U nj>@sdZddlmZddlZddlZddlZddlmZm Z m Z m Z m Z m Z mZddlmZddlmZmZmZddlmZmZmZmZdd lmZdd lmZdd lmZdd l m!Z!dd l"m#Z#m$Z$m%Z%erddl&m'Z'ddl(m)Z)dZ*e dZ+ej,dkreej-e#e%fdeddddddddddd dddddddddddd ddZ.eej-e#e%fdeddddddddddd d ddddddddddd!d" d#dZ.neej-e#e%fdeddddddddd$dddddddddd% d&dZ.eej-e#e%fdeddddddddd$d ddddddddd!d' d(dZ.eej-e#e%fdd?ddddddddddd d)ddddddddddd*d" d+dZ.ee/Z0d,ej,krd-krnnd.d.d/d0d1d2Z1e1ej2_3ddd3dd4d!ddd5d6dd7d8d9Z4d:d;d<d=d>Z5dS)@z7Provide an enhanced dataclass that performs validation.) annotationsN) TYPE_CHECKINGAnyCallableGenericNoReturnTypeVaroverload)warn)Literal TypeGuarddataclass_transform)_config _decorators_namespace_utils _typing_extra) _dataclasses)getattr_migration) ConfigDict)PydanticUserError)Field FieldInfo PrivateAttr)PydanticDataclass)MappingNamespace) dataclassrebuild_dataclass_T )Zfield_specifiersFT. initrepreqorder unsafe_hashfrozenconfigvalidate_on_initkw_onlyslotszLiteral[False]boolz ConfigDict | type[object] | Nonez bool | Nonez-Callable[[type[_T]], type[PydanticDataclass]]) r#r$r%r&r'r(r)r*r+r,returnc CsdSNr"r0r08/tmp/pip-unpacked-wheel-zvl9l234/pydantic/dataclasses.pyrsrztype[_T]type[PydanticDataclass]) _clsr#r$r%r&r'r(r)r*r+r,r.c CsdSr/r0) r3r#r$r%r&r'r(r)r*r+r,r0r0r1r/sr#r$r%r&r'r(r)r*) r#r$r%r&r'r(r)r*r.cCsdSr/r0r4r0r0r1rBs ) r3r#r$r%r&r'r(r)r*r.c CsdSr/r0) r3r#r$r%r&r'r(r)r*r0r0r1rQs ztype[_T] | NonezGCallable[[type[_T]], type[PydanticDataclass]] | type[PydanticDataclass]c s|dkstd|dk s tdtjdkr6| | dnidddd d dd dfd d } |dkrx| S| |S)aUsage docs: https://docs.pydantic.dev/2.10/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, type[Any]None)clsr.cSs|jD]}t|dg}|D]}t||d}t|ts6qd|i}tjdkrV|jrVd|d<|jdk rj|j|d<t||t j f||j ddkri|_ |||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$setattr dataclassesfield__dict__getr8)r7Zannotation_clsr field_nameZ field_valueZ field_argsr0r0r1make_pydantic_fields_compatibles      z2dataclass..make_pydantic_fields_compatibler2c s~ddlm}||r*td|jddd|}tdd|jD}|spd k rpt|d rptd |jd td dd k r|n t |d d }t |}t j |}|j}t|rd }|f}t|trt|j} || f}t|j|}|d k r} |jr(td|jdtd dn |jp&d} tj|fd| d}||_||_|j|_|j|_d|_tj||dd|S)zCreate a Pydantic dataclass from a regular dataclass. Args: cls: The class to create the Pydantic dataclass from. Returns: A Pydantic dataclass. r)is_model_classz(Cannot create a Pydantic dataclass from z" as it is already a Pydantic modelzdataclass-on-model)codecss|]}t|VqdSr/)r@ is_dataclass).0baser0r0r1 sz6dataclass..create_dataclass..N__pydantic_config__z[`config` is set via both the `dataclass` decorator and `__pydantic_config__` for dataclass zK. The `config` specification from `dataclass` decorator will take priority.)category stacklevelzN`frozen` is set via both the `dataclass` decorator and `config` for dataclass zW.This is not recommended. The `frozen` specification on `dataclass` will take priority.FT)r#r$r%r&r'r() raise_errors)Z_internal._utilsrFr__name__any __bases__hasattrr UserWarningr;r ConfigWrapperrZDecoratorInfosbuild__doc___pydantic_dataclassesZis_builtin_dataclass issubclassr__parameters__types new_classr(r@rZ__pydantic_decorators__ __module__ __qualname____pydantic_complete__complete_dataclass) r7rFZ original_clsZhas_dataclass_baseZ config_dictZconfig_wrapperZ decoratorsZ original_docbasesZ generic_baseZfrozen_r)r%r(kwargsrEr&r$r'r0r1create_dataclasssl              z#dataclass..create_dataclassN)AssertionErrorr=r>) r3r#r$r%r&r'r(r)r*r+r,rer0rcr1ras.  #"])r )r rr)argsrdr.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)rirdr0r0r1 _call_initvar srkrM)forcerP_parent_namespace_depth_types_namespaceintzMappingNamespace | None)r7rlrPrmrnr.cCs||s|jrdSd|jkr"t|d|dk r0|}n |dkrLtj|ddpHi}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`. NZ__pydantic_core_schema__rT)Z parent_depthrl)Zparent_namespaceF)check)rP ns_resolverZ _force_build) r`rBdelattrrZparent_frame_namespacerZ NsResolverrYrarrVrL)r7rlrPrmrnZ rebuild_nsrqr0r0r1r*s&   rr5z"TypeGuard[type[PydanticDataclass]])class_r.cCs2zd|jkot|WStk r,YdSXdS)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)rBr@rHAttributeError)rsr0r0r1is_pydantic_dataclassbs ru)N)6rX __future__rZ _annotationsr@r=r\typingrrrrrrr warningsr Ztyping_extensionsr r r _internalrrrrrrYZ _migrationrr)rerrorsrfieldsrrrZ_internal._dataclassesrZ_internal._namespace_utilsr__all__rr>rArrQ __getattr__rkZInitVar__call__rrur0r0r0r1s $        *.& (*98