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from sqlglot import exp
from sqlglot.helper import ensure_collection, ensure_list, subclasses
from sqlglot.optimizer.scope import Scope, traverse_scope
from sqlglot.schema import ensure_schema
def annotate_types(expression, schema=None, annotators=None, coerces_to=None):
"""
Recursively infer & annotate types in an expression syntax tree against a schema.
Assumes that we've already executed the optimizer's qualify_columns step.
Example:
>>> import sqlglot
>>> schema = {"y": {"cola": "SMALLINT"}}
>>> sql = "SELECT x.cola + 2.5 AS cola FROM (SELECT y.cola AS cola FROM y AS y) AS x"
>>> annotated_expr = annotate_types(sqlglot.parse_one(sql), schema=schema)
>>> annotated_expr.expressions[0].type # Get the type of "x.cola + 2.5 AS cola"
<Type.DOUBLE: 'DOUBLE'>
Args:
expression (sqlglot.Expression): Expression to annotate.
schema (dict|sqlglot.optimizer.Schema): Database schema.
annotators (dict): Maps expression type to corresponding annotation function.
coerces_to (dict): Maps expression type to set of types that it can be coerced into.
Returns:
sqlglot.Expression: expression annotated with types
"""
schema = ensure_schema(schema)
return TypeAnnotator(schema, annotators, coerces_to).annotate(expression)
class TypeAnnotator:
ANNOTATORS = {
**{
expr_type: lambda self, expr: self._annotate_unary(expr)
for expr_type in subclasses(exp.__name__, exp.Unary)
},
**{
expr_type: lambda self, expr: self._annotate_binary(expr)
for expr_type in subclasses(exp.__name__, exp.Binary)
},
exp.Cast: lambda self, expr: self._annotate_with_type(expr, expr.args["to"].this),
exp.DataType: lambda self, expr: self._annotate_with_type(expr, expr.this),
exp.Alias: lambda self, expr: self._annotate_unary(expr),
exp.Literal: lambda self, expr: self._annotate_literal(expr),
exp.Boolean: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.BOOLEAN),
exp.Null: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.NULL),
exp.Anonymous: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.UNKNOWN),
exp.ApproxDistinct: lambda self, expr: self._annotate_with_type(
expr, exp.DataType.Type.BIGINT
),
exp.Avg: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.DOUBLE),
exp.Ceil: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.INT),
exp.Count: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.BIGINT),
exp.CurrentDate: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.DATE),
exp.CurrentDatetime: lambda self, expr: self._annotate_with_type(
expr, exp.DataType.Type.DATETIME
),
exp.CurrentTime: lambda self, expr: self._annotate_with_type(
expr, exp.DataType.Type.TIMESTAMP
),
exp.CurrentTimestamp: lambda self, expr: self._annotate_with_type(
expr, exp.DataType.Type.TIMESTAMP
),
exp.DateAdd: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.DATE),
exp.DateSub: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.DATE),
exp.DateDiff: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.INT),
exp.DatetimeAdd: lambda self, expr: self._annotate_with_type(
expr, exp.DataType.Type.DATETIME
),
exp.DatetimeSub: lambda self, expr: self._annotate_with_type(
expr, exp.DataType.Type.DATETIME
),
exp.DatetimeDiff: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.INT),
exp.Extract: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.INT),
exp.TimestampAdd: lambda self, expr: self._annotate_with_type(
expr, exp.DataType.Type.TIMESTAMP
),
exp.TimestampSub: lambda self, expr: self._annotate_with_type(
expr, exp.DataType.Type.TIMESTAMP
),
exp.TimestampDiff: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.INT),
exp.TimeAdd: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.TIMESTAMP),
exp.TimeSub: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.TIMESTAMP),
exp.TimeDiff: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.INT),
exp.DateStrToDate: lambda self, expr: self._annotate_with_type(
expr, exp.DataType.Type.DATE
),
exp.DateToDateStr: lambda self, expr: self._annotate_with_type(
expr, exp.DataType.Type.VARCHAR
),
exp.DateToDi: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.INT),
exp.Day: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.TINYINT),
exp.DiToDate: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.DATE),
exp.Exp: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.DOUBLE),
exp.Floor: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.INT),
exp.Case: lambda self, expr: self._annotate_by_args(expr, "default", "ifs"),
exp.If: lambda self, expr: self._annotate_by_args(expr, "true", "false"),
exp.Coalesce: lambda self, expr: self._annotate_by_args(expr, "this", "expressions"),
exp.IfNull: lambda self, expr: self._annotate_by_args(expr, "this", "expression"),
exp.ConcatWs: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.VARCHAR),
exp.GroupConcat: lambda self, expr: self._annotate_with_type(
expr, exp.DataType.Type.VARCHAR
),
exp.ArrayConcat: lambda self, expr: self._annotate_with_type(
expr, exp.DataType.Type.VARCHAR
),
exp.Initcap: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.VARCHAR),
exp.Length: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.BIGINT),
exp.Levenshtein: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.INT),
exp.Ln: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.DOUBLE),
exp.Log: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.DOUBLE),
exp.Log2: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.DOUBLE),
exp.Log10: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.DOUBLE),
exp.Lower: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.VARCHAR),
exp.Month: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.TINYINT),
exp.Pow: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.DOUBLE),
exp.Quantile: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.DOUBLE),
exp.ApproxQuantile: lambda self, expr: self._annotate_with_type(
expr, exp.DataType.Type.DOUBLE
),
exp.RegexpLike: lambda self, expr: self._annotate_with_type(
expr, exp.DataType.Type.BOOLEAN
),
exp.Round: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.DOUBLE),
exp.SafeDivide: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.DOUBLE),
exp.Substring: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.VARCHAR),
exp.StrPosition: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.INT),
exp.StrToDate: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.DATE),
exp.StrToTime: lambda self, expr: self._annotate_with_type(
expr, exp.DataType.Type.TIMESTAMP
),
exp.Sqrt: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.DOUBLE),
exp.Stddev: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.DOUBLE),
exp.StddevPop: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.DOUBLE),
exp.StddevSamp: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.DOUBLE),
exp.TimeToStr: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.VARCHAR),
exp.TimeToTimeStr: lambda self, expr: self._annotate_with_type(
expr, exp.DataType.Type.VARCHAR
),
exp.TimeStrToDate: lambda self, expr: self._annotate_with_type(
expr, exp.DataType.Type.DATE
),
exp.TimeStrToTime: lambda self, expr: self._annotate_with_type(
expr, exp.DataType.Type.TIMESTAMP
),
exp.Trim: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.VARCHAR),
exp.TsOrDsToDateStr: lambda self, expr: self._annotate_with_type(
expr, exp.DataType.Type.VARCHAR
),
exp.TsOrDsToDate: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.DATE),
exp.TsOrDiToDi: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.INT),
exp.UnixToStr: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.VARCHAR),
exp.UnixToTime: lambda self, expr: self._annotate_with_type(
expr, exp.DataType.Type.TIMESTAMP
),
exp.UnixToTimeStr: lambda self, expr: self._annotate_with_type(
expr, exp.DataType.Type.VARCHAR
),
exp.Upper: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.VARCHAR),
exp.Variance: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.DOUBLE),
exp.VariancePop: lambda self, expr: self._annotate_with_type(
expr, exp.DataType.Type.DOUBLE
),
exp.Week: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.TINYINT),
exp.Year: lambda self, expr: self._annotate_with_type(expr, exp.DataType.Type.TINYINT),
}
# Reference: https://spark.apache.org/docs/3.2.0/sql-ref-ansi-compliance.html
COERCES_TO = {
# CHAR < NCHAR < VARCHAR < NVARCHAR < TEXT
exp.DataType.Type.TEXT: set(),
exp.DataType.Type.NVARCHAR: {exp.DataType.Type.TEXT},
exp.DataType.Type.VARCHAR: {exp.DataType.Type.NVARCHAR, exp.DataType.Type.TEXT},
exp.DataType.Type.NCHAR: {
exp.DataType.Type.VARCHAR,
exp.DataType.Type.NVARCHAR,
exp.DataType.Type.TEXT,
},
exp.DataType.Type.CHAR: {
exp.DataType.Type.NCHAR,
exp.DataType.Type.VARCHAR,
exp.DataType.Type.NVARCHAR,
exp.DataType.Type.TEXT,
},
# TINYINT < SMALLINT < INT < BIGINT < DECIMAL < FLOAT < DOUBLE
exp.DataType.Type.DOUBLE: set(),
exp.DataType.Type.FLOAT: {exp.DataType.Type.DOUBLE},
exp.DataType.Type.DECIMAL: {exp.DataType.Type.FLOAT, exp.DataType.Type.DOUBLE},
exp.DataType.Type.BIGINT: {
exp.DataType.Type.DECIMAL,
exp.DataType.Type.FLOAT,
exp.DataType.Type.DOUBLE,
},
exp.DataType.Type.INT: {
exp.DataType.Type.BIGINT,
exp.DataType.Type.DECIMAL,
exp.DataType.Type.FLOAT,
exp.DataType.Type.DOUBLE,
},
exp.DataType.Type.SMALLINT: {
exp.DataType.Type.INT,
exp.DataType.Type.BIGINT,
exp.DataType.Type.DECIMAL,
exp.DataType.Type.FLOAT,
exp.DataType.Type.DOUBLE,
},
exp.DataType.Type.TINYINT: {
exp.DataType.Type.SMALLINT,
exp.DataType.Type.INT,
exp.DataType.Type.BIGINT,
exp.DataType.Type.DECIMAL,
exp.DataType.Type.FLOAT,
exp.DataType.Type.DOUBLE,
},
# DATE < DATETIME < TIMESTAMP < TIMESTAMPTZ < TIMESTAMPLTZ
exp.DataType.Type.TIMESTAMPLTZ: set(),
exp.DataType.Type.TIMESTAMPTZ: {exp.DataType.Type.TIMESTAMPLTZ},
exp.DataType.Type.TIMESTAMP: {
exp.DataType.Type.TIMESTAMPTZ,
exp.DataType.Type.TIMESTAMPLTZ,
},
exp.DataType.Type.DATETIME: {
exp.DataType.Type.TIMESTAMP,
exp.DataType.Type.TIMESTAMPTZ,
exp.DataType.Type.TIMESTAMPLTZ,
},
exp.DataType.Type.DATE: {
exp.DataType.Type.DATETIME,
exp.DataType.Type.TIMESTAMP,
exp.DataType.Type.TIMESTAMPTZ,
exp.DataType.Type.TIMESTAMPLTZ,
},
}
TRAVERSABLES = (exp.Select, exp.Union, exp.UDTF, exp.Subquery)
def __init__(self, schema=None, annotators=None, coerces_to=None):
self.schema = schema
self.annotators = annotators or self.ANNOTATORS
self.coerces_to = coerces_to or self.COERCES_TO
def annotate(self, expression):
if isinstance(expression, self.TRAVERSABLES):
for scope in traverse_scope(expression):
selects = {}
for name, source in scope.sources.items():
if not isinstance(source, Scope):
continue
if isinstance(source.expression, exp.Values):
selects[name] = {
alias: column
for alias, column in zip(
source.expression.alias_column_names,
source.expression.expressions[0].expressions,
)
}
else:
selects[name] = {
select.alias_or_name: select for select in source.expression.selects
}
# First annotate the current scope's column references
for col in scope.columns:
source = scope.sources[col.table]
if isinstance(source, exp.Table):
col.type = self.schema.get_column_type(source, col)
else:
col.type = selects[col.table][col.name].type
# Then (possibly) annotate the remaining expressions in the scope
self._maybe_annotate(scope.expression)
return self._maybe_annotate(expression) # This takes care of non-traversable expressions
def _maybe_annotate(self, expression):
if not isinstance(expression, exp.Expression):
return None
if expression.type:
return expression # We've already inferred the expression's type
annotator = self.annotators.get(expression.__class__)
return (
annotator(self, expression)
if annotator
else self._annotate_with_type(expression, exp.DataType.Type.UNKNOWN)
)
def _annotate_args(self, expression):
for value in expression.args.values():
for v in ensure_collection(value):
self._maybe_annotate(v)
return expression
def _maybe_coerce(self, type1, type2):
# We propagate the NULL / UNKNOWN types upwards if found
if exp.DataType.Type.NULL in (type1, type2):
return exp.DataType.Type.NULL
if exp.DataType.Type.UNKNOWN in (type1, type2):
return exp.DataType.Type.UNKNOWN
return type2 if type2 in self.coerces_to[type1] else type1
def _annotate_binary(self, expression):
self._annotate_args(expression)
left_type = expression.left.type
right_type = expression.right.type
if isinstance(expression, (exp.And, exp.Or)):
if left_type == exp.DataType.Type.NULL and right_type == exp.DataType.Type.NULL:
expression.type = exp.DataType.Type.NULL
elif exp.DataType.Type.NULL in (left_type, right_type):
expression.type = exp.DataType.build(
"NULLABLE", expressions=exp.DataType.build("BOOLEAN")
)
else:
expression.type = exp.DataType.Type.BOOLEAN
elif isinstance(expression, (exp.Condition, exp.Predicate)):
expression.type = exp.DataType.Type.BOOLEAN
else:
expression.type = self._maybe_coerce(left_type, right_type)
return expression
def _annotate_unary(self, expression):
self._annotate_args(expression)
if isinstance(expression, exp.Condition) and not isinstance(expression, exp.Paren):
expression.type = exp.DataType.Type.BOOLEAN
else:
expression.type = expression.this.type
return expression
def _annotate_literal(self, expression):
if expression.is_string:
expression.type = exp.DataType.Type.VARCHAR
elif expression.is_int:
expression.type = exp.DataType.Type.INT
else:
expression.type = exp.DataType.Type.DOUBLE
return expression
def _annotate_with_type(self, expression, target_type):
expression.type = target_type
return self._annotate_args(expression)
def _annotate_by_args(self, expression, *args):
self._annotate_args(expression)
expressions = []
for arg in args:
arg_expr = expression.args.get(arg)
expressions.extend(expr for expr in ensure_list(arg_expr) if expr)
last_datatype = None
for expr in expressions:
last_datatype = self._maybe_coerce(last_datatype or expr.type, expr.type)
expression.type = last_datatype or exp.DataType.Type.UNKNOWN
return expression
|