Search Facet Response Dto

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

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

    _obj = cls.model_validate(
        {
            "counts": [
                SearchFacetCountResponseDto.from_dict(_item)
                for _item in obj["counts"]
            ]
            if obj.get("counts") is not None
            else None,
            "fieldName": obj.get("fieldName"),
        }
    )
    return _obj

@classmethod
def from_json(cls, json_str: str) -> Optional[Self]:
    """Create an instance of SearchFacetResponseDto 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,
    )
    # override the default output from pydantic by calling `to_dict()` of each item in counts (list)
    _items = []
    if self.counts:
        for _item_counts in self.counts:
            if _item_counts:
                _items.append(_item_counts.to_dict())
        _dict["counts"] = _items
    return _dict

def to_json(self) -> str:
    """Returns the JSON representation of the model using alias"""
    # TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
    return json.dumps(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))