# coding: utf-8

"""
    Generated by: https://openapi-generator.tech
"""

from __future__ import annotations
import pprint
import re  # noqa: F401
import json

from pydantic import BaseModel, ConfigDict, Field, StrictFloat, StrictInt
from typing import Any, ClassVar, Dict, List, Optional, Union
from typing_extensions import Annotated
from regula.facesdk.webclient.gen.models.face_quality_config_name import FaceQualityConfigName
from typing import Optional, Set
from typing_extensions import Self
from pydantic import SkipValidation, Field

class QualityConfig(BaseModel):
    """
    The configuration that defines the list of returned quality check characteristics.
    """ # noqa: E501
    name: SkipValidation[Optional[FaceQualityConfigName]] = Field(alias="name", default=None)
    range: SkipValidation[Optional[List[float]]] = Field(alias="range", default=None, description="The range of applicable values for this characteristic. If the returned in the response value fits this range, the characteristic is identified as compliant with the requirements. For recommended ranges, see [Face Image Quality Assessment](https://docs.regulaforensics.com/develop/face-sdk/web-service/development/usage/face-detection/face-image-quality-check/).")
    __properties: ClassVar[List[str]] = ["name", "range"]

    model_config = ConfigDict(
        populate_by_name=True,
        validate_assignment=True,
        protected_namespaces=(),
        arbitrary_types_allowed=True,
        use_enum_values=True
    )


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

    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())

    @classmethod
    def from_json(cls, json_str: str) -> Optional[Self]:
        """Create an instance of QualityConfig 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

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

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

        _obj = cls.model_validate({
            "name": obj.get("name"),
            "range": obj.get("range")
        })
        return _obj


