# sql/functions.py # Copyright (C) 2005-2019 the SQLAlchemy authors and contributors # # # This module is part of SQLAlchemy and is released under # the MIT License: http://www.opensource.org/licenses/mit-license.php """SQL function API, factories, and built-in functions. """ from . import annotation from . import operators from . import schema from . import sqltypes from . import util as sqlutil from .base import ColumnCollection from .base import Executable from .elements import _clone from .elements import _literal_as_binds 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 Over from .elements import WithinGroup from .selectable import Alias from .selectable import FromClause from .selectable import Select from .visitors import VisitableType from .. import util _registry = util.defaultdict(dict) _case_sensitive_registry = util.defaultdict(lambda: util.defaultdict(dict)) _CASE_SENSITIVE = util.symbol( name="case_sensitive_function", doc="Symbol to mark the functions that are switched into case-sensitive " "mode.", ) def register_function(identifier, fn, package="_default"): """Associate a callable with a particular func. name. This is normally called by _GenericMeta, 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] case_sensitive_reg = _case_sensitive_registry[package] raw_identifier = identifier identifier = identifier.lower() # Check if a function with the same lowercase identifier is registered. if identifier in reg and reg[identifier] is not _CASE_SENSITIVE: if raw_identifier in case_sensitive_reg[identifier]: util.warn( "The GenericFunction '{}' is already registered and " "is going to be overriden.".format(identifier) ) reg[identifier] = fn else: # If a function with the same lowercase identifier is registered, # then these 2 functions are considered as case-sensitive. # Note: This case should raise an error in a later release. util.warn_deprecated( "GenericFunction '{}' is already registered with " "different letter case, so the previously registered function " "'{}' is switched into case-sensitive mode. " "GenericFunction objects will be fully case-insensitive in a " "future release.".format( raw_identifier, list(case_sensitive_reg[identifier].keys())[0], ) ) reg[identifier] = _CASE_SENSITIVE # Check if a function with different letter case identifier is registered. elif identifier in case_sensitive_reg: # Note: This case will be removed in a later release. if raw_identifier not in case_sensitive_reg[identifier]: util.warn_deprecated( "GenericFunction(s) '{}' are already registered with " "different letter cases and might interact with '{}'. " "GenericFunction objects will be fully case-insensitive in a " "future release.".format( sorted(case_sensitive_reg[identifier].keys()), raw_identifier, ) ) else: util.warn( "The GenericFunction '{}' is already registered and " "is going to be overriden.".format(raw_identifier) ) # Register by default else: reg[identifier] = fn # Always register in case-sensitive registry case_sensitive_reg[identifier][raw_identifier] = fn class FunctionElement(Executable, ColumnElement, FromClause): """Base for SQL function-oriented constructs. .. seealso:: :ref:`coretutorial_functions` - in the Core 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. """ packagenames = () _has_args = False def __init__(self, *clauses, **kwargs): 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 = [_literal_as_binds(c, self.name) for c in clauses] self._has_args = self._has_args or bool(args) self.clause_expr = ClauseList( operator=operators.comma_op, group_contents=True, *args ).self_group() def _execute_on_connection(self, connection, multiparams, params): return connection._execute_function(self, multiparams, params) @property def columns(self): """The set of columns exported by this :class:`.FunctionElement`. Function objects currently have no result column names built in; this method returns a single-element column collection with an anonymously named column. An interim approach to providing named columns for a function as a FROM clause is to build a :func:`.select` with the desired columns:: from sqlalchemy.sql import column stmt = select([column('x'), column('y')]).\ select_from(func.myfunction()) """ return ColumnCollection(self.label(None)) @util.memoized_property def clauses(self): """Return the underlying :class:`.ClauseList` which contains the arguments for this :class:`.FunctionElement`. """ return self.clause_expr.element def over(self, partition_by=None, order_by=None, rows=None, range_=None): """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. """ return Over( self, partition_by=partition_by, order_by=order_by, rows=rows, range_=range_, ) def within_group(self, *order_by): """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. .. versionadded:: 1.1 """ return WithinGroup(self, *order_by) def filter(self, *criterion): """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) .. versionadded:: 1.0.0 .. seealso:: :class:`.FunctionFilter` :func:`.funcfilter` """ if not criterion: return self return FunctionFilter(self, *criterion) def as_comparison(self, left_index, right_index): """Interpret this expression as a boolean comparison between two values. 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:`.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 """ return FunctionAsBinary(self, left_index, right_index) @property def _from_objects(self): return self.clauses._from_objects def get_children(self, **kwargs): return (self.clause_expr,) def _copy_internals(self, clone=_clone, **kw): self.clause_expr = clone(self.clause_expr, **kw) self._reset_exported() FunctionElement.clauses._reset(self) def within_group_type(self, within_group): """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=None, flat=False): r"""Produce a :class:`.Alias` construct against this :class:`.FunctionElement`. This construct wraps the function in a named alias which is suitable for the FROM clause, in the style accepted for example by PostgreSQL. e.g.:: from sqlalchemy.sql import column stmt = select([column('data_view')]).\ select_from(SomeTable).\ select_from(func.unnest(SomeTable.data).alias('data_view') ) Would produce: .. sourcecode:: sql SELECT data_view FROM sometable, unnest(sometable.data) AS data_view .. versionadded:: 0.9.8 The :meth:`.FunctionElement.alias` method is now supported. Previously, this method's behavior was undefined and did not behave consistently across versions. """ return Alias._construct(self, name) def select(self): """Produce a :func:`~.expression.select` construct against this :class:`.FunctionElement`. This is shorthand for:: s = select([function_element]) """ s = Select([self]) if self._execution_options: s = s.execution_options(**self._execution_options) return s def scalar(self): """Execute this :class:`.FunctionElement` against an embedded 'bind' and return a scalar value. This first calls :meth:`~.FunctionElement.select` to produce a SELECT construct. Note that :class:`.FunctionElement` can be passed to the :meth:`.Connectable.scalar` method of :class:`.Connection` or :class:`.Engine`. """ return self.select().execute().scalar() def execute(self): """Execute this :class:`.FunctionElement` against an embedded 'bind'. This first calls :meth:`~.FunctionElement.select` to produce a SELECT construct. Note that :class:`.FunctionElement` can be passed to the :meth:`.Connectable.execute` method of :class:`.Connection` or :class:`.Engine`. """ return self.select().execute() def _bind_param(self, operator, obj, type_=None): return BindParameter( None, obj, _compared_to_operator=operator, _compared_to_type=self.type, unique=True, type_=type_, ) def self_group(self, against=None): # 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(FunctionElement, self).self_group(against=against) class FunctionAsBinary(BinaryExpression): def __init__(self, fn, left_index, right_index): left = fn.clauses.clauses[left_index - 1] right = fn.clauses.clauses[right_index - 1] self.sql_function = fn self.left_index = left_index self.right_index = right_index super(FunctionAsBinary, self).__init__( left, right, operators.function_as_comparison_op, type_=sqltypes.BOOLEANTYPE, ) @property def left(self): return self.sql_function.clauses.clauses[self.left_index - 1] @left.setter def left(self, value): self.sql_function.clauses.clauses[self.left_index - 1] = value @property def right(self): return self.sql_function.clauses.clauses[self.right_index - 1] @right.setter def right(self, value): self.sql_function.clauses.clauses[self.right_index - 1] = value def _copy_internals(self, **kw): clone = kw.pop("clone") self.sql_function = clone(self.sql_function, **kw) super(FunctionAsBinary, self)._copy_internals(**kw) class _FunctionGenerator(object): """Generate SQL function expressions. :data:`.func` is a special object instance which generates SQL functions based on name-based attributes, e.g.:: >>> print(func.count(1)) 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:: >>> print(select([func.count(table.c.id)])) 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:: >>> print(func.current_timestamp()) CURRENT_TIMESTAMP To call functions which are present in dot-separated packages, specify them in the same manner:: >>> print(func.stats.yield_curve(5, 10)) 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: >>> print(func.my_string(u'hi', type_=Unicode) + ' ' + ... func.my_string(u'there', type_=Unicode)) 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:`.Connection` or :class:`.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:`coretutorial_functions` - in the Core Tutorial :class:`.Function` """ def __init__(self, **opts): self.__names = [] self.opts = opts def __getattr__(self, name): # passthru __ attributes; fixes pydoc if name.startswith("__"): try: return self.__dict__[name] except KeyError: raise AttributeError(name) elif name.endswith("_"): name = name[0:-1] f = _FunctionGenerator(**self.opts) f.__names = list(self.__names) + [name] return f def __call__(self, *c, **kwargs): 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 _CASE_SENSITIVE: case_sensitive_reg = _case_sensitive_registry[package] func = case_sensitive_reg.get(fname.lower()).get(fname) if func is not None: return func(*c, **o) return Function( self.__names[-1], packagenames=self.__names[0:-1], *c, **o ) func = _FunctionGenerator() func.__doc__ = _FunctionGenerator.__doc__ modifier = _FunctionGenerator(group=False) class Function(FunctionElement): 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:`coretutorial_functions` :data:`.func` - namespace which produces registered or ad-hoc :class:`.Function` instances. :class:`.GenericFunction` - allows creation of registered function types. """ __visit_name__ = "function" def __init__(self, name, *clauses, **kw): """Construct a :class:`.Function`. The :data:`.func` construct is normally used to construct new :class:`.Function` instances. """ self.packagenames = kw.pop("packagenames", None) or [] self.name = name self._bind = kw.get("bind", None) self.type = sqltypes.to_instance(kw.get("type_", None)) FunctionElement.__init__(self, *clauses, **kw) def _bind_param(self, operator, obj, type_=None): return BindParameter( self.name, obj, _compared_to_operator=operator, _compared_to_type=self.type, type_=type_, unique=True, ) class _GenericMeta(VisitableType): def __init__(cls, clsname, bases, clsdict): if annotation.Annotated not in cls.__mro__: cls.name = name = clsdict.get("name", clsname) cls.identifier = identifier = clsdict.get("identifier", name) package = clsdict.pop("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 super(_GenericMeta, cls).__init__(clsname, bases, clsdict) class GenericFunction(util.with_metaclass(_GenericMeta, Function)): """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 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" 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" The above function will render as follows:: >>> print func.geo.buffer() ST_Buffer() """ coerce_arguments = True _register = False def __init__(self, *args, **kwargs): parsed_args = kwargs.pop("_parsed_args", None) if parsed_args is None: parsed_args = [_literal_as_binds(c, self.name) for c in args] self._has_args = self._has_args or bool(parsed_args) self.packagenames = [] self._bind = kwargs.get("bind", None) self.clause_expr = ClauseList( operator=operators.comma_op, group_contents=True, *parsed_args ).self_group() self.type = sqltypes.to_instance( kwargs.pop("type_", None) or getattr(self, "type", None) ) register_function("cast", Cast) register_function("extract", Extract) class next_value(GenericFunction): """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" def __init__(self, seq, **kw): assert isinstance( seq, schema.Sequence ), "next_value() accepts a Sequence object as input." self._bind = kw.get("bind", None) self.sequence = seq @property def _from_objects(self): return [] class AnsiFunction(GenericFunction): def __init__(self, *args, **kwargs): GenericFunction.__init__(self, *args, **kwargs) class ReturnTypeFromArgs(GenericFunction): """Define a function whose return type is the same as its arguments.""" def __init__(self, *args, **kwargs): args = [_literal_as_binds(c, self.name) for c in args] kwargs.setdefault("type_", _type_from_args(args)) kwargs["_parsed_args"] = args super(ReturnTypeFromArgs, self).__init__(*args, **kwargs) class coalesce(ReturnTypeFromArgs): _has_args = True class max(ReturnTypeFromArgs): # noqa pass class min(ReturnTypeFromArgs): # noqa pass class sum(ReturnTypeFromArgs): # noqa pass class now(GenericFunction): # noqa type = sqltypes.DateTime class concat(GenericFunction): type = sqltypes.String class char_length(GenericFunction): type = sqltypes.Integer def __init__(self, arg, **kwargs): GenericFunction.__init__(self, arg, **kwargs) class random(GenericFunction): _has_args = True class count(GenericFunction): 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 def __init__(self, expression=None, **kwargs): if expression is None: expression = literal_column("*") super(count, self).__init__(expression, **kwargs) class current_date(AnsiFunction): type = sqltypes.Date class current_time(AnsiFunction): type = sqltypes.Time class current_timestamp(AnsiFunction): type = sqltypes.DateTime class current_user(AnsiFunction): type = sqltypes.String class localtime(AnsiFunction): type = sqltypes.DateTime class localtimestamp(AnsiFunction): type = sqltypes.DateTime class session_user(AnsiFunction): type = sqltypes.String class sysdate(AnsiFunction): type = sqltypes.DateTime class user(AnsiFunction): type = sqltypes.String class array_agg(GenericFunction): """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]]) .. versionadded:: 1.1 .. seealso:: :func:`.postgresql.array_agg` - PostgreSQL-specific version that returns :class:`.postgresql.ARRAY`, which has PG-specific operators added. """ type = sqltypes.ARRAY def __init__(self, *args, **kwargs): args = [_literal_as_binds(c) 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(args) if isinstance(type_from_args, sqltypes.ARRAY): kwargs["type_"] = type_from_args else: kwargs["type_"] = default_array_type(type_from_args) kwargs["_parsed_args"] = args super(array_agg, self).__init__(*args, **kwargs) class OrderedSetAgg(GenericFunction): """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 def within_group_type(self, within_group): func_clauses = self.clause_expr.element order_by = 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): """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. .. versionadded:: 1.1 """ class percentile_cont(OrderedSetAgg): """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. .. versionadded:: 1.1 """ array_for_multi_clause = True class percentile_disc(OrderedSetAgg): """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. .. versionadded:: 1.1 """ array_for_multi_clause = True class rank(GenericFunction): """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`. .. versionadded:: 1.1 """ type = sqltypes.Integer() class dense_rank(GenericFunction): """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`. .. versionadded:: 1.1 """ type = sqltypes.Integer() class percent_rank(GenericFunction): """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`. .. versionadded:: 1.1 """ type = sqltypes.Numeric() class cume_dist(GenericFunction): """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`. .. versionadded:: 1.1 """ type = sqltypes.Numeric() class cube(GenericFunction): r"""Implement the ``CUBE`` grouping operation. This function is used as part of the GROUP BY of a statement, e.g. :meth:`.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 class rollup(GenericFunction): r"""Implement the ``ROLLUP`` grouping operation. This function is used as part of the GROUP BY of a statement, e.g. :meth:`.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 class grouping_sets(GenericFunction): r"""Implement the ``GROUPING SETS`` grouping operation. This function is used as part of the GROUP BY of a statement, e.g. :meth:`.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