Current File : //proc/thread-self/root/opt/alt/python37/lib64/python3.7/site-packages/sqlalchemy/sql/functions.py
# sql/functions.py
# Copyright (C) 2005-2019 the SQLAlchemy authors and contributors
# <see AUTHORS file>
#
# 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::
: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):
"""Construct a :class:`.FunctionElement`.
"""
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 :class:`.Function` objects based on getattr calls."""
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()
"""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 element 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.
"""
modifier = _FunctionGenerator(group=False)
class Function(FunctionElement):
"""Describe a named SQL function.
See the superclass :class:`.FunctionElement` for a description
of public methods.
.. seealso::
: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
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