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        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:`.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:`.ARRAY` type is calculated by
    recursively adding the dimensions of the inner :class:`.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

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    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])

    The :class:`.postgresql.ARRAY` type may not be supported on all
    PostgreSQL DBAPIs; it is currently known to work on psycopg2 only.

    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`.

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          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.

         .. versionadded:: 0.9.5


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