Wi5>ddlmZddlZddlmZddlmZddlmZddlmZddlm Z dd lm Z d d l m Z d d l mZd d lmZd dlmZd dlmZedeZejfdZejfdZGddejeZGdde jZdZdS)) annotationsN)Any)Optional)TypeVar) CONTAINED_BY)CONTAINS)OVERLAP)types)util) expression) operators)_TypeEngineArgument_T)boundc.|||S)zjA synonym for the ARRAY-level :meth:`.ARRAY.Comparator.any` method. See that method for details. )anyotherarrexproperators n/var/www/html/jarvis.com/web/backend/venv/lib/python3.11/site-packages/sqlalchemy/dialects/postgresql/array.pyrr ;;uh ' ''c.|||S)zjA synonym for the ARRAY-level :meth:`.ARRAY.Comparator.all` method. See that method for details. )allrs rAllr'rrcTeZdZdZdZdZdZfdZedZ d dZ d d Z xZ S) 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:: 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 ``type_`` keyword argument is passed:: array(['foo', 'bar'], type_=CHAR) 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:: 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` postgresqlTc |dd}tjtjg|Ri|d|jD|_||n|jr |jdn tj}t|tr.t|j |j |j dznd|_ dSt||_ dS)Ntype_cg|] }|j S)type).0args r z"array.__init__..ks===CH===rrr) dimensions)popsuper__init__rcomma_opclauses _type_tuplesqltypesNULLTYPE isinstanceARRAY item_typer+r&)selfr0kwtype_arg main_type __class__s rr.zarray.__init__gs66'4((+O  i ' ' )#!+7(1,, DIIIi((DIIIrc|fSNr%r7s r_select_iterablezarray._select_iterables wrFNc|stjurtjd|jdSt fd|DS)NT)_compared_to_operatorr#_compared_to_typeuniquecBg|]}|dS)T)_assume_scalarr#) _bind_param)r'orr7r#s rr)z%array._bind_param..sI$$ !D%r)rgetitemr BindParameterr&r )r7robjrEr#s`` `rrFzarray._bind_params  X):::+&."&)  !  rcx|tjtjtjfvrt j|S|Sr=)rany_opall_oprHrGrouping)r7againsts r self_groupzarray.self_groups3 y')99;LM M M&t,, ,Kr)FNr=) __name__ __module__ __qualname____doc____visit_name__stringify_dialect inherit_cacher.propertyr?rFrP __classcell__)r;s@rr r 0s//bN$M)))))0X*rr ceZdZdZ ddd ZGd d ejjZeZe dZ e dZ dZ e jdZdZdZdZdS)r5a[ 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. FNr6_TypeEngineArgument[Any]as_tupleboolr+ 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)r4r5 ValueErrorr&r6r\r+r_)r7r6r\r+r_s rr.zARRAY.__init__spN i ' ' ?  i & & $! I"  $(rc$eZdZdZdZdZdZdS)ARRAY.Comparatora*Define comparison operations for :class:`_types.ARRAY`. 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