import ast import collections import itertools import math from sqlglot import exp, generator, planner, tokens from sqlglot.dialects.dialect import Dialect, inline_array_sql from sqlglot.executor.context import Context from sqlglot.executor.env import ENV from sqlglot.executor.table import Table from sqlglot.helper import csv_reader class PythonExecutor: def __init__(self, env=None): self.generator = Python().generator(identify=True) self.env = {**ENV, **(env or {})} def execute(self, plan): running = set() finished = set() queue = set(plan.leaves) contexts = {} while queue: node = queue.pop() context = self.context( { name: table for dep in node.dependencies for name, table in contexts[dep].tables.items() } ) running.add(node) if isinstance(node, planner.Scan): contexts[node] = self.scan(node, context) elif isinstance(node, planner.Aggregate): contexts[node] = self.aggregate(node, context) elif isinstance(node, planner.Join): contexts[node] = self.join(node, context) elif isinstance(node, planner.Sort): contexts[node] = self.sort(node, context) else: raise NotImplementedError running.remove(node) finished.add(node) for dep in node.dependents: if dep not in running and all(d in contexts for d in dep.dependencies): queue.add(dep) for dep in node.dependencies: if all(d in finished for d in dep.dependents): contexts.pop(dep) root = plan.root return contexts[root].tables[root.name] def generate(self, expression): """Convert a SQL expression into literal Python code and compile it into bytecode.""" if not expression: return None sql = self.generator.generate(expression) return compile(sql, sql, "eval", optimize=2) def generate_tuple(self, expressions): """Convert an array of SQL expressions into tuple of Python byte code.""" if not expressions: return tuple() return tuple(self.generate(expression) for expression in expressions) def context(self, tables): return Context(tables, env=self.env) def table(self, expressions): return Table(expression.alias_or_name for expression in expressions) def scan(self, step, context): source = step.source if isinstance(source, exp.Expression): source = source.name or source.alias condition = self.generate(step.condition) projections = self.generate_tuple(step.projections) if source in context: if not projections and not condition: return self.context({step.name: context.tables[source]}) table_iter = context.table_iter(source) else: table_iter = self.scan_csv(step) if projections: sink = self.table(step.projections) else: sink = None for reader, ctx in table_iter: if sink is None: sink = Table(reader.columns) if condition and not ctx.eval(condition): continue if projections: sink.append(ctx.eval_tuple(projections)) else: sink.append(reader.row) if len(sink) >= step.limit: break return self.context({step.name: sink}) def scan_csv(self, step): source = step.source alias = source.alias with csv_reader(source) as reader: columns = next(reader) table = Table(columns) context = self.context({alias: table}) types = [] for row in reader: if not types: for v in row: try: types.append(type(ast.literal_eval(v))) except (ValueError, SyntaxError): types.append(str) context.set_row(tuple(t(v) for t, v in zip(types, row))) yield context.table.reader, context def join(self, step, context): source = step.name source_table = context.tables[source] source_context = self.context({source: source_table}) column_ranges = {source: range(0, len(source_table.columns))} for name, join in step.joins.items(): table = context.tables[name] start = max(r.stop for r in column_ranges.values()) column_ranges[name] = range(start, len(table.columns) + start) join_context = self.context({name: table}) if join.get("source_key"): table = self.hash_join(join, source_context, join_context) else: table = self.nested_loop_join(join, source_context, join_context) source_context = self.context( { name: Table(table.columns, table.rows, column_range) for name, column_range in column_ranges.items() } ) condition = self.generate(step.condition) projections = self.generate_tuple(step.projections) if not condition or not projections: return source_context sink = self.table(step.projections if projections else source_context.columns) for reader, ctx in join_context: if condition and not ctx.eval(condition): continue if projections: sink.append(ctx.eval_tuple(projections)) else: sink.append(reader.row) if len(sink) >= step.limit: break return self.context({step.name: sink}) def nested_loop_join(self, _join, source_context, join_context): table = Table(source_context.columns + join_context.columns) for reader_a, _ in source_context: for reader_b, _ in join_context: table.append(reader_a.row + reader_b.row) return table def hash_join(self, join, source_context, join_context): source_key = self.generate_tuple(join["source_key"]) join_key = self.generate_tuple(join["join_key"]) results = collections.defaultdict(lambda: ([], [])) for reader, ctx in source_context: results[ctx.eval_tuple(source_key)][0].append(reader.row) for reader, ctx in join_context: results[ctx.eval_tuple(join_key)][1].append(reader.row) table = Table(source_context.columns + join_context.columns) for a_group, b_group in results.values(): for a_row, b_row in itertools.product(a_group, b_group): table.append(a_row + b_row) return table def aggregate(self, step, context): source = step.source group_by = self.generate_tuple(step.group) aggregations = self.generate_tuple(step.aggregations) operands = self.generate_tuple(step.operands) if operands: source_table = context.tables[source] operand_table = Table(source_table.columns + self.table(step.operands).columns) for reader, ctx in context: operand_table.append(reader.row + ctx.eval_tuple(operands)) context = self.context( {None: operand_table, **{table: operand_table for table in context.tables}} ) context.sort(group_by) group = None start = 0 end = 1 length = len(context.tables[source]) table = self.table(step.group + step.aggregations) for i in range(length): context.set_index(i) key = context.eval_tuple(group_by) group = key if group is None else group end += 1 if i == length - 1: context.set_range(start, end - 1) elif key != group: context.set_range(start, end - 2) else: continue table.append(group + context.eval_tuple(aggregations)) group = key start = end - 2 context = self.context({step.name: table, **{name: table for name in context.tables}}) if step.projections: return self.scan(step, context) return context def sort(self, step, context): projections = self.generate_tuple(step.projections) sink = self.table(step.projections) for reader, ctx in context: sink.append(ctx.eval_tuple(projections)) context = self.context( { None: sink, **{table: sink for table in context.tables}, } ) context.sort(self.generate_tuple(step.key)) if not math.isinf(step.limit): context.table.rows = context.table.rows[0 : step.limit] return self.context({step.name: context.table}) def _cast_py(self, expression): to = expression.args["to"].this this = self.sql(expression, "this") if to == exp.DataType.Type.DATE: return f"datetime.date.fromisoformat({this})" if to == exp.DataType.Type.TEXT: return f"str({this})" raise NotImplementedError def _column_py(self, expression): table = self.sql(expression, "table") or None this = self.sql(expression, "this") return f"scope[{table}][{this}]" def _interval_py(self, expression): this = self.sql(expression, "this") unit = expression.text("unit").upper() if unit == "DAY": return f"datetime.timedelta(days=float({this}))" raise NotImplementedError def _like_py(self, expression): this = self.sql(expression, "this") expression = self.sql(expression, "expression") return f"""bool(re.match({expression}.replace("_", ".").replace("%", ".*"), {this}))""" def _ordered_py(self, expression): this = self.sql(expression, "this") desc = expression.args.get("desc") return f"desc({this})" if desc else this class Python(Dialect): class Tokenizer(tokens.Tokenizer): ESCAPES = ["\\"] class Generator(generator.Generator): TRANSFORMS = { exp.Alias: lambda self, e: self.sql(e.this), exp.Array: inline_array_sql, exp.And: lambda self, e: self.binary(e, "and"), exp.Boolean: lambda self, e: "True" if e.this else "False", exp.Cast: _cast_py, exp.Column: _column_py, exp.EQ: lambda self, e: self.binary(e, "=="), exp.In: lambda self, e: f"{self.sql(e, 'this')} in {self.expressions(e)}", exp.Interval: _interval_py, exp.Is: lambda self, e: self.binary(e, "is"), exp.Like: _like_py, exp.Not: lambda self, e: f"not {self.sql(e.this)}", exp.Null: lambda *_: "None", exp.Or: lambda self, e: self.binary(e, "or"), exp.Ordered: _ordered_py, exp.Star: lambda *_: "1", } def case_sql(self, expression): this = self.sql(expression, "this") chain = self.sql(expression, "default") or "None" for e in reversed(expression.args["ifs"]): true = self.sql(e, "true") condition = self.sql(e, "this") condition = f"{this} = ({condition})" if this else condition chain = f"{true} if {condition} else ({chain})" return chain