hW? @SrSSKJr SSKrSSKrSSKrSSKJrJ r J r J r J r J r JrJr SSKJr SSKJrJr SSKJrJrJrJr SS KJr SS KJr SS KJr SS K J!r! SS K"J#r#J$r$J%r% \(a SSK&J'r' SSK(J)r) Sr*\"S5r+\RXS:a\"\RZ\#\%4S9\SSSSSSSSSSS. S$Sjj55r.\"\RZ\#\%4S9\SSSSSSSSSSS. S%Sjj55r.Oz\"\RZ\#\%4S9\SSSSSSSSS.S&Sjj55r.\"\RZ\#\%4S9\SSSSSSSSS.S'Sjj55r.\"\RZ\#\%4S9S(SSSSSSSSSSS. S)Sjjj5r.\"\/5r0\RXS:aS*Sjr1\1\Rdl3SSS SS!.S+S"jjr4S,S#jr5g)-z7Provide an enhanced dataclass that performs validation.) annotationsN) TYPE_CHECKINGAnyCallableGenericLiteralNoReturnTypeVaroverload)warn) TypeGuarddataclass_transform)_config _decorators_namespace_utils _typing_extra) _dataclasses)getattr_migration) ConfigDict)PydanticUserError)Field FieldInfo PrivateAttr)PydanticDataclass)MappingNamespace) dataclassrebuild_dataclass_T )field_specifiersFT. initrepreqorder unsafe_hashfrozenconfigvalidate_on_initkw_onlyslotsc gNr$s F/var/www/html/env/lib/python3.13/site-packages/pydantic/dataclasses.pyrrs c gr0r1) _clsr%r&r'r(r)r*r+r,r-r.s r2rr/s#&r3r%r&r'r(r)r*r+r,cgr0r1r6s r2rrBs r3cgr0r1) r5r%r&r'r(r)r*r+r,s r2rrQs#&r3c ^^^^^^^ ^ USLdS5eUSLdS5e[RS:aXS.m O0m SSjm S UUUU U UUU4Sjjn UcU $U "U5$) ar!!! abstract "Usage Documentation" [`dataclasses`](../concepts/dataclasses.md) 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. If not set, the value from the provided `config` argument will be used (and will default to `False` otherwise). 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 URHn[US05nUHn[XS5n[U[5(dM&SU0n[R S:aUR (aSUS'URSLaURUS'[X[R"S0UD65 URRS5c0Ul X#URU'M M g) zMake 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__Ndefaultr Tr-r&r1)__mro__getattr isinstancersys version_infor-r&setattr dataclassesfield__dict__getr;)clsannotation_clsr field_name field_value field_argss r2make_pydantic_fields_compatible2dataclass..make_pydantic_fields_compatibles"kkN*1.BSUW*XK) %ct< !+y99%.{#; ##w.;3F3F,0Jy)##4/)4)9)9Jv&):):)HZ)HI<<##$56>*,C'2=2I##J/-**r3c >SSKJn U"U5(a[SURS3SS9eUn[ SUR 55nU(d1T b.[ US 5(a[S URS 3[S S 9 T bT O [US S5n[R"U5n[RRU5nURn[ R""U5(aSSnU4n[%U[&5(a[&UR(n X4-n[*R,"URU5nT"U5 T b2T n UR.(a[SUR<S3[S S 9 OUR.=(d Sn [0R2"U4STT TTU S.TD6nSUlX`lXplUR8UlUR:UlSUl[ R>"XSS9 U$)zCreate a Pydantic dataclass from a regular dataclass. Args: cls: The class to create the Pydantic dataclass from. Returns: A Pydantic dataclass. r)is_model_classz(Cannot create a Pydantic dataclass from z" as it is already a Pydantic modelzdataclass-on-model)codec3N# UHn[R"U5v M g7fr0)rC is_dataclass).0bases r2 6dataclass..create_dataclass..s ZMD!9!9$!?!?Ms#%N__pydantic_config__z[`config` is set via both the `dataclass` decorator and `__pydantic_config__` for dataclass zK. The `config` specification from `dataclass` decorator will take priority.)category stacklevelzN`frozen` is set via both the `dataclass` decorator and `config` for dataclass zW.This is not recommended. The `frozen` specification on `dataclass` will take priority.FT)r%r&r'r(r)r*) raise_errors) _internal._utilsrOr__name__any __bases__hasattrr UserWarningr>r ConfigWrapperrDecoratorInfosbuild__doc___pydantic_dataclassesis_builtin_dataclass issubclassr__parameters__types new_classr*rCr__is_pydantic_dataclass____pydantic_decorators__ __module__ __qualname____pydantic_complete__complete_dataclass)rGrO original_clshas_dataclass_base config_dictconfig_wrapper decorators original_docbases generic_basefrozen_r+r'r*kwargsrLr(r&r)s r2create_dataclass#dataclass..create_dataclasss 5 #  #:3<<.Hjk)   ! ZCMM ZZ!f&8WSJ_=`=` mnqnznzm{|\]$  !' 2fEZ\`8a  ..{; //55c: {{ 5 5c : : L FE#w''&s'9'9: ///#,,6C',  G$$deheqeqdtumm( %++4uG##   #    )-%&0#" %00'44$)! 00SXY r3)rG type[Any]returnNone)rGr~rtype[PydanticDataclass])r@rA)r5r%r&r'r(r)r*r+r,r-r.r|r{rLs `````` @@r2rrass^ 5=SSS= 5 (Y*YY ( 7"$5JB__B $| G1A$1GGr3)r! c[S5e)a!This function does nothing but raise an error that is as similar as possible to what you'd get if you were to try calling `InitVar[int]()` without this monkeypatch. The whole purpose is just to ensure typing._type_check does not error if the type hint evaluates to `InitVar[]`. z 'InitVar' object is not callable) TypeError)argsr{s r2 _call_initvarr#s :;;r3rX)forcer[_parent_namespace_depth_types_namespacecxU(dUR(agSHnXPR;dM[X5 M! SUlUbUnO'US:a[R"USS9=(d 0nO0n[ R "US9n[R"U[R"URSS9UUSS 9$) aDTry 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`. N)__pydantic_core_schema____pydantic_validator____pydantic_serializer__FrT) parent_depthr)parent_namespace)check)r[ ns_resolver _force_build) rprEdelattrrparent_frame_namespacer NsResolverrfrqrrbrW)rGrr[rrattr rebuild_nsrs r2rr-s4 S..a <<  C  b !&C#% 1 $"99G^fjkqoq  "--#K ! 3 3 c55UC!   r3c|SUR;=(a [R"U5$![a gf=f)zWhether a class is a pydantic dataclass. Args: class_: The class. Returns: `True` if the class is a pydantic dataclass, `False` otherwise. rlF)rErCrRAttributeError)class_s r2is_pydantic_dataclassrjs9*foo=b+BZBZ[aBbb s +. ;;)r%Literal[False]r&boolr'rr(rr)rr*rr+ ConfigDict | type[object] | Noner, bool | Noner-rr.rr-Callable[[type[_T]], type[PydanticDataclass]])r5type[_T]r%rr&rr'rr(rr)rr*rr+rr,rr-rr.rrr)r%rr&rr'rr(rr)rr*rr+rr,rrr)r5rr%rr&rr'rr(rr)rr*rr+rr,rrrr0)r5ztype[_T] | Noner%rr&rr'rr(rr)rr*rr+rr,rr-rr.rrzGCallable[[type[_T]], type[PydanticDataclass]] | type[PydanticDataclass])rrr{rrr ) rGrrrr[rrintrzMappingNamespace | Nonerr)rr~rz"TypeGuard[type[PydanticDataclass]])6re __future__r _annotationsrCr@rjtypingrrrrrr r r warningsr typing_extensionsr r _internalrrrrrrf _migrationrr+rerrorsrfieldsrrr_internal._dataclassesr_internal._namespace_utilsr__all__rrArDrr] __getattr__rInitVar__call__rrr1r3r2rs=2 ^^^<LL<)%119< * T]w;+<+