SQL and Generic Functions¶

SQL functions which are known to SQLAlchemy with regards to database-specific rendering, return types and argument behavior. Generic functions are invoked like all SQL functions, using the func attribute:

select([func.count()]).select_from(sometable)

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.

SQL function API, factories, and built-in functions.

class sqlalchemy.sql.functions.AnsiFunction(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.GenericFunction

identifier = 'AnsiFunction'¶

name = 'AnsiFunction'¶

class sqlalchemy.sql.functions.Function(name, *clauses, **kw)¶

Bases: sqlalchemy.sql.functions.FunctionElement

Describe a named SQL function.

The Function object is typically generated from the func 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

Functions

func - namespace which produces registered or ad-hoc Function instances.

GenericFunction - allows creation of registered function types.

__init__(name, *clauses, **kw)¶

Construct a Function.

The func construct is normally used to construct new Function instances.

class sqlalchemy.sql.functions.FunctionAsBinary(fn, left_index, right_index)¶

Bases: sqlalchemy.sql.expression.BinaryExpression

left¶

right¶

class sqlalchemy.sql.functions.FunctionElement(*clauses, **kwargs)¶

Bases: sqlalchemy.sql.expression.Executable, sqlalchemy.sql.expression.ColumnElement, sqlalchemy.sql.expression.FromClause

Base for SQL function-oriented constructs.

See also

Functions - in the Core tutorial

Function - named SQL function.

func - namespace which produces registered or ad-hoc Function instances.

GenericFunction - allows creation of registered function types.

__init__(*clauses, **kwargs)¶

Construct a FunctionElement.

Parameters:	*clauses¶ – list of column expressions that form the arguments of the SQL function call. **kwargs¶ – additional kwargs are typically consumed by subclasses.

See also

func

Function

alias(name=None, flat=False)¶

Produce a Alias construct against this 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:

SELECT data_view
FROM sometable, unnest(sometable.data) AS data_view

New in version 0.9.8: The FunctionElement.alias() method is now supported. Previously, this method’s behavior was undefined and did not behave consistently across versions.

as_comparison(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 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 called 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.

Parameters:	left_index¶ – the integer 1-based index of the function argument that serves as the “left” side of the expression. right_index¶ – the integer 1-based index of the function argument that serves as the “right” side of the expression.

New in version 1.3.

clauses¶

Return the underlying ClauseList which contains the arguments for this FunctionElement.

columns¶

The set of columns exported by this 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 select() with the desired columns:

from sqlalchemy.sql import column

stmt = select([column('x'), column('y')]).                select_from(func.myfunction())

execute()¶

Execute this FunctionElement against an embedded ‘bind’.

This first calls select() to produce a SELECT construct.

Note that FunctionElement can be passed to the Connectable.execute() method of Connection or Engine.

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.

See also

FunctionFilter

funcfilter()

get_children(**kwargs)¶

Return immediate child elements of this ClauseElement.

This is used for visit traversal.

**kwargs may contain flags that change the collection that is returned, for example to return a subset of items in order to cut down on larger traversals, or to return child items from a different context (such as schema-level collections instead of clause-level).

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.

packagenames = ()¶

scalar()¶

Execute this FunctionElement against an embedded ‘bind’ and return a scalar value.

This first calls select() to produce a SELECT construct.

Note that FunctionElement can be passed to the Connectable.scalar() method of Connection or Engine.

select()¶

Produce a select() construct against this FunctionElement.

This is shorthand for:

s = select([function_element])

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 another select(). (Note that subqueries should be normally created using the Select.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 like x OR (y AND z) - AND takes precedence over OR.

The base self_group() method of ClauseElement just returns self.

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.

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.

class sqlalchemy.sql.functions.GenericFunction(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.Function

Define a ‘generic’ function.

A generic function is a pre-established Function class that is instantiated automatically when called by name from the func attribute. Note that calling any name from func has the effect that a new Function instance is created automatically, given that name. The primary use case for defining a 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 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 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 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 func but to render as a different name. The identifier attribute will override the name used to access the function as loaded from 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¶

identifier = 'GenericFunction'¶

name = 'GenericFunction'¶

class sqlalchemy.sql.functions.OrderedSetAgg(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.GenericFunction

Define a function where the return type is based on the sort expression type as defined by the expression passed to the FunctionElement.within_group() method.

array_for_multi_clause = False¶

identifier = 'OrderedSetAgg'¶

name = 'OrderedSetAgg'¶

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.

class sqlalchemy.sql.functions.ReturnTypeFromArgs(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.GenericFunction

Define a function whose return type is the same as its arguments.

identifier = 'ReturnTypeFromArgs'¶

name = 'ReturnTypeFromArgs'¶

class sqlalchemy.sql.functions.array_agg(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.GenericFunction

support for the ARRAY_AGG function.

The func.array_agg(expr) construct returns an expression of type types.ARRAY.

e.g.:

stmt = select([func.array_agg(table.c.values)[2:5]])

New in version 1.1.

See also

postgresql.array_agg() - PostgreSQL-specific version that returns postgresql.ARRAY, which has PG-specific operators added.

identifier = 'array_agg'¶

name = 'array_agg'¶

type¶

alias of sqlalchemy.sql.sqltypes.ARRAY

class sqlalchemy.sql.functions.char_length(arg, **kwargs)¶

Bases: sqlalchemy.sql.functions.GenericFunction

identifier = 'char_length'¶

name = 'char_length'¶

type¶

alias of sqlalchemy.sql.sqltypes.Integer

class sqlalchemy.sql.functions.coalesce(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.ReturnTypeFromArgs

identifier = 'coalesce'¶

name = 'coalesce'¶

class sqlalchemy.sql.functions.concat(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.GenericFunction

identifier = 'concat'¶

name = 'concat'¶

type¶

alias of sqlalchemy.sql.sqltypes.String

class sqlalchemy.sql.functions.count(expression=None, **kwargs)¶

Bases: sqlalchemy.sql.functions.GenericFunction

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

identifier = 'count'¶

name = 'count'¶

type¶

alias of sqlalchemy.sql.sqltypes.Integer

class sqlalchemy.sql.functions.cube(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.GenericFunction

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.

identifier = 'cube'¶

name = 'cube'¶

class sqlalchemy.sql.functions.cume_dist(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.GenericFunction

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.

identifier = 'cume_dist'¶

name = 'cume_dist'¶

type = Numeric()¶

class sqlalchemy.sql.functions.current_date(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.AnsiFunction

identifier = 'current_date'¶

name = 'current_date'¶

type¶

alias of sqlalchemy.sql.sqltypes.Date

class sqlalchemy.sql.functions.current_time(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.AnsiFunction

identifier = 'current_time'¶

name = 'current_time'¶

type¶

alias of sqlalchemy.sql.sqltypes.Time

class sqlalchemy.sql.functions.current_timestamp(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.AnsiFunction

identifier = 'current_timestamp'¶

name = 'current_timestamp'¶

type¶

alias of sqlalchemy.sql.sqltypes.DateTime

class sqlalchemy.sql.functions.current_user(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.AnsiFunction

identifier = 'current_user'¶

name = 'current_user'¶

type¶

alias of sqlalchemy.sql.sqltypes.String

class sqlalchemy.sql.functions.dense_rank(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.GenericFunction

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.

identifier = 'dense_rank'¶

name = 'dense_rank'¶

type = Integer()¶

class sqlalchemy.sql.functions.grouping_sets(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.GenericFunction

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.

identifier = 'grouping_sets'¶

name = 'grouping_sets'¶

class sqlalchemy.sql.functions.localtime(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.AnsiFunction

identifier = 'localtime'¶

name = 'localtime'¶

type¶

alias of sqlalchemy.sql.sqltypes.DateTime

class sqlalchemy.sql.functions.localtimestamp(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.AnsiFunction

identifier = 'localtimestamp'¶

name = 'localtimestamp'¶

type¶

alias of sqlalchemy.sql.sqltypes.DateTime

class sqlalchemy.sql.functions.max(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.ReturnTypeFromArgs

identifier = 'max'¶

name = 'max'¶

class sqlalchemy.sql.functions.min(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.ReturnTypeFromArgs

identifier = 'min'¶

name = 'min'¶

class sqlalchemy.sql.functions.mode(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.OrderedSetAgg

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.

identifier = 'mode'¶

name = 'mode'¶

class sqlalchemy.sql.functions.next_value(seq, **kw)¶

Bases: sqlalchemy.sql.functions.GenericFunction

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.

identifier = 'next_value'¶

name = 'next_value'¶

type = Integer()¶

class sqlalchemy.sql.functions.now(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.GenericFunction

identifier = 'now'¶

name = 'now'¶

type¶

alias of sqlalchemy.sql.sqltypes.DateTime

class sqlalchemy.sql.functions.percent_rank(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.GenericFunction

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.

identifier = 'percent_rank'¶

name = 'percent_rank'¶

type = Numeric()¶

class sqlalchemy.sql.functions.percentile_cont(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.OrderedSetAgg

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 types.ARRAY of the sort expression’s type.

New in version 1.1.

array_for_multi_clause = True¶

identifier = 'percentile_cont'¶

name = 'percentile_cont'¶

class sqlalchemy.sql.functions.percentile_disc(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.OrderedSetAgg

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 types.ARRAY of the sort expression’s type.

New in version 1.1.

array_for_multi_clause = True¶

identifier = 'percentile_disc'¶

name = 'percentile_disc'¶

class sqlalchemy.sql.functions.random(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.GenericFunction

identifier = 'random'¶

name = 'random'¶

class sqlalchemy.sql.functions.rank(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.GenericFunction

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.

identifier = 'rank'¶

name = 'rank'¶

type = Integer()¶

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).

class sqlalchemy.sql.functions.rollup(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.GenericFunction

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.

identifier = 'rollup'¶

name = 'rollup'¶

class sqlalchemy.sql.functions.session_user(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.AnsiFunction

identifier = 'session_user'¶

name = 'session_user'¶

type¶

alias of sqlalchemy.sql.sqltypes.String

class sqlalchemy.sql.functions.sum(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.ReturnTypeFromArgs

identifier = 'sum'¶

name = 'sum'¶

class sqlalchemy.sql.functions.sysdate(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.AnsiFunction

identifier = 'sysdate'¶

name = 'sysdate'¶

type¶

alias of sqlalchemy.sql.sqltypes.DateTime

class sqlalchemy.sql.functions.user(*args, **kwargs)¶

Bases: sqlalchemy.sql.functions.AnsiFunction

identifier = 'user'¶

name = 'user'¶

type¶

alias of sqlalchemy.sql.sqltypes.String