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ClickUp Operator

by noah-vh
dataclasses.cpython-312.pyc14.7 kB
� �MMg>� �D�dZddlmZddlZddlZddlZddlmZm Z m Z m Z m Z m Z mZddlmZddlmZmZmZddlmZmZmZmZdd lmZdd lmZdd lmZdd l m!Z!dd l"m#Z#m$Z$m%Z%er ddl&m'Z'ddl(m)Z)dZ*e d�Z+ejXdk\r�eejZe#e%f��eddddddddddd� d%d���Z.eejZe#e%f��eddddddddddd� d&d���Z.n|eejZe#e%f��eddddddddd� d'd���Z.eejZe#e%f��eddddddddd� d(d���Z.eejZe#e%f�� d)ddddddddddd� d*d��Z.ee/�Z0dejXcxkrdkrnnd+d �Z1e1ejd_3ddd!dd"� d,d#�Z4d-d$�Z5y).z7Provide an enhanced dataclass that performs validation.�)� annotationsN)� TYPE_CHECKING�Any�Callable�Generic�NoReturn�TypeVar�overload)�warn)�Literal� TypeGuard�dataclass_transform�)�_config� _decorators�_namespace_utils� _typing_extra)� _dataclasses)�getattr_migration)� ConfigDict)�PydanticUserError)�Field� FieldInfo� PrivateAttr)�PydanticDataclass)�MappingNamespace)� dataclass�rebuild_dataclass�_T��� )�field_specifiersFT.� �init�repr�eq�order� unsafe_hash�frozen�config�validate_on_init�kw_only�slotsc ��y�N�r$s �`C:\Users\noahv\Documents\GitHub\clickup-operator\.venv\Lib\site-packages\pydantic/dataclasses.pyrrs�� �c ��yr0r1) �_clsr%r&r'r(r)r*r+r,r-r.s r2rr/s��#&r3�r%r&r'r(r)r*r+r,c��yr0r1r6s r2rrBs�� r3c��yr0r1) r5r%r&r'r(r)r*r+r,s r2rrQs��#&r3c �������� � �|dusJd��|dusJd��tjdk\r| | d�� ni� dd�� d ���� � ���fd� } |�| S| |�S) a�Usage 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. 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.c ��|jD]�}t|dg�}|D]�}t||d�}t|t�s�!d|i}tj dk\r|j rd|d<|jdur|j|d<t||tjdi|���|jjd��i|_ |||j|<����y) 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__N�defaultr Tr-r&r1)�__mro__�getattr� isinstancer�sys� version_infor-r&�setattr� dataclasses�field�__dict__�getr;)�cls�annotation_clsr� field_name� field_value� field_argss r2�make_pydantic_fields_compatiblez2dataclass.<locals>.make_pydantic_fields_compatible�s���"�k�k�N�"�.�2C�R�H�K�)� �%�c�:�t�<� �!�+�y�9��%.�{�#;� ��#�#�w�.�;�3F�3F�,0�J�y�)��#�#�4�/�)4�)9�)9�J�v�&���Z��):�):�)H�Z�)H�I��<�<�#�#�$5�6�>�*,�C�'�2=�j�2I��#�#�J�/�-*� *r3c ����ddlm}||�rtd|j�d�d���|}t d�|j D��}|s.� �,t |d �r td |j�d �td � �� �� n t|d d�}tj|�}tjj|�}|j}t!j"|�rNd}|f}t%|t&�rt&|j(} || fz}t+j,|j|�}�|�� �/� } |j.r1td|j�d�td � �n|j.xsd} t1j2|fd�� ��| d����}||_||_|j6|_|j8|_d|_t!j<||d��|S)z�Create a Pydantic dataclass from a regular dataclass. Args: cls: The class to create the Pydantic dataclass from. Returns: A Pydantic dataclass. r)�is_model_classz(Cannot create a Pydantic dataclass from z" as it is already a Pydantic modelzdataclass-on-model)�codec3�FK�|]}tj|����y�wr0)rC� is_dataclass)�.0�bases r2� <genexpr>z6dataclass.<locals>.create_dataclass.<locals>.<genexpr>�s���� Z�M�D��!9�!9�$�!?�M�s�!N�__pydantic_config__z[`config` is set via both the `dataclass` decorator and `__pydantic_config__` for dataclass zK. The `config` specification from `dataclass` decorator will take priority.�)�category� stacklevelzN`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.FT)r%r&r'r(r)r*)� raise_errors)�_internal._utilsrNr�__name__�any� __bases__�hasattrr � UserWarningr>r� ConfigWrapperr�DecoratorInfos�build�__doc__�_pydantic_dataclasses�is_builtin_dataclass� issubclassr�__parameters__�types� new_classr*rCr�__pydantic_decorators__� __module__� __qualname__�__pydantic_complete__�complete_dataclass)rGrN� original_cls�has_dataclass_base� config_dict�config_wrapper� decorators� original_doc�bases� generic_base�frozen_r+r'r*�kwargsrLr(r&r)s ��������r2�create_dataclassz#dataclass.<locals>.create_dataclass�s ��� 5� �#� �#�:�3�<�<�.�Hj�k�)�� � � �!� Z�C�M�M� Z�Z��!�f�&8�W�S�J_�=`� �m�nq�nz�nz�m{�|\�]�$��  �!'� 2�f���EZ�\`�8a� � �.�.�{�;�� �/�/�5�5�c�:� � �{�{� � � 5� 5�c� :� �L� �F�E��#�w�'�&�s�'9�'9�:� ����/���/�/�#�,�,��6�C�'��,� � ��G��$�$��d�eh�eq�eq�dt�um�m�(� � �%�+�+�4�u�G��#�#� �  �����#��  ��  ��'1��#�"�� �%�0�0���'�4�4���$)��!� �0�0��n�SX�Y�� r3)rG� type[Any]�return�None)rGrzr{�type[PydanticDataclass])r@rA)r5r%r&r'r(r)r*r+r,r-r.ryrxrLs `````` @@r2rrasu���\ �5�=�S�S�S�=� �5� (�Y�*Y�Y� (� ���7�"�$�u�5����!J�F[�[�z $�|� �G�1A�$�1G�Gr3)r!�)r!� c��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[<parameter>]`. z 'InitVar' object is not callable)� TypeError)�argsrxs r2� _call_initvarr� s�� �:�;�;r3rV)�forcerY�_parent_namespace_depth�_types_namespacec�B�|s |jryd|jvr t|d�|�|}n#|dkDrtj|d��xsi}ni}t j |��}tj|tj|jd��||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`. N�__pydantic_core_schema__rT)� parent_depthr�)�parent_namespaceF)�check)rY� ns_resolver� _force_build) rmrE�delattrr�parent_frame_namespacer� NsResolverrdrnrr`rU)rGr�rYr�r�� rebuild_nsr�s r2rr*s���4 �S�.�.��!�S�\�\�1���/�0��#�%� � �1� $�"�9�9�G^�fj�k�q�oq� �� �"�-�-�#��K� !� 3� 3� ����c�5�5�U�C�!�� � � r3c�l� d|jvxrtj|�S#t$rYywxYw)z�Whether a class is a pydantic dataclass. Args: class_: The class. 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