zi0 BdZddlmZddlZddlZddlZddlmZm Z m Z m Z m Z m Z mZddlmZmZmZddlmZmZmZddlmZdd lmZdd lmZdd lmZmZerdd l m!Z!d Z"e dZ#ej$dkrceej%efeddddddddddd dEd%Z&eej%efeddddddddddd dFd)Z&n^eej%efeddddddddd*dGd+Z&eej%efeddddddddd*dHd,Z&eej%ef dIddddddddddd dJd/Z&ee'Z(d0ej$cxkrd1krnndKd6Z)e)ej*_+ddd7dd8dLd@Z,dMdDZ-dS)Nz7Provide an enhanced dataclass that performs validation.) annotationsN) TYPE_CHECKINGAnyCallableGenericNoReturnTypeVaroverload)Literal TypeGuarddataclass_transform)_config _decorators _typing_extra) _dataclasses)getattr_migration) ConfigDict)Field FieldInfo)PydanticDataclass) dataclassrebuild_dataclass_T )field_specifiersFT. initrepreqorder unsafe_hashfrozenconfigvalidate_on_initkw_onlyslotsr Literal[False]r!boolr"r#r$r%r& ConfigDict | type[object] | Noner' bool | Noner(r)return-Callable[[type[_T]], type[PydanticDataclass]]c dSNrs _/var/www/tmov.alphamb/tmov_inventario/venv/lib/python3.11/site-packages/pydantic/dataclasses.pyrrs  _clstype[_T]type[PydanticDataclass]c dSr1r2) r5r r!r"r#r$r%r&r'r(r)s r3rr+s r4r r!r"r#r$r%r&r'cdSr1r2r9s r3rr?s  r4cdSr1r2) r5r r!r"r#r$r%r&r's r3rrNs  r4type[_T] | NoneGCallable[[type[_T]], type[PydanticDataclass]] | type[PydanticDataclass]c  |dus Jd|dus Jdtjdkrt| |  dd  ni dd  d fd } || S| |S)a2Usage docs: https://docs.pydantic.dev/2.5/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 or not to include the field in the `__repr__` output. eq: Determines if a `__eq__` 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 an unsafe hashing function should be included in the class. frozen: Determines if the generated class should be a 'frozen' `dataclass`, which does not allow its attributes to be modified from its constructor. config: A configuration for the `dataclass` generation. 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]r.Nonec |jD]e} t||}n#t$rY wxYwt|tr,|jr%t ||tj|dfdS)a3Make sure that stdlib `dataclasses` understands `Field` kwargs like `kw_only` To do that, we simply change `x: int = pydantic.Field(..., kw_only=True)` into `x: int = dataclasses.field(default=pydantic.Field(..., kw_only=True), kw_only=True)` T)defaultr(N) __annotations__getattrAttributeError isinstancerr(setattr dataclassesfield)r? field_name field_values r3make_pydantic_fields_compatiblez2dataclass..make_pydantic_fields_compatibles"1 c c ")#z":":KK%Hk955c+:McC[->{\`-a-a-abbb c cs  ))cdSr1r2)_s r3rMz2dataclass..make_pydantic_fields_compatibles4r4r7c D|} }|t|dd}||}tj|}tj|}|j}tj|rLd}|f}t|trt|j }||fz}tj |j|}|tj|fd  d }||_||_|j|_|j|_tj||dd} | |_|S)zCreate a Pydantic dataclass from a regular dataclass. Args: cls: The class to create the Pydantic dataclass from. Returns: A Pydantic dataclass. N__pydantic_config__T)r r!r"r#r$r%F raise_errorstypes_namespace)rEr ConfigWrapperrDecoratorInfosbuild__doc___pydantic_dataclassesis_builtin_dataclass issubclassr__parameters__types new_class__name__rIr__pydantic_decorators__ __module__ __qualname__complete_dataclass__pydantic_complete__)r? original_cls config_dict cls_configconfig_wrapper decorators original_docbases generic_basepydantic_completer&r"r%kwargsrMr#r!r$s r3create_dataclassz#dataclass..create_dataclasssf    &;TBBJ%(  .{;; /55c:: { 5c : : 7 L FE#w'' 0&s'9: //#,66C'',,,#   #      '1#" %0'41D eT   %6! r4N)r?r@r.rA)r.rA)r?r@r.r7)sys version_infodict)r5r r!r"r#r$r%r&r'r(r)rornrMs `````` @@r3rr_s\ 5===S=== 5 ( ( (*Y ( ( ( 7""gU333 c c c c c"    =============~ |  D ! !!r4)r)r argsrrnrc td)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)rurns r3 _call_initvarrxs :;;;r4)forcerS_parent_namespace_depth_types_namespacer?rzrSr{intr|dict[str, Any] | Nonec|s |jrdS||}n7|dkrtj|pi}|}ni}tj||}t j|tj|j d||S)a}Try 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 build the dataclass core schema for. force: Whether to force the rebuilding of the model 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)checkrR) rdcopyrparent_frame_namespaceget_cls_types_namespacerYrcrrUrQ)r?rzrSr{r|rTframe_parent_nss r3rrs4  S. t  '5E5J5J5L5LOO&**"/"FTk"l"l"l"rpr#2"$+CCYYO$7   !#"9 G G G%+     r4__clsr@"TypeGuard[type[PydanticDataclass]]c<tj|od|jvS)zWhether a class is a pydantic dataclass. Args: __cls: The class. Returns: `True` if the class is a pydantic dataclass, `False` otherwise. __pydantic_validator__)rI is_dataclass__dict__)rs r3is_pydantic_dataclassr/s"  #E * * Y/G5>/YYr4)r r*r!r+r"r+r#r+r$r+r%r+r&r,r'r-r(r+r)r+r.r/)r5r6r r*r!r+r"r+r#r+r$r+r%r+r&r,r'r-r(r+r)r+r.r7)r r*r!r+r"r+r#r+r$r+r%r+r&r,r'r-r.r/)r5r6r r*r!r+r"r+r#r+r$r+r%r+r&r,r'r-r.r7r1)r5r<r r*r!r+r"r+r#r+r$r+r%r+r&r,r'r-r(r+r)r+r.r=)rurrnrr.r) r?r7rzr+rSr+r{r}r|r~r.r-)rr@r.r).rX __future__r _annotationsrIrpr]typingrrrrrr r typing_extensionsr r r _internalrrrrrY _migrationrr&rfieldsrr_internal._dataclassesr__all__rrqrJrr_ __getattr__rxInitVar__call__rrr2r4r3rs==222222 UUUUUUUUUUUUUUUUUUEEEEEEEEEE::::::::::<<<<<<))))))$$$$$$$$:999999 * WT]]w;+