9CgV9 hdZddlmZddlZddlZddlZddlmZm Z m Z m Z m Z m Z mZddlmZddlmZmZmZddlmZmZmZdd lmZdd lmZdd lmZdd lm Z dd l!m"Z"m#Z#m$Z$erddl%m&Z&dZ'e dZ(ej)dkreeej*e"e$feddddddddddd dGd'Z+eej*e"e$feddddddddddd dHd+Z+n`eej*e"e$feddddddddd,dId-Z+eej*e"e$feddddddddd,dJd.Z+eej*e"e$f dKddddddddddd dLd1Z+ee,Z-d2ej)cxkrd3krnndMd8Z.e.ej/_0ddd9dd:dNdBZ1dOdFZ2dS)Pz7Provide an enhanced dataclass that performs validation.) annotationsN) TYPE_CHECKINGAnyCallableGenericNoReturnTypeVaroverload)warn)Literal TypeGuarddataclass_transform)_config _decorators _typing_extra) _dataclasses)getattr_migration) ConfigDict)PydanticUserError)Field FieldInfo PrivateAttr)PydanticDataclass) dataclassrebuild_dataclass_T )field_specifiersFT. initrepreqorder unsafe_hashfrozenconfigvalidate_on_initkw_onlyslotsr#Literal[False]r$boolr%r&r'r(r) ConfigDict | type[object] | Noner* bool | Noner+r,return-Callable[[type[_T]], type[PydanticDataclass]]c dSNr"s F/var/www/api/venv/lib/python3.11/site-packages/pydantic/dataclasses.pyrrs  _clstype[_T]type[PydanticDataclass]c dSr4r5) r8r#r$r%r&r'r(r)r*r+r,s r6rr.s #&#r7r#r$r%r&r'r(r)r*cdSr4r5r<s r6rrAs  r7cdSr4r5) r8r#r$r%r&r'r(r)r*s r6rrPs #&#r7type[_T] | NoneGCallable[[type[_T]], type[PydanticDataclass]] | type[PydanticDataclass]c  |dus Jd|dus Jdtjdkr| | d ni dd  d fd } || n | |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]r1Nonec |jD]}t|dg}|D]}t||d}t|ts)d|i}tjdkr |jrd|d<|jdur |j|d<t||tj di||j di|_ |||j |<dS) 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__getrF)rBannotation_clsr field_name field_value field_argss r6make_pydantic_fields_compatiblez2dataclass..make_pydantic_fields_compatibles"k J JN".2CRHHK) J J %c:t<< !+y99%.{#; #w..;3F.,0Jy)#4//)4)9Jv&Z):)H)HZ)H)HIII<##$566>*,C'2=j2I#J//- J  J Jr7r:c ddlm}||rtd|jdd|}  nt |dd}t j|}tj |}|j }tj |rLd}|f}t|trt|j}||fz}t!j|j|}| * } |jr t'd |jd t(d n |jpd } t+j|fd | d }||_||_ |j|_|j|_d |_tj||d d|S)zCreate a Pydantic dataclass from a regular dataclass. Args: cls: The class to create the Pydantic dataclass from. Returns: A Pydantic dataclass. r)is_model_classz(Cannot create a Pydantic dataclass from z" as it is already a Pydantic modelzdataclass-on-model)codeN__pydantic_config__zN`frozen` is set via both the `dataclass` decorator and `config` for dataclass zW.This is not recommended. The `frozen` specification on `dataclass` will take priority.)category stacklevelFT)r#r$r%r&r'r( raise_errorstypes_namespace)_internal._utilsrXr__name__rIr ConfigWrapperrDecoratorInfosbuild__doc___pydantic_dataclassesis_builtin_dataclass issubclassr__parameters__types new_classr(r UserWarningrNr__pydantic_decorators__ __module__ __qualname____pydantic_complete__complete_dataclass)rBrX original_cls config_dictconfig_wrapper decorators original_docbases generic_basefrozen_r)r%r(kwargsrVr&r$r's r6create_dataclassz#dataclass..create_dataclasss 544444 >#   #k3<kkk)   !' 2ffEZ\`8a8a  .{;; /55c:: { 5c : : 7 L FE#w'' 0&s'9: //#,66C'',,,  G$ meheqmmm( %+4uG#   #      '1#" %0'4$)!0nSXjnoooo r7N)rBrCr1rD)rBrCr1r:)rKrL)r8r#r$r%r&r'r(r)r*r+r,r|r{rVs `````` @@r6rr`s\ 5===S=== 5 ( ( (*Y ( ( ( 7""$u55!J!J!J!JFMMMMMMMMMMMMM^ $|  1A1A$1G1GGr7)r)r argsrr{rc td)a9This function does nothing but raise an error that is as similar as possible to what you'd get if you were to try calling `InitVar[int]()` without this monkeypatch. The whole purpose is just to ensure typing._type_check does not error if the type hint evaluates to `InitVar[]`. z 'InitVar' object is not callable) TypeError)rr{s r6 _call_initvarrs :;;;r7r[)forcer__parent_namespace_depth_types_namespacerBrr_rintrdict[str, Any] | Nonec|s |jrdS||}n7|dkrtj|pi}|}ni}tj||}t j|tj|j d||S)axTry to rebuild the pydantic-core schema for the dataclass. This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails. This is analogous to `BaseModel.model_rebuild`. Args: cls: The class to rebuild the pydantic-core schema for. force: Whether to force the rebuilding of the schema, defaults to `False`. raise_errors: Whether to raise errors, defaults to `True`. _parent_namespace_depth: The depth level of the parent namespace, defaults to 2. _types_namespace: The types namespace, defaults to `None`. Returns: Returns `None` if the schema is already "complete" and rebuilding was not required. If rebuilding _was_ required, returns `True` if rebuilding was successful, otherwise `False`. Nr) parent_depthF)checkr^) rqcopyrparent_frame_namespacemerge_cls_and_parent_nsrgrrrrcrZ)rBrr_rrr`frame_parent_nss r6rrs4  S. t  '5E5J5J5L5LOO&**"/"FTk"l"l"l"rpr#2"$+CCYYO$7   !#"9 G G G%+     r7class_rC"TypeGuard[type[PydanticDataclass]]c` d|jvotj|S#t$rYdSwxYw)zWhether a class is a pydantic dataclass. Args: class_: The class. 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