Загрузить файлы в «venv/Lib/site-packages/sqlalchemy/dialects/postgresql»

venv/Lib/site-packages/sqlalchemy/dialects/postgresql/__init__.py

@@ -0,0 +1,166 @@
+# dialects/postgresql/__init__.py
+# Copyright (C) 2005-2026 the SQLAlchemy authors and contributors
+# <see AUTHORS file>
+#
+# This module is part of SQLAlchemy and is released under
+# the MIT License: https://www.opensource.org/licenses/mit-license.php
+# mypy: ignore-errors
+
+from types import ModuleType
+
+from . import array as arraylib  # noqa # keep above base and other dialects
+from . import asyncpg  # noqa
+from . import base
+from . import pg8000  # noqa
+from . import psycopg  # noqa
+from . import psycopg2  # noqa
+from . import psycopg2cffi  # noqa
+from .array import All
+from .array import Any
+from .array import ARRAY
+from .array import array
+from .base import BIGINT
+from .base import BOOLEAN
+from .base import CHAR
+from .base import DATE
+from .base import DOMAIN
+from .base import DOUBLE_PRECISION
+from .base import FLOAT
+from .base import INTEGER
+from .base import NUMERIC
+from .base import REAL
+from .base import SMALLINT
+from .base import TEXT
+from .base import UUID
+from .base import VARCHAR
+from .dml import Insert
+from .dml import insert
+from .ext import aggregate_order_by
+from .ext import array_agg
+from .ext import ExcludeConstraint
+from .ext import phraseto_tsquery
+from .ext import plainto_tsquery
+from .ext import to_tsquery
+from .ext import to_tsvector
+from .ext import ts_headline
+from .ext import websearch_to_tsquery
+from .hstore import HSTORE
+from .hstore import hstore
+from .json import JSON
+from .json import JSONB
+from .json import JSONPATH
+from .named_types import CreateDomainType
+from .named_types import CreateEnumType
+from .named_types import DropDomainType
+from .named_types import DropEnumType
+from .named_types import ENUM
+from .named_types import NamedType
+from .ranges import AbstractMultiRange
+from .ranges import AbstractRange
+from .ranges import AbstractSingleRange
+from .ranges import DATEMULTIRANGE
+from .ranges import DATERANGE
+from .ranges import INT4MULTIRANGE
+from .ranges import INT4RANGE
+from .ranges import INT8MULTIRANGE
+from .ranges import INT8RANGE
+from .ranges import MultiRange
+from .ranges import NUMMULTIRANGE
+from .ranges import NUMRANGE
+from .ranges import Range
+from .ranges import TSMULTIRANGE
+from .ranges import TSRANGE
+from .ranges import TSTZMULTIRANGE
+from .ranges import TSTZRANGE
+from .types import BIT
+from .types import BYTEA
+from .types import CIDR
+from .types import CITEXT
+from .types import INET
+from .types import INTERVAL
+from .types import MACADDR
+from .types import MACADDR8
+from .types import MONEY
+from .types import OID
+from .types import REGCLASS
+from .types import REGCONFIG
+from .types import TIME
+from .types import TIMESTAMP
+from .types import TSQUERY
+from .types import TSVECTOR
+
+# Alias psycopg also as psycopg_async
+psycopg_async = type(
+    "psycopg_async", (ModuleType,), {"dialect": psycopg.dialect_async}
+)
+
+base.dialect = dialect = psycopg2.dialect
+
+
+__all__ = (
+    "INTEGER",
+    "BIGINT",
+    "SMALLINT",
+    "VARCHAR",
+    "CHAR",
+    "TEXT",
+    "NUMERIC",
+    "FLOAT",
+    "REAL",
+    "INET",
+    "CIDR",
+    "CITEXT",
+    "UUID",
+    "BIT",
+    "MACADDR",
+    "MACADDR8",
+    "MONEY",
+    "OID",
+    "REGCLASS",
+    "REGCONFIG",
+    "TSQUERY",
+    "TSVECTOR",
+    "DOUBLE_PRECISION",
+    "TIMESTAMP",
+    "TIME",
+    "DATE",
+    "BYTEA",
+    "BOOLEAN",
+    "INTERVAL",
+    "ARRAY",
+    "ENUM",
+    "DOMAIN",
+    "dialect",
+    "array",
+    "HSTORE",
+    "hstore",
+    "INT4RANGE",
+    "INT8RANGE",
+    "NUMRANGE",
+    "DATERANGE",
+    "INT4MULTIRANGE",
+    "INT8MULTIRANGE",
+    "NUMMULTIRANGE",
+    "DATEMULTIRANGE",
+    "TSVECTOR",
+    "TSRANGE",
+    "TSTZRANGE",
+    "TSMULTIRANGE",
+    "TSTZMULTIRANGE",
+    "JSON",
+    "JSONB",
+    "JSONPATH",
+    "Any",
+    "All",
+    "DropEnumType",
+    "DropDomainType",
+    "CreateDomainType",
+    "NamedType",
+    "CreateEnumType",
+    "ExcludeConstraint",
+    "Range",
+    "aggregate_order_by",
+    "array_agg",
+    "insert",
+    "Insert",
+)

venv/Lib/site-packages/sqlalchemy/dialects/postgresql/_psycopg_common.py

@@ -0,0 +1,225 @@
+# dialects/postgresql/_psycopg_common.py
+# Copyright (C) 2005-2026 the SQLAlchemy authors and contributors
+# <see AUTHORS file>
+#
+# This module is part of SQLAlchemy and is released under
+# the MIT License: https://www.opensource.org/licenses/mit-license.php
+# mypy: ignore-errors
+from __future__ import annotations
+
+import decimal
+
+from .array import ARRAY as PGARRAY
+from .base import _DECIMAL_TYPES
+from .base import _FLOAT_TYPES
+from .base import _INT_TYPES
+from .base import PGDialect
+from .base import PGExecutionContext
+from .hstore import HSTORE
+from .pg_catalog import _SpaceVector
+from .pg_catalog import INT2VECTOR
+from .pg_catalog import OIDVECTOR
+from ... import exc
+from ... import types as sqltypes
+from ... import util
+from ...engine import processors
+
+_server_side_id = util.counter()
+
+
+class _PsycopgNumeric(sqltypes.Numeric):
+    def bind_processor(self, dialect):
+        return None
+
+    def result_processor(self, dialect, coltype):
+        if self.asdecimal:
+            if coltype in _FLOAT_TYPES:
+                return processors.to_decimal_processor_factory(
+                    decimal.Decimal, self._effective_decimal_return_scale
+                )
+            elif coltype in _DECIMAL_TYPES or coltype in _INT_TYPES:
+                # psycopg returns Decimal natively for 1700
+                return None
+            else:
+                raise exc.InvalidRequestError(
+                    "Unknown PG numeric type: %d" % coltype
+                )
+        else:
+            if coltype in _FLOAT_TYPES:
+                # psycopg returns float natively for 701
+                return None
+            elif coltype in _DECIMAL_TYPES or coltype in _INT_TYPES:
+                return processors.to_float
+            else:
+                raise exc.InvalidRequestError(
+                    "Unknown PG numeric type: %d" % coltype
+                )
+
+
+class _PsycopgFloat(_PsycopgNumeric):
+    __visit_name__ = "float"
+
+
+class _PsycopgHStore(HSTORE):
+    def bind_processor(self, dialect):
+        if dialect._has_native_hstore:
+            return None
+        else:
+            return super().bind_processor(dialect)
+
+    def result_processor(self, dialect, coltype):
+        if dialect._has_native_hstore:
+            return None
+        else:
+            return super().result_processor(dialect, coltype)
+
+
+class _PsycopgARRAY(PGARRAY):
+    render_bind_cast = True
+
+
+class _PsycopgINT2VECTOR(_SpaceVector, INT2VECTOR):
+    pass
+
+
+class _PsycopgOIDVECTOR(_SpaceVector, OIDVECTOR):
+    pass
+
+
+class _PGExecutionContext_common_psycopg(PGExecutionContext):
+    def create_server_side_cursor(self):
+        # use server-side cursors:
+        # psycopg
+        # https://www.psycopg.org/psycopg3/docs/advanced/cursors.html#server-side-cursors
+        # psycopg2
+        # https://www.psycopg.org/docs/usage.html#server-side-cursors
+        ident = "c_%s_%s" % (hex(id(self))[2:], hex(_server_side_id())[2:])
+        return self._dbapi_connection.cursor(ident)
+
+
+class _PGDialect_common_psycopg(PGDialect):
+    supports_statement_cache = True
+    supports_server_side_cursors = True
+
+    default_paramstyle = "pyformat"
+
+    _has_native_hstore = True
+
+    colspecs = util.update_copy(
+        PGDialect.colspecs,
+        {
+            sqltypes.Numeric: _PsycopgNumeric,
+            sqltypes.Float: _PsycopgFloat,
+            HSTORE: _PsycopgHStore,
+            sqltypes.ARRAY: _PsycopgARRAY,
+            INT2VECTOR: _PsycopgINT2VECTOR,
+            OIDVECTOR: _PsycopgOIDVECTOR,
+        },
+    )
+
+    def __init__(
+        self,
+        client_encoding=None,
+        use_native_hstore=True,
+        **kwargs,
+    ):
+        PGDialect.__init__(self, **kwargs)
+        if not use_native_hstore:
+            self._has_native_hstore = False
+        self.use_native_hstore = use_native_hstore
+        self.client_encoding = client_encoding
+
+    def create_connect_args(self, url):
+        opts = url.translate_connect_args(username="user", database="dbname")
+
+        multihosts, multiports = self._split_multihost_from_url(url)
+
+        if opts or url.query:
+            if not opts:
+                opts = {}
+            if "port" in opts:
+                opts["port"] = int(opts["port"])
+            opts.update(url.query)
+
+            if multihosts:
+                opts["host"] = ",".join(multihosts)
+                comma_ports = ",".join(str(p) if p else "" for p in multiports)
+                if comma_ports:
+                    opts["port"] = comma_ports
+            return ([], opts)
+        else:
+            # no connection arguments whatsoever; psycopg2.connect()
+            # requires that "dsn" be present as a blank string.
+            return ([""], opts)
+
+    def get_isolation_level_values(self, dbapi_connection):
+        return (
+            "AUTOCOMMIT",
+            "READ COMMITTED",
+            "READ UNCOMMITTED",
+            "REPEATABLE READ",
+            "SERIALIZABLE",
+        )
+
+    def set_deferrable(self, connection, value):
+        connection.deferrable = value
+
+    def get_deferrable(self, connection):
+        return connection.deferrable
+
+    def _do_autocommit(self, connection, value):
+        connection.autocommit = value
+
+    def detect_autocommit_setting(self, dbapi_connection):
+        return bool(dbapi_connection.autocommit)
+
+    def do_ping(self, dbapi_connection):
+        before_autocommit = dbapi_connection.autocommit
+
+        if not before_autocommit:
+            dbapi_connection.autocommit = True
+        cursor = dbapi_connection.cursor()
+        try:
+            cursor.execute(self._dialect_specific_select_one)
+        finally:
+            cursor.close()
+            if not before_autocommit and not dbapi_connection.closed:
+                dbapi_connection.autocommit = before_autocommit
+
+        return True
+
+    def do_begin_twophase(self, connection, xid):
+        connection.connection.tpc_begin(xid)
+
+    def do_prepare_twophase(self, connection, xid):
+        connection.connection.tpc_prepare()
+
+    def _do_twophase(self, dbapi_conn, operation, xid, recover=False):
+        if recover:
+            if not self._twophase_idle_check(dbapi_conn):
+                dbapi_conn.rollback()
+            operation(xid)
+        else:
+            operation()
+
+    def _twophase_idle_check(self, dbapi_conn):
+        raise NotImplementedError
+
+    def do_rollback_twophase(
+        self, connection, xid, is_prepared=True, recover=False
+    ):
+        dbapi_conn = connection.connection.dbapi_connection
+        self._do_twophase(
+            dbapi_conn, dbapi_conn.tpc_rollback, xid, recover=recover
+        )
+
+    def do_commit_twophase(
+        self, connection, xid, is_prepared=True, recover=False
+    ):
+        dbapi_conn = connection.connection.dbapi_connection
+        self._do_twophase(
+            dbapi_conn, dbapi_conn.tpc_commit, xid, recover=recover
+        )
+
+    def do_recover_twophase(self, connection):
+        return [str(row) for row in connection.connection.tpc_recover()]

venv/Lib/site-packages/sqlalchemy/dialects/postgresql/array.py

@@ -0,0 +1,519 @@
+# dialects/postgresql/array.py
+# Copyright (C) 2005-2026 the SQLAlchemy authors and contributors
+# <see AUTHORS file>
+#
+# This module is part of SQLAlchemy and is released under
+# the MIT License: https://www.opensource.org/licenses/mit-license.php
+
+
+from __future__ import annotations
+
+import re
+from typing import Any as typing_Any
+from typing import Iterable
+from typing import Optional
+from typing import Sequence
+from typing import TYPE_CHECKING
+from typing import TypeVar
+from typing import Union
+
+from .operators import CONTAINED_BY
+from .operators import CONTAINS
+from .operators import OVERLAP
+from ... import types as sqltypes
+from ... import util
+from ...sql import expression
+from ...sql import operators
+from ...sql.visitors import InternalTraversal
+
+if TYPE_CHECKING:
+    from ...engine.interfaces import Dialect
+    from ...sql._typing import _ColumnExpressionArgument
+    from ...sql._typing import _TypeEngineArgument
+    from ...sql.elements import ColumnElement
+    from ...sql.elements import Grouping
+    from ...sql.expression import BindParameter
+    from ...sql.operators import OperatorType
+    from ...sql.selectable import _SelectIterable
+    from ...sql.type_api import _BindProcessorType
+    from ...sql.type_api import _LiteralProcessorType
+    from ...sql.type_api import _ResultProcessorType
+    from ...sql.type_api import TypeEngine
+    from ...sql.visitors import _TraverseInternalsType
+    from ...util.typing import Self
+
+
+_T = TypeVar("_T", bound=typing_Any)
+_CT = TypeVar("_CT", bound=typing_Any)
+
+
+def Any(
+    other: typing_Any,
+    arrexpr: _ColumnExpressionArgument[_T],
+    operator: OperatorType = operators.eq,
+) -> ColumnElement[bool]:
+    """A synonym for the ARRAY-level :meth:`.ARRAY.Comparator.any` method.
+    See that method for details.
+
+    """
+
+    return arrexpr.any(other, operator)  # type: ignore[no-any-return, union-attr]  # noqa: E501
+
+
+def All(
+    other: typing_Any,
+    arrexpr: _ColumnExpressionArgument[_T],
+    operator: OperatorType = operators.eq,
+) -> ColumnElement[bool]:
+    """A synonym for the ARRAY-level :meth:`.ARRAY.Comparator.all` method.
+    See that method for details.
+
+    """
+
+    return arrexpr.all(other, operator)  # type: ignore[no-any-return, union-attr]  # noqa: E501
+
+
+class array(expression.ExpressionClauseList[_T]):
+    """A 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`
+
+    """  # noqa: E501
+
+    __visit_name__ = "array"
+
+    stringify_dialect = "postgresql"
+
+    _traverse_internals: _TraverseInternalsType = [
+        ("clauses", InternalTraversal.dp_clauseelement_tuple),
+        ("type", InternalTraversal.dp_type),
+    ]
+
+    def __init__(
+        self,
+        clauses: Iterable[_T],
+        *,
+        type_: Optional[_TypeEngineArgument[_T]] = None,
+        **kw: typing_Any,
+    ):
+        r"""Construct 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.
+
+        """
+        super().__init__(operators.comma_op, *clauses, **kw)
+
+        main_type = (
+            type_
+            if type_ is not None
+            else self.clauses[0].type if self.clauses else sqltypes.NULLTYPE
+        )
+
+        if isinstance(main_type, ARRAY):
+            self.type = ARRAY(
+                main_type.item_type,
+                dimensions=(
+                    main_type.dimensions + 1
+                    if main_type.dimensions is not None
+                    else 2
+                ),
+            )  # type: ignore[assignment]
+        else:
+            self.type = ARRAY(main_type)  # type: ignore[assignment]
+
+    @property
+    def _select_iterable(self) -> _SelectIterable:
+        return (self,)
+
+    def _bind_param(
+        self,
+        operator: OperatorType,
+        obj: typing_Any,
+        type_: Optional[TypeEngine[_T]] = None,
+        _assume_scalar: bool = False,
+    ) -> BindParameter[_T]:
+        if _assume_scalar or operator is operators.getitem:
+            return expression.BindParameter(
+                None,
+                obj,
+                _compared_to_operator=operator,
+                type_=type_,
+                _compared_to_type=self.type,
+                unique=True,
+            )
+
+        else:
+            return array(
+                [
+                    self._bind_param(
+                        operator, o, _assume_scalar=True, type_=type_
+                    )
+                    for o in obj
+                ]
+            )  # type: ignore[return-value]
+
+    def self_group(
+        self, against: Optional[OperatorType] = None
+    ) -> Union[Self, Grouping[_T]]:
+        if against in (operators.any_op, operators.all_op, operators.getitem):
+            return expression.Grouping(self)
+        else:
+            return self
+
+
+class ARRAY(sqltypes.ARRAY[_T]):
+    """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.
+
+    """
+
+    def __init__(
+        self,
+        item_type: _TypeEngineArgument[_T],
+        as_tuple: bool = False,
+        dimensions: Optional[int] = None,
+        zero_indexes: bool = False,
+    ):
+        """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.
+
+        """
+        if isinstance(item_type, ARRAY):
+            raise ValueError(
+                "Do not nest ARRAY types; ARRAY(basetype) "
+                "handles multi-dimensional arrays of basetype"
+            )
+        if isinstance(item_type, type):
+            item_type = item_type()
+        self.item_type = item_type
+        self.as_tuple = as_tuple
+        self.dimensions = dimensions
+        self.zero_indexes = zero_indexes
+
+    class Comparator(sqltypes.ARRAY.Comparator[_CT]):
+        """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`.
+
+        """
+
+        def contains(
+            self, other: typing_Any, **kwargs: typing_Any
+        ) -> ColumnElement[bool]:
+            """Boolean 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.
+            """
+            return self.operate(CONTAINS, other, result_type=sqltypes.Boolean)
+
+        def contained_by(self, other: typing_Any) -> ColumnElement[bool]:
+            """Boolean expression.  Test if elements are a proper subset of the
+            elements of the argument array expression.
+            """
+            return self.operate(
+                CONTAINED_BY, other, result_type=sqltypes.Boolean
+            )
+
+        def overlap(self, other: typing_Any) -> ColumnElement[bool]:
+            """Boolean expression.  Test if array has elements in common with
+            an argument array expression.
+            """
+            return self.operate(OVERLAP, other, result_type=sqltypes.Boolean)
+
+    comparator_factory = Comparator
+
+    @util.memoized_property
+    def _against_native_enum(self) -> bool:
+        return (
+            isinstance(self.item_type, sqltypes.Enum)
+            and self.item_type.native_enum
+        )
+
+    def literal_processor(
+        self, dialect: Dialect
+    ) -> Optional[_LiteralProcessorType[_T]]:
+        item_proc = self.item_type.dialect_impl(dialect).literal_processor(
+            dialect
+        )
+        if item_proc is None:
+            return None
+
+        def to_str(elements: Iterable[typing_Any]) -> str:
+            return f"ARRAY[{', '.join(elements)}]"
+
+        def process(value: Sequence[typing_Any]) -> str:
+            inner = self._apply_item_processor(
+                value, item_proc, self.dimensions, to_str
+            )
+            return inner
+
+        return process
+
+    def bind_processor(
+        self, dialect: Dialect
+    ) -> Optional[_BindProcessorType[Sequence[typing_Any]]]:
+        item_proc = self.item_type.dialect_impl(dialect).bind_processor(
+            dialect
+        )
+
+        def process(
+            value: Optional[Sequence[typing_Any]],
+        ) -> Optional[list[typing_Any]]:
+            if value is None:
+                return value
+            else:
+                return self._apply_item_processor(
+                    value, item_proc, self.dimensions, list
+                )
+
+        return process
+
+    def result_processor(
+        self, dialect: Dialect, coltype: object
+    ) -> _ResultProcessorType[Sequence[typing_Any]]:
+        item_proc = self.item_type.dialect_impl(dialect).result_processor(
+            dialect, coltype
+        )
+
+        def process(
+            value: Sequence[typing_Any],
+        ) -> Optional[Sequence[typing_Any]]:
+            if value is None:
+                return value
+            else:
+                return self._apply_item_processor(
+                    value,
+                    item_proc,
+                    self.dimensions,
+                    tuple if self.as_tuple else list,
+                )
+
+        if self._against_native_enum:
+            super_rp = process
+            pattern = re.compile(r"^{(.*)}$")
+
+            def handle_raw_string(value: str) -> Sequence[Optional[str]]:
+                inner = pattern.match(value).group(1)  # type: ignore[union-attr]  # noqa: E501
+                return _split_enum_values(inner)
+
+            def process(
+                value: Sequence[typing_Any],
+            ) -> Optional[Sequence[typing_Any]]:
+                if value is None:
+                    return value
+                # isinstance(value, str) is required to handle
+                # the case where a TypeDecorator for and Array of Enum is
+                # used like was required in sa < 1.3.17
+                return super_rp(
+                    handle_raw_string(value)
+                    if isinstance(value, str)
+                    else value
+                )
+
+        return process
+
+
+def _split_enum_values(array_string: str) -> Sequence[Optional[str]]:
+    if '"' not in array_string:
+        # no escape char is present so it can just split on the comma
+        return [
+            r if r != "NULL" else None
+            for r in (array_string.split(",") if array_string else [])
+        ]
+
+    # handles quoted strings from:
+    # r'abc,"quoted","also\\\\quoted", "quoted, comma", "esc \" quot", qpr'
+    # returns
+    # ['abc', 'quoted', 'also\\quoted', 'quoted, comma', 'esc " quot', 'qpr']
+    text = array_string.replace(r"\"", "_$ESC_QUOTE$_")
+    text = text.replace(r"\\", "\\")
+    result = []
+    on_quotes = re.split(r'(")', text)
+    in_quotes = False
+    for tok in on_quotes:
+        if tok == '"':
+            in_quotes = not in_quotes
+        elif in_quotes:
+            result.append(tok.replace("_$ESC_QUOTE$_", '"'))
+        else:
+            # interpret NULL (without quotes!) as None
+            result.extend(
+                [
+                    r if r != "NULL" else None
+                    for r in re.findall(r"([^\s,]+),?", tok)
+                ]
+            )
+    return result