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bazarr/libs/sqlalchemy/sql/functions.py

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# sql/functions.py
# Copyright (C) 2005-2023 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
# mypy: allow-untyped-defs, allow-untyped-calls
"""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 Mapping
from typing import Optional
from typing import overload
from typing import Tuple
from typing import Type
from typing import TYPE_CHECKING
from typing import TypeVar
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 _TypeEngineArgument
from ..engine.base import Connection
from ..engine.cursor import CursorResult
from ..engine.interfaces import _CoreMultiExecuteParams
from ..engine.interfaces import CoreExecuteOptionsParameter
_T = TypeVar("_T", bound=Any)
_registry: util.defaultdict[
str, Dict[str, Type[Function[Any]]]
] = util.defaultdict(dict)
def register_function(identifier, fn, package="_default"):
"""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: 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 = [
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):
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, type_=None):
"""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, **kw):
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=None, joins_implicitly=False):
"""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):
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):
"""synonym for :attr:`.FunctionElement.columns`."""
return ColumnCollection(
columns=[(col.key, col) for col in self._all_selected_columns]
)
@property
def _all_selected_columns(self):
if is_table_value_type(self.type):
cols = self.type._elements
else:
cols = [self.label(None)]
return cols
@property
def exported_columns(self):
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=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.
.. 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):
"""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
.. seealso::
:ref:`tutorial_functions_within_group` -
in the :ref:`unified_tutorial`
"""
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::
: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, right_index):
"""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):
return self.clauses._from_objects
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, joins_implicitly=False):
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[Any]:
"""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, obj, type_=None, **kw):
return BindParameter(
None,
obj,
_compared_to_operator=operator,
_compared_to_type=self.type,
unique=True,
type_=type_,
**kw,
)
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().self_group(against=against)
@property
def entity_namespace(self):
"""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, bindparams):
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):
self.__names = []
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 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]:
...
@property
def coalesce(self) -> Type[coalesce[Any]]:
...
@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]:
...
@property
def max(self) -> Type[max[Any]]: # noqa: A001
...
@property
def min(self) -> Type[min[Any]]: # noqa: A001
...
@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 returntypefromargs(self) -> Type[ReturnTypeFromArgs[Any]]:
...
@property
def rollup(self) -> Type[rollup[Any]]:
...
@property
def session_user(self) -> Type[session_user]:
...
@property
def sum(self) -> Type[sum[Any]]: # noqa: A001
...
@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".
"""
def __init__(
self,
name: str,
*clauses: 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, obj, type_=None, **kw):
return BindParameter(
self.name,
obj,
_compared_to_operator=operator,
_compared_to_type=self.type,
type_=type_,
unique=True,
**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, **kwargs):
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)
register_function("extract", Extract)
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, **kw):
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, **kw):
return (
isinstance(other, next_value)
and self.sequence.name == other.sequence.name
)
@property
def _from_objects(self):
return []
class AnsiFunction(GenericFunction[_T]):
"""Define a function in "ansi" format, which doesn't render parenthesis."""
inherit_cache = True
def __init__(self, *args, **kwargs):
GenericFunction.__init__(self, *args, **kwargs)
class ReturnTypeFromArgs(GenericFunction[_T]):
"""Define a function whose return type is the same as its arguments."""
inherit_cache = True
def __init__(self, *args, **kwargs):
fn_args = [
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, **kw):
# 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=None, **kwargs):
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])
.. versionadded:: 1.1
.. 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, **kwargs):
fn_args = [
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):
func_clauses = cast(ClauseList, 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[_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.
.. versionadded:: 1.1
"""
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.
.. versionadded:: 1.1
"""
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.
.. versionadded:: 1.1
"""
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`.
.. versionadded:: 1.1
"""
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`.
.. versionadded:: 1.1
"""
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`.
.. versionadded:: 1.1
"""
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`.
.. versionadded:: 1.1
"""
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
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