U fd @sUdZddlmZddlZddlZddlZddlZddlZddl m Z m Z ddlm Z m Z ddl Z ddlZddl mZddlmZmZmZmZmZmZmZmZmZmZdd lmZdd lmZmZdd l m!Z!dd l"m#Z#m$Z$dd l%m&Z&m'Z'm(Z(m)Z)m*Z*ddlm+Z+ej,rddl-m.Z.ddl/m0Z0ddl m1Z1m2Z2m3Z3ddlm4Z4m5Z5ddl6m7Z7m8Z8ddl9m:Z;ddlZ>m?Z?ddlZ d'd d?d;d"d@d;dAdBdCZ!dDd'd'd d d d d d3dE dFdGdGd@d@d@d@d@d@dHdI dJdKZ"d'd'd'd d d d d d3dL dMdGdGd@d@d@d@d@d@dNdO dPdQZ#ed3e$e%dRfd@dNdSdTdHdUdVdWZ&edXdNdYdZd[Z'd.d/d\d]d^Z(ed d3d_d'd`d@d@dad"dbdcdddeZ)ed'd'd'dfd9d.dbdbd"d;dgdhdiZ*ed'd'djd9dkdbd"d;dldmdnZ+ed'd'djd9d.dbd"d;dodpdqZ,edrdsdtdudvdwZ-edtdxdydzd{d|Z.ed.d/d}d~dZ/dddddZ0d;d;dddZ1dd;dd;dddZ2ejsVdNd.dfdd Z3dNd.d/dddZ4dNd.dddZ5dNd.d/dddZ6dd4ddZ7dd/dddZ8d.d@dddZ9ejrddddZ:dd4ddZ;dNd4ddZj?j@Z@e>j?jAZAe>j?jBZBe>j?jCZCdNd4ddZDeeEjFdd'ddd4ddZGeeEjFdd'dd$d4ddZHeEjFdd'dd'd'd d d d ddGdGd@d@d@d@ddddZIeEjFdd'dd'd'd d d d eJeJddGdGd@d@d@d@dd@d.dNd ddZKeeEjFdd'dd9d.d;dœddĄZLeeEjFdd'dd'dd'd dǜd9dddNdd@d;d˜dd̈́ZMeeEjFdd'dd'dd'd dǜd9dddNdd@d;dМdd҄ZNeeEjFdd'dd9d.d;dœddՄZOeeEjFdd'ddd9d:d.d;d<dd؄ZPeEjFdd'dd'd'd'd dڜd;dddd@d;dݜdd߄ZQeeEjFdd'dd3e$fd@dNddddZReeEjFdd'dd3e$dd@dNd.dNdddZSeeEjFdd'dd9d.d;dddZTeeEjFdd'dd.d/dddZUeEjFdd'dd.d.d.dddZVeEjFdd'dd.d.d.dddZWeeEjFdd'dd.d.d.dddZXeEjFdd'dd.d.d.dddZYZZS(r/a}Usage docs: https://docs.pydantic.dev/2.6/concepts/models/ A base class for creating Pydantic models. Attributes: __class_vars__: The names of classvars defined on the model. __private_attributes__: Metadata about the private attributes of the model. __signature__: The signature for instantiating the model. __pydantic_complete__: Whether model building is completed, or if there are still undefined fields. __pydantic_core_schema__: The pydantic-core schema used to build the SchemaValidator and SchemaSerializer. __pydantic_custom_init__: Whether the model has a custom `__init__` function. __pydantic_decorators__: Metadata containing the decorators defined on the model. This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1. __pydantic_generic_metadata__: Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these. __pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models. __pydantic_post_init__: The name of the post-init method for the model, if defined. __pydantic_root_model__: Whether the model is a `RootModel`. __pydantic_serializer__: The pydantic-core SchemaSerializer used to dump instances of the model. __pydantic_validator__: The pydantic-core SchemaValidator used to validate instances of the model. __pydantic_extra__: An instance attribute with the values of extra fields from validation when `model_config['extra'] == 'allow'`. __pydantic_fields_set__: An instance attribute with the names of fields explicitly set. __pydantic_private__: Instance attribute with the values of private attributes set on the model instance. zClassVar[ConfigDict] model_configzClassVar[dict[str, FieldInfo]] model_fieldsz&ClassVar[dict[str, ComputedFieldInfo]]model_computed_fieldszClassVar[set[str]]__class_vars__z%ClassVar[dict[str, ModelPrivateAttr]]__private_attributes__zClassVar[Signature] __signature__zClassVar[bool]__pydantic_complete__zClassVar[CoreSchema]__pydantic_core_schema__Z__pydantic_custom_init__z$ClassVar[_decorators.DecoratorInfos]__pydantic_decorators__z+ClassVar[_generics.PydanticGenericMetadata]__pydantic_generic_metadata__zClassVar[dict[str, Any] | None]__pydantic_parent_namespace__z+ClassVar[None | Literal['model_post_init']]__pydantic_post_init____pydantic_root_model__zClassVar[SchemaSerializer]__pydantic_serializer__zClassVar[SchemaValidator]__pydantic_validator__F)initdict[str, Any] | None__pydantic_extra__zset[str]__pydantic_fields_set____pydantic_private__NzXPydantic models should inherit from BaseModel, BaseModel cannot be instantiated directly validatorzbase-model-instantiated)Z val_or_sercodeZ serializer)__dict__rErDrFrNone)datareturncKsd}|jj||ddS)a/Create a new model by parsing and validating input data from keyword arguments. Raises [`ValidationError`][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model. `self` is explicitly positional-only to allow `self` as a field name. T)Z self_instanceNrAvalidate_python)selfrK__tracebackhide__rQP/var/www/html/apigroqsegura/apigroq/lib/python3.8/site-packages/pydantic/main.py__init__s zBaseModel.__init__T)rLcCs|jS)zGet extra fields set during validation. Returns: A dictionary of extra fields, or `None` if `config.extra` is not set to `"allow"`. )rDrOrQrQrR model_extraszBaseModel.model_extracCs|jS)zReturns the set of fields that have been explicitly set on this model instance. Returns: A set of strings representing the fields that have been set, i.e. that were not filled from defaults. )rErTrQrQrRmodel_fields_setszBaseModel.model_fields_set type[Model]zset[str] | Noner.)cls _fields_setvaluesrLc Ksr||}i}t}|jD]n\}}|jrR|j|krR||j||<||q||krt||||<||q|s|jdd||<q|dkr|}d}|j ddkri}|D]\} } | || <qn | |t |d|t |d||j st |d||jrZ|dt|d rn|jdk rn|D] \} } | |jkr6| |j| <q6n|j snt |d d|S) aSCreates a new instance of the `Model` class with validated data. Creates a new model setting `__dict__` and `__pydantic_fields_set__` from trusted or pre-validated data. Default values are respected, but no other validation is performed. Behaves as if `Config.extra = 'allow'` was set since it adds all passed values Args: _fields_set: The set of field names accepted for the Model instance. values: Trusted or pre-validated data dictionary. Returns: A new instance of the `Model` class with validated data. T)call_default_factoryNextraallowrIrErDrF)__new__setr4itemsaliaspopadd is_required get_defaultr3getupdate_object_setattrr?r>model_post_inithasattrrFr7) rXrYrZmZ fields_values fields_setnamefield_extrakvrQrQrRmodel_constructsB           zBaseModel.model_construct)rgdeepbool)rOrgrsrLcCs|r |n|}|r|jddkrl|D]8\}}||jkrN||j|<q0|jdkr^i|_||j|<q0n |j||j | |S)aUsage docs: https://docs.pydantic.dev/2.6/concepts/serialization/#model_copy Returns a copy of the model. Args: update: Values to change/add in the new model. Note: the data is not validated before creating the new model. You should trust this data. deep: Set to `True` to make a deep copy of the model. Returns: New model instance. r\r]N) __deepcopy____copy__r3rfr`r4rIrDrgrEkeys)rOrgrsZcopiedrprqrQrQrR model_copys     zBaseModel.model_copypython) modeincludeexcludeby_alias exclude_unsetexclude_defaults exclude_none round_tripwarningsz!Literal[('json', 'python')] | strr1zdict[str, Any]) rzr{r|r}r~rrrrrLc Cs |jj|||||||||| d S)aUsage docs: https://docs.pydantic.dev/2.6/concepts/serialization/#modelmodel_dump Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Args: mode: The mode in which `to_python` should run. If mode is 'json', the output will only contain JSON serializable types. If mode is 'python', the output may contain non-JSON-serializable Python objects. include: A list of fields to include in the output. exclude: A list of fields to exclude from the output. by_alias: Whether to use the field's alias in the dictionary key if defined. exclude_unset: Whether to exclude fields that have not been explicitly set. exclude_defaults: Whether to exclude fields that are set to their default value. exclude_none: Whether to exclude fields that have a value of `None`. round_trip: If True, dumped values should be valid as input for non-idempotent types such as Json[T]. warnings: Whether to log warnings when invalid fields are encountered. Returns: A dictionary representation of the model. ) rzr}r{r|r~rrrr)r@Z to_python) rOrzr{r|r}r~rrrrrQrQrR model_dumps!zBaseModel.model_dump indentr{r|r}r~rrrrz int | Nonestr) rr{r|r}r~rrrrrLc Cs$|jj|||||||||| d S)aUsage docs: https://docs.pydantic.dev/2.6/concepts/serialization/#modelmodel_dump_json Generates a JSON representation of the model using Pydantic's `to_json` method. Args: indent: Indentation to use in the JSON output. If None is passed, the output will be compact. include: Field(s) to include in the JSON output. exclude: Field(s) to exclude from the JSON output. by_alias: Whether to serialize using field aliases. exclude_unset: Whether to exclude fields that have not been explicitly set. exclude_defaults: Whether to exclude fields that are set to their default value. exclude_none: Whether to exclude fields that have a value of `None`. round_trip: If True, dumped values should be valid as input for non-idempotent types such as Json[T]. warnings: Whether to log warnings when invalid fields are encountered. Returns: A JSON string representation of the model. r)r@Zto_jsondecode) rOrr{r|r}r~rrrrrQrQrRmodel_dump_jsonGszBaseModel.model_dump_json validationztype[GenerateJsonSchema]r)r} ref_templateschema_generatorrzrLcCst|||||dS)aGenerates a JSON schema for a model class. Args: by_alias: Whether to use attribute aliases or not. ref_template: The reference template. schema_generator: To override the logic used to generate the JSON schema, as a subclass of `GenerateJsonSchema` with your desired modifications mode: The mode in which to generate the schema. Returns: The JSON schema for the given model class. )r}rrrz)r)rXr}rrrzrQrQrRrsszBaseModel.model_json_schemaztuple[type[Any], ...])paramsrLcCs>t|tjstddd|D}d|}|jd|dS)a}Compute the class name for parametrizations of generic classes. This method can be overridden to achieve a custom naming scheme for generic BaseModels. Args: params: Tuple of types of the class. Given a generic class `Model` with 2 type variables and a concrete model `Model[str, int]`, the value `(str, int)` would be passed to `params`. Returns: String representing the new class where `params` are passed to `cls` as type variables. Raises: TypeError: Raised when trying to generate concrete names for non-generic models. z;Concrete names should only be generated for generic models.cSs$g|]}t|tr|nt|qSrQ) isinstancerrZdisplay_as_type.0paramrQrQrR sz5BaseModel.model_parametrized_name.., []) issubclasstypingGeneric TypeErrorjoin__name__)rXrZ param_namesZparams_componentrQrQrRmodel_parametrized_names   z!BaseModel.model_parametrized_name)_BaseModel__contextrLcCsdS)zOverride this method to perform additional initialization after `__init__` and `model_construct`. This is useful if you want to do some validation that requires the entire model to be initialized. NrQ)rOrrQrQrRriszBaseModel.model_post_init)force raise_errors_parent_namespace_depth_types_namespaceintz bool | None)rrrrrLc Cs|s|jrdSd|jkr"t|d|dk r4|}nV|dkrrtj|dpJi}t|jpZi}||}t ||_n t|j}t ||}|j ddi}tj ||j tj|dd||dSdS) a1Try to rebuild the pydantic-core schema for the model. 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. Args: 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:r)Z parent_depthZ defer_buildF)check)rtypes_namespace)r9rIdelattrrrZparent_frame_namespacerZunpack_lenient_weakvaluedictr=Zbuild_lenient_weakvaluedictZget_cls_types_namespacer3Zcomplete_model_classrr ConfigWrapper) rXrrrrrZframe_parent_nsZ cls_parent_nsconfigrQrQrR model_rebuilds0      zBaseModel.model_rebuildstrictfrom_attributescontext)rXobjrrrrLcCsd}|jj||||dS)aValidate a pydantic model instance. Args: obj: The object to validate. strict: Whether to enforce types strictly. from_attributes: Whether to extract data from object attributes. context: Additional context to pass to the validator. Raises: ValidationError: If the object could not be validated. Returns: The validated model instance. TrrM)rXrrrrrPrQrQrRmodel_validateszBaseModel.model_validaterrzstr | bytes | bytearray)rX json_datarrrLcCsd}|jj|||dS)aUsage docs: https://docs.pydantic.dev/2.6/concepts/json/#json-parsing Validate the given JSON data against the Pydantic model. Args: json_data: The JSON data to validate. strict: Whether to enforce types strictly. context: Extra variables to pass to the validator. Returns: The validated Pydantic model. Raises: ValueError: If `json_data` is not a JSON string. Tr)rAZ validate_json)rXrrrrPrQrQrRmodel_validate_jsonszBaseModel.model_validate_json)rXrrrrLcCsd}|jj|||dS)aRValidate the given object contains string data against the Pydantic model. Args: obj: The object contains string data to validate. strict: Whether to enforce types strictly. context: Extra variables to pass to the validator. Returns: The validated Pydantic model. Tr)rAZvalidate_strings)rXrrrrPrQrQrRmodel_validate_stringssz BaseModel.model_validate_stringstype[BaseModel]rr")_BaseModel__source_BaseModel__handlerrLcCs"d|jkr|jds|jS||S)aHook into generating the model's CoreSchema. Args: __source: The class we are generating a schema for. This will generally be the same as the `cls` argument if this is a classmethod. __handler: Call into Pydantic's internal JSON schema generation. A callable that calls into Pydantic's internal CoreSchema generation logic. Returns: A `pydantic-core` `CoreSchema`. r:origin)rIr<r:)rXrrrQrQrR__get_pydantic_core_schema__2s  z&BaseModel.__get_pydantic_core_schema__rr)_BaseModel__core_schemarrLcCs||S)acHook into generating the model's JSON schema. Args: __core_schema: A `pydantic-core` CoreSchema. You can ignore this argument and call the handler with a new CoreSchema, wrap this CoreSchema (`{'type': 'nullable', 'schema': current_schema}`), or just call the handler with the original schema. __handler: Call into Pydantic's internal JSON schema generation. This will raise a `pydantic.errors.PydanticInvalidForJsonSchema` if JSON schema generation fails. Since this gets called by `BaseModel.model_json_schema` you can override the `schema_generator` argument to that function to change JSON schema generation globally for a type. Returns: A JSON schema, as a Python object. rQ)rXrrrQrQrR__get_pydantic_json_schema__Jsz&BaseModel.__get_pydantic_json_schema__)kwargsrLcKsdS)aThis is intended to behave just like `__init_subclass__`, but is called by `ModelMetaclass` only after the class is actually fully initialized. In particular, attributes like `model_fields` will be present when this is called. This is necessary because `__init_subclass__` will always be called by `type.__new__`, and it would require a prohibitively large refactor to the `ModelMetaclass` to ensure that `type.__new__` was called in such a manner that the class would already be sufficiently initialized. This will receive the same `kwargs` that would be passed to the standard `__init_subclass__`, namely, any kwargs passed to the class definition that aren't used internally by pydantic. Args: **kwargs: Any keyword arguments passed to the class definition that aren't used internally by pydantic. NrQrXrrQrQrR__pydantic_init_subclass__csz$BaseModel.__pydantic_init_subclass__z!type[Any] | tuple[type[Any], ...]z3type[BaseModel] | _forward_ref.PydanticRecursiveRef)typevar_valuesrLc st||}|dk r|S|tkr(tdt|ds@t|d|jdsdtj|jkrdt|dt |t st|f}t ||t t |jd|trˆr|}t|||n|jd}|s|}nt fdd|D}|jd p|}||}t d d tD}t||} | dk rH| W5QRSt||||}|dk rr|W5QRSz|jd d Wntk rYnXt||||}t|||||W5QRX|S)NzAType parameters should be placed on typing.Generic, not BaseModel__parameters__zG cannot be parametrized because it does not inherit from typing.Generic parametersz is not a generic classargsc3s|]}t|VqdSN)rZ replace_types)rargZ typevars_maprQrR sz.BaseModel.__class_getitem__..rcSsi|] }|dqSrrQrrQrQrR sz/BaseModel.__class_getitem__..)r)rZget_cached_generic_type_earlyr/rrjr<rr __bases__rtupleZcheck_parameters_countdictziprZ all_identicalrwrZZset_cached_generic_typerZiter_contained_typevarsZgeneric_recursion_self_typeZget_cached_generic_type_laterrZcreate_generic_submodel) rXrcachedZsubmodelZ parent_argsrr model_namerZmaybe_self_typerQrrR__class_getitem__vsP        zBaseModel.__class_getitem__)rOrLcCst|}||}t|dt|jt|dt|jt|dt|j|jdkr`t|ddnt|ddd|jD|S)z$Returns a shallow copy of the model.rIrDrENrFcSsi|]\}}|tk r||qSrQrrrprqrQrQrRrsz&BaseModel.__copy__..) typer^rhrrIrDrErFr`)rOrXrkrQrQrRrvs  zBaseModel.__copy__zdict[int, Any] | None)rOmemorLcCst|}||}t|dt|j|dt|dt|j|dt|dt|j|jdkrht|ddn$t|dtdd|j D|d|S) z!Returns a deep copy of the model.rI)rrDrENrFcSsi|]\}}|tk r||qSrQrrrQrQrRrsz*BaseModel.__deepcopy__..) rr^rhrrIrDrrErFr`)rOrrXrkrQrQrRrus  zBaseModel.__deepcopy__)itemrLc s8t|d}||kr||}t|dr6||t|Sz |j|WStk r~}ztt|jd||W5d}~XYnXnzt|d}Wntk rd}YnX|dk rz ||WStk r}ztt|jd||W5d}~XYnXn2t|j |rt |Stt|jd|dS)Nr7__get__ object has no attribute rD) object__getattribute__rjrrrFKeyErrorAttributeErrorr __class__super)rOrZprivate_attributes attributeexcpydantic_extrarrQrR __getattr__s*   .   . zBaseModel.__getattr__)rmvaluerLc Cs||jkr4t|d|jjd|jjd|dn\t|s|jdksR||jkr`t|||n,|j|}t |dr| ||n ||j|<dS| ||t |j|d}t |tr| ||n|jddr|j|||n|jddkr||jkrtd |jjd |d n|jddkr||jkr|jrZ||jkrZ||j|<nzt ||Wn,tk rtt|jd|YnXdS)N __delete__r) r7rjrrFrrrrrr4r __delattr__rD)rOrrrrQrQrRr,s&    ,   zBaseModel.__delattr__cCsX|jddrd}nt|j|ddr.d}ndS||f|d}tj|jj|gdS)NfrozenZfrozen_instanceFZ frozen_fieldrlocinput) r3rfrr4 pydantic_coreValidationErrorfrom_exception_datarr)rOrmrtyperrorrQrQrRrFszBaseModel._check_frozenzdict[Any, Any]cCs0|j}|rdd|D}|j|j|j|dS)NcSsi|]\}}|tk r||qSrQrrrQrQrRrWsz*BaseModel.__getstate__..)rIrDrErF)rFr`rIrDrE)rOprivaterQrQrR __getstate__TszBaseModel.__getstate__)staterLcCsDt|d|dt|d|dt|d|dt|d|ddS)NrErDrFrI)rh)rOrrQrQrR __setstate___szBaseModel.__setstate__)otherrLcCst|tr|jdp|j}|jdp*|j}||krL|j|jkrL|j|jksPdS|j|jkr`dSt|j }|j |kr|j |krdS|rt j |ndd}z||j||jkWSt k rt |j}t |j}||||kYSXntSdS)NrFTcSstjSr)rZ _SENTINEL_rQrQrRz"BaseModel.__eq__..)rr/r<rrFrDrIrr4rwoperator itemgetterrrZSafeGetItemProxyNotImplemented)rOrZ self_typeZ other_typer4getterZself_fields_proxyZother_fields_proxyrQrQrR__eq__es.       zBaseModel.__eq__zUnpack[ConfigDict])rcKsdS)aThis signature is included purely to help type-checkers check arguments to class declaration, which provides a way to conveniently set model_config key/value pairs. ```py from pydantic import BaseModel class MyModel(BaseModel, extra='allow'): ... ``` However, this may be deceiving, since the _actual_ calls to `__init_subclass__` will not receive any of the config arguments, and will only receive any keyword arguments passed during class initialization that are _not_ expected keys in ConfigDict. (This is due to the way `ModelMetaclass.__new__` works.) Args: **kwargs: Keyword arguments passed to the class definition, which set model_config Note: You may want to override `__pydantic_init_subclass__` instead, which behaves similarly but is called *after* the class is fully initialized. NrQrrQrQrR__init_subclass__szBaseModel.__init_subclass__TupleGeneratorccs6dd|jDEdH|j}|r2|EdHdS)zSo `dict(model)` works.cSs"g|]\}}|ds||fqSr) startswithrrQrQrRrs z&BaseModel.__iter__..N)rIr`rD)rOr\rQrQrR__iter__szBaseModel.__iter__cCs|d|ddS)N(r)) __repr_name__ __repr_str__rTrQrQrR__repr__szBaseModel.__repr__z_repr.ReprArgsc#sjD](\}}j|}|r |jr ||fVq ztd}Wntk r\d}YnX|dk r~dd|DEdHfddjDEdHdS)NrDcss|]\}}||fVqdSrrQrrQrQrRrsz*BaseModel.__repr_args__..c3s&|]\}}|jr|t|fVqdSr)reprrrrTrQrRrs) rIr`r4rfr rrrr5)rOrprqrnrrQrTrR __repr_args__s    zBaseModel.__repr_args__cCs |dS)N )r rTrQrQrR__str__szBaseModel.__str__EThe `__fields__` attribute is deprecated, use `model_fields` instead.categoryzdict[str, FieldInfo]cCstjdtd|jS)Nrr)rwarnrr4rTrQrQrR __fields__s zBaseModel.__fields__MThe `__fields_set__` attribute is deprecated, use `model_fields_set` instead.cCstjdtd|jS)Nrr)rrrrErTrQrQrR__fields_set__s zBaseModel.__fields_set__:The `dict` method is deprecated; use `model_dump` instead.r{r|r}r~rrztyping.Dict[str, Any])r{r|r}r~rrrLcCs$tjdtd|j||||||dS)Nrrr)rrrr)rOr{r|r}r~rrrQrQrRrs zBaseModel.dict?The `json` method is deprecated; use `model_dump_json` instead.)r{r|r}r~rrencodermodels_as_dictz"typing.Callable[[Any], Any] | None) r{r|r}r~rrrr dumps_kwargsrLc KsPtjdtd|tk rtd|tk r.td| r:td|j||||||dS)NrrzMThe `encoder` argument is no longer supported; use field serializers instead.zUThe `models_as_dict` argument is no longer supported; use a model serializer instead.z9`dumps_kwargs` keyword arguments are no longer supported.r)rrrrrr) rOr{r|r}r~rrrrrrQrQrRjson s$zBaseModel.jsonCThe `parse_obj` method is deprecated; use `model_validate` instead.)rXrrLcCstjdtd||S)NrrrrrrrXrrQrQrR parse_obj*s zBaseModel.parse_objThe `parse_raw` method is deprecated; if your data is JSON use `model_validate_json`, otherwise load the data then use `model_validate` instead.utf8) content_typeencodingproto allow_picklez str | bytes str | NonezDeprecatedParseProtocol | None)rXbr%r&r'r(rLc Cstjdtdddlm}z|j|||||d}Wnttfk r}zlddl} t |t r`d} n&t || j rrd} nt |trd } nd } t | t|d |d } t j|j| gW5d}~XYnX||S) Nr#rr parser'r%r&r(rzvalue_error.unicodedecodezvalue_error.jsondecodeZ value_errorZ type_error)Z__root__r)rrr deprecatedr,Zload_str_bytesrrrrUnicodeDecodeErrorJSONDecodeErrorrZPydanticCustomErrorrrrrr) rXr*r%r&r'r(r,rrrZtype_strrrQrQrR parse_raw2s8     $zBaseModel.parse_rawThe `parse_file` method is deprecated; load the data from file, then if your data is JSON use `model_validate_json`, otherwise `model_validate` instead.z str | Path)rXpathr%r&r'r(rLcCs8tjdtdddlm}|j|||||d}||S)Nr2rr r+r-)rrrr.r,Z load_filer")rXr3r%r&r'r(r,rrQrQrR parse_filegs zBaseModel.parse_fileqThe `from_orm` method is deprecated; set `model_config['from_attributes']=True` and use `model_validate` instead.cCs2tjdtd|jdds(tddd||S)Nr5rrzHYou must set the config attribute `from_attributes=True` to use from_ormrH)rrrr3rfrrr!rQrQrRfrom_ormszBaseModel.from_ormDThe `construct` method is deprecated; use `model_construct` instead.cKs"tjdtd|jfd|i|S)Nr8rrY)rrrrr)rXrYrZrQrQrR constructs zBaseModel.constructThe `copy` method is deprecated; use `model_copy` instead. See the docstring of `BaseModel.copy` for details about how to handle `include` and `exclude`.)r{r|rgrsz+AbstractSetIntStr | MappingIntStrAny | Noneztyping.Dict[str, Any] | None)rOr{r|rgrsrLc Cstjdtdddlm}t|j|dd||ddf|p8i}|jdkrLd}ndd |jD}|j dkrpd}nR|j }t |j D]} | |kr| | qt |D]} | |j kr| | || <q|r|j |B} n t|j } |r| t|8} |j||| |||d S) aReturns a copy of the model. !!! warning "Deprecated" This method is now deprecated; use `model_copy` instead. If you need `include` or `exclude`, use: ```py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) ``` Args: include: Optional set or mapping specifying which fields to include in the copied model. exclude: Optional set or mapping specifying which fields to exclude in the copied model. update: Optional dictionary of field-value pairs to override field values in the copied model. deep: If True, the values of fields that are Pydantic models will be deep-copied. Returns: A copy of the model with included, excluded and updated fields as specified. r:rr copy_internalsF)Zto_dictr}r{r|r~NcSsi|]\}}|tk r||qSrQrrrQrQrRrsz"BaseModel.copy..)rs)rrrr.r<r_iterrFr`rDrlistrbrErwr__copy_and_set_values) rOr{r|rgrsr<rZrr\rprlrQrQrRrsF#         zBaseModel.copyCThe `schema` method is deprecated; use `model_json_schema` instead.)r}rrLcCstjdtd|j||dS)Nr@rr}r)rrrr)rXr}rrQrQrRschemas zBaseModel.schemaWThe `schema_json` method is deprecated; use `model_json_schema` and json.dumps instead.rA)r}rrrLcKsBtjdtdddl}ddlm}|j|j||dfd|i|S)NrCrrr )pydantic_encoderrAdefault)rrrrZdeprecated.jsonrDdumpsr)rXr}rrrrDrQrQrR schema_jsons  zBaseModel.schema_jsonBThe `validate` method is deprecated; use `model_validate` instead.)rXrrLcCstjdtd||S)NrHrr )rXrrQrQrRvalidate s zBaseModel.validateLThe `update_forward_refs` method is deprecated; use `model_rebuild` instead.)localnsrLcKs*tjdtd|rtd|jdddS)NrJrz,`localns` arguments are not longer accepted.T)r)rrrrr)rXrKrQrQrRupdate_forward_refsszBaseModel.update_forward_refsHThe private method `_iter` will be removed and should no longer be used.)rrrLcOs,tjdtdddlm}|j|f||S)NrMrr r;)rrrr.r<r=rOrrr<rQrQrRr="s  zBaseModel._iterWThe private method `_copy_and_set_values` will be removed and should no longer be used.cOs,tjdtdddlm}|j|f||S)NrOrr r;)rrrr.r<r?rNrQrQrRr?.s  zBaseModel._copy_and_set_valuesMThe private method `_get_value` will be removed and should no longer be used.cOs,tjdtdddlm}|j|f||S)NrPrr r;)rrrr.r< _get_value)rXrrr<rQrQrRrQ;s  zBaseModel._get_valueRThe private method `_calculate_keys` will be removed and should no longer be used.cOs,tjdtdddlm}|j|f||S)NrRrr r;)rrrr.r<_calculate_keysrNrQrQrRrSIs  zBaseModel._calculate_keys)N)N)N)[r __module__ __qualname____doc__r TYPE_CHECKING__annotations___FieldrDrErFr4r5r ZDecoratorInfosr;r=rZ MockValSerrAr@ __slots__rr3r9r?rSZ__pydantic_base_init__rrUrV classmethodrrrxrrrrrrrirrrrrrrrrvrurrrrrrrrrr rrZRepresentationr r Z __pretty__Z __rich_repr__rtyping_extensionsr.rrrrrr"r1r4r7r9rrBrGrIrLr=r?rQrS __classcell__rQrQrrRr/=s   9$1$,7@ + 7   &  "/ "  G      ) metaclass) __config__rV__base__rT__validators____cls_kwargs__rzConfigDict | Noner)rJzdict[str, classmethod] | NonerCrr) __model_namer_rVr`rTrarbfield_definitionsrLcKsdSrrQrcr_rVr`rTrarbrdrQrQrRr2Ws r2)r_rVrTrarbz%type[Model] | tuple[type[Model], ...]rWcKsdSrrQrerQrQrRr2fs )r_rVr`rTrarbrZz,type[Model] | tuple[type[Model], ...] | Noneztuple[str, ...] | None) rcr_rVr`rTrarbrZrdrLc Ks|dk rtdt|dk rB|dk r0tdddt|tsV|f}nttjdt f}|p\i}i} i} | D]\} } t | std| dtt| trtd | } z | \} }Wqt k r}ztd d d|W5d}~XYqXn d| } }| r| | | <|| | <qn|dkr*td }|jd }| |d}|rH|d|i|rX|||| |rxt|j|d<t|}tj|||d\}}}||k r||d<||||||fd|d|S)aUsage docs: https://docs.pydantic.dev/2.6/concepts/models/#dynamic-model-creation Dynamically creates and returns a new Pydantic model, in other words, `create_model` dynamically creates a subclass of [`BaseModel`][pydantic.BaseModel]. Args: __model_name: The name of the newly created model. __config__: The configuration of the new model. __doc__: The docstring of the new model. __base__: The base class or classes for the new model. __module__: The name of the module that the model belongs to; if `None`, the value is taken from `sys._getframe(1)` __validators__: A dictionary of methods that validate fields. __cls_kwargs__: A dictionary of keyword arguments for class creation, such as `metaclass`. __slots__: Deprecated. Should not be passed to `create_model`. **field_definitions: Attributes of the new model. They should be passed in the format: `=(, )` or `=(, )`. Returns: The new [model][pydantic.BaseModel]. Raises: PydanticUserError: If `__base__` and `__config__` are both passed. Nz.__slots__ should not be passed to create_modelzFto avoid confusion `__config__` and `__base__` cannot be used togetherzcreate-model-config-baser6r.z3fields may not start with an underscore, ignoring "rztuple[str, Any]z4Field definitions should be a `(, )`.zcreate-model-field-definitionsr r)rXrTrVr3)kwds__orig_bases__F)Z#__pydantic_reset_parent_namespace__Z_create_model_module)rrRuntimeWarningrrrrcastTyper/r`r rrsys _getframe f_globalsrgr rZ config_dicttypes resolve_bases prepare_class)rcr_rVr`rTrarbrZrdfieldsrf_nameZf_defZ f_annotationZf_valueef namespaceresolved_basesmetansrfrQrQrRr2ust$                 )TrV __future__r _annotationsrrkrnrrrrrrrr\r _internalr r r r rrrrrr _migrationrZannotated_handlersrrrrerrorsrr json_schemarrrrrrrWinspectr pathlibr!r"r#r$r%r&Z_internal._utilsr'r(Zdeprecated.parser)ZDeprecatedParseProtocolrqr*r+r,r-rY GeneratorTuplerrTypeVarr.r1rXDeprecationWarning__all__Zobject_setattrrhZModelMetaclassr/overloadrr2rrQrQrQrRs  0       $$$$g