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For dialects such as that of PostgreSQL, this operator applies to usage of the :class:`_types.ARRAY` datatype, for that of MySQL, it may apply to a subquery. e.g.:: # renders on PostgreSQL: # '5 = ALL (somearray)' expr = 5 == all_(mytable.c.somearray) # renders on MySQL: # '5 = ALL (SELECT value FROM table)' expr = 5 == all_(select(table.c.value)) Comparison to NULL may work using ``None``:: None == all_(mytable.c.somearray) The any_() / all_() operators also feature a special "operand flipping" behavior such that if any_() / all_() are used on the left side of a comparison using a standalone operator such as ``==``, ``!=``, etc. (not including operator methods such as :meth:`_sql.ColumnOperators.is_`) the rendered expression is flipped:: # would render '5 = ALL (column)` all_(mytable.c.column) == 5 Or with ``None``, which note will not perform the usual step of rendering "IS" as is normally the case for NULL:: # would render 'NULL = ALL(somearray)' all_(mytable.c.somearray) == None .. versionchanged:: 1.4.26 repaired the use of any_() / all_() comparing to NULL on the right side to be flipped to the left. The column-level :meth:`_sql.ColumnElement.all_` method (not to be confused with :class:`_types.ARRAY` level :meth:`_types.ARRAY.Comparator.all`) is shorthand for ``all_(col)``:: 5 == mytable.c.somearray.all_() .. seealso:: :meth:`_sql.ColumnOperators.all_` :func:`_expression.any_` )r Z _create_all�r? � rB �U/opt/hc_python/lib64/python3.8/site-packages/sqlalchemy/sql/_elements_constructors.py�all_? s 3rD z5Union[Literal[True], _ColumnExpressionArgument[bool]]z _ColumnExpressionArgument[bool]zColumnElement[bool])�initial_clause�clausesr@ c G s dS )a� 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 :func:`.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 :func:`.and_` operation is also implicit in some cases; the :meth:`_expression.Select.where` method for example can be invoked multiple times against a statement, which will have the effect of each clause being combined using :func:`.and_`:: stmt = select(users_table).\ where(users_table.c.name == 'wendy').\ where(users_table.c.enrolled == True) The :func:`.and_` construct must be given at least one positional argument in order to be valid; a :func:`.and_` construct with no arguments is ambiguous. To produce an "empty" or dynamically generated :func:`.and_` expression, from a given list of expressions, a "default" element of :func:`_sql.true` (or just ``True``) should be specified:: from sqlalchemy import true 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 :func:`_sql.true` value is ignored as it does not affect the outcome of an AND expression that has other elements. .. deprecated:: 1.4 The :func:`.and_` element now requires that at least one argument is passed; creating the :func:`.and_` construct with no arguments is deprecated, and will emit a deprecation warning while continuing to produce a blank SQL string. .. seealso:: :func:`.or_` NrB �rE rF rB rB rC �and_u s ?rH c G s t j| � S )a~ 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 :func:`.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 :func:`.and_` operation is also implicit in some cases; the :meth:`_expression.Select.where` method for example can be invoked multiple times against a statement, which will have the effect of each clause being combined using :func:`.and_`:: stmt = select(users_table).\ where(users_table.c.name == 'wendy').\ where(users_table.c.enrolled == True) The :func:`.and_` construct must be given at least one positional argument in order to be valid; a :func:`.and_` construct with no arguments is ambiguous. To produce an "empty" or dynamically generated :func:`.and_` expression, from a given list of expressions, a "default" element of :func:`_sql.true` (or just ``True``) should be specified:: from sqlalchemy import true 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 :func:`_sql.true` value is ignored as it does not affect the outcome of an AND expression that has other elements. .. deprecated:: 1.4 The :func:`.and_` element now requires that at least one argument is passed; creating the :func:`.and_` construct with no arguments is deprecated, and will emit a deprecation warning while continuing to produce a blank SQL string. .. seealso:: :func:`.or_` )r rH �rF rB rB rC rH � s <c C s t �| �S )a Produce an ANY expression. For dialects such as that of PostgreSQL, this operator applies to usage of the :class:`_types.ARRAY` datatype, for that of MySQL, it may apply to a subquery. e.g.:: # renders on PostgreSQL: # '5 = ANY (somearray)' expr = 5 == any_(mytable.c.somearray) # renders on MySQL: # '5 = ANY (SELECT value FROM table)' expr = 5 == any_(select(table.c.value)) Comparison to NULL may work using ``None`` or :func:`_sql.null`:: None == any_(mytable.c.somearray) The any_() / all_() operators also feature a special "operand flipping" behavior such that if any_() / all_() are used on the left side of a comparison using a standalone operator such as ``==``, ``!=``, etc. (not including operator methods such as :meth:`_sql.ColumnOperators.is_`) the rendered expression is flipped:: # would render '5 = ANY (column)` any_(mytable.c.column) == 5 Or with ``None``, which note will not perform the usual step of rendering "IS" as is normally the case for NULL:: # would render 'NULL = ANY(somearray)' any_(mytable.c.somearray) == None .. versionchanged:: 1.4.26 repaired the use of any_() / all_() comparing to NULL on the right side to be flipped to the left. The column-level :meth:`_sql.ColumnElement.any_` method (not to be confused with :class:`_types.ARRAY` level :meth:`_types.ARRAY.Comparator.any`) is shorthand for ``any_(col)``:: 5 = mytable.c.somearray.any_() .. seealso:: :meth:`_sql.ColumnOperators.any_` :func:`_expression.all_` )r Z _create_anyrA rB rB rC �any_� s 3rJ z'_ColumnExpressionOrStrLabelArgument[_T]zUnaryExpression[_T])�columnr@ c C s t �| �S )a 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 :func:`.asc` function is a standalone version of the :meth:`_expression.ColumnElement.asc` method available on all SQL expressions, e.g.:: stmt = select(users_table).order_by(users_table.c.name.asc()) :param column: A :class:`_expression.ColumnElement` (e.g. scalar SQL expression) with which to apply the :func:`.asc` operation. .. seealso:: :func:`.desc` :func:`.nulls_first` :func:`.nulls_last` :meth:`_expression.Select.order_by` )r0 Z _create_asc�rK rB rB rC �asc. s %rM z _ColumnExpressionArgument[str]�strzBinaryExpression[str])� expression� collationr@ c C s t �| |�S )a� 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. .. versionchanged:: 1.2 quoting is automatically applied to COLLATE expressions if they are case sensitive. )r Z _create_collation_expression)rO rP rB rB rC �collateV s rQ Fz&_ColumnExpressionOrLiteralArgument[_T]r �boolzBinaryExpression[bool])r? � lower_bound� upper_bound� symmetricr@ c C s t �tj| �}|j|||d�S )aV 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 :func:`.between` function is a standalone version of the :meth:`_expression.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 :func:`.between`, including the left side column expression, are coerced from Python scalar values if a the value is not a :class:`_expression.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 :param expr: a column expression, typically a :class:`_expression.ColumnElement` instance or alternatively a Python scalar expression to be coerced into a column expression, serving as the left side of the ``BETWEEN`` expression. :param lower_bound: a column or Python scalar expression serving as the lower bound of the right side of the ``BETWEEN`` expression. :param upper_bound: a column or Python scalar expression serving as the upper bound of the right side of the ``BETWEEN`` expression. :param symmetric: if True, will render " BETWEEN SYMMETRIC ". Note that not all databases support this syntax. .. seealso:: :meth:`_expression.ColumnElement.between` )rU )r �expectr �ExpressionElementRole�between)r? rS rT rU Zcol_exprrB rB rC rX m s 7rX zOptional[TypeEngine[_T]]zBindParameter[_T])�key�type_r@ c C s t | d|ddd�S )ax 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 :class:`~sqlalchemy.engine.CursorResult` object via its ``out_parameters`` attribute, which returns a dictionary containing the values. NFT)rZ �unique� isoutparamr )rY rZ rB rB rC �outparam� s r] zBinaryExpression[_T])�clauser@ c C s d S �NrB �r^ rB rB rC �not_� s ra zColumnElement[_T]c C s d S r_ rB r` rB rB rC ra � s c C s t �tj| ��� S )z�Return a negation of the given clause, i.e. ``NOT(clause)``. The ``~`` operator is also overloaded on all :class:`_expression.ColumnElement` subclasses to produce the same result. )r rV r rW � __invert__r` rB rB rC ra � s z Optional[str]z!Optional[_TypeEngineArgument[_T]]z#Union[bool, Literal[_NoArg.NO_ARG]]zOptional[bool]zOptional[Callable[[], Any]]) rY �valuerZ r[ �required�quote� callable_� expandingr\ �literal_executer@ c C s t | ||||||||| � S )a ' Produce a "bound expression". The return value is an instance of :class:`.BindParameter`; this is a :class:`_expression.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 :func:`.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 :term:`DBAPI` as values which need to be correctly escaped and potentially handled for type-safety. When using :func:`.bindparam` explicitly, the use case is typically one of traditional deferment of parameters; the :func:`.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 :meth:`_engine.Connection.execute`:: result = connection.execute(stmt, {"username": "wendy"}) Explicit use of :func:`.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 :func:`.bindparam` in an implicit sense. It is typical that Python literal values passed to virtually all SQL expression functions are coerced into fixed :func:`.bindparam` constructs. For example, given a comparison operation such as:: expr = users_table.c.name == 'Wendy' The above expression will produce a :class:`.BinaryExpression` construct, where the left side is the :class:`_schema.Column` object representing the ``name`` column, and the right side is a :class:`.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, :func:`.bindparam` is invoked automatically when working with :term:`CRUD` statements as far as the "VALUES" portion is concerned. The :func:`_expression.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 :class:`_expression.Insert` construct, at compilation/execution time, rendered a single :func:`.bindparam` mirroring the column name ``name`` as a result of the single ``name`` parameter we passed to the :meth:`_engine.Connection.execute` method. :param 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 :class:`BindParameter` objects exist with the same key, or if its length is too long and truncation is required. If omitted, an "anonymous" name is generated for the bound parameter; when given a value to bind, the end result is equivalent to calling upon the :func:`.literal` function with a value to bind, particularly if the :paramref:`.bindparam.unique` parameter is also provided. :param 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``. :param 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. :param type\_: A :class:`.TypeEngine` class or instance representing an optional datatype for this :func:`.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 :class:`.String`, :class:`.Integer` or :class:`.Boolean` types being automatically selected. The type of a :func:`.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 :func:`.bindparam` which refers to a datetime value, and is specified as holding the :class:`.DateTime` type, may apply conversion needed to the value (such as stringification on SQLite) before passing the value to the database. :param unique: if True, the key name of this :class:`.BindParameter` will be modified if another :class:`.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 :func:`.bindparam` constructs. :param required: If ``True``, a value is required at execution time. If not passed, it defaults to ``True`` if neither :paramref:`.bindparam.value` or :paramref:`.bindparam.callable` were passed. If either of these parameters are present, then :paramref:`.bindparam.required` defaults to ``False``. :param 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. :param 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. :param 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. .. seealso:: :meth:`.ColumnOperators.in_` :ref:`baked_in` - with baked queries .. note:: The "expanding" feature does not support "executemany"- style parameter sets. .. versionadded:: 1.2 .. versionchanged:: 1.3 the "expanding" bound parameter feature now supports empty lists. :param 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. .. versionadded:: 1.4 Added "post compile" bound parameters .. seealso:: :ref:`change_4808`. .. seealso:: :ref:`tutorial_sending_parameters` - in the :ref:`unified_tutorial` r ) rY rc rZ r[ rd re rf rg r\ rh rB rB rC � bindparam� s {�ri �rc �else_zLUnion[typing_Tuple[_ColumnExpressionArgument[bool], Any], Mapping[Any, Any]]z Optional[Any]z Case[Any])�whensrc rk r@ c G s t || |d��S )a5 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 :class:`.Case`. :func:`.case` in its usual form is passed a series 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, :func:`.case` also has a "shorthand" format used via the :paramref:`.case.value` parameter, which is passed a column expression to be compared. In this form, the :paramref:`.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 :paramref:`.case.whens` as well as with :paramref:`.case.else_` are coerced from Python literals into :func:`.bindparam` constructs. SQL expressions, e.g. :class:`_expression.ColumnElement` constructs, are accepted as well. To coerce a literal string expression into a constant expression rendered inline, use the :func:`_expression.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 :param \*whens: The criteria to be compared against, :paramref:`.case.whens` accepts two different forms, based on whether or not :paramref:`.case.value` is used. .. versionchanged:: 1.4 the :func:`_sql.case` function now accepts the series of WHEN conditions positionally In the first form, it accepts multiple 2-tuples passed as positional arguments; 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 :paramref:`.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 ) :param value: An optional SQL expression which will be used as a fixed "comparison point" for candidate values within a dictionary passed to :paramref:`.case.whens`. :param else\_: An optional SQL expression which will be the evaluated result of the ``CASE`` construct if all expressions within :paramref:`.case.whens` evaluate to false. When omitted, most databases will produce a result of NULL if none of the "when" expressions evaluate to true. rj r )rc rk rl rB rB rC �case� s rm z'_ColumnExpressionOrLiteralArgument[Any]z_TypeEngineArgument[_T]zCast[_T])rO rZ r@ c C s t | |�S )a Produce a ``CAST`` expression. :func:`.cast` returns an instance of :class:`.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 :func:`.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. :class:`.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. An alternative to :func:`.cast` is the :func:`.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. :param expression: A SQL expression, such as a :class:`_expression.ColumnElement` expression or a Python string which will be coerced into a bound literal value. :param type\_: A :class:`.TypeEngine` class or instance indicating the type to which the ``CAST`` should apply. .. seealso:: :ref:`tutorial_casts` :func:`.try_cast` - an alternative to CAST that results in NULLs when the cast fails, instead of raising an error. Only supported by some dialects. :func:`.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. r �rO rZ rB rB rC �castU s 6ro z TryCast[_T]c C s t | |�S )a� Produce a ``TRY_CAST`` expression for backends which support it; this is a ``CAST`` which returns NULL for un-castable conversions. In SQLAlchemy, this construct is supported **only** by the SQL Server dialect, and will raise a :class:`.CompileError` if used on other included backends. However, third party backends may also support this construct. .. tip:: As :func:`_sql.try_cast` originates from the SQL Server dialect, it's importable both from ``sqlalchemy.`` as well as from ``sqlalchemy.dialects.mssql``. :func:`_sql.try_cast` returns an instance of :class:`.TryCast` and generally behaves similarly to the :class:`.Cast` construct; at the SQL level, the difference between ``CAST`` and ``TRY_CAST`` is that ``TRY_CAST`` returns NULL for an un-castable expression, such as attempting to cast a string ``"hi"`` to an integer value. E.g.:: from sqlalchemy import select, try_cast, Numeric stmt = select( try_cast(product_table.c.unit_price, Numeric(10, 4)) ) The above would render on Microsoft SQL Server as:: SELECT TRY_CAST (product_table.unit_price AS NUMERIC(10, 4)) FROM product_table .. versionadded:: 2.0.14 :func:`.try_cast` has been generalized from the SQL Server dialect into a general use construct that may be supported by additional dialects. r, rn rB rB rC �try_cast� s (rp zOptional[FromClause]zColumnClause[_T])�textrZ � is_literal� _selectabler@ c C s t | |||�S )a� Produce a :class:`.ColumnClause` object. The :class:`.ColumnClause` is a lightweight analogue to the :class:`_schema.Column` class. The :func:`_expression.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, :func:`_expression.column` may be used like any other SQL expression element such as within :func:`_expression.select` constructs:: from sqlalchemy.sql import column id, name = column("id"), column("name") stmt = select(id, name).select_from("user") The text handled by :func:`_expression.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 :func:`_expression.literal_column` instead, or pass ``True`` as the value of :paramref:`_expression.column.is_literal`. Additionally, full SQL statements are best handled using the :func:`_expression.text` construct. :func:`_expression.column` can be used in a table-like fashion by combining it with the :func:`.table` function (which is the lightweight analogue to :class:`_schema.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 :func:`_expression.column` / :func:`.table` construct like that illustrated above can be created in an ad-hoc fashion and is not associated with any :class:`_schema.MetaData`, DDL, or events, unlike its :class:`_schema.Table` counterpart. :param text: the text of the element. :param type: :class:`_types.TypeEngine` object which can associate this :class:`.ColumnClause` with a type. :param is_literal: if True, the :class:`.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 :func:`_expression.literal_column()` function essentially invokes :func:`_expression.column` while passing ``is_literal=True``. .. seealso:: :class:`_schema.Column` :func:`_expression.literal_column` :func:`.table` :func:`_expression.text` :ref:`tutorial_select_arbitrary_text` r )rq rZ rr rs rB rB rC rK � s ]rK c C s t �| �S )a 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 :func:`.desc` function is a standalone version of the :meth:`_expression.ColumnElement.desc` method available on all SQL expressions, e.g.:: stmt = select(users_table).order_by(users_table.c.name.desc()) :param column: A :class:`_expression.ColumnElement` (e.g. scalar SQL expression) with which to apply the :func:`.desc` operation. .. seealso:: :func:`.asc` :func:`.nulls_first` :func:`.nulls_last` :meth:`_expression.Select.order_by` )r0 Z _create_descrL rB rB rC �desc s &rt c C s t �| �S )a Produce an column-expression-level unary ``DISTINCT`` clause. This applies the ``DISTINCT`` keyword to an **individual column expression** (e.g. not the whole statement), and renders **specifically in that column position**; this is used for containment within an aggregate function, as in:: from sqlalchemy import distinct, func stmt = select(users_table.c.id, func.count(distinct(users_table.c.name))) The above would produce an statement resembling:: SELECT user.id, count(DISTINCT user.name) FROM user .. tip:: The :func:`_sql.distinct` function does **not** apply DISTINCT to the full SELECT statement, instead applying a DISTINCT modifier to **individual column expressions**. For general ``SELECT DISTINCT`` support, use the :meth:`_sql.Select.distinct` method on :class:`_sql.Select`. The :func:`.distinct` function is also available as a column-level method, e.g. :meth:`_expression.ColumnElement.distinct`, as in:: stmt = select(func.count(users_table.c.name.distinct())) The :func:`.distinct` operator is different from the :meth:`_expression.Select.distinct` method of :class:`_expression.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. .. seealso:: :meth:`_expression.ColumnElement.distinct` :meth:`_expression.Select.distinct` :data:`.func` )r0 Z_create_distinctrA rB rB rC �distinctB s +ru c C s t �| �S )z�Produce a unary bitwise NOT clause, typically via the ``~`` operator. Not to be confused with boolean negation :func:`_sql.not_`. .. versionadded:: 2.0.2 .. seealso:: :ref:`operators_bitwise` )r0 Z_create_bitwise_notrA rB rB rC � bitwise_notp s rv z _ColumnExpressionArgument[Any]r )�fieldr? r@ c C s t | |�S )ac Return a :class:`.Extract` construct. This is typically available as :func:`.extract` as well as ``func.extract`` from the :data:`.func` namespace. :param field: The field to extract. :param expr: A column or Python scalar expression serving as the right side of the ``EXTRACT`` expression. E.g.:: from sqlalchemy import extract from sqlalchemy import table, column logged_table = table("user", column("id"), column("date_created"), ) stmt = select(logged_table.c.id).where( extract("YEAR", logged_table.c.date_created) == 2021 ) In the above example, the statement is used to select ids from the database where the ``YEAR`` component matches a specific value. Similarly, one can also select an extracted component:: stmt = select( extract("YEAR", logged_table.c.date_created) ).where(logged_table.c.id == 1) The implementation of ``EXTRACT`` may vary across database backends. Users are reminded to consult their database documentation. r )rw r? rB rB rC �extract� s &rx r! )r@ c C s t �� S )a� Return a :class:`.False_` construct. E.g.: .. sourcecode:: pycon+sql >>> from sqlalchemy import false >>> print(select(t.c.x).where(false())) {printsql}SELECT x FROM t WHERE false A backend which does not support true/false constants will render as an expression against 1 or 0: .. sourcecode:: pycon+sql >>> print(select(t.c.x).where(false())) {printsql}SELECT x FROM t WHERE 0 = 1 The :func:`.true` and :func:`.false` constants also feature "short circuit" operation within an :func:`.and_` or :func:`.or_` conjunction: .. sourcecode:: pycon+sql >>> print(select(t.c.x).where(or_(t.c.x > 5, true()))) {printsql}SELECT x FROM t WHERE true{stop} >>> print(select(t.c.x).where(and_(t.c.x > 5, false()))) {printsql}SELECT x FROM t WHERE false{stop} .. seealso:: :func:`.true` )r! � _instancerB rB rB rC �false� s %rz zFunctionElement[_T]zFunctionFilter[_T])�func� criterionr@ c G s t | f|�� S )a� Produce a :class:`.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 :data:`~.expression.func` construct itself via the :meth:`.FunctionElement.filter` method. .. seealso:: :ref:`tutorial_functions_within_group` - in the :ref:`unified_tutorial` :meth:`.FunctionElement.filter` r" )r{ r| rB rB rC � funcfilter� s r} z Label[_T])�name�elementrZ r@ c C s t | ||�S )a� Return a :class:`Label` object for the given :class:`_expression.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 :meth:`_expression.ColumnElement.label` method on :class:`_expression.ColumnElement`. :param name: label name :param obj: a :class:`_expression.ColumnElement`. r$ )r~ r rZ rB rB rC �label� s r� r& c C s t �� S )z+Return a constant :class:`.Null` construct.)r& ry rB rB rB rC �null s r� c C s t �| �S )a� Produce the ``NULLS FIRST`` modifier for an ``ORDER BY`` expression. :func:`.nulls_first` is intended to modify the expression produced by :func:`.asc` or :func:`.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 :func:`.asc` and :func:`.desc`, :func:`.nulls_first` is typically invoked from the column expression itself using :meth:`_expression.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()) .. versionchanged:: 1.4 :func:`.nulls_first` is renamed from :func:`.nullsfirst` in previous releases. The previous name remains available for backwards compatibility. .. seealso:: :func:`.asc` :func:`.desc` :func:`.nulls_last` :meth:`_expression.Select.order_by` )r0 Z_create_nulls_firstrL rB rB rC � nulls_first s )r� c C s t �| �S )a� Produce the ``NULLS LAST`` modifier for an ``ORDER BY`` expression. :func:`.nulls_last` is intended to modify the expression produced by :func:`.asc` or :func:`.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 :func:`.asc` and :func:`.desc`, :func:`.nulls_last` is typically invoked from the column expression itself using :meth:`_expression.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()) .. versionchanged:: 1.4 :func:`.nulls_last` is renamed from :func:`.nullslast` in previous releases. The previous name remains available for backwards compatibility. .. seealso:: :func:`.asc` :func:`.desc` :func:`.nulls_first` :meth:`_expression.Select.order_by` )r0 Z_create_nulls_lastrL rB rB rC � nulls_last8 s )r� z6Union[Literal[False], _ColumnExpressionArgument[bool]]c G s dS )a/ 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 :func:`.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 :func:`.or_` construct must be given at least one positional argument in order to be valid; a :func:`.or_` construct with no arguments is ambiguous. To produce an "empty" or dynamically generated :func:`.or_` expression, from a given list of expressions, a "default" element of :func:`_sql.false` (or just ``False``) should be specified:: from sqlalchemy import false 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 :func:`_sql.false` value is ignored as it does not affect the outcome of an OR expression which has other elements. .. deprecated:: 1.4 The :func:`.or_` element now requires that at least one argument is passed; creating the :func:`.or_` construct with no arguments is deprecated, and will emit a deprecation warning while continuing to produce a blank SQL string. .. seealso:: :func:`.and_` NrB rG rB rB rC �or_d s 5r� c G s t j| � S )a� 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 :func:`.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 :func:`.or_` construct must be given at least one positional argument in order to be valid; a :func:`.or_` construct with no arguments is ambiguous. To produce an "empty" or dynamically generated :func:`.or_` expression, from a given list of expressions, a "default" element of :func:`_sql.false` (or just ``False``) should be specified:: from sqlalchemy import false 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 :func:`_sql.false` value is ignored as it does not affect the outcome of an OR expression which has other elements. .. deprecated:: 1.4 The :func:`.or_` element now requires that at least one argument is passed; creating the :func:`.or_` construct with no arguments is deprecated, and will emit a deprecation warning while continuing to produce a blank SQL string. .. seealso:: :func:`.and_` )r r� rI rB rB rC r� � s 2zOptional[_ByArgument]z4Optional[typing_Tuple[Optional[int], Optional[int]]]zOver[_T])r � partition_by�order_by�range_�rowsr@ c C s t | ||||�S )aO Produce an :class:`.Over` object against a function. Used against aggregate or so-called "window" functions, for database backends that support window functions. :func:`_expression.over` is usually called using the :meth:`.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 :paramref:`.expression.over.range_` and :paramref:`.expression.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)) :param element: a :class:`.FunctionElement`, :class:`.WithinGroup`, or other compatible construct. :param 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. :param 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. :param 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. :param 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. This function is also available from the :data:`~.expression.func` construct itself via the :meth:`.FunctionElement.over` method. .. seealso:: :ref:`tutorial_window_functions` - in the :ref:`unified_tutorial` :data:`.expression.func` :func:`_expression.within_group` r' )r r� r� r� r� rB rB rC �over� s Rr� rq z :func:`.text`z:paramref:`.text.text`r* )rq r@ c C s t | �S )a� Construct a new :class:`_expression.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 :func:`_expression.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(r"SELECT * FROM users WHERE name='\:username'") The :class:`_expression.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 :meth:`_expression.TextClause.bindparams` method is used to provide bound parameter detail, and :meth:`_expression.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 :func:`_expression.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}) :func:`_expression.text` is also used for the construction of a full, standalone statement using plain text. As such, SQLAlchemy refers to it as an :class:`.Executable` object and may be used like any other statement passed to an ``.execute()`` method. :param 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. .. seealso:: :ref:`tutorial_select_arbitrary_text` r) )rq rB rB rC rq ( s Kr+ c C s t �� S )a� Return a constant :class:`.True_` construct. E.g.: .. sourcecode:: pycon+sql >>> from sqlalchemy import true >>> print(select(t.c.x).where(true())) {printsql}SELECT x FROM t WHERE true A backend which does not support true/false constants will render as an expression against 1 or 0: .. sourcecode:: pycon+sql >>> print(select(t.c.x).where(true())) {printsql}SELECT x FROM t WHERE 1 = 1 The :func:`.true` and :func:`.false` constants also feature "short circuit" operation within an :func:`.and_` or :func:`.or_` conjunction: .. sourcecode:: pycon+sql >>> print(select(t.c.x).where(or_(t.c.x > 5, true()))) {printsql}SELECT x FROM t WHERE true{stop} >>> print(select(t.c.x).where(and_(t.c.x > 5, false()))) {printsql}SELECT x FROM t WHERE false{stop} .. seealso:: :func:`.false` )r+ ry rB rB rB rC �truev s %r� )�typesz,Optional[Sequence[_TypeEngineArgument[Any]]]r )rF r� r@ c G s t |d| i�S )a| Return a :class:`.Tuple`. Main usage is to produce a composite IN construct using :meth:`.ColumnOperators.in_` :: from sqlalchemy import tuple_ tuple_(table.c.col1, table.c.col2).in_( [(1, 2), (5, 12), (10, 19)] ) .. versionchanged:: 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 :class:`~sqlalchemy.exc.DBAPIError` when such an expression is invoked. r� r )r� rF rB rB rC �tuple_� s r� zTypeCoerce[_T]c C s t | |�S )ag 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 :class:`.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: .. sourcecode:: sql 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 :func:`.type_coerce` construct does not render any SQL syntax of its own, including that it does not imply parenthesization. Please use :meth:`.TypeCoerce.self_group` if explicit parenthesization is required. In order to provide a named label for the expression, use :meth:`_expression.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 :func:`.bindparam` constructs are passed to :func:`.type_coerce` as targets. For example, if a type implements the :meth:`.TypeEngine.bind_expression` method or :meth:`.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 :func:`.type_coerce` with composed expressions, note that **parenthesis are not applied**. If :func:`.type_coerce` is being used in an operator context where the parenthesis normally present from CAST are necessary, use the :meth:`.TypeCoerce.self_group` method: .. sourcecode:: pycon+sql >>> some_integer = column("someint", Integer) >>> some_string = column("somestr", String) >>> expr = type_coerce(some_integer + 5, String) + some_string >>> print(expr) {printsql}someint + :someint_1 || somestr{stop} >>> expr = type_coerce(some_integer + 5, String).self_group() + some_string >>> print(expr) {printsql}(someint + :someint_1) || somestr{stop} :param expression: A SQL expression, such as a :class:`_expression.ColumnElement` expression or a Python string which will be coerced into a bound literal value. :param type\_: A :class:`.TypeEngine` class or instance indicating the type to which the expression is coerced. .. seealso:: :ref:`tutorial_casts` :func:`.cast` r. rn rB rB rC � type_coerce� s Rr� zWithinGroup[_T])r r� r@ c G s t | f|�� S )a� Produce a :class:`.WithinGroup` object against a function. Used against so-called "ordered set aggregate" and "hypothetical set aggregate" functions, including :class:`.percentile_cont`, :class:`.rank`, :class:`.dense_rank`, etc. :func:`_expression.within_group` is usually called using the :meth:`.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)``. :param element: a :class:`.FunctionElement` construct, typically generated by :data:`~.expression.func`. :param \*order_by: one or more column elements that will be used as the ORDER BY clause of the WITHIN GROUP construct. .. seealso:: :ref:`tutorial_functions_within_group` - in the :ref:`unified_tutorial` :data:`.expression.func` :func:`_expression.over` r1 )r r� rB rB rC � within_group s 'r� )F)N)NFN)N)NNNN)X� __future__r �typingr r r r r r r Z typing_Tupler r r � r r �baser r �elementsr r r r r r r r r r! r# r% r& r( r* r+ r- r/ r0 r2 Z functionsr3 Z util.typingr5 Z_typingr6 r7 r8 r9 r: r; Z selectabler< Ztype_apir= r> rD rH rJ rM rQ rX r] ra ZNO_ARGri rm ro rp rK rt ru rv rx rz r} r� r� r� r� r� r� rq r� r� r� r� rB rB rB rC �<module> s� 6B?6( �< ��$ � 9- �`).)( �,,87 �U M*� U