o =n0jA @s`dZddlmZddlZddlZddlZddlmZm 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 dMd(d)Z.eej-e#e%fdeddddddddddd dNd-d)Z.n4eej-e#e%fdeddddddddd.dOd/d)Z.eej-e#e%fdeddddddddd.dPd0d)Z.eej-e#e%fd dQddddddddddd dRd3d)Z.dSd5d6Z/ee0Z1ej,d7krdTddd?dUdFdGZ5dVdKdLZ6dS)Wz7Provide 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 )Zfield_specifiersFT. initrepreqorder unsafe_hashfrozenconfigvalidate_on_initkw_onlyslotsr#Literal[False]r$boolr%r&r'r(r) ConfigDict | type[object] | Noner* bool | Noner+r,return-Callable[[type[_T]], type[PydanticDataclass]]c CdSNr"r5r5[/home/wildlama/miniconda3/envs/lam_a2e/lib/python3.10/site-packages/pydantic/dataclasses.pyrr_clstype[_T]type[PydanticDataclass]c Cr3r4r5) r8r#r$r%r&r'r(r)r*r+r,r5r5r6r/r7r#r$r%r&r'r(r)r*cCr3r4r5r;r5r5r6rB c Cr3r4r5) r8r#r$r%r&r'r(r)r*r5r5r6rQr<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]r1Nonec 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$r5)__mro__getattr isinstancersys version_infor+r$setattr dataclassesfield__dict__getrB)r?Zannotation_clsr field_nameZ field_valueZ field_argsr5r5r6make_pydantic_fields_compatibles"      z2dataclass..make_pydantic_fields_compatibler:c sddlm}||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|_tt|_ 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|VqdSr4)rJ is_dataclass).0baser5r5r6 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$r%r&r'r() raise_errors)#Z_internal._utilsrPr__name__any __bases__hasattrr UserWarningrEr ConfigWrapperrZDecoratorInfosbuild__doc___pydantic_dataclassesZis_builtin_dataclass issubclassr__parameters__types new_classr(rJr__is_pydantic_dataclass__Z__pydantic_decorators__ __module__ __qualname__ classmethod_pydantic_fields_completeZ__pydantic_fields_complete____pydantic_complete__complete_dataclass) r?rPZ original_clsZhas_dataclass_baseZ config_dictZconfig_wrapperZ decoratorsZ original_docbasesZ generic_baseZfrozen_r)r%r(kwargsrOr&r$r'r5r6create_dataclasssr             z#dataclass..create_dataclassN)r?r@r1rA)r?r@r1r:)rGrH) r8r#r$r%r&r'r(r)r*r+r,rrr5rpr6ras/   !br?cCstdd|jDS)zReturn whether the fields where successfully collected (i.e. type hints were successfully resolves). This is a private property, not meant to be used outside Pydantic. css|]}|jVqdSr4)Z _complete)rSZ field_infor5r5r6rU#sz,_pydantic_fields_complete..)allZ__pydantic_fields__values)r?r5r5r6rlsrl)r argsrrqrcOstd)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)rvrqr5r5r6 _call_initvar,srxrW)forcerZ_parent_namespace_depth_types_namespaceryrZrzintr{MappingNamespace | 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)Z__pydantic_core_schema__Z__pydantic_validator__Z__pydantic_serializer__FrT)Z parent_depthry)Zparent_namespace)check)rZ ns_resolverZ _force_build) rmrLdelattrrZparent_frame_namespacerZ NsResolverrcrnrr`rV)r?ryrZrzr{attrZ rebuild_nsrr5r5r6r6s,   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. rhF)rLrJrRAttributeError)rr5r5r6is_pydantic_dataclassss   r)r#r-r$r.r%r.r&r.r'r.r(r.r)r/r*r0r+r.r,r.r1r2)r8r9r#r-r$r.r%r.r&r.r'r.r(r0r)r/r*r0r+r.r,r.r1r:)r#r-r$r.r%r.r&r.r'r.r(r0r)r/r*r0r1r2)r8r9r#r-r$r.r%r.r&r.r'r.r(r0r)r/r*r0r1r:r4)r8r=r#r-r$r.r%r.r&r.r'r.r(r0r)r/r*r0r+r.r,r.r1r>)r?r:r1r.)rvrrqrr1r) r?r:ryr.rZr.rzr|r{r}r1r0)rr@r1r)7rb __future__rZ _annotationsrJrGrftypingrrrrrrr r warningsr Ztyping_extensionsr r _internalrrrrrrcZ _migrationrr)rerrorsrfieldsrrrZ_internal._dataclassesrZ_internal._namespace_utilsr__all__rrHrKrrlr[ __getattr__rxInitVar__call__rrr5r5r5r6s (          =  =