlglot.expressions.JSONPath.key": {"fullname": "sqlglot.expressions.JSONPath.key", "modulename": "sqlglot.expressions", "qualname": "JSONPath.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsonpath'"}, "sqlglot.expressions.JSONPathPart": {"fullname": "sqlglot.expressions.JSONPathPart", "modulename": "sqlglot.expressions", "qualname": "JSONPathPart", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.JSONPathPart.arg_types": {"fullname": "sqlglot.expressions.JSONPathPart.arg_types", "modulename": "sqlglot.expressions", "qualname": "JSONPathPart.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{}"}, "sqlglot.expressions.JSONPathPart.key": {"fullname": "sqlglot.expressions.JSONPathPart.key", "modulename": "sqlglot.expressions", "qualname": "JSONPathPart.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsonpathpart'"}, "sqlglot.expressions.JSONPathFilter": {"fullname": "sqlglot.expressions.JSONPathFilter", "modulename": "sqlglot.expressions", "qualname": "JSONPathFilter", "kind": "class", "doc": "<p></p>\n", "bases": "JSONPathPart"}, "sqlglot.expressions.JSONPathFilter.arg_types": {"fullname": "sqlglot.expressions.JSONPathFilter.arg_types", "modulename": "sqlglot.expressions", "qualname": "JSONPathFilter.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True}"}, "sqlglot.expressions.JSONPathFilter.key": {"fullname": "sqlglot.expressions.JSONPathFilter.key", "modulename": "sqlglot.expressions", "qualname": "JSONPathFilter.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsonpathfilter'"}, "sqlglot.expressions.JSONPathKey": {"fullname": "sqlglot.expressions.JSONPathKey", "modulename": "sqlglot.expressions", "qualname": "JSONPathKey", "kind": "class", "doc": "<p></p>\n", "bases": "JSONPathPart"}, "sqlglot.expressions.JSONPathKey.arg_types": {"fullname": "sqlglot.expressions.JSONPathKey.arg_types", "modulename": "sqlglot.expressions", "qualname": "JSONPathKey.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True}"}, "sqlglot.expressions.JSONPathKey.key": {"fullname": "sqlglot.expressions.JSONPathKey.key", "modulename": "sqlglot.expressions", "qualname": "JSONPathKey.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsonpathkey'"}, "sqlglot.expressions.JSONPathRecursive": {"fullname": "sqlglot.expressions.JSONPathRecursive", "modulename": "sqlglot.expressions", "qualname": "JSONPathRecursive", "kind": "class", "doc": "<p></p>\n", "bases": "JSONPathPart"}, "sqlglot.expressions.JSONPathRecursive.arg_types": {"fullname": "sqlglot.expressions.JSONPathRecursive.arg_types", "modulename": "sqlglot.expressions", "qualname": "JSONPathRecursive.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False}"}, "sqlglot.expressions.JSONPathRecursive.key": {"fullname": "sqlglot.expressions.JSONPathRecursive.key", "modulename": "sqlglot.expressions", "qualname": "JSONPathRecursive.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsonpathrecursive'"}, "sqlglot.expressions.JSONPathRoot": {"fullname": "sqlglot.expressions.JSONPathRoot", "modulename": "sqlglot.expressions", "qualname": "JSONPathRoot", "kind": "class", "doc": "<p></p>\n", "bases": "JSONPathPart"}, "sqlglot.expressions.JSONPathRoot.key": {"fullname": "sqlglot.expressions.JSONPathRoot.key", "modulename": "sqlglot.expressions", "qualname": "JSONPathRoot.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsonpathroot'"}, "sqlglot.expressions.JSONPathScript": {"fullname": "sqlglot.expressions.JSONPathScript", "modulename": "sqlglot.expressions", "qualname": "JSONPathScript", "kind": "class", "doc": "<p></p>\n", "bases": "JSONPathPart"}, "sqlglot.expressions.JSONPathScript.arg_types": {"fullname": "sqlglot.expressions.JSONPathScript.arg_types", "modulename": "sqlglot.expressions", "qualname": "JSONPathScript.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True}"}, "sqlglot.expressions.JSONPathScript.key": {"fullname": "sqlglot.expressions.JSONPathScript.key", "modulename": "sqlglot.expressions", "qualname": "JSONPathScript.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsonpathscript'"}, "sqlglot.expressions.JSONPathSlice": {"fullname": "sqlglot.expressions.JSONPathSlice", "modulename": "sqlglot.expressions", "qualname": "JSONPathSlice", "kind": "class", "doc": "<p></p>\n", "bases": "JSONPathPart"}, "sqlglot.expressions.JSONPathSlice.arg_types": {"fullname": "sqlglot.expressions.JSONPathSlice.arg_types", "modulename": "sqlglot.expressions", "qualname": "JSONPathSlice.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'start': False, 'end': False, 'step': False}"}, "sqlglot.expressions.JSONPathSlice.key": {"fullname": "sqlglot.expressions.JSONPathSlice.key", "modulename": "sqlglot.expressions", "qualname": "JSONPathSlice.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsonpathslice'"}, "sqlglot.expressions.JSONPathSelector": {"fullname": "sqlglot.expressions.JSONPathSelector", "modulename": "sqlglot.expressions", "qualname": "JSONPathSelector", "kind": "class", "doc": "<p></p>\n", "bases": "JSONPathPart"}, "sqlglot.expressions.JSONPathSelector.arg_types": {"fullname": "sqlglot.expressions.JSONPathSelector.arg_types", "modulename": "sqlglot.expressions", "qualname": "JSONPathSelector.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True}"}, "sqlglot.expressions.JSONPathSelector.key": {"fullname": "sqlglot.expressions.JSONPathSelector.key", "modulename": "sqlglot.expressions", "qualname": "JSONPathSelector.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsonpathselector'"}, "sqlglot.expressions.JSONPathSubscript": {"fullname": "sqlglot.expressions.JSONPathSubscript", "modulename": "sqlglot.expressions", "qualname": "JSONPathSubscript", "kind": "class", "doc": "<p></p>\n", "bases": "JSONPathPart"}, "sqlglot.expressions.JSONPathSubscript.arg_types": {"fullname": "sqlglot.expressions.JSONPathSubscript.arg_types", "modulename": "sqlglot.expressions", "qualname": "JSONPathSubscript.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True}"}, "sqlglot.expressions.JSONPathSubscript.key": {"fullname": "sqlglot.expressions.JSONPathSubscript.key", "modulename": "sqlglot.expressions", "qualname": "JSONPathSubscript.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsonpathsubscript'"}, "sqlglot.expressions.JSONPathUnion": {"fullname": "sqlglot.expressions.JSONPathUnion", "modulename": "sqlglot.expressions", "qualname": "JSONPathUnion", "kind": "class", "doc": "<p></p>\n", "bases": "JSONPathPart"}, "sqlglot.expressions.JSONPathUnion.arg_types": {"fullname": "sqlglot.expressions.JSONPathUnion.arg_types", "modulename": "sqlglot.expressions", "qualname": "JSONPathUnion.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'expressions': True}"}, "sqlglot.expressions.JSONPathUnion.key": {"fullname": "sqlglot.expressions.JSONPathUnion.key", "modulename": "sqlglot.expressions", "qualname": "JSONPathUnion.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsonpathunion'"}, "sqlglot.expressions.JSONPathWildcard": {"fullname": "sqlglot.expressions.JSONPathWildcard", "modulename": "sqlglot.expressions", "qualname": "JSONPathWildcard", "kind": "class", "doc": "<p></p>\n", "bases": "JSONPathPart"}, "sqlglot.expressions.JSONPathWildcard.key": {"fullname": "sqlglot.expressions.JSONPathWildcard.key", "modulename": "sqlglot.expressions", "qualname": "JSONPathWildcard.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsonpathwildcard'"}, "sqlglot.expressions.FormatJson": {"fullname": "sqlglot.expressions.FormatJson", "modulename": "sqlglot.expressions", "qualname": "FormatJson", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.FormatJson.key": {"fullname": "sqlglot.expressions.FormatJson.key", "modulename": "sqlglot.expressions", "qualname": "FormatJson.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'formatjson'"}, "sqlglot.expressions.JSONKeyValue": {"fullname": "sqlglot.expressions.JSONKeyValue", "modulename": "sqlglot.expressions", "qualname": "JSONKeyValue", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.JSONKeyValue.arg_types": {"fullname": "sqlglot.expressions.JSONKeyValue.arg_types", "modulename": "sqlglot.expressions", "qualname": "JSONKeyValue.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': True}"}, "sqlglot.expressions.JSONKeyValue.key": {"fullname": "sqlglot.expressions.JSONKeyValue.key", "modulename": "sqlglot.expressions", "qualname": "JSONKeyValue.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsonkeyvalue'"}, "sqlglot.expressions.JSONObject": {"fullname": "sqlglot.expressions.JSONObject", "modulename": "sqlglot.expressions", "qualname": "JSONObject", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.JSONObject.arg_types": {"fullname": "sqlglot.expressions.JSONObject.arg_types", "modulename": "sqlglot.expressions", "qualname": "JSONObject.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'expressions': False, 'null_handling': False, 'unique_keys': False, 'return_type': False, 'encoding': False}"}, "sqlglot.expressions.JSONObject.key": {"fullname": "sqlglot.expressions.JSONObject.key", "modulename": "sqlglot.expressions", "qualname": "JSONObject.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsonobject'"}, "sqlglot.expressions.JSONObjectAgg": {"fullname": "sqlglot.expressions.JSONObjectAgg", "modulename": "sqlglot.expressions", "qualname": "JSONObjectAgg", "kind": "class", "doc": "<p></p>\n", "bases": "AggFunc"}, "sqlglot.expressions.JSONObjectAgg.arg_types": {"fullname": "sqlglot.expressions.JSONObjectAgg.arg_types", "modulename": "sqlglot.expressions", "qualname": "JSONObjectAgg.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'expressions': False, 'null_handling': False, 'unique_keys': False, 'return_type': False, 'encoding': False}"}, "sqlglot.expressions.JSONObjectAgg.key": {"fullname": "sqlglot.expressions.JSONObjectAgg.key", "modulename": "sqlglot.expressions", "qualname": "JSONObjectAgg.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsonobjectagg'"}, "sqlglot.expressions.JSONArray": {"fullname": "sqlglot.expressions.JSONArray", "modulename": "sqlglot.expressions", "qualname": "JSONArray", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.JSONArray.arg_types": {"fullname": "sqlglot.expressions.JSONArray.arg_types", "modulename": "sqlglot.expressions", "qualname": "JSONArray.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'expressions': True, 'null_handling': False, 'return_type': False, 'strict': False}"}, "sqlglot.expressions.JSONArray.key": {"fullname": "sqlglot.expressions.JSONArray.key", "modulename": "sqlglot.expressions", "qualname": "JSONArray.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsonarray'"}, "sqlglot.expressions.JSONArrayAgg": {"fullname": "sqlglot.expressions.JSONArrayAgg", "modulename": "sqlglot.expressions", "qualname": "JSONArrayAgg", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.JSONArrayAgg.arg_types": {"fullname": "sqlglot.expressions.JSONArrayAgg.arg_types", "modulename": "sqlglot.expressions", "qualname": "JSONArrayAgg.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'order': False, 'null_handling': False, 'return_type': False, 'strict': False}"}, "sqlglot.expressions.JSONArrayAgg.key": {"fullname": "sqlglot.expressions.JSONArrayAgg.key", "modulename": "sqlglot.expressions", "qualname": "JSONArrayAgg.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsonarrayagg'"}, "sqlglot.expressions.JSONColumnDef": {"fullname": "sqlglot.expressions.JSONColumnDef", "modulename": "sqlglot.expressions", "qualname": "JSONColumnDef", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.JSONColumnDef.arg_types": {"fullname": "sqlglot.expressions.JSONColumnDef.arg_types", "modulename": "sqlglot.expressions", "qualname": "JSONColumnDef.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False, 'kind': False, 'path': False, 'nested_schema': False}"}, "sqlglot.expressions.JSONColumnDef.key": {"fullname": "sqlglot.expressions.JSONColumnDef.key", "modulename": "sqlglot.expressions", "qualname": "JSONColumnDef.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsoncolumndef'"}, "sqlglot.expressions.JSONSchema": {"fullname": "sqlglot.expressions.JSONSchema", "modulename": "sqlglot.expressions", "qualname": "JSONSchema", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.JSONSchema.arg_types": {"fullname": "sqlglot.expressions.JSONSchema.arg_types", "modulename": "sqlglot.expressions", "qualname": "JSONSchema.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'expressions': True}"}, "sqlglot.expressions.JSONSchema.key": {"fullname": "sqlglot.expressions.JSONSchema.key", "modulename": "sqlglot.expressions", "qualname": "JSONSchema.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsonschema'"}, "sqlglot.expressions.JSONTable": {"fullname": "sqlglot.expressions.JSONTable", "modulename": "sqlglot.expressions", "qualname": "JSONTable", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.JSONTable.arg_types": {"fullname": "sqlglot.expressions.JSONTable.arg_types", "modulename": "sqlglot.expressions", "qualname": "JSONTable.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'schema': True, 'path': False, 'error_handling': False, 'empty_handling': False}"}, "sqlglot.expressions.JSONTable.key": {"fullname": "sqlglot.expressions.JSONTable.key", "modulename": "sqlglot.expressions", "qualname": "JSONTable.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsontable'"}, "sqlglot.expressions.OpenJSONColumnDef": {"fullname": "sqlglot.expressions.OpenJSONColumnDef", "modulename": "sqlglot.expressions", "qualname": "OpenJSONColumnDef", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.OpenJSONColumnDef.arg_types": {"fullname": "sqlglot.expressions.OpenJSONColumnDef.arg_types", "modulename": "sqlglot.expressions", "qualname": "OpenJSONColumnDef.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'kind': True, 'path': False, 'as_json': False}"}, "sqlglot.expressions.OpenJSONColumnDef.key": {"fullname": "sqlglot.expressions.OpenJSONColumnDef.key", "modulename": "sqlglot.expressions", "qualname": "OpenJSONColumnDef.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'openjsoncolumndef'"}, "sqlglot.expressions.OpenJSON": {"fullname": "sqlglot.expressions.OpenJSON", "modulename": "sqlglot.expressions", "qualname": "OpenJSON", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.OpenJSON.arg_types": {"fullname": "sqlglot.expressions.OpenJSON.arg_types", "modulename": "sqlglot.expressions", "qualname": "OpenJSON.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'path': False, 'expressions': False}"}, "sqlglot.expressions.OpenJSON.key": {"fullname": "sqlglot.expressions.OpenJSON.key", "modulename": "sqlglot.expressions", "qualname": "OpenJSON.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'openjson'"}, "sqlglot.expressions.JSONBContains": {"fullname": "sqlglot.expressions.JSONBContains", "modulename": "sqlglot.expressions", "qualname": "JSONBContains", "kind": "class", "doc": "<p></p>\n", "bases": "Binary"}, "sqlglot.expressions.JSONBContains.key": {"fullname": "sqlglot.expressions.JSONBContains.key", "modulename": "sqlglot.expressions", "qualname": "JSONBContains.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsonbcontains'"}, "sqlglot.expressions.JSONExtract": {"fullname": "sqlglot.expressions.JSONExtract", "modulename": "sqlglot.expressions", "qualname": "JSONExtract", "kind": "class", "doc": "<p></p>\n", "bases": "Binary, Func"}, "sqlglot.expressions.JSONExtract.arg_types": {"fullname": "sqlglot.expressions.JSONExtract.arg_types", "modulename": "sqlglot.expressions", "qualname": "JSONExtract.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': True, 'only_json_types': False, 'expressions': False}"}, "sqlglot.expressions.JSONExtract.is_var_len_args": {"fullname": "sqlglot.expressions.JSONExtract.is_var_len_args", "modulename": "sqlglot.expressions", "qualname": "JSONExtract.is_var_len_args", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.expressions.JSONExtract.output_name": {"fullname": "sqlglot.expressions.JSONExtract.output_name", "modulename": "sqlglot.expressions", "qualname": "JSONExtract.output_name", "kind": "variable", "doc": "<p>Name of the output column if this expression is a selection.</p>\n\n<p>If the Expression has no output name, an empty string is returned.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">parse_one</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT a"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'a'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT b AS c"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'c'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT 1 + 2"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">''</span>\n</code></pre>\n </div>\n</blockquote>\n", "annotation": ": str"}, "sqlglot.expressions.JSONExtract.key": {"fullname": "sqlglot.expressions.JSONExtract.key", "modulename": "sqlglot.expressions", "qualname": "JSONExtract.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsonextract'"}, "sqlglot.expressions.JSONExtractScalar": {"fullname": "sqlglot.expressions.JSONExtractScalar", "modulename": "sqlglot.expressions", "qualname": "JSONExtractScalar", "kind": "class", "doc": "<p></p>\n", "bases": "Binary, Func"}, "sqlglot.expressions.JSONExtractScalar.arg_types": {"fullname": "sqlglot.expressions.JSONExtractScalar.arg_types", "modulename": "sqlglot.expressions", "qualname": "JSONExtractScalar.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expression': True, 'only_json_types': False, 'expressions': False}"}, "sqlglot.expressions.JSONExtractScalar.is_var_len_args": {"fullname": "sqlglot.expressions.JSONExtractScalar.is_var_len_args", "modulename": "sqlglot.expressions", "qualname": "JSONExtractScalar.is_var_len_args", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.expressions.JSONExtractScalar.output_name": {"fullname": "sqlglot.expressions.JSONExtractScalar.output_name", "modulename": "sqlglot.expressions", "qualname": "JSONExtractScalar.output_name", "kind": "variable", "doc": "<p>Name of the output column if this expression is a selection.</p>\n\n<p>If the Expression has no output name, an empty string is returned.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">parse_one</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT a"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'a'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT b AS c"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">'c'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT 1 + 2"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">output_name</span>\n<span class=\"go\">''</span>\n</code></pre>\n </div>\n</blockquote>\n", "annotation": ": str"}, "sqlglot.expressions.JSONExtractScalar.key": {"fullname": "sqlglot.expressions.JSONExtractScalar.key", "modulename": "sqlglot.expressions", "qualname": "JSONExtractScalar.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsonextractscalar'"}, "sqlglot.expressions.JSONBExtract": {"fullname": "sqlglot.expressions.JSONBExtract", "modulename": "sqlglot.expressions", "qualname": "JSONBExtract", "kind": "class", "doc": "<p></p>\n", "bases": "Binary, Func"}, "sqlglot.expressions.JSONBExtract.key": {"fullname": "sqlglot.expressions.JSONBExtract.key", "modulename": "sqlglot.expressions", "qualname": "JSONBExtract.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsonbextract'"}, "sqlglot.expressions.JSONBExtractScalar": {"fullname": "sqlglot.expressions.JSONBExtractScalar", "modulename": "sqlglot.expressions", "qualname": "JSONBExtractScalar", "kind": "class", "doc": "<p></p>\n", "bases": "Binary, Func"}, "sqlglot.expressions.JSONBExtractScalar.key": {"fullname": "sqlglot.expressions.JSONBExtractScalar.key", "modulename": "sqlglot.expressions", "qualname": "JSONBExtractScalar.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsonbextractscalar'"}, "sqlglot.expressions.JSONFormat": {"fullname": "sqlglot.expressions.JSONFormat", "modulename": "sqlglot.expressions", "qualname": "JSONFormat", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.JSONFormat.arg_types": {"fullname": "sqlglot.expressions.JSONFormat.arg_types", "modulename": "sqlglot.expressions", "qualname": "JSONFormat.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': False, 'options': False}"}, "sqlglot.expressions.JSONFormat.key": {"fullname": "sqlglot.expressions.JSONFormat.key", "modulename": "sqlglot.expressions", "qualname": "JSONFormat.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsonformat'"}, "sqlglot.expressions.JSONArrayContains": {"fullname": "sqlglot.expressions.JSONArrayContains", "modulename": "sqlglot.expressions", "qualname": "JSONArrayContains", "kind": "class", "doc": "<p></p>\n", "bases": "Binary, Predicate, Func"}, "sqlglot.expressions.JSONArrayContains.key": {"fullname": "sqlglot.expressions.JSONArrayContains.key", "modulename": "sqlglot.expressions", "qualname": "JSONArrayContains.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'jsonarraycontains'"}, "sqlglot.expressions.ParseJSON": {"fullname": "sqlglot.expressions.ParseJSON", "modulename": "sqlglot.expressions", "qualname": "ParseJSON", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.ParseJSON.arg_types": {"fullname": "sqlglot.expressions.ParseJSON.arg_types", "modulename": "sqlglot.expressions", "qualname": "ParseJSON.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expressions': False}"}, "sqlglot.expressions.ParseJSON.is_var_len_args": {"fullname": "sqlglot.expressions.ParseJSON.is_var_len_args", "modulename": "sqlglot.expressions", "qualname": "ParseJSON.is_var_len_args", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.expressions.ParseJSON.key": {"fullname": "sqlglot.expressions.ParseJSON.key", "modulename": "sqlglot.expressions", "qualname": "ParseJSON.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'parsejson'"}, "sqlglot.expressions.Least": {"fullname": "sqlglot.expressions.Least", "modulename": "sqlglot.expressions", "qualname": "Least", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.Least.arg_types": {"fullname": "sqlglot.expressions.Least.arg_types", "modulename": "sqlglot.expressions", "qualname": "Least.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'expressions': False}"}, "sqlglot.expressions.Least.is_var_len_args": {"fullname": "sqlglot.expressions.Least.is_var_len_args", "modulename": "sqlglot.expressions", "qualname": "Least.is_var_len_args", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.expressions.Least.key": {"fullname": "sqlglot.expressions.Least.key", "modulename": "sqlglot.expressions", "qualname": "Least.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'least'"}, "sqlglot.expressions.Left": {"fullname": 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"sqlglot.expressions", "qualname": "Merge.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'using': True, 'on': True, 'expressions': True, 'with': False}"}, "sqlglot.expressions.Merge.key": {"fullname": "sqlglot.expressions.Merge.key", "modulename": "sqlglot.expressions", "qualname": "Merge.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'merge'"}, "sqlglot.expressions.When": {"fullname": "sqlglot.expressions.When", "modulename": "sqlglot.expressions", "qualname": "When", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.When.arg_types": {"fullname": "sqlglot.expressions.When.arg_types", "modulename": "sqlglot.expressions", "qualname": "When.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'matched': True, 'source': False, 'condition': False, 'then': True}"}, "sqlglot.expressions.When.key": {"fullname": "sqlglot.expressions.When.key", "modulename": "sqlglot.expressions", "qualname": "When.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'when'"}, "sqlglot.expressions.NextValueFor": {"fullname": "sqlglot.expressions.NextValueFor", "modulename": "sqlglot.expressions", "qualname": "NextValueFor", "kind": "class", "doc": "<p></p>\n", "bases": "Func"}, "sqlglot.expressions.NextValueFor.arg_types": {"fullname": "sqlglot.expressions.NextValueFor.arg_types", "modulename": "sqlglot.expressions", "qualname": "NextValueFor.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'this': True, 'order': False}"}, "sqlglot.expressions.NextValueFor.key": {"fullname": "sqlglot.expressions.NextValueFor.key", "modulename": "sqlglot.expressions", "qualname": "NextValueFor.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'nextvaluefor'"}, "sqlglot.expressions.Semicolon": {"fullname": "sqlglot.expressions.Semicolon", "modulename": "sqlglot.expressions", "qualname": "Semicolon", "kind": "class", "doc": "<p></p>\n", "bases": "Expression"}, "sqlglot.expressions.Semicolon.arg_types": {"fullname": "sqlglot.expressions.Semicolon.arg_types", "modulename": "sqlglot.expressions", "qualname": "Semicolon.arg_types", "kind": "variable", "doc": "<p></p>\n", "default_value": "{}"}, "sqlglot.expressions.Semicolon.key": {"fullname": "sqlglot.expressions.Semicolon.key", "modulename": "sqlglot.expressions", "qualname": "Semicolon.key", "kind": "variable", "doc": "<p></p>\n", "default_value": "'semicolon'"}, "sqlglot.expressions.ALL_FUNCTIONS": {"fullname": "sqlglot.expressions.ALL_FUNCTIONS", "modulename": "sqlglot.expressions", "qualname": "ALL_FUNCTIONS", "kind": "variable", "doc": "<p></p>\n", "default_value": "[<class 'sqlglot.expressions.Abs'>, <class 'sqlglot.expressions.AddMonths'>, <class 'sqlglot.expressions.AnonymousAggFunc'>, <class 'sqlglot.expressions.AnyValue'>, <class 'sqlglot.expressions.ApproxDistinct'>, <class 'sqlglot.expressions.ApproxQuantile'>, <class 'sqlglot.expressions.ApproxTopK'>, <class 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'sqlglot.expressions.Xor'>, <class 'sqlglot.expressions.Year'>]"}, "sqlglot.expressions.FUNCTION_BY_NAME": {"fullname": "sqlglot.expressions.FUNCTION_BY_NAME", "modulename": "sqlglot.expressions", "qualname": "FUNCTION_BY_NAME", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'ABS': <class 'sqlglot.expressions.Abs'>, 'ADD_MONTHS': <class 'sqlglot.expressions.AddMonths'>, 'ANONYMOUS_AGG_FUNC': <class 'sqlglot.expressions.AnonymousAggFunc'>, 'ANY_VALUE': <class 'sqlglot.expressions.AnyValue'>, 'APPROX_DISTINCT': <class 'sqlglot.expressions.ApproxDistinct'>, 'APPROX_COUNT_DISTINCT': <class 'sqlglot.expressions.ApproxDistinct'>, 'APPROX_QUANTILE': <class 'sqlglot.expressions.ApproxQuantile'>, 'APPROX_TOP_K': <class 'sqlglot.expressions.ApproxTopK'>, 'ARG_MAX': <class 'sqlglot.expressions.ArgMax'>, 'ARGMAX': <class 'sqlglot.expressions.ArgMax'>, 'MAX_BY': <class 'sqlglot.expressions.ArgMax'>, 'ARG_MIN': <class 'sqlglot.expressions.ArgMin'>, 'ARGMIN': <class 'sqlglot.expressions.ArgMin'>, 'MIN_BY': <class 'sqlglot.expressions.ArgMin'>, 'ARRAY': <class 'sqlglot.expressions.Array'>, 'ARRAY_AGG': <class 'sqlglot.expressions.ArrayAgg'>, 'ARRAY_ALL': <class 'sqlglot.expressions.ArrayAll'>, 'ARRAY_ANY': <class 'sqlglot.expressions.ArrayAny'>, 'ARRAY_CONCAT': <class 'sqlglot.expressions.ArrayConcat'>, 'ARRAY_CAT': <class 'sqlglot.expressions.ArrayConcat'>, 'ARRAY_CONSTRUCT_COMPACT': <class 'sqlglot.expressions.ArrayConstructCompact'>, 'ARRAY_CONTAINS': <class 'sqlglot.expressions.ArrayContains'>, 'FILTER': <class 'sqlglot.expressions.ArrayFilter'>, 'ARRAY_FILTER': <class 'sqlglot.expressions.ArrayFilter'>, 'ARRAY_OVERLAPS': <class 'sqlglot.expressions.ArrayOverlaps'>, 'ARRAY_SIZE': <class 'sqlglot.expressions.ArraySize'>, 'ARRAY_LENGTH': <class 'sqlglot.expressions.ArraySize'>, 'ARRAY_SORT': <class 'sqlglot.expressions.ArraySort'>, 'ARRAY_SUM': <class 'sqlglot.expressions.ArraySum'>, 'ARRAY_TO_STRING': <class 'sqlglot.expressions.ArrayToString'>, 'ARRAY_JOIN': <class 'sqlglot.expressions.ArrayToString'>, 'ARRAY_UNION_AGG': <class 'sqlglot.expressions.ArrayUnionAgg'>, 'ARRAY_UNIQUE_AGG': <class 'sqlglot.expressions.ArrayUniqueAgg'>, 'AVG': <class 'sqlglot.expressions.Avg'>, 'CASE': <class 'sqlglot.expressions.Case'>, 'CAST': <class 'sqlglot.expressions.Cast'>, 'CAST_TO_STR_TYPE': <class 'sqlglot.expressions.CastToStrType'>, 'CBRT': <class 'sqlglot.expressions.Cbrt'>, 'CEIL': <class 'sqlglot.expressions.Ceil'>, 'CEILING': <class 'sqlglot.expressions.Ceil'>, 'CHR': <class 'sqlglot.expressions.Chr'>, 'CHAR': <class 'sqlglot.expressions.Chr'>, 'COALESCE': <class 'sqlglot.expressions.Coalesce'>, 'IFNULL': <class 'sqlglot.expressions.Coalesce'>, 'NVL': <class 'sqlglot.expressions.Coalesce'>, 'COLLATE': <class 'sqlglot.expressions.Collate'>, 'COMBINED_AGG_FUNC': <class 'sqlglot.expressions.CombinedAggFunc'>, 'COMBINED_PARAMETERIZED_AGG': <class 'sqlglot.expressions.CombinedParameterizedAgg'>, 'CONCAT': <class 'sqlglot.expressions.Concat'>, 'CONCAT_WS': <class 'sqlglot.expressions.ConcatWs'>, 'CONNECT_BY_ROOT': <class 'sqlglot.expressions.ConnectByRoot'>, 'CONVERT': <class 'sqlglot.expressions.Convert'>, 'CORR': <class 'sqlglot.expressions.Corr'>, 'COUNT': <class 'sqlglot.expressions.Count'>, 'COUNT_IF': <class 'sqlglot.expressions.CountIf'>, 'COUNTIF': <class 'sqlglot.expressions.CountIf'>, 'COVAR_POP': <class 'sqlglot.expressions.CovarPop'>, 'COVAR_SAMP': <class 'sqlglot.expressions.CovarSamp'>, 'CURRENT_DATE': <class 'sqlglot.expressions.CurrentDate'>, 'CURRENT_DATETIME': <class 'sqlglot.expressions.CurrentDatetime'>, 'CURRENT_TIME': <class 'sqlglot.expressions.CurrentTime'>, 'CURRENT_TIMESTAMP': <class 'sqlglot.expressions.CurrentTimestamp'>, 'CURRENT_USER': <class 'sqlglot.expressions.CurrentUser'>, 'DATE': <class 'sqlglot.expressions.Date'>, 'DATE_ADD': <class 'sqlglot.expressions.DateAdd'>, 'DATEDIFF': <class 'sqlglot.expressions.DateDiff'>, 'DATE_DIFF': <class 'sqlglot.expressions.DateDiff'>, 'DATE_FROM_PARTS': <class 'sqlglot.expressions.DateFromParts'>, 'DATEFROMPARTS': <class 'sqlglot.expressions.DateFromParts'>, 'DATE_STR_TO_DATE': <class 'sqlglot.expressions.DateStrToDate'>, 'DATE_SUB': <class 'sqlglot.expressions.DateSub'>, 'DATE_TO_DATE_STR': <class 'sqlglot.expressions.DateToDateStr'>, 'DATE_TO_DI': <class 'sqlglot.expressions.DateToDi'>, 'DATE_TRUNC': <class 'sqlglot.expressions.DateTrunc'>, 'DATETIME_ADD': <class 'sqlglot.expressions.DatetimeAdd'>, 'DATETIME_DIFF': <class 'sqlglot.expressions.DatetimeDiff'>, 'DATETIME_SUB': <class 'sqlglot.expressions.DatetimeSub'>, 'DATETIME_TRUNC': <class 'sqlglot.expressions.DatetimeTrunc'>, 'DAY': <class 'sqlglot.expressions.Day'>, 'DAY_OF_MONTH': <class 'sqlglot.expressions.DayOfMonth'>, 'DAYOFMONTH': <class 'sqlglot.expressions.DayOfMonth'>, 'DAY_OF_WEEK': <class 'sqlglot.expressions.DayOfWeek'>, 'DAYOFWEEK': <class 'sqlglot.expressions.DayOfWeek'>, 'DAY_OF_YEAR': <class 'sqlglot.expressions.DayOfYear'>, 'DAYOFYEAR': <class 'sqlglot.expressions.DayOfYear'>, 'DECODE': <class 'sqlglot.expressions.Decode'>, 'DI_TO_DATE': <class 'sqlglot.expressions.DiToDate'>, 'ENCODE': <class 'sqlglot.expressions.Encode'>, 'EXP': <class 'sqlglot.expressions.Exp'>, 'EXPLODE': <class 'sqlglot.expressions.Explode'>, 'EXPLODE_OUTER': <class 'sqlglot.expressions.ExplodeOuter'>, 'EXTRACT': <class 'sqlglot.expressions.Extract'>, 'FIRST': <class 'sqlglot.expressions.First'>, 'FIRST_VALUE': <class 'sqlglot.expressions.FirstValue'>, 'FLATTEN': <class 'sqlglot.expressions.Flatten'>, 'FLOOR': <class 'sqlglot.expressions.Floor'>, 'FROM_BASE': <class 'sqlglot.expressions.FromBase'>, 'FROM_BASE64': <class 'sqlglot.expressions.FromBase64'>, 'GENERATE_DATE_ARRAY': <class 'sqlglot.expressions.GenerateDateArray'>, 'GENERATE_SERIES': <class 'sqlglot.expressions.GenerateSeries'>, 'GREATEST': <class 'sqlglot.expressions.Greatest'>, 'GROUP_CONCAT': <class 'sqlglot.expressions.GroupConcat'>, 'HEX': <class 'sqlglot.expressions.Hex'>, 'HLL': <class 'sqlglot.expressions.Hll'>, 'IF': <class 'sqlglot.expressions.If'>, 'IIF': <class 'sqlglot.expressions.If'>, 'INITCAP': <class 'sqlglot.expressions.Initcap'>, 'IS_INF': <class 'sqlglot.expressions.IsInf'>, 'ISINF': <class 'sqlglot.expressions.IsInf'>, 'IS_NAN': <class 'sqlglot.expressions.IsNan'>, 'ISNAN': <class 'sqlglot.expressions.IsNan'>, 'J_S_O_N_ARRAY': <class 'sqlglot.expressions.JSONArray'>, 'J_S_O_N_ARRAY_AGG': <class 'sqlglot.expressions.JSONArrayAgg'>, 'JSON_ARRAY_CONTAINS': <class 'sqlglot.expressions.JSONArrayContains'>, 'JSONB_EXTRACT': <class 'sqlglot.expressions.JSONBExtract'>, 'JSONB_EXTRACT_SCALAR': <class 'sqlglot.expressions.JSONBExtractScalar'>, 'JSON_EXTRACT': <class 'sqlglot.expressions.JSONExtract'>, 'JSON_EXTRACT_SCALAR': <class 'sqlglot.expressions.JSONExtractScalar'>, 'JSON_FORMAT': <class 'sqlglot.expressions.JSONFormat'>, 'J_S_O_N_OBJECT': <class 'sqlglot.expressions.JSONObject'>, 'J_S_O_N_OBJECT_AGG': <class 'sqlglot.expressions.JSONObjectAgg'>, 'J_S_O_N_TABLE': <class 'sqlglot.expressions.JSONTable'>, 'LAG': <class 'sqlglot.expressions.Lag'>, 'LAST': <class 'sqlglot.expressions.Last'>, 'LAST_DAY': <class 'sqlglot.expressions.LastDay'>, 'LAST_DAY_OF_MONTH': <class 'sqlglot.expressions.LastDay'>, 'LAST_VALUE': <class 'sqlglot.expressions.LastValue'>, 'LEAD': <class 'sqlglot.expressions.Lead'>, 'LEAST': <class 'sqlglot.expressions.Least'>, 'LEFT': <class 'sqlglot.expressions.Left'>, 'LENGTH': <class 'sqlglot.expressions.Length'>, 'LEN': <class 'sqlglot.expressions.Length'>, 'LEVENSHTEIN': <class 'sqlglot.expressions.Levenshtein'>, 'LN': <class 'sqlglot.expressions.Ln'>, 'LOG': <class 'sqlglot.expressions.Log'>, 'LOGICAL_AND': <class 'sqlglot.expressions.LogicalAnd'>, 'BOOL_AND': <class 'sqlglot.expressions.LogicalAnd'>, 'BOOLAND_AGG': <class 'sqlglot.expressions.LogicalAnd'>, 'LOGICAL_OR': <class 'sqlglot.expressions.LogicalOr'>, 'BOOL_OR': <class 'sqlglot.expressions.LogicalOr'>, 'BOOLOR_AGG': <class 'sqlglot.expressions.LogicalOr'>, 'LOWER': <class 'sqlglot.expressions.Lower'>, 'LCASE': <class 'sqlglot.expressions.Lower'>, 'LOWER_HEX': <class 'sqlglot.expressions.LowerHex'>, 'MD5': <class 'sqlglot.expressions.MD5'>, 'MD5_DIGEST': <class 'sqlglot.expressions.MD5Digest'>, 'MAP': <class 'sqlglot.expressions.Map'>, 'MAP_FROM_ENTRIES': <class 'sqlglot.expressions.MapFromEntries'>, 'MATCH_AGAINST': <class 'sqlglot.expressions.MatchAgainst'>, 'MAX': <class 'sqlglot.expressions.Max'>, 'MIN': <class 'sqlglot.expressions.Min'>, 'MONTH': <class 'sqlglot.expressions.Month'>, 'MONTHS_BETWEEN': <class 'sqlglot.expressions.MonthsBetween'>, 'NEXT_VALUE_FOR': <class 'sqlglot.expressions.NextValueFor'>, 'NTH_VALUE': <class 'sqlglot.expressions.NthValue'>, 'NULLIF': <class 'sqlglot.expressions.Nullif'>, 'NUMBER_TO_STR': <class 'sqlglot.expressions.NumberToStr'>, 'NVL2': <class 'sqlglot.expressions.Nvl2'>, 'OPEN_J_S_O_N': <class 'sqlglot.expressions.OpenJSON'>, 'PARAMETERIZED_AGG': <class 'sqlglot.expressions.ParameterizedAgg'>, 'PARSE_JSON': <class 'sqlglot.expressions.ParseJSON'>, 'JSON_PARSE': <class 'sqlglot.expressions.ParseJSON'>, 'PERCENTILE_CONT': <class 'sqlglot.expressions.PercentileCont'>, 'PERCENTILE_DISC': <class 'sqlglot.expressions.PercentileDisc'>, 'POSEXPLODE': <class 'sqlglot.expressions.Posexplode'>, 'POSEXPLODE_OUTER': <class 'sqlglot.expressions.PosexplodeOuter'>, 'POWER': <class 'sqlglot.expressions.Pow'>, 'POW': <class 'sqlglot.expressions.Pow'>, 'PREDICT': <class 'sqlglot.expressions.Predict'>, 'QUANTILE': <class 'sqlglot.expressions.Quantile'>, 'QUARTER': <class 'sqlglot.expressions.Quarter'>, 'RAND': <class 'sqlglot.expressions.Rand'>, 'RANDOM': <class 'sqlglot.expressions.Rand'>, 'RANDN': <class 'sqlglot.expressions.Randn'>, 'RANGE_N': <class 'sqlglot.expressions.RangeN'>, 'READ_CSV': <class 'sqlglot.expressions.ReadCSV'>, 'REDUCE': <class 'sqlglot.expressions.Reduce'>, 'REGEXP_EXTRACT': <class 'sqlglot.expressions.RegexpExtract'>, 'REGEXP_I_LIKE': <class 'sqlglot.expressions.RegexpILike'>, 'REGEXP_LIKE': <class 'sqlglot.expressions.RegexpLike'>, 'REGEXP_REPLACE': <class 'sqlglot.expressions.RegexpReplace'>, 'REGEXP_SPLIT': <class 'sqlglot.expressions.RegexpSplit'>, 'REPEAT': <class 'sqlglot.expressions.Repeat'>, 'RIGHT': <class 'sqlglot.expressions.Right'>, 'ROUND': <class 'sqlglot.expressions.Round'>, 'ROW_NUMBER': <class 'sqlglot.expressions.RowNumber'>, 'SHA': <class 'sqlglot.expressions.SHA'>, 'SHA1': <class 'sqlglot.expressions.SHA'>, 'SHA2': <class 'sqlglot.expressions.SHA2'>, 'SAFE_DIVIDE': <class 'sqlglot.expressions.SafeDivide'>, 'SIGN': <class 'sqlglot.expressions.Sign'>, 'SIGNUM': <class 'sqlglot.expressions.Sign'>, 'SORT_ARRAY': <class 'sqlglot.expressions.SortArray'>, 'SPLIT': <class 'sqlglot.expressions.Split'>, 'SQRT': <class 'sqlglot.expressions.Sqrt'>, 'STANDARD_HASH': <class 'sqlglot.expressions.StandardHash'>, 'STAR_MAP': <class 'sqlglot.expressions.StarMap'>, 'STARTS_WITH': <class 'sqlglot.expressions.StartsWith'>, 'STARTSWITH': <class 'sqlglot.expressions.StartsWith'>, 'STDDEV': <class 'sqlglot.expressions.Stddev'>, 'STDDEV_POP': <class 'sqlglot.expressions.StddevPop'>, 'STDDEV_SAMP': <class 'sqlglot.expressions.StddevSamp'>, 'STR_POSITION': <class 'sqlglot.expressions.StrPosition'>, 'STR_TO_DATE': <class 'sqlglot.expressions.StrToDate'>, 'STR_TO_MAP': <class 'sqlglot.expressions.StrToMap'>, 'STR_TO_TIME': <class 'sqlglot.expressions.StrToTime'>, 'STR_TO_UNIX': <class 'sqlglot.expressions.StrToUnix'>, 'STRUCT': <class 'sqlglot.expressions.Struct'>, 'STRUCT_EXTRACT': <class 'sqlglot.expressions.StructExtract'>, 'STUFF': <class 'sqlglot.expressions.Stuff'>, 'INSERT': <class 'sqlglot.expressions.Stuff'>, 'SUBSTRING': <class 'sqlglot.expressions.Substring'>, 'SUM': <class 'sqlglot.expressions.Sum'>, 'TIME_ADD': <class 'sqlglot.expressions.TimeAdd'>, 'TIME_DIFF': <class 'sqlglot.expressions.TimeDiff'>, 'TIME_FROM_PARTS': <class 'sqlglot.expressions.TimeFromParts'>, 'TIMEFROMPARTS': <class 'sqlglot.expressions.TimeFromParts'>, 'TIME_STR_TO_DATE': <class 'sqlglot.expressions.TimeStrToDate'>, 'TIME_STR_TO_TIME': <class 'sqlglot.expressions.TimeStrToTime'>, 'TIME_STR_TO_UNIX': <class 'sqlglot.expressions.TimeStrToUnix'>, 'TIME_SUB': <class 'sqlglot.expressions.TimeSub'>, 'TIME_TO_STR': <class 'sqlglot.expressions.TimeToStr'>, 'TIME_TO_TIME_STR': <class 'sqlglot.expressions.TimeToTimeStr'>, 'TIME_TO_UNIX': <class 'sqlglot.expressions.TimeToUnix'>, 'TIME_TRUNC': <class 'sqlglot.expressions.TimeTrunc'>, 'TIMESTAMP': <class 'sqlglot.expressions.Timestamp'>, 'TIMESTAMP_ADD': <class 'sqlglot.expressions.TimestampAdd'>, 'TIMESTAMPDIFF': <class 'sqlglot.expressions.TimestampDiff'>, 'TIMESTAMP_DIFF': <class 'sqlglot.expressions.TimestampDiff'>, 'TIMESTAMP_FROM_PARTS': <class 'sqlglot.expressions.TimestampFromParts'>, 'TIMESTAMPFROMPARTS': <class 'sqlglot.expressions.TimestampFromParts'>, 'TIMESTAMP_SUB': <class 'sqlglot.expressions.TimestampSub'>, 'TIMESTAMP_TRUNC': <class 'sqlglot.expressions.TimestampTrunc'>, 'TO_ARRAY': <class 'sqlglot.expressions.ToArray'>, 'TO_BASE64': <class 'sqlglot.expressions.ToBase64'>, 'TO_CHAR': <class 'sqlglot.expressions.ToChar'>, 'TO_DAYS': <class 'sqlglot.expressions.ToDays'>, 'TO_MAP': <class 'sqlglot.expressions.ToMap'>, 'TO_NUMBER': <class 'sqlglot.expressions.ToNumber'>, 'TRANSFORM': <class 'sqlglot.expressions.Transform'>, 'TRIM': <class 'sqlglot.expressions.Trim'>, 'TRY': <class 'sqlglot.expressions.Try'>, 'TRY_CAST': <class 'sqlglot.expressions.TryCast'>, 'TS_OR_DI_TO_DI': <class 'sqlglot.expressions.TsOrDiToDi'>, 'TS_OR_DS_ADD': <class 'sqlglot.expressions.TsOrDsAdd'>, 'TS_OR_DS_DIFF': <class 'sqlglot.expressions.TsOrDsDiff'>, 'TS_OR_DS_TO_DATE': <class 'sqlglot.expressions.TsOrDsToDate'>, 'TS_OR_DS_TO_DATE_STR': <class 'sqlglot.expressions.TsOrDsToDateStr'>, 'TS_OR_DS_TO_TIME': <class 'sqlglot.expressions.TsOrDsToTime'>, 'TS_OR_DS_TO_TIMESTAMP': <class 'sqlglot.expressions.TsOrDsToTimestamp'>, 'UNHEX': <class 'sqlglot.expressions.Unhex'>, 'UNIX_DATE': <class 'sqlglot.expressions.UnixDate'>, 'UNIX_TO_STR': <class 'sqlglot.expressions.UnixToStr'>, 'UNIX_TO_TIME': <class 'sqlglot.expressions.UnixToTime'>, 'UNIX_TO_TIME_STR': <class 'sqlglot.expressions.UnixToTimeStr'>, 'UPPER': <class 'sqlglot.expressions.Upper'>, 'UCASE': <class 'sqlglot.expressions.Upper'>, 'VAR_MAP': <class 'sqlglot.expressions.VarMap'>, 'VARIANCE': <class 'sqlglot.expressions.Variance'>, 'VARIANCE_SAMP': <class 'sqlglot.expressions.Variance'>, 'VAR_SAMP': <class 'sqlglot.expressions.Variance'>, 'VARIANCE_POP': <class 'sqlglot.expressions.VariancePop'>, 'VAR_POP': <class 'sqlglot.expressions.VariancePop'>, 'WEEK': <class 'sqlglot.expressions.Week'>, 'WEEK_OF_YEAR': <class 'sqlglot.expressions.WeekOfYear'>, 'WEEKOFYEAR': <class 'sqlglot.expressions.WeekOfYear'>, 'WHEN': <class 'sqlglot.expressions.When'>, 'X_M_L_TABLE': <class 'sqlglot.expressions.XMLTable'>, 'XOR': <class 'sqlglot.expressions.Xor'>, 'YEAR': <class 'sqlglot.expressions.Year'>}"}, "sqlglot.expressions.JSON_PATH_PARTS": {"fullname": "sqlglot.expressions.JSON_PATH_PARTS", "modulename": "sqlglot.expressions", "qualname": "JSON_PATH_PARTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "[<class 'sqlglot.expressions.JSONPathFilter'>, <class 'sqlglot.expressions.JSONPathKey'>, <class 'sqlglot.expressions.JSONPathRecursive'>, <class 'sqlglot.expressions.JSONPathRoot'>, <class 'sqlglot.expressions.JSONPathScript'>, <class 'sqlglot.expressions.JSONPathSelector'>, <class 'sqlglot.expressions.JSONPathSlice'>, <class 'sqlglot.expressions.JSONPathSubscript'>, <class 'sqlglot.expressions.JSONPathUnion'>, <class 'sqlglot.expressions.JSONPathWildcard'>]"}, "sqlglot.expressions.PERCENTILES": {"fullname": "sqlglot.expressions.PERCENTILES", "modulename": "sqlglot.expressions", "qualname": "PERCENTILES", "kind": "variable", "doc": "<p></p>\n", "default_value": "(<class 'sqlglot.expressions.PercentileCont'>, <class 'sqlglot.expressions.PercentileDisc'>)"}, "sqlglot.expressions.maybe_parse": {"fullname": "sqlglot.expressions.maybe_parse", "modulename": "sqlglot.expressions", "qualname": "maybe_parse", "kind": "function", "doc": "<p>Gracefully handle a possible string or expression.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">maybe_parse</span><span class=\"p\">(</span><span class=\"s2\">"1"</span><span class=\"p\">)</span>\n<span class=\"go\">Literal(this=1, is_string=False)</span>\n<span class=\"gp\">>>> </span><span class=\"n\">maybe_parse</span><span class=\"p\">(</span><span class=\"n\">to_identifier</span><span class=\"p\">(</span><span class=\"s2\">"x"</span><span class=\"p\">))</span>\n<span class=\"go\">Identifier(this=x, quoted=False)</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>sql_or_expression:</strong> the SQL code string or an expression</li>\n<li><strong>into:</strong> the SQLGlot Expression to parse into</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expressions (in the case that an\ninput expression is a SQL string).</li>\n<li><strong>prefix:</strong> a string to prefix the sql with before it gets parsed\n(automatically includes a space)</li>\n<li><strong>copy:</strong> whether to copy the expression.</li>\n<li><strong>**opts:</strong> other options to use to parse the input expressions (again, in the case\nthat an input expression is a SQL string).</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>Expression: the parsed or given expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">sql_or_expression</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"o\">*</span>,</span><span class=\"param\">\t<span class=\"n\">into</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">],</span> <span class=\"n\">Collection</span><span class=\"p\">[</span><span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]]],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">prefix</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.maybe_copy": {"fullname": "sqlglot.expressions.maybe_copy", "modulename": "sqlglot.expressions", "qualname": "maybe_copy", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">instance</span>, </span><span class=\"param\"><span class=\"n\">copy</span><span class=\"o\">=</span><span class=\"kc\">True</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.expressions.union": {"fullname": "sqlglot.expressions.union", "modulename": "sqlglot.expressions", "qualname": "union", "kind": "function", "doc": "<p>Initializes a syntax tree from one UNION expression.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">union</span><span class=\"p\">(</span><span class=\"s2\">"SELECT * FROM foo"</span><span class=\"p\">,</span> <span class=\"s2\">"SELECT * FROM bla"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT * FROM foo UNION SELECT * FROM bla'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>left:</strong> the SQL code string corresponding to the left-hand side.\nIf an <code>Expression</code> instance is passed, it will be used as-is.</li>\n<li><strong>right:</strong> the SQL code string corresponding to the right-hand side.\nIf an <code>Expression</code> instance is passed, it will be used as-is.</li>\n<li><strong>distinct:</strong> set the DISTINCT flag if and only if this is true.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expression.</li>\n<li><strong>copy:</strong> whether to copy the expression.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The new Union instance.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">left</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">right</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">distinct</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Union</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.intersect": {"fullname": "sqlglot.expressions.intersect", "modulename": "sqlglot.expressions", "qualname": "intersect", "kind": "function", "doc": "<p>Initializes a syntax tree from one INTERSECT expression.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">intersect</span><span class=\"p\">(</span><span class=\"s2\">"SELECT * FROM foo"</span><span class=\"p\">,</span> <span class=\"s2\">"SELECT * FROM bla"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT * FROM foo INTERSECT SELECT * FROM bla'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>left:</strong> the SQL code string corresponding to the left-hand side.\nIf an <code>Expression</code> instance is passed, it will be used as-is.</li>\n<li><strong>right:</strong> the SQL code string corresponding to the right-hand side.\nIf an <code>Expression</code> instance is passed, it will be used as-is.</li>\n<li><strong>distinct:</strong> set the DISTINCT flag if and only if this is true.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expression.</li>\n<li><strong>copy:</strong> whether to copy the expression.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The new Intersect instance.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">left</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">right</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">distinct</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Intersect</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.except_": {"fullname": "sqlglot.expressions.except_", "modulename": "sqlglot.expressions", "qualname": "except_", "kind": "function", "doc": "<p>Initializes a syntax tree from one EXCEPT expression.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">except_</span><span class=\"p\">(</span><span class=\"s2\">"SELECT * FROM foo"</span><span class=\"p\">,</span> <span class=\"s2\">"SELECT * FROM bla"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT * FROM foo EXCEPT SELECT * FROM bla'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>left:</strong> the SQL code string corresponding to the left-hand side.\nIf an <code>Expression</code> instance is passed, it will be used as-is.</li>\n<li><strong>right:</strong> the SQL code string corresponding to the right-hand side.\nIf an <code>Expression</code> instance is passed, it will be used as-is.</li>\n<li><strong>distinct:</strong> set the DISTINCT flag if and only if this is true.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expression.</li>\n<li><strong>copy:</strong> whether to copy the expression.</li>\n<li><strong>opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The new Except instance.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">left</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">right</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">distinct</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Except</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.select": {"fullname": "sqlglot.expressions.select", "modulename": "sqlglot.expressions", "qualname": "select", "kind": "function", "doc": "<p>Initializes a syntax tree from one or multiple SELECT expressions.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"col1"</span><span class=\"p\">,</span> <span class=\"s2\">"col2"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">from_</span><span class=\"p\">(</span><span class=\"s2\">"tbl"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT col1, col2 FROM tbl'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>*expressions:</strong> the SQL code string to parse as the expressions of a\nSELECT statement. If an Expression instance is passed, this is used as-is.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expressions (in the case that an\ninput expression is a SQL string).</li>\n<li><strong>**opts:</strong> other options to use to parse the input expressions (again, in the case\nthat an input expression is a SQL string).</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>Select: the syntax tree for the SELECT statement.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Select</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.from_": {"fullname": "sqlglot.expressions.from_", "modulename": "sqlglot.expressions", "qualname": "from_", "kind": "function", "doc": "<p>Initializes a syntax tree from a FROM expression.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">from_</span><span class=\"p\">(</span><span class=\"s2\">"tbl"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"col1"</span><span class=\"p\">,</span> <span class=\"s2\">"col2"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT col1, col2 FROM tbl'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>*expression:</strong> the SQL code string to parse as the FROM expressions of a\nSELECT statement. If an Expression instance is passed, this is used as-is.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expression (in the case that the\ninput expression is a SQL string).</li>\n<li><strong>**opts:</strong> other options to use to parse the input expressions (again, in the case\nthat the input expression is a SQL string).</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>Select: the syntax tree for the SELECT statement.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Select</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.update": {"fullname": "sqlglot.expressions.update", "modulename": "sqlglot.expressions", "qualname": "update", "kind": "function", "doc": "<p>Creates an update statement.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">update</span><span class=\"p\">(</span><span class=\"s2\">"my_table"</span><span class=\"p\">,</span> <span class=\"p\">{</span><span class=\"s2\">"x"</span><span class=\"p\">:</span> <span class=\"mi\">1</span><span class=\"p\">,</span> <span class=\"s2\">"y"</span><span class=\"p\">:</span> <span class=\"s2\">"2"</span><span class=\"p\">,</span> <span class=\"s2\">"z"</span><span class=\"p\">:</span> <span class=\"kc\">None</span><span class=\"p\">},</span> <span class=\"n\">from_</span><span class=\"o\">=</span><span class=\"s2\">"baz"</span><span class=\"p\">,</span> <span class=\"n\">where</span><span class=\"o\">=</span><span class=\"s2\">"id > 1"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">"UPDATE my_table SET x = 1, y = '2', z = NULL FROM baz WHERE id > 1"</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>*properties:</strong> dictionary of properties to set which are\nauto converted to sql objects eg None -> NULL</li>\n<li><strong>where:</strong> sql conditional parsed into a WHERE statement</li>\n<li><strong>from_:</strong> sql statement parsed into a FROM statement</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expressions.</li>\n<li><strong>**opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>Update: the syntax tree for the UPDATE statement.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">table</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Table</span>,</span><span class=\"param\">\t<span class=\"n\">properties</span><span class=\"p\">:</span> <span class=\"nb\">dict</span>,</span><span class=\"param\">\t<span class=\"n\">where</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">from_</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Update</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.delete": {"fullname": "sqlglot.expressions.delete", "modulename": "sqlglot.expressions", "qualname": "delete", "kind": "function", "doc": "<p>Builds a delete statement.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">delete</span><span class=\"p\">(</span><span class=\"s2\">"my_table"</span><span class=\"p\">,</span> <span class=\"n\">where</span><span class=\"o\">=</span><span class=\"s2\">"id > 1"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'DELETE FROM my_table WHERE id > 1'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>where:</strong> sql conditional parsed into a WHERE statement</li>\n<li><strong>returning:</strong> sql conditional parsed into a RETURNING statement</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expressions.</li>\n<li><strong>**opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>Delete: the syntax tree for the DELETE statement.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">table</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">where</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">returning</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Delete</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.insert": {"fullname": "sqlglot.expressions.insert", "modulename": "sqlglot.expressions", "qualname": "insert", "kind": "function", "doc": "<p>Builds an INSERT statement.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">insert</span><span class=\"p\">(</span><span class=\"s2\">"VALUES (1, 2, 3)"</span><span class=\"p\">,</span> <span class=\"s2\">"tbl"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'INSERT INTO tbl VALUES (1, 2, 3)'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> the sql string or expression of the INSERT statement</li>\n<li><strong>into:</strong> the tbl to insert data to.</li>\n<li><strong>columns:</strong> optionally the table's column names.</li>\n<li><strong>overwrite:</strong> whether to INSERT OVERWRITE or not.</li>\n<li><strong>returning:</strong> sql conditional parsed into a RETURNING statement</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expressions.</li>\n<li><strong>copy:</strong> whether to copy the expression.</li>\n<li><strong>**opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>Insert: the syntax tree for the INSERT statement.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">into</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">columns</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Sequence</span><span class=\"p\">[</span><span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Identifier</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">overwrite</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">bool</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">returning</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Insert</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.condition": {"fullname": "sqlglot.expressions.condition", "modulename": "sqlglot.expressions", "qualname": "condition", "kind": "function", "doc": "<p>Initialize a logical condition expression.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">condition</span><span class=\"p\">(</span><span class=\"s2\">"x=1"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'x = 1'</span>\n</code></pre>\n </div>\n \n <p>This is helpful for composing larger logical syntax trees:</p>\n \n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">where</span> <span class=\"o\">=</span> <span class=\"n\">condition</span><span class=\"p\">(</span><span class=\"s2\">"x=1"</span><span class=\"p\">)</span>\n<span class=\"gp\">>>> </span><span class=\"n\">where</span> <span class=\"o\">=</span> <span class=\"n\">where</span><span class=\"o\">.</span><span class=\"n\">and_</span><span class=\"p\">(</span><span class=\"s2\">"y=1"</span><span class=\"p\">)</span>\n<span class=\"gp\">>>> </span><span class=\"n\">Select</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">from_</span><span class=\"p\">(</span><span class=\"s2\">"tbl"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s2\">"*"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">where</span><span class=\"p\">(</span><span class=\"n\">where</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT * FROM tbl WHERE x = 1 AND y = 1'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>*expression:</strong> the SQL code string to parse.\nIf an Expression instance is passed, this is used as-is.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expression (in the case that the\ninput expression is a SQL string).</li>\n<li><strong>copy:</strong> Whether to copy <code>expression</code> (only applies to expressions).</li>\n<li><strong>**opts:</strong> other options to use to parse the input expressions (again, in the case\nthat the input expression is a SQL string).</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The new Condition instance</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Condition</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.and_": {"fullname": "sqlglot.expressions.and_", "modulename": "sqlglot.expressions", "qualname": "and_", "kind": "function", "doc": "<p>Combine multiple conditions with an AND logical operator.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">and_</span><span class=\"p\">(</span><span class=\"s2\">"x=1"</span><span class=\"p\">,</span> <span class=\"n\">and_</span><span class=\"p\">(</span><span class=\"s2\">"y=1"</span><span class=\"p\">,</span> <span class=\"s2\">"z=1"</span><span class=\"p\">))</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'x = 1 AND (y = 1 AND z = 1)'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>*expressions:</strong> the SQL code strings to parse.\nIf an Expression instance is passed, this is used as-is.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expression.</li>\n<li><strong>copy:</strong> whether to copy <code>expressions</code> (only applies to Expressions).</li>\n<li><strong>**opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The new condition</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Condition</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.or_": {"fullname": "sqlglot.expressions.or_", "modulename": "sqlglot.expressions", "qualname": "or_", "kind": "function", "doc": "<p>Combine multiple conditions with an OR logical operator.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">or_</span><span class=\"p\">(</span><span class=\"s2\">"x=1"</span><span class=\"p\">,</span> <span class=\"n\">or_</span><span class=\"p\">(</span><span class=\"s2\">"y=1"</span><span class=\"p\">,</span> <span class=\"s2\">"z=1"</span><span class=\"p\">))</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'x = 1 OR (y = 1 OR z = 1)'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>*expressions:</strong> the SQL code strings to parse.\nIf an Expression instance is passed, this is used as-is.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expression.</li>\n<li><strong>copy:</strong> whether to copy <code>expressions</code> (only applies to Expressions).</li>\n<li><strong>**opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The new condition</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Condition</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.xor": {"fullname": "sqlglot.expressions.xor", "modulename": "sqlglot.expressions", "qualname": "xor", "kind": "function", "doc": "<p>Combine multiple conditions with an XOR logical operator.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">xor</span><span class=\"p\">(</span><span class=\"s2\">"x=1"</span><span class=\"p\">,</span> <span class=\"n\">xor</span><span class=\"p\">(</span><span class=\"s2\">"y=1"</span><span class=\"p\">,</span> <span class=\"s2\">"z=1"</span><span class=\"p\">))</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'x = 1 XOR (y = 1 XOR z = 1)'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>*expressions:</strong> the SQL code strings to parse.\nIf an Expression instance is passed, this is used as-is.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expression.</li>\n<li><strong>copy:</strong> whether to copy <code>expressions</code> (only applies to Expressions).</li>\n<li><strong>**opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The new condition</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Condition</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.not_": {"fullname": "sqlglot.expressions.not_", "modulename": "sqlglot.expressions", "qualname": "not_", "kind": "function", "doc": "<p>Wrap a condition with a NOT operator.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">not_</span><span class=\"p\">(</span><span class=\"s2\">"this_suit='black'"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">"NOT this_suit = 'black'"</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> the SQL code string to parse.\nIf an Expression instance is passed, this is used as-is.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expression.</li>\n<li><strong>copy:</strong> whether to copy the expression or not.</li>\n<li><strong>**opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The new condition.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Not</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.paren": {"fullname": "sqlglot.expressions.paren", "modulename": "sqlglot.expressions", "qualname": "paren", "kind": "function", "doc": "<p>Wrap an expression in parentheses.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">paren</span><span class=\"p\">(</span><span class=\"s2\">"5 + 3"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'(5 + 3)'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> the SQL code string to parse.\nIf an Expression instance is passed, this is used as-is.</li>\n<li><strong>copy:</strong> whether to copy the expression or not.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The wrapped expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Paren</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.SAFE_IDENTIFIER_RE": {"fullname": "sqlglot.expressions.SAFE_IDENTIFIER_RE", "modulename": "sqlglot.expressions", "qualname": "SAFE_IDENTIFIER_RE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Pattern[str]", "default_value": "re.compile('^[_a-zA-Z][\\\\w]*$')"}, "sqlglot.expressions.to_identifier": {"fullname": "sqlglot.expressions.to_identifier", "modulename": "sqlglot.expressions", "qualname": "to_identifier", "kind": "function", "doc": "<p>Builds an identifier.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>name:</strong> The name to turn into an identifier.</li>\n<li><strong>quoted:</strong> Whether to force quote the identifier.</li>\n<li><strong>copy:</strong> Whether to copy name if it's an Identifier.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The identifier ast node.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">name</span>, </span><span class=\"param\"><span class=\"n\">quoted</span><span class=\"o\">=</span><span class=\"kc\">None</span>, </span><span class=\"param\"><span class=\"n\">copy</span><span class=\"o\">=</span><span class=\"kc\">True</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.expressions.parse_identifier": {"fullname": "sqlglot.expressions.parse_identifier", "modulename": "sqlglot.expressions", "qualname": "parse_identifier", "kind": "function", "doc": "<p>Parses a given string into an identifier.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>name:</strong> The name to parse into an identifier.</li>\n<li><strong>dialect:</strong> The dialect to parse against.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The identifier ast node.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">name</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Identifier</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Identifier</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.INTERVAL_STRING_RE": {"fullname": "sqlglot.expressions.INTERVAL_STRING_RE", "modulename": "sqlglot.expressions", "qualname": "INTERVAL_STRING_RE", "kind": "variable", "doc": "<p></p>\n", "default_value": "re.compile('\\\\s*([0-9]+)\\\\s*([a-zA-Z]+)\\\\s*')"}, "sqlglot.expressions.to_interval": {"fullname": "sqlglot.expressions.to_interval", "modulename": "sqlglot.expressions", "qualname": "to_interval", "kind": "function", "doc": "<p>Builds an interval expression from a string like '1 day' or '5 months'.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">interval</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Literal</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Interval</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.to_table": {"fullname": "sqlglot.expressions.to_table", "modulename": "sqlglot.expressions", "qualname": "to_table", "kind": "function", "doc": "<p>Create a table expression from a <code>[catalog].[schema].[table]</code> sql path. Catalog and schema are optional.\nIf a table is passed in then that table is returned.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>sql_path:</strong> a <code>[catalog].[schema].[table]</code> string.</li>\n<li><strong>dialect:</strong> the source dialect according to which the table name will be parsed.</li>\n<li><strong>copy:</strong> Whether to copy a table if it is passed in.</li>\n<li><strong>kwargs:</strong> the kwargs to instantiate the resulting <code>Table</code> expression with.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>A table expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">sql_path</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Table</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Table</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.to_column": {"fullname": "sqlglot.expressions.to_column", "modulename": "sqlglot.expressions", "qualname": "to_column", "kind": "function", "doc": "<p>Create a column from a <code>[table].[column]</code> sql path. Table is optional.\nIf a column is passed in then that column is returned.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>sql_path:</strong> a <code>[table].[column]</code> string.</li>\n<li><strong>quoted:</strong> Whether or not to force quote identifiers.</li>\n<li><strong>dialect:</strong> the source dialect according to which the column name will be parsed.</li>\n<li><strong>copy:</strong> Whether to copy a column if it is passed in.</li>\n<li><strong>kwargs:</strong> the kwargs to instantiate the resulting <code>Column</code> expression with.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>A column expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">sql_path</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Column</span>,</span><span class=\"param\">\t<span class=\"n\">quoted</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">bool</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Column</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.alias_": {"fullname": "sqlglot.expressions.alias_", "modulename": "sqlglot.expressions", "qualname": "alias_", "kind": "function", "doc": "<p>Create an Alias expression.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">alias_</span><span class=\"p\">(</span><span class=\"s1\">'foo'</span><span class=\"p\">,</span> <span class=\"s1\">'bar'</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'foo AS bar'</span>\n</code></pre>\n </div>\n \n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">alias_</span><span class=\"p\">(</span><span class=\"s1\">'(select 1, 2)'</span><span class=\"p\">,</span> <span class=\"s1\">'bar'</span><span class=\"p\">,</span> <span class=\"n\">table</span><span class=\"o\">=</span><span class=\"p\">[</span><span class=\"s1\">'a'</span><span class=\"p\">,</span> <span class=\"s1\">'b'</span><span class=\"p\">])</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'(SELECT 1, 2) AS bar(a, b)'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> the SQL code strings to parse.\nIf an Expression instance is passed, this is used as-is.</li>\n<li><strong>alias:</strong> the alias name to use. If the name has\nspecial characters it is quoted.</li>\n<li><strong>table:</strong> Whether to create a table alias, can also be a list of columns.</li>\n<li><strong>quoted:</strong> whether to quote the alias</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expression.</li>\n<li><strong>copy:</strong> Whether to copy the expression.</li>\n<li><strong>**opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>Alias: the aliased expression</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">alias</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Identifier</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">table</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">bool</span><span class=\"p\">,</span> <span class=\"n\">Sequence</span><span class=\"p\">[</span><span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Identifier</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"kc\">False</span>,</span><span class=\"param\">\t<span class=\"n\">quoted</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">bool</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.expressions.subquery": {"fullname": "sqlglot.expressions.subquery", "modulename": "sqlglot.expressions", "qualname": "subquery", "kind": "function", "doc": "<p>Build a subquery expression that's selected from.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">subquery</span><span class=\"p\">(</span><span class=\"s1\">'select x from tbl'</span><span class=\"p\">,</span> <span class=\"s1\">'bar'</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">select</span><span class=\"p\">(</span><span class=\"s1\">'x'</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT x FROM (SELECT x FROM tbl) AS bar'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> the SQL code strings to parse.\nIf an Expression instance is passed, this is used as-is.</li>\n<li><strong>alias:</strong> the alias name to use.</li>\n<li><strong>dialect:</strong> the dialect used to parse the input expression.</li>\n<li><strong>**opts:</strong> other options to use to parse the input expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>A new Select instance with the subquery expression included.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">alias</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Identifier</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Select</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.column": {"fullname": "sqlglot.expressions.column", "modulename": "sqlglot.expressions", "qualname": "column", "kind": "function", "doc": "<p>Build a Column.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>col:</strong> Column name.</li>\n<li><strong>table:</strong> Table name.</li>\n<li><strong>db:</strong> Database name.</li>\n<li><strong>catalog:</strong> Catalog name.</li>\n<li><strong>fields:</strong> Additional fields using dots.</li>\n<li><strong>quoted:</strong> Whether to force quotes on the column's identifiers.</li>\n<li><strong>copy:</strong> Whether to copy identifiers if passed in.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The new Column instance.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">col</span>,</span><span class=\"param\">\t<span class=\"n\">table</span><span class=\"o\">=</span><span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">db</span><span class=\"o\">=</span><span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">catalog</span><span class=\"o\">=</span><span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"o\">*</span>,</span><span class=\"param\">\t<span class=\"n\">fields</span><span class=\"o\">=</span><span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">quoted</span><span class=\"o\">=</span><span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"o\">=</span><span class=\"kc\">True</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.expressions.cast": {"fullname": "sqlglot.expressions.cast", "modulename": "sqlglot.expressions", "qualname": "cast", "kind": "function", "doc": "<p>Cast an expression to a data type.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">cast</span><span class=\"p\">(</span><span class=\"s1\">'x + 1'</span><span class=\"p\">,</span> <span class=\"s1\">'int'</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'CAST(x + 1 AS INT)'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> The expression to cast.</li>\n<li><strong>to:</strong> The datatype to cast to.</li>\n<li><strong>copy:</strong> Whether to copy the supplied expressions.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The new Cast instance.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">to</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Cast</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.table_": {"fullname": "sqlglot.expressions.table_", "modulename": "sqlglot.expressions", "qualname": "table_", "kind": "function", "doc": "<p>Build a Table.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>table:</strong> Table name.</li>\n<li><strong>db:</strong> Database name.</li>\n<li><strong>catalog:</strong> Catalog name.</li>\n<li><strong>quote:</strong> Whether to force quotes on the table's identifiers.</li>\n<li><strong>alias:</strong> Table's alias.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The new Table instance.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">table</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Identifier</span> <span class=\"o\">|</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">db</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Identifier</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">catalog</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Identifier</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">quoted</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">bool</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">alias</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Identifier</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Table</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.values": {"fullname": "sqlglot.expressions.values", "modulename": "sqlglot.expressions", "qualname": "values", "kind": "function", "doc": "<p>Build VALUES statement.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">values</span><span class=\"p\">([(</span><span class=\"mi\">1</span><span class=\"p\">,</span> <span class=\"s1\">'2'</span><span class=\"p\">)])</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">"VALUES (1, '2')"</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>values:</strong> values statements that will be converted to SQL</li>\n<li><strong>alias:</strong> optional alias</li>\n<li><strong>columns:</strong> Optional list of ordered column names or ordered dictionary of column names to types.\nIf either are provided then an alias is also required.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>Values: the Values expression object</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">values</span><span class=\"p\">:</span> <span class=\"n\">Iterable</span><span class=\"p\">[</span><span class=\"n\">Tuple</span><span class=\"p\">[</span><span class=\"n\">Any</span><span class=\"p\">,</span> <span class=\"o\">...</span><span class=\"p\">]]</span>,</span><span class=\"param\">\t<span class=\"n\">alias</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">columns</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">Iterable</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">],</span> <span class=\"n\">Dict</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Values</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.var": {"fullname": "sqlglot.expressions.var", "modulename": "sqlglot.expressions", "qualname": "var", "kind": "function", "doc": "<p>Build a SQL variable.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"nb\">repr</span><span class=\"p\">(</span><span class=\"n\">var</span><span class=\"p\">(</span><span class=\"s1\">'x'</span><span class=\"p\">))</span>\n<span class=\"go\">'Var(this=x)'</span>\n</code></pre>\n </div>\n \n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"nb\">repr</span><span class=\"p\">(</span><span class=\"n\">var</span><span class=\"p\">(</span><span class=\"n\">column</span><span class=\"p\">(</span><span class=\"s1\">'x'</span><span class=\"p\">,</span> <span class=\"n\">table</span><span class=\"o\">=</span><span class=\"s1\">'y'</span><span class=\"p\">)))</span>\n<span class=\"go\">'Var(this=x)'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>name:</strong> The name of the var or an expression who's name will become the var.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The new variable node.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">name</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Var</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.rename_table": {"fullname": "sqlglot.expressions.rename_table", "modulename": "sqlglot.expressions", "qualname": "rename_table", "kind": "function", "doc": "<p>Build ALTER TABLE... RENAME... expression</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>old_name:</strong> The old name of the table</li>\n<li><strong>new_name:</strong> The new name of the table</li>\n<li><strong>dialect:</strong> The dialect to parse the table.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>Alter table expression</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">old_name</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Table</span>,</span><span class=\"param\">\t<span class=\"n\">new_name</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Table</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">AlterTable</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.rename_column": {"fullname": "sqlglot.expressions.rename_column", "modulename": "sqlglot.expressions", "qualname": "rename_column", "kind": "function", "doc": "<p>Build ALTER TABLE... RENAME COLUMN... expression</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>table_name:</strong> Name of the table</li>\n<li><strong>old_column:</strong> The old name of the column</li>\n<li><strong>new_column:</strong> The new name of the column</li>\n<li><strong>exists:</strong> Whether to add the <code>IF EXISTS</code> clause</li>\n<li><strong>dialect:</strong> The dialect to parse the table/column.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>Alter table expression</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">table_name</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Table</span>,</span><span class=\"param\">\t<span class=\"n\">old_column_name</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Column</span>,</span><span class=\"param\">\t<span class=\"n\">new_column_name</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Column</span>,</span><span class=\"param\">\t<span class=\"n\">exists</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">bool</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">AlterTable</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.convert": {"fullname": "sqlglot.expressions.convert", "modulename": "sqlglot.expressions", "qualname": "convert", "kind": "function", "doc": "<p>Convert a python value into an expression object.</p>\n\n<p>Raises an error if a conversion is not possible.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>value:</strong> A python object.</li>\n<li><strong>copy:</strong> Whether to copy <code>value</code> (only applies to Expressions and collections).</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The equivalent expression object.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">value</span><span class=\"p\">:</span> <span class=\"n\">Any</span>, </span><span class=\"param\"><span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.replace_children": {"fullname": "sqlglot.expressions.replace_children", "modulename": "sqlglot.expressions", "qualname": "replace_children", "kind": "function", "doc": "<p>Replace children of an expression with the result of a lambda fun(child) -> exp.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">fun</span><span class=\"p\">:</span> <span class=\"n\">Callable</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">args</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.replace_tree": {"fullname": "sqlglot.expressions.replace_tree", "modulename": "sqlglot.expressions", "qualname": "replace_tree", "kind": "function", "doc": "<p>Replace an entire tree with the result of function calls on each node.</p>\n\n<p>This will be traversed in reverse dfs, so leaves first.\nIf new nodes are created as a result of function calls, they will also be traversed.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">fun</span><span class=\"p\">:</span> <span class=\"n\">Callable</span>,</span><span class=\"param\">\t<span class=\"n\">prune</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">],</span> <span class=\"nb\">bool</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.column_table_names": {"fullname": "sqlglot.expressions.column_table_names", "modulename": "sqlglot.expressions", "qualname": "column_table_names", "kind": "function", "doc": "<p>Return all table names referenced through columns in an expression.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"gp\">>>> </span><span class=\"nb\">sorted</span><span class=\"p\">(</span><span class=\"n\">column_table_names</span><span class=\"p\">(</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"a.b AND c.d AND c.e"</span><span class=\"p\">)))</span>\n<span class=\"go\">['a', 'c']</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> expression to find table names.</li>\n<li><strong>exclude:</strong> a table name to exclude</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>A list of unique names.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">exclude</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">''</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Set</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.table_name": {"fullname": "sqlglot.expressions.table_name", "modulename": "sqlglot.expressions", "qualname": "table_name", "kind": "function", "doc": "<p>Get the full name of a table as a string.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>table:</strong> Table expression node or string.</li>\n<li><strong>dialect:</strong> The dialect to generate the table name for.</li>\n<li><strong>identify:</strong> Determines when an identifier should be quoted. Possible values are:\nFalse (default): Never quote, except in cases where it's mandatory by the dialect.\nTrue: Always quote.</li>\n</ul>\n\n<h6 id=\"examples\">Examples:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">exp</span><span class=\"p\">,</span> <span class=\"n\">parse_one</span>\n<span class=\"gp\">>>> </span><span class=\"n\">table_name</span><span class=\"p\">(</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"select * from a.b.c"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">find</span><span class=\"p\">(</span><span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">Table</span><span class=\"p\">))</span>\n<span class=\"go\">'a.b.c'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The table name.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">table</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Table</span> <span class=\"o\">|</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">identify</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.normalize_table_name": {"fullname": "sqlglot.expressions.normalize_table_name", "modulename": "sqlglot.expressions", "qualname": "normalize_table_name", "kind": "function", "doc": "<p>Returns a case normalized table name without quotes.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>table:</strong> the table to normalize</li>\n<li><strong>dialect:</strong> the dialect to use for normalization rules</li>\n<li><strong>copy:</strong> whether to copy the expression.</li>\n</ul>\n\n<h6 id=\"examples\">Examples:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">normalize_table_name</span><span class=\"p\">(</span><span class=\"s2\">"`A-B`.c"</span><span class=\"p\">,</span> <span class=\"n\">dialect</span><span class=\"o\">=</span><span class=\"s2\">"bigquery"</span><span class=\"p\">)</span>\n<span class=\"go\">'A-B.c'</span>\n</code></pre>\n </div>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">table</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Table</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.replace_tables": {"fullname": "sqlglot.expressions.replace_tables", "modulename": "sqlglot.expressions", "qualname": "replace_tables", "kind": "function", "doc": "<p>Replace all tables in expression according to the mapping.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> expression node to be transformed and replaced.</li>\n<li><strong>mapping:</strong> mapping of table names.</li>\n<li><strong>dialect:</strong> the dialect of the mapping table</li>\n<li><strong>copy:</strong> whether to copy the expression.</li>\n</ul>\n\n<h6 id=\"examples\">Examples:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">exp</span><span class=\"p\">,</span> <span class=\"n\">parse_one</span>\n<span class=\"gp\">>>> </span><span class=\"n\">replace_tables</span><span class=\"p\">(</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"select * from a.b"</span><span class=\"p\">),</span> <span class=\"p\">{</span><span class=\"s2\">"a.b"</span><span class=\"p\">:</span> <span class=\"s2\">"c"</span><span class=\"p\">})</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT * FROM c /* a.b */'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The mapped expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"o\">~</span><span class=\"n\">E</span>,</span><span class=\"param\">\t<span class=\"n\">mapping</span><span class=\"p\">:</span> <span class=\"n\">Dict</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"o\">~</span><span class=\"n\">E</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.replace_placeholders": {"fullname": "sqlglot.expressions.replace_placeholders", "modulename": "sqlglot.expressions", "qualname": "replace_placeholders", "kind": "function", "doc": "<p>Replace placeholders in an expression.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> expression node to be transformed and replaced.</li>\n<li><strong>args:</strong> positional names that will substitute unnamed placeholders in the given order.</li>\n<li><strong>kwargs:</strong> keyword arguments that will substitute named placeholders.</li>\n</ul>\n\n<h6 id=\"examples\">Examples:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">exp</span><span class=\"p\">,</span> <span class=\"n\">parse_one</span>\n<span class=\"gp\">>>> </span><span class=\"n\">replace_placeholders</span><span class=\"p\">(</span>\n<span class=\"gp\">... </span> <span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"select * from :tbl where ? = ?"</span><span class=\"p\">),</span>\n<span class=\"gp\">... </span> <span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">to_identifier</span><span class=\"p\">(</span><span class=\"s2\">"str_col"</span><span class=\"p\">),</span> <span class=\"s2\">"b"</span><span class=\"p\">,</span> <span class=\"n\">tbl</span><span class=\"o\">=</span><span class=\"n\">exp</span><span class=\"o\">.</span><span class=\"n\">to_identifier</span><span class=\"p\">(</span><span class=\"s2\">"foo"</span><span class=\"p\">)</span>\n<span class=\"gp\">... </span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">"SELECT * FROM foo WHERE str_col = 'b'"</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The mapped expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">args</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.expand": {"fullname": "sqlglot.expressions.expand", "modulename": "sqlglot.expressions", "qualname": "expand", "kind": "function", "doc": "<p>Transforms an expression by expanding all referenced sources into subqueries.</p>\n\n<h6 id=\"examples\">Examples:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">parse_one</span>\n<span class=\"gp\">>>> </span><span class=\"n\">expand</span><span class=\"p\">(</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"select * from x AS z"</span><span class=\"p\">),</span> <span class=\"p\">{</span><span class=\"s2\">"x"</span><span class=\"p\">:</span> <span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"select * from y"</span><span class=\"p\">)})</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT * FROM (SELECT * FROM y) AS z /* source: x */'</span>\n</code></pre>\n </div>\n \n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">expand</span><span class=\"p\">(</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"select * from x AS z"</span><span class=\"p\">),</span> <span class=\"p\">{</span><span class=\"s2\">"x"</span><span class=\"p\">:</span> <span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"select * from y"</span><span class=\"p\">),</span> <span class=\"s2\">"y"</span><span class=\"p\">:</span> <span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"select * from z"</span><span class=\"p\">)})</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT * FROM (SELECT * FROM (SELECT * FROM z) AS y /* source: y */) AS z /* source: x */'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> The expression to expand.</li>\n<li><strong>sources:</strong> A dictionary of name to Queries.</li>\n<li><strong>dialect:</strong> The dialect of the sources dict.</li>\n<li><strong>copy:</strong> Whether to copy the expression during transformation. Defaults to True.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The transformed expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">sources</span><span class=\"p\">:</span> <span class=\"n\">Dict</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Query</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.func": {"fullname": "sqlglot.expressions.func", "modulename": "sqlglot.expressions", "qualname": "func", "kind": "function", "doc": "<p>Returns a Func expression.</p>\n\n<h6 id=\"examples\">Examples:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">func</span><span class=\"p\">(</span><span class=\"s2\">"abs"</span><span class=\"p\">,</span> <span class=\"mi\">5</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'ABS(5)'</span>\n</code></pre>\n </div>\n \n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">func</span><span class=\"p\">(</span><span class=\"s2\">"cast"</span><span class=\"p\">,</span> <span class=\"n\">this</span><span class=\"o\">=</span><span class=\"mi\">5</span><span class=\"p\">,</span> <span class=\"n\">to</span><span class=\"o\">=</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">build</span><span class=\"p\">(</span><span class=\"s2\">"DOUBLE"</span><span class=\"p\">))</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'CAST(5 AS DOUBLE)'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>name:</strong> the name of the function to build.</li>\n<li><strong>args:</strong> the args used to instantiate the function of interest.</li>\n<li><strong>copy:</strong> whether to copy the argument expressions.</li>\n<li><strong>dialect:</strong> the source dialect.</li>\n<li><strong>kwargs:</strong> the kwargs used to instantiate the function of interest.</li>\n</ul>\n\n<h6 id=\"note\">Note:</h6>\n\n<blockquote>\n <p>The arguments <code>args</code> and <code>kwargs</code> are mutually exclusive.</p>\n</blockquote>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>An instance of the function of interest, or an anonymous function, if <code>name</code> doesn't\n correspond to an existing <code>sqlglot.expressions.Func</code> class.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">name</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">args</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Func</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.case": {"fullname": "sqlglot.expressions.case", "modulename": "sqlglot.expressions", "qualname": "case", "kind": "function", "doc": "<p>Initialize a CASE statement.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <p>case().when(\"a = 1\", \"foo\").else_(\"bar\")</p>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> Optionally, the input expression (not all dialects support this)</li>\n<li><strong>**opts:</strong> Extra keyword arguments for parsing <code>expression</code></li>\n</ul>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Case</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.array": {"fullname": "sqlglot.expressions.array", "modulename": "sqlglot.expressions", "qualname": "array", "kind": "function", "doc": "<p>Returns an array.</p>\n\n<h6 id=\"examples\">Examples:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">array</span><span class=\"p\">(</span><span class=\"mi\">1</span><span class=\"p\">,</span> <span class=\"s1\">'x'</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'ARRAY(1, x)'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expressions:</strong> the expressions to add to the array.</li>\n<li><strong>copy:</strong> whether to copy the argument expressions.</li>\n<li><strong>dialect:</strong> the source dialect.</li>\n<li><strong>kwargs:</strong> the kwargs used to instantiate the function of interest.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>An array expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Array</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.tuple_": {"fullname": "sqlglot.expressions.tuple_", "modulename": "sqlglot.expressions", "qualname": "tuple_", "kind": "function", "doc": "<p>Returns an tuple.</p>\n\n<h6 id=\"examples\">Examples:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">tuple_</span><span class=\"p\">(</span><span class=\"mi\">1</span><span class=\"p\">,</span> <span class=\"s1\">'x'</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'(1, x)'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expressions:</strong> the expressions to add to the tuple.</li>\n<li><strong>copy:</strong> whether to copy the argument expressions.</li>\n<li><strong>dialect:</strong> the source dialect.</li>\n<li><strong>kwargs:</strong> the kwargs used to instantiate the function of interest.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>A tuple expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Tuple</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.true": {"fullname": "sqlglot.expressions.true", "modulename": "sqlglot.expressions", "qualname": "true", "kind": "function", "doc": "<p>Returns a true Boolean expression.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Boolean</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.false": {"fullname": "sqlglot.expressions.false", "modulename": "sqlglot.expressions", "qualname": "false", "kind": "function", "doc": "<p>Returns a false Boolean expression.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Boolean</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.null": {"fullname": "sqlglot.expressions.null", "modulename": "sqlglot.expressions", "qualname": "null", "kind": "function", "doc": "<p>Returns a Null expression.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Null</span>:</span></span>", "funcdef": "def"}, "sqlglot.expressions.NONNULL_CONSTANTS": {"fullname": "sqlglot.expressions.NONNULL_CONSTANTS", "modulename": "sqlglot.expressions", "qualname": "NONNULL_CONSTANTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "(<class 'sqlglot.expressions.Literal'>, <class 'sqlglot.expressions.Boolean'>)"}, "sqlglot.expressions.CONSTANTS": {"fullname": "sqlglot.expressions.CONSTANTS", "modulename": "sqlglot.expressions", "qualname": "CONSTANTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "(<class 'sqlglot.expressions.Literal'>, <class 'sqlglot.expressions.Boolean'>, <class 'sqlglot.expressions.Null'>)"}, "sqlglot.generator": {"fullname": "sqlglot.generator", "modulename": "sqlglot.generator", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.generator.logger": {"fullname": "sqlglot.generator.logger", "modulename": "sqlglot.generator", "qualname": "logger", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Logger sqlglot (WARNING)>"}, "sqlglot.generator.ESCAPED_UNICODE_RE": {"fullname": "sqlglot.generator.ESCAPED_UNICODE_RE", "modulename": "sqlglot.generator", "qualname": "ESCAPED_UNICODE_RE", "kind": "variable", "doc": "<p></p>\n", "default_value": "re.compile('\\\\\\\\(\\\\d+)')"}, "sqlglot.generator.Generator": {"fullname": "sqlglot.generator.Generator", "modulename": "sqlglot.generator", "qualname": "Generator", "kind": "class", "doc": "<p>Generator converts a given syntax tree to the corresponding SQL string.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>pretty:</strong> Whether to format the produced SQL string.\nDefault: False.</li>\n<li><strong>identify:</strong> Determines when an identifier should be quoted. Possible values are:\nFalse (default): Never quote, except in cases where it's mandatory by the dialect.\nTrue or 'always': Always quote.\n'safe': Only quote identifiers that are case insensitive.</li>\n<li><strong>normalize:</strong> Whether to normalize identifiers to lowercase.\nDefault: False.</li>\n<li><strong>pad:</strong> The pad size in a formatted string. For example, this affects the indentation of\na projection in a query, relative to its nesting level.\nDefault: 2.</li>\n<li><strong>indent:</strong> The indentation size in a formatted string. For example, this affects the\nindentation of subqueries and filters under a <code>WHERE</code> clause.\nDefault: 2.</li>\n<li><strong>normalize_functions:</strong> How to normalize function names. Possible values are:\n\"upper\" or True (default): Convert names to uppercase.\n\"lower\": Convert names to lowercase.\nFalse: Disables function name normalization.</li>\n<li><strong>unsupported_level:</strong> Determines the generator's behavior when it encounters unsupported expressions.\nDefault ErrorLevel.WARN.</li>\n<li><strong>max_unsupported:</strong> Maximum number of unsupported messages to include in a raised UnsupportedError.\nThis is only relevant if unsupported_level is ErrorLevel.RAISE.\nDefault: 3</li>\n<li><strong>leading_comma:</strong> Whether the comma is leading or trailing in select expressions.\nThis is only relevant when generating in pretty mode.\nDefault: False</li>\n<li><strong>max_text_width:</strong> The max number of characters in a segment before creating new lines in pretty mode.\nThe default is on the smaller end because the length only represents a segment and not the true\nline length.\nDefault: 80</li>\n<li><strong>comments:</strong> Whether to preserve comments in the output SQL code.\nDefault: True</li>\n</ul>\n"}, "sqlglot.generator.Generator.__init__": {"fullname": "sqlglot.generator.Generator.__init__", "modulename": "sqlglot.generator", "qualname": "Generator.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">pretty</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">bool</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">identify</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span>,</span><span class=\"param\">\t<span class=\"n\">normalize</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span>,</span><span class=\"param\">\t<span class=\"n\">pad</span><span class=\"p\">:</span> <span class=\"nb\">int</span> <span class=\"o\">=</span> <span class=\"mi\">2</span>,</span><span class=\"param\">\t<span class=\"n\">indent</span><span class=\"p\">:</span> <span class=\"nb\">int</span> <span class=\"o\">=</span> <span class=\"mi\">2</span>,</span><span class=\"param\">\t<span class=\"n\">normalize_functions</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"nb\">bool</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">unsupported_level</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">errors</span><span class=\"o\">.</span><span class=\"n\">ErrorLevel</span> <span class=\"o\">=</span> <span class=\"o\"><</span><span class=\"n\">ErrorLevel</span><span class=\"o\">.</span><span class=\"n\">WARN</span><span class=\"p\">:</span> <span class=\"s1\">'WARN'</span><span class=\"o\">></span>,</span><span class=\"param\">\t<span class=\"n\">max_unsupported</span><span class=\"p\">:</span> <span class=\"nb\">int</span> <span class=\"o\">=</span> <span class=\"mi\">3</span>,</span><span class=\"param\">\t<span class=\"n\">leading_comma</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span>,</span><span class=\"param\">\t<span class=\"n\">max_text_width</span><span class=\"p\">:</span> <span class=\"nb\">int</span> <span class=\"o\">=</span> <span class=\"mi\">80</span>,</span><span class=\"param\">\t<span class=\"n\">comments</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span>)</span>"}, "sqlglot.generator.Generator.TRANSFORMS": {"fullname": "sqlglot.generator.Generator.TRANSFORMS", "modulename": "sqlglot.generator", "qualname": "Generator.TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[Type[sqlglot.expressions.Expression], Callable[..., str]]", "default_value": "{<class 'sqlglot.expressions.JSONPathFilter'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathKey'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRecursive'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRoot'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathScript'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSelector'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSlice'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSubscript'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathUnion'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathWildcard'>: <function <lambda>>, <class 'sqlglot.expressions.AllowedValuesProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.BackupProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CaseSpecificColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CharacterSetProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CollateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CommentColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DateFormatColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.DefaultColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EncodeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.EphemeralColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExcludeColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ExternalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.GlobalProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.HeapProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IcebergProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InheritsProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InlineLengthColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.InputModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.IntervalSpan'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtract'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.JSONExtractScalar'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LanguageProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LocationProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.LogProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.MaterializedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NonClusteredColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.NotForReplicationColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnCommitProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OnUpdateColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.OutputModelProperty'>: <function Generator.<lambda>>, <class 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'sqlglot.expressions.TemporaryProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TitleColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.Timestamp'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ToTableProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransformModelProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.TransientProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UppercaseColumnConstraint'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.UnloggedProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VarMap'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.VolatileProperty'>: <function Generator.<lambda>>, <class 'sqlglot.expressions.WithJournalTableProperty'>: 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"sqlglot.generator", "qualname": "Generator.STRUCT_DELIMITER", "kind": "variable", "doc": "<p></p>\n", "default_value": "('<', '>')"}, "sqlglot.generator.Generator.PARAMETER_TOKEN": {"fullname": "sqlglot.generator.Generator.PARAMETER_TOKEN", "modulename": "sqlglot.generator", "qualname": "Generator.PARAMETER_TOKEN", "kind": "variable", "doc": "<p></p>\n", "default_value": "'@'"}, "sqlglot.generator.Generator.NAMED_PLACEHOLDER_TOKEN": {"fullname": "sqlglot.generator.Generator.NAMED_PLACEHOLDER_TOKEN", "modulename": "sqlglot.generator", "qualname": "Generator.NAMED_PLACEHOLDER_TOKEN", "kind": "variable", "doc": "<p></p>\n", "default_value": "':'"}, "sqlglot.generator.Generator.PROPERTIES_LOCATION": {"fullname": "sqlglot.generator.Generator.PROPERTIES_LOCATION", "modulename": "sqlglot.generator", "qualname": "Generator.PROPERTIES_LOCATION", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.AllowedValuesProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.AlgorithmProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.AutoIncrementProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.AutoRefreshProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.BackupProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.BlockCompressionProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.CharacterSetProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ChecksumProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.CollateProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.CopyGrantsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Cluster'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ClusteredByProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DataBlocksizeProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.DataDeletionProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DefinerProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.DictRange'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DictProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DistKeyProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.DistStyleProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.EngineProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ExecuteAsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ExternalProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.FallbackProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.FileFormatProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.FreespaceProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.GlobalProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.HeapProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.InheritsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.IcebergProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.InputModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.IsolatedLoadingProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.JournalProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.LanguageProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LikeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LocationProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LockProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.LockingProperty'>: <Location.POST_ALIAS: 'POST_ALIAS'>, <class 'sqlglot.expressions.LogProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.MaterializedProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.MergeBlockRatioProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.NoPrimaryIndexProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.OnProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.OnCommitProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.Order'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.OutputModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.PartitionedByProperty'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.PartitionedOfProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.PrimaryKey'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Property'>: <Location.POST_WITH: 'POST_WITH'>, <class 'sqlglot.expressions.RemoteWithConnectionModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.ReturnsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatDelimitedProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.RowFormatSerdeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SampleProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SchemaCommentProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SerdeProperties'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.Set'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SettingsProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SetProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.SetConfigProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SharingProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.SequenceProperties'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.SortKeyProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SqlReadWriteProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.SqlSecurityProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.StabilityProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.StrictProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.TemporaryProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.ToTableProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.TransientProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.TransformModelProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.MergeTreeTTL'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.UnloggedProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.ViewAttributeProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>, <class 'sqlglot.expressions.VolatileProperty'>: <Location.POST_CREATE: 'POST_CREATE'>, <class 'sqlglot.expressions.WithDataProperty'>: <Location.POST_EXPRESSION: 'POST_EXPRESSION'>, <class 'sqlglot.expressions.WithJournalTableProperty'>: <Location.POST_NAME: 'POST_NAME'>, <class 'sqlglot.expressions.WithSystemVersioningProperty'>: <Location.POST_SCHEMA: 'POST_SCHEMA'>}"}, "sqlglot.generator.Generator.RESERVED_KEYWORDS": {"fullname": "sqlglot.generator.Generator.RESERVED_KEYWORDS", "modulename": "sqlglot.generator", "qualname": "Generator.RESERVED_KEYWORDS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Set[str]", "default_value": "set()"}, "sqlglot.generator.Generator.WITH_SEPARATED_COMMENTS": {"fullname": "sqlglot.generator.Generator.WITH_SEPARATED_COMMENTS", "modulename": "sqlglot.generator", "qualname": "Generator.WITH_SEPARATED_COMMENTS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Tuple[Type[sqlglot.expressions.Expression], ...]", "default_value": "(<class 'sqlglot.expressions.Create'>, <class 'sqlglot.expressions.Delete'>, <class 'sqlglot.expressions.Drop'>, <class 'sqlglot.expressions.From'>, <class 'sqlglot.expressions.Insert'>, <class 'sqlglot.expressions.Join'>, <class 'sqlglot.expressions.Select'>, <class 'sqlglot.expressions.Union'>, <class 'sqlglot.expressions.Update'>, <class 'sqlglot.expressions.Where'>, <class 'sqlglot.expressions.With'>)"}, "sqlglot.generator.Generator.EXCLUDE_COMMENTS": {"fullname": "sqlglot.generator.Generator.EXCLUDE_COMMENTS", "modulename": "sqlglot.generator", "qualname": "Generator.EXCLUDE_COMMENTS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Tuple[Type[sqlglot.expressions.Expression], ...]", "default_value": "(<class 'sqlglot.expressions.Binary'>, <class 'sqlglot.expressions.Union'>)"}, "sqlglot.generator.Generator.UNWRAPPED_INTERVAL_VALUES": {"fullname": "sqlglot.generator.Generator.UNWRAPPED_INTERVAL_VALUES", "modulename": "sqlglot.generator", "qualname": "Generator.UNWRAPPED_INTERVAL_VALUES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Tuple[Type[sqlglot.expressions.Expression], ...]", "default_value": "(<class 'sqlglot.expressions.Column'>, <class 'sqlglot.expressions.Literal'>, <class 'sqlglot.expressions.Neg'>, <class 'sqlglot.expressions.Paren'>)"}, "sqlglot.generator.Generator.PARAMETERIZABLE_TEXT_TYPES": {"fullname": "sqlglot.generator.Generator.PARAMETERIZABLE_TEXT_TYPES", "modulename": "sqlglot.generator", "qualname": "Generator.PARAMETERIZABLE_TEXT_TYPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<Type.VARCHAR: 'VARCHAR'>, <Type.CHAR: 'CHAR'>, <Type.NCHAR: 'NCHAR'>, <Type.NVARCHAR: 'NVARCHAR'>}"}, "sqlglot.generator.Generator.EXPRESSIONS_WITHOUT_NESTED_CTES": {"fullname": "sqlglot.generator.Generator.EXPRESSIONS_WITHOUT_NESTED_CTES", "modulename": "sqlglot.generator", "qualname": "Generator.EXPRESSIONS_WITHOUT_NESTED_CTES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Set[Type[sqlglot.expressions.Expression]]", "default_value": "set()"}, "sqlglot.generator.Generator.SENTINEL_LINE_BREAK": {"fullname": "sqlglot.generator.Generator.SENTINEL_LINE_BREAK", "modulename": "sqlglot.generator", "qualname": "Generator.SENTINEL_LINE_BREAK", "kind": "variable", "doc": "<p></p>\n", "default_value": "'__SQLGLOT__LB__'"}, "sqlglot.generator.Generator.pretty": {"fullname": "sqlglot.generator.Generator.pretty", "modulename": "sqlglot.generator", "qualname": "Generator.pretty", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.generator.Generator.identify": {"fullname": "sqlglot.generator.Generator.identify", "modulename": "sqlglot.generator", "qualname": "Generator.identify", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.generator.Generator.normalize": {"fullname": "sqlglot.generator.Generator.normalize", "modulename": "sqlglot.generator", "qualname": "Generator.normalize", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.generator.Generator.pad": {"fullname": "sqlglot.generator.Generator.pad", "modulename": "sqlglot.generator", "qualname": "Generator.pad", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.generator.Generator.unsupported_level": {"fullname": "sqlglot.generator.Generator.unsupported_level", "modulename": "sqlglot.generator", "qualname": "Generator.unsupported_level", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.generator.Generator.max_unsupported": {"fullname": "sqlglot.generator.Generator.max_unsupported", "modulename": "sqlglot.generator", "qualname": "Generator.max_unsupported", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.generator.Generator.leading_comma": {"fullname": "sqlglot.generator.Generator.leading_comma", "modulename": "sqlglot.generator", "qualname": "Generator.leading_comma", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.generator.Generator.max_text_width": {"fullname": "sqlglot.generator.Generator.max_text_width", "modulename": "sqlglot.generator", "qualname": "Generator.max_text_width", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.generator.Generator.comments": {"fullname": "sqlglot.generator.Generator.comments", "modulename": "sqlglot.generator", "qualname": "Generator.comments", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.generator.Generator.dialect": {"fullname": "sqlglot.generator.Generator.dialect", "modulename": "sqlglot.generator", "qualname": "Generator.dialect", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.generator.Generator.normalize_functions": {"fullname": "sqlglot.generator.Generator.normalize_functions", "modulename": "sqlglot.generator", "qualname": "Generator.normalize_functions", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.generator.Generator.unsupported_messages": {"fullname": "sqlglot.generator.Generator.unsupported_messages", "modulename": "sqlglot.generator", "qualname": "Generator.unsupported_messages", "kind": "variable", "doc": "<p></p>\n", "annotation": ": List[str]"}, "sqlglot.generator.Generator.generate": {"fullname": "sqlglot.generator.Generator.generate", "modulename": "sqlglot.generator", "qualname": "Generator.generate", "kind": "function", "doc": "<p>Generates the SQL string corresponding to the given syntax tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> The syntax tree.</li>\n<li><strong>copy:</strong> Whether to copy the expression. The generator performs mutations so\nit is safer to copy.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The SQL string corresponding to <code>expression</code>.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">copy</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.preprocess": {"fullname": "sqlglot.generator.Generator.preprocess", "modulename": "sqlglot.generator", "qualname": "Generator.preprocess", "kind": "function", "doc": "<p>Apply generic preprocessing transformations to a given expression.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.unsupported": {"fullname": "sqlglot.generator.Generator.unsupported", "modulename": "sqlglot.generator", "qualname": "Generator.unsupported", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">message</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.sep": {"fullname": "sqlglot.generator.Generator.sep", "modulename": "sqlglot.generator", "qualname": "Generator.sep", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">sep</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">' '</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.seg": {"fullname": "sqlglot.generator.Generator.seg", "modulename": "sqlglot.generator", "qualname": "Generator.seg", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">sql</span><span class=\"p\">:</span> <span class=\"nb\">str</span>, </span><span class=\"param\"><span class=\"n\">sep</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">' '</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.pad_comment": {"fullname": "sqlglot.generator.Generator.pad_comment", "modulename": "sqlglot.generator", "qualname": "Generator.pad_comment", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">comment</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.maybe_comment": {"fullname": "sqlglot.generator.Generator.maybe_comment", "modulename": "sqlglot.generator", "qualname": "Generator.maybe_comment", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">sql</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">comments</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">separated</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.wrap": {"fullname": "sqlglot.generator.Generator.wrap", "modulename": "sqlglot.generator", "qualname": "Generator.wrap", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span> <span class=\"o\">|</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.no_identify": {"fullname": "sqlglot.generator.Generator.no_identify", "modulename": "sqlglot.generator", "qualname": "Generator.no_identify", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">func</span><span class=\"p\">:</span> <span class=\"n\">Callable</span><span class=\"p\">[</span><span class=\"o\">...</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">]</span>, </span><span class=\"param\"><span class=\"o\">*</span><span class=\"n\">args</span>, </span><span class=\"param\"><span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.normalize_func": {"fullname": "sqlglot.generator.Generator.normalize_func", "modulename": "sqlglot.generator", "qualname": "Generator.normalize_func", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">name</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.indent": {"fullname": "sqlglot.generator.Generator.indent", "modulename": "sqlglot.generator", "qualname": "Generator.indent", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">sql</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">level</span><span class=\"p\">:</span> <span class=\"nb\">int</span> <span class=\"o\">=</span> <span class=\"mi\">0</span>,</span><span class=\"param\">\t<span class=\"n\">pad</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">int</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">skip_first</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span>,</span><span class=\"param\">\t<span class=\"n\">skip_last</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.sql": {"fullname": "sqlglot.generator.Generator.sql", "modulename": "sqlglot.generator", "qualname": "Generator.sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">key</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">comment</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.uncache_sql": {"fullname": "sqlglot.generator.Generator.uncache_sql", "modulename": "sqlglot.generator", "qualname": "Generator.uncache_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Uncache</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.cache_sql": {"fullname": "sqlglot.generator.Generator.cache_sql", "modulename": "sqlglot.generator", "qualname": "Generator.cache_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Cache</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.characterset_sql": {"fullname": "sqlglot.generator.Generator.characterset_sql", "modulename": "sqlglot.generator", "qualname": "Generator.characterset_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">CharacterSet</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.column_parts": {"fullname": "sqlglot.generator.Generator.column_parts", "modulename": "sqlglot.generator", "qualname": "Generator.column_parts", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Column</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.column_sql": {"fullname": "sqlglot.generator.Generator.column_sql", "modulename": "sqlglot.generator", "qualname": "Generator.column_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Column</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.columnposition_sql": {"fullname": "sqlglot.generator.Generator.columnposition_sql", "modulename": "sqlglot.generator", "qualname": "Generator.columnposition_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ColumnPosition</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.columndef_sql": {"fullname": "sqlglot.generator.Generator.columndef_sql", "modulename": "sqlglot.generator", "qualname": "Generator.columndef_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ColumnDef</span>, </span><span class=\"param\"><span class=\"n\">sep</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">' '</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.columnconstraint_sql": {"fullname": "sqlglot.generator.Generator.columnconstraint_sql", "modulename": "sqlglot.generator", "qualname": "Generator.columnconstraint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ColumnConstraint</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.computedcolumnconstraint_sql": {"fullname": "sqlglot.generator.Generator.computedcolumnconstraint_sql", "modulename": "sqlglot.generator", "qualname": "Generator.computedcolumnconstraint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ComputedColumnConstraint</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.autoincrementcolumnconstraint_sql": {"fullname": "sqlglot.generator.Generator.autoincrementcolumnconstraint_sql", "modulename": "sqlglot.generator", "qualname": "Generator.autoincrementcolumnconstraint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">_</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.compresscolumnconstraint_sql": {"fullname": "sqlglot.generator.Generator.compresscolumnconstraint_sql", "modulename": "sqlglot.generator", "qualname": "Generator.compresscolumnconstraint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">CompressColumnConstraint</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.generatedasidentitycolumnconstraint_sql": {"fullname": "sqlglot.generator.Generator.generatedasidentitycolumnconstraint_sql", "modulename": "sqlglot.generator", "qualname": "Generator.generatedasidentitycolumnconstraint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">GeneratedAsIdentityColumnConstraint</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.generatedasrowcolumnconstraint_sql": {"fullname": "sqlglot.generator.Generator.generatedasrowcolumnconstraint_sql", "modulename": "sqlglot.generator", "qualname": "Generator.generatedasrowcolumnconstraint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">GeneratedAsRowColumnConstraint</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.periodforsystemtimeconstraint_sql": {"fullname": "sqlglot.generator.Generator.periodforsystemtimeconstraint_sql", "modulename": "sqlglot.generator", "qualname": "Generator.periodforsystemtimeconstraint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">PeriodForSystemTimeConstraint</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.notnullcolumnconstraint_sql": {"fullname": "sqlglot.generator.Generator.notnullcolumnconstraint_sql", "modulename": "sqlglot.generator", "qualname": "Generator.notnullcolumnconstraint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">NotNullColumnConstraint</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.transformcolumnconstraint_sql": {"fullname": "sqlglot.generator.Generator.transformcolumnconstraint_sql", "modulename": "sqlglot.generator", "qualname": "Generator.transformcolumnconstraint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TransformColumnConstraint</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.primarykeycolumnconstraint_sql": {"fullname": "sqlglot.generator.Generator.primarykeycolumnconstraint_sql", "modulename": "sqlglot.generator", "qualname": "Generator.primarykeycolumnconstraint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">PrimaryKeyColumnConstraint</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.uniquecolumnconstraint_sql": {"fullname": "sqlglot.generator.Generator.uniquecolumnconstraint_sql", "modulename": "sqlglot.generator", "qualname": "Generator.uniquecolumnconstraint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">UniqueColumnConstraint</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.createable_sql": {"fullname": "sqlglot.generator.Generator.createable_sql", "modulename": "sqlglot.generator", "qualname": "Generator.createable_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Create</span>,</span><span class=\"param\">\t<span class=\"n\">locations</span><span class=\"p\">:</span> <span class=\"n\">DefaultDict</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.create_sql": {"fullname": "sqlglot.generator.Generator.create_sql", "modulename": "sqlglot.generator", "qualname": "Generator.create_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Create</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.sequenceproperties_sql": {"fullname": "sqlglot.generator.Generator.sequenceproperties_sql", "modulename": "sqlglot.generator", "qualname": "Generator.sequenceproperties_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">SequenceProperties</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.clone_sql": {"fullname": "sqlglot.generator.Generator.clone_sql", "modulename": "sqlglot.generator", "qualname": "Generator.clone_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Clone</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.describe_sql": {"fullname": "sqlglot.generator.Generator.describe_sql", "modulename": "sqlglot.generator", "qualname": "Generator.describe_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Describe</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.heredoc_sql": {"fullname": "sqlglot.generator.Generator.heredoc_sql", "modulename": "sqlglot.generator", "qualname": "Generator.heredoc_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Heredoc</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.prepend_ctes": {"fullname": "sqlglot.generator.Generator.prepend_ctes", "modulename": "sqlglot.generator", "qualname": "Generator.prepend_ctes", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>, </span><span class=\"param\"><span class=\"n\">sql</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.with_sql": {"fullname": "sqlglot.generator.Generator.with_sql", "modulename": "sqlglot.generator", "qualname": "Generator.with_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">With</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.cte_sql": {"fullname": "sqlglot.generator.Generator.cte_sql", "modulename": "sqlglot.generator", "qualname": "Generator.cte_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">CTE</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.tablealias_sql": {"fullname": "sqlglot.generator.Generator.tablealias_sql", "modulename": "sqlglot.generator", "qualname": "Generator.tablealias_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TableAlias</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.bitstring_sql": {"fullname": "sqlglot.generator.Generator.bitstring_sql", "modulename": "sqlglot.generator", "qualname": "Generator.bitstring_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">BitString</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.hexstring_sql": {"fullname": "sqlglot.generator.Generator.hexstring_sql", "modulename": "sqlglot.generator", "qualname": "Generator.hexstring_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">HexString</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.bytestring_sql": {"fullname": "sqlglot.generator.Generator.bytestring_sql", "modulename": "sqlglot.generator", "qualname": "Generator.bytestring_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ByteString</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.unicodestring_sql": {"fullname": "sqlglot.generator.Generator.unicodestring_sql", "modulename": "sqlglot.generator", "qualname": "Generator.unicodestring_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">UnicodeString</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.rawstring_sql": {"fullname": "sqlglot.generator.Generator.rawstring_sql", "modulename": "sqlglot.generator", "qualname": "Generator.rawstring_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">RawString</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.datatypeparam_sql": {"fullname": "sqlglot.generator.Generator.datatypeparam_sql", "modulename": "sqlglot.generator", "qualname": "Generator.datatypeparam_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataTypeParam</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.datatype_sql": {"fullname": "sqlglot.generator.Generator.datatype_sql", "modulename": "sqlglot.generator", "qualname": "Generator.datatype_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.directory_sql": {"fullname": "sqlglot.generator.Generator.directory_sql", "modulename": "sqlglot.generator", "qualname": "Generator.directory_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Directory</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.delete_sql": {"fullname": "sqlglot.generator.Generator.delete_sql", "modulename": "sqlglot.generator", "qualname": "Generator.delete_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Delete</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.drop_sql": {"fullname": "sqlglot.generator.Generator.drop_sql", "modulename": "sqlglot.generator", "qualname": "Generator.drop_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Drop</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.except_sql": {"fullname": "sqlglot.generator.Generator.except_sql", "modulename": "sqlglot.generator", "qualname": "Generator.except_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Except</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.except_op": {"fullname": "sqlglot.generator.Generator.except_op", "modulename": "sqlglot.generator", "qualname": "Generator.except_op", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Except</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.fetch_sql": {"fullname": "sqlglot.generator.Generator.fetch_sql", "modulename": "sqlglot.generator", "qualname": "Generator.fetch_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Fetch</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.filter_sql": {"fullname": "sqlglot.generator.Generator.filter_sql", "modulename": "sqlglot.generator", "qualname": "Generator.filter_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Filter</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.hint_sql": {"fullname": "sqlglot.generator.Generator.hint_sql", "modulename": "sqlglot.generator", "qualname": "Generator.hint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Hint</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.indexparameters_sql": {"fullname": "sqlglot.generator.Generator.indexparameters_sql", "modulename": "sqlglot.generator", "qualname": "Generator.indexparameters_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">IndexParameters</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.index_sql": {"fullname": "sqlglot.generator.Generator.index_sql", "modulename": "sqlglot.generator", "qualname": "Generator.index_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Index</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.identifier_sql": {"fullname": "sqlglot.generator.Generator.identifier_sql", "modulename": "sqlglot.generator", "qualname": "Generator.identifier_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Identifier</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.hex_sql": {"fullname": "sqlglot.generator.Generator.hex_sql", "modulename": "sqlglot.generator", "qualname": "Generator.hex_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Hex</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.lowerhex_sql": {"fullname": "sqlglot.generator.Generator.lowerhex_sql", "modulename": "sqlglot.generator", "qualname": "Generator.lowerhex_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">LowerHex</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.inputoutputformat_sql": {"fullname": "sqlglot.generator.Generator.inputoutputformat_sql", "modulename": "sqlglot.generator", "qualname": "Generator.inputoutputformat_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">InputOutputFormat</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.national_sql": {"fullname": "sqlglot.generator.Generator.national_sql", "modulename": "sqlglot.generator", "qualname": "Generator.national_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">National</span>, </span><span class=\"param\"><span class=\"n\">prefix</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">'N'</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.partition_sql": {"fullname": "sqlglot.generator.Generator.partition_sql", "modulename": "sqlglot.generator", "qualname": "Generator.partition_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Partition</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.properties_sql": {"fullname": "sqlglot.generator.Generator.properties_sql", "modulename": "sqlglot.generator", "qualname": "Generator.properties_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Properties</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.root_properties": {"fullname": "sqlglot.generator.Generator.root_properties", "modulename": "sqlglot.generator", "qualname": "Generator.root_properties", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">properties</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Properties</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.properties": {"fullname": "sqlglot.generator.Generator.properties", "modulename": "sqlglot.generator", "qualname": "Generator.properties", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">properties</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Properties</span>,</span><span class=\"param\">\t<span class=\"n\">prefix</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">''</span>,</span><span class=\"param\">\t<span class=\"n\">sep</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">', '</span>,</span><span class=\"param\">\t<span class=\"n\">suffix</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">''</span>,</span><span class=\"param\">\t<span class=\"n\">wrapped</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.with_properties": {"fullname": "sqlglot.generator.Generator.with_properties", "modulename": "sqlglot.generator", "qualname": "Generator.with_properties", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">properties</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Properties</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.locate_properties": {"fullname": "sqlglot.generator.Generator.locate_properties", "modulename": "sqlglot.generator", "qualname": "Generator.locate_properties", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">properties</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Properties</span></span><span class=\"return-annotation\">) -> <span class=\"n\">DefaultDict</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.property_name": {"fullname": "sqlglot.generator.Generator.property_name", "modulename": "sqlglot.generator", "qualname": "Generator.property_name", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Property</span>,</span><span class=\"param\">\t<span class=\"n\">string_key</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.property_sql": {"fullname": "sqlglot.generator.Generator.property_sql", "modulename": "sqlglot.generator", "qualname": "Generator.property_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Property</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.likeproperty_sql": {"fullname": "sqlglot.generator.Generator.likeproperty_sql", "modulename": "sqlglot.generator", "qualname": "Generator.likeproperty_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">LikeProperty</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.fallbackproperty_sql": {"fullname": "sqlglot.generator.Generator.fallbackproperty_sql", "modulename": "sqlglot.generator", "qualname": "Generator.fallbackproperty_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">FallbackProperty</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.journalproperty_sql": {"fullname": "sqlglot.generator.Generator.journalproperty_sql", "modulename": "sqlglot.generator", "qualname": "Generator.journalproperty_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">JournalProperty</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.freespaceproperty_sql": {"fullname": "sqlglot.generator.Generator.freespaceproperty_sql", "modulename": "sqlglot.generator", "qualname": "Generator.freespaceproperty_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">FreespaceProperty</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.checksumproperty_sql": {"fullname": "sqlglot.generator.Generator.checksumproperty_sql", "modulename": "sqlglot.generator", "qualname": "Generator.checksumproperty_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ChecksumProperty</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.mergeblockratioproperty_sql": {"fullname": "sqlglot.generator.Generator.mergeblockratioproperty_sql", "modulename": "sqlglot.generator", "qualname": "Generator.mergeblockratioproperty_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">MergeBlockRatioProperty</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.datablocksizeproperty_sql": {"fullname": "sqlglot.generator.Generator.datablocksizeproperty_sql", "modulename": "sqlglot.generator", "qualname": "Generator.datablocksizeproperty_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataBlocksizeProperty</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.blockcompressionproperty_sql": {"fullname": "sqlglot.generator.Generator.blockcompressionproperty_sql", "modulename": "sqlglot.generator", "qualname": "Generator.blockcompressionproperty_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">BlockCompressionProperty</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.isolatedloadingproperty_sql": {"fullname": "sqlglot.generator.Generator.isolatedloadingproperty_sql", "modulename": "sqlglot.generator", "qualname": "Generator.isolatedloadingproperty_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">IsolatedLoadingProperty</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.partitionboundspec_sql": {"fullname": "sqlglot.generator.Generator.partitionboundspec_sql", "modulename": "sqlglot.generator", "qualname": "Generator.partitionboundspec_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">PartitionBoundSpec</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.partitionedofproperty_sql": {"fullname": "sqlglot.generator.Generator.partitionedofproperty_sql", "modulename": "sqlglot.generator", "qualname": "Generator.partitionedofproperty_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">PartitionedOfProperty</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.lockingproperty_sql": {"fullname": "sqlglot.generator.Generator.lockingproperty_sql", "modulename": "sqlglot.generator", "qualname": "Generator.lockingproperty_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">LockingProperty</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.withdataproperty_sql": {"fullname": "sqlglot.generator.Generator.withdataproperty_sql", "modulename": "sqlglot.generator", "qualname": "Generator.withdataproperty_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">WithDataProperty</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.withsystemversioningproperty_sql": {"fullname": "sqlglot.generator.Generator.withsystemversioningproperty_sql", "modulename": "sqlglot.generator", "qualname": "Generator.withsystemversioningproperty_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">WithSystemVersioningProperty</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.insert_sql": {"fullname": "sqlglot.generator.Generator.insert_sql", "modulename": "sqlglot.generator", "qualname": "Generator.insert_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Insert</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.intersect_sql": {"fullname": "sqlglot.generator.Generator.intersect_sql", "modulename": "sqlglot.generator", "qualname": "Generator.intersect_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Intersect</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.intersect_op": {"fullname": "sqlglot.generator.Generator.intersect_op", "modulename": "sqlglot.generator", "qualname": "Generator.intersect_op", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Intersect</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.introducer_sql": {"fullname": "sqlglot.generator.Generator.introducer_sql", "modulename": "sqlglot.generator", "qualname": "Generator.introducer_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Introducer</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.kill_sql": {"fullname": "sqlglot.generator.Generator.kill_sql", "modulename": "sqlglot.generator", "qualname": "Generator.kill_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Kill</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.pseudotype_sql": {"fullname": "sqlglot.generator.Generator.pseudotype_sql", "modulename": "sqlglot.generator", "qualname": "Generator.pseudotype_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">PseudoType</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.objectidentifier_sql": {"fullname": "sqlglot.generator.Generator.objectidentifier_sql", "modulename": "sqlglot.generator", "qualname": "Generator.objectidentifier_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ObjectIdentifier</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.onconflict_sql": {"fullname": "sqlglot.generator.Generator.onconflict_sql", "modulename": "sqlglot.generator", "qualname": "Generator.onconflict_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">OnConflict</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.returning_sql": {"fullname": "sqlglot.generator.Generator.returning_sql", "modulename": "sqlglot.generator", "qualname": "Generator.returning_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Returning</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.rowformatdelimitedproperty_sql": {"fullname": "sqlglot.generator.Generator.rowformatdelimitedproperty_sql", "modulename": "sqlglot.generator", "qualname": "Generator.rowformatdelimitedproperty_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">RowFormatDelimitedProperty</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.withtablehint_sql": {"fullname": "sqlglot.generator.Generator.withtablehint_sql", "modulename": "sqlglot.generator", "qualname": "Generator.withtablehint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">WithTableHint</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.indextablehint_sql": {"fullname": "sqlglot.generator.Generator.indextablehint_sql", "modulename": "sqlglot.generator", "qualname": "Generator.indextablehint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">IndexTableHint</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.historicaldata_sql": {"fullname": "sqlglot.generator.Generator.historicaldata_sql", "modulename": "sqlglot.generator", "qualname": "Generator.historicaldata_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">HistoricalData</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.table_parts": {"fullname": "sqlglot.generator.Generator.table_parts", "modulename": "sqlglot.generator", "qualname": "Generator.table_parts", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Table</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.table_sql": {"fullname": "sqlglot.generator.Generator.table_sql", "modulename": "sqlglot.generator", "qualname": "Generator.table_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Table</span>, </span><span class=\"param\"><span class=\"n\">sep</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">' AS '</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.tablesample_sql": {"fullname": "sqlglot.generator.Generator.tablesample_sql", "modulename": "sqlglot.generator", "qualname": "Generator.tablesample_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TableSample</span>,</span><span class=\"param\">\t<span class=\"n\">sep</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">' AS '</span>,</span><span class=\"param\">\t<span class=\"n\">tablesample_keyword</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.pivot_sql": {"fullname": "sqlglot.generator.Generator.pivot_sql", "modulename": "sqlglot.generator", "qualname": "Generator.pivot_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Pivot</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.version_sql": {"fullname": "sqlglot.generator.Generator.version_sql", "modulename": "sqlglot.generator", "qualname": "Generator.version_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Version</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.tuple_sql": {"fullname": "sqlglot.generator.Generator.tuple_sql", "modulename": "sqlglot.generator", "qualname": "Generator.tuple_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Tuple</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.update_sql": {"fullname": "sqlglot.generator.Generator.update_sql", "modulename": "sqlglot.generator", "qualname": "Generator.update_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Update</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.values_sql": {"fullname": "sqlglot.generator.Generator.values_sql", "modulename": "sqlglot.generator", "qualname": "Generator.values_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Values</span>,</span><span class=\"param\">\t<span class=\"n\">values_as_table</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.var_sql": {"fullname": "sqlglot.generator.Generator.var_sql", "modulename": "sqlglot.generator", "qualname": "Generator.var_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Var</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.into_sql": {"fullname": "sqlglot.generator.Generator.into_sql", "modulename": "sqlglot.generator", "qualname": "Generator.into_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Into</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.from_sql": {"fullname": "sqlglot.generator.Generator.from_sql", "modulename": "sqlglot.generator", "qualname": "Generator.from_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">From</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.group_sql": {"fullname": "sqlglot.generator.Generator.group_sql", "modulename": "sqlglot.generator", "qualname": "Generator.group_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Group</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.having_sql": {"fullname": "sqlglot.generator.Generator.having_sql", "modulename": "sqlglot.generator", "qualname": "Generator.having_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Having</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.connect_sql": {"fullname": "sqlglot.generator.Generator.connect_sql", "modulename": "sqlglot.generator", "qualname": "Generator.connect_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Connect</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.prior_sql": {"fullname": "sqlglot.generator.Generator.prior_sql", "modulename": "sqlglot.generator", "qualname": "Generator.prior_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Prior</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.join_sql": {"fullname": "sqlglot.generator.Generator.join_sql", "modulename": "sqlglot.generator", "qualname": "Generator.join_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Join</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.lambda_sql": {"fullname": "sqlglot.generator.Generator.lambda_sql", "modulename": "sqlglot.generator", "qualname": "Generator.lambda_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Lambda</span>,</span><span class=\"param\">\t<span class=\"n\">arrow_sep</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">'->'</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.lateral_op": {"fullname": "sqlglot.generator.Generator.lateral_op", "modulename": "sqlglot.generator", "qualname": "Generator.lateral_op", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Lateral</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.lateral_sql": {"fullname": "sqlglot.generator.Generator.lateral_sql", "modulename": "sqlglot.generator", "qualname": "Generator.lateral_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Lateral</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.limit_sql": {"fullname": "sqlglot.generator.Generator.limit_sql", "modulename": "sqlglot.generator", "qualname": "Generator.limit_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Limit</span>, </span><span class=\"param\"><span class=\"n\">top</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.offset_sql": {"fullname": "sqlglot.generator.Generator.offset_sql", "modulename": "sqlglot.generator", "qualname": "Generator.offset_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Offset</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.setitem_sql": {"fullname": "sqlglot.generator.Generator.setitem_sql", "modulename": "sqlglot.generator", "qualname": "Generator.setitem_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">SetItem</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.set_sql": {"fullname": "sqlglot.generator.Generator.set_sql", "modulename": "sqlglot.generator", "qualname": "Generator.set_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Set</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.pragma_sql": {"fullname": "sqlglot.generator.Generator.pragma_sql", "modulename": "sqlglot.generator", "qualname": "Generator.pragma_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Pragma</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.lock_sql": {"fullname": "sqlglot.generator.Generator.lock_sql", "modulename": "sqlglot.generator", "qualname": "Generator.lock_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Lock</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.literal_sql": {"fullname": "sqlglot.generator.Generator.literal_sql", "modulename": "sqlglot.generator", "qualname": "Generator.literal_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Literal</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.escape_str": {"fullname": "sqlglot.generator.Generator.escape_str", "modulename": "sqlglot.generator", "qualname": "Generator.escape_str", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">text</span><span class=\"p\">:</span> <span class=\"nb\">str</span>, </span><span class=\"param\"><span class=\"n\">escape_backslash</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.loaddata_sql": {"fullname": "sqlglot.generator.Generator.loaddata_sql", "modulename": "sqlglot.generator", "qualname": "Generator.loaddata_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">LoadData</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.null_sql": {"fullname": "sqlglot.generator.Generator.null_sql", "modulename": "sqlglot.generator", "qualname": "Generator.null_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">*</span><span class=\"n\">_</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.boolean_sql": {"fullname": "sqlglot.generator.Generator.boolean_sql", "modulename": "sqlglot.generator", "qualname": "Generator.boolean_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Boolean</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.order_sql": {"fullname": "sqlglot.generator.Generator.order_sql", "modulename": "sqlglot.generator", "qualname": "Generator.order_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Order</span>, </span><span class=\"param\"><span class=\"n\">flat</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.withfill_sql": {"fullname": "sqlglot.generator.Generator.withfill_sql", "modulename": "sqlglot.generator", "qualname": "Generator.withfill_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">WithFill</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.cluster_sql": {"fullname": "sqlglot.generator.Generator.cluster_sql", "modulename": "sqlglot.generator", "qualname": "Generator.cluster_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Cluster</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.distribute_sql": {"fullname": "sqlglot.generator.Generator.distribute_sql", "modulename": "sqlglot.generator", "qualname": "Generator.distribute_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Distribute</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.sort_sql": {"fullname": "sqlglot.generator.Generator.sort_sql", "modulename": "sqlglot.generator", "qualname": "Generator.sort_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Sort</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.ordered_sql": {"fullname": "sqlglot.generator.Generator.ordered_sql", "modulename": "sqlglot.generator", "qualname": "Generator.ordered_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Ordered</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.matchrecognizemeasure_sql": {"fullname": "sqlglot.generator.Generator.matchrecognizemeasure_sql", "modulename": "sqlglot.generator", "qualname": "Generator.matchrecognizemeasure_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">MatchRecognizeMeasure</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.matchrecognize_sql": {"fullname": "sqlglot.generator.Generator.matchrecognize_sql", "modulename": "sqlglot.generator", "qualname": "Generator.matchrecognize_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">MatchRecognize</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.query_modifiers": {"fullname": "sqlglot.generator.Generator.query_modifiers", "modulename": "sqlglot.generator", "qualname": "Generator.query_modifiers", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>, </span><span class=\"param\"><span class=\"o\">*</span><span class=\"n\">sqls</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.queryoption_sql": {"fullname": "sqlglot.generator.Generator.queryoption_sql", "modulename": "sqlglot.generator", "qualname": "Generator.queryoption_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">QueryOption</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.offset_limit_modifiers": {"fullname": "sqlglot.generator.Generator.offset_limit_modifiers", "modulename": "sqlglot.generator", "qualname": "Generator.offset_limit_modifiers", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">fetch</span><span class=\"p\">:</span> <span class=\"nb\">bool</span>,</span><span class=\"param\">\t<span class=\"n\">limit</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Fetch</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Limit</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.after_limit_modifiers": {"fullname": "sqlglot.generator.Generator.after_limit_modifiers", "modulename": "sqlglot.generator", "qualname": "Generator.after_limit_modifiers", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.select_sql": {"fullname": "sqlglot.generator.Generator.select_sql", "modulename": "sqlglot.generator", "qualname": "Generator.select_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Select</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.schema_sql": {"fullname": "sqlglot.generator.Generator.schema_sql", "modulename": "sqlglot.generator", "qualname": "Generator.schema_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Schema</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.schema_columns_sql": {"fullname": "sqlglot.generator.Generator.schema_columns_sql", "modulename": "sqlglot.generator", "qualname": "Generator.schema_columns_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Schema</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.star_sql": {"fullname": "sqlglot.generator.Generator.star_sql", "modulename": "sqlglot.generator", "qualname": "Generator.star_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Star</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.parameter_sql": {"fullname": "sqlglot.generator.Generator.parameter_sql", "modulename": "sqlglot.generator", "qualname": "Generator.parameter_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Parameter</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.sessionparameter_sql": {"fullname": "sqlglot.generator.Generator.sessionparameter_sql", "modulename": "sqlglot.generator", "qualname": "Generator.sessionparameter_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">SessionParameter</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.placeholder_sql": {"fullname": "sqlglot.generator.Generator.placeholder_sql", "modulename": "sqlglot.generator", "qualname": "Generator.placeholder_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Placeholder</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.subquery_sql": {"fullname": "sqlglot.generator.Generator.subquery_sql", "modulename": "sqlglot.generator", "qualname": "Generator.subquery_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Subquery</span>, </span><span class=\"param\"><span class=\"n\">sep</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">' AS '</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.qualify_sql": {"fullname": "sqlglot.generator.Generator.qualify_sql", "modulename": "sqlglot.generator", "qualname": "Generator.qualify_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Qualify</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.set_operations": {"fullname": "sqlglot.generator.Generator.set_operations", "modulename": "sqlglot.generator", "qualname": "Generator.set_operations", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Union</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.union_sql": {"fullname": "sqlglot.generator.Generator.union_sql", "modulename": "sqlglot.generator", "qualname": "Generator.union_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Union</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.union_op": {"fullname": "sqlglot.generator.Generator.union_op", "modulename": "sqlglot.generator", "qualname": "Generator.union_op", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Union</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.unnest_sql": {"fullname": "sqlglot.generator.Generator.unnest_sql", "modulename": "sqlglot.generator", "qualname": "Generator.unnest_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Unnest</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.prewhere_sql": {"fullname": "sqlglot.generator.Generator.prewhere_sql", "modulename": "sqlglot.generator", "qualname": "Generator.prewhere_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">PreWhere</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.where_sql": {"fullname": "sqlglot.generator.Generator.where_sql", "modulename": "sqlglot.generator", "qualname": "Generator.where_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Where</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.window_sql": {"fullname": "sqlglot.generator.Generator.window_sql", "modulename": "sqlglot.generator", "qualname": "Generator.window_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Window</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.partition_by_sql": {"fullname": "sqlglot.generator.Generator.partition_by_sql", "modulename": "sqlglot.generator", "qualname": "Generator.partition_by_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Window</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">MatchRecognize</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.windowspec_sql": {"fullname": "sqlglot.generator.Generator.windowspec_sql", "modulename": "sqlglot.generator", "qualname": "Generator.windowspec_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">WindowSpec</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.withingroup_sql": {"fullname": "sqlglot.generator.Generator.withingroup_sql", "modulename": "sqlglot.generator", "qualname": "Generator.withingroup_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">WithinGroup</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.between_sql": {"fullname": "sqlglot.generator.Generator.between_sql", "modulename": "sqlglot.generator", "qualname": "Generator.between_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Between</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.bracket_offset_expressions": {"fullname": "sqlglot.generator.Generator.bracket_offset_expressions", "modulename": "sqlglot.generator", "qualname": "Generator.bracket_offset_expressions", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Bracket</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.bracket_sql": {"fullname": "sqlglot.generator.Generator.bracket_sql", "modulename": "sqlglot.generator", "qualname": "Generator.bracket_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Bracket</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.all_sql": {"fullname": "sqlglot.generator.Generator.all_sql", "modulename": "sqlglot.generator", "qualname": "Generator.all_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">All</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.any_sql": {"fullname": "sqlglot.generator.Generator.any_sql", "modulename": "sqlglot.generator", "qualname": "Generator.any_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Any</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.exists_sql": {"fullname": "sqlglot.generator.Generator.exists_sql", "modulename": "sqlglot.generator", "qualname": "Generator.exists_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Exists</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.case_sql": {"fullname": "sqlglot.generator.Generator.case_sql", "modulename": "sqlglot.generator", "qualname": "Generator.case_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Case</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.constraint_sql": {"fullname": "sqlglot.generator.Generator.constraint_sql", "modulename": "sqlglot.generator", "qualname": "Generator.constraint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Constraint</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.nextvaluefor_sql": {"fullname": "sqlglot.generator.Generator.nextvaluefor_sql", "modulename": "sqlglot.generator", "qualname": "Generator.nextvaluefor_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">NextValueFor</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.extract_sql": {"fullname": "sqlglot.generator.Generator.extract_sql", "modulename": "sqlglot.generator", "qualname": "Generator.extract_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Extract</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.trim_sql": {"fullname": "sqlglot.generator.Generator.trim_sql", "modulename": "sqlglot.generator", "qualname": "Generator.trim_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Trim</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.convert_concat_args": {"fullname": "sqlglot.generator.Generator.convert_concat_args", "modulename": "sqlglot.generator", "qualname": "Generator.convert_concat_args", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Concat</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ConcatWs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.concat_sql": {"fullname": "sqlglot.generator.Generator.concat_sql", "modulename": "sqlglot.generator", "qualname": "Generator.concat_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Concat</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.concatws_sql": {"fullname": "sqlglot.generator.Generator.concatws_sql", "modulename": "sqlglot.generator", "qualname": "Generator.concatws_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ConcatWs</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.check_sql": {"fullname": "sqlglot.generator.Generator.check_sql", "modulename": "sqlglot.generator", "qualname": "Generator.check_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Check</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.foreignkey_sql": {"fullname": "sqlglot.generator.Generator.foreignkey_sql", "modulename": "sqlglot.generator", "qualname": "Generator.foreignkey_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ForeignKey</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.primarykey_sql": {"fullname": "sqlglot.generator.Generator.primarykey_sql", "modulename": "sqlglot.generator", "qualname": "Generator.primarykey_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ForeignKey</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.if_sql": {"fullname": "sqlglot.generator.Generator.if_sql", "modulename": "sqlglot.generator", "qualname": "Generator.if_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">If</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.matchagainst_sql": {"fullname": "sqlglot.generator.Generator.matchagainst_sql", "modulename": "sqlglot.generator", "qualname": "Generator.matchagainst_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">MatchAgainst</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.jsonkeyvalue_sql": {"fullname": "sqlglot.generator.Generator.jsonkeyvalue_sql", "modulename": "sqlglot.generator", "qualname": "Generator.jsonkeyvalue_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">JSONKeyValue</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.jsonpath_sql": {"fullname": "sqlglot.generator.Generator.jsonpath_sql", "modulename": "sqlglot.generator", "qualname": "Generator.jsonpath_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">JSONPath</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.json_path_part": {"fullname": "sqlglot.generator.Generator.json_path_part", "modulename": "sqlglot.generator", "qualname": "Generator.json_path_part", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"nb\">int</span> <span class=\"o\">|</span> <span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">JSONPathPart</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.formatjson_sql": {"fullname": "sqlglot.generator.Generator.formatjson_sql", "modulename": "sqlglot.generator", "qualname": "Generator.formatjson_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">FormatJson</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.jsonobject_sql": {"fullname": "sqlglot.generator.Generator.jsonobject_sql", "modulename": "sqlglot.generator", "qualname": "Generator.jsonobject_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">JSONObject</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">JSONObjectAgg</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.jsonobjectagg_sql": {"fullname": "sqlglot.generator.Generator.jsonobjectagg_sql", "modulename": "sqlglot.generator", "qualname": "Generator.jsonobjectagg_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">JSONObjectAgg</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.jsonarray_sql": {"fullname": "sqlglot.generator.Generator.jsonarray_sql", "modulename": "sqlglot.generator", "qualname": "Generator.jsonarray_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">JSONArray</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.jsonarrayagg_sql": {"fullname": "sqlglot.generator.Generator.jsonarrayagg_sql", "modulename": "sqlglot.generator", "qualname": "Generator.jsonarrayagg_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">JSONArrayAgg</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.jsoncolumndef_sql": {"fullname": "sqlglot.generator.Generator.jsoncolumndef_sql", "modulename": "sqlglot.generator", "qualname": "Generator.jsoncolumndef_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">JSONColumnDef</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.jsonschema_sql": {"fullname": "sqlglot.generator.Generator.jsonschema_sql", "modulename": "sqlglot.generator", "qualname": "Generator.jsonschema_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">JSONSchema</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.jsontable_sql": {"fullname": "sqlglot.generator.Generator.jsontable_sql", "modulename": "sqlglot.generator", "qualname": "Generator.jsontable_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">JSONTable</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.openjsoncolumndef_sql": {"fullname": "sqlglot.generator.Generator.openjsoncolumndef_sql", "modulename": "sqlglot.generator", "qualname": "Generator.openjsoncolumndef_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">OpenJSONColumnDef</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.openjson_sql": {"fullname": "sqlglot.generator.Generator.openjson_sql", "modulename": "sqlglot.generator", "qualname": "Generator.openjson_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">OpenJSON</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.in_sql": {"fullname": "sqlglot.generator.Generator.in_sql", "modulename": "sqlglot.generator", "qualname": "Generator.in_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">In</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.in_unnest_op": {"fullname": "sqlglot.generator.Generator.in_unnest_op", "modulename": "sqlglot.generator", "qualname": "Generator.in_unnest_op", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">unnest</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Unnest</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.interval_sql": {"fullname": "sqlglot.generator.Generator.interval_sql", "modulename": "sqlglot.generator", "qualname": "Generator.interval_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Interval</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.return_sql": {"fullname": "sqlglot.generator.Generator.return_sql", "modulename": "sqlglot.generator", "qualname": "Generator.return_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Return</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.reference_sql": {"fullname": "sqlglot.generator.Generator.reference_sql", "modulename": "sqlglot.generator", "qualname": "Generator.reference_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Reference</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.anonymous_sql": {"fullname": "sqlglot.generator.Generator.anonymous_sql", "modulename": "sqlglot.generator", "qualname": "Generator.anonymous_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Anonymous</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.paren_sql": {"fullname": "sqlglot.generator.Generator.paren_sql", "modulename": "sqlglot.generator", "qualname": "Generator.paren_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Paren</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.neg_sql": {"fullname": "sqlglot.generator.Generator.neg_sql", "modulename": "sqlglot.generator", "qualname": "Generator.neg_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Neg</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.not_sql": {"fullname": "sqlglot.generator.Generator.not_sql", "modulename": "sqlglot.generator", "qualname": "Generator.not_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Not</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.alias_sql": {"fullname": "sqlglot.generator.Generator.alias_sql", "modulename": "sqlglot.generator", "qualname": "Generator.alias_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Alias</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.pivotalias_sql": {"fullname": "sqlglot.generator.Generator.pivotalias_sql", "modulename": "sqlglot.generator", "qualname": "Generator.pivotalias_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">PivotAlias</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.aliases_sql": {"fullname": "sqlglot.generator.Generator.aliases_sql", "modulename": "sqlglot.generator", "qualname": "Generator.aliases_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Aliases</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.atindex_sql": {"fullname": "sqlglot.generator.Generator.atindex_sql", "modulename": "sqlglot.generator", "qualname": "Generator.atindex_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">AtTimeZone</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.attimezone_sql": {"fullname": "sqlglot.generator.Generator.attimezone_sql", "modulename": "sqlglot.generator", "qualname": "Generator.attimezone_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">AtTimeZone</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.fromtimezone_sql": {"fullname": "sqlglot.generator.Generator.fromtimezone_sql", "modulename": "sqlglot.generator", "qualname": "Generator.fromtimezone_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">FromTimeZone</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.add_sql": {"fullname": "sqlglot.generator.Generator.add_sql", "modulename": "sqlglot.generator", "qualname": "Generator.add_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Add</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.and_sql": {"fullname": "sqlglot.generator.Generator.and_sql", "modulename": "sqlglot.generator", "qualname": "Generator.and_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">And</span>,</span><span class=\"param\">\t<span class=\"n\">stack</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.or_sql": {"fullname": "sqlglot.generator.Generator.or_sql", "modulename": "sqlglot.generator", "qualname": "Generator.or_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Or</span>,</span><span class=\"param\">\t<span class=\"n\">stack</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.xor_sql": {"fullname": "sqlglot.generator.Generator.xor_sql", "modulename": "sqlglot.generator", "qualname": "Generator.xor_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Xor</span>,</span><span class=\"param\">\t<span class=\"n\">stack</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.connector_sql": {"fullname": "sqlglot.generator.Generator.connector_sql", "modulename": "sqlglot.generator", "qualname": "Generator.connector_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Connector</span>,</span><span class=\"param\">\t<span class=\"n\">op</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">stack</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.bitwiseand_sql": {"fullname": "sqlglot.generator.Generator.bitwiseand_sql", "modulename": "sqlglot.generator", "qualname": "Generator.bitwiseand_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">BitwiseAnd</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.bitwiseleftshift_sql": {"fullname": "sqlglot.generator.Generator.bitwiseleftshift_sql", "modulename": "sqlglot.generator", "qualname": "Generator.bitwiseleftshift_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">BitwiseLeftShift</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.bitwisenot_sql": {"fullname": "sqlglot.generator.Generator.bitwisenot_sql", "modulename": "sqlglot.generator", "qualname": "Generator.bitwisenot_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">BitwiseNot</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.bitwiseor_sql": {"fullname": "sqlglot.generator.Generator.bitwiseor_sql", "modulename": "sqlglot.generator", "qualname": "Generator.bitwiseor_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">BitwiseOr</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.bitwiserightshift_sql": {"fullname": "sqlglot.generator.Generator.bitwiserightshift_sql", "modulename": "sqlglot.generator", "qualname": "Generator.bitwiserightshift_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">BitwiseRightShift</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.bitwisexor_sql": {"fullname": "sqlglot.generator.Generator.bitwisexor_sql", "modulename": "sqlglot.generator", "qualname": "Generator.bitwisexor_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">BitwiseXor</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.cast_sql": {"fullname": "sqlglot.generator.Generator.cast_sql", "modulename": "sqlglot.generator", "qualname": "Generator.cast_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Cast</span>,</span><span class=\"param\">\t<span class=\"n\">safe_prefix</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.currentdate_sql": {"fullname": "sqlglot.generator.Generator.currentdate_sql", "modulename": "sqlglot.generator", "qualname": "Generator.currentdate_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">CurrentDate</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.currenttimestamp_sql": {"fullname": "sqlglot.generator.Generator.currenttimestamp_sql", "modulename": "sqlglot.generator", "qualname": "Generator.currenttimestamp_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">CurrentTimestamp</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.collate_sql": {"fullname": "sqlglot.generator.Generator.collate_sql", "modulename": "sqlglot.generator", "qualname": "Generator.collate_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Collate</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.command_sql": {"fullname": "sqlglot.generator.Generator.command_sql", "modulename": "sqlglot.generator", "qualname": "Generator.command_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Command</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.comment_sql": {"fullname": "sqlglot.generator.Generator.comment_sql", "modulename": "sqlglot.generator", "qualname": "Generator.comment_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Comment</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.mergetreettlaction_sql": {"fullname": "sqlglot.generator.Generator.mergetreettlaction_sql", "modulename": "sqlglot.generator", "qualname": "Generator.mergetreettlaction_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">MergeTreeTTLAction</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.mergetreettl_sql": {"fullname": "sqlglot.generator.Generator.mergetreettl_sql", "modulename": "sqlglot.generator", "qualname": "Generator.mergetreettl_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">MergeTreeTTL</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.transaction_sql": {"fullname": "sqlglot.generator.Generator.transaction_sql", "modulename": "sqlglot.generator", "qualname": "Generator.transaction_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Transaction</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.commit_sql": {"fullname": "sqlglot.generator.Generator.commit_sql", "modulename": "sqlglot.generator", "qualname": "Generator.commit_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Commit</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.rollback_sql": {"fullname": "sqlglot.generator.Generator.rollback_sql", "modulename": "sqlglot.generator", "qualname": "Generator.rollback_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Rollback</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.altercolumn_sql": {"fullname": "sqlglot.generator.Generator.altercolumn_sql", "modulename": "sqlglot.generator", "qualname": "Generator.altercolumn_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">AlterColumn</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.alterdiststyle_sql": {"fullname": "sqlglot.generator.Generator.alterdiststyle_sql", "modulename": "sqlglot.generator", "qualname": "Generator.alterdiststyle_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">AlterDistStyle</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.altersortkey_sql": {"fullname": "sqlglot.generator.Generator.altersortkey_sql", "modulename": "sqlglot.generator", "qualname": "Generator.altersortkey_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">AlterSortKey</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.renametable_sql": {"fullname": "sqlglot.generator.Generator.renametable_sql", "modulename": "sqlglot.generator", "qualname": "Generator.renametable_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">RenameTable</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.renamecolumn_sql": {"fullname": "sqlglot.generator.Generator.renamecolumn_sql", "modulename": "sqlglot.generator", "qualname": "Generator.renamecolumn_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">RenameColumn</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.alterset_sql": {"fullname": "sqlglot.generator.Generator.alterset_sql", "modulename": "sqlglot.generator", "qualname": "Generator.alterset_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">AlterSet</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.altertable_sql": {"fullname": "sqlglot.generator.Generator.altertable_sql", "modulename": "sqlglot.generator", "qualname": "Generator.altertable_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">AlterTable</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.add_column_sql": {"fullname": "sqlglot.generator.Generator.add_column_sql", "modulename": "sqlglot.generator", "qualname": "Generator.add_column_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">AlterTable</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.droppartition_sql": {"fullname": "sqlglot.generator.Generator.droppartition_sql", "modulename": "sqlglot.generator", "qualname": "Generator.droppartition_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DropPartition</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.addconstraint_sql": {"fullname": "sqlglot.generator.Generator.addconstraint_sql", "modulename": "sqlglot.generator", "qualname": "Generator.addconstraint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">AddConstraint</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.distinct_sql": {"fullname": "sqlglot.generator.Generator.distinct_sql", "modulename": "sqlglot.generator", "qualname": "Generator.distinct_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Distinct</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.ignorenulls_sql": {"fullname": "sqlglot.generator.Generator.ignorenulls_sql", "modulename": "sqlglot.generator", "qualname": "Generator.ignorenulls_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">IgnoreNulls</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.respectnulls_sql": {"fullname": "sqlglot.generator.Generator.respectnulls_sql", "modulename": "sqlglot.generator", "qualname": "Generator.respectnulls_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">RespectNulls</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.havingmax_sql": {"fullname": "sqlglot.generator.Generator.havingmax_sql", "modulename": "sqlglot.generator", "qualname": "Generator.havingmax_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">HavingMax</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.intdiv_sql": {"fullname": "sqlglot.generator.Generator.intdiv_sql", "modulename": "sqlglot.generator", "qualname": "Generator.intdiv_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">IntDiv</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.dpipe_sql": {"fullname": "sqlglot.generator.Generator.dpipe_sql", "modulename": "sqlglot.generator", "qualname": "Generator.dpipe_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DPipe</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.div_sql": {"fullname": "sqlglot.generator.Generator.div_sql", "modulename": "sqlglot.generator", "qualname": "Generator.div_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Div</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.overlaps_sql": {"fullname": "sqlglot.generator.Generator.overlaps_sql", "modulename": "sqlglot.generator", "qualname": "Generator.overlaps_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Overlaps</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.distance_sql": {"fullname": "sqlglot.generator.Generator.distance_sql", "modulename": "sqlglot.generator", "qualname": "Generator.distance_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Distance</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.dot_sql": {"fullname": "sqlglot.generator.Generator.dot_sql", "modulename": "sqlglot.generator", "qualname": "Generator.dot_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Dot</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.eq_sql": {"fullname": "sqlglot.generator.Generator.eq_sql", "modulename": "sqlglot.generator", "qualname": "Generator.eq_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">EQ</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.propertyeq_sql": {"fullname": "sqlglot.generator.Generator.propertyeq_sql", "modulename": "sqlglot.generator", "qualname": "Generator.propertyeq_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">PropertyEQ</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.escape_sql": {"fullname": "sqlglot.generator.Generator.escape_sql", "modulename": "sqlglot.generator", "qualname": "Generator.escape_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Escape</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.glob_sql": {"fullname": "sqlglot.generator.Generator.glob_sql", "modulename": "sqlglot.generator", "qualname": "Generator.glob_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Glob</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.gt_sql": {"fullname": "sqlglot.generator.Generator.gt_sql", "modulename": "sqlglot.generator", "qualname": "Generator.gt_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">GT</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.gte_sql": {"fullname": "sqlglot.generator.Generator.gte_sql", "modulename": "sqlglot.generator", "qualname": "Generator.gte_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">GTE</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.ilike_sql": {"fullname": "sqlglot.generator.Generator.ilike_sql", "modulename": "sqlglot.generator", "qualname": "Generator.ilike_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ILike</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.ilikeany_sql": {"fullname": "sqlglot.generator.Generator.ilikeany_sql", "modulename": "sqlglot.generator", "qualname": "Generator.ilikeany_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ILikeAny</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.is_sql": {"fullname": "sqlglot.generator.Generator.is_sql", "modulename": "sqlglot.generator", "qualname": "Generator.is_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Is</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.like_sql": {"fullname": "sqlglot.generator.Generator.like_sql", "modulename": "sqlglot.generator", "qualname": "Generator.like_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Like</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.likeany_sql": {"fullname": "sqlglot.generator.Generator.likeany_sql", "modulename": "sqlglot.generator", "qualname": "Generator.likeany_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">LikeAny</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.similarto_sql": {"fullname": "sqlglot.generator.Generator.similarto_sql", "modulename": "sqlglot.generator", "qualname": "Generator.similarto_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">SimilarTo</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.lt_sql": {"fullname": "sqlglot.generator.Generator.lt_sql", "modulename": "sqlglot.generator", "qualname": "Generator.lt_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">LT</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.lte_sql": {"fullname": "sqlglot.generator.Generator.lte_sql", "modulename": "sqlglot.generator", "qualname": "Generator.lte_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">LTE</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.mod_sql": {"fullname": "sqlglot.generator.Generator.mod_sql", "modulename": "sqlglot.generator", "qualname": "Generator.mod_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Mod</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.mul_sql": {"fullname": "sqlglot.generator.Generator.mul_sql", "modulename": "sqlglot.generator", "qualname": "Generator.mul_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Mul</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.neq_sql": {"fullname": "sqlglot.generator.Generator.neq_sql", "modulename": "sqlglot.generator", "qualname": "Generator.neq_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">NEQ</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.nullsafeeq_sql": {"fullname": "sqlglot.generator.Generator.nullsafeeq_sql", "modulename": "sqlglot.generator", "qualname": "Generator.nullsafeeq_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">NullSafeEQ</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.nullsafeneq_sql": {"fullname": "sqlglot.generator.Generator.nullsafeneq_sql", "modulename": "sqlglot.generator", "qualname": "Generator.nullsafeneq_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">NullSafeNEQ</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.slice_sql": {"fullname": "sqlglot.generator.Generator.slice_sql", "modulename": "sqlglot.generator", "qualname": "Generator.slice_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Slice</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.sub_sql": {"fullname": "sqlglot.generator.Generator.sub_sql", "modulename": "sqlglot.generator", "qualname": "Generator.sub_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Sub</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.trycast_sql": {"fullname": "sqlglot.generator.Generator.trycast_sql", "modulename": "sqlglot.generator", "qualname": "Generator.trycast_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TryCast</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.try_sql": {"fullname": "sqlglot.generator.Generator.try_sql", "modulename": "sqlglot.generator", "qualname": "Generator.try_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Try</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.log_sql": {"fullname": "sqlglot.generator.Generator.log_sql", "modulename": "sqlglot.generator", "qualname": "Generator.log_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Log</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.use_sql": {"fullname": "sqlglot.generator.Generator.use_sql", "modulename": "sqlglot.generator", "qualname": "Generator.use_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Use</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.binary": {"fullname": "sqlglot.generator.Generator.binary", "modulename": "sqlglot.generator", "qualname": "Generator.binary", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Binary</span>, </span><span class=\"param\"><span class=\"n\">op</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.function_fallback_sql": {"fullname": "sqlglot.generator.Generator.function_fallback_sql", "modulename": "sqlglot.generator", "qualname": "Generator.function_fallback_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Func</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.func": {"fullname": "sqlglot.generator.Generator.func", "modulename": "sqlglot.generator", "qualname": "Generator.func", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">name</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">args</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">prefix</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">'('</span>,</span><span class=\"param\">\t<span class=\"n\">suffix</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">')'</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.format_args": {"fullname": "sqlglot.generator.Generator.format_args", "modulename": "sqlglot.generator", "qualname": "Generator.format_args", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">*</span><span class=\"n\">args</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.too_wide": {"fullname": "sqlglot.generator.Generator.too_wide", "modulename": "sqlglot.generator", "qualname": "Generator.too_wide", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">args</span><span class=\"p\">:</span> <span class=\"n\">Iterable</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">bool</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.format_time": {"fullname": "sqlglot.generator.Generator.format_time", "modulename": "sqlglot.generator", "qualname": "Generator.format_time", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">inverse_time_mapping</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">inverse_time_trie</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.expressions": {"fullname": "sqlglot.generator.Generator.expressions", "modulename": "sqlglot.generator", "qualname": "Generator.expressions", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">key</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">sqls</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Collection</span><span class=\"p\">[</span><span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">flat</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span>,</span><span class=\"param\">\t<span class=\"n\">indent</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">skip_first</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span>,</span><span class=\"param\">\t<span class=\"n\">skip_last</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span>,</span><span class=\"param\">\t<span class=\"n\">sep</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">', '</span>,</span><span class=\"param\">\t<span class=\"n\">prefix</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">''</span>,</span><span class=\"param\">\t<span class=\"n\">dynamic</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span>,</span><span class=\"param\">\t<span class=\"n\">new_line</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.op_expressions": {"fullname": "sqlglot.generator.Generator.op_expressions", "modulename": "sqlglot.generator", "qualname": "Generator.op_expressions", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">op</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">flat</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.naked_property": {"fullname": "sqlglot.generator.Generator.naked_property", "modulename": "sqlglot.generator", "qualname": "Generator.naked_property", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Property</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.tag_sql": {"fullname": "sqlglot.generator.Generator.tag_sql", "modulename": "sqlglot.generator", "qualname": "Generator.tag_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Tag</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.token_sql": {"fullname": "sqlglot.generator.Generator.token_sql", "modulename": "sqlglot.generator", "qualname": "Generator.token_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">token_type</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">tokens</span><span class=\"o\">.</span><span class=\"n\">TokenType</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.userdefinedfunction_sql": {"fullname": "sqlglot.generator.Generator.userdefinedfunction_sql", "modulename": "sqlglot.generator", "qualname": "Generator.userdefinedfunction_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">UserDefinedFunction</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.joinhint_sql": {"fullname": "sqlglot.generator.Generator.joinhint_sql", "modulename": "sqlglot.generator", "qualname": "Generator.joinhint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">JoinHint</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.kwarg_sql": {"fullname": "sqlglot.generator.Generator.kwarg_sql", "modulename": "sqlglot.generator", "qualname": "Generator.kwarg_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Kwarg</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.when_sql": {"fullname": "sqlglot.generator.Generator.when_sql", "modulename": "sqlglot.generator", "qualname": "Generator.when_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">When</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.merge_sql": {"fullname": "sqlglot.generator.Generator.merge_sql", "modulename": "sqlglot.generator", "qualname": "Generator.merge_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Merge</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.tochar_sql": {"fullname": "sqlglot.generator.Generator.tochar_sql", "modulename": "sqlglot.generator", "qualname": "Generator.tochar_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ToChar</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.tonumber_sql": {"fullname": "sqlglot.generator.Generator.tonumber_sql", "modulename": "sqlglot.generator", "qualname": "Generator.tonumber_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ToNumber</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.dictproperty_sql": {"fullname": "sqlglot.generator.Generator.dictproperty_sql", "modulename": "sqlglot.generator", "qualname": "Generator.dictproperty_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DictProperty</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.dictrange_sql": {"fullname": "sqlglot.generator.Generator.dictrange_sql", "modulename": "sqlglot.generator", "qualname": "Generator.dictrange_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DictRange</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.dictsubproperty_sql": {"fullname": "sqlglot.generator.Generator.dictsubproperty_sql", "modulename": "sqlglot.generator", "qualname": "Generator.dictsubproperty_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DictSubProperty</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.oncluster_sql": {"fullname": "sqlglot.generator.Generator.oncluster_sql", "modulename": "sqlglot.generator", "qualname": "Generator.oncluster_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">OnCluster</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.clusteredbyproperty_sql": {"fullname": "sqlglot.generator.Generator.clusteredbyproperty_sql", "modulename": "sqlglot.generator", "qualname": "Generator.clusteredbyproperty_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ClusteredByProperty</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.anyvalue_sql": {"fullname": "sqlglot.generator.Generator.anyvalue_sql", "modulename": "sqlglot.generator", "qualname": "Generator.anyvalue_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">AnyValue</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.querytransform_sql": {"fullname": "sqlglot.generator.Generator.querytransform_sql", "modulename": "sqlglot.generator", "qualname": "Generator.querytransform_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">QueryTransform</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.indexconstraintoption_sql": {"fullname": "sqlglot.generator.Generator.indexconstraintoption_sql", "modulename": "sqlglot.generator", "qualname": "Generator.indexconstraintoption_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">IndexConstraintOption</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.checkcolumnconstraint_sql": {"fullname": "sqlglot.generator.Generator.checkcolumnconstraint_sql", "modulename": "sqlglot.generator", "qualname": "Generator.checkcolumnconstraint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">CheckColumnConstraint</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.indexcolumnconstraint_sql": {"fullname": "sqlglot.generator.Generator.indexcolumnconstraint_sql", "modulename": "sqlglot.generator", "qualname": "Generator.indexcolumnconstraint_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">IndexColumnConstraint</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.nvl2_sql": {"fullname": "sqlglot.generator.Generator.nvl2_sql", "modulename": "sqlglot.generator", "qualname": "Generator.nvl2_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Nvl2</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.comprehension_sql": {"fullname": "sqlglot.generator.Generator.comprehension_sql", "modulename": "sqlglot.generator", "qualname": "Generator.comprehension_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Comprehension</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.columnprefix_sql": {"fullname": "sqlglot.generator.Generator.columnprefix_sql", "modulename": "sqlglot.generator", "qualname": "Generator.columnprefix_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ColumnPrefix</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.opclass_sql": {"fullname": "sqlglot.generator.Generator.opclass_sql", "modulename": "sqlglot.generator", "qualname": "Generator.opclass_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Opclass</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.predict_sql": {"fullname": "sqlglot.generator.Generator.predict_sql", "modulename": "sqlglot.generator", "qualname": "Generator.predict_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Predict</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.forin_sql": {"fullname": "sqlglot.generator.Generator.forin_sql", "modulename": "sqlglot.generator", "qualname": "Generator.forin_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ForIn</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.refresh_sql": {"fullname": "sqlglot.generator.Generator.refresh_sql", "modulename": "sqlglot.generator", "qualname": "Generator.refresh_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Refresh</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.operator_sql": {"fullname": "sqlglot.generator.Generator.operator_sql", "modulename": "sqlglot.generator", "qualname": "Generator.operator_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Operator</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.toarray_sql": {"fullname": "sqlglot.generator.Generator.toarray_sql", "modulename": "sqlglot.generator", "qualname": "Generator.toarray_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ToArray</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.tsordstotime_sql": {"fullname": "sqlglot.generator.Generator.tsordstotime_sql", "modulename": "sqlglot.generator", "qualname": "Generator.tsordstotime_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TsOrDsToTime</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.tsordstotimestamp_sql": {"fullname": "sqlglot.generator.Generator.tsordstotimestamp_sql", "modulename": "sqlglot.generator", "qualname": "Generator.tsordstotimestamp_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TsOrDsToTimestamp</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.tsordstodate_sql": {"fullname": "sqlglot.generator.Generator.tsordstodate_sql", "modulename": "sqlglot.generator", "qualname": "Generator.tsordstodate_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TsOrDsToDate</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.unixdate_sql": {"fullname": "sqlglot.generator.Generator.unixdate_sql", "modulename": "sqlglot.generator", "qualname": "Generator.unixdate_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">UnixDate</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.lastday_sql": {"fullname": "sqlglot.generator.Generator.lastday_sql", "modulename": "sqlglot.generator", "qualname": "Generator.lastday_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">LastDay</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.dateadd_sql": {"fullname": "sqlglot.generator.Generator.dateadd_sql", "modulename": "sqlglot.generator", "qualname": "Generator.dateadd_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DateAdd</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.arrayany_sql": {"fullname": "sqlglot.generator.Generator.arrayany_sql", "modulename": "sqlglot.generator", "qualname": "Generator.arrayany_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ArrayAny</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.generateseries_sql": {"fullname": "sqlglot.generator.Generator.generateseries_sql", "modulename": "sqlglot.generator", "qualname": "Generator.generateseries_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">GenerateSeries</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.struct_sql": {"fullname": "sqlglot.generator.Generator.struct_sql", "modulename": "sqlglot.generator", "qualname": "Generator.struct_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Struct</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.partitionrange_sql": {"fullname": "sqlglot.generator.Generator.partitionrange_sql", "modulename": "sqlglot.generator", "qualname": "Generator.partitionrange_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">PartitionRange</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.truncatetable_sql": {"fullname": "sqlglot.generator.Generator.truncatetable_sql", "modulename": "sqlglot.generator", "qualname": "Generator.truncatetable_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TruncateTable</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.convert_sql": {"fullname": "sqlglot.generator.Generator.convert_sql", "modulename": "sqlglot.generator", "qualname": "Generator.convert_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Convert</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.copyparameter_sql": {"fullname": "sqlglot.generator.Generator.copyparameter_sql", "modulename": "sqlglot.generator", "qualname": "Generator.copyparameter_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">CopyParameter</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.credentials_sql": {"fullname": "sqlglot.generator.Generator.credentials_sql", "modulename": "sqlglot.generator", "qualname": "Generator.credentials_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Credentials</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.copy_sql": {"fullname": "sqlglot.generator.Generator.copy_sql", "modulename": "sqlglot.generator", "qualname": "Generator.copy_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Copy</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.semicolon_sql": {"fullname": "sqlglot.generator.Generator.semicolon_sql", "modulename": "sqlglot.generator", "qualname": "Generator.semicolon_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Semicolon</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.generator.Generator.datadeletionproperty_sql": {"fullname": "sqlglot.generator.Generator.datadeletionproperty_sql", "modulename": "sqlglot.generator", "qualname": "Generator.datadeletionproperty_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataDeletionProperty</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.helper": {"fullname": "sqlglot.helper", "modulename": "sqlglot.helper", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.helper.CAMEL_CASE_PATTERN": {"fullname": "sqlglot.helper.CAMEL_CASE_PATTERN", "modulename": "sqlglot.helper", "qualname": "CAMEL_CASE_PATTERN", "kind": "variable", "doc": "<p></p>\n", "default_value": "re.compile('(?<!^)(?=[A-Z])')"}, "sqlglot.helper.PYTHON_VERSION": {"fullname": "sqlglot.helper.PYTHON_VERSION", "modulename": "sqlglot.helper", "qualname": "PYTHON_VERSION", "kind": "variable", "doc": "<p></p>\n", "default_value": "(3, 10)"}, "sqlglot.helper.logger": {"fullname": "sqlglot.helper.logger", "modulename": "sqlglot.helper", "qualname": "logger", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Logger sqlglot (WARNING)>"}, "sqlglot.helper.AutoName": {"fullname": "sqlglot.helper.AutoName", "modulename": "sqlglot.helper", "qualname": "AutoName", "kind": "class", "doc": "<p>This is used for creating Enum classes where <code>auto()</code> is the string form\nof the corresponding enum's identifier (e.g. FOO.value results in \"FOO\").</p>\n\n<p>Reference: <a href=\"https://docs.python.org/3/howto/enum.html#using-automatic-values\">https://docs.python.org/3/howto/enum.html#using-automatic-values</a></p>\n", "bases": "enum.Enum"}, "sqlglot.helper.classproperty": {"fullname": "sqlglot.helper.classproperty", "modulename": "sqlglot.helper", "qualname": "classproperty", "kind": "class", "doc": "<p>Similar to a normal property but works for class methods</p>\n", "bases": "builtins.property"}, "sqlglot.helper.seq_get": {"fullname": "sqlglot.helper.seq_get", "modulename": "sqlglot.helper", "qualname": "seq_get", "kind": "function", "doc": "<p>Returns the value in <code>seq</code> at position <code>index</code>, or <code>None</code> if <code>index</code> is out of bounds.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">seq</span><span class=\"p\">:</span> <span class=\"n\">Sequence</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">T</span><span class=\"p\">]</span>, </span><span class=\"param\"><span class=\"n\">index</span><span class=\"p\">:</span> <span class=\"nb\">int</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">T</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.helper.ensure_list": {"fullname": "sqlglot.helper.ensure_list", "modulename": "sqlglot.helper", "qualname": "ensure_list", "kind": "function", "doc": "<p>Ensures that a value is a list, otherwise casts or wraps it into one.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>value:</strong> The value of interest.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The value cast as a list if it's a list or a tuple, or else the value wrapped in a list.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">value</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.helper.ensure_collection": {"fullname": "sqlglot.helper.ensure_collection", "modulename": "sqlglot.helper", "qualname": "ensure_collection", "kind": "function", "doc": "<p>Ensures that a value is a collection (excluding <code>str</code> and <code>bytes</code>), otherwise wraps it into a list.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>value:</strong> The value of interest.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The value if it's a collection, or else the value wrapped in a list.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">value</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.helper.csv": {"fullname": "sqlglot.helper.csv", "modulename": "sqlglot.helper", "qualname": "csv", "kind": "function", "doc": "<p>Formats any number of string arguments as CSV.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>args:</strong> The string arguments to format.</li>\n<li><strong>sep:</strong> The argument separator.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The arguments formatted as a CSV string.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"o\">*</span><span class=\"n\">args</span><span class=\"p\">:</span> <span class=\"nb\">str</span>, </span><span class=\"param\"><span class=\"n\">sep</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">', '</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.helper.subclasses": {"fullname": "sqlglot.helper.subclasses", "modulename": "sqlglot.helper", "qualname": "subclasses", "kind": "function", "doc": "<p>Returns all subclasses for a collection of classes, possibly excluding some of them.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>module_name:</strong> The name of the module to search for subclasses in.</li>\n<li><strong>classes:</strong> Class(es) we want to find the subclasses of.</li>\n<li><strong>exclude:</strong> Class(es) we want to exclude from the returned list.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The target subclasses.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">module_name</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">classes</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">Type</span><span class=\"p\">,</span> <span class=\"n\">Tuple</span><span class=\"p\">[</span><span class=\"n\">Type</span><span class=\"p\">,</span> <span class=\"o\">...</span><span class=\"p\">]]</span>,</span><span class=\"param\">\t<span class=\"n\">exclude</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">Type</span><span class=\"p\">,</span> <span class=\"n\">Tuple</span><span class=\"p\">[</span><span class=\"n\">Type</span><span class=\"p\">,</span> <span class=\"o\">...</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"p\">()</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">Type</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.helper.apply_index_offset": {"fullname": "sqlglot.helper.apply_index_offset", "modulename": "sqlglot.helper", "qualname": "apply_index_offset", "kind": "function", "doc": "<p>Applies an offset to a given integer literal expression.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>this:</strong> The target of the index.</li>\n<li><strong>expressions:</strong> The expression the offset will be applied to, wrapped in a list.</li>\n<li><strong>offset:</strong> The offset that will be applied.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The original expression with the offset applied to it, wrapped in a list. If the provided\n <code>expressions</code> argument contains more than one expression, it's returned unaffected.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">this</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">expressions</span><span class=\"p\">:</span> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">E</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">offset</span><span class=\"p\">:</span> <span class=\"nb\">int</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">E</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.helper.camel_to_snake_case": {"fullname": "sqlglot.helper.camel_to_snake_case", "modulename": "sqlglot.helper", "qualname": "camel_to_snake_case", "kind": "function", "doc": "<p>Converts <code>name</code> from camelCase to snake_case and returns the result.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">name</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.helper.while_changing": {"fullname": "sqlglot.helper.while_changing", "modulename": "sqlglot.helper", "qualname": "while_changing", "kind": "function", "doc": "<p>Applies a transformation to a given expression until a fix point is reached.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> The expression to be transformed.</li>\n<li><strong>func:</strong> The transformation to be applied.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The transformed expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">func</span><span class=\"p\">:</span> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">],</span> <span class=\"o\">~</span><span class=\"n\">E</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"o\">~</span><span class=\"n\">E</span>:</span></span>", "funcdef": "def"}, "sqlglot.helper.tsort": {"fullname": "sqlglot.helper.tsort", "modulename": "sqlglot.helper", "qualname": "tsort", "kind": "function", "doc": "<p>Sorts a given directed acyclic graph in topological order.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>dag:</strong> The graph to be sorted.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>A list that contains all of the graph's nodes in topological order.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">dag</span><span class=\"p\">:</span> <span class=\"n\">Dict</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">T</span><span class=\"p\">,</span> <span class=\"n\">Set</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">T</span><span class=\"p\">]]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">T</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.helper.open_file": {"fullname": "sqlglot.helper.open_file", "modulename": "sqlglot.helper", "qualname": "open_file", "kind": "function", "doc": "<p>Open a file that may be compressed as gzip and return it in universal newline mode.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">file_name</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <class 'TextIO'>:</span></span>", "funcdef": "def"}, "sqlglot.helper.csv_reader": {"fullname": "sqlglot.helper.csv_reader", "modulename": "sqlglot.helper", "qualname": "csv_reader", "kind": "function", "doc": "<p>Returns a csv reader given the expression <code>READ_CSV(name, ['delimiter', '|', ...])</code>.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>read_csv:</strong> A <code>ReadCSV</code> function call.</li>\n</ul>\n\n<h6 id=\"yields\">Yields:</h6>\n\n<blockquote>\n <p>A python csv reader.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">read_csv</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ReadCSV</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Any</span>:</span></span>", "funcdef": "def"}, "sqlglot.helper.find_new_name": {"fullname": "sqlglot.helper.find_new_name", "modulename": "sqlglot.helper", "qualname": "find_new_name", "kind": "function", "doc": "<p>Searches for a new name.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>taken:</strong> A collection of taken names.</li>\n<li><strong>base:</strong> Base name to alter.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The new, available name.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">taken</span><span class=\"p\">:</span> <span class=\"n\">Collection</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span>, </span><span class=\"param\"><span class=\"n\">base</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.helper.is_int": {"fullname": "sqlglot.helper.is_int", "modulename": "sqlglot.helper", "qualname": "is_int", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">text</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">bool</span>:</span></span>", "funcdef": "def"}, "sqlglot.helper.is_float": {"fullname": "sqlglot.helper.is_float", "modulename": "sqlglot.helper", "qualname": "is_float", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">text</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">bool</span>:</span></span>", "funcdef": "def"}, "sqlglot.helper.is_type": {"fullname": "sqlglot.helper.is_type", "modulename": "sqlglot.helper", "qualname": "is_type", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">text</span><span class=\"p\">:</span> <span class=\"nb\">str</span>, </span><span class=\"param\"><span class=\"n\">target_type</span><span class=\"p\">:</span> <span class=\"n\">Type</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">bool</span>:</span></span>", "funcdef": "def"}, "sqlglot.helper.name_sequence": {"fullname": "sqlglot.helper.name_sequence", "modulename": "sqlglot.helper", "qualname": "name_sequence", "kind": "function", "doc": "<p>Returns a name generator given a prefix (e.g. a0, a1, a2, ... if the prefix is \"a\").</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">prefix</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Callable</span><span class=\"p\">[[],</span> <span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.helper.object_to_dict": {"fullname": "sqlglot.helper.object_to_dict", "modulename": "sqlglot.helper", "qualname": "object_to_dict", "kind": "function", "doc": "<p>Returns a dictionary created from an object's attributes.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">obj</span><span class=\"p\">:</span> <span class=\"n\">Any</span>, </span><span class=\"param\"><span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Dict</span>:</span></span>", "funcdef": "def"}, "sqlglot.helper.split_num_words": {"fullname": "sqlglot.helper.split_num_words", "modulename": "sqlglot.helper", "qualname": "split_num_words", "kind": "function", "doc": "<p>Perform a split on a value and return N words as a result with <code>None</code> used for words that don't exist.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>value:</strong> The value to be split.</li>\n<li><strong>sep:</strong> The value to use to split on.</li>\n<li><strong>min_num_words:</strong> The minimum number of words that are going to be in the result.</li>\n<li><strong>fill_from_start:</strong> Indicates that if <code>None</code> values should be inserted at the start or end of the list.</li>\n</ul>\n\n<h6 id=\"examples\">Examples:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">split_num_words</span><span class=\"p\">(</span><span class=\"s2\">"db.table"</span><span class=\"p\">,</span> <span class=\"s2\">"."</span><span class=\"p\">,</span> <span class=\"mi\">3</span><span class=\"p\">)</span>\n<span class=\"go\">[None, 'db', 'table']</span>\n<span class=\"gp\">>>> </span><span class=\"n\">split_num_words</span><span class=\"p\">(</span><span class=\"s2\">"db.table"</span><span class=\"p\">,</span> <span class=\"s2\">"."</span><span class=\"p\">,</span> <span class=\"mi\">3</span><span class=\"p\">,</span> <span class=\"n\">fill_from_start</span><span class=\"o\">=</span><span class=\"kc\">False</span><span class=\"p\">)</span>\n<span class=\"go\">['db', 'table', None]</span>\n<span class=\"gp\">>>> </span><span class=\"n\">split_num_words</span><span class=\"p\">(</span><span class=\"s2\">"db.table"</span><span class=\"p\">,</span> <span class=\"s2\">"."</span><span class=\"p\">,</span> <span class=\"mi\">1</span><span class=\"p\">)</span>\n<span class=\"go\">['db', 'table']</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The list of words returned by <code>split</code>, possibly augmented by a number of <code>None</code> values.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">value</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">sep</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">min_num_words</span><span class=\"p\">:</span> <span class=\"nb\">int</span>,</span><span class=\"param\">\t<span class=\"n\">fill_from_start</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]]</span>:</span></span>", "funcdef": "def"}, "sqlglot.helper.is_iterable": {"fullname": "sqlglot.helper.is_iterable", "modulename": "sqlglot.helper", "qualname": "is_iterable", "kind": "function", "doc": "<p>Checks if the value is an iterable, excluding the types <code>str</code> and <code>bytes</code>.</p>\n\n<h6 id=\"examples\">Examples:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">is_iterable</span><span class=\"p\">([</span><span class=\"mi\">1</span><span class=\"p\">,</span><span class=\"mi\">2</span><span class=\"p\">])</span>\n<span class=\"go\">True</span>\n<span class=\"gp\">>>> </span><span class=\"n\">is_iterable</span><span class=\"p\">(</span><span class=\"s2\">"test"</span><span class=\"p\">)</span>\n<span class=\"go\">False</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>value:</strong> The value to check if it is an iterable.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>A <code>bool</code> value indicating if it is an iterable.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">value</span><span class=\"p\">:</span> <span class=\"n\">Any</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">bool</span>:</span></span>", "funcdef": "def"}, "sqlglot.helper.flatten": {"fullname": "sqlglot.helper.flatten", "modulename": "sqlglot.helper", "qualname": "flatten", "kind": "function", "doc": "<p>Flattens an iterable that can contain both iterable and non-iterable elements. Objects of\ntype <code>str</code> and <code>bytes</code> are not regarded as iterables.</p>\n\n<h6 id=\"examples\">Examples:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"nb\">list</span><span class=\"p\">(</span><span class=\"n\">flatten</span><span class=\"p\">([[</span><span class=\"mi\">1</span><span class=\"p\">,</span> <span class=\"mi\">2</span><span class=\"p\">],</span> <span class=\"mi\">3</span><span class=\"p\">,</span> <span class=\"p\">{</span><span class=\"mi\">4</span><span class=\"p\">},</span> <span class=\"p\">(</span><span class=\"mi\">5</span><span class=\"p\">,</span> <span class=\"s2\">"bla"</span><span class=\"p\">)]))</span>\n<span class=\"go\">[1, 2, 3, 4, 5, 'bla']</span>\n<span class=\"gp\">>>> </span><span class=\"nb\">list</span><span class=\"p\">(</span><span class=\"n\">flatten</span><span class=\"p\">([</span><span class=\"mi\">1</span><span class=\"p\">,</span> <span class=\"mi\">2</span><span class=\"p\">,</span> <span class=\"mi\">3</span><span class=\"p\">]))</span>\n<span class=\"go\">[1, 2, 3]</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>values:</strong> The value to be flattened.</li>\n</ul>\n\n<h6 id=\"yields\">Yields:</h6>\n\n<blockquote>\n <p>Non-iterable elements in <code>values</code>.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">values</span><span class=\"p\">:</span> <span class=\"n\">Iterable</span><span class=\"p\">[</span><span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">Iterable</span><span class=\"p\">[</span><span class=\"n\">Any</span><span class=\"p\">],</span> <span class=\"n\">Any</span><span class=\"p\">]]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Iterator</span><span class=\"p\">[</span><span class=\"n\">Any</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.helper.dict_depth": {"fullname": "sqlglot.helper.dict_depth", "modulename": "sqlglot.helper", "qualname": "dict_depth", "kind": "function", "doc": "<p>Get the nesting depth of a dictionary.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">dict_depth</span><span class=\"p\">(</span><span class=\"kc\">None</span><span class=\"p\">)</span>\n<span class=\"go\">0</span>\n<span class=\"gp\">>>> </span><span class=\"n\">dict_depth</span><span class=\"p\">({})</span>\n<span class=\"go\">1</span>\n<span class=\"gp\">>>> </span><span class=\"n\">dict_depth</span><span class=\"p\">({</span><span class=\"s2\">"a"</span><span class=\"p\">:</span> <span class=\"s2\">"b"</span><span class=\"p\">})</span>\n<span class=\"go\">1</span>\n<span class=\"gp\">>>> </span><span class=\"n\">dict_depth</span><span class=\"p\">({</span><span class=\"s2\">"a"</span><span class=\"p\">:</span> <span class=\"p\">{}})</span>\n<span class=\"go\">2</span>\n<span class=\"gp\">>>> </span><span class=\"n\">dict_depth</span><span class=\"p\">({</span><span class=\"s2\">"a"</span><span class=\"p\">:</span> <span class=\"p\">{</span><span class=\"s2\">"b"</span><span class=\"p\">:</span> <span class=\"p\">{}}})</span>\n<span class=\"go\">3</span>\n</code></pre>\n </div>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">d</span><span class=\"p\">:</span> <span class=\"n\">Dict</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">int</span>:</span></span>", "funcdef": "def"}, "sqlglot.helper.first": {"fullname": "sqlglot.helper.first", "modulename": "sqlglot.helper", "qualname": "first", "kind": "function", "doc": "<p>Returns the first element from an iterable (useful for sets).</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">it</span><span class=\"p\">:</span> <span class=\"n\">Iterable</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">T</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"o\">~</span><span class=\"n\">T</span>:</span></span>", "funcdef": "def"}, "sqlglot.helper.merge_ranges": {"fullname": "sqlglot.helper.merge_ranges", "modulename": "sqlglot.helper", "qualname": "merge_ranges", "kind": "function", "doc": "<p>Merges a sequence of ranges, represented as tuples (low, high) whose values\nbelong to some totally-ordered set.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">merge_ranges</span><span class=\"p\">([(</span><span class=\"mi\">1</span><span class=\"p\">,</span> <span class=\"mi\">3</span><span class=\"p\">),</span> <span class=\"p\">(</span><span class=\"mi\">2</span><span class=\"p\">,</span> <span class=\"mi\">6</span><span class=\"p\">)])</span>\n<span class=\"go\">[(1, 6)]</span>\n</code></pre>\n </div>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">ranges</span><span class=\"p\">:</span> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">Tuple</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">A</span><span class=\"p\">,</span> <span class=\"o\">~</span><span class=\"n\">A</span><span class=\"p\">]]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">Tuple</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">A</span><span class=\"p\">,</span> <span class=\"o\">~</span><span class=\"n\">A</span><span class=\"p\">]]</span>:</span></span>", "funcdef": "def"}, "sqlglot.helper.is_iso_date": {"fullname": "sqlglot.helper.is_iso_date", "modulename": "sqlglot.helper", "qualname": "is_iso_date", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">text</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">bool</span>:</span></span>", "funcdef": "def"}, "sqlglot.helper.is_iso_datetime": {"fullname": "sqlglot.helper.is_iso_datetime", "modulename": "sqlglot.helper", "qualname": "is_iso_datetime", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">text</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">bool</span>:</span></span>", "funcdef": "def"}, "sqlglot.helper.DATE_UNITS": {"fullname": "sqlglot.helper.DATE_UNITS", "modulename": "sqlglot.helper", "qualname": "DATE_UNITS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'year_month', 'week', 'day', 'year', 'month', 'quarter'}"}, "sqlglot.helper.is_date_unit": {"fullname": "sqlglot.helper.is_date_unit", "modulename": "sqlglot.helper", "qualname": "is_date_unit", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">bool</span>:</span></span>", "funcdef": "def"}, "sqlglot.helper.SingleValuedMapping": {"fullname": "sqlglot.helper.SingleValuedMapping", "modulename": "sqlglot.helper", "qualname": "SingleValuedMapping", "kind": "class", "doc": "<p>Mapping where all keys return the same value.</p>\n\n<p>This rigamarole is meant to avoid copying keys, which was originally intended\nas an optimization while qualifying columns for tables with lots of columns.</p>\n", "bases": "typing.Mapping[~K, ~V]"}, "sqlglot.helper.SingleValuedMapping.__init__": {"fullname": "sqlglot.helper.SingleValuedMapping.__init__", "modulename": "sqlglot.helper", "qualname": "SingleValuedMapping.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">keys</span><span class=\"p\">:</span> <span class=\"n\">Collection</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">K</span><span class=\"p\">]</span>, </span><span class=\"param\"><span class=\"n\">value</span><span class=\"p\">:</span> <span class=\"o\">~</span><span class=\"n\">V</span></span>)</span>"}, "sqlglot.jsonpath": {"fullname": "sqlglot.jsonpath", "modulename": "sqlglot.jsonpath", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.jsonpath.JSONPathTokenizer": {"fullname": "sqlglot.jsonpath.JSONPathTokenizer", "modulename": "sqlglot.jsonpath", "qualname": "JSONPathTokenizer", "kind": "class", "doc": "<p></p>\n", "bases": "sqlglot.tokens.Tokenizer"}, "sqlglot.jsonpath.JSONPathTokenizer.SINGLE_TOKENS": {"fullname": "sqlglot.jsonpath.JSONPathTokenizer.SINGLE_TOKENS", "modulename": "sqlglot.jsonpath", "qualname": "JSONPathTokenizer.SINGLE_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'(': <TokenType.L_PAREN: 'L_PAREN'>, ')': <TokenType.R_PAREN: 'R_PAREN'>, '[': <TokenType.L_BRACKET: 'L_BRACKET'>, ']': <TokenType.R_BRACKET: 'R_BRACKET'>, ':': <TokenType.COLON: 'COLON'>, ',': <TokenType.COMMA: 'COMMA'>, '-': <TokenType.DASH: 'DASH'>, '.': <TokenType.DOT: 'DOT'>, '?': <TokenType.PLACEHOLDER: 'PLACEHOLDER'>, '@': <TokenType.PARAMETER: 'PARAMETER'>, "'": <TokenType.QUOTE: 'QUOTE'>, '"': <TokenType.QUOTE: 'QUOTE'>, '$': <TokenType.DOLLAR: 'DOLLAR'>, '*': <TokenType.STAR: 'STAR'>}"}, "sqlglot.jsonpath.JSONPathTokenizer.KEYWORDS": {"fullname": "sqlglot.jsonpath.JSONPathTokenizer.KEYWORDS", "modulename": "sqlglot.jsonpath", "qualname": "JSONPathTokenizer.KEYWORDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'..': <TokenType.DOT: 'DOT'>}"}, "sqlglot.jsonpath.JSONPathTokenizer.IDENTIFIER_ESCAPES": {"fullname": "sqlglot.jsonpath.JSONPathTokenizer.IDENTIFIER_ESCAPES", "modulename": "sqlglot.jsonpath", "qualname": "JSONPathTokenizer.IDENTIFIER_ESCAPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "['\\\\']"}, "sqlglot.jsonpath.JSONPathTokenizer.STRING_ESCAPES": {"fullname": "sqlglot.jsonpath.JSONPathTokenizer.STRING_ESCAPES", "modulename": "sqlglot.jsonpath", "qualname": "JSONPathTokenizer.STRING_ESCAPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "['\\\\']"}, "sqlglot.jsonpath.parse": {"fullname": "sqlglot.jsonpath.parse", "modulename": "sqlglot.jsonpath", "qualname": "parse", "kind": "function", "doc": "<p>Takes in a JSON path string and parses it into a JSONPath expression.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">path</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">JSONPath</span>:</span></span>", "funcdef": "def"}, "sqlglot.jsonpath.JSON_PATH_PART_TRANSFORMS": {"fullname": "sqlglot.jsonpath.JSON_PATH_PART_TRANSFORMS", "modulename": "sqlglot.jsonpath", "qualname": "JSON_PATH_PART_TRANSFORMS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[Type[sqlglot.expressions.Expression], Callable[..., str]]", "default_value": "{<class 'sqlglot.expressions.JSONPathFilter'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathKey'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRecursive'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathRoot'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathScript'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSelector'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSlice'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathSubscript'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathUnion'>: <function <lambda>>, <class 'sqlglot.expressions.JSONPathWildcard'>: <function <lambda>>}"}, "sqlglot.jsonpath.ALL_JSON_PATH_PARTS": {"fullname": "sqlglot.jsonpath.ALL_JSON_PATH_PARTS", "modulename": "sqlglot.jsonpath", "qualname": "ALL_JSON_PATH_PARTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.JSONPathRecursive'>, <class 'sqlglot.expressions.JSONPathKey'>, <class 'sqlglot.expressions.JSONPathWildcard'>, <class 'sqlglot.expressions.JSONPathFilter'>, <class 'sqlglot.expressions.JSONPathUnion'>, <class 'sqlglot.expressions.JSONPathSubscript'>, <class 'sqlglot.expressions.JSONPathSelector'>, <class 'sqlglot.expressions.JSONPathSlice'>, <class 'sqlglot.expressions.JSONPathScript'>, <class 'sqlglot.expressions.JSONPathRoot'>}"}, "sqlglot.lineage": {"fullname": "sqlglot.lineage", "modulename": "sqlglot.lineage", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.lineage.logger": {"fullname": "sqlglot.lineage.logger", "modulename": "sqlglot.lineage", "qualname": "logger", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Logger sqlglot (WARNING)>"}, "sqlglot.lineage.Node": {"fullname": "sqlglot.lineage.Node", "modulename": "sqlglot.lineage", "qualname": "Node", "kind": "class", "doc": "<p></p>\n"}, "sqlglot.lineage.Node.__init__": {"fullname": "sqlglot.lineage.Node.__init__", "modulename": "sqlglot.lineage", "qualname": "Node.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">name</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">source</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">downstream</span><span class=\"p\">:</span> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">lineage</span><span class=\"o\">.</span><span class=\"n\">Node</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"o\"><</span><span class=\"n\">factory</span><span class=\"o\">></span>,</span><span class=\"param\">\t<span class=\"n\">source_name</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">''</span>,</span><span class=\"param\">\t<span class=\"n\">reference_node_name</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">=</span> <span class=\"s1\">''</span></span>)</span>"}, "sqlglot.lineage.Node.name": {"fullname": "sqlglot.lineage.Node.name", "modulename": "sqlglot.lineage", "qualname": "Node.name", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.lineage.Node.expression": {"fullname": "sqlglot.lineage.Node.expression", "modulename": "sqlglot.lineage", "qualname": "Node.expression", "kind": "variable", "doc": "<p></p>\n", "annotation": ": sqlglot.expressions.Expression"}, "sqlglot.lineage.Node.source": {"fullname": "sqlglot.lineage.Node.source", "modulename": "sqlglot.lineage", "qualname": "Node.source", "kind": "variable", "doc": "<p></p>\n", "annotation": ": sqlglot.expressions.Expression"}, "sqlglot.lineage.Node.downstream": {"fullname": "sqlglot.lineage.Node.downstream", "modulename": "sqlglot.lineage", "qualname": "Node.downstream", "kind": "variable", "doc": "<p></p>\n", "annotation": ": List[sqlglot.lineage.Node]"}, "sqlglot.lineage.Node.source_name": {"fullname": "sqlglot.lineage.Node.source_name", "modulename": "sqlglot.lineage", "qualname": "Node.source_name", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str", "default_value": "''"}, "sqlglot.lineage.Node.reference_node_name": {"fullname": "sqlglot.lineage.Node.reference_node_name", "modulename": "sqlglot.lineage", "qualname": "Node.reference_node_name", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str", "default_value": "''"}, "sqlglot.lineage.Node.walk": {"fullname": "sqlglot.lineage.Node.walk", "modulename": "sqlglot.lineage", "qualname": "Node.walk", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Iterator</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">lineage</span><span class=\"o\">.</span><span class=\"n\">Node</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.lineage.Node.to_html": {"fullname": "sqlglot.lineage.Node.to_html", "modulename": "sqlglot.lineage", "qualname": "Node.to_html", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">opts</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">lineage</span><span class=\"o\">.</span><span class=\"n\">GraphHTML</span>:</span></span>", "funcdef": "def"}, "sqlglot.lineage.lineage": {"fullname": "sqlglot.lineage.lineage", "modulename": "sqlglot.lineage", "qualname": "lineage", "kind": "function", "doc": "<p>Build the lineage graph for a column of a SQL query.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>column:</strong> The column to build the lineage for.</li>\n<li><strong>sql:</strong> The SQL string or expression.</li>\n<li><strong>schema:</strong> The schema of tables.</li>\n<li><strong>sources:</strong> A mapping of queries which will be used to continue building lineage.</li>\n<li><strong>dialect:</strong> The dialect of input SQL.</li>\n<li><strong>scope:</strong> A pre-created scope to use instead.</li>\n<li><strong>trim_selects:</strong> Whether or not to clean up selects by trimming to only relevant columns.</li>\n<li><strong>**kwargs:</strong> Qualification optimizer kwargs.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>A lineage node.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">column</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Column</span>,</span><span class=\"param\">\t<span class=\"n\">sql</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">schema</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">schema</span><span class=\"o\">.</span><span class=\"n\">Schema</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">sources</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Mapping</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Query</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">scope</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">optimizer</span><span class=\"o\">.</span><span class=\"n\">scope</span><span class=\"o\">.</span><span class=\"n\">Scope</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">trim_selects</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">lineage</span><span class=\"o\">.</span><span class=\"n\">Node</span>:</span></span>", "funcdef": "def"}, "sqlglot.lineage.to_node": {"fullname": "sqlglot.lineage.to_node", "modulename": "sqlglot.lineage", "qualname": "to_node", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">column</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"nb\">int</span>,</span><span class=\"param\">\t<span class=\"n\">scope</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">optimizer</span><span class=\"o\">.</span><span class=\"n\">scope</span><span class=\"o\">.</span><span class=\"n\">Scope</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">scope_name</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">upstream</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">lineage</span><span class=\"o\">.</span><span class=\"n\">Node</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">source_name</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">reference_node_name</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">trim_selects</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">lineage</span><span class=\"o\">.</span><span class=\"n\">Node</span>:</span></span>", "funcdef": "def"}, "sqlglot.lineage.GraphHTML": {"fullname": "sqlglot.lineage.GraphHTML", "modulename": "sqlglot.lineage", "qualname": "GraphHTML", "kind": "class", "doc": "<p>Node to HTML generator using vis.js.</p>\n\n<p><a href=\"https://visjs.github.io/vis-network/docs/network/\">https://visjs.github.io/vis-network/docs/network/</a></p>\n"}, "sqlglot.lineage.GraphHTML.__init__": {"fullname": "sqlglot.lineage.GraphHTML.__init__", "modulename": "sqlglot.lineage", "qualname": "GraphHTML.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">nodes</span><span class=\"p\">:</span> <span class=\"n\">Dict</span>,</span><span class=\"param\">\t<span class=\"n\">edges</span><span class=\"p\">:</span> <span class=\"n\">List</span>,</span><span class=\"param\">\t<span class=\"n\">imports</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">options</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span>)</span>"}, "sqlglot.lineage.GraphHTML.imports": {"fullname": "sqlglot.lineage.GraphHTML.imports", "modulename": "sqlglot.lineage", "qualname": "GraphHTML.imports", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.lineage.GraphHTML.options": {"fullname": "sqlglot.lineage.GraphHTML.options", "modulename": "sqlglot.lineage", "qualname": "GraphHTML.options", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.lineage.GraphHTML.nodes": {"fullname": "sqlglot.lineage.GraphHTML.nodes", "modulename": "sqlglot.lineage", "qualname": "GraphHTML.nodes", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.lineage.GraphHTML.edges": {"fullname": "sqlglot.lineage.GraphHTML.edges", "modulename": "sqlglot.lineage", "qualname": "GraphHTML.edges", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.optimizer": {"fullname": "sqlglot.optimizer", "modulename": "sqlglot.optimizer", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.optimizer.annotate_types": {"fullname": "sqlglot.optimizer.annotate_types", "modulename": "sqlglot.optimizer.annotate_types", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.optimizer.annotate_types.annotate_types": {"fullname": "sqlglot.optimizer.annotate_types.annotate_types", "modulename": "sqlglot.optimizer.annotate_types", "qualname": "annotate_types", "kind": "function", "doc": "<p>Infers the types of an expression, annotating its AST accordingly.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"gp\">>>> </span><span class=\"n\">schema</span> <span class=\"o\">=</span> <span class=\"p\">{</span><span class=\"s2\">"y"</span><span class=\"p\">:</span> <span class=\"p\">{</span><span class=\"s2\">"cola"</span><span class=\"p\">:</span> <span class=\"s2\">"SMALLINT"</span><span class=\"p\">}}</span>\n<span class=\"gp\">>>> </span><span class=\"n\">sql</span> <span class=\"o\">=</span> <span class=\"s2\">"SELECT x.cola + 2.5 AS cola FROM (SELECT y.cola AS cola FROM y AS y) AS x"</span>\n<span class=\"gp\">>>> </span><span class=\"n\">annotated_expr</span> <span class=\"o\">=</span> <span class=\"n\">annotate_types</span><span class=\"p\">(</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"n\">sql</span><span class=\"p\">),</span> <span class=\"n\">schema</span><span class=\"o\">=</span><span class=\"n\">schema</span><span class=\"p\">)</span>\n<span class=\"gp\">>>> </span><span class=\"n\">annotated_expr</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">type</span><span class=\"o\">.</span><span class=\"n\">this</span> <span class=\"c1\"># Get the type of "x.cola + 2.5 AS cola"</span>\n<span class=\"go\"><Type.DOUBLE: 'DOUBLE'></span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> Expression to annotate.</li>\n<li><strong>schema:</strong> Database schema.</li>\n<li><strong>annotators:</strong> Maps expression type to corresponding annotation function.</li>\n<li><strong>coerces_to:</strong> Maps expression type to set of types that it can be coerced into.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The expression annotated with types.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"o\">~</span><span class=\"n\">E</span>,</span><span class=\"param\">\t<span class=\"n\">schema</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">schema</span><span class=\"o\">.</span><span class=\"n\">Schema</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">annotators</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">[</span><span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">E</span><span class=\"p\">],</span> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">optimizer</span><span class=\"o\">.</span><span class=\"n\">annotate_types</span><span class=\"o\">.</span><span class=\"n\">TypeAnnotator</span><span class=\"p\">,</span> <span class=\"o\">~</span><span class=\"n\">E</span><span class=\"p\">],</span> <span class=\"o\">~</span><span class=\"n\">E</span><span class=\"p\">]]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">coerces_to</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"p\">,</span> <span class=\"n\">Set</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"p\">]]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"o\">~</span><span class=\"n\">E</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.annotate_types.swap_args": {"fullname": "sqlglot.optimizer.annotate_types.swap_args", "modulename": "sqlglot.optimizer.annotate_types", "qualname": "swap_args", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">func</span><span class=\"p\">:</span> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">],</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">],</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.annotate_types.swap_all": {"fullname": "sqlglot.optimizer.annotate_types.swap_all", "modulename": "sqlglot.optimizer.annotate_types", "qualname": "swap_all", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">coercions</span><span class=\"p\">:</span> <span class=\"n\">Dict</span><span class=\"p\">[</span><span class=\"n\">Tuple</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"p\">],</span> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">],</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"p\">]]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Dict</span><span class=\"p\">[</span><span class=\"n\">Tuple</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"p\">],</span> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">],</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"p\">]]</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.annotate_types.TypeAnnotator": {"fullname": "sqlglot.optimizer.annotate_types.TypeAnnotator", "modulename": "sqlglot.optimizer.annotate_types", "qualname": "TypeAnnotator", "kind": "class", "doc": "<p></p>\n"}, "sqlglot.optimizer.annotate_types.TypeAnnotator.__init__": {"fullname": "sqlglot.optimizer.annotate_types.TypeAnnotator.__init__", "modulename": "sqlglot.optimizer.annotate_types", "qualname": "TypeAnnotator.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">schema</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">schema</span><span class=\"o\">.</span><span class=\"n\">Schema</span>,</span><span class=\"param\">\t<span class=\"n\">annotators</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">[</span><span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">E</span><span class=\"p\">],</span> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">optimizer</span><span class=\"o\">.</span><span class=\"n\">annotate_types</span><span class=\"o\">.</span><span class=\"n\">TypeAnnotator</span><span class=\"p\">,</span> <span class=\"o\">~</span><span class=\"n\">E</span><span class=\"p\">],</span> <span class=\"o\">~</span><span class=\"n\">E</span><span class=\"p\">]]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">coerces_to</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"p\">,</span> <span class=\"n\">Set</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"p\">]]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">binary_coercions</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">[</span><span class=\"n\">Tuple</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"p\">],</span> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">],</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"p\">]]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span>)</span>"}, "sqlglot.optimizer.annotate_types.TypeAnnotator.TYPE_TO_EXPRESSIONS": {"fullname": "sqlglot.optimizer.annotate_types.TypeAnnotator.TYPE_TO_EXPRESSIONS", "modulename": "sqlglot.optimizer.annotate_types", "qualname": "TypeAnnotator.TYPE_TO_EXPRESSIONS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[sqlglot.expressions.DataType.Type, Set[Type[sqlglot.expressions.Expression]]]", "default_value": "{<Type.BIGINT: 'BIGINT'>: {<class 'sqlglot.expressions.Count'>, <class 'sqlglot.expressions.ArraySize'>, <class 'sqlglot.expressions.Length'>, <class 'sqlglot.expressions.ApproxDistinct'>}, <Type.BOOLEAN: 'BOOLEAN'>: {<class 'sqlglot.expressions.Between'>, <class 'sqlglot.expressions.RegexpLike'>, <class 'sqlglot.expressions.In'>, <class 'sqlglot.expressions.Boolean'>}, <Type.DATE: 'DATE'>: {<class 'sqlglot.expressions.DateStrToDate'>, <class 'sqlglot.expressions.TimeStrToDate'>, <class 'sqlglot.expressions.DateFromParts'>, <class 'sqlglot.expressions.DiToDate'>, <class 'sqlglot.expressions.StrToDate'>, <class 'sqlglot.expressions.TsOrDsToDate'>, <class 'sqlglot.expressions.CurrentDate'>, <class 'sqlglot.expressions.Date'>}, <Type.DATETIME: 'DATETIME'>: {<class 'sqlglot.expressions.CurrentDatetime'>, <class 'sqlglot.expressions.DatetimeSub'>, <class 'sqlglot.expressions.DatetimeAdd'>}, <Type.DOUBLE: 'DOUBLE'>: {<class 'sqlglot.expressions.Sqrt'>, <class 'sqlglot.expressions.VariancePop'>, <class 'sqlglot.expressions.StddevPop'>, <class 'sqlglot.expressions.Avg'>, <class 'sqlglot.expressions.ApproxQuantile'>, <class 'sqlglot.expressions.Log'>, <class 'sqlglot.expressions.Exp'>, <class 'sqlglot.expressions.Variance'>, <class 'sqlglot.expressions.Quantile'>, <class 'sqlglot.expressions.Ln'>, <class 'sqlglot.expressions.SafeDivide'>, <class 'sqlglot.expressions.Div'>, <class 'sqlglot.expressions.StddevSamp'>, <class 'sqlglot.expressions.Round'>, <class 'sqlglot.expressions.Stddev'>, <class 'sqlglot.expressions.Pow'>}, <Type.INT: 'INT'>: {<class 'sqlglot.expressions.Sign'>, <class 'sqlglot.expressions.Extract'>, <class 'sqlglot.expressions.Floor'>, <class 'sqlglot.expressions.StrPosition'>, <class 'sqlglot.expressions.DatetimeDiff'>, <class 'sqlglot.expressions.Ceil'>, <class 'sqlglot.expressions.DateDiff'>, <class 'sqlglot.expressions.TimeDiff'>, <class 'sqlglot.expressions.Levenshtein'>, <class 'sqlglot.expressions.DateToDi'>, <class 'sqlglot.expressions.TimestampDiff'>, <class 'sqlglot.expressions.TsOrDiToDi'>}, <Type.JSON: 'JSON'>: {<class 'sqlglot.expressions.ParseJSON'>}, <Type.TIMESTAMP: 'TIMESTAMP'>: {<class 'sqlglot.expressions.CurrentTimestamp'>, <class 'sqlglot.expressions.TimeStrToTime'>, <class 'sqlglot.expressions.TimestampAdd'>, <class 'sqlglot.expressions.CurrentTime'>, <class 'sqlglot.expressions.StrToTime'>, <class 'sqlglot.expressions.UnixToTime'>, <class 'sqlglot.expressions.TimeAdd'>, <class 'sqlglot.expressions.TimeSub'>, <class 'sqlglot.expressions.TimestampSub'>}, <Type.TINYINT: 'TINYINT'>: {<class 'sqlglot.expressions.Quarter'>, <class 'sqlglot.expressions.Day'>, <class 'sqlglot.expressions.Year'>, <class 'sqlglot.expressions.Month'>, <class 'sqlglot.expressions.Week'>}, <Type.VARCHAR: 'VARCHAR'>: {<class 'sqlglot.expressions.ConcatWs'>, <class 'sqlglot.expressions.Lower'>, <class 'sqlglot.expressions.Concat'>, <class 'sqlglot.expressions.Upper'>, <class 'sqlglot.expressions.GroupConcat'>, <class 'sqlglot.expressions.ArrayConcat'>, <class 'sqlglot.expressions.TimeToTimeStr'>, <class 'sqlglot.expressions.TsOrDsToDateStr'>, <class 'sqlglot.expressions.UnixToTimeStr'>, <class 'sqlglot.expressions.TimeToStr'>, <class 'sqlglot.expressions.UnixToStr'>, <class 'sqlglot.expressions.Initcap'>, <class 'sqlglot.expressions.Trim'>, <class 'sqlglot.expressions.Substring'>, <class 'sqlglot.expressions.DateToDateStr'>}}"}, "sqlglot.optimizer.annotate_types.TypeAnnotator.ANNOTATORS": {"fullname": "sqlglot.optimizer.annotate_types.TypeAnnotator.ANNOTATORS", "modulename": "sqlglot.optimizer.annotate_types", "qualname": "TypeAnnotator.ANNOTATORS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{<class 'sqlglot.expressions.Alias'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.BitwiseNot'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.Neg'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.Not'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.Paren'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.PivotAlias'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.Unary'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.Add'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.And'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.ArrayContained'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.ArrayContains'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.ArrayOverlaps'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.Binary'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.BitwiseAnd'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.BitwiseLeftShift'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.BitwiseOr'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.BitwiseRightShift'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.BitwiseXor'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.Collate'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.Connector'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.Corr'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.CovarPop'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.CovarSamp'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.DPipe'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.Distance'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.Div'>: <function TypeAnnotator.<lambda>>, <class 'sqlglot.expressions.Dot'>: <function TypeAnnotator.<lambda>>, <class 'sqlglot.expressions.EQ'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.Escape'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.GT'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.GTE'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.Glob'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.ILike'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.ILikeAny'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.IntDiv'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.Is'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.JSONArrayContains'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.JSONBContains'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.JSONBExtract'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.JSONBExtractScalar'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.JSONExtract'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.JSONExtractScalar'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.Kwarg'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.LT'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.LTE'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.Like'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.LikeAny'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.Mod'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.Mul'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.NEQ'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.NullSafeEQ'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.NullSafeNEQ'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.Operator'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.Or'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.Overlaps'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.Pow'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.PropertyEQ'>: <function TypeAnnotator.<lambda>>, <class 'sqlglot.expressions.RegexpILike'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.RegexpLike'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.SimilarTo'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.Slice'>: <function TypeAnnotator.<lambda>>, <class 'sqlglot.expressions.Sub'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.Xor'>: <function TypeAnnotator.<dictcomp>.<lambda>>, <class 'sqlglot.expressions.Count'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.ArraySize'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Length'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.ApproxDistinct'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Between'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.In'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Boolean'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.DateStrToDate'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.TimeStrToDate'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.DateFromParts'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.DiToDate'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.StrToDate'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.TsOrDsToDate'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.CurrentDate'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Date'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.CurrentDatetime'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.DatetimeSub'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.DatetimeAdd'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Sqrt'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.VariancePop'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.StddevPop'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Avg'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.ApproxQuantile'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Log'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Exp'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Variance'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Quantile'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Ln'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.SafeDivide'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.StddevSamp'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Round'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Stddev'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Sign'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Extract'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Floor'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.StrPosition'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.DatetimeDiff'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Ceil'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.DateDiff'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.TimeDiff'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Levenshtein'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.DateToDi'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.TimestampDiff'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.TsOrDiToDi'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.ParseJSON'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.CurrentTimestamp'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.TimeStrToTime'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.TimestampAdd'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.CurrentTime'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.StrToTime'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.UnixToTime'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.TimeAdd'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.TimeSub'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.TimestampSub'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Quarter'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Day'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Year'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Month'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Week'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.ConcatWs'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Lower'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Concat'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Upper'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.GroupConcat'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.ArrayConcat'>: <function TypeAnnotator.<lambda>>, <class 'sqlglot.expressions.TimeToTimeStr'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.TsOrDsToDateStr'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.UnixToTimeStr'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.TimeToStr'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.UnixToStr'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Initcap'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Trim'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Substring'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.DateToDateStr'>: <function _annotate_with_type_lambda.<locals>.<lambda>>, <class 'sqlglot.expressions.Abs'>: <function TypeAnnotator.<lambda>>, <class 'sqlglot.expressions.Anonymous'>: <function TypeAnnotator.<lambda>>, <class 'sqlglot.expressions.Array'>: <function TypeAnnotator.<lambda>>, <class 'sqlglot.expressions.ArrayAgg'>: <function TypeAnnotator.<lambda>>, <class 'sqlglot.expressions.Bracket'>: <function TypeAnnotator.<lambda>>, <class 'sqlglot.expressions.Cast'>: <function TypeAnnotator.<lambda>>, <class 'sqlglot.expressions.Case'>: <function TypeAnnotator.<lambda>>, <class 'sqlglot.expressions.Coalesce'>: <function 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<function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UMEDIUMINT: 'UMEDIUMINT'>, <Type.CHAR: 'CHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UTINYINT: 'UTINYINT'>, <Type.CHAR: 'CHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UINT128: 'UINT128'>, <Type.CHAR: 'CHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UDECIMAL: 'UDECIMAL'>, <Type.CHAR: 'CHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.DOUBLE: 'DOUBLE'>, <Type.CHAR: 'CHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.DECIMAL: 'DECIMAL'>, <Type.CHAR: 'CHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.BIGDECIMAL: 'BIGDECIMAL'>, <Type.CHAR: 'CHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.BIT: 'BIT'>, <Type.CHAR: 'CHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UINT: 'UINT'>, <Type.CHAR: 'CHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.INT: 'INT'>, <Type.CHAR: 'CHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.TINYINT: 'TINYINT'>, <Type.CHAR: 'CHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UINT256: 'UINT256'>, <Type.NCHAR: 'NCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.BIGINT: 'BIGINT'>, <Type.NCHAR: 'NCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.INT128: 'INT128'>, <Type.NCHAR: 'NCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.MONEY: 'MONEY'>, <Type.NCHAR: 'NCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.USMALLINT: 'USMALLINT'>, <Type.NCHAR: 'NCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.SMALLMONEY: 'SMALLMONEY'>, <Type.NCHAR: 'NCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UBIGINT: 'UBIGINT'>, <Type.NCHAR: 'NCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.SMALLINT: 'SMALLINT'>, <Type.NCHAR: 'NCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.INT256: 'INT256'>, <Type.NCHAR: 'NCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.FLOAT: 'FLOAT'>, <Type.NCHAR: 'NCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.MEDIUMINT: 'MEDIUMINT'>, <Type.NCHAR: 'NCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UMEDIUMINT: 'UMEDIUMINT'>, <Type.NCHAR: 'NCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UTINYINT: 'UTINYINT'>, <Type.NCHAR: 'NCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UINT128: 'UINT128'>, <Type.NCHAR: 'NCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UDECIMAL: 'UDECIMAL'>, <Type.NCHAR: 'NCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.DOUBLE: 'DOUBLE'>, <Type.NCHAR: 'NCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.DECIMAL: 'DECIMAL'>, <Type.NCHAR: 'NCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.BIGDECIMAL: 'BIGDECIMAL'>, <Type.NCHAR: 'NCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.BIT: 'BIT'>, <Type.NCHAR: 'NCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UINT: 'UINT'>, <Type.NCHAR: 'NCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.INT: 'INT'>, <Type.NCHAR: 'NCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.TINYINT: 'TINYINT'>, <Type.NCHAR: 'NCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UINT256: 'UINT256'>, <Type.NAME: 'NAME'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.BIGINT: 'BIGINT'>, <Type.NAME: 'NAME'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.INT128: 'INT128'>, <Type.NAME: 'NAME'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.MONEY: 'MONEY'>, <Type.NAME: 'NAME'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.USMALLINT: 'USMALLINT'>, <Type.NAME: 'NAME'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.SMALLMONEY: 'SMALLMONEY'>, <Type.NAME: 'NAME'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UBIGINT: 'UBIGINT'>, <Type.NAME: 'NAME'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.SMALLINT: 'SMALLINT'>, <Type.NAME: 'NAME'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.INT256: 'INT256'>, <Type.NAME: 'NAME'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.FLOAT: 'FLOAT'>, <Type.NAME: 'NAME'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.MEDIUMINT: 'MEDIUMINT'>, <Type.NAME: 'NAME'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UMEDIUMINT: 'UMEDIUMINT'>, <Type.NAME: 'NAME'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UTINYINT: 'UTINYINT'>, <Type.NAME: 'NAME'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UINT128: 'UINT128'>, <Type.NAME: 'NAME'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UDECIMAL: 'UDECIMAL'>, <Type.NAME: 'NAME'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.DOUBLE: 'DOUBLE'>, <Type.NAME: 'NAME'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.DECIMAL: 'DECIMAL'>, <Type.NAME: 'NAME'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.BIGDECIMAL: 'BIGDECIMAL'>, <Type.NAME: 'NAME'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.BIT: 'BIT'>, <Type.NAME: 'NAME'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UINT: 'UINT'>, <Type.NAME: 'NAME'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.INT: 'INT'>, <Type.NAME: 'NAME'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.TINYINT: 'TINYINT'>, <Type.NAME: 'NAME'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UINT256: 'UINT256'>, <Type.VARCHAR: 'VARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.BIGINT: 'BIGINT'>, <Type.VARCHAR: 'VARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.INT128: 'INT128'>, <Type.VARCHAR: 'VARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.MONEY: 'MONEY'>, <Type.VARCHAR: 'VARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.USMALLINT: 'USMALLINT'>, <Type.VARCHAR: 'VARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.SMALLMONEY: 'SMALLMONEY'>, <Type.VARCHAR: 'VARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UBIGINT: 'UBIGINT'>, <Type.VARCHAR: 'VARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.SMALLINT: 'SMALLINT'>, <Type.VARCHAR: 'VARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.INT256: 'INT256'>, <Type.VARCHAR: 'VARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.FLOAT: 'FLOAT'>, <Type.VARCHAR: 'VARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.MEDIUMINT: 'MEDIUMINT'>, <Type.VARCHAR: 'VARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UMEDIUMINT: 'UMEDIUMINT'>, <Type.VARCHAR: 'VARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UTINYINT: 'UTINYINT'>, <Type.VARCHAR: 'VARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UINT128: 'UINT128'>, <Type.VARCHAR: 'VARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UDECIMAL: 'UDECIMAL'>, <Type.VARCHAR: 'VARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.DOUBLE: 'DOUBLE'>, <Type.VARCHAR: 'VARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.DECIMAL: 'DECIMAL'>, <Type.VARCHAR: 'VARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.BIGDECIMAL: 'BIGDECIMAL'>, <Type.VARCHAR: 'VARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.BIT: 'BIT'>, <Type.VARCHAR: 'VARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UINT: 'UINT'>, <Type.VARCHAR: 'VARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.INT: 'INT'>, <Type.VARCHAR: 'VARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.TINYINT: 'TINYINT'>, <Type.VARCHAR: 'VARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UINT256: 'UINT256'>, <Type.NVARCHAR: 'NVARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.BIGINT: 'BIGINT'>, <Type.NVARCHAR: 'NVARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.INT128: 'INT128'>, <Type.NVARCHAR: 'NVARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.MONEY: 'MONEY'>, <Type.NVARCHAR: 'NVARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.USMALLINT: 'USMALLINT'>, <Type.NVARCHAR: 'NVARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.SMALLMONEY: 'SMALLMONEY'>, <Type.NVARCHAR: 'NVARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UBIGINT: 'UBIGINT'>, <Type.NVARCHAR: 'NVARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.SMALLINT: 'SMALLINT'>, <Type.NVARCHAR: 'NVARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.INT256: 'INT256'>, <Type.NVARCHAR: 'NVARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.FLOAT: 'FLOAT'>, <Type.NVARCHAR: 'NVARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.MEDIUMINT: 'MEDIUMINT'>, <Type.NVARCHAR: 'NVARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UMEDIUMINT: 'UMEDIUMINT'>, <Type.NVARCHAR: 'NVARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UTINYINT: 'UTINYINT'>, <Type.NVARCHAR: 'NVARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UINT128: 'UINT128'>, <Type.NVARCHAR: 'NVARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UDECIMAL: 'UDECIMAL'>, <Type.NVARCHAR: 'NVARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.DOUBLE: 'DOUBLE'>, <Type.NVARCHAR: 'NVARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.DECIMAL: 'DECIMAL'>, <Type.NVARCHAR: 'NVARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.BIGDECIMAL: 'BIGDECIMAL'>, <Type.NVARCHAR: 'NVARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.BIT: 'BIT'>, <Type.NVARCHAR: 'NVARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UINT: 'UINT'>, <Type.NVARCHAR: 'NVARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.INT: 'INT'>, <Type.NVARCHAR: 'NVARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.TINYINT: 'TINYINT'>, <Type.NVARCHAR: 'NVARCHAR'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UINT256: 'UINT256'>, <Type.TEXT: 'TEXT'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.BIGINT: 'BIGINT'>, <Type.TEXT: 'TEXT'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.INT128: 'INT128'>, <Type.TEXT: 'TEXT'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.MONEY: 'MONEY'>, <Type.TEXT: 'TEXT'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.USMALLINT: 'USMALLINT'>, <Type.TEXT: 'TEXT'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.SMALLMONEY: 'SMALLMONEY'>, <Type.TEXT: 'TEXT'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UBIGINT: 'UBIGINT'>, <Type.TEXT: 'TEXT'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.SMALLINT: 'SMALLINT'>, <Type.TEXT: 'TEXT'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.INT256: 'INT256'>, <Type.TEXT: 'TEXT'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.FLOAT: 'FLOAT'>, <Type.TEXT: 'TEXT'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.MEDIUMINT: 'MEDIUMINT'>, <Type.TEXT: 'TEXT'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UMEDIUMINT: 'UMEDIUMINT'>, <Type.TEXT: 'TEXT'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UTINYINT: 'UTINYINT'>, <Type.TEXT: 'TEXT'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UINT128: 'UINT128'>, <Type.TEXT: 'TEXT'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UDECIMAL: 'UDECIMAL'>, <Type.TEXT: 'TEXT'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.DOUBLE: 'DOUBLE'>, <Type.TEXT: 'TEXT'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.DECIMAL: 'DECIMAL'>, <Type.TEXT: 'TEXT'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.BIGDECIMAL: 'BIGDECIMAL'>, <Type.TEXT: 'TEXT'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.BIT: 'BIT'>, <Type.TEXT: 'TEXT'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.UINT: 'UINT'>, <Type.TEXT: 'TEXT'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.INT: 'INT'>, <Type.TEXT: 'TEXT'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.TINYINT: 'TINYINT'>, <Type.TEXT: 'TEXT'>): <function TypeAnnotator.<dictcomp>.<lambda>>, (<Type.DATE: 'DATE'>, <Type.INTERVAL: 'INTERVAL'>): <function TypeAnnotator.<lambda>>, (<Type.INTERVAL: 'INTERVAL'>, <Type.DATE: 'DATE'>): <function TypeAnnotator.<lambda>>}"}, "sqlglot.optimizer.annotate_types.TypeAnnotator.schema": {"fullname": "sqlglot.optimizer.annotate_types.TypeAnnotator.schema", "modulename": "sqlglot.optimizer.annotate_types", "qualname": "TypeAnnotator.schema", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.optimizer.annotate_types.TypeAnnotator.annotators": {"fullname": "sqlglot.optimizer.annotate_types.TypeAnnotator.annotators", "modulename": "sqlglot.optimizer.annotate_types", "qualname": "TypeAnnotator.annotators", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.optimizer.annotate_types.TypeAnnotator.coerces_to": {"fullname": "sqlglot.optimizer.annotate_types.TypeAnnotator.coerces_to", "modulename": "sqlglot.optimizer.annotate_types", "qualname": "TypeAnnotator.coerces_to", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.optimizer.annotate_types.TypeAnnotator.binary_coercions": {"fullname": "sqlglot.optimizer.annotate_types.TypeAnnotator.binary_coercions", "modulename": "sqlglot.optimizer.annotate_types", "qualname": "TypeAnnotator.binary_coercions", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.optimizer.annotate_types.TypeAnnotator.annotate": {"fullname": "sqlglot.optimizer.annotate_types.TypeAnnotator.annotate", "modulename": "sqlglot.optimizer.annotate_types", "qualname": "TypeAnnotator.annotate", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"o\">~</span><span class=\"n\">E</span></span><span class=\"return-annotation\">) -> <span class=\"o\">~</span><span class=\"n\">E</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.annotate_types.TypeAnnotator.annotate_scope": {"fullname": "sqlglot.optimizer.annotate_types.TypeAnnotator.annotate_scope", "modulename": "sqlglot.optimizer.annotate_types", "qualname": "TypeAnnotator.annotate_scope", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">scope</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">optimizer</span><span class=\"o\">.</span><span class=\"n\">scope</span><span class=\"o\">.</span><span class=\"n\">Scope</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.canonicalize": {"fullname": "sqlglot.optimizer.canonicalize", "modulename": "sqlglot.optimizer.canonicalize", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.optimizer.canonicalize.canonicalize": {"fullname": "sqlglot.optimizer.canonicalize.canonicalize", "modulename": "sqlglot.optimizer.canonicalize", "qualname": "canonicalize", "kind": "function", "doc": "<p>Converts a sql expression into a standard form.</p>\n\n<p>This method relies on annotate_types because many of the\nconversions rely on type inference.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> The expression to canonicalize.</li>\n</ul>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.canonicalize.add_text_to_concat": {"fullname": "sqlglot.optimizer.canonicalize.add_text_to_concat", "modulename": "sqlglot.optimizer.canonicalize", "qualname": "add_text_to_concat", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">node</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.canonicalize.replace_date_funcs": {"fullname": "sqlglot.optimizer.canonicalize.replace_date_funcs", "modulename": "sqlglot.optimizer.canonicalize", "qualname": "replace_date_funcs", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">node</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.canonicalize.COERCIBLE_DATE_OPS": {"fullname": "sqlglot.optimizer.canonicalize.COERCIBLE_DATE_OPS", "modulename": "sqlglot.optimizer.canonicalize", "qualname": "COERCIBLE_DATE_OPS", "kind": "variable", "doc": "<p></p>\n", "default_value": "(<class 'sqlglot.expressions.Add'>, <class 'sqlglot.expressions.Sub'>, <class 'sqlglot.expressions.EQ'>, <class 'sqlglot.expressions.NEQ'>, <class 'sqlglot.expressions.GT'>, <class 'sqlglot.expressions.GTE'>, <class 'sqlglot.expressions.LT'>, <class 'sqlglot.expressions.LTE'>, <class 'sqlglot.expressions.NullSafeEQ'>, <class 'sqlglot.expressions.NullSafeNEQ'>)"}, "sqlglot.optimizer.canonicalize.coerce_type": {"fullname": "sqlglot.optimizer.canonicalize.coerce_type", "modulename": "sqlglot.optimizer.canonicalize", "qualname": "coerce_type", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">node</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.canonicalize.remove_redundant_casts": {"fullname": "sqlglot.optimizer.canonicalize.remove_redundant_casts", "modulename": "sqlglot.optimizer.canonicalize", "qualname": "remove_redundant_casts", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.canonicalize.ensure_bools": {"fullname": "sqlglot.optimizer.canonicalize.ensure_bools", "modulename": "sqlglot.optimizer.canonicalize", "qualname": "ensure_bools", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">replace_func</span><span class=\"p\">:</span> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.canonicalize.remove_ascending_order": {"fullname": "sqlglot.optimizer.canonicalize.remove_ascending_order", "modulename": "sqlglot.optimizer.canonicalize", "qualname": "remove_ascending_order", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.eliminate_ctes": {"fullname": "sqlglot.optimizer.eliminate_ctes", "modulename": "sqlglot.optimizer.eliminate_ctes", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.optimizer.eliminate_ctes.eliminate_ctes": {"fullname": "sqlglot.optimizer.eliminate_ctes.eliminate_ctes", "modulename": "sqlglot.optimizer.eliminate_ctes", "qualname": "eliminate_ctes", "kind": "function", "doc": "<p>Remove unused CTEs from an expression.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"gp\">>>> </span><span class=\"n\">sql</span> <span class=\"o\">=</span> <span class=\"s2\">"WITH y AS (SELECT a FROM x) SELECT a FROM z"</span>\n<span class=\"gp\">>>> </span><span class=\"n\">expression</span> <span class=\"o\">=</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"n\">sql</span><span class=\"p\">)</span>\n<span class=\"gp\">>>> </span><span class=\"n\">eliminate_ctes</span><span class=\"p\">(</span><span class=\"n\">expression</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT a FROM z'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression (sqlglot.Expression):</strong> expression to optimize</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>sqlglot.Expression: optimized expression</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.eliminate_joins": {"fullname": "sqlglot.optimizer.eliminate_joins", "modulename": "sqlglot.optimizer.eliminate_joins", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.optimizer.eliminate_joins.eliminate_joins": {"fullname": "sqlglot.optimizer.eliminate_joins.eliminate_joins", "modulename": "sqlglot.optimizer.eliminate_joins", "qualname": "eliminate_joins", "kind": "function", "doc": "<p>Remove unused joins from an expression.</p>\n\n<p>This only removes joins when we know that the join condition doesn't produce duplicate rows.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"gp\">>>> </span><span class=\"n\">sql</span> <span class=\"o\">=</span> <span class=\"s2\">"SELECT x.a FROM x LEFT JOIN (SELECT DISTINCT y.b FROM y) AS y ON x.b = y.b"</span>\n<span class=\"gp\">>>> </span><span class=\"n\">expression</span> <span class=\"o\">=</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"n\">sql</span><span class=\"p\">)</span>\n<span class=\"gp\">>>> </span><span class=\"n\">eliminate_joins</span><span class=\"p\">(</span><span class=\"n\">expression</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT x.a FROM x'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression (sqlglot.Expression):</strong> expression to optimize</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>sqlglot.Expression: optimized expression</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.eliminate_joins.join_condition": {"fullname": "sqlglot.optimizer.eliminate_joins.join_condition", "modulename": "sqlglot.optimizer.eliminate_joins", "qualname": "join_condition", "kind": "function", "doc": "<p>Extract the join condition from a join expression.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li>join (exp.Join)</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>tuple[list[str], list[str], exp.Expression]:\n Tuple of (source key, join key, remaining predicate)</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">join</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.eliminate_subqueries": {"fullname": "sqlglot.optimizer.eliminate_subqueries", "modulename": "sqlglot.optimizer.eliminate_subqueries", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.optimizer.eliminate_subqueries.eliminate_subqueries": {"fullname": "sqlglot.optimizer.eliminate_subqueries.eliminate_subqueries", "modulename": "sqlglot.optimizer.eliminate_subqueries", "qualname": "eliminate_subqueries", "kind": "function", "doc": "<p>Rewrite derived tables as CTES, deduplicating if possible.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"gp\">>>> </span><span class=\"n\">expression</span> <span class=\"o\">=</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT a FROM (SELECT * FROM x) AS y"</span><span class=\"p\">)</span>\n<span class=\"gp\">>>> </span><span class=\"n\">eliminate_subqueries</span><span class=\"p\">(</span><span class=\"n\">expression</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'WITH y AS (SELECT * FROM x) SELECT a FROM y AS y'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"this-also-deduplicates-common-subqueries\">This also deduplicates common subqueries:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">expression</span> <span class=\"o\">=</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT a FROM (SELECT * FROM x) AS y CROSS JOIN (SELECT * FROM x) AS z"</span><span class=\"p\">)</span>\n<span class=\"gp\">>>> </span><span class=\"n\">eliminate_subqueries</span><span class=\"p\">(</span><span class=\"n\">expression</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'WITH y AS (SELECT * FROM x) SELECT a FROM y AS y CROSS JOIN y AS z'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression (sqlglot.Expression):</strong> expression</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>sqlglot.Expression: expression</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.isolate_table_selects": {"fullname": "sqlglot.optimizer.isolate_table_selects", "modulename": "sqlglot.optimizer.isolate_table_selects", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.optimizer.isolate_table_selects.isolate_table_selects": {"fullname": "sqlglot.optimizer.isolate_table_selects.isolate_table_selects", "modulename": "sqlglot.optimizer.isolate_table_selects", "qualname": "isolate_table_selects", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span>, </span><span class=\"param\"><span class=\"n\">schema</span><span class=\"o\">=</span><span class=\"kc\">None</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.merge_subqueries": {"fullname": "sqlglot.optimizer.merge_subqueries", "modulename": "sqlglot.optimizer.merge_subqueries", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.optimizer.merge_subqueries.merge_subqueries": {"fullname": "sqlglot.optimizer.merge_subqueries.merge_subqueries", "modulename": "sqlglot.optimizer.merge_subqueries", "qualname": "merge_subqueries", "kind": "function", "doc": "<p>Rewrite sqlglot AST to merge derived tables into the outer query.</p>\n\n<p>This also merges CTEs if they are selected from only once.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"gp\">>>> </span><span class=\"n\">expression</span> <span class=\"o\">=</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT a FROM (SELECT x.a FROM x) CROSS JOIN y"</span><span class=\"p\">)</span>\n<span class=\"gp\">>>> </span><span class=\"n\">merge_subqueries</span><span class=\"p\">(</span><span class=\"n\">expression</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT x.a FROM x CROSS JOIN y'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<p>If <code>leave_tables_isolated</code> is True, this will not merge inner queries into outer\nqueries if it would result in multiple table selects in a single query:</p>\n\n<blockquote>\n <blockquote>\n <blockquote>\n <p>expression = sqlglot.parse_one(\"SELECT a FROM (SELECT x.a FROM x) CROSS JOIN y\")\n merge_subqueries(expression, leave_tables_isolated=True).sql()\n 'SELECT a FROM (SELECT x.a FROM x) CROSS JOIN y'</p>\n </blockquote>\n </blockquote>\n</blockquote>\n\n<p>Inspired by <a href=\"https://dev.mysql.com/doc/refman/8.0/en/derived-table-optimization.html\">https://dev.mysql.com/doc/refman/8.0/en/derived-table-optimization.html</a></p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression (sqlglot.Expression):</strong> expression to optimize</li>\n<li><strong>leave_tables_isolated (bool):</strong> </li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>sqlglot.Expression: optimized expression</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span>, </span><span class=\"param\"><span class=\"n\">leave_tables_isolated</span><span class=\"o\">=</span><span class=\"kc\">False</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.merge_subqueries.UNMERGABLE_ARGS": {"fullname": "sqlglot.optimizer.merge_subqueries.UNMERGABLE_ARGS", "modulename": "sqlglot.optimizer.merge_subqueries", "qualname": "UNMERGABLE_ARGS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'locks', 'with', 'cluster', 'distinct', 'pivots', 'prewhere', 'windows', 'options', 'offset', 'sort', 'settings', 'match', 'connect', 'sample', 'laterals', 'format', 'having', 'group', 'limit', 'qualify', 'kind', 'into', 'distribute'}"}, "sqlglot.optimizer.merge_subqueries.SAFE_TO_REPLACE_UNWRAPPED": {"fullname": "sqlglot.optimizer.merge_subqueries.SAFE_TO_REPLACE_UNWRAPPED", "modulename": "sqlglot.optimizer.merge_subqueries", "qualname": "SAFE_TO_REPLACE_UNWRAPPED", "kind": "variable", "doc": "<p></p>\n", "default_value": "(<class 'sqlglot.expressions.Column'>, <class 'sqlglot.expressions.EQ'>, <class 'sqlglot.expressions.Func'>, <class 'sqlglot.expressions.NEQ'>, <class 'sqlglot.expressions.Paren'>)"}, "sqlglot.optimizer.merge_subqueries.merge_ctes": {"fullname": "sqlglot.optimizer.merge_subqueries.merge_ctes", "modulename": "sqlglot.optimizer.merge_subqueries", "qualname": "merge_ctes", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span>, </span><span class=\"param\"><span class=\"n\">leave_tables_isolated</span><span class=\"o\">=</span><span class=\"kc\">False</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.merge_subqueries.merge_derived_tables": {"fullname": "sqlglot.optimizer.merge_subqueries.merge_derived_tables", "modulename": "sqlglot.optimizer.merge_subqueries", "qualname": "merge_derived_tables", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span>, </span><span class=\"param\"><span class=\"n\">leave_tables_isolated</span><span class=\"o\">=</span><span class=\"kc\">False</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.normalize": {"fullname": "sqlglot.optimizer.normalize", "modulename": "sqlglot.optimizer.normalize", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.optimizer.normalize.logger": {"fullname": "sqlglot.optimizer.normalize.logger", "modulename": "sqlglot.optimizer.normalize", "qualname": "logger", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Logger sqlglot (WARNING)>"}, "sqlglot.optimizer.normalize.normalize": {"fullname": "sqlglot.optimizer.normalize.normalize", "modulename": "sqlglot.optimizer.normalize", "qualname": "normalize", "kind": "function", "doc": "<p>Rewrite sqlglot AST into conjunctive normal form or disjunctive normal form.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"gp\">>>> </span><span class=\"n\">expression</span> <span class=\"o\">=</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"(x AND y) OR z"</span><span class=\"p\">)</span>\n<span class=\"gp\">>>> </span><span class=\"n\">normalize</span><span class=\"p\">(</span><span class=\"n\">expression</span><span class=\"p\">,</span> <span class=\"n\">dnf</span><span class=\"o\">=</span><span class=\"kc\">False</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'(x OR z) AND (y OR z)'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> expression to normalize</li>\n<li><strong>dnf:</strong> rewrite in disjunctive normal form instead.</li>\n<li><strong>max_distance (int):</strong> the maximal estimated distance from cnf/dnf to attempt conversion</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>sqlglot.Expression: normalized expression</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">dnf</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span>,</span><span class=\"param\">\t<span class=\"n\">max_distance</span><span class=\"p\">:</span> <span class=\"nb\">int</span> <span class=\"o\">=</span> <span class=\"mi\">128</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.normalize.normalized": {"fullname": "sqlglot.optimizer.normalize.normalized", "modulename": "sqlglot.optimizer.normalize", "qualname": "normalized", "kind": "function", "doc": "<p>Checks whether a given expression is in a normal form of interest.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">parse_one</span>\n<span class=\"gp\">>>> </span><span class=\"n\">normalized</span><span class=\"p\">(</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"(a AND b) OR c OR (d AND e)"</span><span class=\"p\">),</span> <span class=\"n\">dnf</span><span class=\"o\">=</span><span class=\"kc\">True</span><span class=\"p\">)</span>\n<span class=\"go\">True</span>\n<span class=\"gp\">>>> </span><span class=\"n\">normalized</span><span class=\"p\">(</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"(a OR b) AND c"</span><span class=\"p\">))</span> <span class=\"c1\"># Checks CNF by default</span>\n<span class=\"go\">True</span>\n<span class=\"gp\">>>> </span><span class=\"n\">normalized</span><span class=\"p\">(</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"a AND (b OR c)"</span><span class=\"p\">),</span> <span class=\"n\">dnf</span><span class=\"o\">=</span><span class=\"kc\">True</span><span class=\"p\">)</span>\n<span class=\"go\">False</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> The expression to check if it's normalized.</li>\n<li><strong>dnf:</strong> Whether to check if the expression is in Disjunctive Normal Form (DNF).\nDefault: False, i.e. we check if it's in Conjunctive Normal Form (CNF).</li>\n</ul>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>, </span><span class=\"param\"><span class=\"n\">dnf</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">bool</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.normalize.normalization_distance": {"fullname": "sqlglot.optimizer.normalize.normalization_distance", "modulename": "sqlglot.optimizer.normalize", "qualname": "normalization_distance", "kind": "function", "doc": "<p>The difference in the number of predicates between a given expression and its normalized form.</p>\n\n<p>This is used as an estimate of the cost of the conversion which is exponential in complexity.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"gp\">>>> </span><span class=\"n\">expression</span> <span class=\"o\">=</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"(a AND b) OR (c AND d)"</span><span class=\"p\">)</span>\n<span class=\"gp\">>>> </span><span class=\"n\">normalization_distance</span><span class=\"p\">(</span><span class=\"n\">expression</span><span class=\"p\">)</span>\n<span class=\"go\">4</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> The expression to compute the normalization distance for.</li>\n<li><strong>dnf:</strong> Whether to check if the expression is in Disjunctive Normal Form (DNF).\nDefault: False, i.e. we check if it's in Conjunctive Normal Form (CNF).</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The normalization distance.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>, </span><span class=\"param\"><span class=\"n\">dnf</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">int</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.normalize.distributive_law": {"fullname": "sqlglot.optimizer.normalize.distributive_law", "modulename": "sqlglot.optimizer.normalize", "qualname": "distributive_law", "kind": "function", "doc": "<p>x OR (y AND z) -> (x OR y) AND (x OR z)\n(x AND y) OR (y AND z) -> (x OR y) AND (x OR z) AND (y OR y) AND (y OR z)</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span>, </span><span class=\"param\"><span class=\"n\">dnf</span>, </span><span class=\"param\"><span class=\"n\">max_distance</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.normalize_identifiers": {"fullname": "sqlglot.optimizer.normalize_identifiers", "modulename": "sqlglot.optimizer.normalize_identifiers", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.optimizer.normalize_identifiers.normalize_identifiers": {"fullname": "sqlglot.optimizer.normalize_identifiers.normalize_identifiers", "modulename": "sqlglot.optimizer.normalize_identifiers", "qualname": "normalize_identifiers", "kind": "function", "doc": "<p>Normalize all unquoted identifiers to either lower or upper case, depending\non the dialect. This essentially makes those identifiers case-insensitive.</p>\n\n<p>It's possible to make this a no-op by adding a special comment next to the\nidentifier of interest:</p>\n\n<pre><code>SELECT a /* sqlglot.meta case_sensitive */ FROM table\n</code></pre>\n\n<p>In this example, the identifier <code>a</code> will not be normalized.</p>\n\n<h6 id=\"note\">Note:</h6>\n\n<blockquote>\n <p>Some dialects (e.g. BigQuery) treat identifiers as case-insensitive even\n when they're quoted, so in these cases all identifiers are normalized.</p>\n</blockquote>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"gp\">>>> </span><span class=\"n\">expression</span> <span class=\"o\">=</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s1\">'SELECT Bar.A AS A FROM "Foo".Bar'</span><span class=\"p\">)</span>\n<span class=\"gp\">>>> </span><span class=\"n\">normalize_identifiers</span><span class=\"p\">(</span><span class=\"n\">expression</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT bar.a AS a FROM "Foo".bar'</span>\n<span class=\"gp\">>>> </span><span class=\"n\">normalize_identifiers</span><span class=\"p\">(</span><span class=\"s2\">"foo"</span><span class=\"p\">,</span> <span class=\"n\">dialect</span><span class=\"o\">=</span><span class=\"s2\">"snowflake"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">(</span><span class=\"n\">dialect</span><span class=\"o\">=</span><span class=\"s2\">"snowflake"</span><span class=\"p\">)</span>\n<span class=\"go\">'FOO'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> The expression to transform.</li>\n<li><strong>dialect:</strong> The dialect to use in order to decide how to normalize identifiers.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The transformed expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span>, </span><span class=\"param\"><span class=\"n\">dialect</span><span class=\"o\">=</span><span class=\"kc\">None</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.optimize_joins": {"fullname": "sqlglot.optimizer.optimize_joins", "modulename": "sqlglot.optimizer.optimize_joins", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.optimizer.optimize_joins.JOIN_ATTRS": {"fullname": "sqlglot.optimizer.optimize_joins.JOIN_ATTRS", "modulename": "sqlglot.optimizer.optimize_joins", "qualname": "JOIN_ATTRS", "kind": "variable", "doc": "<p></p>\n", "default_value": "('on', 'side', 'kind', 'using', 'method')"}, "sqlglot.optimizer.optimize_joins.optimize_joins": {"fullname": "sqlglot.optimizer.optimize_joins.optimize_joins", "modulename": "sqlglot.optimizer.optimize_joins", "qualname": "optimize_joins", "kind": "function", "doc": "<p>Removes cross joins if possible and reorder joins based on predicate dependencies.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">parse_one</span>\n<span class=\"gp\">>>> </span><span class=\"n\">optimize_joins</span><span class=\"p\">(</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT * FROM x CROSS JOIN y JOIN z ON x.a = z.a AND y.a = z.a"</span><span class=\"p\">))</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT * FROM x JOIN z ON x.a = z.a AND TRUE JOIN y ON y.a = z.a'</span>\n</code></pre>\n </div>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.optimize_joins.reorder_joins": {"fullname": "sqlglot.optimizer.optimize_joins.reorder_joins", "modulename": "sqlglot.optimizer.optimize_joins", "qualname": "reorder_joins", "kind": "function", "doc": "<p>Reorder joins by topological sort order based on predicate references.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.optimize_joins.normalize": {"fullname": "sqlglot.optimizer.optimize_joins.normalize", "modulename": "sqlglot.optimizer.optimize_joins", "qualname": "normalize", "kind": "function", "doc": "<p>Remove INNER and OUTER from joins as they are optional.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.optimize_joins.other_table_names": {"fullname": "sqlglot.optimizer.optimize_joins.other_table_names", "modulename": "sqlglot.optimizer.optimize_joins", "qualname": "other_table_names", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">join</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Join</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Set</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.optimizer": {"fullname": "sqlglot.optimizer.optimizer", "modulename": "sqlglot.optimizer.optimizer", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.optimizer.optimizer.RULES": {"fullname": "sqlglot.optimizer.optimizer.RULES", "modulename": "sqlglot.optimizer.optimizer", "qualname": "RULES", "kind": "variable", "doc": "<p></p>\n", "default_value": "(<function qualify>, <function pushdown_projections>, <function normalize>, <function unnest_subqueries>, <function pushdown_predicates>, <function optimize_joins>, <function eliminate_subqueries>, <function merge_subqueries>, <function eliminate_joins>, <function eliminate_ctes>, <function quote_identifiers>, <function annotate_types>, <function canonicalize>, <function simplify>)"}, "sqlglot.optimizer.optimizer.optimize": {"fullname": "sqlglot.optimizer.optimizer.optimize", "modulename": "sqlglot.optimizer.optimizer", "qualname": "optimize", "kind": "function", "doc": "<p>Rewrite a sqlglot AST into an optimized form.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> expression to optimize</li>\n<li><strong>schema:</strong> database schema.\nThis can either be an instance of <code>sqlglot.optimizer.Schema</code> or a mapping in one of\nthe following forms:\n 1. {table: {col: type}}\n 2. {db: {table: {col: type}}}\n 3. {catalog: {db: {table: {col: type}}}}\nIf no schema is provided then the default schema defined at <code>sqlgot.schema</code> will be used</li>\n<li><strong>db:</strong> specify the default database, as might be set by a <code>USE DATABASE db</code> statement</li>\n<li><strong>catalog:</strong> specify the default catalog, as might be set by a <code>USE CATALOG c</code> statement</li>\n<li><strong>dialect:</strong> The dialect to parse the sql string.</li>\n<li><strong>rules:</strong> sequence of optimizer rules to use.\nMany of the rules require tables and columns to be qualified.\nDo not remove <code>qualify</code> from the sequence of rules unless you know what you're doing!</li>\n<li><strong><em>*kwargs:</strong> If a rule has a keyword argument with a same name in *</em>kwargs, it will be passed in.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The optimized expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">schema</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">dict</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">schema</span><span class=\"o\">.</span><span class=\"n\">Schema</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">db</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Identifier</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">catalog</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Identifier</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">rules</span><span class=\"p\">:</span> <span class=\"n\">Sequence</span><span class=\"p\">[</span><span class=\"n\">Callable</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"p\">(</span><span class=\"o\"><</span><span class=\"n\">function</span> <span class=\"n\">qualify</span><span class=\"o\">></span><span class=\"p\">,</span> <span class=\"o\"><</span><span class=\"n\">function</span> <span class=\"n\">pushdown_projections</span><span class=\"o\">></span><span class=\"p\">,</span> <span class=\"o\"><</span><span class=\"n\">function</span> <span class=\"n\">normalize</span><span class=\"o\">></span><span class=\"p\">,</span> <span class=\"o\"><</span><span class=\"n\">function</span> <span class=\"n\">unnest_subqueries</span><span class=\"o\">></span><span class=\"p\">,</span> <span class=\"o\"><</span><span class=\"n\">function</span> <span class=\"n\">pushdown_predicates</span><span class=\"o\">></span><span class=\"p\">,</span> <span class=\"o\"><</span><span class=\"n\">function</span> <span class=\"n\">optimize_joins</span><span class=\"o\">></span><span class=\"p\">,</span> <span class=\"o\"><</span><span class=\"n\">function</span> <span class=\"n\">eliminate_subqueries</span><span class=\"o\">></span><span class=\"p\">,</span> <span class=\"o\"><</span><span class=\"n\">function</span> <span class=\"n\">merge_subqueries</span><span class=\"o\">></span><span class=\"p\">,</span> <span class=\"o\"><</span><span class=\"n\">function</span> <span class=\"n\">eliminate_joins</span><span class=\"o\">></span><span class=\"p\">,</span> <span class=\"o\"><</span><span class=\"n\">function</span> <span class=\"n\">eliminate_ctes</span><span class=\"o\">></span><span class=\"p\">,</span> <span class=\"o\"><</span><span class=\"n\">function</span> <span class=\"n\">quote_identifiers</span><span class=\"o\">></span><span class=\"p\">,</span> <span class=\"o\"><</span><span class=\"n\">function</span> <span class=\"n\">annotate_types</span><span class=\"o\">></span><span class=\"p\">,</span> <span class=\"o\"><</span><span class=\"n\">function</span> <span class=\"n\">canonicalize</span><span class=\"o\">></span><span class=\"p\">,</span> <span class=\"o\"><</span><span class=\"n\">function</span> <span class=\"n\">simplify</span><span class=\"o\">></span><span class=\"p\">)</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.pushdown_predicates": {"fullname": "sqlglot.optimizer.pushdown_predicates", "modulename": "sqlglot.optimizer.pushdown_predicates", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.optimizer.pushdown_predicates.pushdown_predicates": {"fullname": "sqlglot.optimizer.pushdown_predicates.pushdown_predicates", "modulename": "sqlglot.optimizer.pushdown_predicates", "qualname": "pushdown_predicates", "kind": "function", "doc": "<p>Rewrite sqlglot AST to pushdown predicates in FROMS and JOINS</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"gp\">>>> </span><span class=\"n\">sql</span> <span class=\"o\">=</span> <span class=\"s2\">"SELECT y.a AS a FROM (SELECT x.a AS a FROM x AS x) AS y WHERE y.a = 1"</span>\n<span class=\"gp\">>>> </span><span class=\"n\">expression</span> <span class=\"o\">=</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"n\">sql</span><span class=\"p\">)</span>\n<span class=\"gp\">>>> </span><span class=\"n\">pushdown_predicates</span><span class=\"p\">(</span><span class=\"n\">expression</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT y.a AS a FROM (SELECT x.a AS a FROM x AS x WHERE x.a = 1) AS y WHERE TRUE'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression (sqlglot.Expression):</strong> expression to optimize</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>sqlglot.Expression: optimized expression</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span>, </span><span class=\"param\"><span class=\"n\">dialect</span><span class=\"o\">=</span><span class=\"kc\">None</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.pushdown_predicates.pushdown": {"fullname": "sqlglot.optimizer.pushdown_predicates.pushdown", "modulename": "sqlglot.optimizer.pushdown_predicates", "qualname": "pushdown", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">condition</span>, </span><span class=\"param\"><span class=\"n\">sources</span>, </span><span class=\"param\"><span class=\"n\">scope_ref_count</span>, </span><span class=\"param\"><span class=\"n\">dialect</span>, </span><span class=\"param\"><span class=\"n\">join_index</span><span class=\"o\">=</span><span class=\"kc\">None</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.pushdown_predicates.pushdown_cnf": {"fullname": "sqlglot.optimizer.pushdown_predicates.pushdown_cnf", "modulename": "sqlglot.optimizer.pushdown_predicates", "qualname": "pushdown_cnf", "kind": "function", "doc": "<p>If the predicates are in CNF like form, we can simply replace each block in the parent.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">predicates</span>, </span><span class=\"param\"><span class=\"n\">sources</span>, </span><span class=\"param\"><span class=\"n\">scope_ref_count</span>, </span><span class=\"param\"><span class=\"n\">join_index</span><span class=\"o\">=</span><span class=\"kc\">None</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.pushdown_predicates.pushdown_dnf": {"fullname": "sqlglot.optimizer.pushdown_predicates.pushdown_dnf", "modulename": "sqlglot.optimizer.pushdown_predicates", "qualname": "pushdown_dnf", "kind": "function", "doc": "<p>If the predicates are in DNF form, we can only push down conditions that are in all blocks.\nAdditionally, we can't remove predicates from their original form.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">predicates</span>, </span><span class=\"param\"><span class=\"n\">sources</span>, </span><span class=\"param\"><span class=\"n\">scope_ref_count</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.pushdown_predicates.nodes_for_predicate": {"fullname": "sqlglot.optimizer.pushdown_predicates.nodes_for_predicate", "modulename": "sqlglot.optimizer.pushdown_predicates", "qualname": "nodes_for_predicate", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">predicate</span>, </span><span class=\"param\"><span class=\"n\">sources</span>, </span><span class=\"param\"><span class=\"n\">scope_ref_count</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.pushdown_predicates.replace_aliases": {"fullname": "sqlglot.optimizer.pushdown_predicates.replace_aliases", "modulename": "sqlglot.optimizer.pushdown_predicates", "qualname": "replace_aliases", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">source</span>, </span><span class=\"param\"><span class=\"n\">predicate</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.pushdown_projections": {"fullname": "sqlglot.optimizer.pushdown_projections", "modulename": "sqlglot.optimizer.pushdown_projections", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.optimizer.pushdown_projections.SELECT_ALL": {"fullname": "sqlglot.optimizer.pushdown_projections.SELECT_ALL", "modulename": "sqlglot.optimizer.pushdown_projections", "qualname": "SELECT_ALL", "kind": "variable", "doc": "<p></p>\n", "default_value": "<object object>"}, "sqlglot.optimizer.pushdown_projections.default_selection": {"fullname": "sqlglot.optimizer.pushdown_projections.default_selection", "modulename": "sqlglot.optimizer.pushdown_projections", "qualname": "default_selection", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">is_agg</span><span class=\"p\">:</span> <span class=\"nb\">bool</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Alias</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.pushdown_projections.pushdown_projections": {"fullname": "sqlglot.optimizer.pushdown_projections.pushdown_projections", "modulename": "sqlglot.optimizer.pushdown_projections", "qualname": "pushdown_projections", "kind": "function", "doc": "<p>Rewrite sqlglot AST to remove unused columns projections.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"gp\">>>> </span><span class=\"n\">sql</span> <span class=\"o\">=</span> <span class=\"s2\">"SELECT y.a AS a FROM (SELECT x.a AS a, x.b AS b FROM x) AS y"</span>\n<span class=\"gp\">>>> </span><span class=\"n\">expression</span> <span class=\"o\">=</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"n\">sql</span><span class=\"p\">)</span>\n<span class=\"gp\">>>> </span><span class=\"n\">pushdown_projections</span><span class=\"p\">(</span><span class=\"n\">expression</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT y.a AS a FROM (SELECT x.a AS a FROM x) AS y'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression (sqlglot.Expression):</strong> expression to optimize</li>\n<li><strong>remove_unused_selections (bool):</strong> remove selects that are unused</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>sqlglot.Expression: optimized expression</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span>, </span><span class=\"param\"><span class=\"n\">schema</span><span class=\"o\">=</span><span class=\"kc\">None</span>, </span><span class=\"param\"><span class=\"n\">remove_unused_selections</span><span class=\"o\">=</span><span class=\"kc\">True</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.qualify": {"fullname": "sqlglot.optimizer.qualify", "modulename": "sqlglot.optimizer.qualify", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.optimizer.qualify.qualify": {"fullname": "sqlglot.optimizer.qualify.qualify", "modulename": "sqlglot.optimizer.qualify", "qualname": "qualify", "kind": "function", "doc": "<p>Rewrite sqlglot AST to have normalized and qualified tables and columns.</p>\n\n<p>This step is necessary for all further SQLGlot optimizations.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"gp\">>>> </span><span class=\"n\">schema</span> <span class=\"o\">=</span> <span class=\"p\">{</span><span class=\"s2\">"tbl"</span><span class=\"p\">:</span> <span class=\"p\">{</span><span class=\"s2\">"col"</span><span class=\"p\">:</span> <span class=\"s2\">"INT"</span><span class=\"p\">}}</span>\n<span class=\"gp\">>>> </span><span class=\"n\">expression</span> <span class=\"o\">=</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT col FROM tbl"</span><span class=\"p\">)</span>\n<span class=\"gp\">>>> </span><span class=\"n\">qualify</span><span class=\"p\">(</span><span class=\"n\">expression</span><span class=\"p\">,</span> <span class=\"n\">schema</span><span class=\"o\">=</span><span class=\"n\">schema</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT "tbl"."col" AS "col" FROM "tbl" AS "tbl"'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> Expression to qualify.</li>\n<li><strong>db:</strong> Default database name for tables.</li>\n<li><strong>catalog:</strong> Default catalog name for tables.</li>\n<li><strong>schema:</strong> Schema to infer column names and types.</li>\n<li><strong>expand_alias_refs:</strong> Whether to expand references to aliases.</li>\n<li><strong>expand_stars:</strong> Whether to expand star queries. This is a necessary step\nfor most of the optimizer's rules to work; do not set to False unless you\nknow what you're doing!</li>\n<li><strong>infer_schema:</strong> Whether to infer the schema if missing.</li>\n<li><strong>isolate_tables:</strong> Whether to isolate table selects.</li>\n<li><strong>qualify_columns:</strong> Whether to qualify columns.</li>\n<li><strong>validate_qualify_columns:</strong> Whether to validate columns.</li>\n<li><strong>quote_identifiers:</strong> Whether to run the quote_identifiers step.\nThis step is necessary to ensure correctness for case sensitive queries.\nBut this flag is provided in case this step is performed at a later time.</li>\n<li><strong>identify:</strong> If True, quote all identifiers, else only necessary ones.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The qualified expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">db</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">catalog</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">schema</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">dict</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">schema</span><span class=\"o\">.</span><span class=\"n\">Schema</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">expand_alias_refs</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">expand_stars</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">infer_schema</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">bool</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">isolate_tables</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span>,</span><span class=\"param\">\t<span class=\"n\">qualify_columns</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">validate_qualify_columns</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">quote_identifiers</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">identify</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.qualify_columns": {"fullname": "sqlglot.optimizer.qualify_columns", "modulename": "sqlglot.optimizer.qualify_columns", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.optimizer.qualify_columns.qualify_columns": {"fullname": "sqlglot.optimizer.qualify_columns.qualify_columns", "modulename": "sqlglot.optimizer.qualify_columns", "qualname": "qualify_columns", "kind": "function", "doc": "<p>Rewrite sqlglot AST to have fully qualified columns.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"gp\">>>> </span><span class=\"n\">schema</span> <span class=\"o\">=</span> <span class=\"p\">{</span><span class=\"s2\">"tbl"</span><span class=\"p\">:</span> <span class=\"p\">{</span><span class=\"s2\">"col"</span><span class=\"p\">:</span> <span class=\"s2\">"INT"</span><span class=\"p\">}}</span>\n<span class=\"gp\">>>> </span><span class=\"n\">expression</span> <span class=\"o\">=</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT col FROM tbl"</span><span class=\"p\">)</span>\n<span class=\"gp\">>>> </span><span class=\"n\">qualify_columns</span><span class=\"p\">(</span><span class=\"n\">expression</span><span class=\"p\">,</span> <span class=\"n\">schema</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT tbl.col AS col FROM tbl'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> Expression to qualify.</li>\n<li><strong>schema:</strong> Database schema.</li>\n<li><strong>expand_alias_refs:</strong> Whether to expand references to aliases.</li>\n<li><strong>expand_stars:</strong> Whether to expand star queries. This is a necessary step\nfor most of the optimizer's rules to work; do not set to False unless you\nknow what you're doing!</li>\n<li><strong>infer_schema:</strong> Whether to infer the schema if missing.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The qualified expression.</p>\n</blockquote>\n\n<h6 id=\"notes\">Notes:</h6>\n\n<blockquote>\n <ul>\n <li>Currently only handles a single PIVOT or UNPIVOT operator</li>\n </ul>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">schema</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">schema</span><span class=\"o\">.</span><span class=\"n\">Schema</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">expand_alias_refs</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">expand_stars</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>,</span><span class=\"param\">\t<span class=\"n\">infer_schema</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">bool</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.qualify_columns.validate_qualify_columns": {"fullname": "sqlglot.optimizer.qualify_columns.validate_qualify_columns", "modulename": "sqlglot.optimizer.qualify_columns", "qualname": "validate_qualify_columns", "kind": "function", "doc": "<p>Raise an <code>OptimizeError</code> if any columns aren't qualified</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"o\">~</span><span class=\"n\">E</span></span><span class=\"return-annotation\">) -> <span class=\"o\">~</span><span class=\"n\">E</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.qualify_columns.qualify_outputs": {"fullname": "sqlglot.optimizer.qualify_columns.qualify_outputs", "modulename": "sqlglot.optimizer.qualify_columns", "qualname": "qualify_outputs", "kind": "function", "doc": "<p>Ensure all output columns are aliased</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">scope_or_expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">optimizer</span><span class=\"o\">.</span><span class=\"n\">scope</span><span class=\"o\">.</span><span class=\"n\">Scope</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.qualify_columns.quote_identifiers": {"fullname": "sqlglot.optimizer.qualify_columns.quote_identifiers", "modulename": "sqlglot.optimizer.qualify_columns", "qualname": "quote_identifiers", "kind": "function", "doc": "<p>Makes sure all identifiers that need to be quoted are quoted.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"o\">~</span><span class=\"n\">E</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">identify</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"o\">~</span><span class=\"n\">E</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.qualify_columns.pushdown_cte_alias_columns": {"fullname": "sqlglot.optimizer.qualify_columns.pushdown_cte_alias_columns", "modulename": "sqlglot.optimizer.qualify_columns", "qualname": "pushdown_cte_alias_columns", "kind": "function", "doc": "<p>Pushes down the CTE alias columns into the projection,</p>\n\n<p>This step is useful in Snowflake where the CTE alias columns can be referenced in the HAVING.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"gp\">>>> </span><span class=\"n\">expression</span> <span class=\"o\">=</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"WITH y (c) AS (SELECT SUM(a) FROM ( SELECT 1 a ) AS x HAVING c > 0) SELECT c FROM y"</span><span class=\"p\">)</span>\n<span class=\"gp\">>>> </span><span class=\"n\">pushdown_cte_alias_columns</span><span class=\"p\">(</span><span class=\"n\">expression</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'WITH y(c) AS (SELECT SUM(a) AS c FROM (SELECT 1 AS a) AS x HAVING c > 0) SELECT c FROM y'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> Expression to pushdown.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The expression with the CTE aliases pushed down into the projection.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.qualify_columns.Resolver": {"fullname": "sqlglot.optimizer.qualify_columns.Resolver", "modulename": "sqlglot.optimizer.qualify_columns", "qualname": "Resolver", "kind": "class", "doc": "<p>Helper for resolving columns.</p>\n\n<p>This is a class so we can lazily load some things and easily share them across functions.</p>\n"}, "sqlglot.optimizer.qualify_columns.Resolver.__init__": {"fullname": "sqlglot.optimizer.qualify_columns.Resolver.__init__", "modulename": "sqlglot.optimizer.qualify_columns", "qualname": "Resolver.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">scope</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">optimizer</span><span class=\"o\">.</span><span class=\"n\">scope</span><span class=\"o\">.</span><span class=\"n\">Scope</span>,</span><span class=\"param\">\t<span class=\"n\">schema</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">schema</span><span class=\"o\">.</span><span class=\"n\">Schema</span>,</span><span class=\"param\">\t<span class=\"n\">infer_schema</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span>)</span>"}, "sqlglot.optimizer.qualify_columns.Resolver.scope": {"fullname": "sqlglot.optimizer.qualify_columns.Resolver.scope", "modulename": "sqlglot.optimizer.qualify_columns", "qualname": "Resolver.scope", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.optimizer.qualify_columns.Resolver.schema": {"fullname": "sqlglot.optimizer.qualify_columns.Resolver.schema", "modulename": "sqlglot.optimizer.qualify_columns", "qualname": "Resolver.schema", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.optimizer.qualify_columns.Resolver.get_table": {"fullname": "sqlglot.optimizer.qualify_columns.Resolver.get_table", "modulename": "sqlglot.optimizer.qualify_columns", "qualname": "Resolver.get_table", "kind": "function", "doc": "<p>Get the table for a column name.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>column_name:</strong> The column name to find the table for.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The table name if it can be found/inferred.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">column_name</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Identifier</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.qualify_columns.Resolver.all_columns": {"fullname": "sqlglot.optimizer.qualify_columns.Resolver.all_columns", "modulename": "sqlglot.optimizer.qualify_columns", "qualname": "Resolver.all_columns", "kind": "variable", "doc": "<p>All available columns of all sources in this scope</p>\n", "annotation": ": Set[str]"}, "sqlglot.optimizer.qualify_columns.Resolver.get_source_columns": {"fullname": "sqlglot.optimizer.qualify_columns.Resolver.get_source_columns", "modulename": "sqlglot.optimizer.qualify_columns", "qualname": "Resolver.get_source_columns", "kind": "function", "doc": "<p>Resolve the source columns for a given source <code>name</code>.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">name</span><span class=\"p\">:</span> <span class=\"nb\">str</span>, </span><span class=\"param\"><span class=\"n\">only_visible</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Sequence</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.qualify_tables": {"fullname": "sqlglot.optimizer.qualify_tables", "modulename": "sqlglot.optimizer.qualify_tables", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.optimizer.qualify_tables.qualify_tables": {"fullname": "sqlglot.optimizer.qualify_tables.qualify_tables", "modulename": "sqlglot.optimizer.qualify_tables", "qualname": "qualify_tables", "kind": "function", "doc": "<p>Rewrite sqlglot AST to have fully qualified tables. Join constructs such as\n(t1 JOIN t2) AS t will be expanded into (SELECT * FROM t1 AS t1, t2 AS t2) AS t.</p>\n\n<h6 id=\"examples\">Examples:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"gp\">>>> </span><span class=\"n\">expression</span> <span class=\"o\">=</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT 1 FROM tbl"</span><span class=\"p\">)</span>\n<span class=\"gp\">>>> </span><span class=\"n\">qualify_tables</span><span class=\"p\">(</span><span class=\"n\">expression</span><span class=\"p\">,</span> <span class=\"n\">db</span><span class=\"o\">=</span><span class=\"s2\">"db"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT 1 FROM db.tbl AS tbl'</span>\n<span class=\"gp\">>>></span>\n<span class=\"gp\">>>> </span><span class=\"n\">expression</span> <span class=\"o\">=</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT 1 FROM (t1 JOIN t2) AS t"</span><span class=\"p\">)</span>\n<span class=\"gp\">>>> </span><span class=\"n\">qualify_tables</span><span class=\"p\">(</span><span class=\"n\">expression</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT 1 FROM (SELECT * FROM t1 AS t1, t2 AS t2) AS t'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> Expression to qualify</li>\n<li><strong>db:</strong> Database name</li>\n<li><strong>catalog:</strong> Catalog name</li>\n<li><strong>schema:</strong> A schema to populate</li>\n<li><strong>dialect:</strong> The dialect to parse catalog and schema into.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The qualified expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"o\">~</span><span class=\"n\">E</span>,</span><span class=\"param\">\t<span class=\"n\">db</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Identifier</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">catalog</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Identifier</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">schema</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">schema</span><span class=\"o\">.</span><span class=\"n\">Schema</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"o\">~</span><span class=\"n\">E</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.scope": {"fullname": "sqlglot.optimizer.scope", "modulename": "sqlglot.optimizer.scope", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.optimizer.scope.logger": {"fullname": "sqlglot.optimizer.scope.logger", "modulename": "sqlglot.optimizer.scope", "qualname": "logger", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Logger sqlglot (WARNING)>"}, "sqlglot.optimizer.scope.TRAVERSABLES": {"fullname": "sqlglot.optimizer.scope.TRAVERSABLES", "modulename": "sqlglot.optimizer.scope", "qualname": "TRAVERSABLES", "kind": "variable", "doc": "<p></p>\n", "default_value": "(<class 'sqlglot.expressions.Query'>, <class 'sqlglot.expressions.DDL'>, <class 'sqlglot.expressions.DML'>)"}, "sqlglot.optimizer.scope.ScopeType": {"fullname": "sqlglot.optimizer.scope.ScopeType", "modulename": "sqlglot.optimizer.scope", "qualname": "ScopeType", "kind": "class", "doc": "<p>An enumeration.</p>\n", "bases": "enum.Enum"}, "sqlglot.optimizer.scope.ScopeType.ROOT": {"fullname": "sqlglot.optimizer.scope.ScopeType.ROOT", "modulename": "sqlglot.optimizer.scope", "qualname": "ScopeType.ROOT", "kind": "variable", "doc": "<p></p>\n", "default_value": "<ScopeType.ROOT: 1>"}, "sqlglot.optimizer.scope.ScopeType.SUBQUERY": {"fullname": "sqlglot.optimizer.scope.ScopeType.SUBQUERY", "modulename": "sqlglot.optimizer.scope", "qualname": "ScopeType.SUBQUERY", "kind": "variable", "doc": "<p></p>\n", "default_value": "<ScopeType.SUBQUERY: 2>"}, "sqlglot.optimizer.scope.ScopeType.DERIVED_TABLE": {"fullname": "sqlglot.optimizer.scope.ScopeType.DERIVED_TABLE", "modulename": "sqlglot.optimizer.scope", "qualname": "ScopeType.DERIVED_TABLE", "kind": "variable", "doc": "<p></p>\n", "default_value": "<ScopeType.DERIVED_TABLE: 3>"}, "sqlglot.optimizer.scope.ScopeType.CTE": {"fullname": "sqlglot.optimizer.scope.ScopeType.CTE", "modulename": "sqlglot.optimizer.scope", "qualname": "ScopeType.CTE", "kind": "variable", "doc": "<p></p>\n", "default_value": "<ScopeType.CTE: 4>"}, "sqlglot.optimizer.scope.ScopeType.UNION": {"fullname": "sqlglot.optimizer.scope.ScopeType.UNION", "modulename": "sqlglot.optimizer.scope", "qualname": "ScopeType.UNION", "kind": "variable", "doc": "<p></p>\n", "default_value": "<ScopeType.UNION: 5>"}, "sqlglot.optimizer.scope.ScopeType.UDTF": {"fullname": "sqlglot.optimizer.scope.ScopeType.UDTF", "modulename": "sqlglot.optimizer.scope", "qualname": "ScopeType.UDTF", "kind": "variable", "doc": "<p></p>\n", "default_value": "<ScopeType.UDTF: 6>"}, "sqlglot.optimizer.scope.Scope": {"fullname": "sqlglot.optimizer.scope.Scope", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope", "kind": "class", "doc": "<p>Selection scope.</p>\n\n<h6 id=\"attributes\">Attributes:</h6>\n\n<ul>\n<li><strong>expression (exp.Select|exp.Union):</strong> Root expression of this scope</li>\n<li><strong>sources (dict[str, exp.Table|Scope]):</strong> Mapping of source name to either\na Table expression or another Scope instance. For example:\n SELECT * FROM x {\"x\": Table(this=\"x\")}\n SELECT * FROM x AS y {\"y\": Table(this=\"x\")}\n SELECT * FROM (SELECT ...) AS y {\"y\": Scope(...)}</li>\n<li><strong>lateral_sources (dict[str, exp.Table|Scope]):</strong> Sources from laterals\nFor example:\n SELECT c FROM x LATERAL VIEW EXPLODE (a) AS c;\nThe LATERAL VIEW EXPLODE gets x as a source.</li>\n<li><strong>cte_sources (dict[str, Scope]):</strong> Sources from CTES</li>\n<li><strong>outer_columns (list[str]):</strong> If this is a derived table or CTE, and the outer query\ndefines a column list for the alias of this scope, this is that list of columns.\nFor example:\n SELECT * FROM (SELECT ...) AS y(col1, col2)\nThe inner query would have <code>[\"col1\", \"col2\"]</code> for its <code>outer_columns</code></li>\n<li><strong>parent (Scope):</strong> Parent scope</li>\n<li><strong>scope_type (ScopeType):</strong> Type of this scope, relative to it's parent</li>\n<li><strong>subquery_scopes (list[Scope]):</strong> List of all child scopes for subqueries</li>\n<li><strong>cte_scopes (list[Scope]):</strong> List of all child scopes for CTEs</li>\n<li><strong>derived_table_scopes (list[Scope]):</strong> List of all child scopes for derived_tables</li>\n<li><strong>udtf_scopes (list[Scope]):</strong> List of all child scopes for user defined tabular functions</li>\n<li><strong>table_scopes (list[Scope]):</strong> derived_table_scopes + udtf_scopes, in the order that they're defined</li>\n<li><strong>union_scopes (list[Scope, Scope]):</strong> If this Scope is for a Union expression, this will be\na list of the left and right child scopes.</li>\n</ul>\n"}, "sqlglot.optimizer.scope.Scope.__init__": {"fullname": "sqlglot.optimizer.scope.Scope.__init__", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span>,</span><span class=\"param\">\t<span class=\"n\">sources</span><span class=\"o\">=</span><span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">outer_columns</span><span class=\"o\">=</span><span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">parent</span><span class=\"o\">=</span><span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">scope_type</span><span class=\"o\">=<</span><span class=\"n\">ScopeType</span><span class=\"o\">.</span><span class=\"n\">ROOT</span><span class=\"p\">:</span> <span class=\"mi\">1</span><span class=\"o\">></span>,</span><span class=\"param\">\t<span class=\"n\">lateral_sources</span><span class=\"o\">=</span><span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">cte_sources</span><span class=\"o\">=</span><span class=\"kc\">None</span></span>)</span>"}, "sqlglot.optimizer.scope.Scope.expression": {"fullname": "sqlglot.optimizer.scope.Scope.expression", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.expression", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.optimizer.scope.Scope.sources": {"fullname": "sqlglot.optimizer.scope.Scope.sources", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.sources", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.optimizer.scope.Scope.lateral_sources": {"fullname": "sqlglot.optimizer.scope.Scope.lateral_sources", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.lateral_sources", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.optimizer.scope.Scope.cte_sources": {"fullname": "sqlglot.optimizer.scope.Scope.cte_sources", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.cte_sources", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.optimizer.scope.Scope.outer_columns": {"fullname": "sqlglot.optimizer.scope.Scope.outer_columns", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.outer_columns", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.optimizer.scope.Scope.parent": {"fullname": "sqlglot.optimizer.scope.Scope.parent", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.parent", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.optimizer.scope.Scope.scope_type": {"fullname": "sqlglot.optimizer.scope.Scope.scope_type", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.scope_type", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.optimizer.scope.Scope.subquery_scopes": {"fullname": "sqlglot.optimizer.scope.Scope.subquery_scopes", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.subquery_scopes", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.optimizer.scope.Scope.derived_table_scopes": {"fullname": "sqlglot.optimizer.scope.Scope.derived_table_scopes", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.derived_table_scopes", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.optimizer.scope.Scope.table_scopes": {"fullname": "sqlglot.optimizer.scope.Scope.table_scopes", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.table_scopes", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.optimizer.scope.Scope.cte_scopes": {"fullname": "sqlglot.optimizer.scope.Scope.cte_scopes", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.cte_scopes", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.optimizer.scope.Scope.union_scopes": {"fullname": "sqlglot.optimizer.scope.Scope.union_scopes", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.union_scopes", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.optimizer.scope.Scope.udtf_scopes": {"fullname": "sqlglot.optimizer.scope.Scope.udtf_scopes", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.udtf_scopes", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.optimizer.scope.Scope.clear_cache": {"fullname": "sqlglot.optimizer.scope.Scope.clear_cache", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.clear_cache", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.scope.Scope.branch": {"fullname": "sqlglot.optimizer.scope.Scope.branch", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.branch", "kind": "function", "doc": "<p>Branch from the current scope to a new, inner scope</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span>,</span><span class=\"param\">\t<span class=\"n\">scope_type</span>,</span><span class=\"param\">\t<span class=\"n\">sources</span><span class=\"o\">=</span><span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">cte_sources</span><span class=\"o\">=</span><span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">lateral_sources</span><span class=\"o\">=</span><span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.scope.Scope.walk": {"fullname": "sqlglot.optimizer.scope.Scope.walk", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.walk", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">bfs</span><span class=\"o\">=</span><span class=\"kc\">True</span>, </span><span class=\"param\"><span class=\"n\">prune</span><span class=\"o\">=</span><span class=\"kc\">None</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.scope.Scope.find": {"fullname": "sqlglot.optimizer.scope.Scope.find", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.find", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">*</span><span class=\"n\">expression_types</span>, </span><span class=\"param\"><span class=\"n\">bfs</span><span class=\"o\">=</span><span class=\"kc\">True</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.scope.Scope.find_all": {"fullname": "sqlglot.optimizer.scope.Scope.find_all", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.find_all", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">*</span><span class=\"n\">expression_types</span>, </span><span class=\"param\"><span class=\"n\">bfs</span><span class=\"o\">=</span><span class=\"kc\">True</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.scope.Scope.replace": {"fullname": "sqlglot.optimizer.scope.Scope.replace", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.replace", "kind": "function", "doc": "<p>Replace <code>old</code> with <code>new</code>.</p>\n\n<p>This can be used instead of <code>exp.Expression.replace</code> to ensure the <code>Scope</code> is kept up-to-date.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>old (exp.Expression):</strong> old node</li>\n<li><strong>new (exp.Expression):</strong> new node</li>\n</ul>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">old</span>, </span><span class=\"param\"><span class=\"n\">new</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.scope.Scope.tables": {"fullname": "sqlglot.optimizer.scope.Scope.tables", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.tables", "kind": "variable", "doc": "<p>List of tables in this scope.</p>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>list[exp.Table]: tables</p>\n</blockquote>\n"}, "sqlglot.optimizer.scope.Scope.ctes": {"fullname": "sqlglot.optimizer.scope.Scope.ctes", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.ctes", "kind": "variable", "doc": "<p>List of CTEs in this scope.</p>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>list[exp.CTE]: ctes</p>\n</blockquote>\n"}, "sqlglot.optimizer.scope.Scope.derived_tables": {"fullname": "sqlglot.optimizer.scope.Scope.derived_tables", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.derived_tables", "kind": "variable", "doc": "<p>List of derived tables in this scope.</p>\n\n<h6 id=\"for-example\">For example:</h6>\n\n<blockquote>\n <p>SELECT * FROM (SELECT ...) <- that's a derived table</p>\n</blockquote>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>list[exp.Subquery]: derived tables</p>\n</blockquote>\n"}, "sqlglot.optimizer.scope.Scope.udtfs": {"fullname": "sqlglot.optimizer.scope.Scope.udtfs", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.udtfs", "kind": "variable", "doc": "<p>List of \"User Defined Tabular Functions\" in this scope.</p>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>list[exp.UDTF]: UDTFs</p>\n</blockquote>\n"}, "sqlglot.optimizer.scope.Scope.subqueries": {"fullname": "sqlglot.optimizer.scope.Scope.subqueries", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.subqueries", "kind": "variable", "doc": "<p>List of subqueries in this scope.</p>\n\n<h6 id=\"for-example\">For example:</h6>\n\n<blockquote>\n <p>SELECT * FROM x WHERE a IN (SELECT ...) <- that's a subquery</p>\n</blockquote>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>list[exp.Select | exp.Union]: subqueries</p>\n</blockquote>\n"}, "sqlglot.optimizer.scope.Scope.columns": {"fullname": "sqlglot.optimizer.scope.Scope.columns", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.columns", "kind": "variable", "doc": "<p>List of columns in this scope.</p>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>list[exp.Column]: Column instances in this scope, plus any\n Columns that reference this scope from correlated subqueries.</p>\n</blockquote>\n"}, "sqlglot.optimizer.scope.Scope.selected_sources": {"fullname": "sqlglot.optimizer.scope.Scope.selected_sources", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.selected_sources", "kind": "variable", "doc": "<p>Mapping of nodes and sources that are actually selected from in this scope.</p>\n\n<p>That is, all tables in a schema are selectable at any point. But a\ntable only becomes a selected source if it's included in a FROM or JOIN clause.</p>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>dict[str, (exp.Table|exp.Select, exp.Table|Scope)]: selected sources and nodes</p>\n</blockquote>\n"}, "sqlglot.optimizer.scope.Scope.references": {"fullname": "sqlglot.optimizer.scope.Scope.references", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.references", "kind": "variable", "doc": "<p></p>\n", "annotation": ": List[Tuple[str, sqlglot.expressions.Expression]]"}, "sqlglot.optimizer.scope.Scope.external_columns": {"fullname": "sqlglot.optimizer.scope.Scope.external_columns", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.external_columns", "kind": "variable", "doc": "<p>Columns that appear to reference sources in outer scopes.</p>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>list[exp.Column]: Column instances that don't reference\n sources in the current scope.</p>\n</blockquote>\n"}, "sqlglot.optimizer.scope.Scope.unqualified_columns": {"fullname": "sqlglot.optimizer.scope.Scope.unqualified_columns", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.unqualified_columns", "kind": "variable", "doc": "<p>Unqualified columns in the current scope.</p>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>list[exp.Column]: Unqualified columns</p>\n</blockquote>\n"}, "sqlglot.optimizer.scope.Scope.join_hints": {"fullname": "sqlglot.optimizer.scope.Scope.join_hints", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.join_hints", "kind": "variable", "doc": "<p>Hints that exist in the scope that reference tables</p>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>list[exp.JoinHint]: Join hints that are referenced within the scope</p>\n</blockquote>\n"}, "sqlglot.optimizer.scope.Scope.pivots": {"fullname": "sqlglot.optimizer.scope.Scope.pivots", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.pivots", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.optimizer.scope.Scope.source_columns": {"fullname": "sqlglot.optimizer.scope.Scope.source_columns", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.source_columns", "kind": "function", "doc": "<p>Get all columns in the current scope for a particular source.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>source_name (str):</strong> Name of the source</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>list[exp.Column]: Column instances that reference <code>source_name</code></p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">source_name</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.scope.Scope.is_subquery": {"fullname": "sqlglot.optimizer.scope.Scope.is_subquery", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.is_subquery", "kind": "variable", "doc": "<p>Determine if this scope is a subquery</p>\n"}, "sqlglot.optimizer.scope.Scope.is_derived_table": {"fullname": "sqlglot.optimizer.scope.Scope.is_derived_table", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.is_derived_table", "kind": "variable", "doc": "<p>Determine if this scope is a derived table</p>\n"}, "sqlglot.optimizer.scope.Scope.is_union": {"fullname": "sqlglot.optimizer.scope.Scope.is_union", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.is_union", "kind": "variable", "doc": "<p>Determine if this scope is a union</p>\n"}, "sqlglot.optimizer.scope.Scope.is_cte": {"fullname": "sqlglot.optimizer.scope.Scope.is_cte", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.is_cte", "kind": "variable", "doc": "<p>Determine if this scope is a common table expression</p>\n"}, "sqlglot.optimizer.scope.Scope.is_root": {"fullname": "sqlglot.optimizer.scope.Scope.is_root", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.is_root", "kind": "variable", "doc": "<p>Determine if this is the root scope</p>\n"}, "sqlglot.optimizer.scope.Scope.is_udtf": {"fullname": "sqlglot.optimizer.scope.Scope.is_udtf", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.is_udtf", "kind": "variable", "doc": "<p>Determine if this scope is a UDTF (User Defined Table Function)</p>\n"}, "sqlglot.optimizer.scope.Scope.is_correlated_subquery": {"fullname": "sqlglot.optimizer.scope.Scope.is_correlated_subquery", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.is_correlated_subquery", "kind": "variable", "doc": "<p>Determine if this scope is a correlated subquery</p>\n"}, "sqlglot.optimizer.scope.Scope.rename_source": {"fullname": "sqlglot.optimizer.scope.Scope.rename_source", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.rename_source", "kind": "function", "doc": "<p>Rename a source in this scope</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">old_name</span>, </span><span class=\"param\"><span class=\"n\">new_name</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.scope.Scope.add_source": {"fullname": "sqlglot.optimizer.scope.Scope.add_source", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.add_source", "kind": "function", "doc": "<p>Add a source to this scope</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">name</span>, </span><span class=\"param\"><span class=\"n\">source</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.scope.Scope.remove_source": {"fullname": "sqlglot.optimizer.scope.Scope.remove_source", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.remove_source", "kind": "function", "doc": "<p>Remove a source from this scope</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">name</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.scope.Scope.traverse": {"fullname": "sqlglot.optimizer.scope.Scope.traverse", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.traverse", "kind": "function", "doc": "<p>Traverse the scope tree from this node.</p>\n\n<h6 id=\"yields\">Yields:</h6>\n\n<blockquote>\n <p>Scope: scope instances in depth-first-search post-order</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.scope.Scope.ref_count": {"fullname": "sqlglot.optimizer.scope.Scope.ref_count", "modulename": "sqlglot.optimizer.scope", "qualname": "Scope.ref_count", "kind": "function", "doc": "<p>Count the number of times each scope in this tree is referenced.</p>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>dict[int, int]: Mapping of Scope instance ID to reference count</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.scope.traverse_scope": {"fullname": "sqlglot.optimizer.scope.traverse_scope", "modulename": "sqlglot.optimizer.scope", "qualname": "traverse_scope", "kind": "function", "doc": "<p>Traverse an expression by its \"scopes\".</p>\n\n<p>\"Scope\" represents the current context of a Select statement.</p>\n\n<p>This is helpful for optimizing queries, where we need more information than\nthe expression tree itself. For example, we might care about the source\nnames within a subquery. Returns a list because a generator could result in\nincomplete properties which is confusing.</p>\n\n<h6 id=\"examples\">Examples:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"gp\">>>> </span><span class=\"n\">expression</span> <span class=\"o\">=</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT a FROM (SELECT a FROM x) AS y"</span><span class=\"p\">)</span>\n<span class=\"gp\">>>> </span><span class=\"n\">scopes</span> <span class=\"o\">=</span> <span class=\"n\">traverse_scope</span><span class=\"p\">(</span><span class=\"n\">expression</span><span class=\"p\">)</span>\n<span class=\"gp\">>>> </span><span class=\"n\">scopes</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">expression</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">(),</span> <span class=\"nb\">list</span><span class=\"p\">(</span><span class=\"n\">scopes</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">sources</span><span class=\"p\">)</span>\n<span class=\"go\">('SELECT a FROM x', ['x'])</span>\n<span class=\"gp\">>>> </span><span class=\"n\">scopes</span><span class=\"p\">[</span><span class=\"mi\">1</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">expression</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">(),</span> <span class=\"nb\">list</span><span class=\"p\">(</span><span class=\"n\">scopes</span><span class=\"p\">[</span><span class=\"mi\">1</span><span class=\"p\">]</span><span class=\"o\">.</span><span class=\"n\">sources</span><span class=\"p\">)</span>\n<span class=\"go\">('SELECT a FROM (SELECT a FROM x) AS y', ['y'])</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> Expression to traverse</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>A list of the created scope instances</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">optimizer</span><span class=\"o\">.</span><span class=\"n\">scope</span><span class=\"o\">.</span><span class=\"n\">Scope</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.scope.build_scope": {"fullname": "sqlglot.optimizer.scope.build_scope", "modulename": "sqlglot.optimizer.scope", "qualname": "build_scope", "kind": "function", "doc": "<p>Build a scope tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> Expression to build the scope tree for.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The root scope</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">optimizer</span><span class=\"o\">.</span><span class=\"n\">scope</span><span class=\"o\">.</span><span class=\"n\">Scope</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.scope.walk_in_scope": {"fullname": "sqlglot.optimizer.scope.walk_in_scope", "modulename": "sqlglot.optimizer.scope", "qualname": "walk_in_scope", "kind": "function", "doc": "<p>Returns a generator object which visits all nodes in the syntrax tree, stopping at\nnodes that start child scopes.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression (exp.Expression):</strong> </li>\n<li><strong>bfs (bool):</strong> if set to True the BFS traversal order will be applied,\notherwise the DFS traversal will be used instead.</li>\n<li><strong>prune ((node, parent, arg_key) -> bool):</strong> callable that returns True if\nthe generator should stop traversing this branch of the tree.</li>\n</ul>\n\n<h6 id=\"yields\">Yields:</h6>\n\n<blockquote>\n <p>tuple[exp.Expression, Optional[exp.Expression], str]: node, parent, arg key</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span>, </span><span class=\"param\"><span class=\"n\">bfs</span><span class=\"o\">=</span><span class=\"kc\">True</span>, </span><span class=\"param\"><span class=\"n\">prune</span><span class=\"o\">=</span><span class=\"kc\">None</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.scope.find_all_in_scope": {"fullname": "sqlglot.optimizer.scope.find_all_in_scope", "modulename": "sqlglot.optimizer.scope", "qualname": "find_all_in_scope", "kind": "function", "doc": "<p>Returns a generator object which visits all nodes in this scope and only yields those that\nmatch at least one of the specified expression types.</p>\n\n<p>This does NOT traverse into subscopes.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression (exp.Expression):</strong> </li>\n<li><strong>expression_types (tuple[type]|type):</strong> the expression type(s) to match.</li>\n<li><strong>bfs (bool):</strong> True to use breadth-first search, False to use depth-first.</li>\n</ul>\n\n<h6 id=\"yields\">Yields:</h6>\n\n<blockquote>\n <p>exp.Expression: nodes</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span>, </span><span class=\"param\"><span class=\"n\">expression_types</span>, </span><span class=\"param\"><span class=\"n\">bfs</span><span class=\"o\">=</span><span class=\"kc\">True</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.scope.find_in_scope": {"fullname": "sqlglot.optimizer.scope.find_in_scope", "modulename": "sqlglot.optimizer.scope", "qualname": "find_in_scope", "kind": "function", "doc": "<p>Returns the first node in this scope which matches at least one of the specified types.</p>\n\n<p>This does NOT traverse into subscopes.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression (exp.Expression):</strong> </li>\n<li><strong>expression_types (tuple[type]|type):</strong> the expression type(s) to match.</li>\n<li><strong>bfs (bool):</strong> True to use breadth-first search, False to use depth-first.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>exp.Expression: the node which matches the criteria or None if no node matching\n the criteria was found.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span>, </span><span class=\"param\"><span class=\"n\">expression_types</span>, </span><span class=\"param\"><span class=\"n\">bfs</span><span class=\"o\">=</span><span class=\"kc\">True</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify": {"fullname": "sqlglot.optimizer.simplify", "modulename": "sqlglot.optimizer.simplify", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.optimizer.simplify.FINAL": {"fullname": "sqlglot.optimizer.simplify.FINAL", "modulename": "sqlglot.optimizer.simplify", "qualname": "FINAL", "kind": "variable", "doc": "<p></p>\n", "default_value": "'final'"}, "sqlglot.optimizer.simplify.TINYINT_MIN": {"fullname": "sqlglot.optimizer.simplify.TINYINT_MIN", "modulename": "sqlglot.optimizer.simplify", "qualname": "TINYINT_MIN", "kind": "variable", "doc": "<p></p>\n", "default_value": "-128"}, "sqlglot.optimizer.simplify.TINYINT_MAX": {"fullname": "sqlglot.optimizer.simplify.TINYINT_MAX", "modulename": "sqlglot.optimizer.simplify", "qualname": "TINYINT_MAX", "kind": "variable", "doc": "<p></p>\n", "default_value": "127"}, "sqlglot.optimizer.simplify.UTINYINT_MIN": {"fullname": "sqlglot.optimizer.simplify.UTINYINT_MIN", "modulename": "sqlglot.optimizer.simplify", "qualname": "UTINYINT_MIN", "kind": "variable", "doc": "<p></p>\n", "default_value": "0"}, "sqlglot.optimizer.simplify.UTINYINT_MAX": {"fullname": "sqlglot.optimizer.simplify.UTINYINT_MAX", "modulename": "sqlglot.optimizer.simplify", "qualname": "UTINYINT_MAX", "kind": "variable", "doc": "<p></p>\n", "default_value": "255"}, "sqlglot.optimizer.simplify.UnsupportedUnit": {"fullname": "sqlglot.optimizer.simplify.UnsupportedUnit", "modulename": "sqlglot.optimizer.simplify", "qualname": "UnsupportedUnit", "kind": "class", "doc": "<p>Common base class for all non-exit exceptions.</p>\n", "bases": "builtins.Exception"}, "sqlglot.optimizer.simplify.simplify": {"fullname": "sqlglot.optimizer.simplify.simplify", "modulename": "sqlglot.optimizer.simplify", "qualname": "simplify", "kind": "function", "doc": "<p>Rewrite sqlglot AST to simplify expressions.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"gp\">>>> </span><span class=\"n\">expression</span> <span class=\"o\">=</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"TRUE AND TRUE"</span><span class=\"p\">)</span>\n<span class=\"gp\">>>> </span><span class=\"n\">simplify</span><span class=\"p\">(</span><span class=\"n\">expression</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'TRUE'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression (sqlglot.Expression):</strong> expression to simplify</li>\n<li><strong>constant_propagation:</strong> whether the constant propagation rule should be used</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>sqlglot.Expression: simplified expression</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">constant_propagation</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.catch": {"fullname": "sqlglot.optimizer.simplify.catch", "modulename": "sqlglot.optimizer.simplify", "qualname": "catch", "kind": "function", "doc": "<p>Decorator that ignores a simplification function if any of <code>exceptions</code> are raised</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"o\">*</span><span class=\"n\">exceptions</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.rewrite_between": {"fullname": "sqlglot.optimizer.simplify.rewrite_between", "modulename": "sqlglot.optimizer.simplify", "qualname": "rewrite_between", "kind": "function", "doc": "<p>Rewrite x between y and z to x >= y AND x <= z.</p>\n\n<p>This is done because comparison simplification is only done on lt/lte/gt/gte.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.COMPLEMENT_COMPARISONS": {"fullname": "sqlglot.optimizer.simplify.COMPLEMENT_COMPARISONS", "modulename": "sqlglot.optimizer.simplify", "qualname": "COMPLEMENT_COMPARISONS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.LT'>: <class 'sqlglot.expressions.GTE'>, <class 'sqlglot.expressions.GT'>: <class 'sqlglot.expressions.LTE'>, <class 'sqlglot.expressions.LTE'>: <class 'sqlglot.expressions.GT'>, <class 'sqlglot.expressions.GTE'>: <class 'sqlglot.expressions.LT'>, <class 'sqlglot.expressions.EQ'>: <class 'sqlglot.expressions.NEQ'>, <class 'sqlglot.expressions.NEQ'>: <class 'sqlglot.expressions.EQ'>}"}, "sqlglot.optimizer.simplify.simplify_not": {"fullname": "sqlglot.optimizer.simplify.simplify_not", "modulename": "sqlglot.optimizer.simplify", "qualname": "simplify_not", "kind": "function", "doc": "<p>Demorgan's Law\nNOT (x OR y) -> NOT x AND NOT y\nNOT (x AND y) -> NOT x OR NOT y</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.flatten": {"fullname": "sqlglot.optimizer.simplify.flatten", "modulename": "sqlglot.optimizer.simplify", "qualname": "flatten", "kind": "function", "doc": "<p>A AND (B AND C) -> A AND B AND C\nA OR (B OR C) -> A OR B OR C</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.simplify_connectors": {"fullname": "sqlglot.optimizer.simplify.simplify_connectors", "modulename": "sqlglot.optimizer.simplify", "qualname": "simplify_connectors", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span>, </span><span class=\"param\"><span class=\"n\">root</span><span class=\"o\">=</span><span class=\"kc\">True</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.LT_LTE": {"fullname": "sqlglot.optimizer.simplify.LT_LTE", "modulename": "sqlglot.optimizer.simplify", "qualname": "LT_LTE", "kind": "variable", "doc": "<p></p>\n", "default_value": "(<class 'sqlglot.expressions.LT'>, <class 'sqlglot.expressions.LTE'>)"}, "sqlglot.optimizer.simplify.GT_GTE": {"fullname": "sqlglot.optimizer.simplify.GT_GTE", "modulename": "sqlglot.optimizer.simplify", "qualname": "GT_GTE", "kind": "variable", "doc": "<p></p>\n", "default_value": "(<class 'sqlglot.expressions.GT'>, <class 'sqlglot.expressions.GTE'>)"}, "sqlglot.optimizer.simplify.COMPARISONS": {"fullname": "sqlglot.optimizer.simplify.COMPARISONS", "modulename": "sqlglot.optimizer.simplify", "qualname": "COMPARISONS", "kind": "variable", "doc": "<p></p>\n", "default_value": "(<class 'sqlglot.expressions.LT'>, <class 'sqlglot.expressions.LTE'>, <class 'sqlglot.expressions.GT'>, <class 'sqlglot.expressions.GTE'>, <class 'sqlglot.expressions.EQ'>, <class 'sqlglot.expressions.NEQ'>, <class 'sqlglot.expressions.Is'>)"}, "sqlglot.optimizer.simplify.INVERSE_COMPARISONS": {"fullname": "sqlglot.optimizer.simplify.INVERSE_COMPARISONS", "modulename": "sqlglot.optimizer.simplify", "qualname": "INVERSE_COMPARISONS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[Type[sqlglot.expressions.Expression], Type[sqlglot.expressions.Expression]]", "default_value": "{<class 'sqlglot.expressions.LT'>: <class 'sqlglot.expressions.GT'>, <class 'sqlglot.expressions.GT'>: <class 'sqlglot.expressions.LT'>, <class 'sqlglot.expressions.LTE'>: <class 'sqlglot.expressions.GTE'>, <class 'sqlglot.expressions.GTE'>: <class 'sqlglot.expressions.LTE'>}"}, "sqlglot.optimizer.simplify.NONDETERMINISTIC": {"fullname": "sqlglot.optimizer.simplify.NONDETERMINISTIC", "modulename": "sqlglot.optimizer.simplify", "qualname": "NONDETERMINISTIC", "kind": "variable", "doc": "<p></p>\n", "default_value": "(<class 'sqlglot.expressions.Rand'>, <class 'sqlglot.expressions.Randn'>)"}, "sqlglot.optimizer.simplify.remove_complements": {"fullname": "sqlglot.optimizer.simplify.remove_complements", "modulename": "sqlglot.optimizer.simplify", "qualname": "remove_complements", "kind": "function", "doc": "<p>Removing complements.</p>\n\n<p>A AND NOT A -> FALSE\nA OR NOT A -> TRUE</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span>, </span><span class=\"param\"><span class=\"n\">root</span><span class=\"o\">=</span><span class=\"kc\">True</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.uniq_sort": {"fullname": "sqlglot.optimizer.simplify.uniq_sort", "modulename": "sqlglot.optimizer.simplify", "qualname": "uniq_sort", "kind": "function", "doc": "<p>Uniq and sort a connector.</p>\n\n<p>C AND A AND B AND B -> A AND B AND C</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span>, </span><span class=\"param\"><span class=\"n\">root</span><span class=\"o\">=</span><span class=\"kc\">True</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.absorb_and_eliminate": {"fullname": "sqlglot.optimizer.simplify.absorb_and_eliminate", "modulename": "sqlglot.optimizer.simplify", "qualname": "absorb_and_eliminate", "kind": "function", "doc": "<p>absorption:\n A AND (A OR B) -> A\n A OR (A AND B) -> A\n A AND (NOT A OR B) -> A AND B\n A OR (NOT A AND B) -> A OR B\nelimination:\n (A AND B) OR (A AND NOT B) -> A\n (A OR B) AND (A OR NOT B) -> A</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span>, </span><span class=\"param\"><span class=\"n\">root</span><span class=\"o\">=</span><span class=\"kc\">True</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.propagate_constants": {"fullname": "sqlglot.optimizer.simplify.propagate_constants", "modulename": "sqlglot.optimizer.simplify", "qualname": "propagate_constants", "kind": "function", "doc": "<p>Propagate constants for conjunctions in DNF:</p>\n\n<p>SELECT * FROM t WHERE a = b AND b = 5 becomes\nSELECT * FROM t WHERE a = 5 AND b = 5</p>\n\n<p>Reference: <a href=\"https://www.sqlite.org/optoverview.html\">https://www.sqlite.org/optoverview.html</a></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span>, </span><span class=\"param\"><span class=\"n\">root</span><span class=\"o\">=</span><span class=\"kc\">True</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.INVERSE_DATE_OPS": {"fullname": "sqlglot.optimizer.simplify.INVERSE_DATE_OPS", "modulename": "sqlglot.optimizer.simplify", "qualname": "INVERSE_DATE_OPS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[Type[sqlglot.expressions.Expression], Type[sqlglot.expressions.Expression]]", "default_value": "{<class 'sqlglot.expressions.DateAdd'>: <class 'sqlglot.expressions.Sub'>, <class 'sqlglot.expressions.DateSub'>: <class 'sqlglot.expressions.Add'>, <class 'sqlglot.expressions.DatetimeAdd'>: <class 'sqlglot.expressions.Sub'>, <class 'sqlglot.expressions.DatetimeSub'>: <class 'sqlglot.expressions.Add'>}"}, "sqlglot.optimizer.simplify.INVERSE_OPS": {"fullname": "sqlglot.optimizer.simplify.INVERSE_OPS", "modulename": "sqlglot.optimizer.simplify", "qualname": "INVERSE_OPS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[Type[sqlglot.expressions.Expression], Type[sqlglot.expressions.Expression]]", "default_value": "{<class 'sqlglot.expressions.DateAdd'>: <class 'sqlglot.expressions.Sub'>, <class 'sqlglot.expressions.DateSub'>: <class 'sqlglot.expressions.Add'>, <class 'sqlglot.expressions.DatetimeAdd'>: <class 'sqlglot.expressions.Sub'>, <class 'sqlglot.expressions.DatetimeSub'>: <class 'sqlglot.expressions.Add'>, <class 'sqlglot.expressions.Add'>: <class 'sqlglot.expressions.Sub'>, <class 'sqlglot.expressions.Sub'>: <class 'sqlglot.expressions.Add'>}"}, "sqlglot.optimizer.simplify.simplify_equality": {"fullname": "sqlglot.optimizer.simplify.simplify_equality", "modulename": "sqlglot.optimizer.simplify", "qualname": "simplify_equality", "kind": "function", "doc": "<h6 id=\"use-the-subtraction-and-addition-properties-of-equality-to-simplify-expressions\">Use the subtraction and addition properties of equality to simplify expressions:</h6>\n\n<blockquote>\n <p>x + 1 = 3 becomes x = 2</p>\n</blockquote>\n\n<p>There are two binary operations in the above expression: + and =\nHere's how we reference all the operands in the code below:</p>\n\n<pre><code> l r\nx + 1 = 3\na b\n</code></pre>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span>, </span><span class=\"param\"><span class=\"o\">*</span><span class=\"n\">args</span>, </span><span class=\"param\"><span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.simplify_literals": {"fullname": "sqlglot.optimizer.simplify.simplify_literals", "modulename": "sqlglot.optimizer.simplify", "qualname": "simplify_literals", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span>, </span><span class=\"param\"><span class=\"n\">root</span><span class=\"o\">=</span><span class=\"kc\">True</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.NULL_OK": {"fullname": "sqlglot.optimizer.simplify.NULL_OK", "modulename": "sqlglot.optimizer.simplify", "qualname": "NULL_OK", "kind": "variable", "doc": "<p></p>\n", "default_value": "(<class 'sqlglot.expressions.NullSafeEQ'>, <class 'sqlglot.expressions.NullSafeNEQ'>, <class 'sqlglot.expressions.PropertyEQ'>)"}, "sqlglot.optimizer.simplify.simplify_parens": {"fullname": "sqlglot.optimizer.simplify.simplify_parens", "modulename": "sqlglot.optimizer.simplify", "qualname": "simplify_parens", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.simplify_coalesce": {"fullname": "sqlglot.optimizer.simplify.simplify_coalesce", "modulename": "sqlglot.optimizer.simplify", "qualname": "simplify_coalesce", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.CONCATS": {"fullname": "sqlglot.optimizer.simplify.CONCATS", "modulename": "sqlglot.optimizer.simplify", "qualname": "CONCATS", "kind": "variable", "doc": "<p></p>\n", "default_value": "(<class 'sqlglot.expressions.Concat'>, <class 'sqlglot.expressions.DPipe'>)"}, "sqlglot.optimizer.simplify.simplify_concat": {"fullname": "sqlglot.optimizer.simplify.simplify_concat", "modulename": "sqlglot.optimizer.simplify", "qualname": "simplify_concat", "kind": "function", "doc": "<p>Reduces all groups that contain string literals by concatenating them.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.simplify_conditionals": {"fullname": "sqlglot.optimizer.simplify.simplify_conditionals", "modulename": "sqlglot.optimizer.simplify", "qualname": "simplify_conditionals", "kind": "function", "doc": "<p>Simplifies expressions like IF, CASE if their condition is statically known.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.simplify_startswith": {"fullname": "sqlglot.optimizer.simplify.simplify_startswith", "modulename": "sqlglot.optimizer.simplify", "qualname": "simplify_startswith", "kind": "function", "doc": "<p>Reduces a prefix check to either TRUE or FALSE if both the string and the\nprefix are statically known.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">from</span> <span class=\"nn\">sqlglot</span> <span class=\"kn\">import</span> <span class=\"n\">parse_one</span>\n<span class=\"gp\">>>> </span><span class=\"n\">simplify_startswith</span><span class=\"p\">(</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"STARTSWITH('foo', 'f')"</span><span class=\"p\">))</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'TRUE'</span>\n</code></pre>\n </div>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.DateRange": {"fullname": "sqlglot.optimizer.simplify.DateRange", "modulename": "sqlglot.optimizer.simplify", "qualname": "DateRange", "kind": "variable", "doc": "<p></p>\n", "default_value": "typing.Tuple[datetime.date, datetime.date]"}, "sqlglot.optimizer.simplify.DATETRUNC_BINARY_COMPARISONS": {"fullname": "sqlglot.optimizer.simplify.DATETRUNC_BINARY_COMPARISONS", "modulename": "sqlglot.optimizer.simplify", "qualname": "DATETRUNC_BINARY_COMPARISONS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[Type[sqlglot.expressions.Expression], Callable[[sqlglot.expressions.Expression, datetime.date, str, sqlglot.dialects.dialect.Dialect, sqlglot.expressions.DataType], Optional[sqlglot.expressions.Expression]]]", "default_value": "{<class 'sqlglot.expressions.LT'>: <function <lambda>>, <class 'sqlglot.expressions.GT'>: <function <lambda>>, <class 'sqlglot.expressions.LTE'>: <function <lambda>>, <class 'sqlglot.expressions.GTE'>: <function <lambda>>, <class 'sqlglot.expressions.EQ'>: <function _datetrunc_eq>, <class 'sqlglot.expressions.NEQ'>: <function _datetrunc_neq>}"}, "sqlglot.optimizer.simplify.DATETRUNC_COMPARISONS": {"fullname": "sqlglot.optimizer.simplify.DATETRUNC_COMPARISONS", "modulename": "sqlglot.optimizer.simplify", "qualname": "DATETRUNC_COMPARISONS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<class 'sqlglot.expressions.GTE'>, <class 'sqlglot.expressions.EQ'>, <class 'sqlglot.expressions.LTE'>, <class 'sqlglot.expressions.GT'>, <class 'sqlglot.expressions.NEQ'>, <class 'sqlglot.expressions.LT'>, <class 'sqlglot.expressions.In'>}"}, "sqlglot.optimizer.simplify.DATETRUNCS": {"fullname": "sqlglot.optimizer.simplify.DATETRUNCS", "modulename": "sqlglot.optimizer.simplify", "qualname": "DATETRUNCS", "kind": "variable", "doc": "<p></p>\n", "default_value": "(<class 'sqlglot.expressions.DateTrunc'>, <class 'sqlglot.expressions.TimestampTrunc'>)"}, "sqlglot.optimizer.simplify.simplify_datetrunc": {"fullname": "sqlglot.optimizer.simplify.simplify_datetrunc", "modulename": "sqlglot.optimizer.simplify", "qualname": "simplify_datetrunc", "kind": "function", "doc": "<p>Simplify expressions like <code>DATE_TRUNC('year', x) >= CAST('2021-01-01' AS DATE)</code></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span>, </span><span class=\"param\"><span class=\"o\">*</span><span class=\"n\">args</span>, </span><span class=\"param\"><span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.sort_comparison": {"fullname": "sqlglot.optimizer.simplify.sort_comparison", "modulename": "sqlglot.optimizer.simplify", "qualname": "sort_comparison", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.JOINS": {"fullname": "sqlglot.optimizer.simplify.JOINS", "modulename": "sqlglot.optimizer.simplify", "qualname": "JOINS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{('RIGHT', ''), ('RIGHT', 'OUTER'), ('', 'INNER'), ('', '')}"}, "sqlglot.optimizer.simplify.remove_where_true": {"fullname": "sqlglot.optimizer.simplify.remove_where_true", "modulename": "sqlglot.optimizer.simplify", "qualname": "remove_where_true", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.always_true": {"fullname": "sqlglot.optimizer.simplify.always_true", "modulename": "sqlglot.optimizer.simplify", "qualname": "always_true", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.always_false": {"fullname": "sqlglot.optimizer.simplify.always_false", "modulename": "sqlglot.optimizer.simplify", "qualname": "always_false", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.is_complement": {"fullname": "sqlglot.optimizer.simplify.is_complement", "modulename": "sqlglot.optimizer.simplify", "qualname": "is_complement", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">a</span>, </span><span class=\"param\"><span class=\"n\">b</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.is_false": {"fullname": "sqlglot.optimizer.simplify.is_false", "modulename": "sqlglot.optimizer.simplify", "qualname": "is_false", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">a</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">bool</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.is_null": {"fullname": "sqlglot.optimizer.simplify.is_null", "modulename": "sqlglot.optimizer.simplify", "qualname": "is_null", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">a</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">bool</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.eval_boolean": {"fullname": "sqlglot.optimizer.simplify.eval_boolean", "modulename": "sqlglot.optimizer.simplify", "qualname": "eval_boolean", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span>, </span><span class=\"param\"><span class=\"n\">a</span>, </span><span class=\"param\"><span class=\"n\">b</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.cast_as_date": {"fullname": "sqlglot.optimizer.simplify.cast_as_date", "modulename": "sqlglot.optimizer.simplify", "qualname": "cast_as_date", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">value</span><span class=\"p\">:</span> <span class=\"n\">Any</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">datetime</span><span class=\"o\">.</span><span class=\"n\">date</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.cast_as_datetime": {"fullname": "sqlglot.optimizer.simplify.cast_as_datetime", "modulename": "sqlglot.optimizer.simplify", "qualname": "cast_as_datetime", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">value</span><span class=\"p\">:</span> <span class=\"n\">Any</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">datetime</span><span class=\"o\">.</span><span class=\"n\">datetime</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.cast_value": {"fullname": "sqlglot.optimizer.simplify.cast_value", "modulename": "sqlglot.optimizer.simplify", "qualname": "cast_value", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">value</span><span class=\"p\">:</span> <span class=\"n\">Any</span>, </span><span class=\"param\"><span class=\"n\">to</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">datetime</span><span class=\"o\">.</span><span class=\"n\">date</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.extract_date": {"fullname": "sqlglot.optimizer.simplify.extract_date", "modulename": "sqlglot.optimizer.simplify", "qualname": "extract_date", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">cast</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">datetime</span><span class=\"o\">.</span><span class=\"n\">date</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.extract_interval": {"fullname": "sqlglot.optimizer.simplify.extract_interval", "modulename": "sqlglot.optimizer.simplify", "qualname": "extract_interval", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.extract_type": {"fullname": "sqlglot.optimizer.simplify.extract_type", "modulename": "sqlglot.optimizer.simplify", "qualname": "extract_type", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"o\">*</span><span class=\"n\">expressions</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.date_literal": {"fullname": "sqlglot.optimizer.simplify.date_literal", "modulename": "sqlglot.optimizer.simplify", "qualname": "date_literal", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">date</span>, </span><span class=\"param\"><span class=\"n\">target_type</span><span class=\"o\">=</span><span class=\"kc\">None</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.interval": {"fullname": "sqlglot.optimizer.simplify.interval", "modulename": "sqlglot.optimizer.simplify", "qualname": "interval", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">unit</span><span class=\"p\">:</span> <span class=\"nb\">str</span>, </span><span class=\"param\"><span class=\"n\">n</span><span class=\"p\">:</span> <span class=\"nb\">int</span> <span class=\"o\">=</span> <span class=\"mi\">1</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.date_floor": {"fullname": "sqlglot.optimizer.simplify.date_floor", "modulename": "sqlglot.optimizer.simplify", "qualname": "date_floor", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">d</span><span class=\"p\">:</span> <span class=\"n\">datetime</span><span class=\"o\">.</span><span class=\"n\">date</span>,</span><span class=\"param\">\t<span class=\"n\">unit</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span></span><span class=\"return-annotation\">) -> <span class=\"n\">datetime</span><span class=\"o\">.</span><span class=\"n\">date</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.date_ceil": {"fullname": "sqlglot.optimizer.simplify.date_ceil", "modulename": "sqlglot.optimizer.simplify", "qualname": "date_ceil", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">d</span><span class=\"p\">:</span> <span class=\"n\">datetime</span><span class=\"o\">.</span><span class=\"n\">date</span>,</span><span class=\"param\">\t<span class=\"n\">unit</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span></span><span class=\"return-annotation\">) -> <span class=\"n\">datetime</span><span class=\"o\">.</span><span class=\"n\">date</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.boolean_literal": {"fullname": "sqlglot.optimizer.simplify.boolean_literal", "modulename": "sqlglot.optimizer.simplify", "qualname": "boolean_literal", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">condition</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.gen": {"fullname": "sqlglot.optimizer.simplify.gen", "modulename": "sqlglot.optimizer.simplify", "qualname": "gen", "kind": "function", "doc": "<p>Simple pseudo sql generator for quickly generating sortable and uniq strings.</p>\n\n<p>Sorting and deduping sql is a necessary step for optimization. Calling the actual\ngenerator is expensive so we have a bare minimum sql generator here.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">Any</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen": {"fullname": "sqlglot.optimizer.simplify.Gen", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen", "kind": "class", "doc": "<p></p>\n"}, "sqlglot.optimizer.simplify.Gen.stack": {"fullname": "sqlglot.optimizer.simplify.Gen.stack", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.stack", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.optimizer.simplify.Gen.sqls": {"fullname": "sqlglot.optimizer.simplify.Gen.sqls", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.sqls", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.optimizer.simplify.Gen.gen": {"fullname": "sqlglot.optimizer.simplify.Gen.gen", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.gen", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.add_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.add_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.add_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Add</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.alias_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.alias_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.alias_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Alias</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.and_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.and_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.and_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">And</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.anonymous_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.anonymous_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.anonymous_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Anonymous</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.between_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.between_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.between_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Between</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.boolean_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.boolean_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.boolean_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Boolean</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.bracket_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.bracket_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.bracket_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Bracket</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.column_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.column_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.column_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Column</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.datatype_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.datatype_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.datatype_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.div_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.div_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.div_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Div</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.dot_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.dot_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.dot_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Dot</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.eq_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.eq_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.eq_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">EQ</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.from_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.from_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.from_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">From</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.gt_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.gt_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.gt_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">GT</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.gte_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.gte_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.gte_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">GTE</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.identifier_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.identifier_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.identifier_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Identifier</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.ilike_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.ilike_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.ilike_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">ILike</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.in_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.in_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.in_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">In</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.intdiv_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.intdiv_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.intdiv_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">IntDiv</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.is_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.is_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.is_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Is</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.like_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.like_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.like_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Like</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.literal_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.literal_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.literal_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Literal</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.lt_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.lt_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.lt_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">LT</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.lte_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.lte_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.lte_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">LTE</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.mod_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.mod_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.mod_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Mod</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.mul_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.mul_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.mul_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Mul</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.neg_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.neg_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.neg_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Neg</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.neq_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.neq_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.neq_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">NEQ</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.not_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.not_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.not_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Not</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.null_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.null_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.null_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Null</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.or_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.or_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.or_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Or</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.paren_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.paren_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.paren_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Paren</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.sub_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.sub_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.sub_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Sub</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.subquery_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.subquery_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.subquery_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Subquery</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.table_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.table_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.table_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Table</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.tablealias_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.tablealias_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.tablealias_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">TableAlias</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.simplify.Gen.var_sql": {"fullname": "sqlglot.optimizer.simplify.Gen.var_sql", "modulename": "sqlglot.optimizer.simplify", "qualname": "Gen.var_sql", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">e</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Var</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.optimizer.unnest_subqueries": {"fullname": "sqlglot.optimizer.unnest_subqueries", "modulename": "sqlglot.optimizer.unnest_subqueries", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.optimizer.unnest_subqueries.unnest_subqueries": {"fullname": "sqlglot.optimizer.unnest_subqueries.unnest_subqueries", "modulename": "sqlglot.optimizer.unnest_subqueries", "qualname": "unnest_subqueries", "kind": "function", "doc": "<p>Rewrite sqlglot AST to convert some predicates with subqueries into joins.</p>\n\n<p>Convert scalar subqueries into cross joins.\nConvert correlated or vectorized subqueries into a group by so it is not a many to many left join.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"gp\">>>> </span><span class=\"n\">expression</span> <span class=\"o\">=</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT * FROM x AS x WHERE (SELECT y.a AS a FROM y AS y WHERE x.a = y.a) = 1 "</span><span class=\"p\">)</span>\n<span class=\"gp\">>>> </span><span class=\"n\">unnest_subqueries</span><span class=\"p\">(</span><span class=\"n\">expression</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT * FROM x AS x LEFT JOIN (SELECT y.a AS a FROM y AS y WHERE TRUE GROUP BY y.a) AS _u_0 ON x.a = _u_0.a WHERE _u_0.a = 1'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression (sqlglot.Expression):</strong> expression to unnest</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>sqlglot.Expression: unnested expression</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.unnest_subqueries.unnest": {"fullname": "sqlglot.optimizer.unnest_subqueries.unnest", "modulename": "sqlglot.optimizer.unnest_subqueries", "qualname": "unnest", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">select</span>, </span><span class=\"param\"><span class=\"n\">parent_select</span>, </span><span class=\"param\"><span class=\"n\">next_alias_name</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.optimizer.unnest_subqueries.decorrelate": {"fullname": "sqlglot.optimizer.unnest_subqueries.decorrelate", "modulename": "sqlglot.optimizer.unnest_subqueries", "qualname": "decorrelate", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">select</span>, </span><span class=\"param\"><span class=\"n\">parent_select</span>, </span><span class=\"param\"><span class=\"n\">external_columns</span>, </span><span class=\"param\"><span class=\"n\">next_alias_name</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.parser": {"fullname": "sqlglot.parser", "modulename": "sqlglot.parser", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.parser.logger": {"fullname": "sqlglot.parser.logger", "modulename": "sqlglot.parser", "qualname": "logger", "kind": "variable", "doc": "<p></p>\n", "default_value": "<Logger sqlglot (WARNING)>"}, "sqlglot.parser.OPTIONS_TYPE": {"fullname": "sqlglot.parser.OPTIONS_TYPE", "modulename": "sqlglot.parser", "qualname": "OPTIONS_TYPE", "kind": "variable", "doc": "<p></p>\n", "default_value": "typing.Dict[str, typing.Sequence[typing.Union[typing.Sequence[str], str]]]"}, "sqlglot.parser.build_var_map": {"fullname": "sqlglot.parser.build_var_map", "modulename": "sqlglot.parser", "qualname": "build_var_map", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">args</span><span class=\"p\">:</span> <span class=\"n\">List</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">StarMap</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">VarMap</span>:</span></span>", "funcdef": "def"}, "sqlglot.parser.build_like": {"fullname": "sqlglot.parser.build_like", "modulename": "sqlglot.parser", "qualname": "build_like", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">args</span><span class=\"p\">:</span> <span class=\"n\">List</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Escape</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Like</span>:</span></span>", "funcdef": "def"}, "sqlglot.parser.binary_range_parser": {"fullname": "sqlglot.parser.binary_range_parser", "modulename": "sqlglot.parser", "qualname": "binary_range_parser", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expr_type</span><span class=\"p\">:</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parser</span><span class=\"o\">.</span><span class=\"n\">Parser</span><span class=\"p\">,</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]],</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]]</span>:</span></span>", "funcdef": "def"}, "sqlglot.parser.build_logarithm": {"fullname": "sqlglot.parser.build_logarithm", "modulename": "sqlglot.parser", "qualname": "build_logarithm", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">args</span><span class=\"p\">:</span> <span class=\"n\">List</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Func</span>:</span></span>", "funcdef": "def"}, "sqlglot.parser.build_hex": {"fullname": "sqlglot.parser.build_hex", "modulename": "sqlglot.parser", "qualname": "build_hex", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">args</span><span class=\"p\">:</span> <span class=\"n\">List</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Hex</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">LowerHex</span>:</span></span>", "funcdef": "def"}, "sqlglot.parser.build_lower": {"fullname": "sqlglot.parser.build_lower", "modulename": "sqlglot.parser", "qualname": "build_lower", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">args</span><span class=\"p\">:</span> <span class=\"n\">List</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Lower</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Hex</span>:</span></span>", "funcdef": "def"}, "sqlglot.parser.build_upper": {"fullname": "sqlglot.parser.build_upper", "modulename": "sqlglot.parser", "qualname": "build_upper", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">args</span><span class=\"p\">:</span> <span class=\"n\">List</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Upper</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Hex</span>:</span></span>", "funcdef": "def"}, "sqlglot.parser.build_extract_json_with_path": {"fullname": "sqlglot.parser.build_extract_json_with_path", "modulename": "sqlglot.parser", "qualname": "build_extract_json_with_path", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expr_type</span><span class=\"p\">:</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">E</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">List</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"o\">~</span><span class=\"n\">E</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.parser.build_mod": {"fullname": "sqlglot.parser.build_mod", "modulename": "sqlglot.parser", "qualname": "build_mod", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">args</span><span class=\"p\">:</span> <span class=\"n\">List</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Mod</span>:</span></span>", "funcdef": "def"}, "sqlglot.parser.Parser": {"fullname": "sqlglot.parser.Parser", "modulename": "sqlglot.parser", "qualname": "Parser", "kind": "class", "doc": "<p>Parser consumes a list of tokens produced by the Tokenizer and produces a parsed syntax tree.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>error_level:</strong> The desired error level.\nDefault: ErrorLevel.IMMEDIATE</li>\n<li><strong>error_message_context:</strong> The amount of context to capture from a query string when displaying\nthe error message (in number of characters).\nDefault: 100</li>\n<li><strong>max_errors:</strong> Maximum number of error messages to include in a raised ParseError.\nThis is only relevant if error_level is ErrorLevel.RAISE.\nDefault: 3</li>\n</ul>\n"}, "sqlglot.parser.Parser.__init__": {"fullname": "sqlglot.parser.Parser.__init__", "modulename": "sqlglot.parser", "qualname": "Parser.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">error_level</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">errors</span><span class=\"o\">.</span><span class=\"n\">ErrorLevel</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">error_message_context</span><span class=\"p\">:</span> <span class=\"nb\">int</span> <span class=\"o\">=</span> <span class=\"mi\">100</span>,</span><span class=\"param\">\t<span class=\"n\">max_errors</span><span class=\"p\">:</span> <span class=\"nb\">int</span> <span class=\"o\">=</span> <span class=\"mi\">3</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span>)</span>"}, "sqlglot.parser.Parser.FUNCTIONS": {"fullname": "sqlglot.parser.Parser.FUNCTIONS", "modulename": "sqlglot.parser", "qualname": "Parser.FUNCTIONS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, Callable]", "default_value": "{'ABS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Abs'>>, 'ADD_MONTHS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AddMonths'>>, 'ANONYMOUS_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnonymousAggFunc'>>, 'ANY_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.AnyValue'>>, 'APPROX_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_COUNT_DISTINCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxDistinct'>>, 'APPROX_QUANTILE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxQuantile'>>, 'APPROX_TOP_K': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ApproxTopK'>>, 'ARG_MAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARGMAX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'MAX_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMax'>>, 'ARG_MIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARGMIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'MIN_BY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArgMin'>>, 'ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Array'>>, 'ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAgg'>>, 'ARRAY_ALL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAll'>>, 'ARRAY_ANY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayAny'>>, 'ARRAY_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConcat'>>, 'ARRAY_CONSTRUCT_COMPACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayConstructCompact'>>, 'ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayContains'>>, 'FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_FILTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayFilter'>>, 'ARRAY_OVERLAPS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayOverlaps'>>, 'ARRAY_SIZE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySize'>>, 'ARRAY_SORT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySort'>>, 'ARRAY_SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArraySum'>>, 'ARRAY_TO_STRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_JOIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayToString'>>, 'ARRAY_UNION_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUnionAgg'>>, 'ARRAY_UNIQUE_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ArrayUniqueAgg'>>, 'AVG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Avg'>>, 'CASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Case'>>, 'CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cast'>>, 'CAST_TO_STR_TYPE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CastToStrType'>>, 'CBRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Cbrt'>>, 'CEIL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CEILING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ceil'>>, 'CHR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Chr'>>, 'COALESCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'IFNULL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'NVL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Coalesce'>>, 'COLLATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Collate'>>, 'COMBINED_AGG_FUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedAggFunc'>>, 'COMBINED_PARAMETERIZED_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CombinedParameterizedAgg'>>, 'CONCAT': <function Parser.<lambda>>, 'CONCAT_WS': <function Parser.<lambda>>, 'CONNECT_BY_ROOT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ConnectByRoot'>>, 'CONVERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Convert'>>, 'CORR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Corr'>>, 'COUNT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Count'>>, 'COUNT_IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COUNTIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CountIf'>>, 'COVAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarPop'>>, 'COVAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CovarSamp'>>, 'CURRENT_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDate'>>, 'CURRENT_DATETIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentDatetime'>>, 'CURRENT_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTime'>>, 'CURRENT_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentTimestamp'>>, 'CURRENT_USER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.CurrentUser'>>, 'DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Date'>>, 'DATE_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateAdd'>>, 'DATEDIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateDiff'>>, 'DATE_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateDiff'>>, 'DATE_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATEFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateFromParts'>>, 'DATE_STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateStrToDate'>>, 'DATE_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateSub'>>, 'DATE_TO_DATE_STR': <function Parser.<lambda>>, 'DATE_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateToDi'>>, 'DATE_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DateTrunc'>>, 'DATETIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeAdd'>>, 'DATETIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeDiff'>>, 'DATETIME_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeSub'>>, 'DATETIME_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DatetimeTrunc'>>, 'DAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Day'>>, 'DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAYOFMONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfMonth'>>, 'DAY_OF_WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAYOFWEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfWeek'>>, 'DAY_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DAYOFYEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DayOfYear'>>, 'DECODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Decode'>>, 'DI_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.DiToDate'>>, 'ENCODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Encode'>>, 'EXP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Exp'>>, 'EXPLODE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Explode'>>, 'EXPLODE_OUTER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ExplodeOuter'>>, 'EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Extract'>>, 'FIRST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.First'>>, 'FIRST_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FirstValue'>>, 'FLATTEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Flatten'>>, 'FLOOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Floor'>>, 'FROM_BASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase'>>, 'FROM_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.FromBase64'>>, 'GENERATE_DATE_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GenerateDateArray'>>, 'GENERATE_SERIES': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GenerateSeries'>>, 'GREATEST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Greatest'>>, 'GROUP_CONCAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.GroupConcat'>>, 'HEX': <function build_hex>, 'HLL': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Hll'>>, 'IF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'IIF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.If'>>, 'INITCAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Initcap'>>, 'IS_INF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'ISINF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsInf'>>, 'IS_NAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'ISNAN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.IsNan'>>, 'J_S_O_N_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArray'>>, 'J_S_O_N_ARRAY_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArrayAgg'>>, 'JSON_ARRAY_CONTAINS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONArrayContains'>>, 'JSONB_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONBExtract'>>, 'JSONB_EXTRACT_SCALAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONBExtractScalar'>>, 'JSON_EXTRACT': <function build_extract_json_with_path.<locals>._builder>, 'JSON_EXTRACT_SCALAR': <function build_extract_json_with_path.<locals>._builder>, 'JSON_FORMAT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONFormat'>>, 'J_S_O_N_OBJECT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONObject'>>, 'J_S_O_N_OBJECT_AGG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONObjectAgg'>>, 'J_S_O_N_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.JSONTable'>>, 'LAG': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lag'>>, 'LAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Last'>>, 'LAST_DAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastDay'>>, 'LAST_DAY_OF_MONTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastDay'>>, 'LAST_VALUE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LastValue'>>, 'LEAD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Lead'>>, 'LEAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Least'>>, 'LEFT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Left'>>, 'LENGTH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Length'>>, 'LEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Length'>>, 'LEVENSHTEIN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Levenshtein'>>, 'LN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Ln'>>, 'LOG': <function build_logarithm>, 'LOGICAL_AND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 'BOOL_AND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.LogicalAnd'>>, 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Func.from_arg_list of <class 'sqlglot.expressions.Quarter'>>, 'RAND': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'RANDOM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Rand'>>, 'RANDN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Randn'>>, 'RANGE_N': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RangeN'>>, 'READ_CSV': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ReadCSV'>>, 'REDUCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Reduce'>>, 'REGEXP_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpExtract'>>, 'REGEXP_I_LIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpILike'>>, 'REGEXP_LIKE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpLike'>>, 'REGEXP_REPLACE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.RegexpReplace'>>, 'REGEXP_SPLIT': <bound method 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'SPLIT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Split'>>, 'SQRT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sqrt'>>, 'STANDARD_HASH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StandardHash'>>, 'STAR_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StarMap'>>, 'STARTS_WITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STARTSWITH': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StartsWith'>>, 'STDDEV': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stddev'>>, 'STDDEV_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StddevPop'>>, 'STDDEV_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StddevSamp'>>, 'STR_POSITION': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrPosition'>>, 'STR_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToDate'>>, 'STR_TO_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToMap'>>, 'STR_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToTime'>>, 'STR_TO_UNIX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StrToUnix'>>, 'STRUCT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Struct'>>, 'STRUCT_EXTRACT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.StructExtract'>>, 'STUFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stuff'>>, 'INSERT': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Stuff'>>, 'SUBSTRING': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Substring'>>, 'SUM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Sum'>>, 'TIME_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeAdd'>>, 'TIME_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimeDiff'>>, 'TIME_FROM_PARTS': 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'TIMESTAMP_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampAdd'>>, 'TIMESTAMPDIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampDiff'>>, 'TIMESTAMP_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampDiff'>>, 'TIMESTAMP_FROM_PARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampFromParts'>>, 'TIMESTAMPFROMPARTS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampFromParts'>>, 'TIMESTAMP_SUB': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampSub'>>, 'TIMESTAMP_TRUNC': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TimestampTrunc'>>, 'TO_ARRAY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToArray'>>, 'TO_BASE64': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToBase64'>>, 'TO_CHAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToChar'>>, 'TO_DAYS': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToDays'>>, 'TO_MAP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToMap'>>, 'TO_NUMBER': <bound method Func.from_arg_list of <class 'sqlglot.expressions.ToNumber'>>, 'TRANSFORM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Transform'>>, 'TRIM': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Trim'>>, 'TRY': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Try'>>, 'TRY_CAST': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TryCast'>>, 'TS_OR_DI_TO_DI': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDiToDi'>>, 'TS_OR_DS_ADD': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsAdd'>>, 'TS_OR_DS_DIFF': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsDiff'>>, 'TS_OR_DS_TO_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToDate'>>, 'TS_OR_DS_TO_DATE_STR': <function Parser.<lambda>>, 'TS_OR_DS_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTime'>>, 'TS_OR_DS_TO_TIMESTAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.TsOrDsToTimestamp'>>, 'UNHEX': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Unhex'>>, 'UNIX_DATE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixDate'>>, 'UNIX_TO_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToStr'>>, 'UNIX_TO_TIME': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTime'>>, 'UNIX_TO_TIME_STR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.UnixToTimeStr'>>, 'UPPER': <function build_upper>, 'UCASE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Upper'>>, 'VAR_MAP': <function build_var_map>, 'VARIANCE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VAR_SAMP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Variance'>>, 'VARIANCE_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'VAR_POP': <bound method Func.from_arg_list of <class 'sqlglot.expressions.VariancePop'>>, 'WEEK': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Week'>>, 'WEEK_OF_YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.WeekOfYear'>>, 'WEEKOFYEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.WeekOfYear'>>, 'WHEN': <bound method Func.from_arg_list of <class 'sqlglot.expressions.When'>>, 'X_M_L_TABLE': <bound method Func.from_arg_list of <class 'sqlglot.expressions.XMLTable'>>, 'XOR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Xor'>>, 'YEAR': <bound method Func.from_arg_list of <class 'sqlglot.expressions.Year'>>, 'GLOB': <function Parser.<lambda>>, 'JSON_EXTRACT_PATH_TEXT': <function build_extract_json_with_path.<locals>._builder>, 'LIKE': <function build_like>, 'LOG2': <function Parser.<lambda>>, 'LOG10': <function Parser.<lambda>>, 'MOD': <function build_mod>, 'TO_HEX': <function build_hex>}"}, "sqlglot.parser.Parser.NO_PAREN_FUNCTIONS": {"fullname": "sqlglot.parser.Parser.NO_PAREN_FUNCTIONS", "modulename": "sqlglot.parser", "qualname": "Parser.NO_PAREN_FUNCTIONS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.CURRENT_DATE: 'CURRENT_DATE'>: <class 'sqlglot.expressions.CurrentDate'>, <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>: <class 'sqlglot.expressions.CurrentDate'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>: <class 'sqlglot.expressions.CurrentTime'>, <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>: <class 'sqlglot.expressions.CurrentTimestamp'>, <TokenType.CURRENT_USER: 'CURRENT_USER'>: <class 'sqlglot.expressions.CurrentUser'>}"}, "sqlglot.parser.Parser.STRUCT_TYPE_TOKENS": {"fullname": "sqlglot.parser.Parser.STRUCT_TYPE_TOKENS", "modulename": "sqlglot.parser", "qualname": "Parser.STRUCT_TYPE_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.NESTED: 'NESTED'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.STRUCT: 'STRUCT'>}"}, "sqlglot.parser.Parser.NESTED_TYPE_TOKENS": {"fullname": "sqlglot.parser.Parser.NESTED_TYPE_TOKENS", "modulename": "sqlglot.parser", "qualname": "Parser.NESTED_TYPE_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.NESTED: 'NESTED'>, <TokenType.ARRAY: 'ARRAY'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.NULLABLE: 'NULLABLE'>, <TokenType.STRUCT: 'STRUCT'>, <TokenType.MAP: 'MAP'>}"}, "sqlglot.parser.Parser.ENUM_TYPE_TOKENS": {"fullname": "sqlglot.parser.Parser.ENUM_TYPE_TOKENS", "modulename": "sqlglot.parser", "qualname": "Parser.ENUM_TYPE_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.ENUM: 'ENUM'>, <TokenType.ENUM8: 'ENUM8'>, <TokenType.ENUM16: 'ENUM16'>}"}, "sqlglot.parser.Parser.AGGREGATE_TYPE_TOKENS": {"fullname": "sqlglot.parser.Parser.AGGREGATE_TYPE_TOKENS", "modulename": "sqlglot.parser", "qualname": "Parser.AGGREGATE_TYPE_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.AGGREGATEFUNCTION: 'AGGREGATEFUNCTION'>, <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>}"}, "sqlglot.parser.Parser.TYPE_TOKENS": {"fullname": "sqlglot.parser.Parser.TYPE_TOKENS", "modulename": "sqlglot.parser", "qualname": "Parser.TYPE_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.MONEY: 'MONEY'>, <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, <TokenType.VARBINARY: 'VARBINARY'>, <TokenType.HSTORE: 'HSTORE'>, <TokenType.IPADDRESS: 'IPADDRESS'>, <TokenType.NUMRANGE: 'NUMRANGE'>, <TokenType.DATE32: 'DATE32'>, <TokenType.INT8RANGE: 'INT8RANGE'>, <TokenType.AGGREGATEFUNCTION: 'AGGREGATEFUNCTION'>, <TokenType.VARCHAR: 'VARCHAR'>, <TokenType.TIMETZ: 'TIMETZ'>, <TokenType.GEOMETRY: 'GEOMETRY'>, <TokenType.ENUM8: 'ENUM8'>, <TokenType.UINT256: 'UINT256'>, <TokenType.BIGINT: 'BIGINT'>, <TokenType.INT128: 'INT128'>, <TokenType.SMALLMONEY: 'SMALLMONEY'>, <TokenType.HLLSKETCH: 'HLLSKETCH'>, <TokenType.SMALLINT: 'SMALLINT'>, <TokenType.INT256: 'INT256'>, <TokenType.FLOAT: 'FLOAT'>, <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, <TokenType.NULL: 'NULL'>, <TokenType.NULLABLE: 'NULLABLE'>, <TokenType.TINYTEXT: 'TINYTEXT'>, <TokenType.DATE: 'DATE'>, <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <TokenType.BINARY: 'BINARY'>, <TokenType.ARRAY: 'ARRAY'>, <TokenType.SERIAL: 'SERIAL'>, <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, <TokenType.INTERVAL: 'INTERVAL'>, <TokenType.BPCHAR: 'BPCHAR'>, <TokenType.BIT: 'BIT'>, <TokenType.UINT: 'UINT'>, <TokenType.UUID: 'UUID'>, <TokenType.STRUCT: 'STRUCT'>, <TokenType.SUPER: 'SUPER'>, <TokenType.IMAGE: 'IMAGE'>, <TokenType.UBIGINT: 'UBIGINT'>, <TokenType.LONGBLOB: 'LONGBLOB'>, <TokenType.UMEDIUMINT: 'UMEDIUMINT'>, <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, <TokenType.UINT128: 'UINT128'>, <TokenType.MAP: 'MAP'>, <TokenType.IPV4: 'IPV4'>, <TokenType.USERDEFINED: 'USERDEFINED'>, <TokenType.NVARCHAR: 'NVARCHAR'>, <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, <TokenType.TIMESTAMP_MS: 'TIMESTAMP_MS'>, <TokenType.VARIANT: 'VARIANT'>, <TokenType.ENUM: 'ENUM'>, <TokenType.USMALLINT: 'USMALLINT'>, <TokenType.TIMESTAMP_S: 'TIMESTAMP_S'>, <TokenType.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>, <TokenType.TEXT: 'TEXT'>, <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, <TokenType.PSEUDO_TYPE: 'PSEUDO_TYPE'>, <TokenType.FIXEDSTRING: 'FIXEDSTRING'>, <TokenType.INT: 'INT'>, <TokenType.BIGSERIAL: 'BIGSERIAL'>, <TokenType.BOOLEAN: 'BOOLEAN'>, <TokenType.UNKNOWN: 'UNKNOWN'>, <TokenType.TSTZRANGE: 'TSTZRANGE'>, <TokenType.DATETIME64: 'DATETIME64'>, <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, <TokenType.DATETIME: 'DATETIME'>, <TokenType.MEDIUMINT: 'MEDIUMINT'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>, <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, <TokenType.XML: 'XML'>, <TokenType.JSON: 'JSON'>, <TokenType.UTINYINT: 'UTINYINT'>, <TokenType.TIME: 'TIME'>, <TokenType.UDECIMAL: 'UDECIMAL'>, <TokenType.NESTED: 'NESTED'>, <TokenType.ROWVERSION: 'ROWVERSION'>, <TokenType.TIMESTAMP_NS: 'TIMESTAMP_NS'>, <TokenType.INET: 'INET'>, <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>, <TokenType.NAME: 'NAME'>, <TokenType.ENUM16: 'ENUM16'>, <TokenType.YEAR: 'YEAR'>, <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, <TokenType.DOUBLE: 'DOUBLE'>, <TokenType.INT4RANGE: 'INT4RANGE'>, <TokenType.IPPREFIX: 'IPPREFIX'>, <TokenType.JSONB: 'JSONB'>, <TokenType.TDIGEST: 'TDIGEST'>, <TokenType.CHAR: 'CHAR'>, <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.DATERANGE: 'DATERANGE'>, <TokenType.TSRANGE: 'TSRANGE'>, <TokenType.DECIMAL: 'DECIMAL'>, <TokenType.NCHAR: 'NCHAR'>, <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, <TokenType.LONGTEXT: 'LONGTEXT'>, <TokenType.IPV6: 'IPV6'>, <TokenType.TINYINT: 'TINYINT'>, <TokenType.TINYBLOB: 'TINYBLOB'>}"}, "sqlglot.parser.Parser.SIGNED_TO_UNSIGNED_TYPE_TOKEN": {"fullname": "sqlglot.parser.Parser.SIGNED_TO_UNSIGNED_TYPE_TOKEN", "modulename": "sqlglot.parser", "qualname": "Parser.SIGNED_TO_UNSIGNED_TYPE_TOKEN", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.BIGINT: 'BIGINT'>: <TokenType.UBIGINT: 'UBIGINT'>, <TokenType.INT: 'INT'>: <TokenType.UINT: 'UINT'>, <TokenType.MEDIUMINT: 'MEDIUMINT'>: <TokenType.UMEDIUMINT: 'UMEDIUMINT'>, <TokenType.SMALLINT: 'SMALLINT'>: <TokenType.USMALLINT: 'USMALLINT'>, <TokenType.TINYINT: 'TINYINT'>: <TokenType.UTINYINT: 'UTINYINT'>, <TokenType.DECIMAL: 'DECIMAL'>: <TokenType.UDECIMAL: 'UDECIMAL'>}"}, "sqlglot.parser.Parser.SUBQUERY_PREDICATES": {"fullname": "sqlglot.parser.Parser.SUBQUERY_PREDICATES", "modulename": 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<TokenType.R_BRACE: 'R_BRACE'>, <TokenType.DASH: 'DASH'>, <TokenType.NOT: 'NOT'>, <TokenType.L_PAREN: 'L_PAREN'>, <TokenType.AMP: 'AMP'>, <TokenType.BACKSLASH: 'BACKSLASH'>, <TokenType.SELECT: 'SELECT'>, <TokenType.COMMA: 'COMMA'>, <TokenType.STAR: 'STAR'>, <TokenType.PLUS: 'PLUS'>, <TokenType.DOT: 'DOT'>, <TokenType.PIPE: 'PIPE'>, <TokenType.SLASH: 'SLASH'>, <TokenType.CARET: 'CARET'>, <TokenType.HASH: 'HASH'>, <TokenType.TILDA: 'TILDA'>}"}, "sqlglot.parser.Parser.DB_CREATABLES": {"fullname": "sqlglot.parser.Parser.DB_CREATABLES", "modulename": "sqlglot.parser", "qualname": "Parser.DB_CREATABLES", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.DATABASE: 'DATABASE'>, <TokenType.STORAGE_INTEGRATION: 'STORAGE_INTEGRATION'>, <TokenType.SCHEMA: 'SCHEMA'>, <TokenType.TAG: 'TAG'>, <TokenType.MODEL: 'MODEL'>, <TokenType.SEQUENCE: 'SEQUENCE'>, <TokenType.VIEW: 'VIEW'>, <TokenType.DICTIONARY: 'DICTIONARY'>, <TokenType.TABLE: 'TABLE'>}"}, 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'TDIGEST'>, <TokenType.CHAR: 'CHAR'>, <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.ROW: 'ROW'>, <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.TABLE: 'TABLE'>, <TokenType.DATERANGE: 'DATERANGE'>, <TokenType.TSRANGE: 'TSRANGE'>, <TokenType.ESCAPE: 'ESCAPE'>, <TokenType.PIVOT: 'PIVOT'>, <TokenType.DECIMAL: 'DECIMAL'>, <TokenType.NCHAR: 'NCHAR'>, <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, <TokenType.UPDATE: 'UPDATE'>, <TokenType.MODEL: 'MODEL'>, <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, <TokenType.SEQUENCE: 'SEQUENCE'>, <TokenType.LONGTEXT: 'LONGTEXT'>, <TokenType.DESCRIBE: 'DESCRIBE'>, <TokenType.IPV6: 'IPV6'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, <TokenType.TINYINT: 'TINYINT'>, <TokenType.TINYBLOB: 'TINYBLOB'>}"}, "sqlglot.parser.Parser.UPDATE_ALIAS_TOKENS": {"fullname": "sqlglot.parser.Parser.UPDATE_ALIAS_TOKENS", "modulename": "sqlglot.parser", 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'PARTITION'>, <TokenType.UINT256: 'UINT256'>, <TokenType.BIGINT: 'BIGINT'>, <TokenType.CACHE: 'CACHE'>, <TokenType.OPERATOR: 'OPERATOR'>, <TokenType.COLUMN: 'COLUMN'>, <TokenType.INT128: 'INT128'>, <TokenType.SMALLMONEY: 'SMALLMONEY'>, <TokenType.HLLSKETCH: 'HLLSKETCH'>, <TokenType.UNPIVOT: 'UNPIVOT'>, <TokenType.SMALLINT: 'SMALLINT'>, <TokenType.INT256: 'INT256'>, <TokenType.FLOAT: 'FLOAT'>, <TokenType.COMMIT: 'COMMIT'>, <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, <TokenType.EXISTS: 'EXISTS'>, <TokenType.NULL: 'NULL'>, <TokenType.RECURSIVE: 'RECURSIVE'>, <TokenType.NULLABLE: 'NULLABLE'>, <TokenType.REFRESH: 'REFRESH'>, <TokenType.TINYTEXT: 'TINYTEXT'>, <TokenType.SHOW: 'SHOW'>, <TokenType.DEFAULT: 'DEFAULT'>, <TokenType.DATE: 'DATE'>, <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <TokenType.MERGE: 'MERGE'>, <TokenType.FIRST: 'FIRST'>, <TokenType.BINARY: 'BINARY'>, <TokenType.ARRAY: 'ARRAY'>, <TokenType.SERIAL: 'SERIAL'>, <TokenType.EXECUTE: 'EXECUTE'>, <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, <TokenType.INTERVAL: 'INTERVAL'>, <TokenType.PRAGMA: 'PRAGMA'>, <TokenType.STORAGE_INTEGRATION: 'STORAGE_INTEGRATION'>, <TokenType.BPCHAR: 'BPCHAR'>, <TokenType.BIT: 'BIT'>, <TokenType.UINT: 'UINT'>, <TokenType.UUID: 'UUID'>, <TokenType.STRUCT: 'STRUCT'>, <TokenType.FALSE: 'FALSE'>, <TokenType.FUNCTION: 'FUNCTION'>, <TokenType.TOP: 'TOP'>, <TokenType.SUPER: 'SUPER'>, <TokenType.CASE: 'CASE'>, <TokenType.IMAGE: 'IMAGE'>, <TokenType.UBIGINT: 'UBIGINT'>, <TokenType.LONGBLOB: 'LONGBLOB'>, <TokenType.ROLLUP: 'ROLLUP'>, <TokenType.VAR: 'VAR'>, <TokenType.COMMAND: 'COMMAND'>, <TokenType.LOAD: 'LOAD'>, <TokenType.TRUNCATE: 'TRUNCATE'>, <TokenType.KEEP: 'KEEP'>, <TokenType.UMEDIUMINT: 'UMEDIUMINT'>, <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, <TokenType.UINT128: 'UINT128'>, <TokenType.END: 'END'>, <TokenType.MAP: 'MAP'>, <TokenType.IPV4: 'IPV4'>, <TokenType.USERDEFINED: 'USERDEFINED'>, <TokenType.REFERENCES: 'REFERENCES'>, <TokenType.REPLACE: 'REPLACE'>, <TokenType.RANGE: 'RANGE'>, <TokenType.NVARCHAR: 'NVARCHAR'>, <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, <TokenType.TRUE: 'TRUE'>, <TokenType.TIMESTAMP_MS: 'TIMESTAMP_MS'>, <TokenType.VARIANT: 'VARIANT'>, <TokenType.ENUM: 'ENUM'>, <TokenType.USE: 'USE'>, <TokenType.USMALLINT: 'USMALLINT'>, <TokenType.OVERLAPS: 'OVERLAPS'>, <TokenType.TIMESTAMP_S: 'TIMESTAMP_S'>, <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, <TokenType.UNIQUE: 'UNIQUE'>, <TokenType.ORDINALITY: 'ORDINALITY'>, <TokenType.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>, <TokenType.TEXT: 'TEXT'>, <TokenType.DATABASE: 'DATABASE'>, <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, <TokenType.PSEUDO_TYPE: 'PSEUDO_TYPE'>, <TokenType.FIXEDSTRING: 'FIXEDSTRING'>, <TokenType.NEXT: 'NEXT'>, <TokenType.INT: 'INT'>, <TokenType.BIGSERIAL: 'BIGSERIAL'>, <TokenType.BOOLEAN: 'BOOLEAN'>, <TokenType.IS: 'IS'>, <TokenType.CONSTRAINT: 'CONSTRAINT'>, <TokenType.FINAL: 'FINAL'>, <TokenType.UNKNOWN: 'UNKNOWN'>, <TokenType.SETTINGS: 'SETTINGS'>, <TokenType.ROWS: 'ROWS'>, <TokenType.TSTZRANGE: 'TSTZRANGE'>, <TokenType.DATETIME64: 'DATETIME64'>, <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, <TokenType.DATETIME: 'DATETIME'>, <TokenType.MEDIUMINT: 'MEDIUMINT'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>, <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, <TokenType.XML: 'XML'>, <TokenType.JSON: 'JSON'>, <TokenType.UTINYINT: 'UTINYINT'>, <TokenType.DELETE: 'DELETE'>, <TokenType.TIME: 'TIME'>, <TokenType.UDECIMAL: 'UDECIMAL'>, <TokenType.NESTED: 'NESTED'>, <TokenType.DESC: 'DESC'>, <TokenType.ROWVERSION: 'ROWVERSION'>, <TokenType.TIMESTAMP_NS: 'TIMESTAMP_NS'>, <TokenType.ANY: 'ANY'>, <TokenType.DIV: 'DIV'>, <TokenType.DICTIONARY: 'DICTIONARY'>, <TokenType.INET: 'INET'>, <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, <TokenType.COMMENT: 'COMMENT'>, <TokenType.CURRENT_USER: 'CURRENT_USER'>, <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>, <TokenType.ALL: 'ALL'>, <TokenType.NAME: 'NAME'>, <TokenType.SOME: 'SOME'>, <TokenType.ENUM16: 'ENUM16'>, <TokenType.YEAR: 'YEAR'>, <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, <TokenType.DOUBLE: 'DOUBLE'>, <TokenType.INT4RANGE: 'INT4RANGE'>, <TokenType.FORMAT: 'FORMAT'>, <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, <TokenType.IPPREFIX: 'IPPREFIX'>, <TokenType.OVERWRITE: 'OVERWRITE'>, <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>, <TokenType.COLLATE: 'COLLATE'>, <TokenType.FILTER: 'FILTER'>, <TokenType.JSONB: 'JSONB'>, <TokenType.TDIGEST: 'TDIGEST'>, <TokenType.CHAR: 'CHAR'>, <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.ROW: 'ROW'>, <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.TABLE: 'TABLE'>, <TokenType.DATERANGE: 'DATERANGE'>, <TokenType.TSRANGE: 'TSRANGE'>, <TokenType.ESCAPE: 'ESCAPE'>, <TokenType.PIVOT: 'PIVOT'>, <TokenType.DECIMAL: 'DECIMAL'>, <TokenType.NCHAR: 'NCHAR'>, <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, <TokenType.UPDATE: 'UPDATE'>, <TokenType.MODEL: 'MODEL'>, <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, <TokenType.SEQUENCE: 'SEQUENCE'>, <TokenType.LONGTEXT: 'LONGTEXT'>, <TokenType.DESCRIBE: 'DESCRIBE'>, <TokenType.IPV6: 'IPV6'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, <TokenType.TINYINT: 'TINYINT'>, <TokenType.TINYBLOB: 'TINYBLOB'>}"}, "sqlglot.parser.Parser.TRIM_TYPES": {"fullname": "sqlglot.parser.Parser.TRIM_TYPES", "modulename": "sqlglot.parser", "qualname": "Parser.TRIM_TYPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'TRAILING', 'LEADING', 'BOTH'}"}, "sqlglot.parser.Parser.FUNC_TOKENS": {"fullname": "sqlglot.parser.Parser.FUNC_TOKENS", "modulename": "sqlglot.parser", "qualname": "Parser.FUNC_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.MONEY: 'MONEY'>, <TokenType.PRIMARY_KEY: 'PRIMARY_KEY'>, <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, <TokenType.IDENTIFIER: 'IDENTIFIER'>, <TokenType.VARBINARY: 'VARBINARY'>, <TokenType.HSTORE: 'HSTORE'>, <TokenType.IPADDRESS: 'IPADDRESS'>, <TokenType.ISNULL: 'ISNULL'>, <TokenType.NUMRANGE: 'NUMRANGE'>, <TokenType.DATE32: 'DATE32'>, <TokenType.INT8RANGE: 'INT8RANGE'>, <TokenType.AGGREGATEFUNCTION: 'AGGREGATEFUNCTION'>, <TokenType.VARCHAR: 'VARCHAR'>, <TokenType.TIMETZ: 'TIMETZ'>, <TokenType.GEOMETRY: 'GEOMETRY'>, <TokenType.ENUM8: 'ENUM8'>, <TokenType.INDEX: 'INDEX'>, <TokenType.UINT256: 'UINT256'>, <TokenType.BIGINT: 'BIGINT'>, <TokenType.INT128: 'INT128'>, <TokenType.SMALLMONEY: 'SMALLMONEY'>, <TokenType.HLLSKETCH: 'HLLSKETCH'>, <TokenType.RLIKE: 'RLIKE'>, <TokenType.SMALLINT: 'SMALLINT'>, <TokenType.INT256: 'INT256'>, <TokenType.GLOB: 'GLOB'>, <TokenType.FLOAT: 'FLOAT'>, <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, <TokenType.UNNEST: 'UNNEST'>, <TokenType.EXISTS: 'EXISTS'>, <TokenType.NULL: 'NULL'>, <TokenType.XOR: 'XOR'>, <TokenType.NULLABLE: 'NULLABLE'>, <TokenType.TINYTEXT: 'TINYTEXT'>, <TokenType.DATE: 'DATE'>, <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <TokenType.MERGE: 'MERGE'>, <TokenType.FIRST: 'FIRST'>, <TokenType.BINARY: 'BINARY'>, <TokenType.ARRAY: 'ARRAY'>, <TokenType.SERIAL: 'SERIAL'>, <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, <TokenType.INTERVAL: 'INTERVAL'>, <TokenType.WINDOW: 'WINDOW'>, <TokenType.RIGHT: 'RIGHT'>, <TokenType.BPCHAR: 'BPCHAR'>, <TokenType.BIT: 'BIT'>, <TokenType.UINT: 'UINT'>, <TokenType.ILIKE: 'ILIKE'>, <TokenType.UUID: 'UUID'>, <TokenType.STRUCT: 'STRUCT'>, <TokenType.LEFT: 'LEFT'>, <TokenType.SUPER: 'SUPER'>, <TokenType.IMAGE: 'IMAGE'>, <TokenType.UBIGINT: 'UBIGINT'>, <TokenType.LONGBLOB: 'LONGBLOB'>, <TokenType.VAR: 'VAR'>, <TokenType.COMMAND: 'COMMAND'>, <TokenType.TRUNCATE: 'TRUNCATE'>, <TokenType.UMEDIUMINT: 'UMEDIUMINT'>, <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, <TokenType.UINT128: 'UINT128'>, <TokenType.MAP: 'MAP'>, <TokenType.IPV4: 'IPV4'>, <TokenType.USERDEFINED: 'USERDEFINED'>, <TokenType.REPLACE: 'REPLACE'>, <TokenType.RANGE: 'RANGE'>, <TokenType.NVARCHAR: 'NVARCHAR'>, <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, <TokenType.TIMESTAMP_MS: 'TIMESTAMP_MS'>, <TokenType.VARIANT: 'VARIANT'>, <TokenType.ENUM: 'ENUM'>, <TokenType.USMALLINT: 'USMALLINT'>, <TokenType.TIMESTAMP_S: 'TIMESTAMP_S'>, <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, <TokenType.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>, <TokenType.TEXT: 'TEXT'>, <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, <TokenType.PSEUDO_TYPE: 'PSEUDO_TYPE'>, <TokenType.FIXEDSTRING: 'FIXEDSTRING'>, <TokenType.INT: 'INT'>, <TokenType.BIGSERIAL: 'BIGSERIAL'>, <TokenType.BOOLEAN: 'BOOLEAN'>, <TokenType.UNKNOWN: 'UNKNOWN'>, <TokenType.TSTZRANGE: 'TSTZRANGE'>, <TokenType.DATETIME64: 'DATETIME64'>, <TokenType.DATETIME: 'DATETIME'>, <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, <TokenType.MEDIUMINT: 'MEDIUMINT'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>, <TokenType.LIKE: 'LIKE'>, <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, <TokenType.XML: 'XML'>, <TokenType.JSON: 'JSON'>, <TokenType.UTINYINT: 'UTINYINT'>, <TokenType.TIME: 'TIME'>, <TokenType.UDECIMAL: 'UDECIMAL'>, <TokenType.NESTED: 'NESTED'>, <TokenType.ROWVERSION: 'ROWVERSION'>, <TokenType.OFFSET: 'OFFSET'>, <TokenType.INSERT: 'INSERT'>, <TokenType.TIMESTAMP_NS: 'TIMESTAMP_NS'>, <TokenType.ANY: 'ANY'>, <TokenType.INET: 'INET'>, <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, <TokenType.CURRENT_USER: 'CURRENT_USER'>, <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>, <TokenType.ALL: 'ALL'>, <TokenType.NAME: 'NAME'>, <TokenType.SOME: 'SOME'>, <TokenType.ENUM16: 'ENUM16'>, <TokenType.YEAR: 'YEAR'>, <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, <TokenType.DOUBLE: 'DOUBLE'>, <TokenType.INT4RANGE: 'INT4RANGE'>, <TokenType.FORMAT: 'FORMAT'>, <TokenType.IPPREFIX: 'IPPREFIX'>, <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>, <TokenType.COLLATE: 'COLLATE'>, <TokenType.FILTER: 'FILTER'>, <TokenType.JSONB: 'JSONB'>, <TokenType.TDIGEST: 'TDIGEST'>, <TokenType.CHAR: 'CHAR'>, <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.ROW: 'ROW'>, <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.TABLE: 'TABLE'>, <TokenType.DATERANGE: 'DATERANGE'>, <TokenType.TSRANGE: 'TSRANGE'>, <TokenType.DECIMAL: 'DECIMAL'>, <TokenType.NCHAR: 'NCHAR'>, <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, <TokenType.SEQUENCE: 'SEQUENCE'>, <TokenType.LONGTEXT: 'LONGTEXT'>, <TokenType.IPV6: 'IPV6'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, <TokenType.TINYINT: 'TINYINT'>, <TokenType.TINYBLOB: 'TINYBLOB'>}"}, "sqlglot.parser.Parser.CONJUNCTION": {"fullname": "sqlglot.parser.Parser.CONJUNCTION", "modulename": "sqlglot.parser", "qualname": "Parser.CONJUNCTION", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.AND: 'AND'>: <class 'sqlglot.expressions.And'>, <TokenType.OR: 'OR'>: <class 'sqlglot.expressions.Or'>}"}, "sqlglot.parser.Parser.EQUALITY": {"fullname": "sqlglot.parser.Parser.EQUALITY", "modulename": "sqlglot.parser", "qualname": "Parser.EQUALITY", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.EQ: 'EQ'>: <class 'sqlglot.expressions.EQ'>, <TokenType.NEQ: 'NEQ'>: <class 'sqlglot.expressions.NEQ'>, <TokenType.NULLSAFE_EQ: 'NULLSAFE_EQ'>: <class 'sqlglot.expressions.NullSafeEQ'>}"}, "sqlglot.parser.Parser.COMPARISON": {"fullname": "sqlglot.parser.Parser.COMPARISON", "modulename": "sqlglot.parser", "qualname": "Parser.COMPARISON", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.GT: 'GT'>: <class 'sqlglot.expressions.GT'>, <TokenType.GTE: 'GTE'>: <class 'sqlglot.expressions.GTE'>, <TokenType.LT: 'LT'>: <class 'sqlglot.expressions.LT'>, <TokenType.LTE: 'LTE'>: <class 'sqlglot.expressions.LTE'>}"}, "sqlglot.parser.Parser.BITWISE": {"fullname": "sqlglot.parser.Parser.BITWISE", "modulename": "sqlglot.parser", "qualname": "Parser.BITWISE", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.AMP: 'AMP'>: <class 'sqlglot.expressions.BitwiseAnd'>, <TokenType.CARET: 'CARET'>: <class 'sqlglot.expressions.BitwiseXor'>, <TokenType.PIPE: 'PIPE'>: <class 'sqlglot.expressions.BitwiseOr'>}"}, "sqlglot.parser.Parser.TERM": {"fullname": "sqlglot.parser.Parser.TERM", "modulename": "sqlglot.parser", "qualname": "Parser.TERM", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.DASH: 'DASH'>: <class 'sqlglot.expressions.Sub'>, <TokenType.PLUS: 'PLUS'>: <class 'sqlglot.expressions.Add'>, <TokenType.MOD: 'MOD'>: <class 'sqlglot.expressions.Mod'>, <TokenType.COLLATE: 'COLLATE'>: <class 'sqlglot.expressions.Collate'>}"}, "sqlglot.parser.Parser.FACTOR": {"fullname": "sqlglot.parser.Parser.FACTOR", "modulename": "sqlglot.parser", "qualname": "Parser.FACTOR", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.DIV: 'DIV'>: <class 'sqlglot.expressions.IntDiv'>, <TokenType.LR_ARROW: 'LR_ARROW'>: <class 'sqlglot.expressions.Distance'>, <TokenType.SLASH: 'SLASH'>: <class 'sqlglot.expressions.Div'>, <TokenType.STAR: 'STAR'>: <class 'sqlglot.expressions.Mul'>}"}, "sqlglot.parser.Parser.EXPONENT": {"fullname": "sqlglot.parser.Parser.EXPONENT", "modulename": "sqlglot.parser", "qualname": "Parser.EXPONENT", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[sqlglot.tokens.TokenType, Type[sqlglot.expressions.Expression]]", "default_value": "{}"}, "sqlglot.parser.Parser.TIMES": {"fullname": "sqlglot.parser.Parser.TIMES", "modulename": "sqlglot.parser", "qualname": "Parser.TIMES", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.TIME: 'TIME'>, <TokenType.TIMETZ: 'TIMETZ'>}"}, "sqlglot.parser.Parser.TIMESTAMPS": {"fullname": "sqlglot.parser.Parser.TIMESTAMPS", "modulename": "sqlglot.parser", "qualname": "Parser.TIMESTAMPS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.TIME: 'TIME'>, <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.TIMETZ: 'TIMETZ'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>}"}, 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'INT'>, <TokenType.BIGSERIAL: 'BIGSERIAL'>, <TokenType.BOOLEAN: 'BOOLEAN'>, <TokenType.IS: 'IS'>, <TokenType.CONSTRAINT: 'CONSTRAINT'>, <TokenType.FINAL: 'FINAL'>, <TokenType.UNKNOWN: 'UNKNOWN'>, <TokenType.SETTINGS: 'SETTINGS'>, <TokenType.TSTZRANGE: 'TSTZRANGE'>, <TokenType.DATETIME64: 'DATETIME64'>, <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, <TokenType.DATETIME: 'DATETIME'>, <TokenType.MEDIUMINT: 'MEDIUMINT'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>, <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, <TokenType.XML: 'XML'>, <TokenType.SEMI: 'SEMI'>, <TokenType.JSON: 'JSON'>, <TokenType.DELETE: 'DELETE'>, <TokenType.UTINYINT: 'UTINYINT'>, <TokenType.TIME: 'TIME'>, <TokenType.UDECIMAL: 'UDECIMAL'>, <TokenType.NESTED: 'NESTED'>, <TokenType.DESC: 'DESC'>, <TokenType.ROWVERSION: 'ROWVERSION'>, <TokenType.OFFSET: 'OFFSET'>, <TokenType.TIMESTAMP_NS: 'TIMESTAMP_NS'>, <TokenType.ANY: 'ANY'>, <TokenType.DIV: 'DIV'>, <TokenType.DICTIONARY: 'DICTIONARY'>, <TokenType.INET: 'INET'>, <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, <TokenType.COMMENT: 'COMMENT'>, <TokenType.CURRENT_USER: 'CURRENT_USER'>, <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>, <TokenType.ALL: 'ALL'>, <TokenType.NAME: 'NAME'>, <TokenType.SOME: 'SOME'>, <TokenType.ENUM16: 'ENUM16'>, <TokenType.YEAR: 'YEAR'>, <TokenType.FULL: 'FULL'>, <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, <TokenType.TINYBLOB: 'TINYBLOB'>, <TokenType.DOUBLE: 'DOUBLE'>, <TokenType.INT4RANGE: 'INT4RANGE'>, <TokenType.FORMAT: 'FORMAT'>, <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, <TokenType.IPPREFIX: 'IPPREFIX'>, <TokenType.OVERWRITE: 'OVERWRITE'>, <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>, <TokenType.COLLATE: 'COLLATE'>, <TokenType.FILTER: 'FILTER'>, <TokenType.JSONB: 'JSONB'>, <TokenType.TDIGEST: 'TDIGEST'>, <TokenType.CHAR: 'CHAR'>, <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.TABLE: 'TABLE'>, <TokenType.DATERANGE: 'DATERANGE'>, <TokenType.NATURAL: 'NATURAL'>, <TokenType.TSRANGE: 'TSRANGE'>, <TokenType.ESCAPE: 'ESCAPE'>, <TokenType.PIVOT: 'PIVOT'>, <TokenType.DECIMAL: 'DECIMAL'>, <TokenType.NCHAR: 'NCHAR'>, <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, <TokenType.UPDATE: 'UPDATE'>, <TokenType.MODEL: 'MODEL'>, <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, <TokenType.SEQUENCE: 'SEQUENCE'>, <TokenType.LONGTEXT: 'LONGTEXT'>, <TokenType.DESCRIBE: 'DESCRIBE'>, <TokenType.IPV6: 'IPV6'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, <TokenType.TINYINT: 'TINYINT'>, <TokenType.ANTI: 'ANTI'>}"}, "sqlglot.parser.Parser.ADD_CONSTRAINT_TOKENS": {"fullname": "sqlglot.parser.Parser.ADD_CONSTRAINT_TOKENS", "modulename": "sqlglot.parser", "qualname": "Parser.ADD_CONSTRAINT_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.CONSTRAINT: 'CONSTRAINT'>, <TokenType.PRIMARY_KEY: 'PRIMARY_KEY'>, <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>}"}, "sqlglot.parser.Parser.DISTINCT_TOKENS": {"fullname": "sqlglot.parser.Parser.DISTINCT_TOKENS", "modulename": "sqlglot.parser", "qualname": "Parser.DISTINCT_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.DISTINCT: 'DISTINCT'>}"}, "sqlglot.parser.Parser.NULL_TOKENS": {"fullname": "sqlglot.parser.Parser.NULL_TOKENS", "modulename": "sqlglot.parser", "qualname": "Parser.NULL_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.NULL: 'NULL'>}"}, "sqlglot.parser.Parser.UNNEST_OFFSET_ALIAS_TOKENS": {"fullname": "sqlglot.parser.Parser.UNNEST_OFFSET_ALIAS_TOKENS", "modulename": "sqlglot.parser", "qualname": "Parser.UNNEST_OFFSET_ALIAS_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.KILL: 'KILL'>, <TokenType.MONEY: 'MONEY'>, <TokenType.COPY: 'COPY'>, <TokenType.PERCENT: 'PERCENT'>, <TokenType.TAG: 'TAG'>, <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, <TokenType.VOLATILE: 'VOLATILE'>, <TokenType.IDENTIFIER: 'IDENTIFIER'>, <TokenType.VARBINARY: 'VARBINARY'>, <TokenType.HSTORE: 'HSTORE'>, <TokenType.ASC: 'ASC'>, <TokenType.IPADDRESS: 'IPADDRESS'>, <TokenType.ISNULL: 'ISNULL'>, <TokenType.TEMPORARY: 'TEMPORARY'>, <TokenType.PROCEDURE: 'PROCEDURE'>, <TokenType.SCHEMA: 'SCHEMA'>, <TokenType.NUMRANGE: 'NUMRANGE'>, <TokenType.DATE32: 'DATE32'>, <TokenType.INT8RANGE: 'INT8RANGE'>, <TokenType.AGGREGATEFUNCTION: 'AGGREGATEFUNCTION'>, <TokenType.VIEW: 'VIEW'>, <TokenType.VARCHAR: 'VARCHAR'>, <TokenType.TIMETZ: 'TIMETZ'>, <TokenType.GEOMETRY: 'GEOMETRY'>, <TokenType.BEGIN: 'BEGIN'>, <TokenType.ENUM8: 'ENUM8'>, <TokenType.INDEX: 'INDEX'>, <TokenType.PARTITION: 'PARTITION'>, <TokenType.UINT256: 'UINT256'>, <TokenType.BIGINT: 'BIGINT'>, <TokenType.CACHE: 'CACHE'>, <TokenType.OPERATOR: 'OPERATOR'>, <TokenType.COLUMN: 'COLUMN'>, <TokenType.INT128: 'INT128'>, <TokenType.SMALLMONEY: 'SMALLMONEY'>, <TokenType.HLLSKETCH: 'HLLSKETCH'>, <TokenType.UNPIVOT: 'UNPIVOT'>, <TokenType.SMALLINT: 'SMALLINT'>, <TokenType.INT256: 'INT256'>, <TokenType.FLOAT: 'FLOAT'>, <TokenType.COMMIT: 'COMMIT'>, <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, <TokenType.EXISTS: 'EXISTS'>, <TokenType.NULL: 'NULL'>, <TokenType.RECURSIVE: 'RECURSIVE'>, <TokenType.SET: 'SET'>, <TokenType.NULLABLE: 'NULLABLE'>, <TokenType.REFRESH: 'REFRESH'>, <TokenType.TINYTEXT: 'TINYTEXT'>, <TokenType.SHOW: 'SHOW'>, <TokenType.DEFAULT: 'DEFAULT'>, <TokenType.DATE: 'DATE'>, <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, <TokenType.MERGE: 'MERGE'>, <TokenType.FIRST: 'FIRST'>, <TokenType.BINARY: 'BINARY'>, <TokenType.ARRAY: 'ARRAY'>, <TokenType.SERIAL: 'SERIAL'>, <TokenType.EXECUTE: 'EXECUTE'>, <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, <TokenType.INTERVAL: 'INTERVAL'>, <TokenType.PRAGMA: 'PRAGMA'>, <TokenType.APPLY: 'APPLY'>, <TokenType.STORAGE_INTEGRATION: 'STORAGE_INTEGRATION'>, <TokenType.ASOF: 'ASOF'>, <TokenType.WINDOW: 'WINDOW'>, <TokenType.RIGHT: 'RIGHT'>, <TokenType.BPCHAR: 'BPCHAR'>, <TokenType.BIT: 'BIT'>, <TokenType.UINT: 'UINT'>, <TokenType.UUID: 'UUID'>, <TokenType.STRUCT: 'STRUCT'>, <TokenType.FALSE: 'FALSE'>, <TokenType.LEFT: 'LEFT'>, <TokenType.TOP: 'TOP'>, <TokenType.FUNCTION: 'FUNCTION'>, <TokenType.SUPER: 'SUPER'>, <TokenType.CASE: 'CASE'>, <TokenType.IMAGE: 'IMAGE'>, <TokenType.UBIGINT: 'UBIGINT'>, <TokenType.LONGBLOB: 'LONGBLOB'>, <TokenType.ROLLUP: 'ROLLUP'>, <TokenType.VAR: 'VAR'>, <TokenType.COMMAND: 'COMMAND'>, <TokenType.LOAD: 'LOAD'>, <TokenType.TRUNCATE: 'TRUNCATE'>, <TokenType.KEEP: 'KEEP'>, <TokenType.UMEDIUMINT: 'UMEDIUMINT'>, <TokenType.OBJECT_IDENTIFIER: 'OBJECT_IDENTIFIER'>, <TokenType.UINT128: 'UINT128'>, <TokenType.END: 'END'>, <TokenType.MAP: 'MAP'>, <TokenType.IPV4: 'IPV4'>, <TokenType.USERDEFINED: 'USERDEFINED'>, <TokenType.REFERENCES: 'REFERENCES'>, <TokenType.REPLACE: 'REPLACE'>, <TokenType.RANGE: 'RANGE'>, <TokenType.NVARCHAR: 'NVARCHAR'>, <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, <TokenType.TRUE: 'TRUE'>, <TokenType.TIMESTAMP_MS: 'TIMESTAMP_MS'>, <TokenType.VARIANT: 'VARIANT'>, <TokenType.ENUM: 'ENUM'>, <TokenType.USE: 'USE'>, <TokenType.USMALLINT: 'USMALLINT'>, <TokenType.OVERLAPS: 'OVERLAPS'>, <TokenType.TIMESTAMP_S: 'TIMESTAMP_S'>, <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, <TokenType.UNIQUE: 'UNIQUE'>, <TokenType.ORDINALITY: 'ORDINALITY'>, <TokenType.UNIQUEIDENTIFIER: 'UNIQUEIDENTIFIER'>, <TokenType.TEXT: 'TEXT'>, <TokenType.DATABASE: 'DATABASE'>, <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, <TokenType.PSEUDO_TYPE: 'PSEUDO_TYPE'>, <TokenType.FIXEDSTRING: 'FIXEDSTRING'>, <TokenType.NEXT: 'NEXT'>, <TokenType.INT: 'INT'>, <TokenType.BIGSERIAL: 'BIGSERIAL'>, <TokenType.BOOLEAN: 'BOOLEAN'>, <TokenType.IS: 'IS'>, <TokenType.CONSTRAINT: 'CONSTRAINT'>, <TokenType.FINAL: 'FINAL'>, <TokenType.UNKNOWN: 'UNKNOWN'>, <TokenType.SETTINGS: 'SETTINGS'>, <TokenType.ROWS: 'ROWS'>, <TokenType.TSTZRANGE: 'TSTZRANGE'>, <TokenType.DATETIME64: 'DATETIME64'>, <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, <TokenType.DATETIME: 'DATETIME'>, <TokenType.MEDIUMINT: 'MEDIUMINT'>, <TokenType.TIMESTAMP: 'TIMESTAMP'>, <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, <TokenType.XML: 'XML'>, <TokenType.SEMI: 'SEMI'>, <TokenType.JSON: 'JSON'>, <TokenType.DELETE: 'DELETE'>, <TokenType.UTINYINT: 'UTINYINT'>, <TokenType.TIME: 'TIME'>, <TokenType.UDECIMAL: 'UDECIMAL'>, <TokenType.NESTED: 'NESTED'>, <TokenType.DESC: 'DESC'>, <TokenType.ROWVERSION: 'ROWVERSION'>, <TokenType.OFFSET: 'OFFSET'>, <TokenType.TIMESTAMP_NS: 'TIMESTAMP_NS'>, <TokenType.ANY: 'ANY'>, <TokenType.DIV: 'DIV'>, <TokenType.DICTIONARY: 'DICTIONARY'>, <TokenType.INET: 'INET'>, <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, <TokenType.COMMENT: 'COMMENT'>, <TokenType.CURRENT_USER: 'CURRENT_USER'>, <TokenType.SIMPLEAGGREGATEFUNCTION: 'SIMPLEAGGREGATEFUNCTION'>, <TokenType.ALL: 'ALL'>, <TokenType.NAME: 'NAME'>, <TokenType.SOME: 'SOME'>, <TokenType.ENUM16: 'ENUM16'>, <TokenType.YEAR: 'YEAR'>, <TokenType.FULL: 'FULL'>, <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, <TokenType.TINYBLOB: 'TINYBLOB'>, <TokenType.DOUBLE: 'DOUBLE'>, <TokenType.INT4RANGE: 'INT4RANGE'>, <TokenType.FORMAT: 'FORMAT'>, <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, <TokenType.IPPREFIX: 'IPPREFIX'>, <TokenType.OVERWRITE: 'OVERWRITE'>, <TokenType.CURRENT_DATETIME: 'CURRENT_DATETIME'>, <TokenType.COLLATE: 'COLLATE'>, <TokenType.FILTER: 'FILTER'>, <TokenType.JSONB: 'JSONB'>, <TokenType.TDIGEST: 'TDIGEST'>, <TokenType.CHAR: 'CHAR'>, <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, <TokenType.LOWCARDINALITY: 'LOWCARDINALITY'>, <TokenType.ROW: 'ROW'>, <TokenType.SMALLSERIAL: 'SMALLSERIAL'>, <TokenType.OBJECT: 'OBJECT'>, <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, <TokenType.TABLE: 'TABLE'>, <TokenType.DATERANGE: 'DATERANGE'>, <TokenType.NATURAL: 'NATURAL'>, <TokenType.TSRANGE: 'TSRANGE'>, <TokenType.ESCAPE: 'ESCAPE'>, <TokenType.PIVOT: 'PIVOT'>, <TokenType.DECIMAL: 'DECIMAL'>, <TokenType.NCHAR: 'NCHAR'>, <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, <TokenType.UPDATE: 'UPDATE'>, <TokenType.MODEL: 'MODEL'>, <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, <TokenType.SEQUENCE: 'SEQUENCE'>, <TokenType.LONGTEXT: 'LONGTEXT'>, <TokenType.DESCRIBE: 'DESCRIBE'>, <TokenType.IPV6: 'IPV6'>, <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, <TokenType.TINYINT: 'TINYINT'>, <TokenType.ANTI: 'ANTI'>}"}, "sqlglot.parser.Parser.SELECT_START_TOKENS": {"fullname": "sqlglot.parser.Parser.SELECT_START_TOKENS", "modulename": "sqlglot.parser", "qualname": "Parser.SELECT_START_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.L_PAREN: 'L_PAREN'>, <TokenType.SELECT: 'SELECT'>, <TokenType.WITH: 'WITH'>}"}, "sqlglot.parser.Parser.STRICT_CAST": {"fullname": "sqlglot.parser.Parser.STRICT_CAST", "modulename": "sqlglot.parser", "qualname": "Parser.STRICT_CAST", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.parser.Parser.PREFIXED_PIVOT_COLUMNS": {"fullname": "sqlglot.parser.Parser.PREFIXED_PIVOT_COLUMNS", "modulename": "sqlglot.parser", "qualname": "Parser.PREFIXED_PIVOT_COLUMNS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.parser.Parser.IDENTIFY_PIVOT_STRINGS": {"fullname": "sqlglot.parser.Parser.IDENTIFY_PIVOT_STRINGS", "modulename": "sqlglot.parser", "qualname": "Parser.IDENTIFY_PIVOT_STRINGS", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.parser.Parser.LOG_DEFAULTS_TO_LN": {"fullname": "sqlglot.parser.Parser.LOG_DEFAULTS_TO_LN", "modulename": "sqlglot.parser", "qualname": "Parser.LOG_DEFAULTS_TO_LN", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.parser.Parser.ALTER_TABLE_ADD_REQUIRED_FOR_EACH_COLUMN": {"fullname": "sqlglot.parser.Parser.ALTER_TABLE_ADD_REQUIRED_FOR_EACH_COLUMN", "modulename": "sqlglot.parser", "qualname": "Parser.ALTER_TABLE_ADD_REQUIRED_FOR_EACH_COLUMN", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.parser.Parser.TABLESAMPLE_CSV": {"fullname": "sqlglot.parser.Parser.TABLESAMPLE_CSV", "modulename": "sqlglot.parser", "qualname": "Parser.TABLESAMPLE_CSV", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.parser.Parser.DEFAULT_SAMPLING_METHOD": {"fullname": "sqlglot.parser.Parser.DEFAULT_SAMPLING_METHOD", "modulename": "sqlglot.parser", "qualname": "Parser.DEFAULT_SAMPLING_METHOD", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]", "default_value": "None"}, "sqlglot.parser.Parser.SET_REQUIRES_ASSIGNMENT_DELIMITER": {"fullname": "sqlglot.parser.Parser.SET_REQUIRES_ASSIGNMENT_DELIMITER", "modulename": "sqlglot.parser", "qualname": "Parser.SET_REQUIRES_ASSIGNMENT_DELIMITER", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.parser.Parser.TRIM_PATTERN_FIRST": {"fullname": "sqlglot.parser.Parser.TRIM_PATTERN_FIRST", "modulename": "sqlglot.parser", "qualname": "Parser.TRIM_PATTERN_FIRST", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.parser.Parser.STRING_ALIASES": {"fullname": "sqlglot.parser.Parser.STRING_ALIASES", "modulename": "sqlglot.parser", "qualname": "Parser.STRING_ALIASES", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.parser.Parser.MODIFIERS_ATTACHED_TO_UNION": {"fullname": "sqlglot.parser.Parser.MODIFIERS_ATTACHED_TO_UNION", "modulename": "sqlglot.parser", "qualname": "Parser.MODIFIERS_ATTACHED_TO_UNION", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.parser.Parser.UNION_MODIFIERS": {"fullname": "sqlglot.parser.Parser.UNION_MODIFIERS", "modulename": "sqlglot.parser", "qualname": "Parser.UNION_MODIFIERS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'limit', 'offset', 'order'}"}, "sqlglot.parser.Parser.NO_PAREN_IF_COMMANDS": {"fullname": "sqlglot.parser.Parser.NO_PAREN_IF_COMMANDS", "modulename": "sqlglot.parser", "qualname": "Parser.NO_PAREN_IF_COMMANDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.parser.Parser.JSON_ARROWS_REQUIRE_JSON_TYPE": {"fullname": "sqlglot.parser.Parser.JSON_ARROWS_REQUIRE_JSON_TYPE", "modulename": "sqlglot.parser", "qualname": "Parser.JSON_ARROWS_REQUIRE_JSON_TYPE", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.parser.Parser.COLON_IS_JSON_EXTRACT": {"fullname": "sqlglot.parser.Parser.COLON_IS_JSON_EXTRACT", "modulename": "sqlglot.parser", "qualname": "Parser.COLON_IS_JSON_EXTRACT", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.parser.Parser.VALUES_FOLLOWED_BY_PAREN": {"fullname": "sqlglot.parser.Parser.VALUES_FOLLOWED_BY_PAREN", "modulename": "sqlglot.parser", "qualname": "Parser.VALUES_FOLLOWED_BY_PAREN", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.parser.Parser.SUPPORTS_IMPLICIT_UNNEST": {"fullname": "sqlglot.parser.Parser.SUPPORTS_IMPLICIT_UNNEST", "modulename": "sqlglot.parser", "qualname": "Parser.SUPPORTS_IMPLICIT_UNNEST", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.parser.Parser.INTERVAL_SPANS": {"fullname": "sqlglot.parser.Parser.INTERVAL_SPANS", "modulename": "sqlglot.parser", "qualname": "Parser.INTERVAL_SPANS", "kind": "variable", "doc": "<p></p>\n", "default_value": "True"}, "sqlglot.parser.Parser.SUPPORTS_PARTITION_SELECTION": {"fullname": "sqlglot.parser.Parser.SUPPORTS_PARTITION_SELECTION", "modulename": "sqlglot.parser", "qualname": "Parser.SUPPORTS_PARTITION_SELECTION", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.parser.Parser.SHOW_TRIE": {"fullname": "sqlglot.parser.Parser.SHOW_TRIE", "modulename": "sqlglot.parser", "qualname": "Parser.SHOW_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{}"}, "sqlglot.parser.Parser.SET_TRIE": {"fullname": "sqlglot.parser.Parser.SET_TRIE", "modulename": "sqlglot.parser", "qualname": "Parser.SET_TRIE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict", "default_value": "{'GLOBAL': {0: True}, 'LOCAL': {0: True}, 'SESSION': {0: True}, 'TRANSACTION': {0: True}}"}, "sqlglot.parser.Parser.error_level": {"fullname": "sqlglot.parser.Parser.error_level", "modulename": "sqlglot.parser", "qualname": "Parser.error_level", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.parser.Parser.error_message_context": {"fullname": "sqlglot.parser.Parser.error_message_context", "modulename": "sqlglot.parser", "qualname": "Parser.error_message_context", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.parser.Parser.max_errors": {"fullname": "sqlglot.parser.Parser.max_errors", "modulename": "sqlglot.parser", "qualname": "Parser.max_errors", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.parser.Parser.dialect": {"fullname": "sqlglot.parser.Parser.dialect", "modulename": "sqlglot.parser", "qualname": "Parser.dialect", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.parser.Parser.reset": {"fullname": "sqlglot.parser.Parser.reset", "modulename": "sqlglot.parser", "qualname": "Parser.reset", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">):</span></span>", "funcdef": "def"}, "sqlglot.parser.Parser.parse": {"fullname": "sqlglot.parser.Parser.parse", "modulename": "sqlglot.parser", "qualname": "Parser.parse", "kind": "function", "doc": "<p>Parses a list of tokens and returns a list of syntax trees, one tree\nper parsed SQL statement.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>raw_tokens:</strong> The list of tokens.</li>\n<li><strong>sql:</strong> The original SQL string, used to produce helpful debug messages.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The list of the produced syntax trees.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">raw_tokens</span><span class=\"p\">:</span> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">tokens</span><span class=\"o\">.</span><span class=\"n\">Token</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">sql</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]]</span>:</span></span>", "funcdef": "def"}, "sqlglot.parser.Parser.parse_into": {"fullname": "sqlglot.parser.Parser.parse_into", "modulename": "sqlglot.parser", "qualname": "Parser.parse_into", "kind": "function", "doc": "<p>Parses a list of tokens into a given Expression type. If a collection of Expression\ntypes is given instead, this method will try to parse the token list into each one\nof them, stopping at the first for which the parsing succeeds.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression_types:</strong> The expression type(s) to try and parse the token list into.</li>\n<li><strong>raw_tokens:</strong> The list of tokens.</li>\n<li><strong>sql:</strong> The original SQL string, used to produce helpful debug messages.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The target Expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">expression_types</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">],</span> <span class=\"n\">Collection</span><span class=\"p\">[</span><span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]]]]</span>,</span><span class=\"param\">\t<span class=\"n\">raw_tokens</span><span class=\"p\">:</span> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">tokens</span><span class=\"o\">.</span><span class=\"n\">Token</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">sql</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]]</span>:</span></span>", "funcdef": "def"}, "sqlglot.parser.Parser.check_errors": {"fullname": "sqlglot.parser.Parser.check_errors", "modulename": "sqlglot.parser", "qualname": "Parser.check_errors", "kind": "function", "doc": "<p>Logs or raises any found errors, depending on the chosen error level setting.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.parser.Parser.raise_error": {"fullname": "sqlglot.parser.Parser.raise_error", "modulename": "sqlglot.parser", "qualname": "Parser.raise_error", "kind": "function", "doc": "<p>Appends an error in the list of recorded errors or raises it, depending on the chosen\nerror level setting.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">message</span><span class=\"p\">:</span> <span class=\"nb\">str</span>, </span><span class=\"param\"><span class=\"n\">token</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">tokens</span><span class=\"o\">.</span><span class=\"n\">Token</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.parser.Parser.expression": {"fullname": "sqlglot.parser.Parser.expression", "modulename": "sqlglot.parser", "qualname": "Parser.expression", "kind": "function", "doc": "<p>Creates a new, validated Expression.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>exp_class:</strong> The expression class to instantiate.</li>\n<li><strong>comments:</strong> An optional list of comments to attach to the expression.</li>\n<li><strong>kwargs:</strong> The arguments to set for the expression along with their respective values.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The target expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">exp_class</span><span class=\"p\">:</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"o\">~</span><span class=\"n\">E</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">comments</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"o\">~</span><span class=\"n\">E</span>:</span></span>", "funcdef": "def"}, "sqlglot.parser.Parser.validate_expression": {"fullname": "sqlglot.parser.Parser.validate_expression", "modulename": "sqlglot.parser", "qualname": "Parser.validate_expression", "kind": "function", "doc": "<p>Validates an Expression, making sure that all its mandatory arguments are set.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> The expression to validate.</li>\n<li><strong>args:</strong> An optional list of items that was used to instantiate the expression, if it's a Func.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The validated expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"o\">~</span><span class=\"n\">E</span>, </span><span class=\"param\"><span class=\"n\">args</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">List</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"o\">~</span><span class=\"n\">E</span>:</span></span>", "funcdef": "def"}, "sqlglot.parser.Parser.errors": {"fullname": "sqlglot.parser.Parser.errors", "modulename": "sqlglot.parser", "qualname": "Parser.errors", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.parser.Parser.sql": {"fullname": "sqlglot.parser.Parser.sql", "modulename": "sqlglot.parser", "qualname": "Parser.sql", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.planner": {"fullname": "sqlglot.planner", "modulename": "sqlglot.planner", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.planner.Plan": {"fullname": "sqlglot.planner.Plan", "modulename": "sqlglot.planner", "qualname": "Plan", "kind": "class", "doc": "<p></p>\n"}, "sqlglot.planner.Plan.__init__": {"fullname": "sqlglot.planner.Plan.__init__", "modulename": "sqlglot.planner", "qualname": "Plan.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span>)</span>"}, "sqlglot.planner.Plan.expression": {"fullname": "sqlglot.planner.Plan.expression", "modulename": "sqlglot.planner", "qualname": "Plan.expression", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.planner.Plan.root": {"fullname": "sqlglot.planner.Plan.root", "modulename": "sqlglot.planner", "qualname": "Plan.root", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.planner.Plan.dag": {"fullname": "sqlglot.planner.Plan.dag", "modulename": "sqlglot.planner", "qualname": "Plan.dag", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[sqlglot.planner.Step, Set[sqlglot.planner.Step]]"}, "sqlglot.planner.Plan.leaves": {"fullname": "sqlglot.planner.Plan.leaves", "modulename": "sqlglot.planner", "qualname": "Plan.leaves", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Iterator[sqlglot.planner.Step]"}, "sqlglot.planner.Step": {"fullname": "sqlglot.planner.Step", "modulename": "sqlglot.planner", "qualname": "Step", "kind": "class", "doc": "<p></p>\n"}, "sqlglot.planner.Step.from_expression": {"fullname": "sqlglot.planner.Step.from_expression", "modulename": "sqlglot.planner", "qualname": "Step.from_expression", "kind": "function", "doc": "<p>Builds a DAG of Steps from a SQL expression so that it's easier to execute in an engine.\nNote: the expression's tables and subqueries must be aliased for this method to work. For\nexample, given the following expression:</p>\n\n<p>SELECT\n x.a,\n SUM(x.b)\nFROM x AS x\nJOIN y AS y\n ON x.a = y.a\nGROUP BY x.a</p>\n\n<p>the following DAG is produced (the expression IDs might differ per execution):</p>\n\n<ul>\n<li>Aggregate: x (4347984624)\nContext:\n Aggregations:\n - SUM(x.b)\n Group:\n - x.a\nProjections:\n<ul>\n<li>x.a</li>\n<li>\"x\".\"\"\nDependencies:\n<ul>\n<li>Join: x (4347985296)\nContext:\ny:\nOn: x.a = y.a\nProjections:\nDependencies:</li>\n</ul></li>\n<li>Scan: x (4347983136)\nContext:\n Source: x AS x\nProjections:</li>\n<li>Scan: y (4343416624)\nContext:\n Source: y AS y\nProjections:</li>\n</ul></li>\n</ul>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> the expression to build the DAG from.</li>\n<li><strong>ctes:</strong> a dictionary that maps CTEs to their corresponding Step DAG by name.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>A Step DAG corresponding to <code>expression</code>.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">cls</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">ctes</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">planner</span><span class=\"o\">.</span><span class=\"n\">Step</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">planner</span><span class=\"o\">.</span><span class=\"n\">Step</span>:</span></span>", "funcdef": "def"}, "sqlglot.planner.Step.name": {"fullname": "sqlglot.planner.Step.name", "modulename": "sqlglot.planner", "qualname": "Step.name", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]"}, "sqlglot.planner.Step.dependencies": {"fullname": "sqlglot.planner.Step.dependencies", "modulename": "sqlglot.planner", "qualname": "Step.dependencies", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Set[sqlglot.planner.Step]"}, "sqlglot.planner.Step.dependents": {"fullname": "sqlglot.planner.Step.dependents", "modulename": "sqlglot.planner", "qualname": "Step.dependents", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Set[sqlglot.planner.Step]"}, "sqlglot.planner.Step.projections": {"fullname": "sqlglot.planner.Step.projections", "modulename": "sqlglot.planner", "qualname": "Step.projections", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Sequence[sqlglot.expressions.Expression]"}, "sqlglot.planner.Step.limit": {"fullname": "sqlglot.planner.Step.limit", "modulename": "sqlglot.planner", "qualname": "Step.limit", "kind": "variable", "doc": "<p></p>\n", "annotation": ": float"}, "sqlglot.planner.Step.condition": {"fullname": "sqlglot.planner.Step.condition", "modulename": "sqlglot.planner", "qualname": "Step.condition", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[sqlglot.expressions.Expression]"}, "sqlglot.planner.Step.add_dependency": {"fullname": "sqlglot.planner.Step.add_dependency", "modulename": "sqlglot.planner", "qualname": "Step.add_dependency", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">dependency</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">planner</span><span class=\"o\">.</span><span class=\"n\">Step</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.planner.Step.to_s": {"fullname": "sqlglot.planner.Step.to_s", "modulename": "sqlglot.planner", "qualname": "Step.to_s", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">level</span><span class=\"p\">:</span> <span class=\"nb\">int</span> <span class=\"o\">=</span> <span class=\"mi\">0</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">str</span>:</span></span>", "funcdef": "def"}, "sqlglot.planner.Step.type_name": {"fullname": "sqlglot.planner.Step.type_name", "modulename": "sqlglot.planner", "qualname": "Step.type_name", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.planner.Step.id": {"fullname": "sqlglot.planner.Step.id", "modulename": "sqlglot.planner", "qualname": "Step.id", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.planner.Scan": {"fullname": "sqlglot.planner.Scan", "modulename": "sqlglot.planner", "qualname": "Scan", "kind": "class", "doc": "<p></p>\n", "bases": "Step"}, "sqlglot.planner.Scan.from_expression": {"fullname": "sqlglot.planner.Scan.from_expression", "modulename": "sqlglot.planner", "qualname": "Scan.from_expression", "kind": "function", "doc": "<p>Builds a DAG of Steps from a SQL expression so that it's easier to execute in an engine.\nNote: the expression's tables and subqueries must be aliased for this method to work. For\nexample, given the following expression:</p>\n\n<p>SELECT\n x.a,\n SUM(x.b)\nFROM x AS x\nJOIN y AS y\n ON x.a = y.a\nGROUP BY x.a</p>\n\n<p>the following DAG is produced (the expression IDs might differ per execution):</p>\n\n<ul>\n<li>Aggregate: x (4347984624)\nContext:\n Aggregations:\n - SUM(x.b)\n Group:\n - x.a\nProjections:\n<ul>\n<li>x.a</li>\n<li>\"x\".\"\"\nDependencies:\n<ul>\n<li>Join: x (4347985296)\nContext:\ny:\nOn: x.a = y.a\nProjections:\nDependencies:</li>\n</ul></li>\n<li>Scan: x (4347983136)\nContext:\n Source: x AS x\nProjections:</li>\n<li>Scan: y (4343416624)\nContext:\n Source: y AS y\nProjections:</li>\n</ul></li>\n</ul>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> the expression to build the DAG from.</li>\n<li><strong>ctes:</strong> a dictionary that maps CTEs to their corresponding Step DAG by name.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>A Step DAG corresponding to <code>expression</code>.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">cls</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">ctes</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">planner</span><span class=\"o\">.</span><span class=\"n\">Step</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">planner</span><span class=\"o\">.</span><span class=\"n\">Step</span>:</span></span>", "funcdef": "def"}, "sqlglot.planner.Scan.source": {"fullname": "sqlglot.planner.Scan.source", "modulename": "sqlglot.planner", "qualname": "Scan.source", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[sqlglot.expressions.Expression]"}, "sqlglot.planner.Join": {"fullname": "sqlglot.planner.Join", "modulename": "sqlglot.planner", "qualname": "Join", "kind": "class", "doc": "<p></p>\n", "bases": "Step"}, "sqlglot.planner.Join.from_joins": {"fullname": "sqlglot.planner.Join.from_joins", "modulename": "sqlglot.planner", "qualname": "Join.from_joins", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">cls</span>,</span><span class=\"param\">\t<span class=\"n\">joins</span><span class=\"p\">:</span> <span class=\"n\">Iterable</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Join</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">ctes</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">planner</span><span class=\"o\">.</span><span class=\"n\">Step</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">planner</span><span class=\"o\">.</span><span class=\"n\">Join</span>:</span></span>", "funcdef": "def"}, "sqlglot.planner.Join.source_name": {"fullname": "sqlglot.planner.Join.source_name", "modulename": "sqlglot.planner", "qualname": "Join.source_name", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]"}, "sqlglot.planner.Join.joins": {"fullname": "sqlglot.planner.Join.joins", "modulename": "sqlglot.planner", "qualname": "Join.joins", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, Dict[str, Union[List[str], sqlglot.expressions.Expression]]]"}, "sqlglot.planner.Aggregate": {"fullname": "sqlglot.planner.Aggregate", "modulename": "sqlglot.planner", "qualname": "Aggregate", "kind": "class", "doc": "<p></p>\n", "bases": "Step"}, "sqlglot.planner.Aggregate.aggregations": {"fullname": "sqlglot.planner.Aggregate.aggregations", "modulename": "sqlglot.planner", "qualname": "Aggregate.aggregations", "kind": "variable", "doc": "<p></p>\n", "annotation": ": List[sqlglot.expressions.Expression]"}, "sqlglot.planner.Aggregate.operands": {"fullname": "sqlglot.planner.Aggregate.operands", "modulename": "sqlglot.planner", "qualname": "Aggregate.operands", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Tuple[sqlglot.expressions.Expression, ...]"}, "sqlglot.planner.Aggregate.group": {"fullname": "sqlglot.planner.Aggregate.group", "modulename": "sqlglot.planner", "qualname": "Aggregate.group", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, sqlglot.expressions.Expression]"}, "sqlglot.planner.Aggregate.source": {"fullname": "sqlglot.planner.Aggregate.source", "modulename": "sqlglot.planner", "qualname": "Aggregate.source", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Optional[str]"}, "sqlglot.planner.Sort": {"fullname": "sqlglot.planner.Sort", "modulename": "sqlglot.planner", "qualname": "Sort", "kind": "class", "doc": "<p></p>\n", "bases": "Step"}, "sqlglot.planner.Sort.key": {"fullname": "sqlglot.planner.Sort.key", "modulename": "sqlglot.planner", "qualname": "Sort.key", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.planner.SetOperation": {"fullname": "sqlglot.planner.SetOperation", "modulename": "sqlglot.planner", "qualname": "SetOperation", "kind": "class", "doc": "<p></p>\n", "bases": "Step"}, "sqlglot.planner.SetOperation.__init__": {"fullname": "sqlglot.planner.SetOperation.__init__", "modulename": "sqlglot.planner", "qualname": "SetOperation.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">op</span><span class=\"p\">:</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">left</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">right</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">distinct</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span></span>)</span>"}, "sqlglot.planner.SetOperation.op": {"fullname": "sqlglot.planner.SetOperation.op", "modulename": "sqlglot.planner", "qualname": "SetOperation.op", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.planner.SetOperation.left": {"fullname": "sqlglot.planner.SetOperation.left", "modulename": "sqlglot.planner", "qualname": "SetOperation.left", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.planner.SetOperation.right": {"fullname": "sqlglot.planner.SetOperation.right", "modulename": "sqlglot.planner", "qualname": "SetOperation.right", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.planner.SetOperation.distinct": {"fullname": "sqlglot.planner.SetOperation.distinct", "modulename": "sqlglot.planner", "qualname": "SetOperation.distinct", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.planner.SetOperation.from_expression": {"fullname": "sqlglot.planner.SetOperation.from_expression", "modulename": "sqlglot.planner", "qualname": "SetOperation.from_expression", "kind": "function", "doc": "<p>Builds a DAG of Steps from a SQL expression so that it's easier to execute in an engine.\nNote: the expression's tables and subqueries must be aliased for this method to work. For\nexample, given the following expression:</p>\n\n<p>SELECT\n x.a,\n SUM(x.b)\nFROM x AS x\nJOIN y AS y\n ON x.a = y.a\nGROUP BY x.a</p>\n\n<p>the following DAG is produced (the expression IDs might differ per execution):</p>\n\n<ul>\n<li>Aggregate: x (4347984624)\nContext:\n Aggregations:\n - SUM(x.b)\n Group:\n - x.a\nProjections:\n<ul>\n<li>x.a</li>\n<li>\"x\".\"\"\nDependencies:\n<ul>\n<li>Join: x (4347985296)\nContext:\ny:\nOn: x.a = y.a\nProjections:\nDependencies:</li>\n</ul></li>\n<li>Scan: x (4347983136)\nContext:\n Source: x AS x\nProjections:</li>\n<li>Scan: y (4343416624)\nContext:\n Source: y AS y\nProjections:</li>\n</ul></li>\n</ul>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> the expression to build the DAG from.</li>\n<li><strong>ctes:</strong> a dictionary that maps CTEs to their corresponding Step DAG by name.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>A Step DAG corresponding to <code>expression</code>.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">cls</span>,</span><span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">ctes</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">planner</span><span class=\"o\">.</span><span class=\"n\">Step</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">planner</span><span class=\"o\">.</span><span class=\"n\">SetOperation</span>:</span></span>", "funcdef": "def"}, "sqlglot.planner.SetOperation.type_name": {"fullname": "sqlglot.planner.SetOperation.type_name", "modulename": "sqlglot.planner", "qualname": "SetOperation.type_name", "kind": "variable", "doc": "<p></p>\n", "annotation": ": str"}, "sqlglot.schema.Schema": {"fullname": "sqlglot.schema.Schema", "modulename": "sqlglot.schema", "qualname": "Schema", "kind": "class", "doc": "<p>Abstract base class for database schemas</p>\n", "bases": "abc.ABC"}, "sqlglot.schema.Schema.dialect": {"fullname": "sqlglot.schema.Schema.dialect", "modulename": "sqlglot.schema", "qualname": "Schema.dialect", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Union[str, sqlglot.dialects.dialect.Dialect, Type[sqlglot.dialects.dialect.Dialect], NoneType]"}, "sqlglot.schema.Schema.add_table": {"fullname": "sqlglot.schema.Schema.add_table", "modulename": "sqlglot.schema", "qualname": "Schema.add_table", "kind": "function", "doc": "<p>Register or update a table. Some implementing classes may require column information to also be provided.\nThe added table must have the necessary number of qualifiers in its path to match the schema's nesting level.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>table:</strong> the <code>Table</code> expression instance or string representing the table.</li>\n<li><strong>column_mapping:</strong> a column mapping that describes the structure of the table.</li>\n<li><strong>dialect:</strong> the SQL dialect that will be used to parse <code>table</code> if it's a string.</li>\n<li><strong>normalize:</strong> whether to normalize identifiers according to the dialect of interest.</li>\n<li><strong>match_depth:</strong> whether to enforce that the table must match the schema's depth or not.</li>\n</ul>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">table</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Table</span> <span class=\"o\">|</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">column_mapping</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">StructType</span><span class=\"p\">,</span> <span class=\"n\">List</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">normalize</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">bool</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">match_depth</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.schema.Schema.column_names": {"fullname": "sqlglot.schema.Schema.column_names", "modulename": "sqlglot.schema", "qualname": "Schema.column_names", "kind": "function", "doc": "<p>Get the column names for a table.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>table:</strong> the <code>Table</code> expression instance.</li>\n<li><strong>only_visible:</strong> whether to include invisible columns.</li>\n<li><strong>dialect:</strong> the SQL dialect that will be used to parse <code>table</code> if it's a string.</li>\n<li><strong>normalize:</strong> whether to normalize identifiers according to the dialect of interest.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The sequence of column names.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">table</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Table</span> <span class=\"o\">|</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">only_visible</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">normalize</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">bool</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Sequence</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.schema.Schema.get_column_type": {"fullname": "sqlglot.schema.Schema.get_column_type", "modulename": "sqlglot.schema", "qualname": "Schema.get_column_type", "kind": "function", "doc": "<p>Get the <code>sqlglot.exp.DataType</code> type of a column in the schema.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>table:</strong> the source table.</li>\n<li><strong>column:</strong> the target column.</li>\n<li><strong>dialect:</strong> the SQL dialect that will be used to parse <code>table</code> if it's a string.</li>\n<li><strong>normalize:</strong> whether to normalize identifiers according to the dialect of interest.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The resulting column type.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">table</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Table</span> <span class=\"o\">|</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">column</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Column</span> <span class=\"o\">|</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">normalize</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">bool</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span>:</span></span>", "funcdef": "def"}, "sqlglot.schema.Schema.has_column": {"fullname": "sqlglot.schema.Schema.has_column", "modulename": "sqlglot.schema", "qualname": "Schema.has_column", "kind": "function", "doc": "<p>Returns whether <code>column</code> appears in <code>table</code>'s schema.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>table:</strong> the source table.</li>\n<li><strong>column:</strong> the target column.</li>\n<li><strong>dialect:</strong> the SQL dialect that will be used to parse <code>table</code> if it's a string.</li>\n<li><strong>normalize:</strong> whether to normalize identifiers according to the dialect of interest.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>True if the column appears in the schema, False otherwise.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">table</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Table</span> <span class=\"o\">|</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">column</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Column</span> <span class=\"o\">|</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">normalize</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">bool</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">bool</span>:</span></span>", "funcdef": "def"}, "sqlglot.schema.Schema.supported_table_args": {"fullname": "sqlglot.schema.Schema.supported_table_args", "modulename": "sqlglot.schema", "qualname": "Schema.supported_table_args", "kind": "variable", "doc": "<p>Table arguments this schema support, e.g. <code>(\"this\", \"db\", \"catalog\")</code></p>\n", "annotation": ": Tuple[str, ...]"}, "sqlglot.schema.Schema.empty": {"fullname": "sqlglot.schema.Schema.empty", "modulename": "sqlglot.schema", "qualname": "Schema.empty", "kind": "variable", "doc": "<p>Returns whether the schema is empty.</p>\n", "annotation": ": bool"}, "sqlglot.schema.AbstractMappingSchema": {"fullname": "sqlglot.schema.AbstractMappingSchema", "modulename": "sqlglot.schema", "qualname": "AbstractMappingSchema", "kind": "class", "doc": "<p></p>\n"}, "sqlglot.schema.AbstractMappingSchema.__init__": {"fullname": "sqlglot.schema.AbstractMappingSchema.__init__", "modulename": "sqlglot.schema", "qualname": "AbstractMappingSchema.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">mapping</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span>)</span>"}, "sqlglot.schema.AbstractMappingSchema.mapping": {"fullname": "sqlglot.schema.AbstractMappingSchema.mapping", "modulename": "sqlglot.schema", "qualname": "AbstractMappingSchema.mapping", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.schema.AbstractMappingSchema.mapping_trie": {"fullname": "sqlglot.schema.AbstractMappingSchema.mapping_trie", "modulename": "sqlglot.schema", "qualname": "AbstractMappingSchema.mapping_trie", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.schema.AbstractMappingSchema.empty": {"fullname": "sqlglot.schema.AbstractMappingSchema.empty", "modulename": "sqlglot.schema", "qualname": "AbstractMappingSchema.empty", "kind": "variable", "doc": "<p></p>\n", "annotation": ": bool"}, "sqlglot.schema.AbstractMappingSchema.depth": {"fullname": "sqlglot.schema.AbstractMappingSchema.depth", "modulename": "sqlglot.schema", "qualname": "AbstractMappingSchema.depth", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">int</span>:</span></span>", "funcdef": "def"}, "sqlglot.schema.AbstractMappingSchema.supported_table_args": {"fullname": "sqlglot.schema.AbstractMappingSchema.supported_table_args", "modulename": "sqlglot.schema", "qualname": "AbstractMappingSchema.supported_table_args", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Tuple[str, ...]"}, "sqlglot.schema.AbstractMappingSchema.table_parts": {"fullname": "sqlglot.schema.AbstractMappingSchema.table_parts", "modulename": "sqlglot.schema", "qualname": "AbstractMappingSchema.table_parts", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">table</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Table</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.schema.AbstractMappingSchema.find": {"fullname": "sqlglot.schema.AbstractMappingSchema.find", "modulename": "sqlglot.schema", "qualname": "AbstractMappingSchema.find", "kind": "function", "doc": "<p>Returns the schema of a given table.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>table:</strong> the target table.</li>\n<li><strong>raise_on_missing:</strong> whether to raise in case the schema is not found.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The schema of the target table.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">table</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Table</span>,</span><span class=\"param\">\t<span class=\"n\">raise_on_missing</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Any</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.schema.AbstractMappingSchema.nested_get": {"fullname": "sqlglot.schema.AbstractMappingSchema.nested_get", "modulename": "sqlglot.schema", "qualname": "AbstractMappingSchema.nested_get", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">parts</span><span class=\"p\">:</span> <span class=\"n\">Sequence</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">d</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">raise_on_missing</span><span class=\"o\">=</span><span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Any</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.schema.MappingSchema": {"fullname": "sqlglot.schema.MappingSchema", "modulename": "sqlglot.schema", "qualname": "MappingSchema", "kind": "class", "doc": "<p>Schema based on a nested mapping.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>schema:</strong> Mapping in one of the following forms:\n<ol>\n<li>{table: {col: type}}</li>\n<li>{db: {table: {col: type}}}</li>\n<li>{catalog: {db: {table: {col: type}}}}</li>\n<li>None - Tables will be added later</li>\n</ol></li>\n<li><strong>visible:</strong> Optional mapping of which columns in the schema are visible. If not provided, all columns\nare assumed to be visible. The nesting should mirror that of the schema:\n<ol>\n<li>{table: set(<em>cols)}}</li>\n<li>{db: {table: set(</em>cols)}}}</li>\n<li>{catalog: {db: {table: set(*cols)}}}}</li>\n</ol></li>\n<li><strong>dialect:</strong> The dialect to be used for custom type mappings & parsing string arguments.</li>\n<li><strong>normalize:</strong> Whether to normalize identifier names according to the given dialect or not.</li>\n</ul>\n", "bases": "AbstractMappingSchema, Schema"}, "sqlglot.schema.MappingSchema.__init__": {"fullname": "sqlglot.schema.MappingSchema.__init__", "modulename": "sqlglot.schema", "qualname": "MappingSchema.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">schema</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">visible</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">normalize</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span>)</span>"}, "sqlglot.schema.MappingSchema.dialect": {"fullname": "sqlglot.schema.MappingSchema.dialect", "modulename": "sqlglot.schema", "qualname": "MappingSchema.dialect", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.schema.MappingSchema.visible": {"fullname": "sqlglot.schema.MappingSchema.visible", "modulename": "sqlglot.schema", "qualname": "MappingSchema.visible", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.schema.MappingSchema.normalize": {"fullname": "sqlglot.schema.MappingSchema.normalize", "modulename": "sqlglot.schema", "qualname": "MappingSchema.normalize", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.schema.MappingSchema.from_mapping_schema": {"fullname": "sqlglot.schema.MappingSchema.from_mapping_schema", "modulename": "sqlglot.schema", "qualname": "MappingSchema.from_mapping_schema", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">cls</span>,</span><span class=\"param\">\t<span class=\"n\">mapping_schema</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">schema</span><span class=\"o\">.</span><span class=\"n\">MappingSchema</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">schema</span><span class=\"o\">.</span><span class=\"n\">MappingSchema</span>:</span></span>", "funcdef": "def"}, "sqlglot.schema.MappingSchema.copy": {"fullname": "sqlglot.schema.MappingSchema.copy", "modulename": "sqlglot.schema", "qualname": "MappingSchema.copy", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"o\">**</span><span class=\"n\">kwargs</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">schema</span><span class=\"o\">.</span><span class=\"n\">MappingSchema</span>:</span></span>", "funcdef": "def"}, "sqlglot.schema.MappingSchema.add_table": {"fullname": "sqlglot.schema.MappingSchema.add_table", "modulename": "sqlglot.schema", "qualname": "MappingSchema.add_table", "kind": "function", "doc": "<p>Register or update a table. Updates are only performed if a new column mapping is provided.\nThe added table must have the necessary number of qualifiers in its path to match the schema's nesting level.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>table:</strong> the <code>Table</code> expression instance or string representing the table.</li>\n<li><strong>column_mapping:</strong> a column mapping that describes the structure of the table.</li>\n<li><strong>dialect:</strong> the SQL dialect that will be used to parse <code>table</code> if it's a string.</li>\n<li><strong>normalize:</strong> whether to normalize identifiers according to the dialect of interest.</li>\n<li><strong>match_depth:</strong> whether to enforce that the table must match the schema's depth or not.</li>\n</ul>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">table</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Table</span> <span class=\"o\">|</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">column_mapping</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">StructType</span><span class=\"p\">,</span> <span class=\"n\">List</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">normalize</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">bool</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">match_depth</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.schema.MappingSchema.column_names": {"fullname": "sqlglot.schema.MappingSchema.column_names", "modulename": "sqlglot.schema", "qualname": "MappingSchema.column_names", "kind": "function", "doc": "<p>Get the column names for a table.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>table:</strong> the <code>Table</code> expression instance.</li>\n<li><strong>only_visible:</strong> whether to include invisible columns.</li>\n<li><strong>dialect:</strong> the SQL dialect that will be used to parse <code>table</code> if it's a string.</li>\n<li><strong>normalize:</strong> whether to normalize identifiers according to the dialect of interest.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The sequence of column names.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">table</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Table</span> <span class=\"o\">|</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">only_visible</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">normalize</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">bool</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.schema.MappingSchema.get_column_type": {"fullname": "sqlglot.schema.MappingSchema.get_column_type", "modulename": "sqlglot.schema", "qualname": "MappingSchema.get_column_type", "kind": "function", "doc": "<p>Get the <code>sqlglot.exp.DataType</code> type of a column in the schema.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>table:</strong> the source table.</li>\n<li><strong>column:</strong> the target column.</li>\n<li><strong>dialect:</strong> the SQL dialect that will be used to parse <code>table</code> if it's a string.</li>\n<li><strong>normalize:</strong> whether to normalize identifiers according to the dialect of interest.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The resulting column type.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">table</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Table</span> <span class=\"o\">|</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">column</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Column</span> <span class=\"o\">|</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">normalize</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">bool</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span>:</span></span>", "funcdef": "def"}, "sqlglot.schema.MappingSchema.has_column": {"fullname": "sqlglot.schema.MappingSchema.has_column", "modulename": "sqlglot.schema", "qualname": "MappingSchema.has_column", "kind": "function", "doc": "<p>Returns whether <code>column</code> appears in <code>table</code>'s schema.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>table:</strong> the source table.</li>\n<li><strong>column:</strong> the target column.</li>\n<li><strong>dialect:</strong> the SQL dialect that will be used to parse <code>table</code> if it's a string.</li>\n<li><strong>normalize:</strong> whether to normalize identifiers according to the dialect of interest.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>True if the column appears in the schema, False otherwise.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"bp\">self</span>,</span><span class=\"param\">\t<span class=\"n\">table</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Table</span> <span class=\"o\">|</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">column</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Column</span> <span class=\"o\">|</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">normalize</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">bool</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">bool</span>:</span></span>", "funcdef": "def"}, "sqlglot.schema.MappingSchema.depth": {"fullname": "sqlglot.schema.MappingSchema.depth", "modulename": "sqlglot.schema", "qualname": "MappingSchema.depth", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">) -> <span class=\"nb\">int</span>:</span></span>", "funcdef": "def"}, "sqlglot.schema.normalize_name": {"fullname": "sqlglot.schema.normalize_name", "modulename": "sqlglot.schema", "qualname": "normalize_name", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">identifier</span><span class=\"p\">:</span> <span class=\"nb\">str</span> <span class=\"o\">|</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Identifier</span>,</span><span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">is_table</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">False</span>,</span><span class=\"param\">\t<span class=\"n\">normalize</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">bool</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Identifier</span>:</span></span>", "funcdef": "def"}, "sqlglot.schema.ensure_schema": {"fullname": "sqlglot.schema.ensure_schema", "modulename": "sqlglot.schema", "qualname": "ensure_schema", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">schema</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">schema</span><span class=\"o\">.</span><span class=\"n\">Schema</span><span class=\"p\">,</span> <span class=\"n\">Dict</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"o\">**</span><span class=\"n\">kwargs</span><span class=\"p\">:</span> <span class=\"n\">Any</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">schema</span><span class=\"o\">.</span><span class=\"n\">Schema</span>:</span></span>", "funcdef": "def"}, "sqlglot.schema.ensure_column_mapping": {"fullname": "sqlglot.schema.ensure_column_mapping", "modulename": "sqlglot.schema", "qualname": "ensure_column_mapping", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">mapping</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dataframe</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"o\">.</span><span class=\"n\">types</span><span class=\"o\">.</span><span class=\"n\">StructType</span><span class=\"p\">,</span> <span class=\"n\">List</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Dict</span>:</span></span>", "funcdef": "def"}, "sqlglot.schema.flatten_schema": {"fullname": "sqlglot.schema.flatten_schema", "modulename": "sqlglot.schema", "qualname": "flatten_schema", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">schema</span><span class=\"p\">:</span> <span class=\"n\">Dict</span>,</span><span class=\"param\">\t<span class=\"n\">depth</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">int</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span>,</span><span class=\"param\">\t<span class=\"n\">keys</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]]</span>:</span></span>", "funcdef": "def"}, "sqlglot.schema.nested_get": {"fullname": "sqlglot.schema.nested_get", "modulename": "sqlglot.schema", "qualname": "nested_get", "kind": "function", "doc": "<p>Get a value for a nested dictionary.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>d:</strong> the dictionary to search.</li>\n<li><strong>*path:</strong> tuples of (name, key), where:\n<code>key</code> is the key in the dictionary to get.\n<code>name</code> is a string to use in the error if <code>key</code> isn't found.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The value or None if it doesn't exist.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">d</span><span class=\"p\">:</span> <span class=\"n\">Dict</span>,</span><span class=\"param\">\t<span class=\"o\">*</span><span class=\"n\">path</span><span class=\"p\">:</span> <span class=\"n\">Tuple</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">raise_on_missing</span><span class=\"p\">:</span> <span class=\"nb\">bool</span> <span class=\"o\">=</span> <span class=\"kc\">True</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Any</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.schema.nested_set": {"fullname": "sqlglot.schema.nested_set", "modulename": "sqlglot.schema", "qualname": "nested_set", "kind": "function", "doc": "<p>In-place set a value for a nested dictionary</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">nested_set</span><span class=\"p\">({},</span> <span class=\"p\">[</span><span class=\"s2\">"top_key"</span><span class=\"p\">,</span> <span class=\"s2\">"second_key"</span><span class=\"p\">],</span> <span class=\"s2\">"value"</span><span class=\"p\">)</span>\n<span class=\"go\">{'top_key': {'second_key': 'value'}}</span>\n</code></pre>\n </div>\n \n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">nested_set</span><span class=\"p\">({</span><span class=\"s2\">"top_key"</span><span class=\"p\">:</span> <span class=\"p\">{</span><span class=\"s2\">"third_key"</span><span class=\"p\">:</span> <span class=\"s2\">"third_value"</span><span class=\"p\">}},</span> <span class=\"p\">[</span><span class=\"s2\">"top_key"</span><span class=\"p\">,</span> <span class=\"s2\">"second_key"</span><span class=\"p\">],</span> <span class=\"s2\">"value"</span><span class=\"p\">)</span>\n<span class=\"go\">{'top_key': {'third_key': 'third_value', 'second_key': 'value'}}</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>d:</strong> dictionary to update.</li>\n<li><strong>keys:</strong> the keys that makeup the path to <code>value</code>.</li>\n<li><strong>value:</strong> the value to set in the dictionary for the given key path.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The (possibly) updated dictionary.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"n\">d</span><span class=\"p\">:</span> <span class=\"n\">Dict</span>, </span><span class=\"param\"><span class=\"n\">keys</span><span class=\"p\">:</span> <span class=\"n\">Sequence</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span>, </span><span class=\"param\"><span class=\"n\">value</span><span class=\"p\">:</span> <span class=\"n\">Any</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Dict</span>:</span></span>", "funcdef": "def"}, "sqlglot.serde": {"fullname": "sqlglot.serde", "modulename": "sqlglot.serde", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.serde.dump": {"fullname": "sqlglot.serde.dump", "modulename": "sqlglot.serde", "qualname": "dump", "kind": "function", "doc": "<p>Recursively dump an AST into a JSON-serializable dict.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">node</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">ForwardRef</span><span class=\"p\">(</span><span class=\"s1\">'Node'</span><span class=\"p\">)],</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"nb\">dict</span><span class=\"p\">,</span> <span class=\"nb\">list</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"nb\">float</span><span class=\"p\">,</span> <span class=\"nb\">int</span><span class=\"p\">,</span> <span class=\"nb\">bool</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">dict</span><span class=\"p\">,</span> <span class=\"nb\">list</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"nb\">float</span><span class=\"p\">,</span> <span class=\"nb\">int</span><span class=\"p\">,</span> <span class=\"nb\">bool</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.serde.load": {"fullname": "sqlglot.serde.load", "modulename": "sqlglot.serde", "qualname": "load", "kind": "function", "doc": "<p>Recursively load a dict (as returned by <code>dump</code>) into an AST.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">obj</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">dict</span><span class=\"p\">,</span> <span class=\"nb\">list</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"nb\">float</span><span class=\"p\">,</span> <span class=\"nb\">int</span><span class=\"p\">,</span> <span class=\"nb\">bool</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">ForwardRef</span><span class=\"p\">(</span><span class=\"s1\">'Node'</span><span class=\"p\">)],</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">DataType</span><span class=\"o\">.</span><span class=\"n\">Type</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">,</span> <span class=\"nb\">dict</span><span class=\"p\">,</span> <span class=\"nb\">list</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"nb\">float</span><span class=\"p\">,</span> <span class=\"nb\">int</span><span class=\"p\">,</span> <span class=\"nb\">bool</span><span class=\"p\">,</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.time": {"fullname": "sqlglot.time", "modulename": "sqlglot.time", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.time.format_time": {"fullname": "sqlglot.time.format_time", "modulename": "sqlglot.time", "qualname": "format_time", "kind": "function", "doc": "<p>Converts a time string given a mapping.</p>\n\n<h6 id=\"examples\">Examples:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">format_time</span><span class=\"p\">(</span><span class=\"s2\">"%Y"</span><span class=\"p\">,</span> <span class=\"p\">{</span><span class=\"s2\">"%Y"</span><span class=\"p\">:</span> <span class=\"s2\">"YYYY"</span><span class=\"p\">})</span>\n<span class=\"go\">'YYYY'</span>\n</code></pre>\n </div>\n \n <p>Args:\n mapping: dictionary of time format to target time format.\n trie: optional trie, can be passed in for performance.</p>\n \n <p>Returns:\n The converted time string.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">string</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">mapping</span><span class=\"p\">:</span> <span class=\"n\">Dict</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"nb\">str</span><span class=\"p\">]</span>,</span><span class=\"param\">\t<span class=\"n\">trie</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.time.TIMEZONES": {"fullname": "sqlglot.time.TIMEZONES", "modulename": "sqlglot.time", "qualname": "TIMEZONES", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'america/grand_turk', 'africa/casablanca', 'asia/riyadh', 'africa/tripoli', 'pacific/funafuti', 'pacific/kanton', 'etc/gmt-1', 'asia/chungking', 'america/costa_rica', 'australia/eucla', 'etc/gmt-12', 'gmt0', 'asia/chita', 'asia/amman', 'africa/bujumbura', 'america/fort_nelson', 'europe/nicosia', 'asia/aden', 'singapore', 'etc/gmt-4', 'africa/kinshasa', 'pacific/galapagos', 'iran', 'indian/mauritius', 'europe/sarajevo', 'america/argentina/cordoba', 'america/indiana/knox', 'asia/anadyr', 'asia/ujung_pandang', 'pacific/chatham', 'africa/douala', 'america/argentina/tucuman', 'canada/central', 'america/st_lucia', 'europe/paris', 'antarctica/casey', 'etc/gmt+3', 'america/sitka', 'america/thunder_bay', 'africa/kampala', 'america/barbados', 'australia/yancowinna', 'africa/lome', 'etc/gmt+1', 'poland', 'america/rainy_river', 'asia/qostanay', 'asia/yekaterinburg', 'america/merida', 'europe/andorra', 'europe/zaporozhye', 'australia/queensland', 'america/danmarkshavn', 'indian/reunion', 'gmt-0', 'europe/sofia', 'asia/chongqing', 'america/maceio', 'america/boise', 'europe/malta', 'europe/zagreb', 'us/aleutian', 'asia/yerevan', 'america/monterrey', 'europe/minsk', 'us/indiana-starke', 'asia/dubai', 'america/mendoza', 'atlantic/canary', 'america/anguilla', 'africa/nairobi', 'asia/manila', 'america/dominica', 'america/managua', 'asia/qyzylorda', 'america/montreal', 'america/argentina/la_rioja', 'america/indiana/vevay', 'america/montevideo', 'chile/continental', 'asia/tomsk', 'indian/mayotte', 'america/tegucigalpa', 'australia/nsw', 'hongkong', 'pacific/yap', 'europe/budapest', 'pacific/wake', 'america/aruba', 'asia/omsk', 'etc/gmt-5', 'america/argentina/catamarca', 'us/hawaii', 'us/samoa', 'america/cayenne', 'asia/krasnoyarsk', 'america/argentina/san_juan', 'asia/choibalsan', 'asia/novosibirsk', 'mst7mdt', 'america/nome', 'etc/gmt+8', 'america/paramaribo', 'europe/berlin', 'europe/mariehamn', 'america/santiago', 'europe/warsaw', 'america/punta_arenas', 'europe/podgorica', 'america/jamaica', 'america/cordoba', 'atlantic/cape_verde', 'australia/adelaide', 'europe/kirov', 'atlantic/azores', 'us/east-indiana', 'antarctica/mcmurdo', 'us/michigan', 'arctic/longyearbyen', 'pacific/noumea', 'america/thule', 'asia/karachi', 'africa/niamey', 'pacific/kwajalein', 'australia/currie', 'europe/simferopol', 'gmt', 'america/pangnirtung', 'europe/vaduz', 'asia/harbin', 'america/manaus', 'america/eirunepe', 'australia/perth', 'america/louisville', 'america/tijuana', 'america/indiana/petersburg', 'asia/kolkata', 'america/indiana/vincennes', 'america/santarem', 'etc/gmt-2', 'america/metlakatla', 'w-su', 'america/st_thomas', 'africa/harare', 'africa/luanda', 'etc/gmt+12', 'brazil/acre', 'africa/bamako', 'cet', 'atlantic/reykjavik', 'europe/kyiv', 'america/argentina/san_luis', 'asia/jayapura', 'atlantic/faeroe', 'europe/istanbul', 'asia/taipei', 'canada/mountain', 'pacific/guam', 'america/north_dakota/beulah', 'africa/johannesburg', 'pacific/kosrae', 'america/argentina/comodrivadavia', 'america/argentina/ushuaia', 'america/cambridge_bay', 'australia/lord_howe', 'africa/bangui', 'cuba', 'asia/khandyga', 'canada/yukon', 'etc/greenwich', 'libya', 'america/bahia', 'canada/eastern', 'mexico/bajanorte', 'canada/newfoundland', 'america/porto_velho', 'america/port-au-prince', 'asia/hovd', 'etc/gmt+7', 'pacific/tahiti', 'america/guayaquil', 'africa/malabo', 'asia/kashgar', 'america/whitehorse', 'us/central', 'america/regina', 'atlantic/jan_mayen', 'hst', 'europe/jersey', 'asia/dacca', 'europe/astrakhan', 'etc/gmt-14', 'antarctica/south_pole', 'america/indianapolis', 'pacific/marquesas', 'america/kentucky/monticello', 'asia/kamchatka', 'antarctica/davis', 'africa/kigali', 'gb', 'asia/tehran', 'america/indiana/tell_city', 'america/winnipeg', 'us/pacific', 'australia/lhi', 'etc/gmt-11', 'asia/urumqi', 'america/cayman', 'etc/gmt-10', 'america/moncton', 'america/st_kitts', 'america/st_vincent', 'europe/amsterdam', 'asia/kuwait', 'america/chihuahua', 'indian/cocos', 'asia/thimbu', 'america/knox_in', 'asia/bangkok', 'us/mountain', 'asia/hebron', 'pacific/truk', 'etc/gmt+4', 'america/buenos_aires', 'asia/macao', 'japan', 'asia/phnom_penh', 'canada/pacific', 'antarctica/vostok', 'prc', 'asia/qatar', 'nz-chat', 'africa/mogadishu', 'america/kentucky/louisville', 'asia/oral', 'europe/gibraltar', 'pacific/tongatapu', 'europe/belfast', 'asia/ashkhabad', 'america/la_paz', 'indian/comoro', 'us/eastern', 'europe/vilnius', 'europe/copenhagen', 'gmt+0', 'africa/khartoum', 'america/swift_current', 'asia/gaza', 'america/north_dakota/center', 'america/tortola', 'mexico/bajasur', 'asia/muscat', 'europe/moscow', 'pacific/enderbury', 'africa/maseru', 'america/argentina/buenos_aires', 'universal', 'america/godthab', 'america/rio_branco', 'europe/busingen', 'pacific/kiritimati', 'america/scoresbysund', 'asia/jerusalem', 'europe/kaliningrad', 'europe/monaco', 'australia/act', 'asia/srednekolymsk', 'africa/monrovia', 'america/nuuk', 'etc/gmt+10', 'etc/gmt+0', 'asia/tel_aviv', 'america/north_dakota/new_salem', 'africa/blantyre', 'australia/north', 'pacific/majuro', 'antarctica/macquarie', 'america/rosario', 'atlantic/bermuda', 'atlantic/madeira', 'europe/volgograd', 'pacific/ponape', 'pacific/auckland', 'america/noronha', 'africa/dar_es_salaam', 'africa/nouakchott', 'america/indiana/indianapolis', 'rok', 'america/halifax', 'america/martinique', 'asia/aqtobe', 'asia/yakutsk', 'europe/prague', 'africa/djibouti', 'brazil/denoronha', 'asia/saigon', 'america/lima', 'america/port_of_spain', 'asia/samarkand', 'america/mazatlan', 'america/argentina/mendoza', 'america/glace_bay', 'asia/kabul', 'america/nipigon', 'etc/gmt-7', 'africa/bissau', 'pacific/port_moresby', 'africa/abidjan', 'greenwich', 'europe/brussels', 'america/belize', 'mst', 'africa/addis_ababa', 'america/matamoros', 'antarctica/mawson', 'pacific/gambier', 'asia/dushanbe', 'turkey', 'asia/almaty', 'etc/gmt', 'pacific/apia', 'europe/samara', 'america/indiana/marengo', 'asia/baku', 'africa/lagos', 'america/los_angeles', 'pacific/fakaofo', 'asia/vladivostok', 'europe/stockholm', 'africa/dakar', 'indian/christmas', 'asia/brunei', 'america/kralendijk', 'asia/baghdad', 'europe/bucharest', 'asia/ust-nera', 'america/campo_grande', 'australia/south', 'pacific/niue', 'america/cuiaba', 'etc/gmt+9', 'antarctica/syowa', 'asia/magadan', 'america/recife', 'america/curacao', 'pacific/chuuk', 'pacific/guadalcanal', 'europe/rome', 'europe/tirane', 'pacific/efate', 'africa/banjul', 'cst6cdt', 'etc/zulu', 'africa/timbuktu', 'asia/ulaanbaatar', 'antarctica/troll', 'etc/gmt+2', 'asia/beirut', 'nz', 'america/st_johns', 'utc', 'europe/tiraspol', 'us/alaska', 'asia/sakhalin', 'europe/bratislava', 'atlantic/st_helena', 'africa/lubumbashi', 'roc', 'africa/ceuta', 'asia/jakarta', 'indian/maldives', 'africa/sao_tome', 'etc/gmt0', 'asia/bahrain', 'america/goose_bay', 'pacific/bougainville', 'asia/vientiane', 'africa/juba', 'europe/luxembourg', 'america/virgin', 'indian/chagos', 'america/anchorage', 'america/nassau', 'asia/yangon', 'pacific/pohnpei', 'america/dawson_creek', 'australia/melbourne', 'australia/canberra', 'etc/gmt-3', 'america/argentina/rio_gallegos', 'africa/asmara', 'europe/guernsey', 'gb-eire', 'indian/mahe', 'europe/london', 'america/phoenix', 'america/inuvik', 'etc/gmt-6', 'pacific/easter', 'asia/tokyo', 'america/iqaluit', 'asia/seoul', 'canada/atlantic', 'australia/broken_hill', 'australia/hobart', 'australia/darwin', 'america/marigot', 'pacific/pitcairn', 'europe/belgrade', 'africa/tunis', 'indian/antananarivo', 'kwajalein', 'america/puerto_rico', 'mexico/general', 'asia/atyrau', 'pst8pdt', 'america/miquelon', 'europe/dublin', 'america/caracas', 'africa/brazzaville', 'australia/tasmania', 'africa/libreville', 'antarctica/rothera', 'africa/ndjamena', 'america/guyana', 'met', 'europe/madrid', 'america/catamarca', 'asia/kathmandu', 'asia/bishkek', 'pacific/saipan', 'africa/ouagadougou', 'africa/algiers', 'america/sao_paulo', 'europe/saratov', 'africa/gaborone', 'asia/irkutsk', 'est5edt', 'etc/utc', 'europe/helsinki', 'pacific/tarawa', 'asia/tashkent', 'australia/sydney', 'europe/riga', 'america/santa_isabel', 'america/adak', 'pacific/wallis', 'europe/tallinn', 'europe/ulyanovsk', 'asia/singapore', 'etc/gmt-9', 'america/argentina/salta', 'america/toronto', 'asia/nicosia', 'america/shiprock', 'america/juneau', 'america/guadeloupe', 'america/hermosillo', 'europe/vatican', 'asia/ho_chi_minh', 'africa/el_aaiun', 'pacific/rarotonga', 'eire', 'asia/kuala_lumpur', 'europe/chisinau', 'australia/lindeman', 'america/denver', 'uct', 'america/edmonton', 'atlantic/faroe', 'america/araguaina', 'est', 'america/havana', 'africa/accra', 'asia/dili', 'africa/mbabane', 'america/bahia_banderas', 'eet', 'america/atka', 'etc/gmt+5', 'israel', 'australia/victoria', 'africa/cairo', 'asia/katmandu', 'america/argentina/jujuy', 'africa/windhoek', 'america/el_salvador', 'asia/istanbul', 'america/blanc-sablon', 'antarctica/palmer', 'brazil/west', 'asia/famagusta', 'pacific/midway', 'us/arizona', 'africa/conakry', 'america/antigua', 'africa/maputo', 'america/resolute', 'america/atikokan', 'zulu', 'america/indiana/winamac', 'america/porto_acre', 'asia/ashgabat', 'egypt', 'asia/macau', 'chile/easterisland', 'america/ciudad_juarez', 'america/st_barthelemy', 'wet', 'pacific/nauru', 'antarctica/dumontdurville', 'america/creston', 'africa/porto-novo', 'europe/san_marino', 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"TokenType.SEQUENCE", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.SEQUENCE: 'SEQUENCE'>"}, "sqlglot.tokens.TokenType.SERDE_PROPERTIES": {"fullname": "sqlglot.tokens.TokenType.SERDE_PROPERTIES", "modulename": "sqlglot.tokens", "qualname": "TokenType.SERDE_PROPERTIES", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.SERDE_PROPERTIES: 'SERDE_PROPERTIES'>"}, "sqlglot.tokens.TokenType.SET": {"fullname": "sqlglot.tokens.TokenType.SET", "modulename": "sqlglot.tokens", "qualname": "TokenType.SET", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.SET: 'SET'>"}, "sqlglot.tokens.TokenType.SETTINGS": {"fullname": "sqlglot.tokens.TokenType.SETTINGS", "modulename": "sqlglot.tokens", "qualname": "TokenType.SETTINGS", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.SETTINGS: 'SETTINGS'>"}, "sqlglot.tokens.TokenType.SHOW": {"fullname": "sqlglot.tokens.TokenType.SHOW", "modulename": "sqlglot.tokens", "qualname": "TokenType.SHOW", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.SHOW: 'SHOW'>"}, "sqlglot.tokens.TokenType.SIMILAR_TO": {"fullname": "sqlglot.tokens.TokenType.SIMILAR_TO", "modulename": "sqlglot.tokens", "qualname": "TokenType.SIMILAR_TO", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.SIMILAR_TO: 'SIMILAR_TO'>"}, "sqlglot.tokens.TokenType.SOME": {"fullname": "sqlglot.tokens.TokenType.SOME", "modulename": "sqlglot.tokens", "qualname": "TokenType.SOME", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.SOME: 'SOME'>"}, "sqlglot.tokens.TokenType.SORT_BY": {"fullname": "sqlglot.tokens.TokenType.SORT_BY", "modulename": "sqlglot.tokens", "qualname": "TokenType.SORT_BY", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.SORT_BY: 'SORT_BY'>"}, "sqlglot.tokens.TokenType.START_WITH": {"fullname": "sqlglot.tokens.TokenType.START_WITH", "modulename": "sqlglot.tokens", "qualname": "TokenType.START_WITH", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.START_WITH: 'START_WITH'>"}, "sqlglot.tokens.TokenType.STORAGE_INTEGRATION": {"fullname": "sqlglot.tokens.TokenType.STORAGE_INTEGRATION", "modulename": "sqlglot.tokens", "qualname": "TokenType.STORAGE_INTEGRATION", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.STORAGE_INTEGRATION: 'STORAGE_INTEGRATION'>"}, "sqlglot.tokens.TokenType.STRUCT": {"fullname": "sqlglot.tokens.TokenType.STRUCT", "modulename": "sqlglot.tokens", "qualname": "TokenType.STRUCT", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.STRUCT: 'STRUCT'>"}, "sqlglot.tokens.TokenType.TABLE_SAMPLE": {"fullname": "sqlglot.tokens.TokenType.TABLE_SAMPLE", "modulename": "sqlglot.tokens", "qualname": "TokenType.TABLE_SAMPLE", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.TABLE_SAMPLE: 'TABLE_SAMPLE'>"}, "sqlglot.tokens.TokenType.TAG": {"fullname": "sqlglot.tokens.TokenType.TAG", "modulename": "sqlglot.tokens", "qualname": "TokenType.TAG", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.TAG: 'TAG'>"}, "sqlglot.tokens.TokenType.TEMPORARY": {"fullname": "sqlglot.tokens.TokenType.TEMPORARY", "modulename": "sqlglot.tokens", "qualname": "TokenType.TEMPORARY", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.TEMPORARY: 'TEMPORARY'>"}, "sqlglot.tokens.TokenType.TOP": {"fullname": "sqlglot.tokens.TokenType.TOP", "modulename": "sqlglot.tokens", "qualname": "TokenType.TOP", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.TOP: 'TOP'>"}, "sqlglot.tokens.TokenType.THEN": {"fullname": "sqlglot.tokens.TokenType.THEN", "modulename": "sqlglot.tokens", "qualname": "TokenType.THEN", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.THEN: 'THEN'>"}, "sqlglot.tokens.TokenType.TRUE": {"fullname": "sqlglot.tokens.TokenType.TRUE", "modulename": "sqlglot.tokens", "qualname": "TokenType.TRUE", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.TRUE: 'TRUE'>"}, "sqlglot.tokens.TokenType.TRUNCATE": {"fullname": "sqlglot.tokens.TokenType.TRUNCATE", "modulename": "sqlglot.tokens", "qualname": "TokenType.TRUNCATE", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.TRUNCATE: 'TRUNCATE'>"}, "sqlglot.tokens.TokenType.UNCACHE": {"fullname": "sqlglot.tokens.TokenType.UNCACHE", "modulename": "sqlglot.tokens", "qualname": "TokenType.UNCACHE", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.UNCACHE: 'UNCACHE'>"}, "sqlglot.tokens.TokenType.UNION": {"fullname": "sqlglot.tokens.TokenType.UNION", "modulename": "sqlglot.tokens", "qualname": "TokenType.UNION", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.UNION: 'UNION'>"}, "sqlglot.tokens.TokenType.UNNEST": {"fullname": "sqlglot.tokens.TokenType.UNNEST", "modulename": "sqlglot.tokens", "qualname": "TokenType.UNNEST", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.UNNEST: 'UNNEST'>"}, "sqlglot.tokens.TokenType.UNPIVOT": {"fullname": "sqlglot.tokens.TokenType.UNPIVOT", "modulename": "sqlglot.tokens", "qualname": "TokenType.UNPIVOT", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.UNPIVOT: 'UNPIVOT'>"}, "sqlglot.tokens.TokenType.UPDATE": {"fullname": "sqlglot.tokens.TokenType.UPDATE", "modulename": "sqlglot.tokens", "qualname": "TokenType.UPDATE", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.UPDATE: 'UPDATE'>"}, "sqlglot.tokens.TokenType.USE": {"fullname": "sqlglot.tokens.TokenType.USE", "modulename": "sqlglot.tokens", "qualname": "TokenType.USE", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.USE: 'USE'>"}, "sqlglot.tokens.TokenType.USING": {"fullname": "sqlglot.tokens.TokenType.USING", "modulename": "sqlglot.tokens", "qualname": "TokenType.USING", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.USING: 'USING'>"}, "sqlglot.tokens.TokenType.VALUES": {"fullname": "sqlglot.tokens.TokenType.VALUES", "modulename": "sqlglot.tokens", "qualname": "TokenType.VALUES", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.VALUES: 'VALUES'>"}, "sqlglot.tokens.TokenType.VIEW": {"fullname": "sqlglot.tokens.TokenType.VIEW", "modulename": "sqlglot.tokens", "qualname": "TokenType.VIEW", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.VIEW: 'VIEW'>"}, "sqlglot.tokens.TokenType.VOLATILE": {"fullname": "sqlglot.tokens.TokenType.VOLATILE", "modulename": "sqlglot.tokens", "qualname": "TokenType.VOLATILE", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.VOLATILE: 'VOLATILE'>"}, "sqlglot.tokens.TokenType.WHEN": {"fullname": "sqlglot.tokens.TokenType.WHEN", "modulename": "sqlglot.tokens", "qualname": "TokenType.WHEN", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.WHEN: 'WHEN'>"}, "sqlglot.tokens.TokenType.WHERE": {"fullname": "sqlglot.tokens.TokenType.WHERE", "modulename": "sqlglot.tokens", "qualname": "TokenType.WHERE", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.WHERE: 'WHERE'>"}, "sqlglot.tokens.TokenType.WINDOW": {"fullname": "sqlglot.tokens.TokenType.WINDOW", "modulename": "sqlglot.tokens", "qualname": "TokenType.WINDOW", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.WINDOW: 'WINDOW'>"}, "sqlglot.tokens.TokenType.WITH": {"fullname": "sqlglot.tokens.TokenType.WITH", "modulename": "sqlglot.tokens", "qualname": "TokenType.WITH", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.WITH: 'WITH'>"}, "sqlglot.tokens.TokenType.UNIQUE": {"fullname": "sqlglot.tokens.TokenType.UNIQUE", "modulename": "sqlglot.tokens", "qualname": "TokenType.UNIQUE", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.UNIQUE: 'UNIQUE'>"}, "sqlglot.tokens.TokenType.VERSION_SNAPSHOT": {"fullname": "sqlglot.tokens.TokenType.VERSION_SNAPSHOT", "modulename": "sqlglot.tokens", "qualname": "TokenType.VERSION_SNAPSHOT", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.VERSION_SNAPSHOT: 'VERSION_SNAPSHOT'>"}, "sqlglot.tokens.TokenType.TIMESTAMP_SNAPSHOT": {"fullname": "sqlglot.tokens.TokenType.TIMESTAMP_SNAPSHOT", "modulename": "sqlglot.tokens", "qualname": "TokenType.TIMESTAMP_SNAPSHOT", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.TIMESTAMP_SNAPSHOT: 'TIMESTAMP_SNAPSHOT'>"}, "sqlglot.tokens.TokenType.OPTION": {"fullname": "sqlglot.tokens.TokenType.OPTION", "modulename": "sqlglot.tokens", "qualname": "TokenType.OPTION", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.OPTION: 'OPTION'>"}, "sqlglot.tokens.Token": {"fullname": "sqlglot.tokens.Token", "modulename": "sqlglot.tokens", "qualname": "Token", "kind": "class", "doc": "<p></p>\n"}, "sqlglot.tokens.Token.__init__": {"fullname": "sqlglot.tokens.Token.__init__", "modulename": "sqlglot.tokens", "qualname": "Token.__init__", "kind": "function", "doc": "<p>Token initializer.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>token_type:</strong> The TokenType Enum.</li>\n<li><strong>text:</strong> The text of the token.</li>\n<li><strong>line:</strong> The line that the token ends on.</li>\n<li><strong>col:</strong> The column that the token ends on.</li>\n<li><strong>start:</strong> The start index of the token.</li>\n<li><strong>end:</strong> The ending index of the token.</li>\n<li><strong>comments:</strong> The comments to attach to the token.</li>\n</ul>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">token_type</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">tokens</span><span class=\"o\">.</span><span class=\"n\">TokenType</span>,</span><span class=\"param\">\t<span class=\"n\">text</span><span class=\"p\">:</span> <span class=\"nb\">str</span>,</span><span class=\"param\">\t<span class=\"n\">line</span><span class=\"p\">:</span> <span class=\"nb\">int</span> <span class=\"o\">=</span> <span class=\"mi\">1</span>,</span><span class=\"param\">\t<span class=\"n\">col</span><span class=\"p\">:</span> <span class=\"nb\">int</span> <span class=\"o\">=</span> <span class=\"mi\">1</span>,</span><span class=\"param\">\t<span class=\"n\">start</span><span class=\"p\">:</span> <span class=\"nb\">int</span> <span class=\"o\">=</span> <span class=\"mi\">0</span>,</span><span class=\"param\">\t<span class=\"n\">end</span><span class=\"p\">:</span> <span class=\"nb\">int</span> <span class=\"o\">=</span> <span class=\"mi\">0</span>,</span><span class=\"param\">\t<span class=\"n\">comments</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">List</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">]]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span>)</span>"}, "sqlglot.tokens.Token.number": {"fullname": "sqlglot.tokens.Token.number", "modulename": "sqlglot.tokens", "qualname": "Token.number", "kind": "function", "doc": "<p>Returns a NUMBER token with <code>number</code> as its text.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">cls</span>, </span><span class=\"param\"><span class=\"n\">number</span><span class=\"p\">:</span> <span class=\"nb\">int</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">tokens</span><span class=\"o\">.</span><span class=\"n\">Token</span>:</span></span>", "funcdef": "def"}, "sqlglot.tokens.Token.string": {"fullname": "sqlglot.tokens.Token.string", "modulename": "sqlglot.tokens", "qualname": "Token.string", "kind": "function", "doc": "<p>Returns a STRING token with <code>string</code> as its text.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">cls</span>, </span><span class=\"param\"><span class=\"n\">string</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">tokens</span><span class=\"o\">.</span><span class=\"n\">Token</span>:</span></span>", "funcdef": "def"}, "sqlglot.tokens.Token.identifier": {"fullname": "sqlglot.tokens.Token.identifier", "modulename": "sqlglot.tokens", "qualname": "Token.identifier", "kind": "function", "doc": "<p>Returns an IDENTIFIER token with <code>identifier</code> as its text.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">cls</span>, </span><span class=\"param\"><span class=\"n\">identifier</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">tokens</span><span class=\"o\">.</span><span class=\"n\">Token</span>:</span></span>", "funcdef": "def"}, "sqlglot.tokens.Token.var": {"fullname": "sqlglot.tokens.Token.var", "modulename": "sqlglot.tokens", "qualname": "Token.var", "kind": "function", "doc": "<p>Returns an VAR token with <code>var</code> as its text.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">cls</span>, </span><span class=\"param\"><span class=\"n\">var</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">tokens</span><span class=\"o\">.</span><span class=\"n\">Token</span>:</span></span>", "funcdef": "def"}, "sqlglot.tokens.Token.token_type": {"fullname": "sqlglot.tokens.Token.token_type", "modulename": "sqlglot.tokens", "qualname": "Token.token_type", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.tokens.Token.text": {"fullname": "sqlglot.tokens.Token.text", "modulename": "sqlglot.tokens", "qualname": "Token.text", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.tokens.Token.line": {"fullname": "sqlglot.tokens.Token.line", "modulename": "sqlglot.tokens", "qualname": "Token.line", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.tokens.Token.col": {"fullname": "sqlglot.tokens.Token.col", "modulename": "sqlglot.tokens", "qualname": "Token.col", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.tokens.Token.start": {"fullname": "sqlglot.tokens.Token.start", "modulename": "sqlglot.tokens", "qualname": "Token.start", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.tokens.Token.end": {"fullname": "sqlglot.tokens.Token.end", "modulename": "sqlglot.tokens", "qualname": "Token.end", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.tokens.Token.comments": {"fullname": "sqlglot.tokens.Token.comments", "modulename": "sqlglot.tokens", "qualname": "Token.comments", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.tokens.Tokenizer": {"fullname": "sqlglot.tokens.Tokenizer", "modulename": "sqlglot.tokens", "qualname": "Tokenizer", "kind": "class", "doc": "<p></p>\n"}, "sqlglot.tokens.Tokenizer.__init__": {"fullname": "sqlglot.tokens.Tokenizer.__init__", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.__init__", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">dialect</span><span class=\"p\">:</span> <span class=\"n\">Union</span><span class=\"p\">[</span><span class=\"nb\">str</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">,</span> <span class=\"n\">Type</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">dialects</span><span class=\"o\">.</span><span class=\"n\">dialect</span><span class=\"o\">.</span><span class=\"n\">Dialect</span><span class=\"p\">],</span> <span class=\"n\">NoneType</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span>)</span>"}, "sqlglot.tokens.Tokenizer.SINGLE_TOKENS": {"fullname": "sqlglot.tokens.Tokenizer.SINGLE_TOKENS", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.SINGLE_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{'(': <TokenType.L_PAREN: 'L_PAREN'>, ')': <TokenType.R_PAREN: 'R_PAREN'>, '[': <TokenType.L_BRACKET: 'L_BRACKET'>, ']': <TokenType.R_BRACKET: 'R_BRACKET'>, '{': <TokenType.L_BRACE: 'L_BRACE'>, '}': <TokenType.R_BRACE: 'R_BRACE'>, '&': <TokenType.AMP: 'AMP'>, '^': <TokenType.CARET: 'CARET'>, ':': <TokenType.COLON: 'COLON'>, ',': <TokenType.COMMA: 'COMMA'>, '.': <TokenType.DOT: 'DOT'>, '-': <TokenType.DASH: 'DASH'>, '=': <TokenType.EQ: 'EQ'>, '>': <TokenType.GT: 'GT'>, '<': <TokenType.LT: 'LT'>, '%': <TokenType.MOD: 'MOD'>, '!': <TokenType.NOT: 'NOT'>, '|': <TokenType.PIPE: 'PIPE'>, '+': <TokenType.PLUS: 'PLUS'>, ';': <TokenType.SEMICOLON: 'SEMICOLON'>, '/': <TokenType.SLASH: 'SLASH'>, '\\\\': <TokenType.BACKSLASH: 'BACKSLASH'>, '*': <TokenType.STAR: 'STAR'>, '~': <TokenType.TILDA: 'TILDA'>, '?': <TokenType.PLACEHOLDER: 'PLACEHOLDER'>, '@': <TokenType.PARAMETER: 'PARAMETER'>, '#': <TokenType.HASH: 'HASH'>, "'": <TokenType.UNKNOWN: 'UNKNOWN'>, '`': <TokenType.UNKNOWN: 'UNKNOWN'>, '"': <TokenType.UNKNOWN: 'UNKNOWN'>}"}, "sqlglot.tokens.Tokenizer.BIT_STRINGS": {"fullname": "sqlglot.tokens.Tokenizer.BIT_STRINGS", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.BIT_STRINGS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": List[Union[str, Tuple[str, str]]]", "default_value": "[]"}, "sqlglot.tokens.Tokenizer.BYTE_STRINGS": {"fullname": "sqlglot.tokens.Tokenizer.BYTE_STRINGS", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.BYTE_STRINGS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": List[Union[str, Tuple[str, str]]]", "default_value": "[]"}, "sqlglot.tokens.Tokenizer.HEX_STRINGS": {"fullname": "sqlglot.tokens.Tokenizer.HEX_STRINGS", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.HEX_STRINGS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": List[Union[str, Tuple[str, str]]]", "default_value": "[]"}, "sqlglot.tokens.Tokenizer.RAW_STRINGS": {"fullname": "sqlglot.tokens.Tokenizer.RAW_STRINGS", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.RAW_STRINGS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": List[Union[str, Tuple[str, str]]]", "default_value": "[]"}, "sqlglot.tokens.Tokenizer.HEREDOC_STRINGS": {"fullname": "sqlglot.tokens.Tokenizer.HEREDOC_STRINGS", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.HEREDOC_STRINGS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": List[Union[str, Tuple[str, str]]]", "default_value": "[]"}, "sqlglot.tokens.Tokenizer.UNICODE_STRINGS": {"fullname": "sqlglot.tokens.Tokenizer.UNICODE_STRINGS", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.UNICODE_STRINGS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": List[Union[str, Tuple[str, str]]]", "default_value": "[]"}, "sqlglot.tokens.Tokenizer.IDENTIFIERS": {"fullname": "sqlglot.tokens.Tokenizer.IDENTIFIERS", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.IDENTIFIERS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": List[Union[str, Tuple[str, str]]]", "default_value": "['"']"}, "sqlglot.tokens.Tokenizer.IDENTIFIER_ESCAPES": {"fullname": "sqlglot.tokens.Tokenizer.IDENTIFIER_ESCAPES", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.IDENTIFIER_ESCAPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "['"']"}, "sqlglot.tokens.Tokenizer.QUOTES": {"fullname": "sqlglot.tokens.Tokenizer.QUOTES", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.QUOTES", "kind": "variable", "doc": "<p></p>\n", "annotation": ": List[Union[str, Tuple[str, str]]]", "default_value": "["'"]"}, "sqlglot.tokens.Tokenizer.STRING_ESCAPES": {"fullname": "sqlglot.tokens.Tokenizer.STRING_ESCAPES", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.STRING_ESCAPES", "kind": "variable", "doc": "<p></p>\n", "default_value": "["'"]"}, "sqlglot.tokens.Tokenizer.VAR_SINGLE_TOKENS": {"fullname": "sqlglot.tokens.Tokenizer.VAR_SINGLE_TOKENS", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.VAR_SINGLE_TOKENS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Set[str]", "default_value": "set()"}, "sqlglot.tokens.Tokenizer.HEREDOC_TAG_IS_IDENTIFIER": {"fullname": "sqlglot.tokens.Tokenizer.HEREDOC_TAG_IS_IDENTIFIER", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.HEREDOC_TAG_IS_IDENTIFIER", "kind": "variable", "doc": "<p></p>\n", "default_value": "False"}, "sqlglot.tokens.Tokenizer.HEREDOC_STRING_ALTERNATIVE": {"fullname": "sqlglot.tokens.Tokenizer.HEREDOC_STRING_ALTERNATIVE", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.HEREDOC_STRING_ALTERNATIVE", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TokenType.VAR: 'VAR'>"}, "sqlglot.tokens.Tokenizer.KEYWORDS": {"fullname": "sqlglot.tokens.Tokenizer.KEYWORDS", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.KEYWORDS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, sqlglot.tokens.TokenType]", "default_value": "{'{%': <TokenType.BLOCK_START: 'BLOCK_START'>, '{%+': <TokenType.BLOCK_START: 'BLOCK_START'>, '{%-': <TokenType.BLOCK_START: 'BLOCK_START'>, '%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '+%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '-%}': <TokenType.BLOCK_END: 'BLOCK_END'>, '{{+': <TokenType.BLOCK_START: 'BLOCK_START'>, '{{-': <TokenType.BLOCK_START: 'BLOCK_START'>, '+}}': <TokenType.BLOCK_END: 'BLOCK_END'>, '-}}': <TokenType.BLOCK_END: 'BLOCK_END'>, '/*+': <TokenType.HINT: 'HINT'>, '==': <TokenType.EQ: 'EQ'>, '::': <TokenType.DCOLON: 'DCOLON'>, '||': <TokenType.DPIPE: 'DPIPE'>, '>=': <TokenType.GTE: 'GTE'>, '<=': <TokenType.LTE: 'LTE'>, '<>': <TokenType.NEQ: 'NEQ'>, '!=': <TokenType.NEQ: 'NEQ'>, ':=': <TokenType.COLON_EQ: 'COLON_EQ'>, '<=>': <TokenType.NULLSAFE_EQ: 'NULLSAFE_EQ'>, '->': <TokenType.ARROW: 'ARROW'>, '->>': <TokenType.DARROW: 'DARROW'>, '=>': <TokenType.FARROW: 'FARROW'>, '#>': <TokenType.HASH_ARROW: 'HASH_ARROW'>, '#>>': <TokenType.DHASH_ARROW: 'DHASH_ARROW'>, '<->': <TokenType.LR_ARROW: 'LR_ARROW'>, '&&': <TokenType.DAMP: 'DAMP'>, '??': <TokenType.DQMARK: 'DQMARK'>, 'ALL': <TokenType.ALL: 'ALL'>, 'ALWAYS': <TokenType.ALWAYS: 'ALWAYS'>, 'AND': <TokenType.AND: 'AND'>, 'ANTI': <TokenType.ANTI: 'ANTI'>, 'ANY': <TokenType.ANY: 'ANY'>, 'ASC': <TokenType.ASC: 'ASC'>, 'AS': <TokenType.ALIAS: 'ALIAS'>, 'ASOF': <TokenType.ASOF: 'ASOF'>, 'AUTOINCREMENT': <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, 'AUTO_INCREMENT': <TokenType.AUTO_INCREMENT: 'AUTO_INCREMENT'>, 'BEGIN': <TokenType.BEGIN: 'BEGIN'>, 'BETWEEN': <TokenType.BETWEEN: 'BETWEEN'>, 'CACHE': <TokenType.CACHE: 'CACHE'>, 'UNCACHE': <TokenType.UNCACHE: 'UNCACHE'>, 'CASE': <TokenType.CASE: 'CASE'>, 'CHARACTER SET': <TokenType.CHARACTER_SET: 'CHARACTER_SET'>, 'CLUSTER BY': <TokenType.CLUSTER_BY: 'CLUSTER_BY'>, 'COLLATE': <TokenType.COLLATE: 'COLLATE'>, 'COLUMN': <TokenType.COLUMN: 'COLUMN'>, 'COMMIT': <TokenType.COMMIT: 'COMMIT'>, 'CONNECT BY': <TokenType.CONNECT_BY: 'CONNECT_BY'>, 'CONSTRAINT': <TokenType.CONSTRAINT: 'CONSTRAINT'>, 'COPY': <TokenType.COPY: 'COPY'>, 'CREATE': <TokenType.CREATE: 'CREATE'>, 'CROSS': <TokenType.CROSS: 'CROSS'>, 'CUBE': <TokenType.CUBE: 'CUBE'>, 'CURRENT_DATE': <TokenType.CURRENT_DATE: 'CURRENT_DATE'>, 'CURRENT_TIME': <TokenType.CURRENT_TIME: 'CURRENT_TIME'>, 'CURRENT_TIMESTAMP': <TokenType.CURRENT_TIMESTAMP: 'CURRENT_TIMESTAMP'>, 'CURRENT_USER': <TokenType.CURRENT_USER: 'CURRENT_USER'>, 'DATABASE': <TokenType.DATABASE: 'DATABASE'>, 'DEFAULT': <TokenType.DEFAULT: 'DEFAULT'>, 'DELETE': <TokenType.DELETE: 'DELETE'>, 'DESC': <TokenType.DESC: 'DESC'>, 'DESCRIBE': <TokenType.DESCRIBE: 'DESCRIBE'>, 'DISTINCT': <TokenType.DISTINCT: 'DISTINCT'>, 'DISTRIBUTE BY': <TokenType.DISTRIBUTE_BY: 'DISTRIBUTE_BY'>, 'DIV': <TokenType.DIV: 'DIV'>, 'DROP': <TokenType.DROP: 'DROP'>, 'ELSE': <TokenType.ELSE: 'ELSE'>, 'END': <TokenType.END: 'END'>, 'ENUM': <TokenType.ENUM: 'ENUM'>, 'ESCAPE': <TokenType.ESCAPE: 'ESCAPE'>, 'EXCEPT': <TokenType.EXCEPT: 'EXCEPT'>, 'EXECUTE': <TokenType.EXECUTE: 'EXECUTE'>, 'EXISTS': <TokenType.EXISTS: 'EXISTS'>, 'FALSE': <TokenType.FALSE: 'FALSE'>, 'FETCH': <TokenType.FETCH: 'FETCH'>, 'FILTER': <TokenType.FILTER: 'FILTER'>, 'FIRST': <TokenType.FIRST: 'FIRST'>, 'FULL': <TokenType.FULL: 'FULL'>, 'FUNCTION': <TokenType.FUNCTION: 'FUNCTION'>, 'FOR': <TokenType.FOR: 'FOR'>, 'FOREIGN KEY': <TokenType.FOREIGN_KEY: 'FOREIGN_KEY'>, 'FORMAT': <TokenType.FORMAT: 'FORMAT'>, 'FROM': <TokenType.FROM: 'FROM'>, 'GEOGRAPHY': <TokenType.GEOGRAPHY: 'GEOGRAPHY'>, 'GEOMETRY': <TokenType.GEOMETRY: 'GEOMETRY'>, 'GLOB': <TokenType.GLOB: 'GLOB'>, 'GROUP BY': <TokenType.GROUP_BY: 'GROUP_BY'>, 'GROUPING SETS': <TokenType.GROUPING_SETS: 'GROUPING_SETS'>, 'HAVING': <TokenType.HAVING: 'HAVING'>, 'ILIKE': <TokenType.ILIKE: 'ILIKE'>, 'IN': <TokenType.IN: 'IN'>, 'INDEX': <TokenType.INDEX: 'INDEX'>, 'INET': <TokenType.INET: 'INET'>, 'INNER': <TokenType.INNER: 'INNER'>, 'INSERT': <TokenType.INSERT: 'INSERT'>, 'INTERVAL': <TokenType.INTERVAL: 'INTERVAL'>, 'INTERSECT': <TokenType.INTERSECT: 'INTERSECT'>, 'INTO': <TokenType.INTO: 'INTO'>, 'IS': <TokenType.IS: 'IS'>, 'ISNULL': <TokenType.ISNULL: 'ISNULL'>, 'JOIN': <TokenType.JOIN: 'JOIN'>, 'KEEP': <TokenType.KEEP: 'KEEP'>, 'KILL': <TokenType.KILL: 'KILL'>, 'LATERAL': <TokenType.LATERAL: 'LATERAL'>, 'LEFT': <TokenType.LEFT: 'LEFT'>, 'LIKE': <TokenType.LIKE: 'LIKE'>, 'LIMIT': <TokenType.LIMIT: 'LIMIT'>, 'LOAD': <TokenType.LOAD: 'LOAD'>, 'LOCK': <TokenType.LOCK: 'LOCK'>, 'MERGE': <TokenType.MERGE: 'MERGE'>, 'NATURAL': <TokenType.NATURAL: 'NATURAL'>, 'NEXT': <TokenType.NEXT: 'NEXT'>, 'NOT': <TokenType.NOT: 'NOT'>, 'NOTNULL': <TokenType.NOTNULL: 'NOTNULL'>, 'NULL': <TokenType.NULL: 'NULL'>, 'OBJECT': <TokenType.OBJECT: 'OBJECT'>, 'OFFSET': <TokenType.OFFSET: 'OFFSET'>, 'ON': <TokenType.ON: 'ON'>, 'OR': <TokenType.OR: 'OR'>, 'XOR': <TokenType.XOR: 'XOR'>, 'ORDER BY': <TokenType.ORDER_BY: 'ORDER_BY'>, 'ORDINALITY': <TokenType.ORDINALITY: 'ORDINALITY'>, 'OUTER': <TokenType.OUTER: 'OUTER'>, 'OVER': <TokenType.OVER: 'OVER'>, 'OVERLAPS': <TokenType.OVERLAPS: 'OVERLAPS'>, 'OVERWRITE': <TokenType.OVERWRITE: 'OVERWRITE'>, 'PARTITION': <TokenType.PARTITION: 'PARTITION'>, 'PARTITION BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PARTITIONED BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PARTITIONED_BY': <TokenType.PARTITION_BY: 'PARTITION_BY'>, 'PERCENT': <TokenType.PERCENT: 'PERCENT'>, 'PIVOT': <TokenType.PIVOT: 'PIVOT'>, 'PRAGMA': <TokenType.PRAGMA: 'PRAGMA'>, 'PRIMARY KEY': <TokenType.PRIMARY_KEY: 'PRIMARY_KEY'>, 'PROCEDURE': <TokenType.PROCEDURE: 'PROCEDURE'>, 'QUALIFY': <TokenType.QUALIFY: 'QUALIFY'>, 'RANGE': <TokenType.RANGE: 'RANGE'>, 'RECURSIVE': <TokenType.RECURSIVE: 'RECURSIVE'>, 'REGEXP': <TokenType.RLIKE: 'RLIKE'>, 'REPLACE': <TokenType.REPLACE: 'REPLACE'>, 'RETURNING': <TokenType.RETURNING: 'RETURNING'>, 'REFERENCES': <TokenType.REFERENCES: 'REFERENCES'>, 'RIGHT': <TokenType.RIGHT: 'RIGHT'>, 'RLIKE': <TokenType.RLIKE: 'RLIKE'>, 'ROLLBACK': <TokenType.ROLLBACK: 'ROLLBACK'>, 'ROLLUP': <TokenType.ROLLUP: 'ROLLUP'>, 'ROW': <TokenType.ROW: 'ROW'>, 'ROWS': <TokenType.ROWS: 'ROWS'>, 'SCHEMA': <TokenType.SCHEMA: 'SCHEMA'>, 'SELECT': <TokenType.SELECT: 'SELECT'>, 'SEMI': <TokenType.SEMI: 'SEMI'>, 'SET': <TokenType.SET: 'SET'>, 'SETTINGS': <TokenType.SETTINGS: 'SETTINGS'>, 'SHOW': <TokenType.SHOW: 'SHOW'>, 'SIMILAR TO': <TokenType.SIMILAR_TO: 'SIMILAR_TO'>, 'SOME': <TokenType.SOME: 'SOME'>, 'SORT BY': <TokenType.SORT_BY: 'SORT_BY'>, 'START WITH': <TokenType.START_WITH: 'START_WITH'>, 'TABLE': <TokenType.TABLE: 'TABLE'>, 'TABLESAMPLE': <TokenType.TABLE_SAMPLE: 'TABLE_SAMPLE'>, 'TEMP': <TokenType.TEMPORARY: 'TEMPORARY'>, 'TEMPORARY': <TokenType.TEMPORARY: 'TEMPORARY'>, 'THEN': <TokenType.THEN: 'THEN'>, 'TRUE': <TokenType.TRUE: 'TRUE'>, 'TRUNCATE': <TokenType.TRUNCATE: 'TRUNCATE'>, 'UNION': <TokenType.UNION: 'UNION'>, 'UNKNOWN': <TokenType.UNKNOWN: 'UNKNOWN'>, 'UNNEST': <TokenType.UNNEST: 'UNNEST'>, 'UNPIVOT': <TokenType.UNPIVOT: 'UNPIVOT'>, 'UPDATE': <TokenType.UPDATE: 'UPDATE'>, 'USE': <TokenType.USE: 'USE'>, 'USING': <TokenType.USING: 'USING'>, 'UUID': <TokenType.UUID: 'UUID'>, 'VALUES': <TokenType.VALUES: 'VALUES'>, 'VIEW': <TokenType.VIEW: 'VIEW'>, 'VOLATILE': <TokenType.VOLATILE: 'VOLATILE'>, 'WHEN': <TokenType.WHEN: 'WHEN'>, 'WHERE': <TokenType.WHERE: 'WHERE'>, 'WINDOW': <TokenType.WINDOW: 'WINDOW'>, 'WITH': <TokenType.WITH: 'WITH'>, 'APPLY': <TokenType.APPLY: 'APPLY'>, 'ARRAY': <TokenType.ARRAY: 'ARRAY'>, 'BIT': <TokenType.BIT: 'BIT'>, 'BOOL': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BOOLEAN': <TokenType.BOOLEAN: 'BOOLEAN'>, 'BYTE': <TokenType.TINYINT: 'TINYINT'>, 'MEDIUMINT': <TokenType.MEDIUMINT: 'MEDIUMINT'>, 'INT1': <TokenType.TINYINT: 'TINYINT'>, 'TINYINT': <TokenType.TINYINT: 'TINYINT'>, 'INT16': <TokenType.SMALLINT: 'SMALLINT'>, 'SHORT': <TokenType.SMALLINT: 'SMALLINT'>, 'SMALLINT': <TokenType.SMALLINT: 'SMALLINT'>, 'INT128': <TokenType.INT128: 'INT128'>, 'HUGEINT': <TokenType.INT128: 'INT128'>, 'INT2': <TokenType.SMALLINT: 'SMALLINT'>, 'INTEGER': <TokenType.INT: 'INT'>, 'INT': <TokenType.INT: 'INT'>, 'INT4': <TokenType.INT: 'INT'>, 'INT32': <TokenType.INT: 'INT'>, 'INT64': <TokenType.BIGINT: 'BIGINT'>, 'LONG': <TokenType.BIGINT: 'BIGINT'>, 'BIGINT': <TokenType.BIGINT: 'BIGINT'>, 'INT8': <TokenType.TINYINT: 'TINYINT'>, 'UINT': <TokenType.UINT: 'UINT'>, 'DEC': <TokenType.DECIMAL: 'DECIMAL'>, 'DECIMAL': <TokenType.DECIMAL: 'DECIMAL'>, 'BIGDECIMAL': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'BIGNUMERIC': <TokenType.BIGDECIMAL: 'BIGDECIMAL'>, 'MAP': <TokenType.MAP: 'MAP'>, 'NULLABLE': <TokenType.NULLABLE: 'NULLABLE'>, 'NUMBER': <TokenType.DECIMAL: 'DECIMAL'>, 'NUMERIC': <TokenType.DECIMAL: 'DECIMAL'>, 'FIXED': <TokenType.DECIMAL: 'DECIMAL'>, 'REAL': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT4': <TokenType.FLOAT: 'FLOAT'>, 'FLOAT8': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE': <TokenType.DOUBLE: 'DOUBLE'>, 'DOUBLE PRECISION': <TokenType.DOUBLE: 'DOUBLE'>, 'JSON': <TokenType.JSON: 'JSON'>, 'CHAR': <TokenType.CHAR: 'CHAR'>, 'CHARACTER': <TokenType.CHAR: 'CHAR'>, 'NCHAR': <TokenType.NCHAR: 'NCHAR'>, 'VARCHAR': <TokenType.VARCHAR: 'VARCHAR'>, 'VARCHAR2': <TokenType.VARCHAR: 'VARCHAR'>, 'NVARCHAR': <TokenType.NVARCHAR: 'NVARCHAR'>, 'NVARCHAR2': <TokenType.NVARCHAR: 'NVARCHAR'>, 'BPCHAR': <TokenType.BPCHAR: 'BPCHAR'>, 'STR': <TokenType.TEXT: 'TEXT'>, 'STRING': <TokenType.TEXT: 'TEXT'>, 'TEXT': <TokenType.TEXT: 'TEXT'>, 'LONGTEXT': <TokenType.LONGTEXT: 'LONGTEXT'>, 'MEDIUMTEXT': <TokenType.MEDIUMTEXT: 'MEDIUMTEXT'>, 'TINYTEXT': <TokenType.TINYTEXT: 'TINYTEXT'>, 'CLOB': <TokenType.TEXT: 'TEXT'>, 'LONGVARCHAR': <TokenType.TEXT: 'TEXT'>, 'BINARY': <TokenType.BINARY: 'BINARY'>, 'BLOB': <TokenType.VARBINARY: 'VARBINARY'>, 'LONGBLOB': <TokenType.LONGBLOB: 'LONGBLOB'>, 'MEDIUMBLOB': <TokenType.MEDIUMBLOB: 'MEDIUMBLOB'>, 'TINYBLOB': <TokenType.TINYBLOB: 'TINYBLOB'>, 'BYTEA': <TokenType.VARBINARY: 'VARBINARY'>, 'VARBINARY': <TokenType.VARBINARY: 'VARBINARY'>, 'TIME': <TokenType.TIME: 'TIME'>, 'TIMETZ': <TokenType.TIMETZ: 'TIMETZ'>, 'TIMESTAMP': <TokenType.TIMESTAMP: 'TIMESTAMP'>, 'TIMESTAMPTZ': <TokenType.TIMESTAMPTZ: 'TIMESTAMPTZ'>, 'TIMESTAMPLTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMP_LTZ': <TokenType.TIMESTAMPLTZ: 'TIMESTAMPLTZ'>, 'TIMESTAMPNTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'TIMESTAMP_NTZ': <TokenType.TIMESTAMPNTZ: 'TIMESTAMPNTZ'>, 'DATE': <TokenType.DATE: 'DATE'>, 'DATETIME': <TokenType.DATETIME: 'DATETIME'>, 'INT4RANGE': <TokenType.INT4RANGE: 'INT4RANGE'>, 'INT4MULTIRANGE': <TokenType.INT4MULTIRANGE: 'INT4MULTIRANGE'>, 'INT8RANGE': <TokenType.INT8RANGE: 'INT8RANGE'>, 'INT8MULTIRANGE': <TokenType.INT8MULTIRANGE: 'INT8MULTIRANGE'>, 'NUMRANGE': <TokenType.NUMRANGE: 'NUMRANGE'>, 'NUMMULTIRANGE': <TokenType.NUMMULTIRANGE: 'NUMMULTIRANGE'>, 'TSRANGE': <TokenType.TSRANGE: 'TSRANGE'>, 'TSMULTIRANGE': <TokenType.TSMULTIRANGE: 'TSMULTIRANGE'>, 'TSTZRANGE': <TokenType.TSTZRANGE: 'TSTZRANGE'>, 'TSTZMULTIRANGE': <TokenType.TSTZMULTIRANGE: 'TSTZMULTIRANGE'>, 'DATERANGE': <TokenType.DATERANGE: 'DATERANGE'>, 'DATEMULTIRANGE': <TokenType.DATEMULTIRANGE: 'DATEMULTIRANGE'>, 'UNIQUE': <TokenType.UNIQUE: 'UNIQUE'>, 'STRUCT': <TokenType.STRUCT: 'STRUCT'>, 'SEQUENCE': <TokenType.SEQUENCE: 'SEQUENCE'>, 'VARIANT': <TokenType.VARIANT: 'VARIANT'>, 'ALTER': <TokenType.ALTER: 'ALTER'>, 'ANALYZE': <TokenType.COMMAND: 'COMMAND'>, 'CALL': <TokenType.COMMAND: 'COMMAND'>, 'COMMENT': <TokenType.COMMENT: 'COMMENT'>, 'EXPLAIN': <TokenType.COMMAND: 'COMMAND'>, 'GRANT': <TokenType.COMMAND: 'COMMAND'>, 'OPTIMIZE': <TokenType.COMMAND: 'COMMAND'>, 'PREPARE': <TokenType.COMMAND: 'COMMAND'>, 'VACUUM': <TokenType.COMMAND: 'COMMAND'>, 'USER-DEFINED': <TokenType.USERDEFINED: 'USERDEFINED'>, 'FOR VERSION': <TokenType.VERSION_SNAPSHOT: 'VERSION_SNAPSHOT'>, 'FOR TIMESTAMP': <TokenType.TIMESTAMP_SNAPSHOT: 'TIMESTAMP_SNAPSHOT'>}"}, "sqlglot.tokens.Tokenizer.WHITE_SPACE": {"fullname": "sqlglot.tokens.Tokenizer.WHITE_SPACE", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.WHITE_SPACE", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[Optional[str], sqlglot.tokens.TokenType]", "default_value": "{' ': <TokenType.SPACE: 'SPACE'>, '\\t': <TokenType.SPACE: 'SPACE'>, '\\n': <TokenType.BREAK: 'BREAK'>, '\\r': <TokenType.BREAK: 'BREAK'>}"}, "sqlglot.tokens.Tokenizer.COMMANDS": {"fullname": "sqlglot.tokens.Tokenizer.COMMANDS", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.COMMANDS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.SHOW: 'SHOW'>, <TokenType.EXECUTE: 'EXECUTE'>, <TokenType.FETCH: 'FETCH'>, <TokenType.COMMAND: 'COMMAND'>}"}, "sqlglot.tokens.Tokenizer.COMMAND_PREFIX_TOKENS": {"fullname": "sqlglot.tokens.Tokenizer.COMMAND_PREFIX_TOKENS", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.COMMAND_PREFIX_TOKENS", "kind": "variable", "doc": "<p></p>\n", "default_value": "{<TokenType.BEGIN: 'BEGIN'>, <TokenType.SEMICOLON: 'SEMICOLON'>}"}, "sqlglot.tokens.Tokenizer.NUMERIC_LITERALS": {"fullname": "sqlglot.tokens.Tokenizer.NUMERIC_LITERALS", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.NUMERIC_LITERALS", "kind": "variable", "doc": "<p></p>\n", "annotation": ": Dict[str, str]", "default_value": "{}"}, "sqlglot.tokens.Tokenizer.COMMENTS": {"fullname": "sqlglot.tokens.Tokenizer.COMMENTS", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.COMMENTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "['--', ('/*', '*/')]"}, "sqlglot.tokens.Tokenizer.dialect": {"fullname": "sqlglot.tokens.Tokenizer.dialect", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.dialect", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.tokens.Tokenizer.reset": {"fullname": "sqlglot.tokens.Tokenizer.reset", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.reset", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span></span><span class=\"return-annotation\">) -> <span class=\"kc\">None</span>:</span></span>", "funcdef": "def"}, "sqlglot.tokens.Tokenizer.tokenize": {"fullname": "sqlglot.tokens.Tokenizer.tokenize", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.tokenize", "kind": "function", "doc": "<p>Returns a list of tokens corresponding to the SQL string <code>sql</code>.</p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">sql</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">tokens</span><span class=\"o\">.</span><span class=\"n\">Token</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.tokens.Tokenizer.tokenize_rs": {"fullname": "sqlglot.tokens.Tokenizer.tokenize_rs", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.tokenize_rs", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code condensed\">(<span class=\"param\"><span class=\"bp\">self</span>, </span><span class=\"param\"><span class=\"n\">sql</span><span class=\"p\">:</span> <span class=\"nb\">str</span></span><span class=\"return-annotation\">) -> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">tokens</span><span class=\"o\">.</span><span class=\"n\">Token</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.tokens.Tokenizer.size": {"fullname": "sqlglot.tokens.Tokenizer.size", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.size", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.tokens.Tokenizer.sql": {"fullname": "sqlglot.tokens.Tokenizer.sql", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.sql", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.tokens.Tokenizer.tokens": {"fullname": "sqlglot.tokens.Tokenizer.tokens", "modulename": "sqlglot.tokens", "qualname": "Tokenizer.tokens", "kind": "variable", "doc": "<p></p>\n"}, "sqlglot.transforms": {"fullname": "sqlglot.transforms", "modulename": "sqlglot.transforms", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.transforms.unalias_group": {"fullname": "sqlglot.transforms.unalias_group", "modulename": "sqlglot.transforms", "qualname": "unalias_group", "kind": "function", "doc": "<p>Replace references to select aliases in GROUP BY clauses.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"kn\">import</span> <span class=\"nn\">sqlglot</span>\n<span class=\"gp\">>>> </span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">parse_one</span><span class=\"p\">(</span><span class=\"s2\">"SELECT a AS b FROM x GROUP BY b"</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">transform</span><span class=\"p\">(</span><span class=\"n\">unalias_group</span><span class=\"p\">)</span><span class=\"o\">.</span><span class=\"n\">sql</span><span class=\"p\">()</span>\n<span class=\"go\">'SELECT a AS b FROM x GROUP BY 1'</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> the expression that will be transformed.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The transformed expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.transforms.eliminate_distinct_on": {"fullname": "sqlglot.transforms.eliminate_distinct_on", "modulename": "sqlglot.transforms", "qualname": "eliminate_distinct_on", "kind": "function", "doc": "<p>Convert SELECT DISTINCT ON statements to a subquery with a window function.</p>\n\n<p>This is useful for dialects that don't support SELECT DISTINCT ON but support window functions.</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>expression:</strong> the expression that will be transformed.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The transformed expression.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.transforms.eliminate_qualify": {"fullname": "sqlglot.transforms.eliminate_qualify", "modulename": "sqlglot.transforms", "qualname": "eliminate_qualify", "kind": "function", "doc": "<p>Convert SELECT statements that contain the QUALIFY clause into subqueries, filtered equivalently.</p>\n\n<p>The idea behind this transformation can be seen in Snowflake's documentation for QUALIFY:\n<a href=\"https://docs.snowflake.com/en/sql-reference/constructs/qualify\">https://docs.snowflake.com/en/sql-reference/constructs/qualify</a></p>\n\n<p>Some dialects don't support window functions in the WHERE clause, so we need to include them as\nprojections in the subquery, in order to refer to them in the outer filter using aliases. Also,\nif a column is referenced in the QUALIFY clause but is not selected, we need to include it too,\notherwise we won't be able to refer to it in the outer query's WHERE clause. Finally, if a\nnewly aliased projection is referenced in the QUALIFY clause, it will be replaced by the\ncorresponding expression to avoid creating invalid column references.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.transforms.remove_precision_parameterized_types": {"fullname": "sqlglot.transforms.remove_precision_parameterized_types", "modulename": "sqlglot.transforms", "qualname": "remove_precision_parameterized_types", "kind": "function", "doc": "<p>Some dialects only allow the precision for parameterized types to be defined in the DDL and not in\nother expressions. This transforms removes the precision from parameterized types in expressions.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.transforms.unqualify_unnest": {"fullname": "sqlglot.transforms.unqualify_unnest", "modulename": "sqlglot.transforms", "qualname": "unqualify_unnest", "kind": "function", "doc": "<p>Remove references to unnest table aliases, added by the optimizer's qualify_columns step.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.transforms.unnest_to_explode": {"fullname": "sqlglot.transforms.unnest_to_explode", "modulename": "sqlglot.transforms", "qualname": "unnest_to_explode", "kind": "function", "doc": "<p>Convert cross join unnest into lateral view explode.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.transforms.explode_to_unnest": {"fullname": "sqlglot.transforms.explode_to_unnest", "modulename": "sqlglot.transforms", "qualname": "explode_to_unnest", "kind": "function", "doc": "<p>Convert explode/posexplode into unnest.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">index_offset</span><span class=\"p\">:</span> <span class=\"nb\">int</span> <span class=\"o\">=</span> <span class=\"mi\">0</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">],</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.transforms.add_within_group_for_percentiles": {"fullname": "sqlglot.transforms.add_within_group_for_percentiles", "modulename": "sqlglot.transforms", "qualname": "add_within_group_for_percentiles", "kind": "function", "doc": "<p>Transforms percentiles by adding a WITHIN GROUP clause to them.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.transforms.remove_within_group_for_percentiles": {"fullname": "sqlglot.transforms.remove_within_group_for_percentiles", "modulename": "sqlglot.transforms", "qualname": "remove_within_group_for_percentiles", "kind": "function", "doc": "<p>Transforms percentiles by getting rid of their corresponding WITHIN GROUP clause.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.transforms.add_recursive_cte_column_names": {"fullname": "sqlglot.transforms.add_recursive_cte_column_names", "modulename": "sqlglot.transforms", "qualname": "add_recursive_cte_column_names", "kind": "function", "doc": "<p>Uses projection output names in recursive CTE definitions to define the CTEs' columns.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.transforms.epoch_cast_to_ts": {"fullname": "sqlglot.transforms.epoch_cast_to_ts", "modulename": "sqlglot.transforms", "qualname": "epoch_cast_to_ts", "kind": "function", "doc": "<p>Replace 'epoch' in casts by the equivalent date literal.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.transforms.eliminate_semi_and_anti_joins": {"fullname": "sqlglot.transforms.eliminate_semi_and_anti_joins", "modulename": "sqlglot.transforms", "qualname": "eliminate_semi_and_anti_joins", "kind": "function", "doc": "<p>Convert SEMI and ANTI joins into equivalent forms that use EXIST instead.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.transforms.eliminate_full_outer_join": {"fullname": "sqlglot.transforms.eliminate_full_outer_join", "modulename": "sqlglot.transforms", "qualname": "eliminate_full_outer_join", "kind": "function", "doc": "<p>Converts a query with a FULL OUTER join to a union of identical queries that\nuse LEFT/RIGHT OUTER joins instead. This transformation currently only works\nfor queries that have a single FULL OUTER join.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.transforms.move_ctes_to_top_level": {"fullname": "sqlglot.transforms.move_ctes_to_top_level", "modulename": "sqlglot.transforms", "qualname": "move_ctes_to_top_level", "kind": "function", "doc": "<p>Some dialects (e.g. Hive, T-SQL, Spark prior to version 3) only allow CTEs to be\ndefined at the top-level, so for example queries like:</p>\n\n<pre><code>SELECT * FROM (WITH t(c) AS (SELECT 1) SELECT * FROM t) AS subq\n</code></pre>\n\n<p>are invalid in those dialects. This transformation can be used to ensure all CTEs are\nmoved to the top level so that the final SQL code is valid from a syntax standpoint.</p>\n\n<p>TODO: handle name clashes whilst moving CTEs (it can get quite tricky & costly).</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.transforms.ensure_bools": {"fullname": "sqlglot.transforms.ensure_bools", "modulename": "sqlglot.transforms", "qualname": "ensure_bools", "kind": "function", "doc": "<p>Converts numeric values used in conditions into explicit boolean expressions.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.transforms.unqualify_columns": {"fullname": "sqlglot.transforms.unqualify_columns", "modulename": "sqlglot.transforms", "qualname": "unqualify_columns", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.transforms.remove_unique_constraints": {"fullname": "sqlglot.transforms.remove_unique_constraints", "modulename": "sqlglot.transforms", "qualname": "remove_unique_constraints", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.transforms.ctas_with_tmp_tables_to_create_tmp_view": {"fullname": "sqlglot.transforms.ctas_with_tmp_tables_to_create_tmp_view", "modulename": "sqlglot.transforms", "qualname": "ctas_with_tmp_tables_to_create_tmp_view", "kind": "function", "doc": "<p></p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>,</span><span class=\"param\">\t<span class=\"n\">tmp_storage_provider</span><span class=\"p\">:</span> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">],</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"o\"><</span><span class=\"n\">function</span> <span class=\"o\"><</span><span class=\"k\">lambda</span><span class=\"o\">>></span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.transforms.move_schema_columns_to_partitioned_by": {"fullname": "sqlglot.transforms.move_schema_columns_to_partitioned_by", "modulename": "sqlglot.transforms", "qualname": "move_schema_columns_to_partitioned_by", "kind": "function", "doc": "<p>In Hive, the PARTITIONED BY property acts as an extension of a table's schema. When the\nPARTITIONED BY value is an array of column names, they are transformed into a schema.\nThe corresponding columns are removed from the create statement.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.transforms.move_partitioned_by_to_schema_columns": {"fullname": "sqlglot.transforms.move_partitioned_by_to_schema_columns", "modulename": "sqlglot.transforms", "qualname": "move_partitioned_by_to_schema_columns", "kind": "function", "doc": "<p>Spark 3 supports both \"HIVEFORMAT\" and \"DATASOURCE\" formats for CREATE TABLE.</p>\n\n<p>Currently, SQLGlot uses the DATASOURCE format for Spark 3.</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.transforms.struct_kv_to_alias": {"fullname": "sqlglot.transforms.struct_kv_to_alias", "modulename": "sqlglot.transforms", "qualname": "struct_kv_to_alias", "kind": "function", "doc": "<p>Converts struct arguments to aliases, e.g. STRUCT(1 AS y).</p>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">expression</span><span class=\"p\">:</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span></span><span class=\"return-annotation\">) -> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span>:</span></span>", "funcdef": "def"}, "sqlglot.transforms.preprocess": {"fullname": "sqlglot.transforms.preprocess", "modulename": "sqlglot.transforms", "qualname": "preprocess", "kind": "function", "doc": "<p>Creates a new transform by chaining a sequence of transformations and converts the resulting\nexpression to SQL, using either the \"_sql\" method corresponding to the resulting expression,\nor the appropriate <code>Generator.TRANSFORMS</code> function (when applicable -- see below).</p>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>transforms:</strong> sequence of transform functions. These will be called in order.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>Function that can be used as a generator transform.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">transforms</span><span class=\"p\">:</span> <span class=\"n\">List</span><span class=\"p\">[</span><span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">],</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">]]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Callable</span><span class=\"p\">[[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">generator</span><span class=\"o\">.</span><span class=\"n\">Generator</span><span class=\"p\">,</span> <span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">expressions</span><span class=\"o\">.</span><span class=\"n\">Expression</span><span class=\"p\">],</span> <span class=\"nb\">str</span><span class=\"p\">]</span>:</span></span>", "funcdef": "def"}, "sqlglot.trie": {"fullname": "sqlglot.trie", "modulename": "sqlglot.trie", "kind": "module", "doc": "<p></p>\n"}, "sqlglot.trie.key": {"fullname": "sqlglot.trie.key", "modulename": "sqlglot.trie", "qualname": "key", "kind": "variable", "doc": "<p></p>\n", "default_value": "typing.Sequence[typing.Hashable]"}, "sqlglot.trie.TrieResult": {"fullname": "sqlglot.trie.TrieResult", "modulename": "sqlglot.trie", "qualname": "TrieResult", "kind": "class", "doc": "<p>An enumeration.</p>\n", "bases": "enum.Enum"}, "sqlglot.trie.TrieResult.FAILED": {"fullname": "sqlglot.trie.TrieResult.FAILED", "modulename": "sqlglot.trie", "qualname": "TrieResult.FAILED", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TrieResult.FAILED: 1>"}, "sqlglot.trie.TrieResult.PREFIX": {"fullname": "sqlglot.trie.TrieResult.PREFIX", "modulename": "sqlglot.trie", "qualname": "TrieResult.PREFIX", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TrieResult.PREFIX: 2>"}, "sqlglot.trie.TrieResult.EXISTS": {"fullname": "sqlglot.trie.TrieResult.EXISTS", "modulename": "sqlglot.trie", "qualname": "TrieResult.EXISTS", "kind": "variable", "doc": "<p></p>\n", "default_value": "<TrieResult.EXISTS: 3>"}, "sqlglot.trie.new_trie": {"fullname": "sqlglot.trie.new_trie", "modulename": "sqlglot.trie", "qualname": "new_trie", "kind": "function", "doc": "<p>Creates a new trie out of a collection of keywords.</p>\n\n<p>The trie is represented as a sequence of nested dictionaries keyed by either single\ncharacter strings, or by 0, which is used to designate that a keyword is in the trie.</p>\n\n<h6 id=\"example\">Example:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">new_trie</span><span class=\"p\">([</span><span class=\"s2\">"bla"</span><span class=\"p\">,</span> <span class=\"s2\">"foo"</span><span class=\"p\">,</span> <span class=\"s2\">"blab"</span><span class=\"p\">])</span>\n<span class=\"go\">{'b': {'l': {'a': {0: True, 'b': {0: True}}}}, 'f': {'o': {'o': {0: True}}}}</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>keywords:</strong> the keywords to create the trie from.</li>\n<li><strong>trie:</strong> a trie to mutate instead of creating a new one</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>The trie corresponding to <code>keywords</code>.</p>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">keywords</span><span class=\"p\">:</span> <span class=\"n\">Iterable</span><span class=\"p\">[</span><span class=\"n\">Sequence</span><span class=\"p\">[</span><span class=\"n\">Hashable</span><span class=\"p\">]]</span>,</span><span class=\"param\">\t<span class=\"n\">trie</span><span class=\"p\">:</span> <span class=\"n\">Optional</span><span class=\"p\">[</span><span class=\"n\">Dict</span><span class=\"p\">]</span> <span class=\"o\">=</span> <span class=\"kc\">None</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Dict</span>:</span></span>", "funcdef": "def"}, "sqlglot.trie.in_trie": {"fullname": "sqlglot.trie.in_trie", "modulename": "sqlglot.trie", "qualname": "in_trie", "kind": "function", "doc": "<p>Checks whether a key is in a trie.</p>\n\n<h6 id=\"examples\">Examples:</h6>\n\n<blockquote>\n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">in_trie</span><span class=\"p\">(</span><span class=\"n\">new_trie</span><span class=\"p\">([</span><span class=\"s2\">"cat"</span><span class=\"p\">]),</span> <span class=\"s2\">"bob"</span><span class=\"p\">)</span>\n<span class=\"go\">(<TrieResult.FAILED: 1>, {'c': {'a': {'t': {0: True}}}})</span>\n</code></pre>\n </div>\n \n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">in_trie</span><span class=\"p\">(</span><span class=\"n\">new_trie</span><span class=\"p\">([</span><span class=\"s2\">"cat"</span><span class=\"p\">]),</span> <span class=\"s2\">"ca"</span><span class=\"p\">)</span>\n<span class=\"go\">(<TrieResult.PREFIX: 2>, {'t': {0: True}})</span>\n</code></pre>\n </div>\n \n <div class=\"pdoc-code codehilite\">\n<pre><span></span><code><span class=\"gp\">>>> </span><span class=\"n\">in_trie</span><span class=\"p\">(</span><span class=\"n\">new_trie</span><span class=\"p\">([</span><span class=\"s2\">"cat"</span><span class=\"p\">]),</span> <span class=\"s2\">"cat"</span><span class=\"p\">)</span>\n<span class=\"go\">(<TrieResult.EXISTS: 3>, {0: True})</span>\n</code></pre>\n </div>\n</blockquote>\n\n<h6 id=\"arguments\">Arguments:</h6>\n\n<ul>\n<li><strong>trie:</strong> The trie to be searched.</li>\n<li><strong>key:</strong> The target key.</li>\n</ul>\n\n<h6 id=\"returns\">Returns:</h6>\n\n<blockquote>\n <p>A pair <code>(value, subtrie)</code>, where <code>subtrie</code> is the sub-trie we get at the point\n where the search stops, and <code>value</code> is a TrieResult value that can be one of:</p>\n \n <ul>\n <li>TrieResult.FAILED: the search was unsuccessful</li>\n <li>TrieResult.PREFIX: <code>value</code> is a prefix of a keyword in <code>trie</code></li>\n <li>TrieResult.EXISTS: <code>key</code> exists in <code>trie</code></li>\n </ul>\n</blockquote>\n", "signature": "<span class=\"signature pdoc-code multiline\">(<span class=\"param\">\t<span class=\"n\">trie</span><span class=\"p\">:</span> <span class=\"n\">Dict</span>,</span><span class=\"param\">\t<span class=\"n\">key</span><span class=\"p\">:</span> <span class=\"n\">Sequence</span><span class=\"p\">[</span><span class=\"n\">Hashable</span><span class=\"p\">]</span></span><span class=\"return-annotation\">) -> <span class=\"n\">Tuple</span><span class=\"p\">[</span><span class=\"n\">sqlglot</span><span class=\"o\">.</span><span class=\"n\">trie</span><span class=\"o\">.</span><span class=\"n\">TrieResult</span><span class=\"p\">,</span> <span class=\"n\">Dict</span><span class=\"p\">]</span>:</span></span> |