# 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 regula.facesdk.webclient.gen.models.face_sdk_result_code import FaceSDKResultCode
from regula.facesdk.webclient.gen.models.match_and_search_response_data_detections_item import MatchAndSearchResponseDataDetectionsItem
from regula.facesdk.webclient.gen.models.match_image_result import MatchImageResult
from typing import Optional, Set
from typing_extensions import Self
from pydantic import SkipValidation, Field

class MatchAndSearchResponse(BaseModel):
    """
    MatchAndSearchResponse
    """ # noqa: E501
    code: SkipValidation[FaceSDKResultCode] = Field(alias="code")
    results: SkipValidation[Optional[List[MatchImageResult]]] = Field(alias="results", default=None, description="The match and search results.")
    elapsed_time: SkipValidation[Optional[float]] = Field(alias="elapsedTime", default=None, description="Server processing time, ms. Does not include the time taken to receive the request or deliver the response.")
    metadata: SkipValidation[Optional[Dict[str, object]]] = Field(alias="metadata", default=None, description="A free-form object containing person's extended attributes.")
    detections: SkipValidation[Optional[List[MatchAndSearchResponseDataDetectionsItem]]] = Field(alias="detections", default=None, description="The detection results.")
    __properties: ClassVar[List[str]] = ["code", "results", "elapsedTime", "metadata", "detections"]

    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 MatchAndSearchResponse 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 results (list)
        _items = []
        if self.results:
            for _item_results in self.results:
                if _item_results:
                    _items.append(_item_results.to_dict())
            _dict['results'] = _items
        # override the default output from pydantic by calling `to_dict()` of each item in detections (list)
        _items = []
        if self.detections:
            for _item_detections in self.detections:
                if _item_detections:
                    _items.append(_item_detections.to_dict())
            _dict['detections'] = _items
        return _dict

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

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

        _obj = cls.model_validate({
            "code": obj.get("code"),
            "results": [MatchImageResult.from_dict(_item) for _item in obj.get("results", []) if MatchImageResult.from_dict(_item) is not None],
            "elapsedTime": obj.get("elapsedTime"),
            "metadata": obj.get("metadata"),
            "detections": [MatchAndSearchResponseDataDetectionsItem.from_dict(_item) for _item in obj.get("detections", []) if MatchAndSearchResponseDataDetectionsItem.from_dict(_item) is not None]
        })
        return _obj


