codekingpro/portable-devtools
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S \S' S\S ' S \S ' S \S ' S!\S"' S#\S$' S%\S&' \R " S S'9rS(\S)' \R " S S'9rS*\S+' \R " S S'9rS(\S,' \( d5 \R* " S-S.S/9r\R. " S-S0S.S19r\R. " S-S2S.S19rS3rS�S4 jrS5\l \ R< \ S�S6 j5 5 r \ R< \ S�S7 j5 5 r!\"S�S8 j5 r#\"S�S9 j5 r$\ S�S�S: jj5 r%SS S;.S�S< jjr&S=SSSSS S S S S S5SS SS>. S�S? jjr'SS SSSSS S S S S S5SS SS@. S�SA jjr(\ S5\)\*SB4SCSD. S�SE jjj5 r+\ S�SF j5 r,S�SG jr-\ S S5SHSSI. S�SJ jj5 r.\ SSSSSSSK. S�SL jj5 r/\ SSSSSSM. S�SN jj5 r0\ SSSSSSM. S�SO jj5 r1\ S�SP j5 r2\ S�SQ j5 r3\ S�SR j5 r4\ S�SS j5 r5 S�ST jr6S�SU jr7S�S�SV jjr8\( d S�U 4SW jjr9S�SX jr:S�SY jr;S�SZ jr<S�S[ jr=S�S\ jr>S�S] jr?\( d S�S^ jr@\( a S�S_ jrAS�S` jrBS�Sa jrCS�Sb jrD\ER� R� rG\ER� R� rH\ER� R� rI\ER� R� rJ\ER� R� rKS�Sc jrL\"\MR� " SdSSe9S�Sf j5 5 rO\"\MR� " SgSSe9S�Sh j5 5 rP\MR� " SiSSe9SSS S S S Sj. S�Sk jj5 rQ\MR� " SlSSe9SSS S S S \R\RSm. S�Sn jj5 rS\ \MR� " SoSSe9S�Sp j5 5 rT\ \MR� " SqSSe9SSrSS Ss. S�St jj5 5 rU\ \MR� " SuSSe9SSrSS Ss. S�Sv jj5 5 rV\ \MR� " SwSSe9S�Sx j5 5 rW\ \MR� " SySSe9S�S�Sz jj5 5 rX\MR� " S{SSe9SSSS S|. S�S} jj5 rY\ \MR� " S~SSe9S5\)4 S�S jj5 5 rZ\ \MR� " S�SSe9S5\)S�. S�S� jj5 5 r[\ \MR� " S�SSe9S�S� j5 5 r\\ \MR� " S�SSe9S�S� j5 5 r]\MR� " S�SSe9S�S� j5 r^\MR� " S�SSe9S�S� j5 r_\ \MR� " S�SSe9S�S� j5 5 r`\MR� " S�SSe9S�S� j5 raS�rbU =rc$ )�rC �w a� !!! abstract "Usage Documentation"32 [Models](../concepts/models.md)33 34A base class for creating Pydantic models.35 36Attributes:37 __class_vars__: The names of the class variables defined on the model.38 __private_attributes__: Metadata about the private attributes of the model.39 __signature__: The synthesized `__init__` [`Signature`][inspect.Signature] of the model.40 41 __pydantic_complete__: Whether model building is completed, or if there are still undefined fields.42 __pydantic_core_schema__: The core schema of the model.43 __pydantic_custom_init__: Whether the model has a custom `__init__` function.44 __pydantic_decorators__: Metadata containing the decorators defined on the model.45 This replaces `Model.__validators__` and `Model.__root_validators__` from Pydantic V1.46 __pydantic_generic_metadata__: A dictionary containing metadata about generic Pydantic models.47 The `origin` and `args` items map to the [`__origin__`][genericalias.__origin__]48 and [`__args__`][genericalias.__args__] attributes of [generic aliases][types-genericalias],49 and the `parameter` item maps to the `__parameter__` attribute of generic classes.50 __pydantic_parent_namespace__: Parent namespace of the model, used for automatic rebuilding of models.51 __pydantic_post_init__: The name of the post-init method for the model, if defined.52 __pydantic_root_model__: Whether the model is a [`RootModel`][pydantic.root_model.RootModel].53 __pydantic_serializer__: The `pydantic-core` `SchemaSerializer` used to dump instances of the model.54 __pydantic_validator__: The `pydantic-core` `SchemaValidator` used to validate instances of the model.55 56 __pydantic_fields__: A dictionary of field names and their corresponding [`FieldInfo`][pydantic.fields.FieldInfo] objects.57 __pydantic_computed_fields__: A dictionary of computed field names and their corresponding [`ComputedFieldInfo`][pydantic.fields.ComputedFieldInfo] objects.58 59 __pydantic_extra__: A dictionary containing extra values, if [`extra`][pydantic.config.ConfigDict.extra]60 is set to `'allow'`.61 __pydantic_fields_set__: The names of fields explicitly set during instantiation.62 __pydantic_private__: Values of private attributes set on the model instance.63zClassVar[ConfigDict]rO zClassVar[set[str]]�__class_vars__z%ClassVar[Dict[str, ModelPrivateAttr]]�__private_attributes__zClassVar[Signature]�
__signature__FzClassVar[bool]�__pydantic_complete__zClassVar[CoreSchema]�__pydantic_core_schema__�__pydantic_custom_init__z$ClassVar[_decorators.DecoratorInfos]�__pydantic_decorators__z+ClassVar[_generics.PydanticGenericMetadata]� __pydantic_generic_metadata__Nz ClassVar[Dict[str, Any] | None]� __pydantic_parent_namespace__z+ClassVar[None | Literal['model_post_init']]�__pydantic_post_init__�__pydantic_root_model__zClassVar[SchemaSerializer]�__pydantic_serializer__z4ClassVar[SchemaValidator | PluggableSchemaValidator]rk z ClassVar[Dict[str, FieldInfo]]rR z:ClassVar[Dict[str, Callable[[BaseModel, str, Any], None]]]� __pydantic_setattr_handlers__z&ClassVar[Dict[str, ComputedFieldInfo]]� __pydantic_computed_fields__z"ClassVar[PydanticExtraInfo | None]�__pydantic_extra_info__)�init�Dict[str, Any] | None�__pydantic_extra__�set[str]r_ rf zXPydantic models should inherit from BaseModel, BaseModel cannot be instantiated directlyzbase-model-instantiated��code� validator)�64val_or_serr� �65serializer)r^ r_ r� rf c �n � SnU R R XS9nXLa [ R " SSS9 gg)a Create a new model by parsing and validating input data from keyword arguments.66 67Raises [`ValidationError`][pydantic_core.ValidationError] if the input data cannot be68validated to form a valid model.69 70`self` is explicitly positional-only to allow `self` as a field name.71T)�
self_instancea* A custom validator is returning a value other than `self`.72Returning anything other than `self` from a top level model validator isn't supported when validating via `__init__`.73See the `model_validator` docs (https://docs.pydantic.dev/latest/concepts/validators/#model-validators) for more details.� ��74stacklevelN)rk �validate_python�warnings�warn)�self�data�__tracebackhide__�validated_selfs rY �__init__�BaseModel.__init__� sE � � !�� �4�4�D�D�T�D�^�� � %� �M�M�L� �
� &r[ Tc � � [ U S0 5 $ )a A mapping of field names to their respective [`FieldInfo`][pydantic.fields.FieldInfo] instances.75 76!!! warning77 Accessing this attribute from a model instance is deprecated, and will not work in Pydantic V3.78 Instead, you should access this attribute from the model class.79rR �rQ ��clss rY � model_fields�BaseModel.model_fields s � � �s� 1�2�6�6r[ c � � [ U S0 5 $ )a/ A mapping of computed field names to their respective [`ComputedFieldInfo`][pydantic.fields.ComputedFieldInfo] instances.80 81!!! warning82 Accessing this attribute from a model instance is deprecated, and will not work in Pydantic V3.83 Instead, you should access this attribute from the model class.84r� r� r� s rY �model_computed_fields� BaseModel.model_computed_fields s � � �s� :�B�?�?r[ c � � U R $ )z�Get extra fields set during validation.85 86Returns:87 A dictionary of extra fields, or `None` if `config.extra` is not set to `"allow"`.88)r� �r� s rY � model_extra�BaseModel.model_extra) s � � �&�&�&r[ c � � U R $ )z�Returns the set of fields that have been explicitly set on this model instance.89 90Returns:91 A set of strings representing the fields that have been set,92 i.e. that were not filled from defaults.93)r_ r� s rY �model_fields_set�BaseModel.model_fields_set2 s � � �+�+�+r[ c �p � U R U 5 n0 n[ 5 nU R R 5 GH� u pgUR b> UR U; a. UR UR 5 XF' UR
U5 Xe; a� UR b� [ UR [ 5 ( a UR R O UR /nU H� n [ U [ 5 ( a+ X�; a& UR U 5 XF' UR
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U5 GMj UR 5 ( a GM� UR! SUS9XF' GM� Uc UnU R" R% S5 S:X a UOSn [' USU5 [' USU5 U R( ( d [' USU 5 [' US S5 U R* ( ag UR- S5 [/ US 5 ( aE UR0 b8 UR 5 H$ u p�X�R2 ; d M X�R0 U ' M& U$ )96a� Creates a new instance of the `Model` class with validated data.97 98Creates a new model setting `__dict__` and `__pydantic_fields_set__` from trusted or pre-validated data.99Default values are respected, but no other validation is performed.100 101!!! note102 `model_construct()` generally respects the `model_config.extra` setting on the provided model.103 That is, if `model_config.extra == 'allow'`, then all extra passed values are added to the model instance's `__dict__`104 and `__pydantic_extra__` fields. If `model_config.extra == 'ignore'` (the default), then all extra passed values are ignored.105 Because no validation is performed with a call to `model_construct()`, having `model_config.extra == 'forbid'` does not result in106 an error if extra values are passed, but they will be ignored.107 108Args:109 _fields_set: A set of field names that were originally explicitly set during instantiation. If provided,110 this is directly used for the [`model_fields_set`][pydantic.BaseModel.model_fields_set] attribute.111 Otherwise, the field names from the `values` argument will be used.112 values: Trusted or pre-validated data dictionary.113 114Returns:115 A new instance of the `Model` class with validated data.116NT)�call_default_factory�validated_data�extra�allowr^ r_ r� rf )�__new__�setrR �items�alias�popr` �validation_alias�117isinstancer( �choices�strr) �search_dict_for_pathr � is_required� get_defaultrO rP rq r� r� �model_post_init�hasattrrf ry )r� � _fields_set�values�m�
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� � �d� #��q�0�1�1�a�6L�6L�6X� "�L�L�N�D�A�� 4� 4�4�45�.�.�q�1� +� �r[ )�update�deepc �� � U( a U R 5 OU R 5 nU( a� U R R S5 S:X a[ UR 5 HF u pEX@R120 ; a XSR U' M$ UR c 0 Ul XSR U' MH OUR R U5 UR R UR 5 5 U$ )av !!! abstract "Usage Documentation"121 [`model_copy`](../concepts/models.md#model-copy)122 123Returns a copy of the model.124 125!!! note126 The underlying instance's [`__dict__`][object.__dict__] attribute is copied. This127 might have unexpected side effects if you store anything in it, on top of the model128 fields (e.g. the value of [cached properties][functools.cached_property]).129 130Args:131 update: Values to change/add in the new model. Note: the data is not validated132 before creating the new model. You should trust this data.133 deep: Set to `True` to make a deep copy of the model.134 135Returns:136 New model instance.137r� r� ) � __deepcopy__�__copy__rO rP r� rR r^ r� r� r_ �keys)r� r� r� �copiedr� r� s rY �138model_copy�BaseModel.model_copy� s� � �& )-��"�"�$�$�-�-�/�� �� � �$�$�W�-��8� "�L�L�N�D�A�� 4� 4�4�-.����*�!�4�4�<�8:�F� 5�78�1�1�!�4�
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US9$ )aX !!! abstract "Usage Documentation"141 [`model_dump`](../concepts/serialization.md#python-mode)142 143Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.144 145Args:146 mode: The mode in which `to_python` should run.147 If mode is 'json', the output will only contain JSON serializable types.148 If mode is 'python', the output may contain non-JSON-serializable Python objects.149 include: A set of fields to include in the output.150 exclude: A set of fields to exclude from the output.151 context: Additional context to pass to the serializer.152 by_alias: Whether to use the field's alias in the dictionary key if defined.153 exclude_unset: Whether to exclude fields that have not been explicitly set.154 exclude_defaults: Whether to exclude fields that are set to their default value.155 exclude_none: Whether to exclude fields that have a value of `None`.156 exclude_computed_fields: Whether to exclude computed fields.157 While this can be useful for round-tripping, it is usually recommended to use the dedicated158 `round_trip` parameter instead.159 round_trip: If True, dumped values should be valid as input for non-idempotent types such as Json[T].160 warnings: How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors,161 "error" raises a [`PydanticSerializationError`][pydantic_core.PydanticSerializationError].162 fallback: A function to call when an unknown value is encountered. If not provided,163 a [`PydanticSerializationError`][pydantic_core.PydanticSerializationError] error is raised.164 serialize_as_any: Whether to serialize fields with duck-typing serialization behavior.165 polymorphic_serialization: Whether to use model and dataclass polymorphic serialization for this call.166 167Returns:168 A dictionary representation of the model.169)r� r� r� r� r� r� r� r� r� r� r� r� r� r� )r� � to_python)r� r� r� r� r� r� r� r� r� r� r� r� r� r� r� s rY �170model_dump�BaseModel.model_dump� sP � �` �+�+�5�5� �� ����'� -�%�$;�!� � � -�&?� 6� 171� 172r[ ��indent� ensure_asciir� r� r� r� r� r� r� r� r� r� r� r� r� c �n � U R R U UUUUUUUUU U173U U U
UUS9R 5 $ )aW !!! abstract "Usage Documentation"174 [`model_dump_json`](../concepts/serialization.md#json-mode)175 176Generates a JSON representation of the model using Pydantic's `to_json` method.177 178Args:179 indent: Indentation to use in the JSON output. If None is passed, the output will be compact.180 ensure_ascii: If `True`, the output is guaranteed to have all incoming non-ASCII characters escaped.181 If `False` (the default), these characters will be output as-is.182 include: Field(s) to include in the JSON output.183 exclude: Field(s) to exclude from the JSON output.184 context: Additional context to pass to the serializer.185 by_alias: Whether to serialize using field aliases.186 exclude_unset: Whether to exclude fields that have not been explicitly set.187 exclude_defaults: Whether to exclude fields that are set to their default value.188 exclude_none: Whether to exclude fields that have a value of `None`.189 exclude_computed_fields: Whether to exclude computed fields.190 While this can be useful for round-tripping, it is usually recommended to use the dedicated191 `round_trip` parameter instead.192 round_trip: If True, dumped values should be valid as input for non-idempotent types such as Json[T].193 warnings: How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors,194 "error" raises a [`PydanticSerializationError`][pydantic_core.PydanticSerializationError].195 fallback: A function to call when an unknown value is encountered. If not provided,196 a [`PydanticSerializationError`][pydantic_core.PydanticSerializationError] error is raised.197 serialize_as_any: Whether to serialize fields with duck-typing serialization behavior.198 polymorphic_serialization: Whether to use model and dataclass polymorphic serialization for this call.199 200Returns:201 A JSON string representation of the model.202r� )r� �to_json�decode)r� r� r� r� r� r� r� r� r� r� r� r� r� r� r� r� s rY �model_dump_json�BaseModel.model_dump_json� s\ � �b �+�+�3�3� ��%���� �'� -�%�$;�!� � � -�&?�! 4� 203�" �&�(�# r[ �204validation�any_of)� union_formatc � � [ U UUUUUS9$ )a Generates a JSON schema for a model class.205 206Args:207 by_alias: Whether to use attribute aliases or not.208 ref_template: The reference template.209 union_format: The format to use when combining schemas from unions together. Can be one of:210 211 - `'any_of'`: Use the [`anyOf`](https://json-schema.org/understanding-json-schema/reference/combining#anyOf)212 keyword to combine schemas (the default).213 - `'primitive_type_array'`: Use the [`type`](https://json-schema.org/understanding-json-schema/reference/type)214 keyword as an array of strings, containing each type of the combination. If any of the schemas is not a primitive215 type (`string`, `boolean`, `null`, `integer` or `number`) or contains constraints/metadata, falls back to216 `any_of`.217 schema_generator: To override the logic used to generate the JSON schema, as a subclass of218 `GenerateJsonSchema` with your desired modifications219 mode: The mode in which to generate the schema.220 221Returns:222 The JSON schema for the given model class.223)r� � ref_templater� �schema_generatorr� )r4 )r� r� r� r� r� r� s rY r4 �BaseModel.model_json_schema1 s# � �< !� � �%�%� -��
224� 225r[ c � � [ U [ 5 ( d [ S5 eU Vs/ s H0 n[ U[ 5 ( a UO[226 R " U5 PM2 nnSR U5 nU R SU S3$ s snf )a- Compute the class name for parametrizations of generic classes.227 228This method can be overridden to achieve a custom naming scheme for generic BaseModels.229 230Args:231 params: Tuple of types of the class. Given a generic class232 `Model` with 2 type variables and a concrete model `Model[str, int]`,233 the value `(str, int)` would be passed to `params`.234 235Returns:236 String representing the new class where `params` are passed to `cls` as type variables.237 238Raises:239 TypeError: Raised when trying to generate concrete names for non-generic models.240z;Concrete names should only be generated for generic models.�, �[�]) �241issubclassr � TypeErrorr� r� r$ �display_as_type�joinrT )r� �params�param� param_names�params_components rY �model_parametrized_name�!BaseModel.model_parametrized_nameX s� � �" �#�w�'�'�� Y�Z� Z�242 gm�m�fl�]b�243�5�#� 6� 6�u�E�<Q�<Q�RW�<X�X�fl� �m� �9�9�[�1���,�,� �q�!1� 2�!�4�4�� ns �7Bc � � g)z�Override this method to perform additional initialization after `__init__` and `model_construct`.244This is useful if you want to do some validation that requires the entire model to be initialized.245N� )r� r� s rY r� �BaseModel.model_post_inits � � r[ r� )�force� raise_errors�_parent_namespace_depth�_types_namespacec �6 � U R nU( a U( d gSU l S HI nX`R ; d M [ [ X5 [ R246 5 ( a M> [
X5 MK Ub UnO'US:� a [ R " USS9=( d 0 nO0 n[ R " U R 5 =( d 0 n[ R " 0 UEUES9n [ R " U [ R " U R" SS9U UU( + US 9$ )247a� Try to rebuild the pydantic-core schema for the model.248 249This may be necessary when one of the annotations is a ForwardRef which could not be resolved during250the initial attempt to build the schema, and automatic rebuilding fails.251 252Args:253 force: Whether to force the rebuilding of the model schema, defaults to `False`.254 raise_errors: Whether to raise errors, defaults to `True`.255 _parent_namespace_depth: The depth level of the parent namespace, defaults to 2.256 _types_namespace: The types namespace, defaults to `None`.257 258Returns:259 Returns `None` if the schema is already "complete" and rebuilding was not required.260 If rebuilding _was_ required, returns `True` if rebuilding was successful, otherwise `False`.261NF)r| rk r� r T)� parent_depthr )�parent_namespace)�check)r262 �call_on_complete_hook�is_force_rebuild)r{ r^ r� rQ r! �263MockValSer�delattrr% �parent_frame_namespacer" � unpack_lenient_weakvaluedictr� r# �264NsResolver�complete_model_classr �
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model_rebuild�BaseModel.model_rebuildx s � �0 �4�4�� �E��$)��!�e�D��|�|�#�J�w�s�7I�=�Kc�Kc�,d�,d�269 ��"�
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(�&�=�=�Kb�jn�o�u�su�J��J�'�D�D�S�Ef�Ef�g�m�km� �&�1�1� 8�270� 8�i� 8�271� � #�7�7� � � !� !�#�"2�"2�%� @� �%�&6�"6� "�272� 273r[ ��strictr� �from_attributesr� r� �by_namec 274 �l � SnUSL a USLa275 [ SSS9eU R R UUUUUUUS9$ )a� Validate a pydantic model instance.276 277Args:278 obj: The object to validate.279 strict: Whether to enforce types strictly.280 extra: Whether to ignore, allow, or forbid extra data during model validation.281 See the [`extra` configuration value][pydantic.ConfigDict.extra] for details.282 from_attributes: Whether to extract data from object attributes.283 context: Additional context to pass to the validator.284 by_alias: Whether to use the field's alias when validating against the provided input data.285 by_name: Whether to use the field's name when validating against the provided input data.286 287Raises:288 ValidationError: If the object could not be validated.289 290Returns:291 The validated model instance.292TF�<At least one of `by_alias` or `by_name` must be set to True.� validate-by-alias-and-name-falser� r! )r/ rk r� ) r� �objr" r� r# r� r� r$ r� s rY �model_validate�BaseModel.model_validate� sa � �> !�� �u� ���!4�#�N�7��
�293 �)�)�9�9� ��� +�� �� :� 294� 295r[ �r" r� r� r� r$ c �d � SnUSL a USLa296 [ SSS9eU R R XX4XVS9$ )a$ !!! abstract "Usage Documentation"297 [JSON Parsing](../concepts/json.md#json-parsing)298 299Validate the given JSON data against the Pydantic model.300 301Args:302 json_data: The JSON data to validate.303 strict: Whether to enforce types strictly.304 extra: Whether to ignore, allow, or forbid extra data during model validation.305 See the [`extra` configuration value][pydantic.ConfigDict.extra] for details.306 context: Extra variables to pass to the validator.307 by_alias: Whether to use the field's alias when validating against the provided input data.308 by_name: Whether to use the field's name when validating against the provided input data.309 310Returns:311 The validated Pydantic model.312 313Raises:314 ValidationError: If `json_data` is not a JSON string or the object could not be validated.315TFr& r' r� r+ )r/ rk �
validate_json)r� � json_datar" r� r� r� r$ r� s rY �model_validate_json� BaseModel.model_validate_json� sT � �@ !�� �u� ���!4�#�N�7��
�316 �)�)�7�7� �E�X� 8� 317� 318r[ c �d � SnUSL a USLa319 [ SSS9eU R R XX4XVS9$ )a Validate the given object with string data against the Pydantic model.320 321Args:322 obj: The object containing string data to validate.323 strict: Whether to enforce types strictly.324 extra: Whether to ignore, allow, or forbid extra data during model validation.325 See the [`extra` configuration value][pydantic.ConfigDict.extra] for details.326 context: Extra variables to pass to the validator.327 by_alias: Whether to use the field's alias when validating against the provided input data.328 by_name: Whether to use the field's name when validating against the provided input data.329 330Returns:331 The validated Pydantic model.332TFr& r' r� r+ )r/ rk �validate_strings)r� r( r" r� r� r� r$ r� s rY �model_validate_strings� BaseModel.model_validate_strings sS � �4 !�� �u� ���!4�#�N�7��
�333 �)�)�:�:� �e�x� ;� 334� 335r[ c �� � [ R " S[ SS9 U R R S5 nUb+ [ U[ R 5 ( d U R $ U" U5 $ )Na> The `__get_pydantic_core_schema__` method of the `BaseModel` class is deprecated. If you are calling `super().__get_pydantic_core_schema__` when overriding the method on a Pydantic model, consider using `handler(source)` instead. However, note that overriding this method on models can lead to unexpected side effects.r� r� r| ) r� r� r r^ rP r� r! �MockCoreSchemar| )r� �source�handler�schemas rY � __get_pydantic_core_schema__�&BaseModel.__get_pydantic_core_schema__8 sb � �336 �
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337� � � �!�!�"<�=�� � �j�� �9U�9U�&V�&V��/�/� /��v�� r[ c � � U" U5 $ )a� Hook into generating the model's JSON schema.338 339Args:340 core_schema: A `pydantic-core` CoreSchema.341 You can ignore this argument and call the handler with a new CoreSchema,342 wrap this CoreSchema (`{'type': 'nullable', 'schema': current_schema}`),343 or just call the handler with the original schema.344 handler: Call into Pydantic's internal JSON schema generation.345 This will raise a `pydantic.errors.PydanticInvalidForJsonSchema` if JSON schema346 generation fails.347 Since this gets called by `BaseModel.model_json_schema` you can override the348 `schema_generator` argument to that function to change JSON schema generation globally349 for a type.350 351Returns:352 A JSON schema, as a Python object.353r )r� � core_schemar8 s rY � __get_pydantic_json_schema__�&BaseModel.__get_pydantic_json_schema__L s � �0 �{�#�#r[ c � � g)a� This is intended to behave just like `__init_subclass__`, but is called by `ModelMetaclass`354only after basic class initialization is complete. In particular, attributes like `model_fields` will355be present when this is called, but forward annotations are not guaranteed to be resolved yet,356meaning that creating an instance of the class may fail.357 358This is necessary because `__init_subclass__` will always be called by `type.__new__`,359and it would require a prohibitively large refactor to the `ModelMetaclass` to ensure that360`type.__new__` was called in such a manner that the class would already be sufficiently initialized.361 362This will receive the same `kwargs` that would be passed to the standard `__init_subclass__`, namely,363any kwargs passed to the class definition that aren't used internally by Pydantic.364 365Args:366 **kwargs: Any keyword arguments passed to the class definition that aren't used internally367 by Pydantic.368 369Note:370 You may want to override [`__pydantic_on_complete__()`][pydantic.main.BaseModel.__pydantic_on_complete__]371 instead, which is called once the class and its fields are fully initialized and ready for validation.372Nr �r� �kwargss rY �__pydantic_init_subclass__�$BaseModel.__pydantic_init_subclass__f r r[ c � � g)a� This is called once the class and its fields are fully initialized and ready to be used.373 374This typically happens when the class is created (just before375[`__pydantic_init_subclass__()`][pydantic.main.BaseModel.__pydantic_init_subclass__] is called on the superclass),376except when forward annotations are used that could not immediately be resolved.377In that case, it will be called later, when the model is rebuilt automatically or explicitly using378[`model_rebuild()`][pydantic.main.BaseModel.model_rebuild].379Nr r� s rY �__pydantic_on_complete__�"BaseModel.__pydantic_on_complete__} r r[ c �. ^ � [ R " X5 nUb U$ U [ L a [ S5 e[ U S5 ( d [ U S35 eU R380 S ( d" [ U R ; a [ U S35 e[ U[ 5 ( d U4n[ R " X5 m [ S T R 5 5 5 n[ R " T R 5 T R 5 5 ( a" T ( a U n[ R " XU5 U$ U R381 S nU( d UnO[ U 4S jU 5 5 nU R382 S =( d U nUR! U5 n[ [" R% [ R& " T R 5 5 5 5 n[ R( " Xe5 n [ R* " XXe5 nUb UsS S S 5 $ U b U sS S S 5 $ [, R. " S383S 9=( d 0 n384UR1 U385S 9 [ R4 " XvXX5 n[ R " XX6U5 S S S 5 U$ ! [2 a NEf = f! , ( d f W$ = f)
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:w a [% SUR SU S35 eTc* X R& U' U R( R+ U5 g[ S $ [ S $ )aX Get a handler for setting an attribute on the model instance.401 402Returns:403 A handler for setting an attribute on the model instance. Used for memoization of the handler.404 Memoizing the handlers leads to a dramatic performance improvement in `__setattr__`405 Returns `None` when memoization is not safe, then the attribute is set directly.406z is a ClassVar of `zR` and cannot be set on an instance. If you want to set a value on the class, use `�.z407 = value`.N�__set__c �& >� TR X5 $ r] �r� )rb �_namerc rx s �rY rm �,BaseModel._setattr_handler.<locals>.<lambda>- s �� ��9J�9J�5�9Vr[ rs r c �& >� TR X5 $ r] r� )rb r� rc r s �rY rm r� A s �� �� � �e�1Ir[ rl r� r� �"z" object has no field "rt rr )rt rx rs rT r �is_valid_field_namery rP r� ru rq rQ r� r rZ �propertyrO rR �408ValueErrorr� r_ r` )r� rV rW r� r rx s @@rY r~ �BaseModel._setattr_handler s� �� � �.�.�C��)�)�)�$��h� 1�#�,�,� � @E�EH�\�\�N�RS�TX�SY�Yc�e�� � �0�0��6�6�!$�!;�!;�!?�!?��!E�E�I�R� �y�)�4�4� V�V� 7� � B�B�#�D��6� ��3�d�+�D�409 �$��0�0�/�0A�B�B� �#�U� +� �$��)�)�I�I��!�!�%�%�&;�<�<�/�0E�F�F�� 4� 4�4��#�#�'�'��0�G�;�$�q�� � ��6M�d�V�ST�%U�V�V��\�49�+�+�D�1��0�0�4�4�T�:� � 4�M�B�B�/�
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U SSXSS940 U=( d 0 D6nU R c SnO9U R R 5 VV s0 s H u p�U [ Ld M X�_M nnn U R c Sn492O�U R R 5 n493[ U R 5 H nX�; d M494 U495R U5 M [ U5 H' nX�R ; d M UR U5 X�' M) U( a U R UR 5 - n O[! U R 5 n U( a U [! U5 - n UR# XX�XtS 9$ s sn nf )496a+ Returns a copy of the model.497 498!!! warning "Deprecated"499 This method is now deprecated; use `model_copy` instead.500 501If you need `include` or `exclude`, use:502 503```python {test="skip" lint="skip"}504data = self.model_dump(include=include, exclude=exclude, round_trip=True)505data = {**data, **(update or {})}506copied = self.model_validate(data)507```508 509Args:510 include: Optional set or mapping specifying which fields to include in the copied model.511 exclude: Optional set or mapping specifying which fields to exclude in the copied model.512 update: Optional dictionary of field-value pairs to override field values in the copied model.513 deep: If True, the values of fields that are Pydantic models will be deep-copied.514 515Returns:516 A copy of the model with included, excluded and updated fields as specified.517r r� r� r ��copy_internalsF)�to_dictr� r� r� r� N)r� )r� r� r r� r r[ �_iterrf r� r r� r �listr� r_ r� r� �_copy_and_set_values) r� r� r� r� r� r r� rs r� r� r� r� s rY r �BaseModel.copy� sq � �F �
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