
    +hu7                     ~   d dl Z ddlmZ ddlmZ ddlmZ ddlmZ ddlmZ ddlm	Z	 ej                  fd	Zej                  fd
Z G d dej                  ej                        Z ej                   ddd      Z ej                   ddd      Z ej                   ddd      Z G d dej(                        Zd Zy)    N   )types)util)	coercions)
expression)	operators)rolesc                 &    |j                  | |      S )zjA synonym for the ARRAY-level :meth:`.ARRAY.Comparator.any` method.
    See that method for details.

    )anyotherarrexproperators      W/var/www/html/venv/lib/python3.12/site-packages/sqlalchemy/dialects/postgresql/array.pyAnyr           ;;uh''    c                 &    |j                  | |      S )zjA synonym for the ARRAY-level :meth:`.ARRAY.Comparator.all` method.
    See that method for details.

    )allr   s      r   Allr      r   r   c                   N     e Zd ZdZd ZdZdZ fdZed        Z	ddZ
d	dZ xZS )
arraya  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::

        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                    |D cg c]&  }t        j                  t        j                  |      ( }}t	        t
        |   |i | |D cg c]  }|j                   c}| _        |j                  d| j                  r| j                  d   nt        j                        }t        |t              r8t        |j                  |j                  |j                  dz   nd      | _        y t        |      | _        y c c}w c c}w )Ntype_r         )
dimensions)r   expectr	   ExpressionElementRolesuperr   __init__type_type_tuplepopsqltypesNULLTYPE
isinstanceARRAY	item_typer   )selfclauseskwcarg	main_type	__class__s         r   r"   zarray.__init__\   s    FM
ABIU88!<
 
 	eT#W33078CHH8FF#'#3#3DQ9J9J
	
 i'##''3 %//!3	DI i(DI)
 9s   +C9
C>c                     | fS N r+   s    r   _select_iterablezarray._select_iterables   s	    wr   c                     |s|t         j                  u r%t        j                  d |||| j                  d      S t        |D cg c]  }| j                  ||d|       c}      S c c}w )NT)_compared_to_operatorr   _compared_to_typeunique)_assume_scalarr   )r   getitemr   BindParameterr#   r   _bind_param)r+   r   objr;   r   os         r   r>   zarray._bind_paramw   s    X):)::++&."&))  
 !	  $$ !D %  s   A&c                     |t         j                  t         j                  t         j                  fv rt	        j
                  |       S | S r3   )r   any_opall_opr<   r   Grouping)r+   againsts     r   
self_groupzarray.self_group   s9    y'')9)99;L;LMM&&t,,Kr   )FNr3   )__name__
__module____qualname____doc____visit_name__stringify_dialectinherit_cacher"   propertyr6   r>   rF   __classcell__)r1   s   @r   r   r   $   s>    /b N$M).  *r   r   z@>   T)
precedenceis_comparisonz<@z&&c                       e Zd ZdZ G d dej
                  j                        ZeZ	 ddZe	d        Z
e	d        Zd Zd	 Zej                  d
        Zd Zd Zd Zy)r)   a
  PostgreSQL ARRAY type.

    .. versionchanged:: 1.1 The :class:`_postgresql.ARRAY` type is now
       a subclass of the core :class:`_types.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])

    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`.

    .. 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.

    c                   "    e Zd ZdZd Zd Zd Zy)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`.

        c                 N    | j                  t        |t        j                        S )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)operateCONTAINSr&   Boolean)r+   r   kwargss      r   containszARRAY.Comparator.contains   s     <<%X=M=M<NNr   c                 N    | j                  t        |t        j                        S )zBoolean expression.  Test if elements are a proper subset of the
            elements of the argument array expression.
            rW   )rY   CONTAINED_BYr&   r[   r+   r   s     r   contained_byzARRAY.Comparator.contained_by   s'     <<e1A1A    r   c                 N    | j                  t        |t        j                        S )zuBoolean expression.  Test if array has elements in common with
            an argument array expression.
            rW   )rY   OVERLAPr&   r[   r`   s     r   overlapzARRAY.Comparator.overlap   s     <<H<L<L<MMr   N)rG   rH   rI   rJ   r]   ra   rd   r4   r   r   
ComparatorrU      s    		O		Nr   re   Nc                     t        |t              rt        d      t        |t              r |       }|| _        || _        || _        || _        y)aP  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.

         .. versionadded:: 0.9.5


        zUDo not nest ARRAY types; ARRAY(basetype) handles multi-dimensional arrays of basetypeN)r(   r)   
ValueErrorr#   r*   as_tupler   zero_indexes)r+   r*   rh   r   ri   s        r   r"   zARRAY.__init__  sQ    L i'?  i&!I" $(r   c                     | j                   S r3   )rh   r5   s    r   hashablezARRAY.hashable8  s    }}r   c                     t         S r3   )listr5   s    r   python_typezARRAY.python_type<  s    r   c                     ||k(  S r3   r4   )r+   xys      r   compare_valueszARRAY.compare_values@  s    Avr   c                      t        |      }dk(  s6|rt        |d   t         t        f      sr fd|D              S  |      S   fd|D              S )Nr   r   c              3   .   K   | ]  } |        y wr3   r4   ).0rp   itemprocs     r   	<genexpr>z$ARRAY._proc_array.<locals>.<genexpr>R  s     !;!(1+!;s   c              3   T   K   | ]  }j                  |dz
  nd        ! y wNr   )_proc_array)ru   rp   
collectiondimrv   r+   s     r   rw   z$ARRAY._proc_array.<locals>.<genexpr>V  s<          "C!GD	s   %()rm   r(   tuple)r+   arrrv   r|   r{   s   ` ```r   rz   zARRAY._proc_arrayC  sp    ;s)C1H{
 !#a&4-8 !!;s!;;;!#&    r   c                 z    t        | j                  t        j                        xr | j                  j                  S r3   )r(   r*   r&   Enumnative_enumr5   s    r   _against_native_enumzARRAY._against_native_enum`  s-     t~~x}}5 +**	
r   c                     |S r3   r4   )r+   	bindvalues     r   bind_expressionzARRAY.bind_expressiong  s    r   c                 j      j                   j                  |      j                  |       fd}|S )Nc                 P    | | S j                  | j                  t              S r3   )rz   r   rm   value	item_procr+   s    r   processz%ARRAY.bind_processor.<locals>.processo  s-    }''9doot r   )r*   dialect_implbind_processor)r+   dialectr   r   s   `  @r   r   zARRAY.bind_processorj  s1    NN//8GG
		 r   c                       j                   j                  |      j                  ||       fd} j                  r"|t	        j
                  d      fdfd}|S )Nc                 |    | | S j                  | j                  j                  r
t              S t              S r3   )rz   r   rh   r}   rm   r   s    r   r   z'ARRAY.result_processor.<locals>.process~  sE    }''OO!]]E	  15	 r   z^{(.*)}$c                 Z    j                  |       j                  d      }t        |      S ry   )matchgroup_split_enum_values)r   innerpatterns     r   handle_raw_stringz1ARRAY.result_processor.<locals>.handle_raw_string  s'    e,2215)%00r   c                 h    | | S  t        | t        j                        r |             S |       S r3   )r(   r   string_types)r   r   super_rps    r   r   z'ARRAY.result_processor.<locals>.process  sE    = L  !%):):; &e,   r   )r*   r   result_processorr   recompile)r+   r   coltyper   r   r   r   r   s   `   @@@@r   r   zARRAY.result_processory  s[    NN//8IIW
			 $$Hjj-G1
 r   )FNF)rG   rH   rI   rJ   r&   r)   re   comparator_factoryr"   rN   rk   rn   rr   rz   r   memoized_propertyr   r   r   r   r4   r   r   r)   r)      s    DL NX^^..  ND $ HM0)d    : 

 
$r   r)   c                 f   d| vr| r| j                  d      S g S | j                  dd      }|j                  dd      }g }t        j                   d|      }d}|D ]T  }|dk(  r| }|r"|j                  |j                  dd             0|j	                  t        j
                  d	|             V |S )
N",z\"z_$ESC_QUOTE$_z\\\z(")Fz([^\s,]+),?)splitreplacer   appendextendfindall)array_stringtextresult	on_quotes	in_quotestoks         r   r   r     s    
,*6|!!#&>B> 7D<<t$DF&II ;#:%IMM#++os;<MM"**^S9:; Mr   )r    r   r&   r   sqlr   r   r   r	   eqr   r   
ClauseListColumnElementr   	custom_oprZ   r_   rc   r)   r   r4   r   r   <module>r      s    
 !      "+ ( "+ (lJ!!:#;#; l^ 9tF"y""4ATJ
)

dq
ECHNN CLr   