o `^hV9 @sXdZddlmZddlZddlZddlZddlmZm Z m Z m Z m Z m Z mZddlmZddlmZmZmZddlmZmZmZdd lmZdd lmZdd lmZdd lm Z dd l!m"Z"m#Z#m$Z$erjddl%m&Z&dZ'e dZ(ej)dkreej*e"e$fdeddddddddddd dKd'd(Z+eej*e"e$fdeddddddddddd dLd,d(Z+n4eej*e"e$fdeddddddddd-dMd.d(Z+eej*e"e$fdeddddddddd-dNd/d(Z+eej*e"e$fd dOddddddddddd dPd2d(Z+ee,Z-d3ej)krd4krnn dQd9d:Z.e.ej/_0ddd;dd<dRdDdEZ1dSdIdJZ2dS)Tz7Provide an enhanced dataclass that performs validation.) annotationsN) TYPE_CHECKINGAnyCallableGenericNoReturnTypeVaroverload)warn)Literal TypeGuarddataclass_transform)_config _decorators _typing_extra) _dataclasses)getattr_migration) ConfigDict)PydanticUserError)Field FieldInfo PrivateAttr)PydanticDataclass) dataclassrebuild_dataclass_T )field_specifiersFT. initrepreqorder unsafe_hashfrozenconfigvalidate_on_initkw_onlyslotsr"Literal[False]r#boolr$r%r&r'r( ConfigDict | type[object] | Noner) bool | Noner*r+return-Callable[[type[_T]], type[PydanticDataclass]]c CdSNr!r4r4R/home/air/shanriGPT/back/venv/lib/python3.10/site-packages/pydantic/dataclasses.pyrr_clstype[_T]type[PydanticDataclass]c Cr2r3r4) r7r"r#r$r%r&r'r(r)r*r+r4r4r5r.r6r"r#r$r%r&r'r(r)cCr2r3r4r:r4r4r5rA c Cr2r3r4) r7r"r#r$r%r&r'r(r)r4r4r5rPr;type[_T] | NoneGCallable[[type[_T]], type[PydanticDataclass]] | type[PydanticDataclass]c st|dusJd|dusJdtjdkr| | dnidd d dfd d } |dur6| S| |S)aUsage docs: https://docs.pydantic.dev/2.9/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. 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+cls type[Any]r0Nonec Ss|jD]Q}t|dg}|D]F}t||d}t|tsq d|i}tjdkr+|jr+d|d<|jdur5|j|d<t||t j di||j ddurLi|_ |||j |<q qdS) 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__getrA)r>annotation_clsr field_name field_value field_argsr4r4r5make_pydantic_fields_compatibles"      z2dataclass..make_pydantic_fields_compatibler9c s8ddlm}||rtd|jddd|}durnt|dd}t|}tj |}|j }t |rQd}|f}t |trJt|j}||f}t|j|}|durk} |jrjtd |jd td d n|jpod } tj|fd| d}||_||_ |j|_|j|_d |_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__zN`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.)category stacklevelFT)r"r#r$r%r&r' raise_errorstypes_namespace)_internal._utilsrRr__name__rDr ConfigWrapperrDecoratorInfosbuild__doc___pydantic_dataclassesis_builtin_dataclass issubclassr__parameters__types new_classr'r UserWarningrIr__pydantic_decorators__ __module__ __qualname____pydantic_complete__complete_dataclass) r>rR original_cls config_dictconfig_wrapper decorators original_docbases generic_basefrozen_r(r$r'kwargsrQr%r#r&r4r5create_dataclasss`            z#dataclass..create_dataclassN)r>r?r0r@)r>r?r0r9)rFrG) r7r"r#r$r%r&r'r(r)r*r+rwr4rur5r`s.   #O)r)r argsrrvrcOstd)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)rzrvr4r4r5 _call_initvarsr|rU)forcerY_parent_namespace_depth_types_namespacer>r}rYr~intrdict[str, Any] | NonecCsl|s|jrdS|dur|}n|dkrtj|dpi}|}ni}t||}tj|tj|j dd||dS)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)checkrX) rkcopyrparent_frame_namespacemerge_cls_and_parent_nsrarlrr]rT)r>r}rYr~rrZframe_parent_nsr4r4r5rs   rclass_r?"TypeGuard[type[PydanticDataclass]]cCs,z d|jvo t|WStyYdSw)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)rKrI is_dataclassAttributeError)rr4r4r5is_pydantic_dataclassLs   r)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=)rzrrvrr0r) r>r9r}r-rYr-r~rrrr0r/)rr?r0r)3r` __future__r _annotationsrIrFretypingrrrrrrr warningsr typing_extensionsr r r _internalrrrrra _migrationrr(rerrorsrfieldsrrr_internal._dataclassesr__all__rrGrJrr\ __getattr__r|InitVar__call__rrr4r4r4r5s $        + 1