a c gr5@sddlmZddlZddlmZddlmZddlmZddlmZddlm Z dd lm Z d d l m Z d d l mZd d lmZd dlmZd dlmZededZejfddZejfddZGdddejeZGddde jZddZdS)) annotationsN)Any)Optional)TypeVar) CONTAINED_BY)CONTAINS)OVERLAP)types)util) expression) operators)_TypeEngineArgument_T)boundcCs |||S)zjA synonym for the ARRAY-level :meth:`.ARRAY.Comparator.any` method. See that method for details. )anyotherZarrexproperatorrg/var/www/html/llm_bihealth/app/venv/lib/python3.9/site-packages/sqlalchemy/dialects/postgresql/array.pyrsrcCs |||S)zjA synonym for the ARRAY-level :meth:`.ARRAY.Comparator.all` method. See that method for details. )allrrrrAll'srcsLeZdZdZdZdZdZfddZeddZ dd d Z dd d Z Z S)arrayaA 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 postgresqlTc s|dd}tjtjg|Ri|dd|jD|_|durF|n|jrV|jdntj}t |t rt |j |j dur|j dndd|_ n t ||_ dS)Ntype_cSsg|] }|jqSr)type).0argrrr lz"array.__init__..rr) dimensions)popsuper__init__rZcomma_opclausesZ _type_tuplesqltypesZNULLTYPE isinstanceARRAY item_typer"r)selfr&kwZtype_argZ main_type __class__rrr%hs"     zarray.__init__cCs|fSNrr+rrr_select_iterableszarray._select_iterableFNcsD|stjur&tjd|jddStfdd|DSdS)NT)Z_compared_to_operatorrZ_compared_to_typeuniquecsg|]}j|ddqS)T)_assume_scalarr) _bind_param)rorr+rrrrsz%array._bind_param..)rgetitemr Z BindParameterrr)r+robjr3rrr6rr4s zarray._bind_paramcCs&|tjtjtjfvrt|S|SdSr/)rZany_opZall_opr7r ZGrouping)r+Zagainstrrr self_groups zarray.self_group)FN)N) __name__ __module__ __qualname____doc__Z__visit_name__Zstringify_dialectZ inherit_cacher%propertyr1r4r9 __classcell__rrr-rr0s1   rc@seZdZdZGdddejjZeZdddddd d d Ze d d Z e ddZ ddZ e jddZddZddZddZdS)r)aF PostgreSQL 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@s(eZdZdZddZddZddZdS) zARRAY.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`. cKs|jt|tjdS)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. Z result_type)operaterr'Boolean)r+rkwargsrrrcontainsszARRAY.Comparator.containscCs|jt|tjdS)zBoolean expression. Test if elements are a proper subset of the elements of the argument array expression. r@)rArr'rBr+rrrr contained_byszARRAY.Comparator.contained_bycCs|jt|tjdS)zuBoolean expression. Test if array has elements in common with an argument array expression. r@)rAr r'rBrErrroverlapszARRAY.Comparator.overlapN)r:r;r<r=rDrFrGrrrr Comparators  rHFNz_TypeEngineArgument[Any]boolz Optional[int])r*as_tupler" zero_indexescCs>t|trtdt|tr"|}||_||_||_||_dS)a-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. zUDo not nest ARRAY types; ARRAY(basetype) handles multi-dimensional arrays of basetypeN)r(r) ValueErrorrr*rJr"rK)r+r*rJr"rKrrrr%s'  zARRAY.__init__cCs|jSr/)rJr0rrrhashable;szARRAY.hashablecCstSr/)listr0rrr python_type?szARRAY.python_typecCs||kSr/r)r+xyrrrcompare_valuesCszARRAY.compare_valuescCst|jtjo|jjSr/)r(r*r'EnumZ native_enumr0rrr_against_native_enumFszARRAY._against_native_enumcs:j||durdSddfdd}|S)NcSsdd|dS)NzARRAY[z, ])join)elementsrrrto_strTsz'ARRAY.literal_processor..to_strcs|j}|Sr/)_apply_item_processorr"valueinner item_procr+rXrrprocessWs z(ARRAY.literal_processor..process)r* dialect_implliteral_processorr+dialectr_rr]rraMs zARRAY.literal_processorcs$j||fdd}|S)Ncs"|dur |S|jtSdSr/)rYr"rNr[r^r+rrr_ds  z%ARRAY.bind_processor..process)r*r`bind_processorrbrrerrf_s  zARRAY.bind_processorcsTj|||fdd}jrP|tdfddfdd}|S)Ncs,|dur |S|jjr"tntSdSr/)rYr"rJtuplerNrdrerrr_ss z'ARRAY.result_processor..processz^{(.*)}$cs|d}t|S)Nr)matchgroup_split_enum_valuesrZ)patternrrhandle_raw_stringsz1ARRAY.result_processor..handle_raw_stringcs&|dur |St|tr |n|Sr/)r(strrd)rlsuper_rprrr_s )r*r`result_processorrTrecompile)r+rcZcoltyper_r)rlr^rkr+rnrrons     zARRAY.result_processor)FNF)r:r;r<r=r'r)rHZcomparator_factoryr%r>rMrOrRr Zmemoized_propertyrTrarfrorrrrr)s"C"3   r)cCsd|vr|r|dSgS|dd}|dd}g}td|}d}|D]>}|dkr^| }qJ|rv||ddqJ|td |qJ|S) N",z\"z _$ESC_QUOTE$_z\\\z(")Fz ([^\s,]+),?)splitreplacerpappendextendfindall)Z array_stringtextresultZ on_quotesZ in_quotestokrrrrjs   rj) __future__rrptypingrrrrrrr r r'r Zsqlr Z sql._typingrreqrZExpressionClauseListrr)rjrrrr s&               pv