ѮhU6 (dZddlmZddlZddlZddlZddlmZm Z m Z m Z m Z m Z mZddlmZmZmZddlmZmZmZddlmZdd lmZdd lmZdd lmZdd lm Z m!Z!m"Z"erdd l#m$Z$dZ%e dZ&ejNdk\reejPe e"feddddddddddd d#dZ)eejPe e"feddddddddddd d$dZ)n|eejPe e"feddddddddd d%dZ)eejPe e"feddddddddd d&dZ)eejPe e"f d'ddddddddddd d(dZ)ee*Z+dejNcxkrdkrnnd)dZ,e,ejZ_.ddddd  d*d!Z/d+d"Z0y),z7Provide an enhanced dataclass that performs validation.) annotationsN) TYPE_CHECKINGAnyCallableGenericNoReturnTypeVaroverload)Literal TypeGuarddataclass_transform)_config _decorators _typing_extra) _dataclasses)getattr_migration) ConfigDict)PydanticUserError)Field FieldInfo PrivateAttr)PydanticDataclass) dataclassrebuild_dataclass_T )field_specifiersFT. initrepreqorder unsafe_hashfrozenconfigvalidate_on_initkw_onlyslotsc yNr!s f/home/www/academy-backend.kofcorporation.com/venv/lib/python3.12/site-packages/pydantic/dataclasses.pyrrs c yr-r.) _clsr"r#r$r%r&r'r(r)r*r+s r/rr-s#&r0r"r#r$r%r&r'r(r)cyr-r.r3s r/rr@s r0cyr-r.) r2r"r#r$r%r&r'r(r)s r/rrOs#&r0c  |dusJd|dusJdtjdk\rt| |  ni dd d  fd } || S| |S) aSUsage docs: https://docs.pydantic.dev/2.8/concepts/dataclasses/ A decorator used to create a Pydantic-enhanced dataclass, similar to the standard Python `dataclass`, but with added validation. This function should be used similarly to `dataclasses.dataclass`. Args: _cls: The target `dataclass`. init: Included for signature compatibility with `dataclasses.dataclass`, and is passed through to `dataclasses.dataclass` when appropriate. If specified, must be set to `False`, as pydantic inserts its own `__init__` function. repr: A boolean indicating whether to include the field in the `__repr__` output. eq: Determines if a `__eq__` method should be generated for the class. order: Determines if comparison magic methods should be generated, such as `__lt__`, but not `__eq__`. unsafe_hash: Determines if a `__hash__` method should be included in the class, as in `dataclasses.dataclass`. frozen: Determines if the generated class should be a 'frozen' `dataclass`, which does not allow its attributes to be modified after it has been initialized. config: The Pydantic config to use for the `dataclass`. validate_on_init: A deprecated parameter included for backwards compatibility; in V2, all Pydantic dataclasses are validated on init. kw_only: Determines if `__init__` method parameters must be specified by keyword only. Defaults to `False`. slots: Determines if the generated class should be a 'slots' `dataclass`, which does not allow the addition of new attributes after instantiation. Returns: A decorator that accepts a class as its argument and returns a Pydantic `dataclass`. Raises: AssertionError: Raised if `init` is not `False` or `validate_on_init` is `False`. Fz7pydantic.dataclasses.dataclass only supports init=Falsez-validate_on_init=False is no longer supportedr)r*r+c |jD]}t|dg}|D]}t||d}t|ts!d|i}tj dk\r|j rd|d<|jdur|j|d<t||tjdi||jjdi|_ |||j|<y) aMake sure that stdlib `dataclasses` understands `Field` kwargs like `kw_only` To do that, we simply change `x: int = pydantic.Field(..., kw_only=True)` into `x: int = dataclasses.field(default=pydantic.Field(..., kw_only=True), kw_only=True)` __annotations__NdefaultrTr*r#r.)__mro__getattr isinstancersys version_infor*r#setattr dataclassesfield__dict__getr8)clsannotation_clsr field_name field_value field_argss r/make_pydantic_fields_compatiblez2dataclass..make_pydantic_fields_compatibles"kk JN".2CRHK) J %c:t< !+y9%.{#; ##w.;3F3F,0Jy)##4/)4)9)9Jv&Z):):)HZ)HI<<##$56>*,C'2=j2I##J/- J  Jr0c ddlm}||rtd|jdd|} }|t |dd}||}t j |}tjj|}|j}tj|rNd}|f}t|trt|j} || fz}t!j"|j|}|t%j&|fd   d }||_||_ |j*|_|j,|_tj.||d d } | |_|S) zCreate a Pydantic dataclass from a regular dataclass. 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Returns: A Pydantic dataclass. r)is_model_classz(Cannot create a Pydantic dataclass from z" as it is already a Pydantic modelzdataclass-on-model)codeN__pydantic_config__T)r"r#r$r%r&r'F raise_errorstypes_namespace)_internal._utilsrKr__name__r;r ConfigWrapperrDecoratorInfosbuild__doc___pydantic_dataclassesis_builtin_dataclass issubclassr__parameters__types new_classr@r__pydantic_decorators__ __module__ __qualname__complete_dataclass__pydantic_complete__)rDrK original_cls config_dict cls_configconfig_wrapper decorators original_docbases generic_basepydantic_completer(r$r'kwargsrIr%r#r&s r/create_dataclassz#dataclass..create_dataclasssy 5 # #:3<<.Hjk)      &;TBJ%(  ..{; //55c: {{ 5 5c : L FE#w'&s'9'9: ///#,,6C',##   #    '1#" %00'441DD eT %6! r0)rD type[Any]returnNone)rDrmrntype[PydanticDataclass])r=r>dict)r2r"r#r$r%r&r'r(r)r*r+rlrkrIs `````` @@r/rr_sw\ 5=SSS= 5 (Y*YY ( 7"gU3!JFEEN | D !!r0)r)r ctd)a9This function does nothing but raise an error that is as similar as possible to what you'd get if you were to try calling `InitVar[int]()` without this monkeypatch. The whole purpose is just to ensure typing._type_check does not error if the type hint evaluates to `InitVar[]`. z 'InitVar' object is not callable) TypeError)argsrks r/ _call_initvarrw s :;;r0)forcerO_parent_namespace_depth_types_namespacec*|s |jry||j}n:|dkDrtj|xsi}|}ni}tj||}t j |tj|jd||S)axTry to rebuild the pydantic-core schema for the dataclass. This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails. This is analogous to `BaseModel.model_rebuild`. Args: cls: The class to rebuild the pydantic-core schema for. force: Whether to force the rebuilding of the schema, defaults to `False`. raise_errors: Whether to raise errors, defaults to `True`. _parent_namespace_depth: The depth level of the parent namespace, defaults to 2. _types_namespace: The types namespace, defaults to `None`. Returns: Returns `None` if the schema is already "complete" and rebuilding was not required. If rebuilding _was_ required, returns `True` if rebuilding was successful, otherwise `False`. Nr) parent_depthF)checkrN) racopyrparent_frame_namespaceget_cls_types_namespacerWr`rrSrM)rDryrOrzr{rPframe_parent_nss r/rrs4 S..  '5E5J5J5LO&*"/"F"FTk"l"rpr#2"$+CCCYO$77   ! !#"9"9 G%+   r0cl d|jvxrtj|S#t$rYywxYw)zWhether a class is a pydantic dataclass. Args: class_: The class. Returns: `True` if the class is a pydantic dataclass, `False` otherwise. __pydantic_validator__F)rBr@ is_dataclassAttributeError)class_s r/is_pydantic_dataclassrFs9'6??:_{?W?WX^?__ s $' 33)r"Literal[False]r#boolr$rr%rr&rr'rr( ConfigDict | type[object] | Noner) bool | Noner*rr+rrn-Callable[[type[_T]], type[PydanticDataclass]])r2type[_T]r"rr#rr$rr%rr&rr'rr(rr)rr*rr+rrnrp)r"rr#rr$rr%rr&rr'rr(rr)rrnr)r2rr"rr#rr$rr%rr&rr'rr(rr)rrnrpr-)r2ztype[_T] | Noner"rr#rr$rr%rr&rr'rr(rr)rr*rr+rrnzGCallable[[type[_T]], type[PydanticDataclass]] | type[PydanticDataclass])rvrrkrrnr) rDrpryrrOrrzintr{zdict[str, Any] | Nonernr)rrmrnz"TypeGuard[type[PydanticDataclass]])1rV __future__r _annotationsr@r=r[typingrrrrrr r typing_extensionsr r r _internalrrrrrW _migrationrr(rerrorsrfieldsrrr_internal._dataclassesr__all__rr>rArrR __getattr__rwInitVar__call__rrr.r0r/rs=2 UUUEE::<)%119 * T]w;+<+