3
a/                 @   s   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	d
Zej
fddZG d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 dejZdS )    N   )types)util)	coercions)
expression)	operators)rolesc             C   s   |j | |S )zA synonym for the :meth:`.ARRAY.Comparator.any` method.

    This method is legacy and is here for backwards-compatibility.

    .. seealso::

        :func:`_expression.any_`

    )any)otherarrexproperator r   J/tmp/pip-build-6_cqtusv/SQLAlchemy/sqlalchemy/dialects/postgresql/array.pyAny   s    r   c             C   s   |j | |S )zA synonym for the :meth:`.ARRAY.Comparator.all` method.

    This method is legacy and is here for backwards-compatibility.

    .. seealso::

        :func:`_expression.all_`

    )all)r
   r   r   r   r   r   All    s    r   c                   sH   e Zd ZdZd ZdZ fddZedd Zdd	d
Z	dddZ
  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`

    Z
postgresqlc                s   dd |D }t t| j|| dd |D | _|jd| jrF| jd ntj}t|tr~t|j	|j
d k	rr|j
d ndd| _n
t|| _d S )	Nc             S   s   g | ]}t jtj|qS r   )r   expectr   ZExpressionElementRole).0cr   r   r   
<listcomp>g   s    z"array.__init__.<locals>.<listcomp>c             S   s   g | ]
}|j qS r   )type)r   argr   r   r   r   l   s    type_r         )
dimensions)superr   __init__Z_type_tuplepopsqltypesZNULLTYPE
isinstanceARRAY	item_typer   r   )selfZclauseskwZ	main_type)	__class__r   r   r   e   s    
zarray.__init__c             C   s   | fS )Nr   )r$   r   r   r   _select_iterable|   s    zarray._select_iterableFNc                sD   |s t jkr&tjd | jddS t fdd|D S d S )NT)Z_compared_to_operatorr   Z_compared_to_typeuniquec                s   g | ]}j  |d dqS )T)_assume_scalarr   )_bind_param)r   o)r   r$   r   r   r   r      s   z%array._bind_param.<locals>.<listcomp>)r   getitemr   ZBindParameterr   r   )r$   r   objr)   r   r   )r   r$   r   r   r*      s    zarray._bind_paramc             C   s&   |t jt jt jfkrtj| S | S d S )N)r   Zany_opZall_opr,   r   ZGrouping)r$   Zagainstr   r   r   
self_group   s    
zarray.self_group)FN)N)__name__
__module____qualname____doc__Z__visit_name__Zstringify_dialectr   propertyr'   r*   r.   __classcell__r   r   )r&   r   r   .   s   1
r   z@>   )
precedencez<@z&&c               @   s   e Zd ZdZG dd dejjZeZdddZe	dd	 Z
e	d
d Zdd Zdd Zejdd Zdd Zdd Zdd ZdS )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`.

    .. seealso::

        :class:`_types.ARRAY` - base array type

        :class:`_postgresql.array` - produces a literal array value.

    c               @   s(   e Zd ZdZdd Zdd Zdd ZdS )	z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             K   s   | j t|tjdS )zBoolean expression.  Test if elements are a superset of the
            elements of the argument array expression.
            )result_type)operateCONTAINSr    Boolean)r$   r
   kwargsr   r   r   contains   s    zARRAY.Comparator.containsc             C   s   | j t|tjdS )zBoolean expression.  Test if elements are a proper subset of the
            elements of the argument array expression.
            )r7   )r8   CONTAINED_BYr    r:   )r$   r
   r   r   r   contained_by   s    zARRAY.Comparator.contained_byc             C   s   | j t|tjdS )zuBoolean expression.  Test if array has elements in common with
            an argument array expression.
            )r7   )r8   OVERLAPr    r:   )r$   r
   r   r   r   overlap   s    zARRAY.Comparator.overlapN)r/   r0   r1   r2   r<   r>   r@   r   r   r   r   
Comparator   s   	rA   FNc             C   s>   t |trtdt |tr"| }|| _|| _|| _|| _dS )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$   r#   rC   r   rD   r   r   r   r      s    &

zARRAY.__init__c             C   s   | j S )N)rC   )r$   r   r   r   hashable%  s    zARRAY.hashablec             C   s   t S )N)list)r$   r   r   r   python_type)  s    zARRAY.python_typec             C   s   ||kS )Nr   )r$   xyr   r   r   compare_values-  s    zARRAY.compare_valuesc                s~   d krt |}dks:d kr^| s:t|d t tf r^rT fdd|D S  |S n  fdd|D S d S )Nr   r   c             3   s   | ]} |V  qd S )Nr   )r   rH   )itemprocr   r   	<genexpr>?  s    z$ARRAY._proc_array.<locals>.<genexpr>c             3   s.   | ]&}j |d k	rd nd  V  qd S )Nr   )_proc_array)r   rH   )
collectiondimrK   r$   r   r   rL   D  s   )rF   r!   tuple)r$   ZarrrK   rO   rN   r   )rN   rO   rK   r$   r   rM   0  s    
zARRAY._proc_arrayc             C   s   t | jtjo| jjS )N)r!   r#   r    EnumZnative_enum)r$   r   r   r   _against_native_enumM  s    zARRAY._against_native_enumc             C   s   |S )Nr   )r$   Z	bindvaluer   r   r   bind_expressionT  s    zARRAY.bind_expressionc                s$   j j|j|  fdd}|S )Nc                s"   | d kr| S j |  jtS d S )N)rM   r   rF   )value)	item_procr$   r   r   process\  s    z%ARRAY.bind_processor.<locals>.process)r#   dialect_implbind_processor)r$   dialectrV   r   )rU   r$   r   rX   W  s    zARRAY.bind_processorc                sF   j j|j||fdd}jrB|dd   fdd}|S )Nc                s,   | d kr| S j |  jjr"tntS d S )N)rM   r   rC   rP   rF   )rT   )rU   r$   r   r   rV   k  s    z'ARRAY.result_processor.<locals>.processc             S   s$   t jd| jd}|r |jdS g S )Nz^{(.*)}$r   ,)rematchgroupsplit)rT   innerr   r   r   handle_raw_stringy  s    z1ARRAY.result_processor.<locals>.handle_raw_stringc                s(   | d kr| S t | tjr" | n| S )N)r!   r   string_types)rT   )r`   super_rpr   r   rV   }  s
    )r#   rW   result_processorrR   )r$   rY   ZcoltyperV   r   )r`   rU   r$   rb   r   rc   f  s    zARRAY.result_processor)FNF)r/   r0   r1   r2   r    r"   rA   Zcomparator_factoryr   r3   rE   rG   rJ   rM   r   Zmemoized_propertyrR   rS   rX   rc   r   r   r   r   r"      s   -
1r"   )r[    r   r    r   Zsqlr   r   r   r   eqr   r   Z
ClauseListZColumnElementr   Z	custom_opr9   r=   r?   r"   r   r   r   r   <module>   s   n