]jClSSKJr SSKrSSKJr SSKJr SSKJr SSKJr SSKJ r SSKJ r SS KJ r S S K J r S S K Jr S S K Jr SSKJr SSKJr SSKJr SSKJ r SSKJr \ (aTSSKJr SSKJr SSKJr SSKJr SSKJr SSK J!r! SSK"J#r# SSK$J%r% SSK&J'r' SSK&J(r( SSK&J)r) SSK&J*r* SS KJ+r+ SS!K,J-r- \ "S"\S#9r.\ "S$\S#9r/\ R`4S,S%jjr\ R`4S,S&jjr1"S'S(\Rd\.5r3"S)S*\Rh\.5r4S-S+jr5g).) annotationsN)Any)Iterable)Optional)Sequence) TYPE_CHECKING)TypeVar)Union) CONTAINED_BY)CONTAINS)OVERLAP)types)util) expression) operators)InternalTraversal)Dialect)_ColumnExpressionArgument)_TypeEngineArgument) ColumnElement)Grouping) BindParameter) OperatorType)_SelectIterable)_BindProcessorType)_LiteralProcessorType)_ResultProcessorType) TypeEngine)_TraverseInternalsType)Self_T)bound_CTc$URX5$)zbA synonym for the ARRAY-level :meth:`.ARRAY.Comparator.any` method. See that method for details. )anyotherarrexproperators a/home/mande/repo/quber/.venv/lib/python3.13/site-packages/sqlalchemy/dialects/postgresql/array.pyrr2 ;;u ''c$URX5$)zbA synonym for the ARRAY-level :meth:`.ARRAY.Comparator.all` method. See that method for details. )allr(s r,Allr1?r-r.c^\rSrSr%SrSrSrS\R4S\R4/r S\ S'SS .SU4S jjjr \ SS j5rSSS jjrSSS jjrSrU=r$)arrayLaA PostgreSQL ARRAY literal. This is used to produce ARRAY literals in SQL expressions, e.g.:: from sqlalchemy.dialects.postgresql import array from sqlalchemy.dialects import postgresql from sqlalchemy import select, func stmt = select(array([1, 2]) + array([3, 4, 5])) print(stmt.compile(dialect=postgresql.dialect())) Produces the SQL: .. sourcecode:: sql SELECT ARRAY[%(param_1)s, %(param_2)s] || ARRAY[%(param_3)s, %(param_4)s, %(param_5)s]) AS anon_1 An instance of :class:`.array` will always have the datatype :class:`_types.ARRAY`. The "inner" type of the array is inferred from the values present, unless the :paramref:`_postgresql.array.type_` keyword argument is passed:: array(["foo", "bar"], type_=CHAR) When constructing an empty array, the :paramref:`_postgresql.array.type_` argument is particularly important as PostgreSQL server typically requires a cast to be rendered for the inner type in order to render an empty array. SQLAlchemy's compilation for the empty array will produce this cast so that:: stmt = array([], type_=Integer) print(stmt.compile(dialect=postgresql.dialect())) Produces: .. sourcecode:: sql ARRAY[]::INTEGER[] As required by PostgreSQL for empty arrays. .. versionadded:: 2.0.40 added support to render empty PostgreSQL array literals with a required cast. Multidimensional arrays are produced by nesting :class:`.array` constructs. The dimensionality of the final :class:`_types.ARRAY` type is calculated by recursively adding the dimensions of the inner :class:`_types.ARRAY` type:: stmt = select( array( [array([1, 2]), array([3, 4]), array([column("q"), column("x")])] ) ) print(stmt.compile(dialect=postgresql.dialect())) Produces: .. sourcecode:: sql SELECT ARRAY[ ARRAY[%(param_1)s, %(param_2)s], ARRAY[%(param_3)s, %(param_4)s], ARRAY[q, x] ] AS anon_1 .. versionadded:: 1.3.6 added support for multidimensional array literals .. seealso:: :class:`_postgresql.ARRAY` postgresqlclausestyper!_traverse_internalsN)type_c ~>[TU]"[R/UQ70UD6 UbUO9UR(aURSR O[ Rn[U[5(a6[URURbURS-OSS9Ulg[U5Ulg)zConstruct an ARRAY literal. :param clauses: iterable, such as a list, containing elements to be rendered in the array :param type\_: optional type. If omitted, the type is inferred from the contents of the array. Nrr ) dimensions) super__init__rcomma_opr6r7sqltypesNULLTYPE isinstanceARRAY item_typer<)selfr6r9kw main_type __class__s r,r>array.__init__s ++propertyrNrVr^__static_attributes__ __classcell__)rHs@r,r3r3LsKZN$ %<<= "**+3/48 !)!)1 !)  !)!)F+/$ (     815- "r.r3c\rSrSrSrS S Sjjr"SS\RR\ 5r\r \ RSSj5r SSjrSS jrSS jrS rg)rCa PostgreSQL ARRAY type. The :class:`_postgresql.ARRAY` type is constructed in the same way as the core :class:`_types.ARRAY` type; a member type is required, and a number of dimensions is recommended if the type is to be used for more than one dimension:: from sqlalchemy.dialects import postgresql mytable = Table( "mytable", metadata, Column("data", postgresql.ARRAY(Integer, dimensions=2)), ) The :class:`_postgresql.ARRAY` type provides all operations defined on the core :class:`_types.ARRAY` type, including support for "dimensions", indexed access, and simple matching such as :meth:`.types.ARRAY.Comparator.any` and :meth:`.types.ARRAY.Comparator.all`. :class:`_postgresql.ARRAY` class also provides PostgreSQL-specific methods for containment operations, including :meth:`.postgresql.ARRAY.Comparator.contains` :meth:`.postgresql.ARRAY.Comparator.contained_by`, and :meth:`.postgresql.ARRAY.Comparator.overlap`, e.g.:: mytable.c.data.contains([1, 2]) Indexed access is one-based by default, to match that of PostgreSQL; for zero-based indexed access, set :paramref:`_postgresql.ARRAY.zero_indexes`. Additionally, the :class:`_postgresql.ARRAY` type does not work directly in conjunction with the :class:`.ENUM` type. For a workaround, see the special type at :ref:`postgresql_array_of_enum`. .. container:: topic **Detecting Changes in ARRAY columns when using the ORM** The :class:`_postgresql.ARRAY` type, when used with the SQLAlchemy ORM, does not detect in-place mutations to the array. In order to detect these, the :mod:`sqlalchemy.ext.mutable` extension must be used, using the :class:`.MutableList` class:: from sqlalchemy.dialects.postgresql import ARRAY from sqlalchemy.ext.mutable import MutableList class SomeOrmClass(Base): # ... data = Column(MutableList.as_mutable(ARRAY(Integer))) This extension will allow "in-place" changes such to the array such as ``.append()`` to produce events which will be detected by the unit of work. Note that changes to elements **inside** the array, including subarrays that are mutated in place, are **not** detected. Alternatively, assigning a new array value to an ORM element that replaces the old one will always trigger a change event. .. seealso:: :class:`_types.ARRAY` - base array type :class:`_postgresql.array` - produces a literal array value. Nc[U[5(a [S5e[U[5(aU"5nXlX lX0lX@lg)auConstruct an ARRAY. E.g.:: Column("myarray", ARRAY(Integer)) Arguments are: :param item_type: The data type of items of this array. Note that dimensionality is irrelevant here, so multi-dimensional arrays like ``INTEGER[][]``, are constructed as ``ARRAY(Integer)``, not as ``ARRAY(ARRAY(Integer))`` or such. :param as_tuple=False: Specify whether return results should be converted to tuples from lists. DBAPIs such as psycopg2 return lists by default. When tuples are returned, the results are hashable. :param dimensions: if non-None, the ARRAY will assume a fixed number of dimensions. This will cause the DDL emitted for this ARRAY to include the exact number of bracket clauses ``[]``, and will also optimize the performance of the type overall. Note that PG arrays are always implicitly "non-dimensioned", meaning they can store any number of dimensions no matter how they were declared. :param zero_indexes=False: when True, index values will be converted between Python zero-based and PostgreSQL one-based indexes, e.g. a value of one will be added to all index values before passing to the database. zUDo not nest ARRAY types; ARRAY(basetype) handles multi-dimensional arrays of basetypeN)rBrC ValueErrorr7rDas_tupler< zero_indexes)rErDrtr<rus r,r>ARRAY.__init__6sON i ' '?  i & &! I" $(r.cB\rSrSrSrSSjrS SjrS SjrSrg) zARRAY.ComparatoriiaDefine comparison operations for :class:`_types.ARRAY`. 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