D7net
Home
Console
Upload
information
Create File
Create Folder
About
Tools
:
/
proc
/
self
/
root
/
opt
/
hc_python
/
lib64
/
python3.8
/
site-packages
/
sqlalchemy
/
sql
/
Filename :
functions.py
back
Copy
# sql/functions.py # Copyright (C) 2005-2024 the SQLAlchemy authors and contributors # <see AUTHORS file> # # This module is part of SQLAlchemy and is released under # the MIT License: https://www.opensource.org/licenses/mit-license.php """SQL function API, factories, and built-in functions. """ from __future__ import annotations import datetime import decimal from typing import Any from typing import cast from typing import Dict from typing import List from typing import Mapping from typing import Optional from typing import overload from typing import Sequence from typing import Tuple from typing import Type from typing import TYPE_CHECKING from typing import TypeVar from typing import Union from . import annotation from . import coercions from . import operators from . import roles from . import schema from . import sqltypes from . import type_api from . import util as sqlutil from ._typing import is_table_value_type from .base import _entity_namespace from .base import ColumnCollection from .base import Executable from .base import Generative from .base import HasMemoized from .elements import _type_from_args from .elements import BinaryExpression from .elements import BindParameter from .elements import Cast from .elements import ClauseList from .elements import ColumnElement from .elements import Extract from .elements import FunctionFilter from .elements import Grouping from .elements import literal_column from .elements import NamedColumn from .elements import Over from .elements import WithinGroup from .selectable import FromClause from .selectable import Select from .selectable import TableValuedAlias from .sqltypes import TableValueType from .type_api import TypeEngine from .visitors import InternalTraversal from .. import util if TYPE_CHECKING: from ._typing import _ByArgument from ._typing import _ColumnExpressionArgument from ._typing import _ColumnExpressionOrLiteralArgument from ._typing import _ColumnExpressionOrStrLabelArgument from ._typing import _StarOrOne from ._typing import _TypeEngineArgument from .base import _EntityNamespace from .elements import ClauseElement from .elements import KeyedColumnElement from .elements import TableValuedColumn from .operators import OperatorType from ..engine.base import Connection from ..engine.cursor import CursorResult from ..engine.interfaces import _CoreMultiExecuteParams from ..engine.interfaces import CoreExecuteOptionsParameter from ..util.typing import Self _T = TypeVar("_T", bound=Any) _S = TypeVar("_S", bound=Any) _registry: util.defaultdict[str, Dict[str, Type[Function[Any]]]] = ( util.defaultdict(dict) ) def register_function( identifier: str, fn: Type[Function[Any]], package: str = "_default" ) -> None: """Associate a callable with a particular func. name. This is normally called by GenericFunction, but is also available by itself so that a non-Function construct can be associated with the :data:`.func` accessor (i.e. CAST, EXTRACT). """ reg = _registry[package] identifier = str(identifier).lower() # Check if a function with the same identifier is registered. if identifier in reg: util.warn( "The GenericFunction '{}' is already registered and " "is going to be overridden.".format(identifier) ) reg[identifier] = fn class FunctionElement(Executable, ColumnElement[_T], FromClause, Generative): """Base for SQL function-oriented constructs. This is a `generic type <https://peps.python.org/pep-0484/#generics>`_, meaning that type checkers and IDEs can be instructed on the types to expect in a :class:`_engine.Result` for this function. See :class:`.GenericFunction` for an example of how this is done. .. seealso:: :ref:`tutorial_functions` - in the :ref:`unified_tutorial` :class:`.Function` - named SQL function. :data:`.func` - namespace which produces registered or ad-hoc :class:`.Function` instances. :class:`.GenericFunction` - allows creation of registered function types. """ _traverse_internals = [ ("clause_expr", InternalTraversal.dp_clauseelement), ("_with_ordinality", InternalTraversal.dp_boolean), ("_table_value_type", InternalTraversal.dp_has_cache_key), ] packagenames: Tuple[str, ...] = () _has_args = False _with_ordinality = False _table_value_type: Optional[TableValueType] = None # some attributes that are defined between both ColumnElement and # FromClause are set to Any here to avoid typing errors primary_key: Any _is_clone_of: Any clause_expr: Grouping[Any] def __init__(self, *clauses: _ColumnExpressionOrLiteralArgument[Any]): r"""Construct a :class:`.FunctionElement`. :param \*clauses: list of column expressions that form the arguments of the SQL function call. :param \**kwargs: additional kwargs are typically consumed by subclasses. .. seealso:: :data:`.func` :class:`.Function` """ args: Sequence[_ColumnExpressionArgument[Any]] = [ coercions.expect( roles.ExpressionElementRole, c, name=getattr(self, "name", None), apply_propagate_attrs=self, ) for c in clauses ] self._has_args = self._has_args or bool(args) self.clause_expr = Grouping( ClauseList(operator=operators.comma_op, group_contents=True, *args) ) _non_anon_label = None @property def _proxy_key(self) -> Any: return super()._proxy_key or getattr(self, "name", None) def _execute_on_connection( self, connection: Connection, distilled_params: _CoreMultiExecuteParams, execution_options: CoreExecuteOptionsParameter, ) -> CursorResult[Any]: return connection._execute_function( self, distilled_params, execution_options ) def scalar_table_valued( self, name: str, type_: Optional[_TypeEngineArgument[_T]] = None ) -> ScalarFunctionColumn[_T]: """Return a column expression that's against this :class:`_functions.FunctionElement` as a scalar table-valued expression. The returned expression is similar to that returned by a single column accessed off of a :meth:`_functions.FunctionElement.table_valued` construct, except no FROM clause is generated; the function is rendered in the similar way as a scalar subquery. E.g.: .. sourcecode:: pycon+sql >>> from sqlalchemy import func, select >>> fn = func.jsonb_each("{'k', 'v'}").scalar_table_valued("key") >>> print(select(fn)) {printsql}SELECT (jsonb_each(:jsonb_each_1)).key .. versionadded:: 1.4.0b2 .. seealso:: :meth:`_functions.FunctionElement.table_valued` :meth:`_functions.FunctionElement.alias` :meth:`_functions.FunctionElement.column_valued` """ # noqa: E501 return ScalarFunctionColumn(self, name, type_) def table_valued( self, *expr: _ColumnExpressionOrStrLabelArgument[Any], **kw: Any ) -> TableValuedAlias: r"""Return a :class:`_sql.TableValuedAlias` representation of this :class:`_functions.FunctionElement` with table-valued expressions added. e.g.: .. sourcecode:: pycon+sql >>> fn = ( ... func.generate_series(1, 5). ... table_valued("value", "start", "stop", "step") ... ) >>> print(select(fn)) {printsql}SELECT anon_1.value, anon_1.start, anon_1.stop, anon_1.step FROM generate_series(:generate_series_1, :generate_series_2) AS anon_1{stop} >>> print(select(fn.c.value, fn.c.stop).where(fn.c.value > 2)) {printsql}SELECT anon_1.value, anon_1.stop FROM generate_series(:generate_series_1, :generate_series_2) AS anon_1 WHERE anon_1.value > :value_1{stop} A WITH ORDINALITY expression may be generated by passing the keyword argument "with_ordinality": .. sourcecode:: pycon+sql >>> fn = func.generate_series(4, 1, -1).table_valued("gen", with_ordinality="ordinality") >>> print(select(fn)) {printsql}SELECT anon_1.gen, anon_1.ordinality FROM generate_series(:generate_series_1, :generate_series_2, :generate_series_3) WITH ORDINALITY AS anon_1 :param \*expr: A series of string column names that will be added to the ``.c`` collection of the resulting :class:`_sql.TableValuedAlias` construct as columns. :func:`_sql.column` objects with or without datatypes may also be used. :param name: optional name to assign to the alias name that's generated. If omitted, a unique anonymizing name is used. :param with_ordinality: string name that when present results in the ``WITH ORDINALITY`` clause being added to the alias, and the given string name will be added as a column to the .c collection of the resulting :class:`_sql.TableValuedAlias`. :param joins_implicitly: when True, the table valued function may be used in the FROM clause without any explicit JOIN to other tables in the SQL query, and no "cartesian product" warning will be generated. May be useful for SQL functions such as ``func.json_each()``. .. versionadded:: 1.4.33 .. versionadded:: 1.4.0b2 .. seealso:: :ref:`tutorial_functions_table_valued` - in the :ref:`unified_tutorial` :ref:`postgresql_table_valued` - in the :ref:`postgresql_toplevel` documentation :meth:`_functions.FunctionElement.scalar_table_valued` - variant of :meth:`_functions.FunctionElement.table_valued` which delivers the complete table valued expression as a scalar column expression :meth:`_functions.FunctionElement.column_valued` :meth:`_sql.TableValuedAlias.render_derived` - renders the alias using a derived column clause, e.g. ``AS name(col1, col2, ...)`` """ # noqa: 501 new_func = self._generate() with_ordinality = kw.pop("with_ordinality", None) joins_implicitly = kw.pop("joins_implicitly", None) name = kw.pop("name", None) if with_ordinality: expr += (with_ordinality,) new_func._with_ordinality = True new_func.type = new_func._table_value_type = TableValueType(*expr) return new_func.alias(name=name, joins_implicitly=joins_implicitly) def column_valued( self, name: Optional[str] = None, joins_implicitly: bool = False ) -> TableValuedColumn[_T]: """Return this :class:`_functions.FunctionElement` as a column expression that selects from itself as a FROM clause. E.g.: .. sourcecode:: pycon+sql >>> from sqlalchemy import select, func >>> gs = func.generate_series(1, 5, -1).column_valued() >>> print(select(gs)) {printsql}SELECT anon_1 FROM generate_series(:generate_series_1, :generate_series_2, :generate_series_3) AS anon_1 This is shorthand for:: gs = func.generate_series(1, 5, -1).alias().column :param name: optional name to assign to the alias name that's generated. If omitted, a unique anonymizing name is used. :param joins_implicitly: when True, the "table" portion of the column valued function may be a member of the FROM clause without any explicit JOIN to other tables in the SQL query, and no "cartesian product" warning will be generated. May be useful for SQL functions such as ``func.json_array_elements()``. .. versionadded:: 1.4.46 .. seealso:: :ref:`tutorial_functions_column_valued` - in the :ref:`unified_tutorial` :ref:`postgresql_column_valued` - in the :ref:`postgresql_toplevel` documentation :meth:`_functions.FunctionElement.table_valued` """ # noqa: 501 return self.alias(name=name, joins_implicitly=joins_implicitly).column @util.ro_non_memoized_property def columns(self) -> ColumnCollection[str, KeyedColumnElement[Any]]: # type: ignore[override] # noqa: E501 r"""The set of columns exported by this :class:`.FunctionElement`. This is a placeholder collection that allows the function to be placed in the FROM clause of a statement: .. sourcecode:: pycon+sql >>> from sqlalchemy import column, select, func >>> stmt = select(column('x'), column('y')).select_from(func.myfunction()) >>> print(stmt) {printsql}SELECT x, y FROM myfunction() The above form is a legacy feature that is now superseded by the fully capable :meth:`_functions.FunctionElement.table_valued` method; see that method for details. .. seealso:: :meth:`_functions.FunctionElement.table_valued` - generates table-valued SQL function expressions. """ # noqa: E501 return self.c @util.ro_memoized_property def c(self) -> ColumnCollection[str, KeyedColumnElement[Any]]: # type: ignore[override] # noqa: E501 """synonym for :attr:`.FunctionElement.columns`.""" return ColumnCollection( columns=[(col.key, col) for col in self._all_selected_columns] ) @property def _all_selected_columns(self) -> Sequence[KeyedColumnElement[Any]]: if is_table_value_type(self.type): # TODO: this might not be fully accurate cols = cast( "Sequence[KeyedColumnElement[Any]]", self.type._elements ) else: cols = [self.label(None)] return cols @property def exported_columns( # type: ignore[override] self, ) -> ColumnCollection[str, KeyedColumnElement[Any]]: return self.columns @HasMemoized.memoized_attribute def clauses(self) -> ClauseList: """Return the underlying :class:`.ClauseList` which contains the arguments for this :class:`.FunctionElement`. """ return cast(ClauseList, self.clause_expr.element) def over( self, *, partition_by: Optional[_ByArgument] = None, order_by: Optional[_ByArgument] = None, rows: Optional[Tuple[Optional[int], Optional[int]]] = None, range_: Optional[Tuple[Optional[int], Optional[int]]] = None, ) -> Over[_T]: """Produce an OVER clause against this function. Used against aggregate or so-called "window" functions, for database backends that support window functions. The expression:: func.row_number().over(order_by='x') is shorthand for:: from sqlalchemy import over over(func.row_number(), order_by='x') See :func:`_expression.over` for a full description. .. seealso:: :func:`_expression.over` :ref:`tutorial_window_functions` - in the :ref:`unified_tutorial` """ return Over( self, partition_by=partition_by, order_by=order_by, rows=rows, range_=range_, ) def within_group( self, *order_by: _ColumnExpressionArgument[Any] ) -> WithinGroup[_T]: """Produce a WITHIN GROUP (ORDER BY expr) clause against this function. Used against so-called "ordered set aggregate" and "hypothetical set aggregate" functions, including :class:`.percentile_cont`, :class:`.rank`, :class:`.dense_rank`, etc. See :func:`_expression.within_group` for a full description. .. seealso:: :ref:`tutorial_functions_within_group` - in the :ref:`unified_tutorial` """ return WithinGroup(self, *order_by) @overload def filter(self) -> Self: ... @overload def filter( self, __criterion0: _ColumnExpressionArgument[bool], *criterion: _ColumnExpressionArgument[bool], ) -> FunctionFilter[_T]: ... def filter( self, *criterion: _ColumnExpressionArgument[bool] ) -> Union[Self, FunctionFilter[_T]]: """Produce a FILTER clause against this function. Used against aggregate and window functions, for database backends that support the "FILTER" clause. The expression:: func.count(1).filter(True) is shorthand for:: from sqlalchemy import funcfilter funcfilter(func.count(1), True) .. seealso:: :ref:`tutorial_functions_within_group` - in the :ref:`unified_tutorial` :class:`.FunctionFilter` :func:`.funcfilter` """ if not criterion: return self return FunctionFilter(self, *criterion) def as_comparison( self, left_index: int, right_index: int ) -> FunctionAsBinary: """Interpret this expression as a boolean comparison between two values. This method is used for an ORM use case described at :ref:`relationship_custom_operator_sql_function`. A hypothetical SQL function "is_equal()" which compares to values for equality would be written in the Core expression language as:: expr = func.is_equal("a", "b") If "is_equal()" above is comparing "a" and "b" for equality, the :meth:`.FunctionElement.as_comparison` method would be invoked as:: expr = func.is_equal("a", "b").as_comparison(1, 2) Where above, the integer value "1" refers to the first argument of the "is_equal()" function and the integer value "2" refers to the second. This would create a :class:`.BinaryExpression` that is equivalent to:: BinaryExpression("a", "b", operator=op.eq) However, at the SQL level it would still render as "is_equal('a', 'b')". The ORM, when it loads a related object or collection, needs to be able to manipulate the "left" and "right" sides of the ON clause of a JOIN expression. The purpose of this method is to provide a SQL function construct that can also supply this information to the ORM, when used with the :paramref:`_orm.relationship.primaryjoin` parameter. The return value is a containment object called :class:`.FunctionAsBinary`. An ORM example is as follows:: class Venue(Base): __tablename__ = 'venue' id = Column(Integer, primary_key=True) name = Column(String) descendants = relationship( "Venue", primaryjoin=func.instr( remote(foreign(name)), name + "/" ).as_comparison(1, 2) == 1, viewonly=True, order_by=name ) Above, the "Venue" class can load descendant "Venue" objects by determining if the name of the parent Venue is contained within the start of the hypothetical descendant value's name, e.g. "parent1" would match up to "parent1/child1", but not to "parent2/child1". Possible use cases include the "materialized path" example given above, as well as making use of special SQL functions such as geometric functions to create join conditions. :param left_index: the integer 1-based index of the function argument that serves as the "left" side of the expression. :param right_index: the integer 1-based index of the function argument that serves as the "right" side of the expression. .. versionadded:: 1.3 .. seealso:: :ref:`relationship_custom_operator_sql_function` - example use within the ORM """ return FunctionAsBinary(self, left_index, right_index) @property def _from_objects(self) -> Any: return self.clauses._from_objects def within_group_type( self, within_group: WithinGroup[_S] ) -> Optional[TypeEngine[_S]]: """For types that define their return type as based on the criteria within a WITHIN GROUP (ORDER BY) expression, called by the :class:`.WithinGroup` construct. Returns None by default, in which case the function's normal ``.type`` is used. """ return None def alias( self, name: Optional[str] = None, joins_implicitly: bool = False ) -> TableValuedAlias: r"""Produce a :class:`_expression.Alias` construct against this :class:`.FunctionElement`. .. tip:: The :meth:`_functions.FunctionElement.alias` method is part of the mechanism by which "table valued" SQL functions are created. However, most use cases are covered by higher level methods on :class:`_functions.FunctionElement` including :meth:`_functions.FunctionElement.table_valued`, and :meth:`_functions.FunctionElement.column_valued`. This construct wraps the function in a named alias which is suitable for the FROM clause, in the style accepted for example by PostgreSQL. A column expression is also provided using the special ``.column`` attribute, which may be used to refer to the output of the function as a scalar value in the columns or where clause, for a backend such as PostgreSQL. For a full table-valued expression, use the :meth:`_functions.FunctionElement.table_valued` method first to establish named columns. e.g.: .. sourcecode:: pycon+sql >>> from sqlalchemy import func, select, column >>> data_view = func.unnest([1, 2, 3]).alias("data_view") >>> print(select(data_view.column)) {printsql}SELECT data_view FROM unnest(:unnest_1) AS data_view The :meth:`_functions.FunctionElement.column_valued` method provides a shortcut for the above pattern: .. sourcecode:: pycon+sql >>> data_view = func.unnest([1, 2, 3]).column_valued("data_view") >>> print(select(data_view)) {printsql}SELECT data_view FROM unnest(:unnest_1) AS data_view .. versionadded:: 1.4.0b2 Added the ``.column`` accessor :param name: alias name, will be rendered as ``AS <name>`` in the FROM clause :param joins_implicitly: when True, the table valued function may be used in the FROM clause without any explicit JOIN to other tables in the SQL query, and no "cartesian product" warning will be generated. May be useful for SQL functions such as ``func.json_each()``. .. versionadded:: 1.4.33 .. seealso:: :ref:`tutorial_functions_table_valued` - in the :ref:`unified_tutorial` :meth:`_functions.FunctionElement.table_valued` :meth:`_functions.FunctionElement.scalar_table_valued` :meth:`_functions.FunctionElement.column_valued` """ return TableValuedAlias._construct( self, name=name, table_value_type=self.type, joins_implicitly=joins_implicitly, ) def select(self) -> Select[Tuple[_T]]: """Produce a :func:`_expression.select` construct against this :class:`.FunctionElement`. This is shorthand for:: s = select(function_element) """ s: Select[Any] = Select(self) if self._execution_options: s = s.execution_options(**self._execution_options) return s def _bind_param( self, operator: OperatorType, obj: Any, type_: Optional[TypeEngine[_T]] = None, expanding: bool = False, **kw: Any, ) -> BindParameter[_T]: return BindParameter( None, obj, _compared_to_operator=operator, _compared_to_type=self.type, unique=True, type_=type_, expanding=expanding, **kw, ) def self_group(self, against: Optional[OperatorType] = None) -> ClauseElement: # type: ignore[override] # noqa E501 # for the moment, we are parenthesizing all array-returning # expressions against getitem. This may need to be made # more portable if in the future we support other DBs # besides postgresql. if against is operators.getitem and isinstance( self.type, sqltypes.ARRAY ): return Grouping(self) else: return super().self_group(against=against) @property def entity_namespace(self) -> _EntityNamespace: """overrides FromClause.entity_namespace as functions are generally column expressions and not FromClauses. """ # ideally functions would not be fromclauses but we failed to make # this adjustment in 1.4 return _entity_namespace(self.clause_expr) class FunctionAsBinary(BinaryExpression[Any]): _traverse_internals = [ ("sql_function", InternalTraversal.dp_clauseelement), ("left_index", InternalTraversal.dp_plain_obj), ("right_index", InternalTraversal.dp_plain_obj), ("modifiers", InternalTraversal.dp_plain_dict), ] sql_function: FunctionElement[Any] left_index: int right_index: int def _gen_cache_key(self, anon_map: Any, bindparams: Any) -> Any: return ColumnElement._gen_cache_key(self, anon_map, bindparams) def __init__( self, fn: FunctionElement[Any], left_index: int, right_index: int ): self.sql_function = fn self.left_index = left_index self.right_index = right_index self.operator = operators.function_as_comparison_op self.type = sqltypes.BOOLEANTYPE self.negate = None self._is_implicitly_boolean = True self.modifiers = {} @property def left_expr(self) -> ColumnElement[Any]: return self.sql_function.clauses.clauses[self.left_index - 1] @left_expr.setter def left_expr(self, value: ColumnElement[Any]) -> None: self.sql_function.clauses.clauses[self.left_index - 1] = value @property def right_expr(self) -> ColumnElement[Any]: return self.sql_function.clauses.clauses[self.right_index - 1] @right_expr.setter def right_expr(self, value: ColumnElement[Any]) -> None: self.sql_function.clauses.clauses[self.right_index - 1] = value if not TYPE_CHECKING: # mypy can't accommodate @property to replace an instance # variable left = left_expr right = right_expr class ScalarFunctionColumn(NamedColumn[_T]): __visit_name__ = "scalar_function_column" _traverse_internals = [ ("name", InternalTraversal.dp_anon_name), ("type", InternalTraversal.dp_type), ("fn", InternalTraversal.dp_clauseelement), ] is_literal = False table = None def __init__( self, fn: FunctionElement[_T], name: str, type_: Optional[_TypeEngineArgument[_T]] = None, ): self.fn = fn self.name = name # if type is None, we get NULLTYPE, which is our _T. But I don't # know how to get the overloads to express that correctly self.type = type_api.to_instance(type_) # type: ignore class _FunctionGenerator: """Generate SQL function expressions. :data:`.func` is a special object instance which generates SQL functions based on name-based attributes, e.g.: .. sourcecode:: pycon+sql >>> print(func.count(1)) {printsql}count(:param_1) The returned object is an instance of :class:`.Function`, and is a column-oriented SQL element like any other, and is used in that way: .. sourcecode:: pycon+sql >>> print(select(func.count(table.c.id))) {printsql}SELECT count(sometable.id) FROM sometable Any name can be given to :data:`.func`. If the function name is unknown to SQLAlchemy, it will be rendered exactly as is. For common SQL functions which SQLAlchemy is aware of, the name may be interpreted as a *generic function* which will be compiled appropriately to the target database: .. sourcecode:: pycon+sql >>> print(func.current_timestamp()) {printsql}CURRENT_TIMESTAMP To call functions which are present in dot-separated packages, specify them in the same manner: .. sourcecode:: pycon+sql >>> print(func.stats.yield_curve(5, 10)) {printsql}stats.yield_curve(:yield_curve_1, :yield_curve_2) SQLAlchemy can be made aware of the return type of functions to enable type-specific lexical and result-based behavior. For example, to ensure that a string-based function returns a Unicode value and is similarly treated as a string in expressions, specify :class:`~sqlalchemy.types.Unicode` as the type: .. sourcecode:: pycon+sql >>> print(func.my_string(u'hi', type_=Unicode) + ' ' + ... func.my_string(u'there', type_=Unicode)) {printsql}my_string(:my_string_1) || :my_string_2 || my_string(:my_string_3) The object returned by a :data:`.func` call is usually an instance of :class:`.Function`. This object meets the "column" interface, including comparison and labeling functions. The object can also be passed the :meth:`~.Connectable.execute` method of a :class:`_engine.Connection` or :class:`_engine.Engine`, where it will be wrapped inside of a SELECT statement first:: print(connection.execute(func.current_timestamp()).scalar()) In a few exception cases, the :data:`.func` accessor will redirect a name to a built-in expression such as :func:`.cast` or :func:`.extract`, as these names have well-known meaning but are not exactly the same as "functions" from a SQLAlchemy perspective. Functions which are interpreted as "generic" functions know how to calculate their return type automatically. For a listing of known generic functions, see :ref:`generic_functions`. .. note:: The :data:`.func` construct has only limited support for calling standalone "stored procedures", especially those with special parameterization concerns. See the section :ref:`stored_procedures` for details on how to use the DBAPI-level ``callproc()`` method for fully traditional stored procedures. .. seealso:: :ref:`tutorial_functions` - in the :ref:`unified_tutorial` :class:`.Function` """ # noqa def __init__(self, **opts: Any): self.__names: List[str] = [] self.opts = opts def __getattr__(self, name: str) -> _FunctionGenerator: # passthru __ attributes; fixes pydoc if name.startswith("__"): try: return self.__dict__[name] # type: ignore except KeyError: raise AttributeError(name) elif name.endswith("_"): name = name[0:-1] f = _FunctionGenerator(**self.opts) f.__names = list(self.__names) + [name] return f @overload def __call__( self, *c: Any, type_: _TypeEngineArgument[_T], **kwargs: Any ) -> Function[_T]: ... @overload def __call__(self, *c: Any, **kwargs: Any) -> Function[Any]: ... def __call__(self, *c: Any, **kwargs: Any) -> Function[Any]: o = self.opts.copy() o.update(kwargs) tokens = len(self.__names) if tokens == 2: package, fname = self.__names elif tokens == 1: package, fname = "_default", self.__names[0] else: package = None if package is not None: func = _registry[package].get(fname.lower()) if func is not None: return func(*c, **o) return Function( self.__names[-1], packagenames=tuple(self.__names[0:-1]), *c, **o ) if TYPE_CHECKING: # START GENERATED FUNCTION ACCESSORS # code within this block is **programmatically, # statically generated** by tools/generate_sql_functions.py @property def aggregate_strings(self) -> Type[aggregate_strings]: ... @property def ansifunction(self) -> Type[AnsiFunction[Any]]: ... @property def array_agg(self) -> Type[array_agg[Any]]: ... @property def cast(self) -> Type[Cast[Any]]: ... @property def char_length(self) -> Type[char_length]: ... # set ColumnElement[_T] as a separate overload, to appease mypy # which seems to not want to accept _T from _ColumnExpressionArgument. # this is even if all non-generic types are removed from it, so # reasons remain unclear for why this does not work @overload def coalesce( self, col: ColumnElement[_T], *args: _ColumnExpressionOrLiteralArgument[Any], **kwargs: Any, ) -> coalesce[_T]: ... @overload def coalesce( self, col: _ColumnExpressionArgument[_T], *args: _ColumnExpressionOrLiteralArgument[Any], **kwargs: Any, ) -> coalesce[_T]: ... @overload def coalesce( self, col: _ColumnExpressionOrLiteralArgument[_T], *args: _ColumnExpressionOrLiteralArgument[Any], **kwargs: Any, ) -> coalesce[_T]: ... def coalesce( self, col: _ColumnExpressionOrLiteralArgument[_T], *args: _ColumnExpressionOrLiteralArgument[Any], **kwargs: Any, ) -> coalesce[_T]: ... @property def concat(self) -> Type[concat]: ... @property def count(self) -> Type[count]: ... @property def cube(self) -> Type[cube[Any]]: ... @property def cume_dist(self) -> Type[cume_dist]: ... @property def current_date(self) -> Type[current_date]: ... @property def current_time(self) -> Type[current_time]: ... @property def current_timestamp(self) -> Type[current_timestamp]: ... @property def current_user(self) -> Type[current_user]: ... @property def dense_rank(self) -> Type[dense_rank]: ... @property def extract(self) -> Type[Extract]: ... @property def grouping_sets(self) -> Type[grouping_sets[Any]]: ... @property def localtime(self) -> Type[localtime]: ... @property def localtimestamp(self) -> Type[localtimestamp]: ... # set ColumnElement[_T] as a separate overload, to appease mypy # which seems to not want to accept _T from _ColumnExpressionArgument. # this is even if all non-generic types are removed from it, so # reasons remain unclear for why this does not work @overload def max( # noqa: A001 self, col: ColumnElement[_T], *args: _ColumnExpressionOrLiteralArgument[Any], **kwargs: Any, ) -> max[_T]: ... @overload def max( # noqa: A001 self, col: _ColumnExpressionArgument[_T], *args: _ColumnExpressionOrLiteralArgument[Any], **kwargs: Any, ) -> max[_T]: ... @overload def max( # noqa: A001 self, col: _ColumnExpressionOrLiteralArgument[_T], *args: _ColumnExpressionOrLiteralArgument[Any], **kwargs: Any, ) -> max[_T]: ... def max( # noqa: A001 self, col: _ColumnExpressionOrLiteralArgument[_T], *args: _ColumnExpressionOrLiteralArgument[Any], **kwargs: Any, ) -> max[_T]: ... # set ColumnElement[_T] as a separate overload, to appease mypy # which seems to not want to accept _T from _ColumnExpressionArgument. # this is even if all non-generic types are removed from it, so # reasons remain unclear for why this does not work @overload def min( # noqa: A001 self, col: ColumnElement[_T], *args: _ColumnExpressionOrLiteralArgument[Any], **kwargs: Any, ) -> min[_T]: ... @overload def min( # noqa: A001 self, col: _ColumnExpressionArgument[_T], *args: _ColumnExpressionOrLiteralArgument[Any], **kwargs: Any, ) -> min[_T]: ... @overload def min( # noqa: A001 self, col: _ColumnExpressionOrLiteralArgument[_T], *args: _ColumnExpressionOrLiteralArgument[Any], **kwargs: Any, ) -> min[_T]: ... def min( # noqa: A001 self, col: _ColumnExpressionOrLiteralArgument[_T], *args: _ColumnExpressionOrLiteralArgument[Any], **kwargs: Any, ) -> min[_T]: ... @property def mode(self) -> Type[mode[Any]]: ... @property def next_value(self) -> Type[next_value]: ... @property def now(self) -> Type[now]: ... @property def orderedsetagg(self) -> Type[OrderedSetAgg[Any]]: ... @property def percent_rank(self) -> Type[percent_rank]: ... @property def percentile_cont(self) -> Type[percentile_cont[Any]]: ... @property def percentile_disc(self) -> Type[percentile_disc[Any]]: ... @property def random(self) -> Type[random]: ... @property def rank(self) -> Type[rank]: ... @property def rollup(self) -> Type[rollup[Any]]: ... @property def session_user(self) -> Type[session_user]: ... # set ColumnElement[_T] as a separate overload, to appease mypy # which seems to not want to accept _T from _ColumnExpressionArgument. # this is even if all non-generic types are removed from it, so # reasons remain unclear for why this does not work @overload def sum( # noqa: A001 self, col: ColumnElement[_T], *args: _ColumnExpressionOrLiteralArgument[Any], **kwargs: Any, ) -> sum[_T]: ... @overload def sum( # noqa: A001 self, col: _ColumnExpressionArgument[_T], *args: _ColumnExpressionOrLiteralArgument[Any], **kwargs: Any, ) -> sum[_T]: ... @overload def sum( # noqa: A001 self, col: _ColumnExpressionOrLiteralArgument[_T], *args: _ColumnExpressionOrLiteralArgument[Any], **kwargs: Any, ) -> sum[_T]: ... def sum( # noqa: A001 self, col: _ColumnExpressionOrLiteralArgument[_T], *args: _ColumnExpressionOrLiteralArgument[Any], **kwargs: Any, ) -> sum[_T]: ... @property def sysdate(self) -> Type[sysdate]: ... @property def user(self) -> Type[user]: ... # END GENERATED FUNCTION ACCESSORS func = _FunctionGenerator() func.__doc__ = _FunctionGenerator.__doc__ modifier = _FunctionGenerator(group=False) class Function(FunctionElement[_T]): r"""Describe a named SQL function. The :class:`.Function` object is typically generated from the :data:`.func` generation object. :param \*clauses: list of column expressions that form the arguments of the SQL function call. :param type\_: optional :class:`.TypeEngine` datatype object that will be used as the return value of the column expression generated by this function call. :param packagenames: a string which indicates package prefix names to be prepended to the function name when the SQL is generated. The :data:`.func` generator creates these when it is called using dotted format, e.g.:: func.mypackage.some_function(col1, col2) .. seealso:: :ref:`tutorial_functions` - in the :ref:`unified_tutorial` :data:`.func` - namespace which produces registered or ad-hoc :class:`.Function` instances. :class:`.GenericFunction` - allows creation of registered function types. """ __visit_name__ = "function" _traverse_internals = FunctionElement._traverse_internals + [ ("packagenames", InternalTraversal.dp_plain_obj), ("name", InternalTraversal.dp_string), ("type", InternalTraversal.dp_type), ] name: str identifier: str type: TypeEngine[_T] """A :class:`_types.TypeEngine` object which refers to the SQL return type represented by this SQL function. This datatype may be configured when generating a :class:`_functions.Function` object by passing the :paramref:`_functions.Function.type_` parameter, e.g.:: >>> select(func.lower("some VALUE", type_=String)) The small number of built-in classes of :class:`_functions.Function` come with a built-in datatype that's appropriate to the class of function and its arguments. For functions that aren't known, the type defaults to the "null type". """ @overload def __init__( self, name: str, *clauses: _ColumnExpressionOrLiteralArgument[_T], type_: None = ..., packagenames: Optional[Tuple[str, ...]] = ..., ): ... @overload def __init__( self, name: str, *clauses: _ColumnExpressionOrLiteralArgument[Any], type_: _TypeEngineArgument[_T] = ..., packagenames: Optional[Tuple[str, ...]] = ..., ): ... def __init__( self, name: str, *clauses: _ColumnExpressionOrLiteralArgument[Any], type_: Optional[_TypeEngineArgument[_T]] = None, packagenames: Optional[Tuple[str, ...]] = None, ): """Construct a :class:`.Function`. The :data:`.func` construct is normally used to construct new :class:`.Function` instances. """ self.packagenames = packagenames or () self.name = name # if type is None, we get NULLTYPE, which is our _T. But I don't # know how to get the overloads to express that correctly self.type = type_api.to_instance(type_) # type: ignore FunctionElement.__init__(self, *clauses) def _bind_param( self, operator: OperatorType, obj: Any, type_: Optional[TypeEngine[_T]] = None, expanding: bool = False, **kw: Any, ) -> BindParameter[_T]: return BindParameter( self.name, obj, _compared_to_operator=operator, _compared_to_type=self.type, type_=type_, unique=True, expanding=expanding, **kw, ) class GenericFunction(Function[_T]): """Define a 'generic' function. A generic function is a pre-established :class:`.Function` class that is instantiated automatically when called by name from the :data:`.func` attribute. Note that calling any name from :data:`.func` has the effect that a new :class:`.Function` instance is created automatically, given that name. The primary use case for defining a :class:`.GenericFunction` class is so that a function of a particular name may be given a fixed return type. It can also include custom argument parsing schemes as well as additional methods. Subclasses of :class:`.GenericFunction` are automatically registered under the name of the class. For example, a user-defined function ``as_utc()`` would be available immediately:: from sqlalchemy.sql.functions import GenericFunction from sqlalchemy.types import DateTime class as_utc(GenericFunction): type = DateTime() inherit_cache = True print(select(func.as_utc())) User-defined generic functions can be organized into packages by specifying the "package" attribute when defining :class:`.GenericFunction`. Third party libraries containing many functions may want to use this in order to avoid name conflicts with other systems. For example, if our ``as_utc()`` function were part of a package "time":: class as_utc(GenericFunction): type = DateTime() package = "time" inherit_cache = True The above function would be available from :data:`.func` using the package name ``time``:: print(select(func.time.as_utc())) A final option is to allow the function to be accessed from one name in :data:`.func` but to render as a different name. The ``identifier`` attribute will override the name used to access the function as loaded from :data:`.func`, but will retain the usage of ``name`` as the rendered name:: class GeoBuffer(GenericFunction): type = Geometry() package = "geo" name = "ST_Buffer" identifier = "buffer" inherit_cache = True The above function will render as follows: .. sourcecode:: pycon+sql >>> print(func.geo.buffer()) {printsql}ST_Buffer() The name will be rendered as is, however without quoting unless the name contains special characters that require quoting. To force quoting on or off for the name, use the :class:`.sqlalchemy.sql.quoted_name` construct:: from sqlalchemy.sql import quoted_name class GeoBuffer(GenericFunction): type = Geometry() package = "geo" name = quoted_name("ST_Buffer", True) identifier = "buffer" inherit_cache = True The above function will render as: .. sourcecode:: pycon+sql >>> print(func.geo.buffer()) {printsql}"ST_Buffer"() Type parameters for this class as a `generic type <https://peps.python.org/pep-0484/#generics>`_ can be passed and should match the type seen in a :class:`_engine.Result`. For example:: class as_utc(GenericFunction[datetime.datetime]): type = DateTime() inherit_cache = True The above indicates that the following expression returns a ``datetime`` object:: connection.scalar(select(func.as_utc())) .. versionadded:: 1.3.13 The :class:`.quoted_name` construct is now recognized for quoting when used with the "name" attribute of the object, so that quoting can be forced on or off for the function name. """ coerce_arguments = True inherit_cache = True _register: bool name = "GenericFunction" def __init_subclass__(cls) -> None: if annotation.Annotated not in cls.__mro__: cls._register_generic_function(cls.__name__, cls.__dict__) super().__init_subclass__() @classmethod def _register_generic_function( cls, clsname: str, clsdict: Mapping[str, Any] ) -> None: cls.name = name = clsdict.get("name", clsname) cls.identifier = identifier = clsdict.get("identifier", name) package = clsdict.get("package", "_default") # legacy if "__return_type__" in clsdict: cls.type = clsdict["__return_type__"] # Check _register attribute status cls._register = getattr(cls, "_register", True) # Register the function if required if cls._register: register_function(identifier, cls, package) else: # Set _register to True to register child classes by default cls._register = True def __init__( self, *args: _ColumnExpressionOrLiteralArgument[Any], **kwargs: Any ): parsed_args = kwargs.pop("_parsed_args", None) if parsed_args is None: parsed_args = [ coercions.expect( roles.ExpressionElementRole, c, name=self.name, apply_propagate_attrs=self, ) for c in args ] self._has_args = self._has_args or bool(parsed_args) self.packagenames = () self.clause_expr = Grouping( ClauseList( operator=operators.comma_op, group_contents=True, *parsed_args ) ) self.type = type_api.to_instance( # type: ignore kwargs.pop("type_", None) or getattr(self, "type", None) ) register_function("cast", Cast) # type: ignore register_function("extract", Extract) # type: ignore class next_value(GenericFunction[int]): """Represent the 'next value', given a :class:`.Sequence` as its single argument. Compiles into the appropriate function on each backend, or will raise NotImplementedError if used on a backend that does not provide support for sequences. """ type = sqltypes.Integer() name = "next_value" _traverse_internals = [ ("sequence", InternalTraversal.dp_named_ddl_element) ] def __init__(self, seq: schema.Sequence, **kw: Any): assert isinstance( seq, schema.Sequence ), "next_value() accepts a Sequence object as input." self.sequence = seq self.type = sqltypes.to_instance( # type: ignore seq.data_type or getattr(self, "type", None) ) def compare(self, other: Any, **kw: Any) -> bool: return ( isinstance(other, next_value) and self.sequence.name == other.sequence.name ) @property def _from_objects(self) -> Any: return [] class AnsiFunction(GenericFunction[_T]): """Define a function in "ansi" format, which doesn't render parenthesis.""" inherit_cache = True def __init__(self, *args: _ColumnExpressionArgument[Any], **kwargs: Any): GenericFunction.__init__(self, *args, **kwargs) class ReturnTypeFromArgs(GenericFunction[_T]): """Define a function whose return type is the same as its arguments.""" inherit_cache = True # set ColumnElement[_T] as a separate overload, to appease mypy which seems # to not want to accept _T from _ColumnExpressionArgument. this is even if # all non-generic types are removed from it, so reasons remain unclear for # why this does not work @overload def __init__( self, col: ColumnElement[_T], *args: _ColumnExpressionOrLiteralArgument[Any], **kwargs: Any, ): ... @overload def __init__( self, col: _ColumnExpressionArgument[_T], *args: _ColumnExpressionOrLiteralArgument[Any], **kwargs: Any, ): ... @overload def __init__( self, col: _ColumnExpressionOrLiteralArgument[_T], *args: _ColumnExpressionOrLiteralArgument[Any], **kwargs: Any, ): ... def __init__( self, *args: _ColumnExpressionOrLiteralArgument[Any], **kwargs: Any ): fn_args: Sequence[ColumnElement[Any]] = [ coercions.expect( roles.ExpressionElementRole, c, name=self.name, apply_propagate_attrs=self, ) for c in args ] kwargs.setdefault("type_", _type_from_args(fn_args)) kwargs["_parsed_args"] = fn_args super().__init__(*fn_args, **kwargs) class coalesce(ReturnTypeFromArgs[_T]): _has_args = True inherit_cache = True class max(ReturnTypeFromArgs[_T]): # noqa: A001 """The SQL MAX() aggregate function.""" inherit_cache = True class min(ReturnTypeFromArgs[_T]): # noqa: A001 """The SQL MIN() aggregate function.""" inherit_cache = True class sum(ReturnTypeFromArgs[_T]): # noqa: A001 """The SQL SUM() aggregate function.""" inherit_cache = True class now(GenericFunction[datetime.datetime]): """The SQL now() datetime function. SQLAlchemy dialects will usually render this particular function in a backend-specific way, such as rendering it as ``CURRENT_TIMESTAMP``. """ type = sqltypes.DateTime() inherit_cache = True class concat(GenericFunction[str]): """The SQL CONCAT() function, which concatenates strings. E.g.: .. sourcecode:: pycon+sql >>> print(select(func.concat('a', 'b'))) {printsql}SELECT concat(:concat_2, :concat_3) AS concat_1 String concatenation in SQLAlchemy is more commonly available using the Python ``+`` operator with string datatypes, which will render a backend-specific concatenation operator, such as : .. sourcecode:: pycon+sql >>> print(select(literal("a") + "b")) {printsql}SELECT :param_1 || :param_2 AS anon_1 """ type = sqltypes.String() inherit_cache = True class char_length(GenericFunction[int]): """The CHAR_LENGTH() SQL function.""" type = sqltypes.Integer() inherit_cache = True def __init__(self, arg: _ColumnExpressionArgument[str], **kw: Any): # slight hack to limit to just one positional argument # not sure why this one function has this special treatment super().__init__(arg, **kw) class random(GenericFunction[float]): """The RANDOM() SQL function.""" _has_args = True inherit_cache = True class count(GenericFunction[int]): r"""The ANSI COUNT aggregate function. With no arguments, emits COUNT \*. E.g.:: from sqlalchemy import func from sqlalchemy import select from sqlalchemy import table, column my_table = table('some_table', column('id')) stmt = select(func.count()).select_from(my_table) Executing ``stmt`` would emit:: SELECT count(*) AS count_1 FROM some_table """ type = sqltypes.Integer() inherit_cache = True def __init__( self, expression: Union[ _ColumnExpressionArgument[Any], _StarOrOne, None ] = None, **kwargs: Any, ): if expression is None: expression = literal_column("*") super().__init__(expression, **kwargs) class current_date(AnsiFunction[datetime.date]): """The CURRENT_DATE() SQL function.""" type = sqltypes.Date() inherit_cache = True class current_time(AnsiFunction[datetime.time]): """The CURRENT_TIME() SQL function.""" type = sqltypes.Time() inherit_cache = True class current_timestamp(AnsiFunction[datetime.datetime]): """The CURRENT_TIMESTAMP() SQL function.""" type = sqltypes.DateTime() inherit_cache = True class current_user(AnsiFunction[str]): """The CURRENT_USER() SQL function.""" type = sqltypes.String() inherit_cache = True class localtime(AnsiFunction[datetime.datetime]): """The localtime() SQL function.""" type = sqltypes.DateTime() inherit_cache = True class localtimestamp(AnsiFunction[datetime.datetime]): """The localtimestamp() SQL function.""" type = sqltypes.DateTime() inherit_cache = True class session_user(AnsiFunction[str]): """The SESSION_USER() SQL function.""" type = sqltypes.String() inherit_cache = True class sysdate(AnsiFunction[datetime.datetime]): """The SYSDATE() SQL function.""" type = sqltypes.DateTime() inherit_cache = True class user(AnsiFunction[str]): """The USER() SQL function.""" type = sqltypes.String() inherit_cache = True class array_agg(GenericFunction[_T]): """Support for the ARRAY_AGG function. The ``func.array_agg(expr)`` construct returns an expression of type :class:`_types.ARRAY`. e.g.:: stmt = select(func.array_agg(table.c.values)[2:5]) .. seealso:: :func:`_postgresql.array_agg` - PostgreSQL-specific version that returns :class:`_postgresql.ARRAY`, which has PG-specific operators added. """ inherit_cache = True def __init__(self, *args: _ColumnExpressionArgument[Any], **kwargs: Any): fn_args: Sequence[ColumnElement[Any]] = [ coercions.expect( roles.ExpressionElementRole, c, apply_propagate_attrs=self ) for c in args ] default_array_type = kwargs.pop("_default_array_type", sqltypes.ARRAY) if "type_" not in kwargs: type_from_args = _type_from_args(fn_args) if isinstance(type_from_args, sqltypes.ARRAY): kwargs["type_"] = type_from_args else: kwargs["type_"] = default_array_type( type_from_args, dimensions=1 ) kwargs["_parsed_args"] = fn_args super().__init__(*fn_args, **kwargs) class OrderedSetAgg(GenericFunction[_T]): """Define a function where the return type is based on the sort expression type as defined by the expression passed to the :meth:`.FunctionElement.within_group` method.""" array_for_multi_clause = False inherit_cache = True def within_group_type( self, within_group: WithinGroup[Any] ) -> TypeEngine[Any]: func_clauses = cast(ClauseList, self.clause_expr.element) order_by: Sequence[ColumnElement[Any]] = sqlutil.unwrap_order_by( within_group.order_by ) if self.array_for_multi_clause and len(func_clauses.clauses) > 1: return sqltypes.ARRAY(order_by[0].type) else: return order_by[0].type class mode(OrderedSetAgg[_T]): """Implement the ``mode`` ordered-set aggregate function. This function must be used with the :meth:`.FunctionElement.within_group` modifier to supply a sort expression to operate upon. The return type of this function is the same as the sort expression. """ inherit_cache = True class percentile_cont(OrderedSetAgg[_T]): """Implement the ``percentile_cont`` ordered-set aggregate function. This function must be used with the :meth:`.FunctionElement.within_group` modifier to supply a sort expression to operate upon. The return type of this function is the same as the sort expression, or if the arguments are an array, an :class:`_types.ARRAY` of the sort expression's type. """ array_for_multi_clause = True inherit_cache = True class percentile_disc(OrderedSetAgg[_T]): """Implement the ``percentile_disc`` ordered-set aggregate function. This function must be used with the :meth:`.FunctionElement.within_group` modifier to supply a sort expression to operate upon. The return type of this function is the same as the sort expression, or if the arguments are an array, an :class:`_types.ARRAY` of the sort expression's type. """ array_for_multi_clause = True inherit_cache = True class rank(GenericFunction[int]): """Implement the ``rank`` hypothetical-set aggregate function. This function must be used with the :meth:`.FunctionElement.within_group` modifier to supply a sort expression to operate upon. The return type of this function is :class:`.Integer`. """ type = sqltypes.Integer() inherit_cache = True class dense_rank(GenericFunction[int]): """Implement the ``dense_rank`` hypothetical-set aggregate function. This function must be used with the :meth:`.FunctionElement.within_group` modifier to supply a sort expression to operate upon. The return type of this function is :class:`.Integer`. """ type = sqltypes.Integer() inherit_cache = True class percent_rank(GenericFunction[decimal.Decimal]): """Implement the ``percent_rank`` hypothetical-set aggregate function. This function must be used with the :meth:`.FunctionElement.within_group` modifier to supply a sort expression to operate upon. The return type of this function is :class:`.Numeric`. """ type: sqltypes.Numeric[decimal.Decimal] = sqltypes.Numeric() inherit_cache = True class cume_dist(GenericFunction[decimal.Decimal]): """Implement the ``cume_dist`` hypothetical-set aggregate function. This function must be used with the :meth:`.FunctionElement.within_group` modifier to supply a sort expression to operate upon. The return type of this function is :class:`.Numeric`. """ type: sqltypes.Numeric[decimal.Decimal] = sqltypes.Numeric() inherit_cache = True class cube(GenericFunction[_T]): r"""Implement the ``CUBE`` grouping operation. This function is used as part of the GROUP BY of a statement, e.g. :meth:`_expression.Select.group_by`:: stmt = select( func.sum(table.c.value), table.c.col_1, table.c.col_2 ).group_by(func.cube(table.c.col_1, table.c.col_2)) .. versionadded:: 1.2 """ _has_args = True inherit_cache = True class rollup(GenericFunction[_T]): r"""Implement the ``ROLLUP`` grouping operation. This function is used as part of the GROUP BY of a statement, e.g. :meth:`_expression.Select.group_by`:: stmt = select( func.sum(table.c.value), table.c.col_1, table.c.col_2 ).group_by(func.rollup(table.c.col_1, table.c.col_2)) .. versionadded:: 1.2 """ _has_args = True inherit_cache = True class grouping_sets(GenericFunction[_T]): r"""Implement the ``GROUPING SETS`` grouping operation. This function is used as part of the GROUP BY of a statement, e.g. :meth:`_expression.Select.group_by`:: stmt = select( func.sum(table.c.value), table.c.col_1, table.c.col_2 ).group_by(func.grouping_sets(table.c.col_1, table.c.col_2)) In order to group by multiple sets, use the :func:`.tuple_` construct:: from sqlalchemy import tuple_ stmt = select( func.sum(table.c.value), table.c.col_1, table.c.col_2, table.c.col_3 ).group_by( func.grouping_sets( tuple_(table.c.col_1, table.c.col_2), tuple_(table.c.value, table.c.col_3), ) ) .. versionadded:: 1.2 """ _has_args = True inherit_cache = True class aggregate_strings(GenericFunction[str]): """Implement a generic string aggregation function. This function will concatenate non-null values into a string and separate the values by a delimiter. This function is compiled on a per-backend basis, into functions such as ``group_concat()``, ``string_agg()``, or ``LISTAGG()``. e.g. Example usage with delimiter '.':: stmt = select(func.aggregate_strings(table.c.str_col, ".")) The return type of this function is :class:`.String`. .. versionadded: 2.0.21 """ type = sqltypes.String() _has_args = True inherit_cache = True def __init__(self, clause: _ColumnExpressionArgument[Any], separator: str): super().__init__(clause, separator)