B \'@sddlmZddlmZddlmZddlmZddlmZyddl m Z Wne k rdd Z YnXej fd d Zej fd d ZGdddejZejdddZejdddZejdddZGdddejZeeej<eed<d S))colspecs) ischema_names)types) expression) operators)UUIDNcCs |||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)otherarrexproperatorrClib/python3.7/site-packages/sqlalchemy/dialects/postgresql/array.pyAnys rcCs |||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 rrrAll#s rcs8eZdZdZdZfddZd ddZd dd ZZS) arrayabA 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:`.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) .. seealso:: :class:`.postgresql.ARRAY` c s"tt|j||t|j|_dS)N)superr__init__ARRAYtype)selfZclauseskw) __class__rrrTszarray.__init__FNcsR|stjkr4t|tsttjd|jddStfdd|DSdS)NT)Z_compared_to_operatortype_Z_compared_to_typeuniquecsg|]}j|ddqS)T)_assume_scalarr) _bind_param).0o)r rrrr isz%array._bind_param..) rgetitem isinstanceintAssertionErrorrZ BindParameterrr)rr objrrr)r rrrrXszarray._bind_paramcCs&|tjtjtjfkrt|S|SdS)N)rZany_opZall_opr"rZGrouping)rZagainstrrr self_groupps zarray.self_group)FN)N) __name__ __module__ __qualname____doc__Z__visit_name__rrr' __classcell__rr)rrr1s   rz@>)Z precedencez<@z&&c@sjeZdZdZGdddejjZeZdddZe dd Z e d d Z d d Z ddZ ddZddZdS)raPostgreSQL 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(eZdZdZddZddZddZdS) zARRAY.Comparatora$Define comparison operations for :class:`.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`. cKs|jt|tjdS)zBoolean expression. Test if elements are a superset of the elements of the argument array expression. ) result_type)operateCONTAINSsqltypesBoolean)rr kwargsrrrcontainsszARRAY.Comparator.containscCs|jt|tjdS)zBoolean expression. Test if elements are a proper subset of the elements of the argument array expression. )r.)r/ CONTAINED_BYr1r2)rr rrr contained_byszARRAY.Comparator.contained_bycCs|jt|tjdS)zuBoolean expression. Test if array has elements in common with an argument array expression. )r.)r/OVERLAPr1r2)rr rrroverlapszARRAY.Comparator.overlapN)r(r)r*r+r4r6r8rrrr Comparators r9FNcCs>t|trtdt|tr"|}||_||_||_||_dS)aPConstruct 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 item_typeas_tuple dimensions zero_indexes)rr;r<r=r>rrrrs&  zARRAY.__init__cCs|jS)N)r<)rrrrhashableszARRAY.hashablecCstS)N)list)rrrr python_typeszARRAY.python_typecCs||kS)Nr)rxyrrrcompare_valuesszARRAY.compare_valuescszdkrt|}dks6dkrZ|r6t|dttfsZrPfdd|DS|Snfdd|DSdS)Nrrc3s|]}|VqdS)Nr)rrB)itemprocrr sz$ARRAY._proc_array..c3s.|]&}|dk rdndVqdS)Nr) _proc_array)rrB) collectiondimrErrrrFs)r@r#tuple)rZarrrErIrHr)rHrIrErrrG s zARRAY._proc_arraycs$j||fdd}|S)Ncs"|dkr |S|jtSdS)N)rGr=r@)value) item_procrrrprocess+sz%ARRAY.bind_processor..process)r; dialect_implbind_processor)rdialectrMr)rLrrrO&s zARRAY.bind_processorcs&j|||fdd}|S)Ncs,|dkr |S|jjr"tntSdS)N)rGr=r<rJr@)rK)rLrrrrM:sz'ARRAY.result_processor..process)r;rNresult_processor)rrPZcoltyperMr)rLrrrQ5s  zARRAY.result_processor)FNF)r(r)r*r+r1rr9Zcomparator_factoryrpropertyr?rArDrGrOrQrrrrr~s+ 1  rZ_array)baserrrr1ZsqlrrZuuidr Z _python_UUID ImportErroreqrrZTuplerZ custom_opr0r5r7rrrrrs$      FK