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           if an explicit value is not otherwise supplied.

           .. versionchanged:: 1.4.12 :class:`_types.Enum` inherits the
              :paramref:`_schema.MetaData.schema` parameter of the
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    value is stored as a date which is relative to the "epoch"
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    Note that the ``Interval`` type does not currently provide date arithmetic
    operations on platforms which do not support interval types natively. Such
    operations usually require transformation of both sides of the expression
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       * PostgreSQL - see :class:`sqlalchemy.dialects.postgresql.JSON` and
         :class:`sqlalchemy.dialects.postgresql.JSONB` for backend-specific
         notes

       * MySQL - see
         :class:`sqlalchemy.dialects.mysql.JSON` for backend-specific notes

       * SQLite as of version 3.9 - see
         :class:`sqlalchemy.dialects.sqlite.JSON` for backend-specific notes

       * Microsoft SQL Server 2016 and later - see
         :class:`sqlalchemy.dialects.mssql.JSON` for backend-specific notes

    :class:`_types.JSON` is part of the Core in support of the growing
    popularity of native JSON datatypes.

    The :class:`_types.JSON` type stores arbitrary JSON format data, e.g.::

        data_table = Table('data_table', metadata,
            Column('id', Integer, primary_key=True),
            Column('data', JSON)
        )

        with engine.connect() as conn:
            conn.execute(
                data_table.insert(),
                {"data": {"key1": "value1", "key2": "value2"}}
            )

    **JSON-Specific Expression Operators**

    The :class:`_types.JSON`
    datatype provides these additional SQL operations:

    * Keyed index operations::

        data_table.c.data['some key']

    * Integer index operations::

        data_table.c.data[3]

    * Path index operations::

        data_table.c.data[('key_1', 'key_2', 5, ..., 'key_n')]

    * Data casters for specific JSON element types, subsequent to an index
      or path operation being invoked::

        data_table.c.data["some key"].as_integer()

      .. versionadded:: 1.3.11

    Additional operations may be available from the dialect-specific versions
    of :class:`_types.JSON`, such as
    :class:`sqlalchemy.dialects.postgresql.JSON` and
    :class:`sqlalchemy.dialects.postgresql.JSONB` which both offer additional
    PostgreSQL-specific operations.

    **Casting JSON Elements to Other Types**

    Index operations, i.e. those invoked by calling upon the expression using
    the Python bracket operator as in ``some_column['some key']``, return an
    expression object whose type defaults to :class:`_types.JSON` by default,
    so that
    further JSON-oriented instructions may be called upon the result type.
    However, it is likely more common that an index operation is expected
    to return a specific scalar element, such as a string or integer.  In
    order to provide access to these elements in a backend-agnostic way,
    a series of data casters are provided:

    * :meth:`.JSON.Comparator.as_string` - return the element as a string

    * :meth:`.JSON.Comparator.as_boolean` - return the element as a boolean

    * :meth:`.JSON.Comparator.as_float` - return the element as a float

    * :meth:`.JSON.Comparator.as_integer` - return the element as an integer

    These data casters are implemented by supporting dialects in order to
    assure that comparisons to the above types will work as expected, such as::

        # integer comparison
        data_table.c.data["some_integer_key"].as_integer() == 5

        # boolean comparison
        data_table.c.data["some_boolean"].as_boolean() == True

    .. versionadded:: 1.3.11 Added type-specific casters for the basic JSON
       data element types.

    .. note::

        The data caster functions are new in version 1.3.11, and supersede
        the previous documented approaches of using CAST; for reference,
        this looked like::

           from sqlalchemy import cast, type_coerce
           from sqlalchemy import String, JSON
           cast(
               data_table.c.data['some_key'], String
           ) == type_coerce(55, JSON)

        The above case now works directly as::

            data_table.c.data['some_key'].as_integer() == 5

        For details on the previous comparison approach within the 1.3.x
        series, see the documentation for SQLAlchemy 1.2 or the included HTML
        files in the doc/ directory of the version's distribution.

    **Detecting Changes in JSON columns when using the ORM**

    The :class:`_types.JSON` type, when used with the SQLAlchemy ORM, does not
    detect in-place mutations to the structure.  In order to detect these, the
    :mod:`sqlalchemy.ext.mutable` extension must be used, most typically
    using the :class:`.MutableDict` class.  This extension will
    allow "in-place" changes to the datastructure to produce events which
    will be detected by the unit of work.  See the example at :class:`.HSTORE`
    for a simple example involving a dictionary.

    Alternatively, assigning a JSON structure to an ORM element that
    replaces the old one will always trigger a change event.

    **Support for JSON null vs. SQL NULL**

    When working with NULL values, the :class:`_types.JSON` type recommends the
    use of two specific constants in order to differentiate between a column
    that evaluates to SQL NULL, e.g. no value, vs. the JSON-encoded string of
    ``"null"``. To insert or select against a value that is SQL NULL, use the
    constant :func:`.null`. This symbol may be passed as a parameter value
    specifically when using the :class:`_types.JSON` datatype, which contains
    special logic that interprets this symbol to mean that the column value
    should be SQL NULL as opposed to JSON ``"null"``::

        from sqlalchemy import null
        conn.execute(table.insert(), {"json_value": null()})

    To insert or select against a value that is JSON ``"null"``, use the
    constant :attr:`_types.JSON.NULL`::

        conn.execute(table.insert(), {"json_value": JSON.NULL})

    The :class:`_types.JSON` type supports a flag
    :paramref:`_types.JSON.none_as_null` which when set to True will result
    in the Python constant ``None`` evaluating to the value of SQL
    NULL, and when set to False results in the Python constant
    ``None`` evaluating to the value of JSON ``"null"``.    The Python
    value ``None`` may be used in conjunction with either
    :attr:`_types.JSON.NULL` and :func:`.null` in order to indicate NULL
    values, but care must be taken as to the value of the
    :paramref:`_types.JSON.none_as_null` in these cases.

    **Customizing the JSON Serializer**

    The JSON serializer and deserializer used by :class:`_types.JSON`
    defaults to
    Python's ``json.dumps`` and ``json.loads`` functions; in the case of the
    psycopg2 dialect, psycopg2 may be using its own custom loader function.

    In order to affect the serializer / deserializer, they are currently
    configurable at the :func:`_sa.create_engine` level via the
    :paramref:`_sa.create_engine.json_serializer` and
    :paramref:`_sa.create_engine.json_deserializer` parameters.  For example,
    to turn off ``ensure_ascii``::

        engine = create_engine(
            "sqlite://",
            json_serializer=lambda obj: json.dumps(obj, ensure_ascii=False))

    .. versionchanged:: 1.3.7

        SQLite dialect's ``json_serializer`` and ``json_deserializer``
        parameters renamed from ``_json_serializer`` and
        ``_json_deserializer``.

    .. seealso::

        :class:`sqlalchemy.dialects.postgresql.JSON`

        :class:`sqlalchemy.dialects.postgresql.JSONB`

        :class:`sqlalchemy.dialects.mysql.JSON`

        :class:`sqlalchemy.dialects.sqlite.JSON`

    .. versionadded:: 1.1


    R^
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         value that is specially interpreted by the :class:`_types.JSON` type
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             from sqlalchemy import null
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              :paramref:`_types.JSON.none_as_null` does **not** apply to the
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        )

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    SELECT statements::

        select(mytable.c.data[5], mytable.c.data[2:7])

    as well as UPDATE statements when the :meth:`_expression.Update.values`
    method
    is used::

        mytable.update().values({
            mytable.c.data[5]: 7,
            mytable.c.data[2:7]: [1, 2, 3]
        })

    The :class:`_types.ARRAY` type also provides for the operators
    :meth:`.types.ARRAY.Comparator.any` and
    :meth:`.types.ARRAY.Comparator.all`. The PostgreSQL-specific version of
    :class:`_types.ARRAY` also provides additional operators.

    .. container:: topic

        **Detecting Changes in ARRAY columns when using the ORM**

        The :class:`_sqltypes.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 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.

    .. versionadded:: 1.1.0

    .. seealso::

        :class:`sqlalchemy.dialects.postgresql.ARRAY`

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                :func:`_sql.any_` function is also mirrored at the method level
                via the :meth:`_sql.ColumnOperators.any_` method.

            Usage of array-specific :meth:`_types.ARRAY.Comparator.any`
            is as follows::

                from sqlalchemy.sql import operators

                conn.execute(
                    select(table.c.data).where(
                            table.c.data.any(7, operator=operators.lt)
                        )
                )

            :param other: expression to be compared
            :param operator: an operator object from the
             :mod:`sqlalchemy.sql.operators`
             package, defaults to :func:`.operators.eq`.

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cCsvtj
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                :func:`_sql.any_` function is also mirrored at the method level
                via the :meth:`_sql.ColumnOperators.any_` method.

            Usage of array-specific :meth:`_types.ARRAY.Comparator.all`
            is as follows::

                from sqlalchemy.sql import operators

                conn.execute(
                    select(table.c.data).where(
                            table.c.data.all(7, operator=operators.lt)
                        )
                )

            :param other: expression to be compared
            :param operator: an operator object from the
             :mod:`sqlalchemy.sql.operators`
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