!h#dZddlmZddlZddlZddlZddlmZm Z ddlm Z m Z ddl m Z mZmZmZddlmZdd lmZdd lmZmZdd lmZd d lmZmZd dlmZd dlmZm Z d dl!m"Z"d dl#m$Z$d dl%m&Z&d dl'm(Z(d dl)m*Z*ej+r'ddl,m-Z.ddl/m0Z0ddl1m2Z2Gdde.ej3Z4neZ5 d/d0d"Z6d#dd$d%d1d+Z7d2d.Z8dS)3z0Private logic for creating pydantic dataclasses.) annotationsN)partialwraps)AnyClassVar) ArgsKwargsSchemaSerializerSchemaValidator core_schema) TypeGuard)PydanticUndefinedAnnotation)PluggableSchemaValidatorcreate_schema_validator)PydanticDeprecatedSince20)_config _decorators)collect_dataclass_fields)GenerateSchemaInvalidSchemaError)get_standard_typevars_map)set_dataclass_mocks) NsResolver)generate_pydantic_signature)LazyClassAttribute)DataclassInstance) ConfigDict) FieldInfocreZdZUdZded<ded<ded<ded <d ed <d ed <ded<eddZdS)PydanticDataclassaiA protocol containing attributes only available once a class has been decorated as a Pydantic dataclass. Attributes: __pydantic_config__: Pydantic-specific configuration settings for the dataclass. __pydantic_complete__: Whether dataclass building is completed, or if there are still undefined fields. __pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer. __pydantic_decorators__: Metadata containing the decorators defined on the dataclass. __pydantic_fields__: Metadata about the fields defined on the dataclass. __pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the dataclass. __pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the dataclass. zClassVar[ConfigDict]__pydantic_config__zClassVar[bool]__pydantic_complete__z ClassVar[core_schema.CoreSchema]__pydantic_core_schema__z$ClassVar[_decorators.DecoratorInfos]__pydantic_decorators__zClassVar[dict[str, FieldInfo]]__pydantic_fields__zClassVar[SchemaSerializer]__pydantic_serializer__z4ClassVar[SchemaValidator | PluggableSchemaValidator]__pydantic_validator__returnboolcdSN)clss Yc:\xampp_lite_8_4\www\timesheet\venv\Lib\site-packages\pydantic/_internal/_dataclasses.py__pydantic_fields_complete__z.PydanticDataclass.__pydantic_fields_complete__:s7:sN)r)r*)__name__ __module__ __qualname____doc____annotations__ classmethodr0r-r1r/r!r!%s  2111----BBBBEEEE;;;;;;;;TTTT ::: :::r1r!r.type[StandardDataclass] ns_resolverNsResolver | Noneconfig_wrapper_config.ConfigWrapper | Noner)NonecXt|}t||||}||_dS)zCollect and set `cls.__pydantic_fields__`. Args: cls: The class. ns_resolver: Namespace resolver to use when getting dataclass annotations. config_wrapper: The config wrapper instance, defaults to `None`. )r9 typevars_mapr;N)rrr&)r.r9r;r?fieldss r/set_dataclass_fieldsrACs?-S11L % .__init__xs:    00D&1I1IYZ0[[[[[r1z .__init__)r;F__post_init_post_parse__zVSupport for `__post_init_post_parse__` has been dropped, the method will not be called)r9r? __signature__T)initr@validate_by_nameextra is_dataclass`N)titleztype[PydanticDataclass] dataclassinstancefieldstrvaluec6|||dSr,)validate_assignment)rYrZr\ validators r/validated_setattrz-complete_dataclass..validated_setattrs!  ) )(E5 A A A A Ar1)rGr!rHrrIrr)r=)rYrrZr[r\r[r)r=))rOr4 config_dictr"rA defer_buildrhasattrwarningswarnDeprecationWarningrrrrrr&rSrTrQgenerate_schemarname core_configr2 clean_schemartypingcastr$rr3plugin_settingsr(r r'r^r __setattr____get__r#)r.r;rBr9rC original_initrOr? gen_schemaschemaerir`r_s @r/complete_dataclassrtWs:LM\\\\ #/:::HCL,8Ck.IIII N6C   us.//  dfx   -S11L!J+ '*+< &   C++C00 &   CQV///uuuuu  !,,3<,@@K((00 C   uu +/ 5 5C$*C -DS^S%5{KQ_Qo..C#36;"G"GC)? s   B B B B B  B,33D#>> $C 4s*#C99 D*D%%D* EE<;E<_cls"TypeGuard[type[StandardDataclass]]c tj|oSt|d oBt|jtt |diS)aBReturns True if a class is a stdlib dataclass and *not* a pydantic dataclass. We check that - `_cls` is a dataclass - `_cls` does not inherit from a processed pydantic dataclass (and thus have a `__pydantic_validator__`) - `_cls` does not have any annotations that are not dataclass fields e.g. ```python import dataclasses import pydantic.dataclasses @dataclasses.dataclass class A: x: int @pydantic.dataclasses.dataclass class B(A): y: int ``` In this case, when we first check `B`, we make an extra check and look at the annotations ('y'), which won't be a superset of all the dataclass fields (only the stdlib fields i.e. 'x') Args: cls: The class. Returns: `True` if the class is a stdlib dataclass, `False` otherwise. r(r6) dataclassesrUrcset__dataclass_fields__ issupersetgetattr)rus r/is_builtin_dataclassr}sf>  && a677 7 a ) * * 5 5c'$HY[]:^:^6_6_ ` `r1)NN)r.r8r9r:r;r<r)r=) r.rDr;rErBr*r9r:rCr*r)r*)rurDr)rv)9r5 __future__r _annotationsrxrkrd functoolsrrrr pydantic_corerr r r typing_extensionsr errorsrplugin._schema_validatorrrrrr_fieldsr_generate_schemarr _genericsr _mock_val_serr_namespace_utilsr _signaturer_utilsr TYPE_CHECKING _typeshedrStandardDataclassconfigrr@rProtocolr!rfrArtr}r-r1r/rs66222222 $$$$$$$$  ('''''000000XXXXXXXX000000""""""""------@@@@@@@@000000......((((((333333&&&&&& !3@@@@@@######"""""";;;;;-v;;;;63 &*37%%%%%0%) rrrrrrj""""""r1