# coding: utf-8

"""
    Mixpeek API

    This is the Mixpeek API, providing access to various endpoints for data processing and retrieval.

    The version of the OpenAPI document: 0.81.1
    Contact: info@mixpeek.com
    Generated by OpenAPI Generator (https://openapi-generator.tech)

    Do not edit the class manually.
"""  # noqa: E501


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

from pydantic import BaseModel, ConfigDict, Field, StrictStr
from typing import Any, ClassVar, Dict, List, Optional, Union
from typing_extensions import Annotated
from typing import Optional, Set
from typing_extensions import Self

class SuitableCollection(BaseModel):
    """
    Information about a collection that might fulfill the user's request.  Attributes:     collection_id: Collection identifier     collection_name: Human-readable collection name     feature_extractor: Extractor used in this collection     capabilities: What this collection can do (e.g., \"video search\", \"face detection\")     match_score: How well this collection matches the request (0.0-1.0)
    """ # noqa: E501
    collection_id: StrictStr = Field(description="Collection ID")
    collection_name: StrictStr = Field(description="Collection name")
    feature_extractor: StrictStr = Field(description="Feature extractor name")
    capabilities: Optional[List[StrictStr]] = Field(default=None, description="Collection capabilities")
    match_score: Union[Annotated[float, Field(le=1, strict=True, ge=0)], Annotated[int, Field(le=1, strict=True, ge=0)]] = Field(description="Match confidence")
    __properties: ClassVar[List[str]] = ["collection_id", "collection_name", "feature_extractor", "capabilities", "match_score"]

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


    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 SuitableCollection 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 SuitableCollection from a dict"""
        if obj is None:
            return None

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

        _obj = cls.model_validate({
            "collection_id": obj.get("collection_id"),
            "collection_name": obj.get("collection_name"),
            "feature_extractor": obj.get("feature_extractor"),
            "capabilities": obj.get("capabilities"),
            "match_score": obj.get("match_score")
        })
        return _obj


