ihr0r1ceZdZUdZdZdZdejfdejfgZ de d<dddfdZ e d dZ d!d"dZ d#d$dZxZS)%arrayaA 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_ Iterable[_T]r;!Optional[_TypeEngineArgument[_T]]kwr&c Vtjtjg|Ri|||n$|jr|jdjn t j}t|tr.t|j |j |j dznd|_dSt||_dS)aConstruct 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_opr8r9sqltypesNULLTYPE isinstanceARRAY item_typerA)selfr8r;r> main_type __class__s r/rCzarray.__init__s +z%array._bind_param..sI$$ !D%r1)rgetitemrrr9r6)rJr)rRr;rTs`` ` r/r\zarray._bind_params  X):::+&."&)  !  r1againstOptional[OperatorType]Union[Self, Grouping[_T]]cx|tjtjtjfvrt j|S|SrN)rany_opall_opr`rr)rJras r/ self_groupzarray.self_groups5 y')99;LM M M&t,, ,Kr1)r8r<r;r=r>r&)r*r)NF) r)rrRr&r;rSrTrUr*rVrN)rarbr*rc)__name__ __module__ __qualname____doc____visit_name__stringify_dialectrdp_clauseelement_tupledp_typer:__annotations__rCpropertyrQr\rg __classcell__)rLs@r/r6r6KsKKZN$ %<= "*+348 !)!)!)!)!)!)!)!)FX+/$ 815r1r6ceZdZdZ ddd ZGd d ejjeZeZ e j ddZ ddZ ddZddZdS) rHan 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. FNrI_TypeEngineArgument[_T]as_tuplerUrA Optional[int] zero_indexesct|trtdt|tr |}||_||_||_||_dS)a-Construct 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)rGrH ValueErrorr9rIrurArw)rJrIrurArws r/rCzARRAY.__init__5spN i ' ' ?  i & & $! I"  $(r1c*eZdZdZd dZd dZd d Zd S) ARRAY.Comparatora*Define comparison operations for :class:`_types.ARRAY`. Note that these operations are in addition to those provided by the base :class:`.types.ARRAY.Comparator` class, including :meth:`.types.ARRAY.Comparator.any` and :meth:`.types.ARRAY.Comparator.all`. r%r&kwargsr*r+c P|t|tjS)zBoolean expression. Test if elements are a superset of the elements of the argument array expression. kwargs may be ignored by this operator but are required for API conformance.  result_type)operater rEBoolean)rJr%r|s r/containszARRAY.Comparator.containsrs<<%X=M<NN Nr1cP|t|tjS)zBoolean expression. Test if elements are a proper subset of the elements of the argument array expression. r~)rr rErrJr%s r/ contained_byzARRAY.Comparator.contained_by}s)<<e1A  r1cP|t|tjS)zuBoolean expression. 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