Column Elements and Expressions

The expression API consists of a series of classes each of which represents a specific lexical element within a SQL string. Composed together into a larger structure, they form a statement construct that may be compiled into a string representation that can be passed to a database. The classes are organized into a hierarchy that begins at the basemost ClauseElement class. Key subclasses include ColumnElement, which represents the role of any column-based expression in a SQL statement, such as in the columns clause, WHERE clause, and ORDER BY clause, and FromClause, which represents the role of a token that is placed in the FROM clause of a SELECT statement.

Column Element Foundational Constructors

Standalone functions imported from the sqlalchemy namespace which are used when building up SQLAlchemy Expression Language constructs.

function sqlalchemy.sql.expression.``and_(\clauses*)

Produce a conjunction of expressions joined by AND.

E.g.:

from sqlalchemy import and_
stmt = select(users_table).where(
                and_(
                    users_table.c.name == 'wendy',
                    users_table.c.enrolled == True
                )
            )

The and_() conjunction is also available using the Python & operator (though note that compound expressions need to be parenthesized in order to function with Python operator precedence behavior):

stmt = select(users_table).where(
                (users_table.c.name == 'wendy') &
                (users_table.c.enrolled == True)
            )

The and_() operation is also implicit in some cases; the Select.where() method for example can be invoked multiple times against a statement, which will have the effect of each clause being combined using and_():

stmt = select(users_table).\
        where(users_table.c.name == 'wendy').\
        where(users_table.c.enrolled == True)

The and_() construct must be given at least one positional argument in order to be valid; a and_() construct with no arguments is ambiguous. To produce an “empty” or dynamically generated and_() expression, from a given list of expressions, a “default” element of True should be specified:

criteria = and_(True, *expressions)

The above expression will compile to SQL as the expression true or 1 = 1, depending on backend, if no other expressions are present. If expressions are present, then the True value is ignored as it does not affect the outcome of an AND expression that has other elements.

Deprecated since version 1.4: The and_() element now requires that at least one argument is passed; creating the and_() construct with no arguments is deprecated, and will emit a deprecation warning while continuing to produce a blank SQL string.

See also

or_()

function sqlalchemy.sql.expression.``bindparam(key, value=symbol(‘NO_ARG’), type_=None, unique=False, required=symbol(‘NO_ARG’), quote=None, callable_=None, expanding=False, isoutparam=False, literal_execute=False, _compared_to_operator=None, _compared_to_type=None, _is_crud=False)

Produce a “bound expression”.

The return value is an instance of BindParameter; this is a ColumnElement subclass which represents a so-called “placeholder” value in a SQL expression, the value of which is supplied at the point at which the statement in executed against a database connection.

In SQLAlchemy, the bindparam() construct has the ability to carry along the actual value that will be ultimately used at expression time. In this way, it serves not just as a “placeholder” for eventual population, but also as a means of representing so-called “unsafe” values which should not be rendered directly in a SQL statement, but rather should be passed along to the DBAPI as values which need to be correctly escaped and potentially handled for type-safety.

When using bindparam() explicitly, the use case is typically one of traditional deferment of parameters; the bindparam() construct accepts a name which can then be referred to at execution time:

from sqlalchemy import bindparam
stmt = select(users_table).\
            where(users_table.c.name == bindparam('username'))

The above statement, when rendered, will produce SQL similar to:

SELECT id, name FROM user WHERE name = :username

In order to populate the value of :username above, the value would typically be applied at execution time to a method like Connection.execute():

result = connection.execute(stmt, username='wendy')

Explicit use of bindparam() is also common when producing UPDATE or DELETE statements that are to be invoked multiple times, where the WHERE criterion of the statement is to change on each invocation, such as:

stmt = (users_table.update().
        where(user_table.c.name == bindparam('username')).
        values(fullname=bindparam('fullname'))
        )
connection.execute(
    stmt, [{"username": "wendy", "fullname": "Wendy Smith"},
           {"username": "jack", "fullname": "Jack Jones"},
           ]
)

SQLAlchemy’s Core expression system makes wide use of bindparam() in an implicit sense. It is typical that Python literal values passed to virtually all SQL expression functions are coerced into fixed bindparam() constructs. For example, given a comparison operation such as:

expr = users_table.c.name == 'Wendy'

The above expression will produce a BinaryExpression construct, where the left side is the Column object representing the name column, and the right side is a BindParameter representing the literal value:

print(repr(expr.right))
BindParameter('%(4327771088 name)s', 'Wendy', type_=String())

The expression above will render SQL such as:

user.name = :name_1

Where the :name_1 parameter name is an anonymous name. The actual string Wendy is not in the rendered string, but is carried along where it is later used within statement execution. If we invoke a statement like the following:

stmt = select(users_table).where(users_table.c.name == 'Wendy')
result = connection.execute(stmt)

We would see SQL logging output as:

SELECT "user".id, "user".name
FROM "user"
WHERE "user".name = %(name_1)s
{'name_1': 'Wendy'}

Above, we see that Wendy is passed as a parameter to the database, while the placeholder :name_1 is rendered in the appropriate form for the target database, in this case the PostgreSQL database.

Similarly, bindparam() is invoked automatically when working with CRUD statements as far as the “VALUES” portion is concerned. The insert() construct produces an INSERT expression which will, at statement execution time, generate bound placeholders based on the arguments passed, as in:

stmt = users_table.insert()
result = connection.execute(stmt, name='Wendy')

The above will produce SQL output as:

INSERT INTO "user" (name) VALUES (%(name)s)
{'name': 'Wendy'}

The Insert construct, at compilation/execution time, rendered a single bindparam() mirroring the column name name as a result of the single name parameter we passed to the Connection.execute() method.

• Parameters

  • key – the key (e.g. the name) for this bind param. Will be used in the generated SQL statement for dialects that use named parameters. This value may be modified when part of a compilation operation, if other BindParameter objects exist with the same key, or if its length is too long and truncation is required.

  • value – Initial value for this bind param. Will be used at statement execution time as the value for this parameter passed to the DBAPI, if no other value is indicated to the statement execution method for this particular parameter name. Defaults to None.

  • callable_ – A callable function that takes the place of “value”. The function will be called at statement execution time to determine the ultimate value. Used for scenarios where the actual bind value cannot be determined at the point at which the clause construct is created, but embedded bind values are still desirable.

  • type_ –

    A TypeEngine class or instance representing an optional datatype for this bindparam(). If not passed, a type may be determined automatically for the bind, based on the given value; for example, trivial Python types such as str, int, bool may result in the String, Integer or Boolean types being automatically selected.

    The type of a bindparam() is significant especially in that the type will apply pre-processing to the value before it is passed to the database. For example, a bindparam() which refers to a datetime value, and is specified as holding the DateTime type, may apply conversion needed to the value (such as stringification on SQLite) before passing the value to the database.

  • unique – if True, the key name of this BindParameter will be modified if another BindParameter of the same name already has been located within the containing expression. This flag is used generally by the internals when producing so-called “anonymous” bound expressions, it isn’t generally applicable to explicitly-named bindparam() constructs.

  • required – If True, a value is required at execution time. If not passed, it defaults to True if neither bindparam.value or bindparam.callable were passed. If either of these parameters are present, then bindparam.required defaults to False.

  • quote – True if this parameter name requires quoting and is not currently known as a SQLAlchemy reserved word; this currently only applies to the Oracle backend, where bound names must sometimes be quoted.

  • isoutparam – if True, the parameter should be treated like a stored procedure “OUT” parameter. This applies to backends such as Oracle which support OUT parameters.

  • expanding –

    if True, this parameter will be treated as an “expanding” parameter at execution time; the parameter value is expected to be a sequence, rather than a scalar value, and the string SQL statement will be transformed on a per-execution basis to accommodate the sequence with a variable number of parameter slots passed to the DBAPI. This is to allow statement caching to be used in conjunction with an IN clause.

    See also

    ColumnOperators.in_()

    Using IN expressions - with baked queries

    Note

    The “expanding” feature does not support “executemany”- style parameter sets.

    New in version 1.2.

    Changed in version 1.3: the “expanding” bound parameter feature now supports empty lists.

See also

Bind Parameter Objects

Insert Expressions

outparam()

• Parameters

  literal_execute –

  if True, the bound parameter will be rendered in the compile phase with a special “POSTCOMPILE” token, and the SQLAlchemy compiler will render the final value of the parameter into the SQL statement at statement execution time, omitting the value from the parameter dictionary / list passed to DBAPI cursor.execute(). This produces a similar effect as that of using the literal_binds, compilation flag, however takes place as the statement is sent to the DBAPI cursor.execute() method, rather than when the statement is compiled. The primary use of this capability is for rendering LIMIT / OFFSET clauses for database drivers that can’t accommodate for bound parameters in these contexts, while allowing SQL constructs to be cacheable at the compilation level.

  New in version 1.4: Added “post compile” bound parameters

  See also

  New “post compile” bound parameters used for LIMIT/OFFSET in Oracle, SQL Server.

function sqlalchemy.sql.expression.``case(\whens, **kw*)

Produce a CASE expression.

The CASE construct in SQL is a conditional object that acts somewhat analogously to an “if/then” construct in other languages. It returns an instance of Case.

case() in its usual form is passed a list of “when” constructs, that is, a list of conditions and results as tuples:

from sqlalchemy import case
stmt = select(users_table).\
            where(
                case(
                    (users_table.c.name == 'wendy', 'W'),
                    (users_table.c.name == 'jack', 'J'),
                    else_='E'
                )
            )

The above statement will produce SQL resembling:

SELECT id, name FROM user
WHERE CASE
    WHEN (name = :name_1) THEN :param_1
    WHEN (name = :name_2) THEN :param_2
    ELSE :param_3
END

When simple equality expressions of several values against a single parent column are needed, case() also has a “shorthand” format used via the case.value parameter, which is passed a column expression to be compared. In this form, the case.whens parameter is passed as a dictionary containing expressions to be compared against keyed to result expressions. The statement below is equivalent to the preceding statement:

stmt = select(users_table).\
            where(
                case(
                    {"wendy": "W", "jack": "J"},
                    value=users_table.c.name,
                    else_='E'
                )
            )

The values which are accepted as result values in case.whens as well as with case.else_ are coerced from Python literals into bindparam() constructs. SQL expressions, e.g. ColumnElement constructs, are accepted as well. To coerce a literal string expression into a constant expression rendered inline, use the literal_column() construct, as in:

from sqlalchemy import case, literal_column
case(
    (
        orderline.c.qty > 100,
        literal_column("'greaterthan100'")
    ),
    (
        orderline.c.qty > 10,
        literal_column("'greaterthan10'")
    ),
    else_=literal_column("'lessthan10'")
)

The above will render the given constants without using bound parameters for the result values (but still for the comparison values), as in:

CASE
    WHEN (orderline.qty > :qty_1) THEN 'greaterthan100'
    WHEN (orderline.qty > :qty_2) THEN 'greaterthan10'
    ELSE 'lessthan10'
END

• Parameters

  • *whens –

    The criteria to be compared against, case.whens accepts two different forms, based on whether or not case.value is used.

    Changed in version 1.4: the case() function now accepts the series of WHEN conditions positionally; passing the expressions within a list is deprecated.

    In the first form, it accepts a list of 2-tuples; each 2-tuple consists of (<sql expression>, <value>), where the SQL expression is a boolean expression and “value” is a resulting value, e.g.:

    case(
        (users_table.c.name == 'wendy', 'W'),
        (users_table.c.name == 'jack', 'J')
    )

    In the second form, it accepts a Python dictionary of comparison values mapped to a resulting value; this form requires case.value to be present, and values will be compared using the == operator, e.g.:

    case(
        {"wendy": "W", "jack": "J"},
        value=users_table.c.name
    )

  • value – An optional SQL expression which will be used as a fixed “comparison point” for candidate values within a dictionary passed to case.whens.

  • else_ – An optional SQL expression which will be the evaluated result of the CASE construct if all expressions within case.whens evaluate to false. When omitted, most databases will produce a result of NULL if none of the “when” expressions evaluate to true.

function sqlalchemy.sql.expression.``cast(expression, type_)

Produce a CAST expression.

cast() returns an instance of Cast.

E.g.:

from sqlalchemy import cast, Numeric
stmt = select(cast(product_table.c.unit_price, Numeric(10, 4)))

The above statement will produce SQL resembling:

SELECT CAST(unit_price AS NUMERIC(10, 4)) FROM product

The cast() function performs two distinct functions when used. The first is that it renders the CAST expression within the resulting SQL string. The second is that it associates the given type (e.g. TypeEngine class or instance) with the column expression on the Python side, which means the expression will take on the expression operator behavior associated with that type, as well as the bound-value handling and result-row-handling behavior of the type.

Changed in version 0.9.0: cast() now applies the given type to the expression such that it takes effect on the bound-value, e.g. the Python-to-database direction, in addition to the result handling, e.g. database-to-Python, direction.

An alternative to cast() is the type_coerce() function. This function performs the second task of associating an expression with a specific type, but does not render the CAST expression in SQL.

• Parameters

  • expression – A SQL expression, such as a ColumnElement expression or a Python string which will be coerced into a bound literal value.

  • type_ – A TypeEngine class or instance indicating the type to which the CAST should apply.

See also

Data Casts and Type Coercion

type_coerce() - an alternative to CAST that coerces the type on the Python side only, which is often sufficient to generate the correct SQL and data coercion.

function sqlalchemy.sql.expression.``column(text, type_=None, is_literal=False, _selectable=None)

Produce a ColumnClause object.

The ColumnClause is a lightweight analogue to the Column class. The column() function can be invoked with just a name alone, as in:

from sqlalchemy import column
id, name = column("id"), column("name")
stmt = select(id, name).select_from("user")

The above statement would produce SQL like:

SELECT id, name FROM user

Once constructed, column() may be used like any other SQL expression element such as within select() constructs:

from sqlalchemy.sql import column
id, name = column("id"), column("name")
stmt = select(id, name).select_from("user")

The text handled by column() is assumed to be handled like the name of a database column; if the string contains mixed case, special characters, or matches a known reserved word on the target backend, the column expression will render using the quoting behavior determined by the backend. To produce a textual SQL expression that is rendered exactly without any quoting, use literal_column() instead, or pass True as the value of column.is_literal. Additionally, full SQL statements are best handled using the text() construct.

column() can be used in a table-like fashion by combining it with the table() function (which is the lightweight analogue to Table ) to produce a working table construct with minimal boilerplate:

from sqlalchemy import table, column, select
user = table("user",
        column("id"),
        column("name"),
        column("description"),
)
stmt = select(user.c.description).where(user.c.name == 'wendy')

A column() / table() construct like that illustrated above can be created in an ad-hoc fashion and is not associated with any MetaData, DDL, or events, unlike its Table counterpart.

Changed in version 1.0.0: column() can now be imported from the plain sqlalchemy namespace like any other SQL element.

• Parameters

  • text – the text of the element.

  • type – TypeEngine object which can associate this ColumnClause with a type.

  • is_literal – if True, the ColumnClause is assumed to be an exact expression that will be delivered to the output with no quoting rules applied regardless of case sensitive settings. the literal_column() function essentially invokes column() while passing is_literal=True.

See also

Column

literal_column()

table()

text()

Using More Specific Text with table(), _expression.literal_column(), and _expression.column()

class sqlalchemy.sql.expression.``custom_op(opstring, precedence=0, is_comparison=False, return_type=None, natural_self_precedent=False, eager_grouping=False)

Represent a ‘custom’ operator.

custom_op is normally instantiated when the Operators.op() or Operators.bool_op() methods are used to create a custom operator callable. The class can also be used directly when programmatically constructing expressions. E.g. to represent the “factorial” operation:

from sqlalchemy.sql import UnaryExpression
from sqlalchemy.sql import operators
from sqlalchemy import Numeric
unary = UnaryExpression(table.c.somecolumn,
        modifier=operators.custom_op("!"),
        type_=Numeric)

See also

Operators.op()

Operators.bool_op()

function sqlalchemy.sql.expression.``distinct(expr)

Produce an column-expression-level unary DISTINCT clause.

This applies the DISTINCT keyword to an individual column expression, and is typically contained within an aggregate function, as in:

from sqlalchemy import distinct, func
stmt = select(func.count(distinct(users_table.c.name)))

The above would produce an expression resembling:

SELECT COUNT(DISTINCT name) FROM user

The distinct() function is also available as a column-level method, e.g. ColumnElement.distinct(), as in:

stmt = select(func.count(users_table.c.name.distinct()))

The distinct() operator is different from the Select.distinct() method of Select, which produces a SELECT statement with DISTINCT applied to the result set as a whole, e.g. a SELECT DISTINCT expression. See that method for further information.

See also

ColumnElement.distinct()

Select.distinct()

func

function sqlalchemy.sql.expression.``extract(field, expr, \*kwargs*)

Return a Extract construct.

This is typically available as extract() as well as func.extract from the func namespace.

function sqlalchemy.sql.expression.``false()

Return a False_ construct.

E.g.:

>>> from sqlalchemy import false
>>> print(select(t.c.x).where(false()))
SELECT x FROM t WHERE false

A backend which does not support true/false constants will render as an expression against 1 or 0:

>>> print(select(t.c.x).where(false()))
SELECT x FROM t WHERE 0 = 1

The true() and false() constants also feature “short circuit” operation within an and_() or or_() conjunction:

>>> print(select(t.c.x).where(or_(t.c.x > 5, true())))
SELECT x FROM t WHERE true
>>> print(select(t.c.x).where(and_(t.c.x > 5, false())))
SELECT x FROM t WHERE false

Changed in version 0.9: true() and false() feature better integrated behavior within conjunctions and on dialects that don’t support true/false constants.

See also

true()

sqlalchemy.sql.expression.``func = <sqlalchemy.sql.functions._FunctionGenerator object>

Generate SQL function expressions.

func is a special object instance which generates SQL functions based on name-based attributes, e.g.:

>>> print(func.count(1))
count(:param_1)

The returned object is an instance of Function, and is a column-oriented SQL element like any other, and is used in that way:

>>> print(select(func.count(table.c.id)))
SELECT count(sometable.id) FROM sometable

Any name can be given to func. If the function name is unknown to SQLAlchemy, it will be rendered exactly as is. For common SQL functions which SQLAlchemy is aware of, the name may be interpreted as a generic function which will be compiled appropriately to the target database:

>>> print(func.current_timestamp())
CURRENT_TIMESTAMP

To call functions which are present in dot-separated packages, specify them in the same manner:

>>> print(func.stats.yield_curve(5, 10))
stats.yield_curve(:yield_curve_1, :yield_curve_2)

SQLAlchemy can be made aware of the return type of functions to enable type-specific lexical and result-based behavior. For example, to ensure that a string-based function returns a Unicode value and is similarly treated as a string in expressions, specify Unicode as the type:

>>> print(func.my_string(u'hi', type_=Unicode) + ' ' +
...       func.my_string(u'there', type_=Unicode))
my_string(:my_string_1) || :my_string_2 || my_string(:my_string_3)

The object returned by a func call is usually an instance of Function. This object meets the “column” interface, including comparison and labeling functions. The object can also be passed the Connectable.execute() method of a Connection or 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 func accessor will redirect a name to a built-in expression such as cast() or 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 SQL and Generic Functions.

Note

The func construct has only limited support for calling standalone “stored procedures”, especially those with special parameterization concerns.

See the section Calling Stored Procedures for details on how to use the DBAPI-level callproc() method for fully traditional stored procedures.

See also

Functions - in the Core Tutorial

Function

function sqlalchemy.sql.expression.``lambda_stmt(lmb, enable_tracking=True, track_closure_variables=True, track_on=None, global_track_bound_values=True, track_bound_values=True, lambda_cache=None)

Produce a SQL statement that is cached as a lambda.

The Python code object within the lambda is scanned for both Python literals that will become bound parameters as well as closure variables that refer to Core or ORM constructs that may vary. The lambda itself will be invoked only once per particular set of constructs detected.

E.g.:

from sqlalchemy import lambda_stmt
stmt = lambda_stmt(lambda: table.select())
stmt += lambda s: s.where(table.c.id == 5)
result = connection.execute(stmt)

The object returned is an instance of StatementLambdaElement.

New in version 1.4.

• Parameters

  • lmb – a Python function, typically a lambda, which takes no arguments and returns a SQL expression construct

  • enable_tracking – when False, all scanning of the given lambda for changes in closure variables or bound parameters is disabled. Use for a lambda that produces the identical results in all cases with no parameterization.

  • track_closure_variables – when False, changes in closure variables within the lambda will not be scanned. Use for a lambda where the state of its closure variables will never change the SQL structure returned by the lambda.

  • track_bound_values – when False, bound parameter tracking will be disabled for the given lambda. Use for a lambda that either does not produce any bound values, or where the initial bound values never change.

  • global_track_bound_values – when False, bound parameter tracking will be disabled for the entire statement including additional links added via the StatementLambdaElement.add_criteria() method.

  • lambda_cache – a dictionary or other mapping-like object where information about the lambda’s Python code as well as the tracked closure variables in the lambda itself will be stored. Defaults to a global LRU cache. This cache is independent of the “compiled_cache” used by the Connection object.

See also

Using Lambdas to add significant speed gains to statement production

function sqlalchemy.sql.expression.``literal(value, type_=None)

Return a literal clause, bound to a bind parameter.

Literal clauses are created automatically when non- ClauseElement objects (such as strings, ints, dates, etc.) are used in a comparison operation with a ColumnElement subclass, such as a Column object. Use this function to force the generation of a literal clause, which will be created as a BindParameter with a bound value.

• Parameters

  • value – the value to be bound. Can be any Python object supported by the underlying DB-API, or is translatable via the given type argument.

  • type_ – an optional TypeEngine which will provide bind-parameter translation for this literal.

function sqlalchemy.sql.expression.``literal_column(text, type_=None)

Produce a ColumnClause object that has the column.is_literal flag set to True.

literal_column() is similar to column(), except that it is more often used as a “standalone” column expression that renders exactly as stated; while column() stores a string name that will be assumed to be part of a table and may be quoted as such, literal_column() can be that, or any other arbitrary column-oriented expression.

• Parameters

  • text – the text of the expression; can be any SQL expression. Quoting rules will not be applied. To specify a column-name expression which should be subject to quoting rules, use the column() function.

  • type_ – an optional TypeEngine object which will provide result-set translation and additional expression semantics for this column. If left as None the type will be NullType.

See also

column()

text()

Using More Specific Text with table(), _expression.literal_column(), and _expression.column()

function sqlalchemy.sql.expression.``not_(clause)

Return a negation of the given clause, i.e. NOT(clause).

The ~ operator is also overloaded on all ColumnElement subclasses to produce the same result.

function sqlalchemy.sql.expression.``null()

Return a constant Null construct.

function sqlalchemy.sql.expression.``or_(\clauses*)

Produce a conjunction of expressions joined by OR.

E.g.:

from sqlalchemy import or_
stmt = select(users_table).where(
                or_(
                    users_table.c.name == 'wendy',
                    users_table.c.name == 'jack'
                )
            )

The or_() conjunction is also available using the Python | operator (though note that compound expressions need to be parenthesized in order to function with Python operator precedence behavior):

stmt = select(users_table).where(
                (users_table.c.name == 'wendy') |
                (users_table.c.name == 'jack')
            )

The or_() construct must be given at least one positional argument in order to be valid; a or_() construct with no arguments is ambiguous. To produce an “empty” or dynamically generated or_() expression, from a given list of expressions, a “default” element of False should be specified:

or_criteria = or_(False, *expressions)

The above expression will compile to SQL as the expression false or 0 = 1, depending on backend, if no other expressions are present. If expressions are present, then the False value is ignored as it does not affect the outcome of an OR expression which has other elements.

Deprecated since version 1.4: The or_() element now requires that at least one argument is passed; creating the or_() construct with no arguments is deprecated, and will emit a deprecation warning while continuing to produce a blank SQL string.

See also

and_()

function sqlalchemy.sql.expression.``outparam(key, type_=None)

Create an ‘OUT’ parameter for usage in functions (stored procedures), for databases which support them.

The outparam can be used like a regular function parameter. The “output” value will be available from the CursorResult object via its out_parameters attribute, which returns a dictionary containing the values.

function sqlalchemy.sql.expression.``text(text, bind=None)

Construct a new TextClause clause, representing a textual SQL string directly.

E.g.:

from sqlalchemy import text
t = text("SELECT * FROM users")
result = connection.execute(t)

The advantages text() provides over a plain string are backend-neutral support for bind parameters, per-statement execution options, as well as bind parameter and result-column typing behavior, allowing SQLAlchemy type constructs to play a role when executing a statement that is specified literally. The construct can also be provided with a .c collection of column elements, allowing it to be embedded in other SQL expression constructs as a subquery.

Bind parameters are specified by name, using the format :name. E.g.:

t = text("SELECT * FROM users WHERE id=:user_id")
result = connection.execute(t, user_id=12)

For SQL statements where a colon is required verbatim, as within an inline string, use a backslash to escape:

t = text("SELECT * FROM users WHERE name='\:username'")

The TextClause construct includes methods which can provide information about the bound parameters as well as the column values which would be returned from the textual statement, assuming it’s an executable SELECT type of statement. The TextClause.bindparams() method is used to provide bound parameter detail, and TextClause.columns() method allows specification of return columns including names and types:

t = text("SELECT * FROM users WHERE id=:user_id").\
        bindparams(user_id=7).\
        columns(id=Integer, name=String)
for id, name in connection.execute(t):
    print(id, name)

The text() construct is used in cases when a literal string SQL fragment is specified as part of a larger query, such as for the WHERE clause of a SELECT statement:

s = select(users.c.id, users.c.name).where(text("id=:user_id"))
result = connection.execute(s, user_id=12)

text() is also used for the construction of a full, standalone statement using plain text. As such, SQLAlchemy refers to it as an Executable object, and it supports the Executable.execution_options() method. For example, a text() construct that should be subject to “autocommit” can be set explicitly so using the Connection.execution_options.autocommit option:

t = text("EXEC my_procedural_thing()").\
        execution_options(autocommit=True)

Deprecated since version 1.4: The “autocommit” execution option is deprecated and will be removed in SQLAlchemy 2.0. See Library-level (but not driver level) “Autocommit” removed from both Core and ORM for discussion.

• Parameters

  • text –

    the text of the SQL statement to be created. Use :<param> to specify bind parameters; they will be compiled to their engine-specific format.

    Warning

    The text.text argument to text() can be passed as a Python string argument, which will be treated as trusted SQL text and rendered as given. DO NOT PASS UNTRUSTED INPUT TO THIS PARAMETER.

  • bind –

    an optional connection or engine to be used for this text query.

    Deprecated since version 1.4: The text.bind argument is deprecated and will be removed in SQLAlchemy 2.0.

See also

Using Textual SQL - in the Core tutorial

function sqlalchemy.sql.expression.``true()

Return a constant True_ construct.

E.g.:

>>> from sqlalchemy import true
>>> print(select(t.c.x).where(true()))
SELECT x FROM t WHERE true

A backend which does not support true/false constants will render as an expression against 1 or 0:

>>> print(select(t.c.x).where(true()))
SELECT x FROM t WHERE 1 = 1

The true() and false() constants also feature “short circuit” operation within an and_() or or_() conjunction:

>>> print(select(t.c.x).where(or_(t.c.x > 5, true())))
SELECT x FROM t WHERE true
>>> print(select(t.c.x).where(and_(t.c.x > 5, false())))
SELECT x FROM t WHERE false

Changed in version 0.9: true() and false() feature better integrated behavior within conjunctions and on dialects that don’t support true/false constants.

See also

false()

function sqlalchemy.sql.expression.``tuple_(\clauses, **kw*)

Return a Tuple.

Main usage is to produce a composite IN construct using ColumnOperators.in_()

from sqlalchemy import tuple_
tuple_(table.c.col1, table.c.col2).in_(
    [(1, 2), (5, 12), (10, 19)]
)

Changed in version 1.3.6: Added support for SQLite IN tuples.

Warning

The composite IN construct is not supported by all backends, and is currently known to work on PostgreSQL, MySQL, and SQLite. Unsupported backends will raise a subclass of DBAPIError when such an expression is invoked.

function sqlalchemy.sql.expression.``type_coerce(expression, type_)

Associate a SQL expression with a particular type, without rendering CAST.

E.g.:

from sqlalchemy import type_coerce
stmt = select(type_coerce(log_table.date_string, StringDateTime()))

The above construct will produce a TypeCoerce object, which does not modify the rendering in any way on the SQL side, with the possible exception of a generated label if used in a columns clause context:

SELECT date_string AS date_string FROM log

When result rows are fetched, the StringDateTime type processor will be applied to result rows on behalf of the date_string column.

Note

the type_coerce() construct does not render any SQL syntax of its own, including that it does not imply parenthesization. Please use TypeCoerce.self_group() if explicit parenthesization is required.

In order to provide a named label for the expression, use ColumnElement.label():

stmt = select(
    type_coerce(log_table.date_string, StringDateTime()).label('date')
)

A type that features bound-value handling will also have that behavior take effect when literal values or bindparam() constructs are passed to type_coerce() as targets. For example, if a type implements the TypeEngine.bind_expression() method or TypeEngine.bind_processor() method or equivalent, these functions will take effect at statement compilation/execution time when a literal value is passed, as in:

# bound-value handling of MyStringType will be applied to the
# literal value "some string"
stmt = select(type_coerce("some string", MyStringType))

When using type_coerce() with composed expressions, note that parenthesis are not applied. If type_coerce() is being used in an operator context where the parenthesis normally present from CAST are necessary, use the TypeCoerce.self_group() method:

>>> some_integer = column("someint", Integer)
>>> some_string = column("somestr", String)
>>> expr = type_coerce(some_integer + 5, String) + some_string
>>> print(expr)
someint + :someint_1 || somestr
>>> expr = type_coerce(some_integer + 5, String).self_group() + some_string
>>> print(expr)
(someint + :someint_1) || somestr

• Parameters

  • expression – A SQL expression, such as a ColumnElement expression or a Python string which will be coerced into a bound literal value.

  • type_ – A TypeEngine class or instance indicating the type to which the expression is coerced.

See also

Data Casts and Type Coercion

cast()

class sqlalchemy.sql.expression.``quoted_name(value, quote)

Represent a SQL identifier combined with quoting preferences.

quoted_name is a Python unicode/str subclass which represents a particular identifier name along with a quote flag. This quote flag, when set to True or False, overrides automatic quoting behavior for this identifier in order to either unconditionally quote or to not quote the name. If left at its default of None, quoting behavior is applied to the identifier on a per-backend basis based on an examination of the token itself.

A quoted_name object with quote=True is also prevented from being modified in the case of a so-called “name normalize” option. Certain database backends, such as Oracle, Firebird, and DB2 “normalize” case-insensitive names as uppercase. The SQLAlchemy dialects for these backends convert from SQLAlchemy’s lower-case-means-insensitive convention to the upper-case-means-insensitive conventions of those backends. The quote=True flag here will prevent this conversion from occurring to support an identifier that’s quoted as all lower case against such a backend.

The quoted_name object is normally created automatically when specifying the name for key schema constructs such as Table, Column, and others. The class can also be passed explicitly as the name to any function that receives a name which can be quoted. Such as to use the Engine.has_table() method with an unconditionally quoted name:

from sqlalchemy import create_engine
from sqlalchemy.sql import quoted_name
engine = create_engine("oracle+cx_oracle://some_dsn")
engine.has_table(quoted_name("some_table", True))

The above logic will run the “has table” logic against the Oracle backend, passing the name exactly as "some_table" without converting to upper case.

New in version 0.9.0.

Changed in version 1.2: The quoted_name construct is now importable from sqlalchemy.sql, in addition to the previous location of sqlalchemy.sql.elements.

Class signature

class sqlalchemy.sql.expression.quoted_name (sqlalchemy.util.langhelpers.MemoizedSlots, builtins.str)

• attribute sqlalchemy.sql.expression.quoted_name.quote

  whether the string should be unconditionally quoted

Column Element Modifier Constructors

Functions listed here are more commonly available as methods from any ColumnElement construct, for example, the label() function is usually invoked via the ColumnElement.label() method.

function sqlalchemy.sql.expression.``all_(expr)

Produce an ALL expression.

This may apply to an array type for some dialects (e.g. postgresql), or to a subquery for others (e.g. mysql). e.g.:

# postgresql '5 = ALL (somearray)'
expr = 5 == all_(mytable.c.somearray)
# mysql '5 = ALL (SELECT value FROM table)'
expr = 5 == all_(select(table.c.value))

The operator is more conveniently available from any ColumnElement object that makes use of the ARRAY datatype:

expr = mytable.c.somearray.all(5)

See also

any_()

Comparator.all()

function sqlalchemy.sql.expression.``any_(expr)

Produce an ANY expression.

This may apply to an array type for some dialects (e.g. postgresql), or to a subquery for others (e.g. mysql). e.g.:

# postgresql '5 = ANY (somearray)'
expr = 5 == any_(mytable.c.somearray)
# mysql '5 = ANY (SELECT value FROM table)'
expr = 5 == any_(select(table.c.value))

The operator is more conveniently available from any ColumnElement object that makes use of the ARRAY datatype:

expr = mytable.c.somearray.any(5)

See also

all_()

ARRAY.any()

function sqlalchemy.sql.expression.``asc(column)

Produce an ascending ORDER BY clause element.

e.g.:

from sqlalchemy import asc
stmt = select(users_table).order_by(asc(users_table.c.name))

will produce SQL as:

SELECT id, name FROM user ORDER BY name ASC

The asc() function is a standalone version of the ColumnElement.asc() method available on all SQL expressions, e.g.:

stmt = select(users_table).order_by(users_table.c.name.asc())

• Parameters

  column – A ColumnElement (e.g. scalar SQL expression) with which to apply the asc() operation.

See also

desc()

nulls_first()

nulls_last()

Select.order_by()

function sqlalchemy.sql.expression.``between(expr, lower_bound, upper_bound, symmetric=False)

Produce a BETWEEN predicate clause.

E.g.:

from sqlalchemy import between
stmt = select(users_table).where(between(users_table.c.id, 5, 7))

Would produce SQL resembling:

SELECT id, name FROM user WHERE id BETWEEN :id_1 AND :id_2

The between() function is a standalone version of the ColumnElement.between() method available on all SQL expressions, as in:

stmt = select(users_table).where(users_table.c.id.between(5, 7))

All arguments passed to between(), including the left side column expression, are coerced from Python scalar values if a the value is not a ColumnElement subclass. For example, three fixed values can be compared as in:

print(between(5, 3, 7))

Which would produce:

:param_1 BETWEEN :param_2 AND :param_3

• Parameters

  • expr – a column expression, typically a ColumnElement instance or alternatively a Python scalar expression to be coerced into a column expression, serving as the left side of the BETWEEN expression.

  • lower_bound – a column or Python scalar expression serving as the lower bound of the right side of the BETWEEN expression.

  • upper_bound – a column or Python scalar expression serving as the upper bound of the right side of the BETWEEN expression.

  • symmetric –

    if True, will render ” BETWEEN SYMMETRIC “. Note that not all databases support this syntax.

    New in version 0.9.5.

See also

ColumnElement.between()

function sqlalchemy.sql.expression.``collate(expression, collation)

Return the clause expression COLLATE collation.

e.g.:

collate(mycolumn, 'utf8_bin')

produces:

mycolumn COLLATE utf8_bin

The collation expression is also quoted if it is a case sensitive identifier, e.g. contains uppercase characters.

Changed in version 1.2: quoting is automatically applied to COLLATE expressions if they are case sensitive.

function sqlalchemy.sql.expression.``desc(column)

Produce a descending ORDER BY clause element.

e.g.:

from sqlalchemy import desc
stmt = select(users_table).order_by(desc(users_table.c.name))

will produce SQL as:

SELECT id, name FROM user ORDER BY name DESC

The desc() function is a standalone version of the ColumnElement.desc() method available on all SQL expressions, e.g.:

stmt = select(users_table).order_by(users_table.c.name.desc())

• Parameters

  column – A ColumnElement (e.g. scalar SQL expression) with which to apply the desc() operation.

See also

asc()

nulls_first()

nulls_last()

Select.order_by()

function sqlalchemy.sql.expression.``funcfilter(func, \criterion*)

Produce a FunctionFilter object against a function.

Used against aggregate and window functions, for database backends that support the “FILTER” clause.

E.g.:

from sqlalchemy import funcfilter
funcfilter(func.count(1), MyClass.name == 'some name')

Would produce “COUNT(1) FILTER (WHERE myclass.name = ‘some name’)”.

This function is also available from the func construct itself via the FunctionElement.filter() method.

New in version 1.0.0.

See also

Special Modifiers WITHIN GROUP, FILTER - in the SQLAlchemy 1.4 / 2.0 Tutorial

FunctionElement.filter()

function sqlalchemy.sql.expression.``label(name, element, type_=None)

Return a Label object for the given ColumnElement.

A label changes the name of an element in the columns clause of a SELECT statement, typically via the AS SQL keyword.

This functionality is more conveniently available via the ColumnElement.label() method on ColumnElement.

• Parameters

  • name – label name

  • obj – a ColumnElement.

function sqlalchemy.sql.expression.``nulls_first(column)

Produce the NULLS FIRST modifier for an ORDER BY expression.

nulls_first() is intended to modify the expression produced by asc() or desc(), and indicates how NULL values should be handled when they are encountered during ordering:

from sqlalchemy import desc, nulls_first
stmt = select(users_table).order_by(
    nulls_first(desc(users_table.c.name)))

The SQL expression from the above would resemble:

SELECT id, name FROM user ORDER BY name DESC NULLS FIRST

Like asc() and desc(), nulls_first() is typically invoked from the column expression itself using ColumnElement.nulls_first(), rather than as its standalone function version, as in:

stmt = select(users_table).order_by(
    users_table.c.name.desc().nulls_first())

Changed in version 1.4: nulls_first() is renamed from nullsfirst() in previous releases. The previous name remains available for backwards compatibility.

See also

asc()

desc()

nulls_last()

Select.order_by()

function sqlalchemy.sql.expression.``nulls_last(column)

Produce the NULLS LAST modifier for an ORDER BY expression.

nulls_last() is intended to modify the expression produced by asc() or desc(), and indicates how NULL values should be handled when they are encountered during ordering:

from sqlalchemy import desc, nulls_last
stmt = select(users_table).order_by(
    nulls_last(desc(users_table.c.name)))

The SQL expression from the above would resemble:

SELECT id, name FROM user ORDER BY name DESC NULLS LAST

Like asc() and desc(), nulls_last() is typically invoked from the column expression itself using ColumnElement.nulls_last(), rather than as its standalone function version, as in:

stmt = select(users_table).order_by(
    users_table.c.name.desc().nulls_last())

Changed in version 1.4: nulls_last() is renamed from nullslast() in previous releases. The previous name remains available for backwards compatibility.

See also

asc()

desc()

nulls_first()

Select.order_by()

function sqlalchemy.sql.expression.``over(element, partition_by=None, order_by=None, range_=None, rows=None)

Produce an Over object against a function.

Used against aggregate or so-called “window” functions, for database backends that support window functions.

over() is usually called using the FunctionElement.over() method, e.g.:

func.row_number().over(order_by=mytable.c.some_column)

Would produce:

ROW_NUMBER() OVER(ORDER BY some_column)

Ranges are also possible using the over.range_ and over.rows parameters. These mutually-exclusive parameters each accept a 2-tuple, which contains a combination of integers and None:

func.row_number().over(
    order_by=my_table.c.some_column, range_=(None, 0))

The above would produce:

ROW_NUMBER() OVER(ORDER BY some_column
RANGE BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW)

A value of None indicates “unbounded”, a value of zero indicates “current row”, and negative / positive integers indicate “preceding” and “following”:

• RANGE BETWEEN 5 PRECEDING AND 10 FOLLOWING:

  func.row_number().over(order_by='x', range_=(-5, 10))

• ROWS BETWEEN UNBOUNDED PRECEDING AND CURRENT ROW:

  func.row_number().over(order_by='x', rows=(None, 0))

• RANGE BETWEEN 2 PRECEDING AND UNBOUNDED FOLLOWING:

  func.row_number().over(order_by='x', range_=(-2, None))

• RANGE BETWEEN 1 FOLLOWING AND 3 FOLLOWING:

  func.row_number().over(order_by='x', range_=(1, 3))

New in version 1.1: support for RANGE / ROWS within a window

• Parameters

  • element – a FunctionElement, WithinGroup, or other compatible construct.

  • partition_by – a column element or string, or a list of such, that will be used as the PARTITION BY clause of the OVER construct.

  • order_by – a column element or string, or a list of such, that will be used as the ORDER BY clause of the OVER construct.

  • range_ –

    optional range clause for the window. This is a tuple value which can contain integer values or None, and will render a RANGE BETWEEN PRECEDING / FOLLOWING clause.

    New in version 1.1.

  • rows –

    optional rows clause for the window. This is a tuple value which can contain integer values or None, and will render a ROWS BETWEEN PRECEDING / FOLLOWING clause.

    New in version 1.1.

This function is also available from the func construct itself via the FunctionElement.over() method.

See also

Using Window Functions - in the SQLAlchemy 1.4 / 2.0 Tutorial

func

within_group()

function sqlalchemy.sql.expression.``within_group(element, \order_by*)

Produce a WithinGroup object against a function.

Used against so-called “ordered set aggregate” and “hypothetical set aggregate” functions, including percentile_cont, rank, dense_rank, etc.

within_group() is usually called using the FunctionElement.within_group() method, e.g.:

from sqlalchemy import within_group
stmt = select(
    department.c.id,
    func.percentile_cont(0.5).within_group(
        department.c.salary.desc()
    )
)

The above statement would produce SQL similar to SELECT department.id, percentile_cont(0.5) WITHIN GROUP (ORDER BY department.salary DESC).

• Parameters

  • element – a FunctionElement construct, typically generated by func.

  • *order_by – one or more column elements that will be used as the ORDER BY clause of the WITHIN GROUP construct.

New in version 1.1.

See also

Special Modifiers WITHIN GROUP, FILTER - in the SQLAlchemy 1.4 / 2.0 Tutorial

func

over()

Column Element Class Documentation

The classes here are generated using the constructors listed at Column Element Foundational Constructors and Column Element Modifier Constructors.

class sqlalchemy.sql.expression.``BinaryExpression(left, right, operator, type_=None, negate=None, modifiers=None)

Represent an expression that is LEFT <operator> RIGHT.

A BinaryExpression is generated automatically whenever two column expressions are used in a Python binary expression:

>>> from sqlalchemy.sql import column
>>> column('a') + column('b')
<sqlalchemy.sql.expression.BinaryExpression object at 0x101029dd0>
>>> print(column('a') + column('b'))
a + b

Class signature

class sqlalchemy.sql.expression.BinaryExpression (sqlalchemy.sql.expression.ColumnElement)

• method sqlalchemy.sql.expression.BinaryExpression.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.

class sqlalchemy.sql.expression.``BindParameter(key, value=symbol(‘NO_ARG’), type_=None, unique=False, required=symbol(‘NO_ARG’), quote=None, callable_=None, expanding=False, isoutparam=False, literal_execute=False, _compared_to_operator=None, _compared_to_type=None, _is_crud=False)

Represent a “bound expression”.

BindParameter is invoked explicitly using the bindparam() function, as in:

from sqlalchemy import bindparam
stmt = select(users_table).\
            where(users_table.c.name == bindparam('username'))

Detailed discussion of how BindParameter is used is at bindparam().

See also

bindparam()

Class signature

class sqlalchemy.sql.expression.BindParameter (sqlalchemy.sql.roles.InElementRole, sqlalchemy.sql.expression.ColumnElement)

• method sqlalchemy.sql.expression.BindParameter.__init__(key, value=symbol(‘NO_ARG’), type_=None, unique=False, required=symbol(‘NO_ARG’), quote=None, callable_=None, expanding=False, isoutparam=False, literal_execute=False, _compared_to_operator=None, _compared_to_type=None, _is_crud=False)

  Construct a new BindParameter object.

  This constructor is mirrored as a public API function; see sqlalchemy.sql.expression.bindparam() for a full usage and argument description.

• attribute sqlalchemy.sql.expression.BindParameter.effective_value

  Return the value of this bound parameter, taking into account if the callable parameter was set.

  The callable value will be evaluated and returned if present, else value.

class sqlalchemy.sql.expression.``CacheKey(key, bindparams)

Class signature

class sqlalchemy.sql.expression.CacheKey (sqlalchemy.sql.traversals.CacheKey)

• method sqlalchemy.sql.expression.CacheKey.to_offline_string(statement_cache, statement, parameters)

  Generate an “offline string” form of this CacheKey

  The “offline string” is basically the string SQL for the statement plus a repr of the bound parameter values in series. Whereas the CacheKey object is dependent on in-memory identities in order to work as a cache key, the “offline” version is suitable for a cache that will work for other processes as well.

  The given statement_cache is a dictionary-like object where the string form of the statement itself will be cached. This dictionary should be in a longer lived scope in order to reduce the time spent stringifying statements.

class sqlalchemy.sql.expression.``Case(\whens, **kw*)

Represent a CASE expression.

Case is produced using the case() factory function, as in:

from sqlalchemy import case
stmt = select(users_table).                    where(
                case(
                    (users_table.c.name == 'wendy', 'W'),
                    (users_table.c.name == 'jack', 'J'),
                    else_='E'
                )
            )

Details on Case usage is at case().

See also

case()

Class signature

class sqlalchemy.sql.expression.Case (sqlalchemy.sql.expression.ColumnElement)

• method sqlalchemy.sql.expression.Case.__init__(\whens, **kw*)

  Construct a new Case object.

  This constructor is mirrored as a public API function; see sqlalchemy.sql.expression.case() for a full usage and argument description.

class sqlalchemy.sql.expression.``Cast(expression, type_)

Represent a CAST expression.

Cast is produced using the cast() factory function, as in:

from sqlalchemy import cast, Numeric
stmt = select(cast(product_table.c.unit_price, Numeric(10, 4)))

Details on Cast usage is at cast().

See also

Data Casts and Type Coercion

cast()

type_coerce() - an alternative to CAST that coerces the type on the Python side only, which is often sufficient to generate the correct SQL and data coercion.

Class signature

class sqlalchemy.sql.expression.Cast (sqlalchemy.sql.expression.WrapsColumnExpression, sqlalchemy.sql.expression.ColumnElement)

• method sqlalchemy.sql.expression.Cast.__init__(expression, type_)

  Construct a new Cast object.

  This constructor is mirrored as a public API function; see sqlalchemy.sql.expression.cast() for a full usage and argument description.

class sqlalchemy.sql.expression.``ClauseElement

Base class for elements of a programmatically constructed SQL expression.

Class signature

class sqlalchemy.sql.expression.ClauseElement (sqlalchemy.sql.roles.SQLRole, sqlalchemy.sql.annotation.SupportsWrappingAnnotations, sqlalchemy.sql.traversals.MemoizedHasCacheKey, sqlalchemy.sql.traversals.HasCopyInternals, sqlalchemy.sql.visitors.Traversible)

• method sqlalchemy.sql.expression.ClauseElement.compare(other, \*kw*)

  Compare this ClauseElement to the given ClauseElement.

  Subclasses should override the default behavior, which is a straight identity comparison.

  **kw are arguments consumed by subclass compare() methods and may be used to modify the criteria for comparison (see ColumnElement).

• method sqlalchemy.sql.expression.ClauseElement.compile(bind=None, dialect=None, \*kw*)

  Compile this SQL expression.

  The return value is a Compiled object. Calling str() or unicode() on the returned value will yield a string representation of the result. The Compiled object also can return a dictionary of bind parameter names and values using the params accessor.

  • Parameters

    • bind – An Engine or Connection from which a Compiled will be acquired. This argument takes precedence over this ClauseElement’s bound engine, if any.

    • column_keys – Used for INSERT and UPDATE statements, a list of column names which should be present in the VALUES clause of the compiled statement. If None, all columns from the target table object are rendered.

    • dialect – A Dialect instance from which a Compiled will be acquired. This argument takes precedence over the bind argument as well as this ClauseElement ‘s bound engine, if any.

    • compile_kwargs –

      optional dictionary of additional parameters that will be passed through to the compiler within all “visit” methods. This allows any custom flag to be passed through to a custom compilation construct, for example. It is also used for the case of passing the literal_binds flag through:

      from sqlalchemy.sql import table, column, select
      t = table('t', column('x'))
      s = select(t).where(t.c.x == 5)
      print(s.compile(compile_kwargs={"literal_binds": True}))

      New in version 0.9.0.

See also
[How do I render SQL expressions as strings, possibly with bound parameters inlined?]($23f306fd0cdd485d.md#faq-sql-expression-string)

• method sqlalchemy.sql.expression.ClauseElement.get_children(omit_attrs=(), \*kw*)

  Return immediate child Traversible elements of this Traversible.

  This is used for visit traversal.

  **kw 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).

• class memoized_attribute(fget, doc=None)

  A read-only @property that is only evaluated once.

• method sqlalchemy.sql.expression.ClauseElement.classmethod memoized_instancemethod(fn)

  inherited from the HasMemoized.memoized_instancemethod() method of HasMemoized

  Decorate a method memoize its return value.

• method sqlalchemy.sql.expression.ClauseElement.params(\optionaldict, **kwargs*)

  Return a copy with bindparam() elements replaced.

  Returns a copy of this ClauseElement with bindparam() elements replaced with values taken from the given dictionary:

  >>> clause = column('x') + bindparam('foo')
  >>> print(clause.compile().params)
  {'foo':None}
  >>> print(clause.params({'foo':7}).compile().params)
  {'foo':7}

• method sqlalchemy.sql.expression.ClauseElement.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.

• method sqlalchemy.sql.expression.ClauseElement.unique_params(\optionaldict, **kwargs*)

  Return a copy with bindparam() elements replaced.

  Same functionality as ClauseElement.params(), except adds unique=True to affected bind parameters so that multiple statements can be used.

class sqlalchemy.sql.expression.``ClauseList(\clauses, **kwargs*)

Describe a list of clauses, separated by an operator.

By default, is comma-separated, such as a column listing.

Class signature

class sqlalchemy.sql.expression.ClauseList (sqlalchemy.sql.roles.InElementRole, sqlalchemy.sql.roles.OrderByRole, sqlalchemy.sql.roles.ColumnsClauseRole, sqlalchemy.sql.roles.DMLColumnRole, sqlalchemy.sql.expression.ClauseElement)

• method sqlalchemy.sql.expression.ClauseList.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.

class sqlalchemy.sql.expression.``ColumnClause(text, type_=None, is_literal=False, _selectable=None)

Represents a column expression from any textual string.

The ColumnClause, a lightweight analogue to the Column class, is typically invoked using the column() function, as in:

from sqlalchemy import column
id, name = column("id"), column("name")
stmt = select(id, name).select_from("user")

The above statement would produce SQL like:

SELECT id, name FROM user

ColumnClause is the immediate superclass of the schema-specific Column object. While the Column class has all the same capabilities as ColumnClause, the ColumnClause class is usable by itself in those cases where behavioral requirements are limited to simple SQL expression generation. The object has none of the associations with schema-level metadata or with execution-time behavior that Column does, so in that sense is a “lightweight” version of Column.

Full details on ColumnClause usage is at column().

See also

column()

Column

Class signature

class sqlalchemy.sql.expression.ColumnClause (sqlalchemy.sql.roles.DDLReferredColumnRole, sqlalchemy.sql.roles.LabeledColumnExprRole, sqlalchemy.sql.roles.StrAsPlainColumnRole, sqlalchemy.sql.expression.Immutable, sqlalchemy.sql.expression.NamedColumn)

• method sqlalchemy.sql.expression.ColumnClause.__init__(text, type_=None, is_literal=False, _selectable=None)

  Construct a new ColumnClause object.

  This constructor is mirrored as a public API function; see sqlalchemy.sql.expression.column() for a full usage and argument description.

• method sqlalchemy.sql.expression.ColumnClause.get_children(column_tables=False, \*kw*)

  Return immediate child Traversible elements of this Traversible.

  This is used for visit traversal.

  **kw 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).

class sqlalchemy.sql.expression.``ColumnCollection(columns=None)

Collection of ColumnElement instances, typically for selectables.

The ColumnCollection has both mapping- and sequence- like behaviors. A ColumnCollection usually stores Column objects, which are then accessible both via mapping style access as well as attribute access style. The name for which a Column would be present is normally that of the Column.key parameter, however depending on the context, it may be stored under a special label name:

>>> from sqlalchemy import Column, Integer
>>> from sqlalchemy.sql import ColumnCollection
>>> x, y = Column('x', Integer), Column('y', Integer)
>>> cc = ColumnCollection(columns=[(x.name, x), (y.name, y)])
>>> cc.x
Column('x', Integer(), table=None)
>>> cc.y
Column('y', Integer(), table=None)
>>> cc['x']
Column('x', Integer(), table=None)
>>> cc['y']

ColumnCollection also indexes the columns in order and allows them to be accessible by their integer position:

>>> cc[0]
Column('x', Integer(), table=None)
>>> cc[1]
Column('y', Integer(), table=None)

New in version 1.4: ColumnCollection allows integer-based index access to the collection.

Iterating the collection yields the column expressions in order:

>>> list(cc)
[Column('x', Integer(), table=None),
 Column('y', Integer(), table=None)]

The base ColumnCollection object can store duplicates, which can mean either two columns with the same key, in which case the column returned by key access is arbitrary:

>>> x1, x2 = Column('x', Integer), Column('x', Integer)
>>> cc = ColumnCollection(columns=[(x1.name, x1), (x2.name, x2)])
>>> list(cc)
[Column('x', Integer(), table=None),
 Column('x', Integer(), table=None)]
>>> cc['x'] is x1
False
>>> cc['x'] is x2
True

Or it can also mean the same column multiple times. These cases are supported as ColumnCollection is used to represent the columns in a SELECT statement which may include duplicates.

A special subclass DedupeColumnCollection exists which instead maintains SQLAlchemy’s older behavior of not allowing duplicates; this collection is used for schema level objects like Table and PrimaryKeyConstraint where this deduping is helpful. The DedupeColumnCollection class also has additional mutation methods as the schema constructs have more use cases that require removal and replacement of columns.

Changed in version 1.4: ColumnCollection now stores duplicate column keys as well as the same column in multiple positions. The DedupeColumnCollection class is added to maintain the former behavior in those cases where deduplication as well as additional replace/remove operations are needed.

• method sqlalchemy.sql.expression.ColumnCollection.contains_column(col)

  Checks if a column object exists in this collection

• method sqlalchemy.sql.expression.ColumnCollection.corresponding_column(column, require_embedded=False)

  Given a ColumnElement, return the exported ColumnElement object from this ColumnCollection which corresponds to that original ColumnElement via a common ancestor column.

  • Parameters

    • column – the target ColumnElement to be matched.

    • require_embedded – only return corresponding columns for the given ColumnElement, if the given ColumnElement is actually present within a sub-element of this Selectable. Normally the column will match if it merely shares a common ancestor with one of the exported columns of this Selectable.

See also
[`Selectable.corresponding_column()`]($fc2d211e9d1454ca.md#sqlalchemy.sql.expression.Selectable.corresponding_column "sqlalchemy.sql.expression.Selectable.corresponding_column") - invokes this method against the collection returned by [`Selectable.exported_columns`]($fc2d211e9d1454ca.md#sqlalchemy.sql.expression.Selectable.exported_columns "sqlalchemy.sql.expression.Selectable.exported_columns").
Changed in version 1.4: the implementation for `corresponding_column` was moved onto the [`ColumnCollection`](#sqlalchemy.sql.expression.ColumnCollection "sqlalchemy.sql.expression.ColumnCollection") itself.

class sqlalchemy.sql.expression.``ColumnElement

Represent a column-oriented SQL expression suitable for usage in the “columns” clause, WHERE clause etc. of a statement.

While the most familiar kind of ColumnElement is the Column object, ColumnElement serves as the basis for any unit that may be present in a SQL expression, including the expressions themselves, SQL functions, bound parameters, literal expressions, keywords such as NULL, etc. ColumnElement is the ultimate base class for all such elements.

A wide variety of SQLAlchemy Core functions work at the SQL expression level, and are intended to accept instances of ColumnElement as arguments. These functions will typically document that they accept a “SQL expression” as an argument. What this means in terms of SQLAlchemy usually refers to an input which is either already in the form of a ColumnElement object, or a value which can be coerced into one. The coercion rules followed by most, but not all, SQLAlchemy Core functions with regards to SQL expressions are as follows:

• a literal Python value, such as a string, integer or floating point value, boolean, datetime, Decimal object, or virtually any other Python object, will be coerced into a “literal bound value”. This generally means that a bindparam() will be produced featuring the given value embedded into the construct; the resulting BindParameter object is an instance of ColumnElement. The Python value will ultimately be sent to the DBAPI at execution time as a parameterized argument to the execute() or executemany() methods, after SQLAlchemy type-specific converters (e.g. those provided by any associated TypeEngine objects) are applied to the value.

• any special object value, typically ORM-level constructs, which feature an accessor called __clause_element__(). The Core expression system looks for this method when an object of otherwise unknown type is passed to a function that is looking to coerce the argument into a ColumnElement and sometimes a SelectBase expression. It is used within the ORM to convert from ORM-specific objects like mapped classes and mapped attributes into Core expression objects.

• The Python None value is typically interpreted as NULL, which in SQLAlchemy Core produces an instance of null().

A ColumnElement provides the ability to generate new ColumnElement objects using Python expressions. This means that Python operators such as ==, != and < are overloaded to mimic SQL operations, and allow the instantiation of further ColumnElement instances which are composed from other, more fundamental ColumnElement objects. For example, two ColumnClause objects can be added together with the addition operator + to produce a BinaryExpression. Both ColumnClause and BinaryExpression are subclasses of ColumnElement:

>>> from sqlalchemy.sql import column
>>> column('a') + column('b')
<sqlalchemy.sql.expression.BinaryExpression object at 0x101029dd0>
>>> print(column('a') + column('b'))
a + b

See also

Column

column()

Class signature

class sqlalchemy.sql.expression.ColumnElement (sqlalchemy.sql.roles.ColumnArgumentOrKeyRole, sqlalchemy.sql.roles.StatementOptionRole, sqlalchemy.sql.roles.WhereHavingRole, sqlalchemy.sql.roles.BinaryElementRole, sqlalchemy.sql.roles.OrderByRole, sqlalchemy.sql.roles.ColumnsClauseRole, sqlalchemy.sql.roles.LimitOffsetRole, sqlalchemy.sql.roles.DMLColumnRole, sqlalchemy.sql.roles.DDLConstraintColumnRole, sqlalchemy.sql.roles.DDLExpressionRole, sqlalchemy.sql.expression.ColumnOperators, sqlalchemy.sql.expression.ClauseElement)

• method sqlalchemy.sql.expression.ColumnElement.__eq__(other)

  inherited from the sqlalchemy.sql.expression.ColumnOperators.__eq__ method of ColumnOperators

  Implement the == operator.

  In a column context, produces the clause a = b. If the target is None, produces a IS NULL.

• method sqlalchemy.sql.expression.ColumnElement.__le__(other)

  inherited from the sqlalchemy.sql.expression.ColumnOperators.__le__ method of ColumnOperators

  Implement the <= operator.

  In a column context, produces the clause a <= b.

• method sqlalchemy.sql.expression.ColumnElement.__lt__(other)

  inherited from the sqlalchemy.sql.expression.ColumnOperators.__lt__ method of ColumnOperators

  Implement the < operator.

  In a column context, produces the clause a < b.

• method sqlalchemy.sql.expression.ColumnElement.__ne__(other)

  inherited from the sqlalchemy.sql.expression.ColumnOperators.__ne__ method of ColumnOperators

  Implement the != operator.

  In a column context, produces the clause a != b. If the target is None, produces a IS NOT NULL.

• method sqlalchemy.sql.expression.ColumnElement.all_()

  inherited from the ColumnOperators.all_() method of ColumnOperators

  Produce a all_() clause against the parent object.

  This operator is only appropriate against a scalar subquery object, or for some backends an column expression that is against the ARRAY type, e.g.:

  # postgresql '5 = ALL (somearray)'
  expr = 5 == mytable.c.somearray.all_()
  # mysql '5 = ALL (SELECT value FROM table)'
  expr = 5 == select(table.c.value).scalar_subquery().all_()

  See also

  all_() - standalone version

  any_() - ANY operator

  New in version 1.1.

• attribute sqlalchemy.sql.expression.ColumnElement.allows_lambda = True

• attribute sqlalchemy.sql.expression.ColumnElement.anon_key_label

  Provides a constant ‘anonymous key label’ for this ColumnElement.

  Compare to anon_label, except that the “key” of the column, if available, is used to generate the label.

  This is used when a deduplicating key is placed into the columns collection of a selectable.

• attribute sqlalchemy.sql.expression.ColumnElement.anon_label

  Provides a constant ‘anonymous label’ for this ColumnElement.

  This is a label() expression which will be named at compile time. The same label() is returned each time anon_label is called so that expressions can reference anon_label multiple times, producing the same label name at compile time.

  The compiler uses this function automatically at compile time for expressions that are known to be ‘unnamed’ like binary expressions and function calls.

• method sqlalchemy.sql.expression.ColumnElement.any_()

  inherited from the ColumnOperators.any_() method of ColumnOperators

  Produce a any_() clause against the parent object.

  This operator is only appropriate against a scalar subquery object, or for some backends an column expression that is against the ARRAY type, e.g.:

  # postgresql '5 = ANY (somearray)'
  expr = 5 == mytable.c.somearray.any_()
  # mysql '5 = ANY (SELECT value FROM table)'
  expr = 5 == select(table.c.value).scalar_subquery().any_()

  See also

  any_() - standalone version

  all_() - ALL operator

  New in version 1.1.

• method sqlalchemy.sql.expression.ColumnElement.asc()

  inherited from the ColumnOperators.asc() method of ColumnOperators

  Produce a asc() clause against the parent object.

• attribute sqlalchemy.sql.expression.ColumnElement.base_columns

• method sqlalchemy.sql.expression.ColumnElement.between(cleft, cright, symmetric=False)

  inherited from the ColumnOperators.between() method of ColumnOperators

  Produce a between() clause against the parent object, given the lower and upper range.

• attribute sqlalchemy.sql.expression.ColumnElement.bind = None

• method sqlalchemy.sql.expression.ColumnElement.bool_op(opstring, precedence=0)

  inherited from the Operators.bool_op() method of Operators

  Return a custom boolean operator.

  This method is shorthand for calling Operators.op() and passing the Operators.op.is_comparison flag with True.

  See also

  Operators.op()

• method sqlalchemy.sql.expression.ColumnElement.cast(type_)

  Produce a type cast, i.e. CAST(<expression> AS <type>).

  This is a shortcut to the cast() function.

  See also

  Data Casts and Type Coercion

  cast()

  type_coerce()

  New in version 1.0.7.

• method sqlalchemy.sql.expression.ColumnElement.collate(collation)

  inherited from the ColumnOperators.collate() method of ColumnOperators

  Produce a collate() clause against the parent object, given the collation string.

  See also

  collate()

• attribute sqlalchemy.sql.expression.ColumnElement.comparator

• method sqlalchemy.sql.expression.ColumnElement.compare(other, \*kw*)

  inherited from the ClauseElement.compare() method of ClauseElement

  Compare this ClauseElement to the given ClauseElement.

  Subclasses should override the default behavior, which is a straight identity comparison.

  **kw are arguments consumed by subclass compare() methods and may be used to modify the criteria for comparison (see ColumnElement).

• method sqlalchemy.sql.expression.ColumnElement.compile(bind=None, dialect=None, \*kw*)

  inherited from the ClauseElement.compile() method of ClauseElement

  Compile this SQL expression.

  The return value is a Compiled object. Calling str() or unicode() on the returned value will yield a string representation of the result. The Compiled object also can return a dictionary of bind parameter names and values using the params accessor.

  • Parameters

    • bind – An Engine or Connection from which a Compiled will be acquired. This argument takes precedence over this ClauseElement’s bound engine, if any.

    • column_keys – Used for INSERT and UPDATE statements, a list of column names which should be present in the VALUES clause of the compiled statement. If None, all columns from the target table object are rendered.

    • dialect – A Dialect instance from which a Compiled will be acquired. This argument takes precedence over the bind argument as well as this ClauseElement ‘s bound engine, if any.

    • compile_kwargs –

      optional dictionary of additional parameters that will be passed through to the compiler within all “visit” methods. This allows any custom flag to be passed through to a custom compilation construct, for example. It is also used for the case of passing the literal_binds flag through:

      from sqlalchemy.sql import table, column, select
      t = table('t', column('x'))
      s = select(t).where(t.c.x == 5)
      print(s.compile(compile_kwargs={"literal_binds": True}))

      New in version 0.9.0.

See also
[How do I render SQL expressions as strings, possibly with bound parameters inlined?]($23f306fd0cdd485d.md#faq-sql-expression-string)

• method sqlalchemy.sql.expression.ColumnElement.concat(other)

  inherited from the ColumnOperators.concat() method of ColumnOperators

  Implement the ‘concat’ operator.

  In a column context, produces the clause a || b, or uses the concat() operator on MySQL.

• method sqlalchemy.sql.expression.ColumnElement.contains(other, \*kwargs*)

  inherited from the ColumnOperators.contains() method of ColumnOperators

  Implement the ‘contains’ operator.

  Produces a LIKE expression that tests against a match for the middle of a string value:

  column LIKE '%' || <other> || '%'

  E.g.:

  stmt = select(sometable).\
      where(sometable.c.column.contains("foobar"))

  Since the operator uses LIKE, wildcard characters "%" and "_" that are present inside the <other> expression will behave like wildcards as well. For literal string values, the ColumnOperators.contains.autoescape flag may be set to True to apply escaping to occurrences of these characters within the string value so that they match as themselves and not as wildcard characters. Alternatively, the ColumnOperators.contains.escape parameter will establish a given character as an escape character which can be of use when the target expression is not a literal string.

  • Parameters

    • other – expression to be compared. This is usually a plain string value, but can also be an arbitrary SQL expression. LIKE wildcard characters % and _ are not escaped by default unless the ColumnOperators.contains.autoescape flag is set to True.

    • autoescape –

      boolean; when True, establishes an escape character within the LIKE expression, then applies it to all occurrences of "%", "_" and the escape character itself within the comparison value, which is assumed to be a literal string and not a SQL expression.

      An expression such as:

      somecolumn.contains("foo%bar", autoescape=True)

      Will render as:

      somecolumn LIKE '%' || :param || '%' ESCAPE '/'

      With the value of :param as "foo/%bar".

    • escape –

      a character which when given will render with the ESCAPE keyword to establish that character as the escape character. This character can then be placed preceding occurrences of % and _ to allow them to act as themselves and not wildcard characters.

      An expression such as:

      somecolumn.contains("foo/%bar", escape="^")

      Will render as:

      somecolumn LIKE '%' || :param || '%' ESCAPE '^'

      The parameter may also be combined with ColumnOperators.contains.autoescape:

      somecolumn.contains("foo%bar^bat", escape="^", autoescape=True)

      Where above, the given literal parameter will be converted to "foo^%bar^^bat" before being passed to the database.

See also
[`ColumnOperators.startswith()`](#sqlalchemy.sql.expression.ColumnOperators.startswith "sqlalchemy.sql.expression.ColumnOperators.startswith")
[`ColumnOperators.endswith()`](#sqlalchemy.sql.expression.ColumnOperators.endswith "sqlalchemy.sql.expression.ColumnOperators.endswith")
[`ColumnOperators.like()`](#sqlalchemy.sql.expression.ColumnOperators.like "sqlalchemy.sql.expression.ColumnOperators.like")

• method sqlalchemy.sql.expression.ColumnElement.desc()

  inherited from the ColumnOperators.desc() method of ColumnOperators

  Produce a desc() clause against the parent object.

• attribute sqlalchemy.sql.expression.ColumnElement.description = None

• method sqlalchemy.sql.expression.ColumnElement.distinct()

  inherited from the ColumnOperators.distinct() method of ColumnOperators

  Produce a distinct() clause against the parent object.

• method sqlalchemy.sql.expression.ColumnElement.endswith(other, \*kwargs*)

  inherited from the ColumnOperators.endswith() method of ColumnOperators

  Implement the ‘endswith’ operator.

  Produces a LIKE expression that tests against a match for the end of a string value:

  column LIKE '%' || <other>

  E.g.:

  stmt = select(sometable).\
      where(sometable.c.column.endswith("foobar"))

  Since the operator uses LIKE, wildcard characters "%" and "_" that are present inside the <other> expression will behave like wildcards as well. For literal string values, the ColumnOperators.endswith.autoescape flag may be set to True to apply escaping to occurrences of these characters within the string value so that they match as themselves and not as wildcard characters. Alternatively, the ColumnOperators.endswith.escape parameter will establish a given character as an escape character which can be of use when the target expression is not a literal string.

  • Parameters

    • other – expression to be compared. This is usually a plain string value, but can also be an arbitrary SQL expression. LIKE wildcard characters % and _ are not escaped by default unless the ColumnOperators.endswith.autoescape flag is set to True.

    • autoescape –

      boolean; when True, establishes an escape character within the LIKE expression, then applies it to all occurrences of "%", "_" and the escape character itself within the comparison value, which is assumed to be a literal string and not a SQL expression.

      An expression such as:

      somecolumn.endswith("foo%bar", autoescape=True)

      Will render as:

      somecolumn LIKE '%' || :param ESCAPE '/'

      With the value of :param as "foo/%bar".

    • escape –

      a character which when given will render with the ESCAPE keyword to establish that character as the escape character. This character can then be placed preceding occurrences of % and _ to allow them to act as themselves and not wildcard characters.

      An expression such as:

      somecolumn.endswith("foo/%bar", escape="^")

      Will render as:

      somecolumn LIKE '%' || :param ESCAPE '^'

      The parameter may also be combined with ColumnOperators.endswith.autoescape:

      somecolumn.endswith("foo%bar^bat", escape="^", autoescape=True)

      Where above, the given literal parameter will be converted to "foo^%bar^^bat" before being passed to the database.

See also
[`ColumnOperators.startswith()`](#sqlalchemy.sql.expression.ColumnOperators.startswith "sqlalchemy.sql.expression.ColumnOperators.startswith")
[`ColumnOperators.contains()`](#sqlalchemy.sql.expression.ColumnOperators.contains "sqlalchemy.sql.expression.ColumnOperators.contains")
[`ColumnOperators.like()`](#sqlalchemy.sql.expression.ColumnOperators.like "sqlalchemy.sql.expression.ColumnOperators.like")

• attribute sqlalchemy.sql.expression.ColumnElement.expression

  Return a column expression.

  Part of the inspection interface; returns self.

• attribute sqlalchemy.sql.expression.ColumnElement.foreign_keys = []

• method sqlalchemy.sql.expression.ColumnElement.get_children(omit_attrs=(), \*kw*)

  inherited from the ClauseElement.get_children() method of ClauseElement

  Return immediate child Traversible elements of this Traversible.

  This is used for visit traversal.

  **kw 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).

• method sqlalchemy.sql.expression.ColumnElement.ilike(other, escape=None)

  inherited from the ColumnOperators.ilike() method of ColumnOperators

  Implement the ilike operator, e.g. case insensitive LIKE.

  In a column context, produces an expression either of the form:

  lower(a) LIKE lower(other)

  Or on backends that support the ILIKE operator:

  a ILIKE other

  E.g.:

  stmt = select(sometable).\
      where(sometable.c.column.ilike("%foobar%"))

  • Parameters

    • other – expression to be compared

    • escape –

      optional escape character, renders the ESCAPE keyword, e.g.:

      somecolumn.ilike("foo/%bar", escape="/")

See also
[`ColumnOperators.like()`](#sqlalchemy.sql.expression.ColumnOperators.like "sqlalchemy.sql.expression.ColumnOperators.like")

• method sqlalchemy.sql.expression.ColumnElement.in_(other)

  inherited from the ColumnOperators.in_() method of ColumnOperators

  Implement the in operator.

  In a column context, produces the clause column IN <other>.

  The given parameter other may be:

  • A list of literal values, e.g.:

    stmt.where(column.in_([1, 2, 3]))

    In this calling form, the list of items is converted to a set of bound parameters the same length as the list given:

    WHERE COL IN (?, ?, ?)

  • A list of tuples may be provided if the comparison is against a tuple_() containing multiple expressions:

    from sqlalchemy import tuple_
    stmt.where(tuple_(col1, col2).in_([(1, 10), (2, 20), (3, 30)]))

  • An empty list, e.g.:

    stmt.where(column.in_([]))

    In this calling form, the expression renders an “empty set” expression. These expressions are tailored to individual backends and are generally trying to get an empty SELECT statement as a subquery. Such as on SQLite, the expression is:

    WHERE col IN (SELECT 1 FROM (SELECT 1) WHERE 1!=1)

    Changed in version 1.4: empty IN expressions now use an execution-time generated SELECT subquery in all cases.

  • A bound parameter, e.g. bindparam(), may be used if it includes the bindparam.expanding flag:

    stmt.where(column.in_(bindparam('value', expanding=True)))

    In this calling form, the expression renders a special non-SQL placeholder expression that looks like:

    WHERE COL IN ([EXPANDING_value])

    This placeholder expression is intercepted at statement execution time to be converted into the variable number of bound parameter form illustrated earlier. If the statement were executed as:

    connection.execute(stmt, {"value": [1, 2, 3]})

    The database would be passed a bound parameter for each value:

    WHERE COL IN (?, ?, ?)

    New in version 1.2: added “expanding” bound parameters

    If an empty list is passed, a special “empty list” expression, which is specific to the database in use, is rendered. On SQLite this would be:

    WHERE COL IN (SELECT 1 FROM (SELECT 1) WHERE 1!=1)

    New in version 1.3: “expanding” bound parameters now support empty lists

  • a select() construct, which is usually a correlated scalar select:

    stmt.where(
        column.in_(
            select(othertable.c.y).
            where(table.c.x == othertable.c.x)
        )
    )

    In this calling form, ColumnOperators.in_() renders as given:

    WHERE COL IN (SELECT othertable.y
    FROM othertable WHERE othertable.x = table.x)

  • Parameters

    other – a list of literals, a select() construct, or a bindparam() construct that includes the bindparam.expanding flag set to True.

• method sqlalchemy.sql.expression.ColumnElement.is_(other)

  inherited from the ColumnOperators.is_() method of ColumnOperators

  Implement the IS operator.

  Normally, IS is generated automatically when comparing to a value of None, which resolves to NULL. However, explicit usage of IS may be desirable if comparing to boolean values on certain platforms.

  See also

  ColumnOperators.is_not()

• attribute sqlalchemy.sql.expression.ColumnElement.is_clause_element = True

• method sqlalchemy.sql.expression.ColumnElement.is_distinct_from(other)

  inherited from the ColumnOperators.is_distinct_from() method of ColumnOperators

  Implement the IS DISTINCT FROM operator.

  Renders “a IS DISTINCT FROM b” on most platforms; on some such as SQLite may render “a IS NOT b”.

  New in version 1.1.

• method sqlalchemy.sql.expression.ColumnElement.is_not(other)

  inherited from the ColumnOperators.is_not() method of ColumnOperators

  Implement the IS NOT operator.

  Normally, IS NOT is generated automatically when comparing to a value of None, which resolves to NULL. However, explicit usage of IS NOT may be desirable if comparing to boolean values on certain platforms.

  Changed in version 1.4: The is_not() operator is renamed from isnot() in previous releases. The previous name remains available for backwards compatibility.

  See also

  ColumnOperators.is_()

• method sqlalchemy.sql.expression.ColumnElement.is_not_distinct_from(other)

  inherited from the ColumnOperators.is_not_distinct_from() method of ColumnOperators

  Implement the IS NOT DISTINCT FROM operator.

  Renders “a IS NOT DISTINCT FROM b” on most platforms; on some such as SQLite may render “a IS b”.

  Changed in version 1.4: The is_not_distinct_from() operator is renamed from isnot_distinct_from() in previous releases. The previous name remains available for backwards compatibility.

  New in version 1.1.

• attribute sqlalchemy.sql.expression.ColumnElement.is_selectable = False

• method sqlalchemy.sql.expression.ColumnElement.isnot(other)

  inherited from the ColumnOperators.isnot() method of ColumnOperators

  Implement the IS NOT operator.

  Normally, IS NOT is generated automatically when comparing to a value of None, which resolves to NULL. However, explicit usage of IS NOT may be desirable if comparing to boolean values on certain platforms.

  Changed in version 1.4: The is_not() operator is renamed from isnot() in previous releases. The previous name remains available for backwards compatibility.

  See also

  ColumnOperators.is_()

• method sqlalchemy.sql.expression.ColumnElement.isnot_distinct_from(other)

  inherited from the ColumnOperators.isnot_distinct_from() method of ColumnOperators

  Implement the IS NOT DISTINCT FROM operator.

  Renders “a IS NOT DISTINCT FROM b” on most platforms; on some such as SQLite may render “a IS b”.

  Changed in version 1.4: The is_not_distinct_from() operator is renamed from isnot_distinct_from() in previous releases. The previous name remains available for backwards compatibility.

  New in version 1.1.

• attribute sqlalchemy.sql.expression.ColumnElement.key = None

  The ‘key’ that in some circumstances refers to this object in a Python namespace.

  This typically refers to the “key” of the column as present in the .c collection of a selectable, e.g. sometable.c["somekey"] would return a Column with a .key of “somekey”.

• method sqlalchemy.sql.expression.ColumnElement.label(name)

  Produce a column label, i.e. <columnname> AS <name>.

  This is a shortcut to the label() function.

  If ‘name’ is None, an anonymous label name will be generated.

• method sqlalchemy.sql.expression.ColumnElement.like(other, escape=None)

  inherited from the ColumnOperators.like() method of ColumnOperators

  Implement the like operator.

  In a column context, produces the expression:

  a LIKE other

  E.g.:

  stmt = select(sometable).\
      where(sometable.c.column.like("%foobar%"))

  • Parameters

    • other – expression to be compared

    • escape –

      optional escape character, renders the ESCAPE keyword, e.g.:

      somecolumn.like("foo/%bar", escape="/")