a OfU6@sdZddlmZddlZddlZddlZddlmZm 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'dkreej(e e"fdeddddddddddd dddddddddddd ddZ)eej(e e"fdeddddddddddd ddddddddddddd d!dZ)neej(e e"fdeddddddddd"dddddddddd# d$dZ)eej(e e"fdeddddddddd"ddddddddddd% d&dZ)eej(e e"fdd=ddddddddddd d'ddddddddddd(d d)dZ)ee*Z+d*ej'krd+krnnd,d,d-d.d/d0Z,e,ej-_.ddd1dd2dddd3d4dd5d6d7Z/d8d9d:d;d<Z0dS)>z7Provide an enhanced dataclass that performs validation.) annotationsN) TYPE_CHECKINGAnyCallableGenericNoReturnTypeVaroverload)Literal TypeGuarddataclass_transform)_config _decorators _typing_extra) _dataclasses)getattr_migration) ConfigDict)PydanticUserError)Field FieldInfo PrivateAttr)PydanticDataclass) dataclassrebuild_dataclass_T )field_specifiersFT. initrepreqorder unsafe_hashfrozenconfigvalidate_on_initkw_onlyslotszLiteral[False]boolz ConfigDict | type[object] | Nonez bool | Nonez-Callable[[type[_T]], type[PydanticDataclass]]) r!r"r#r$r%r&r'r(r)r*returnc CsdSNr r.r.M/var/www/ai-form-bot/venv/lib/python3.9/site-packages/pydantic/dataclasses.pyrsrztype[_T]type[PydanticDataclass]) _clsr!r"r#r$r%r&r'r(r)r*r,c CsdSr-r.) r1r!r"r#r$r%r&r'r(r)r*r.r.r/r-sr!r"r#r$r%r&r'r() r!r"r#r$r%r&r'r(r,cCsdSr-r.r2r.r.r/r@s ) r1r!r"r#r$r%r&r'r(r,c CsdSr-r.) r1r!r"r#r$r%r&r'r(r.r.r/rOs ztype[_T] | NonezGCallable[[type[_T]], type[PydanticDataclass]] | type[PydanticDataclass]c s|dusJd|dus Jdtjdkr8t| | dnidddd d dd dfd d } |durz| 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* type[Any]None)clsr,c Ss|jD]}t|dg}|D]}t||d}t|ts6qd|i}tjdkrV|jrVd|d<|jdurj|j|d<t||t j fi||j dduri|_ |||j |<qqdS)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")__mro__getattr isinstancersys version_infor)r"setattr dataclassesfield__dict__getr6)r5Zannotation_clsr field_nameZ field_valueZ field_argsr.r.r/make_pydantic_fields_compatibles      z2dataclass..make_pydantic_fields_compatibler0c sddlm}||r*td|jddd|}}|durRt|dd}|durR|}t|}tj |}|j }t |rd}|f}t |trt|j} || f}t|j|}|tj|fd d }||_||_ |j|_|j|_t j||d dd } | |_|S) 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)codeN__pydantic_config__T)r!r"r#r$r%r&F raise_errorstypes_namespace)Z_internal._utilsrDr__name__r9r ConfigWrapperrZDecoratorInfosbuild__doc___pydantic_dataclassesZis_builtin_dataclass issubclassr__parameters__types new_classr>rZ__pydantic_decorators__ __module__ __qualname__complete_dataclass__pydantic_complete__) r5rDZ original_clsZ config_dictZ cls_configZconfig_wrapperZ decoratorsZ original_docbases generic_baseZpydantic_completer'r#r&kwargsrCr$r"r%r.r/create_dataclasssX           z#dataclass..create_dataclassN)r;r<dict) r1r!r"r#r$r%r&r'r(r)r*r[r.rYr/r_s. #"G)r)r rr)argsrZr,cOs tddS)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 callableN) TypeError)r_rZr.r.r/ _call_initvar sra)forcerH_parent_namespace_depth_types_namespaceintzdict[str, Any] | None)r5rcrHrdrer,cCsp|s|jrdS|dur |}n.|dkr>tj|dp6i}|}ni}t||}tj|tj|j dd||dSdS)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)Z parent_depthF)checkrG) rVcopyrZparent_frame_namespaceZget_cls_types_namespacerNrUrrKrF)r5rcrHrdrerIZframe_parent_nsr.r.r/rs   rr3z"TypeGuard[type[PydanticDataclass]])class_r,cCs0zd|jvot|WSty*YdS0dS)zWhether a class is a pydantic dataclass. Args: class_: The class. Returns: `True` if the class is a pydantic dataclass, `False` otherwise. Z__pydantic_validator__FN)r@r> is_dataclassAttributeError)rir.r.r/is_pydantic_dataclassFs  rl)N)1rM __future__rZ _annotationsr>r;rQtypingrrrrrrr typing_extensionsr r r _internalrrrrrNZ _migrationrr'rerrorsrfieldsrrrZ_internal._dataclassesr__all__rr<r?rrJ __getattr__raInitVar__call__rrlr.r.r.r/s $      *.& (*&1