SQLAlchemy 1.4 Documentation
SQLAlchemy Core
- SQL Expression Language Tutorial (1.x API)
- SQL Statements and Expressions API
- Column Elements and Expressions
- Operator Reference
- Selectables, Tables, FROM objects
- Insert, Updates, Deletes
- SQL and Generic Functions¶
- Function API
AnsiFunction
Function
FunctionElement
FunctionElement.__init__()
FunctionElement.alias()
FunctionElement.as_comparison()
FunctionElement.clauses
FunctionElement.column_valued()
FunctionElement.columns
FunctionElement.entity_namespace
FunctionElement.execute()
FunctionElement.exported_columns
FunctionElement.filter()
FunctionElement.over()
FunctionElement.scalar()
FunctionElement.scalar_table_valued()
FunctionElement.select()
FunctionElement.self_group()
FunctionElement.table_valued()
FunctionElement.within_group()
FunctionElement.within_group_type()
GenericFunction
register_function()
- Selected “Known” Functions
- Function API
- Custom SQL Constructs and Compilation Extension
- Expression Serializer Extension
- SQL Expression Language Foundational Constructs
- Visitor and Traversal Utilities
- Schema Definition Language
- SQL Datatype Objects
- Engine and Connection Use
- Core API Basics
- SQLAlchemy 2.0 Future (Core)
Project Versions
- Previous: Insert, Updates, Deletes
- Next: Custom SQL Constructs and Compilation Extension
- Up: Home
- On this page:
- SQL and Generic Functions
- Function API
AnsiFunction
Function
FunctionElement
FunctionElement.__init__()
FunctionElement.alias()
FunctionElement.as_comparison()
FunctionElement.clauses
FunctionElement.column_valued()
FunctionElement.columns
FunctionElement.entity_namespace
FunctionElement.execute()
FunctionElement.exported_columns
FunctionElement.filter()
FunctionElement.over()
FunctionElement.scalar()
FunctionElement.scalar_table_valued()
FunctionElement.select()
FunctionElement.self_group()
FunctionElement.table_valued()
FunctionElement.within_group()
FunctionElement.within_group_type()
GenericFunction
register_function()
- Selected “Known” Functions
- Function API
SQL and Generic Functions¶
SQL functions are invoked by using the func
namespace.
See the tutorial at Working with SQL Functions for background on how to
use the func
object to render SQL functions in statements.
See also
Working with SQL Functions - in the SQLAlchemy 1.4 / 2.0 Tutorial
Function API¶
The base API for SQL functions, which provides for the func
namespace as well as classes that may be used for extensibility.
Object Name | Description |
---|---|
Define a function in “ansi” format, which doesn’t render parenthesis. |
|
Describe a named SQL function. |
|
Base for SQL function-oriented constructs. |
|
Define a ‘generic’ function. |
|
register_function(identifier, fn[, package]) |
Associate a callable with a particular func. name. |
- class sqlalchemy.sql.functions.AnsiFunction(*args, **kwargs)¶
Define a function in “ansi” format, which doesn’t render parenthesis.
Class signature
class
sqlalchemy.sql.functions.AnsiFunction
(sqlalchemy.sql.functions.GenericFunction
)
- class sqlalchemy.sql.functions.Function(name, *clauses, **kw)¶
Describe a named SQL function.
The
Function
object is typically generated from thefunc
generation object.- Parameters:
*clauses¶ – list of column expressions that form the arguments of the SQL function call.
type_¶ – optional
TypeEngine
datatype object that will be used as the return value of the column expression generated by this function call.packagenames¶ –
a string which indicates package prefix names to be prepended to the function name when the SQL is generated. The
func
generator creates these when it is called using dotted format, e.g.:func.mypackage.some_function(col1, col2)
See also
Working with SQL Functions - in the SQLAlchemy 1.4 / 2.0 Tutorial
func
- namespace which produces registered or ad-hocFunction
instances.GenericFunction
- allows creation of registered function types.Class signature
class
sqlalchemy.sql.functions.Function
(sqlalchemy.sql.functions.FunctionElement
)
- class sqlalchemy.sql.functions.FunctionElement(*clauses, **kwargs)¶
Base for SQL function-oriented constructs.
See also
Working with SQL Functions - in the SQLAlchemy 1.4 / 2.0 Tutorial
Function
- named SQL function.func
- namespace which produces registered or ad-hocFunction
instances.GenericFunction
- allows creation of registered function types.Members
__init__(), alias(), as_comparison(), clauses, column_valued(), columns, entity_namespace, execute(), exported_columns, filter(), over(), scalar(), scalar_table_valued(), select(), self_group(), table_valued(), within_group(), within_group_type()
Class signature
class
sqlalchemy.sql.functions.FunctionElement
(sqlalchemy.sql.expression.Executable
,sqlalchemy.sql.expression.ColumnElement
,sqlalchemy.sql.expression.FromClause
,sqlalchemy.sql.expression.Generative
)-
method
sqlalchemy.sql.functions.FunctionElement.
__init__(*clauses, **kwargs)¶ Construct a
FunctionElement
.
-
method
sqlalchemy.sql.functions.FunctionElement.
alias(name=None, joins_implicitly=False)¶ Produce a
Alias
construct against thisFunctionElement
.Tip
The
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 onFunctionElement
includingFunctionElement.table_valued()
, andFunctionElement.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
FunctionElement.table_valued()
method first to establish named columns.e.g.:
>>> from sqlalchemy import func, select, column >>> data_view = func.unnest([1, 2, 3]).alias("data_view") >>> print(select(data_view.column)) SELECT data_view FROM unnest(:unnest_1) AS data_view
The
FunctionElement.column_valued()
method provides a shortcut for the above pattern:>>> data_view = func.unnest([1, 2, 3]).column_valued("data_view") >>> print(select(data_view)) SELECT data_view FROM unnest(:unnest_1) AS data_view
New in version 1.4.0b2: Added the
.column
accessor- Parameters:
name¶ – alias name, will be rendered as
AS <name>
in the FROM clausejoins_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()
.New in version 1.4.33.
-
method
sqlalchemy.sql.functions.FunctionElement.
as_comparison(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 Custom operators based on SQL functions.
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
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
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
relationship.primaryjoin
parameter. The return value is a containment object calledFunctionAsBinary
.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.
- Parameters:
New in version 1.3.
See also
Custom operators based on SQL functions - example use within the ORM
-
attribute
sqlalchemy.sql.functions.FunctionElement.
clauses¶ Return the underlying
ClauseList
which contains the arguments for thisFunctionElement
.
-
method
sqlalchemy.sql.functions.FunctionElement.
column_valued(name=None, joins_implicitly=False)¶ Return this
FunctionElement
as a column expression that selects from itself as a FROM clause.E.g.:
>>> from sqlalchemy import select, func >>> gs = func.generate_series(1, 5, -1).column_valued() >>> print(select(gs)) 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
- Parameters:
name¶ – optional name to assign to the alias name that’s generated. If omitted, a unique anonymizing name is used.
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()
.New in version 1.4.46.
See also
Column Valued Functions - Table Valued Function as a Scalar Column - in the SQLAlchemy 1.4 / 2.0 Tutorial
Column Valued Functions - in the PostgreSQL documentation
-
attribute
sqlalchemy.sql.functions.FunctionElement.
columns¶ The set of columns exported by this
FunctionElement
.This is a placeholder collection that allows the function to be placed in the FROM clause of a statement:
>>> from sqlalchemy import column, select, func >>> stmt = select(column('x'), column('y')).select_from(func.myfunction()) >>> print(stmt) SELECT x, y FROM myfunction()
The above form is a legacy feature that is now superseded by the fully capable
FunctionElement.table_valued()
method; see that method for details.See also
FunctionElement.table_valued()
- generates table-valued SQL function expressions.
-
attribute
sqlalchemy.sql.functions.FunctionElement.
entity_namespace¶ overrides FromClause.entity_namespace as functions are generally column expressions and not FromClauses.
-
method
sqlalchemy.sql.functions.FunctionElement.
execute()¶ Execute this
FunctionElement
against an embedded ‘bind’.Deprecated since version 1.4: The
FunctionElement.execute()
method is considered legacy as of the 1.x series of SQLAlchemy and will be removed in 2.0. All statement execution in SQLAlchemy 2.0 is performed by theConnection.execute()
method ofConnection
, or in the ORM by theSession.execute()
method ofSession
. (Background on SQLAlchemy 2.0 at: Migrating to SQLAlchemy 2.0)This first calls
FunctionElement.select()
to produce a SELECT construct.Note that
FunctionElement
can be passed to theConnectable.execute()
method ofConnection
orEngine
.
-
attribute
sqlalchemy.sql.functions.FunctionElement.
exported_columns¶
-
method
sqlalchemy.sql.functions.FunctionElement.
filter(*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)
New in version 1.0.0.
-
method
sqlalchemy.sql.functions.FunctionElement.
over(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
over()
for a full description.
-
method
sqlalchemy.sql.functions.FunctionElement.
scalar()¶ Execute this
FunctionElement
against an embedded ‘bind’ and return a scalar value.Deprecated since version 1.4: The
FunctionElement.scalar()
method is considered legacy as of the 1.x series of SQLAlchemy and will be removed in 2.0. Scalar execution in SQLAlchemy 2.0 is performed by theConnection.scalar()
method ofConnection
, or in the ORM by theSession.scalar()
method ofSession
. (Background on SQLAlchemy 2.0 at: Migrating to SQLAlchemy 2.0)This first calls
FunctionElement.select()
to produce a SELECT construct.Note that
FunctionElement
can be passed to theConnectable.scalar()
method ofConnection
orEngine
.
-
method
sqlalchemy.sql.functions.FunctionElement.
scalar_table_valued(name, type_=None)¶ Return a column expression that’s against this
FunctionElement
as a scalar table-valued expression.The returned expression is similar to that returned by a single column accessed off of a
FunctionElement.table_valued()
construct, except no FROM clause is generated; the function is rendered in the similar way as a scalar subquery.E.g.:
>>> from sqlalchemy import func, select >>> fn = func.jsonb_each("{'k', 'v'}").scalar_table_valued("key") >>> print(select(fn)) SELECT (jsonb_each(:jsonb_each_1)).key
New in version 1.4.0b2.
-
method
sqlalchemy.sql.functions.FunctionElement.
select()¶ Produce a
select()
construct against thisFunctionElement
.This is shorthand for:
s = select(function_element)
-
method
sqlalchemy.sql.functions.FunctionElement.
self_group(against=None)¶ Apply a ‘grouping’ to this
ClauseElement
.This method is overridden by subclasses to return a “grouping” construct, i.e. parenthesis. In particular it’s used by “binary” expressions to provide a grouping around themselves when placed into a larger expression, as well as by
select()
constructs when placed into the FROM clause of anotherselect()
. (Note that subqueries should be normally created using theSelect.alias()
method, as many platforms require nested SELECT statements to be named).As expressions are composed together, the application of
self_group()
is automatic - end-user code should never need to use this method directly. Note that SQLAlchemy’s clause constructs take operator precedence into account - so parenthesis might not be needed, for example, in an expression likex OR (y AND z)
- AND takes precedence over OR.The base
self_group()
method ofClauseElement
just returns self.
-
method
sqlalchemy.sql.functions.FunctionElement.
table_valued(*expr, **kw)¶ Return a
TableValuedAlias
representation of thisFunctionElement
with table-valued expressions added.e.g.:
>>> fn = ( ... func.generate_series(1, 5). ... table_valued("value", "start", "stop", "step") ... ) >>> print(select(fn)) 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 >>> print(select(fn.c.value, fn.c.stop).where(fn.c.value > 2)) 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
A WITH ORDINALITY expression may be generated by passing the keyword argument “with_ordinality”:
>>> fn = func.generate_series(4, 1, -1).table_valued("gen", with_ordinality="ordinality") >>> print(select(fn)) SELECT anon_1.gen, anon_1.ordinality FROM generate_series(:generate_series_1, :generate_series_2, :generate_series_3) WITH ORDINALITY AS anon_1
- Parameters:
*expr¶ – A series of string column names that will be added to the
.c
collection of the resultingTableValuedAlias
construct as columns.column()
objects with or without datatypes may also be used.name¶ – optional name to assign to the alias name that’s generated. If omitted, a unique anonymizing name is used.
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 resultingTableValuedAlias
.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()
.New in version 1.4.33.
New in version 1.4.0b2.
See also
Table-Valued Functions - in the SQLAlchemy 1.4 / 2.0 Tutorial
Table-Valued Functions - in the PostgreSQL documentation
FunctionElement.scalar_table_valued()
- variant ofFunctionElement.table_valued()
which delivers the complete table valued expression as a scalar column expressionFunctionElement.column_valued()
TableValuedAlias.render_derived()
- renders the alias using a derived column clause, e.g.AS name(col1, col2, ...)
-
method
sqlalchemy.sql.functions.FunctionElement.
within_group(*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
percentile_cont
,rank
,dense_rank
, etc.See
within_group()
for a full description.New in version 1.1.
See also
Special Modifiers WITHIN GROUP, FILTER - in the SQLAlchemy 1.4 / 2.0 Tutorial
-
method
sqlalchemy.sql.functions.FunctionElement.
within_group_type(within_group)¶ For types that define their return type as based on the criteria within a WITHIN GROUP (ORDER BY) expression, called by the
WithinGroup
construct.Returns None by default, in which case the function’s normal
.type
is used.
-
method
- class sqlalchemy.sql.functions.GenericFunction(*args, **kwargs)¶
Define a ‘generic’ function.
A generic function is a pre-established
Function
class that is instantiated automatically when called by name from thefunc
attribute. Note that calling any name fromfunc
has the effect that a newFunction
instance is created automatically, given that name. The primary use case for defining aGenericFunction
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
GenericFunction
are automatically registered under the name of the class. For example, a user-defined functionas_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
GenericFunction
. Third party libraries containing many functions may want to use this in order to avoid name conflicts with other systems. For example, if ouras_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
func
using the package nametime
:print(select(func.time.as_utc()))
A final option is to allow the function to be accessed from one name in
func
but to render as a different name. Theidentifier
attribute will override the name used to access the function as loaded fromfunc
, but will retain the usage ofname
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:
>>> print(func.geo.buffer()) 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
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:
>>> print(func.geo.buffer()) "ST_Buffer"()
New in version 1.3.13: The
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.Class signature
class
sqlalchemy.sql.functions.GenericFunction
(sqlalchemy.sql.functions.Function
)
- function sqlalchemy.sql.functions.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
func
accessor (i.e. CAST, EXTRACT).
Selected “Known” Functions¶
These are GenericFunction
implementations for a selected set of
common SQL functions that set up the expected return type for each function
automatically. The are invoked in the same way as any other member of the
func
namespace:
select(func.count("*")).select_from(some_table)
Note that any name not known to func
generates the function name
as is - there is no restriction on what SQL functions can be called, known or
unknown to SQLAlchemy, built-in or user defined. The section here only
describes those functions where SQLAlchemy already knows what argument and
return types are in use.
Object Name | Description |
---|---|
Support for the ARRAY_AGG function. |
|
The CHAR_LENGTH() SQL function. |
|
The SQL CONCAT() function, which concatenates strings. |
|
The ANSI COUNT aggregate function. With no arguments, emits COUNT *. |
|
Implement the |
|
Implement the |
|
The CURRENT_DATE() SQL function. |
|
The CURRENT_TIME() SQL function. |
|
The CURRENT_TIMESTAMP() SQL function. |
|
The CURRENT_USER() SQL function. |
|
Implement the |
|
Implement the |
|
The localtime() SQL function. |
|
The localtimestamp() SQL function. |
|
The SQL MAX() aggregate function. |
|
The SQL MIN() aggregate function. |
|
Implement the |
|
Represent the ‘next value’, given a |
|
The SQL now() datetime function. |
|
Implement the |
|
Implement the |
|
Implement the |
|
The RANDOM() SQL function. |
|
Implement the |
|
Implement the |
|
The SESSION_USER() SQL function. |
|
The SQL SUM() aggregate function. |
|
The SYSDATE() SQL function. |
|
The USER() SQL function. |
- class sqlalchemy.sql.functions.array_agg(*args, **kwargs)¶
Support for the ARRAY_AGG function.
The
func.array_agg(expr)
construct returns an expression of typeARRAY
.e.g.:
stmt = select(func.array_agg(table.c.values)[2:5])
New in version 1.1.
See also
array_agg()
- PostgreSQL-specific version that returnsARRAY
, which has PG-specific operators added.Class signature
class
sqlalchemy.sql.functions.array_agg
(sqlalchemy.sql.functions.GenericFunction
)
- class sqlalchemy.sql.functions.char_length(arg, **kwargs)¶
The CHAR_LENGTH() SQL function.
Class signature
class
sqlalchemy.sql.functions.char_length
(sqlalchemy.sql.functions.GenericFunction
)
- class sqlalchemy.sql.functions.coalesce(*args, **kwargs)¶
Class signature
class
sqlalchemy.sql.functions.coalesce
(sqlalchemy.sql.functions.ReturnTypeFromArgs
)
- class sqlalchemy.sql.functions.concat(*args, **kwargs)¶
The SQL CONCAT() function, which concatenates strings.
E.g.:
>>> print(select(func.concat('a', 'b'))) 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>>> print(select(literal("a") + "b")) SELECT :param_1 || :param_2 AS anon_1
Class signature
class
sqlalchemy.sql.functions.concat
(sqlalchemy.sql.functions.GenericFunction
)
- class sqlalchemy.sql.functions.count(expression=None, **kwargs)¶
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
Class signature
class
sqlalchemy.sql.functions.count
(sqlalchemy.sql.functions.GenericFunction
)
- class sqlalchemy.sql.functions.cube(*args, **kwargs)¶
Implement the
CUBE
grouping operation.This function is used as part of the GROUP BY of a statement, e.g.
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))
New in version 1.2.
Class signature
class
sqlalchemy.sql.functions.cube
(sqlalchemy.sql.functions.GenericFunction
)
- class sqlalchemy.sql.functions.cume_dist(*args, **kwargs)¶
Implement the
cume_dist
hypothetical-set aggregate function.This function must be used with the
FunctionElement.within_group()
modifier to supply a sort expression to operate upon.The return type of this function is
Numeric
.New in version 1.1.
Class signature
class
sqlalchemy.sql.functions.cume_dist
(sqlalchemy.sql.functions.GenericFunction
)
- class sqlalchemy.sql.functions.current_date(*args, **kwargs)¶
The CURRENT_DATE() SQL function.
Class signature
class
sqlalchemy.sql.functions.current_date
(sqlalchemy.sql.functions.AnsiFunction
)
- class sqlalchemy.sql.functions.current_time(*args, **kwargs)¶
The CURRENT_TIME() SQL function.
Class signature
class
sqlalchemy.sql.functions.current_time
(sqlalchemy.sql.functions.AnsiFunction
)
- class sqlalchemy.sql.functions.current_timestamp(*args, **kwargs)¶
The CURRENT_TIMESTAMP() SQL function.
Class signature
class
sqlalchemy.sql.functions.current_timestamp
(sqlalchemy.sql.functions.AnsiFunction
)
- class sqlalchemy.sql.functions.current_user(*args, **kwargs)¶
The CURRENT_USER() SQL function.
Class signature
class
sqlalchemy.sql.functions.current_user
(sqlalchemy.sql.functions.AnsiFunction
)
- class sqlalchemy.sql.functions.dense_rank(*args, **kwargs)¶
Implement the
dense_rank
hypothetical-set aggregate function.This function must be used with the
FunctionElement.within_group()
modifier to supply a sort expression to operate upon.The return type of this function is
Integer
.New in version 1.1.
Class signature
class
sqlalchemy.sql.functions.dense_rank
(sqlalchemy.sql.functions.GenericFunction
)
- class sqlalchemy.sql.functions.grouping_sets(*args, **kwargs)¶
Implement the
GROUPING SETS
grouping operation.This function is used as part of the GROUP BY of a statement, e.g.
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
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), ) )
New in version 1.2.
Class signature
class
sqlalchemy.sql.functions.grouping_sets
(sqlalchemy.sql.functions.GenericFunction
)
- class sqlalchemy.sql.functions.localtime(*args, **kwargs)¶
The localtime() SQL function.
Class signature
class
sqlalchemy.sql.functions.localtime
(sqlalchemy.sql.functions.AnsiFunction
)
- class sqlalchemy.sql.functions.localtimestamp(*args, **kwargs)¶
The localtimestamp() SQL function.
Class signature
class
sqlalchemy.sql.functions.localtimestamp
(sqlalchemy.sql.functions.AnsiFunction
)
- class sqlalchemy.sql.functions.max(*args, **kwargs)¶
The SQL MAX() aggregate function.
Class signature
class
sqlalchemy.sql.functions.max
(sqlalchemy.sql.functions.ReturnTypeFromArgs
)
- class sqlalchemy.sql.functions.min(*args, **kwargs)¶
The SQL MIN() aggregate function.
Class signature
class
sqlalchemy.sql.functions.min
(sqlalchemy.sql.functions.ReturnTypeFromArgs
)
- class sqlalchemy.sql.functions.mode(*args, **kwargs)¶
Implement the
mode
ordered-set aggregate function.This function must be used with the
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.
New in version 1.1.
Class signature
class
sqlalchemy.sql.functions.mode
(sqlalchemy.sql.functions.OrderedSetAgg
)
- class sqlalchemy.sql.functions.next_value(seq, **kw)¶
Represent the ‘next value’, given a
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.
Class signature
class
sqlalchemy.sql.functions.next_value
(sqlalchemy.sql.functions.GenericFunction
)
- class sqlalchemy.sql.functions.now(*args, **kwargs)¶
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
.Class signature
class
sqlalchemy.sql.functions.now
(sqlalchemy.sql.functions.GenericFunction
)
- class sqlalchemy.sql.functions.percent_rank(*args, **kwargs)¶
Implement the
percent_rank
hypothetical-set aggregate function.This function must be used with the
FunctionElement.within_group()
modifier to supply a sort expression to operate upon.The return type of this function is
Numeric
.New in version 1.1.
Class signature
class
sqlalchemy.sql.functions.percent_rank
(sqlalchemy.sql.functions.GenericFunction
)
- class sqlalchemy.sql.functions.percentile_cont(*args, **kwargs)¶
Implement the
percentile_cont
ordered-set aggregate function.This function must be used with the
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
ARRAY
of the sort expression’s type.New in version 1.1.
Class signature
class
sqlalchemy.sql.functions.percentile_cont
(sqlalchemy.sql.functions.OrderedSetAgg
)
- class sqlalchemy.sql.functions.percentile_disc(*args, **kwargs)¶
Implement the
percentile_disc
ordered-set aggregate function.This function must be used with the
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
ARRAY
of the sort expression’s type.New in version 1.1.
Class signature
class
sqlalchemy.sql.functions.percentile_disc
(sqlalchemy.sql.functions.OrderedSetAgg
)
- class sqlalchemy.sql.functions.random(*args, **kwargs)¶
The RANDOM() SQL function.
Class signature
class
sqlalchemy.sql.functions.random
(sqlalchemy.sql.functions.GenericFunction
)
- class sqlalchemy.sql.functions.rank(*args, **kwargs)¶
Implement the
rank
hypothetical-set aggregate function.This function must be used with the
FunctionElement.within_group()
modifier to supply a sort expression to operate upon.The return type of this function is
Integer
.New in version 1.1.
Class signature
class
sqlalchemy.sql.functions.rank
(sqlalchemy.sql.functions.GenericFunction
)
- class sqlalchemy.sql.functions.rollup(*args, **kwargs)¶
Implement the
ROLLUP
grouping operation.This function is used as part of the GROUP BY of a statement, e.g.
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))
New in version 1.2.
Class signature
class
sqlalchemy.sql.functions.rollup
(sqlalchemy.sql.functions.GenericFunction
)
- class sqlalchemy.sql.functions.session_user(*args, **kwargs)¶
The SESSION_USER() SQL function.
Class signature
class
sqlalchemy.sql.functions.session_user
(sqlalchemy.sql.functions.AnsiFunction
)
- class sqlalchemy.sql.functions.sum(*args, **kwargs)¶
The SQL SUM() aggregate function.
Class signature
class
sqlalchemy.sql.functions.sum
(sqlalchemy.sql.functions.ReturnTypeFromArgs
)
- class sqlalchemy.sql.functions.sysdate(*args, **kwargs)¶
The SYSDATE() SQL function.
Class signature
class
sqlalchemy.sql.functions.sysdate
(sqlalchemy.sql.functions.AnsiFunction
)
- class sqlalchemy.sql.functions.user(*args, **kwargs)¶
The USER() SQL function.
Class signature
class
sqlalchemy.sql.functions.user
(sqlalchemy.sql.functions.AnsiFunction
)
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