from __future__ import annotations import typing as t from sqlglot import expressions as exp from sqlglot.helper import find_new_name if t.TYPE_CHECKING: from sqlglot.generator import Generator def unalias_group(expression: exp.Expression) -> exp.Expression: """ Replace references to select aliases in GROUP BY clauses. Example: >>> import sqlglot >>> sqlglot.parse_one("SELECT a AS b FROM x GROUP BY b").transform(unalias_group).sql() 'SELECT a AS b FROM x GROUP BY 1' Args: expression: the expression that will be transformed. Returns: The transformed expression. """ if isinstance(expression, exp.Group) and isinstance(expression.parent, exp.Select): aliased_selects = { e.alias: i for i, e in enumerate(expression.parent.expressions, start=1) if isinstance(e, exp.Alias) } for group_by in expression.expressions: if ( isinstance(group_by, exp.Column) and not group_by.table and group_by.name in aliased_selects ): group_by.replace(exp.Literal.number(aliased_selects.get(group_by.name))) return expression def eliminate_distinct_on(expression: exp.Expression) -> exp.Expression: """ Convert SELECT DISTINCT ON statements to a subquery with a window function. This is useful for dialects that don't support SELECT DISTINCT ON but support window functions. Args: expression: the expression that will be transformed. Returns: The transformed expression. """ if ( isinstance(expression, exp.Select) and expression.args.get("distinct") and expression.args["distinct"].args.get("on") and isinstance(expression.args["distinct"].args["on"], exp.Tuple) ): distinct_cols = expression.args["distinct"].pop().args["on"].expressions outer_selects = expression.selects row_number = find_new_name(expression.named_selects, "_row_number") window = exp.Window( this=exp.RowNumber(), partition_by=distinct_cols, ) order = expression.args.get("order") if order: window.set("order", order.pop().copy()) window = exp.alias_(window, row_number) expression.select(window, copy=False) return exp.select(*outer_selects).from_(expression.subquery()).where(f'"{row_number}" = 1') return expression def eliminate_qualify(expression: exp.Expression) -> exp.Expression: """ Convert SELECT statements that contain the QUALIFY clause into subqueries, filtered equivalently. The idea behind this transformation can be seen in Snowflake's documentation for QUALIFY: https://docs.snowflake.com/en/sql-reference/constructs/qualify Some dialects don't support window functions in the WHERE clause, so we need to include them as projections in the subquery, in order to refer to them in the outer filter using aliases. Also, if a column is referenced in the QUALIFY clause but is not selected, we need to include it too, otherwise we won't be able to refer to it in the outer query's WHERE clause. """ if isinstance(expression, exp.Select) and expression.args.get("qualify"): taken = set(expression.named_selects) for select in expression.selects: if not select.alias_or_name: alias = find_new_name(taken, "_c") select.replace(exp.alias_(select.copy(), alias)) taken.add(alias) outer_selects = exp.select(*[select.alias_or_name for select in expression.selects]) qualify_filters = expression.args["qualify"].pop().this for expr in qualify_filters.find_all((exp.Window, exp.Column)): if isinstance(expr, exp.Window): alias = find_new_name(expression.named_selects, "_w") expression.select(exp.alias_(expr.copy(), alias), copy=False) expr.replace(exp.column(alias)) elif expr.name not in expression.named_selects: expression.select(expr.copy(), copy=False) return outer_selects.from_(expression.subquery(alias="_t")).where(qualify_filters) return expression def remove_precision_parameterized_types(expression: exp.Expression) -> exp.Expression: """ Some dialects only allow the precision for parameterized types to be defined in the DDL and not in other expressions. This transforms removes the precision from parameterized types in expressions. """ return expression.transform( lambda node: exp.DataType( **{ **node.args, "expressions": [ node_expression for node_expression in node.expressions if isinstance(node_expression, exp.DataType) ], } ) if isinstance(node, exp.DataType) else node, ) def preprocess( transforms: t.List[t.Callable[[exp.Expression], exp.Expression]], to_sql: t.Callable[[Generator, exp.Expression], str], ) -> t.Callable[[Generator, exp.Expression], str]: """ Creates a new transform by chaining a sequence of transformations and converts the resulting expression to SQL, using an appropriate `Generator.TRANSFORMS` function. Args: transforms: sequence of transform functions. These will be called in order. to_sql: final transform that converts the resulting expression to a SQL string. Returns: Function that can be used as a generator transform. """ def _to_sql(self, expression): expression = transforms[0](expression.copy()) for t in transforms[1:]: expression = t(expression) return to_sql(self, expression) return _to_sql def delegate(attr: str) -> t.Callable: """ Create a new method that delegates to `attr`. This is useful for creating `Generator.TRANSFORMS` functions that delegate to existing generator methods. """ def _transform(self, *args, **kwargs): return getattr(self, attr)(*args, **kwargs) return _transform UNALIAS_GROUP = {exp.Group: preprocess([unalias_group], delegate("group_sql"))} ELIMINATE_DISTINCT_ON = {exp.Select: preprocess([eliminate_distinct_on], delegate("select_sql"))} ELIMINATE_QUALIFY = {exp.Select: preprocess([eliminate_qualify], delegate("select_sql"))} REMOVE_PRECISION_PARAMETERIZED_TYPES = { exp.Cast: preprocess([remove_precision_parameterized_types], delegate("cast_sql")) }