U EZh>@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 )field_specifiersFT. initrepreqorder unsafe_hashfrozenconfigvalidate_on_initkw_onlyslotszLiteral[False]boolz ConfigDict | type[object] | Nonez bool | Nonez-Callable[[type[_T]], type[PydanticDataclass]]) r$r%r&r'r(r)r*r+r,r-returnc CsdSNr#r1r1[/home/aprabhat/apps/x.techxrdev.in/venv/lib/python3.8/site-packages/pydantic/dataclasses.pyrsrztype[_T]type[PydanticDataclass]) _clsr$r%r&r'r(r)r*r+r,r-r/c CsdSr0r1) r4r$r%r&r'r(r)r*r+r,r-r1r1r2r/sr$r%r&r'r(r)r*r+) r$r%r&r'r(r)r*r+r/cCsdSr0r1r5r1r1r2rBs ) r4r$r%r&r'r(r)r*r+r/c CsdSr0r1) r4r$r%r&r'r(r)r*r+r1r1r2rQs 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. 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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__getr9)r8Zannotation_clsr field_nameZ field_valueZ field_argsr1r1r2make_pydantic_fields_compatibles      z2dataclass..make_pydantic_fields_compatibler3c 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. 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