Asset Metadata Bulk Delete Item Dto

@field_validator("asset_id", mode="before")
def asset_id_validate_regular_expression(cls, value):
    """Validates the regular expression"""
    if isinstance(value, str) and not re.match(
        r"^([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-4[0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12})$",
        value,
    ):
        raise ValueError(
            r"must validate the regular expression /^([0-9a-fA-F]{8}-[0-9a-fA-F]{4}-4[0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12})$/"
        )
    return value

@classmethod
def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
    """Create an instance of AssetMetadataBulkDeleteItemDto from a dict"""
    if obj is None:
        return None

    if not isinstance(obj, dict):
        return cls.model_validate(obj)

    _obj = cls.model_validate(
        {"assetId": obj.get("assetId"), "key": obj.get("key")}
    )
    return _obj

@classmethod
def from_json(cls, json_str: str) -> Optional[Self]:
    """Create an instance of AssetMetadataBulkDeleteItemDto from a JSON string"""
    return cls.from_dict(json.loads(json_str))

def to_dict(self) -> Dict[str, Any]:
    """Return the dictionary representation of the model using alias.

    This has the following differences from calling pydantic's
    `self.model_dump(by_alias=True)`:

    * `None` is only added to the output dict for nullable fields that
      were set at model initialization. Other fields with value `None`
      are ignored.
    """
    excluded_fields: Set[str] = set([])

    _dict = self.model_dump(
        by_alias=True,
        exclude=excluded_fields,
        exclude_none=True,
    )
    return _dict

def to_json(self) -> str:
    """Returns the JSON representation of the model using alias"""
    return json.dumps(to_jsonable_python(self.to_dict()))

def to_str(self) -> str:
    """Returns the string representation of the model using alias"""
    return pprint.pformat(self.model_dump(by_alias=True))