o }j6hW? @sVdZddlmZddlZddlZddlZddlmZm Z m Z m Z m Z m Z mZmZddlmZddlmZmZddlmZmZmZmZdd lmZdd lmZdd lmZdd l m!Z!dd l"m#Z#m$Z$m%Z%errddl&m'Z'ddl(m)Z)dZ*edZ+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.dNd0d)Z.eej-e#e%fd dOddddddddddd dPd3d)Z.ee/Z0ej,d4krdQd9d:Z1e1ej2_3ddd;dd<dRdDdEZ4dSdIdJZ5dS)Tz7Provide 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_onlyslotsr$Literal[False]r%boolr&r'r(r)r* ConfigDict | type[object] | Noner+ bool | Noner,r-return-Callable[[type[_T]], type[PydanticDataclass]]c CdSNr#r6r6c/var/www/html/chefvision.cloud.itp360.com/venv/lib/python3.10/site-packages/pydantic/dataclasses.pyrr_clstype[_T]type[PydanticDataclass]c Cr4r5r6) r9r$r%r&r'r(r)r*r+r,r-r6r6r7r/r8r$r%r&r'r(r)r*r+cCr4r5r6r<r6r6r7rB c Cr4r5r6) r9r$r%r&r'r(r)r*r+r6r6r7rQr=type[_T] | NoneGCallable[[type[_T]], type[PydanticDataclass]] | type[PydanticDataclass]c st|dusJd|dusJdtjdkr| | dnidd d dfd d } |dur6| S| |S)a!!! 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-cls type[Any]r2Nonec Ss|jD]Q}t|di}|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%r6)__mro__getattr isinstancersys version_infor,r%setattr dataclassesfield__dict__getrC)r@annotation_clsr field_name field_value field_argsr6r6r7make_pydantic_fields_compatibles"      z2dataclass..make_pydantic_fields_compatibler;c s~ddlm}||rtd|jddd|}tdd|jD}|s8d ur8t|d r8td |jd td dd ur>nt |d d }t |}t j |}|j}t|rrd }|f}t|trkt|j} || f}t|j|}|d ur} |jrtd|jdtd dn|jpd} tj|fd| d}d|_||_||_|j|_|j|_d|_tj||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)codecss|]}t|VqdSr5)rK is_dataclass).0baser6r6r7 sz6dataclass..create_dataclass..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$r%r&r'r(r)) raise_errors) _internal._utilsrTr__name__any __bases__hasattrr UserWarningrFr ConfigWrapperrDecoratorInfosbuild__doc___pydantic_dataclassesis_builtin_dataclass issubclassr__parameters__types new_classr)rKr__is_pydantic_dataclass____pydantic_decorators__ __module__ __qualname____pydantic_complete__complete_dataclass) r@rT original_clshas_dataclass_base config_dictconfig_wrapper decorators original_docbases generic_basefrozen_r*r&r)kwargsrSr'r%r(r6r7create_dataclasssp            z#dataclass..create_dataclassN)r@rAr2rB)r@rAr2r;)rHrI) r9r$r%r&r'r(r)r*r+r,r-rr6r~r7ras/   !a)r argsrrrcOstd)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)rrr6r6r7 _call_initvar#srr[)forcer^_parent_namespace_depth_types_namespacer@rr^rintrMappingNamespace | NonecCs|s|jrdSdD] }||jvrt||q d|_|dur |}n|dkr.tj|ddp,i}ni}tj|d}tj|t j |j dd||dd S) 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`. N)__pydantic_core_schema____pydantic_validator____pydantic_serializer__FrT) parent_depthr)parent_namespace)check)r^ ns_resolver _force_build) rsrMdelattrrparent_frame_namespacer NsResolverrirtrrerZ)r@rr^rrattr rebuild_nsrr6r6r7r-s,   rclass_rA"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. roF)rMrKrVAttributeError)rr6r6r7is_pydantic_dataclassjs   r)r$r.r%r/r&r/r'r/r(r/r)r/r*r0r+r1r,r/r-r/r2r3)r9r:r$r.r%r/r&r/r'r/r(r/r)r1r*r0r+r1r,r/r-r/r2r;)r$r.r%r/r&r/r'r/r(r/r)r1r*r0r+r1r2r3)r9r:r$r.r%r/r&r/r'r/r(r/r)r1r*r0r+r1r2r;r5)r9r>r$r.r%r/r&r/r'r/r(r/r)r1r*r0r+r1r,r/r-r/r2r?)rrrrr2r) r@r;rr/r^r/rrrrr2r1)rrAr2r)6rh __future__r _annotationsrKrHrmtypingrrrrrrr r warningsr typing_extensionsr r _internalrrrrrri _migrationrr*rerrorsrfieldsrrr_internal._dataclassesr_internal._namespace_utilsr__all__rrIrLrr` __getattr__rInitVar__call__rrr6r6r6r7s (         <  =