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"SS\R^5r0"SS\0\R^5r1O\r2SS Sjjr3SS.S!Sjjr4S"Sjr5g)#z0Private logic for creating pydantic dataclasses.) annotationsN)partialwraps)AnyCallableClassVar) ArgsKwargsSchemaSerializerSchemaValidator core_schema) TypeGuard)PydanticUndefinedAnnotation)PluggableSchemaValidatorcreate_schema_validator)PydanticDeprecatedSince20)_config _decorators _typing_extra)collect_dataclass_fields)GenerateSchema)get_standard_typevars_map)set_dataclass_mocks)CallbackGetCoreSchemaHandler)generate_pydantic_signature) ConfigDict) FieldInfoc>\rSrSr%S\S'S\S'S\S'S SjrS rg ) StandardDataclass"zClassVar[dict[str, Any]]__dataclass_fields__z ClassVar[Any]__dataclass_params__zClassVar[Callable[..., None]] __post_init__cgN)selfargskwargss ^/root/lseg-credit/backend/venv/lib/python3.13/site-packages/pydantic/_internal/_dataclasses.py__init__StandardDataclass.__init__'s r'N)r)objectr*r/returnNone)__name__ __module__ __qualname____firstlineno____annotations__r,__static_attributes__r'r.r+r r "s66++44 r.r c`\rSrSr%SrS\S'S\S'S\S'S \S 'S \S 'S \S'S\S'Srg)PydanticDataclass*a!A protocol containing attributes only available once a class has been decorated as a Pydantic dataclass. Attributes: __pydantic_config__: Pydantic-specific configuration settings for the dataclass. __pydantic_complete__: Whether dataclass building is completed, or if there are still undefined fields. __pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer. __pydantic_decorators__: Metadata containing the decorators defined on the dataclass. __pydantic_fields__: Metadata about the fields defined on the dataclass. __pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the dataclass. __pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the dataclass. zClassVar[ConfigDict]__pydantic_config__zClassVar[bool]__pydantic_complete__z ClassVar[core_schema.CoreSchema]__pydantic_core_schema__z$ClassVar[_decorators.DecoratorInfos]__pydantic_decorators__zClassVar[dict[str, FieldInfo]]__pydantic_fields__zClassVar[SchemaSerializer]__pydantic_serializer__z4ClassVar[SchemaValidator | PluggableSchemaValidator]__pydantic_validator__r'N)r2r3r4r5__doc__r6r7r'r.r+r9r9*s3 21--"BB!EE;;!;; TTr.r9c:[U5n[XX2S9nX@lg)zCollect and set `cls.__pydantic_fields__`. Args: cls: The class. types_namespace: The types namespace, defaults to `None`. config_wrapper: The config wrapper instance, defaults to `None`. ) typevars_mapconfig_wrapperN)rrr?)clstypes_namespacerErDfieldss r+set_dataclass_fieldsrIEs -S1L %c uF$r.T) raise_errorsc ^ [US5(a[R"S[5 Uc[R "U5n[ XUS9 [U5n[UUU5n[URURUSS9nSSjnURS3Ul Xpl URUlX`l[!US S5nU(a%U"U[#[%UR&S S 9US S 95n OUR'US S 9n UR1U5n UR3U 5n [6R8"SU5nXl[=XUR>URSXR@5=Ul!m [EX5Ul#URH(a7[KURL5SU 4Sjj5n U ROSU5Ul&SUl(g![(a6n U(ae[+XR,SU R.S35 Sn A g Sn A ff=f!UR4a [+XR,S5 g f=f)agFinish building a pydantic dataclass. This logic is called on a class which has already been wrapped in `dataclasses.dataclass()`. This is somewhat analogous to `pydantic._internal._model_construction.complete_model_class`. Args: cls: The class. config_wrapper: The config wrapper instance. raise_errors: Whether to raise errors, defaults to `True`. types_namespace: The types namespace. 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H(,HH!&I  I c [R"U5=(aP [US5(+=(a8 [UR5R [[ US0555$)aReturns True if a class is a stdlib dataclass and *not* a pydantic dataclass. We check that - `_cls` is a dataclass - `_cls` does not inherit from a processed pydantic dataclass (and thus have a `__pydantic_validator__`) - `_cls` does not have any annotations that are not dataclass fields e.g. ```py import dataclasses import pydantic.dataclasses @dataclasses.dataclass class A: x: int @pydantic.dataclasses.dataclass class B(A): y: int ``` In this case, when we first check `B`, we make an extra check and look at the annotations ('y'), which won't be a superset of all the dataclass fields (only the stdlib fields i.e. 'x') Args: cls: The class. 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