]fU6 \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&ej'dkreeej(e e"feddddddddddd dFd&Z)eej(e e"feddddddddddd dGd*Z)n`eej(e e"feddddddddd+dHd,Z)eej(e e"feddddddddd+dId-Z)eej(e e"f dJddddddddddd dKd0Z)ee*Z+d1ej'cxkrd2krnndLd7Z,e,ej-_.ddd8dd9dMdAZ/dNdEZ0dS)Oz7Provide 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_onlyslotsr"Literal[False]r#boolr$r%r&r'r( ConfigDict | type[object] | Noner) bool | Noner*r+return-Callable[[type[_T]], type[PydanticDataclass]]c dSNr!s F/var/www/html/env/lib/python3.11/site-packages/pydantic/dataclasses.pyrrs  _clstype[_T]type[PydanticDataclass]c dSr3r4) r7r"r#r$r%r&r'r(r)r*r+s r5rr-s #&#r6r"r#r$r%r&r'r(r)cdSr3r4r;s r5rr@s  r6cdSr3r4) r7r"r#r$r%r&r'r(r)s r5rrOs #&#r6type[_T] | NoneGCallable[[type[_T]], type[PydanticDataclass]] | type[PydanticDataclass]c  |dus Jd|dus Jdtjdkrt| |  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+cls type[Any]r0Nonec |jD]}t|dg}|D]}t||d}t|ts)d|i}tjdkr |jrd|d<|jdur |j|d<t||tj di||j di|_ |||j |<dS) 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#r4)__mro__getattr isinstancersys version_infor*r#setattr dataclassesfield__dict__getrE)rAannotation_clsr field_name field_value field_argss r5make_pydantic_fields_compatiblez2dataclass..make_pydantic_fields_compatibles"k J JN".2CRHHK) J J %c:t<< !+y99%.{#; #w..;3F.,0Jy)#4//)4)9Jv&Z):)H)HZ)H)HIII<##$566>*,C'2=j2I#J//- J  J Jr6r9c ddlm}||rtd|jdd|} }|t |dd}||}t j|}tj |}|j }tj |rLd}|f}t|trt|j} || fz}t!j|j|}|t%j|fd   d }||_||_ |j|_|j|_tj||d d } | |_|S) zCreate a Pydantic dataclass from a regular dataclass. 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Returns: A Pydantic dataclass. r)is_model_classz(Cannot create a Pydantic dataclass from z" as it is already a Pydantic modelzdataclass-on-model)codeN__pydantic_config__T)r"r#r$r%r&r'F raise_errorstypes_namespace)_internal._utilsrWr__name__rHr ConfigWrapperrDecoratorInfosbuild__doc___pydantic_dataclassesis_builtin_dataclass issubclassr__parameters__types new_classrMr__pydantic_decorators__ __module__ __qualname__complete_dataclass__pydantic_complete__)rArW original_cls config_dict cls_configconfig_wrapper decorators original_docbases generic_basepydantic_completer(r$r'kwargsrUr%r#r&s r5create_dataclassz#dataclass..create_dataclasss 544444 >#   #k3<kkk)      &;TBBJ%(  .{;; /55c:: { 5c : : 7 L FE#w'' 0&s'9: //#,66C'',,,#   #      '1#" %0'41D eT   %6! r6N)rArBr0rC)rArBr0r9)rJrKdict)r7r"r#r$r%r&r'r(r)r*r+rxrwrUs `````` @@r5rr_s\ 5===S=== 5 ( ( (*Y ( ( ( 7""gU333!J!J!J!JFEEEEEEEEEEEEEN |  D ! !!r6)r)r argsrrwrc td)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)r|rws r5 _call_initvarr s :;;;r6)forcer[_parent_namespace_depth_types_namespacerArr[rintrdict[str, Any] | Nonec|s |jrdS||}n7|dkrtj|pi}|}ni}tj||}t j|tj|j d||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)checkrZ) rmcopyrparent_frame_namespaceget_cls_types_namespacercrlrr_rY)rArr[rrr\frame_parent_nss r5rrs4  S. t  '5E5J5J5L5LOO&**"/"FTk"l"l"l"rpr#2"$+CCYYO$7   !#"9 G G G%+     r6class_rB"TypeGuard[type[PydanticDataclass]]c` d|jvotj|S#t$rYdSwxYw)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)rOrM is_dataclassAttributeError)rs r5is_pydantic_dataclassrFsG'6?:_{?WX^?_?__ uus  --)r"r,r#r-r$r-r%r-r&r-r'r-r(r.r)r/r*r-r+r-r0r1)r7r8r"r,r#r-r$r-r%r-r&r-r'r-r(r.r)r/r*r-r+r-r0r9)r"r,r#r-r$r-r%r-r&r-r'r-r(r.r)r/r0r1)r7r8r"r,r#r-r$r-r%r-r&r-r'r-r(r.r)r/r0r9r3)r7r>r"r,r#r-r$r-r%r-r&r-r'r-r(r.r)r/r*r-r+r-r0r?)r|rrwrr0r) rAr9rr-r[r-rrrrr0r/)rrBr0r)1rb __future__r _annotationsrMrJrgtypingrrrrrr r typing_extensionsr r r _internalrrrrrc _migrationrr(rerrorsrfieldsrrr_internal._dataclassesr__all__rrKrNrr^ __getattr__rInitVar__call__rrr4r6r5rs==222222 UUUUUUUUUUUUUUUUUUEEEEEEEEEE::::::::::<<<<<<))))))%%%%%%1111111111:999999 * WT]]w;+