# coding: utf-8

"""
    Merlin

    API Guide for accessing Merlin's model management, deployment, and serving functionalities

    The version of the OpenAPI document: 0.14.0
    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 typing import Any, ClassVar, Dict, List, Optional
from pydantic import BaseModel, StrictStr, field_validator
from client.models.prediction_job_config_model_result import PredictionJobConfigModelResult
try:
    from typing import Self
except ImportError:
    from typing_extensions import Self

class PredictionJobConfigModel(BaseModel):
    """
    PredictionJobConfigModel
    """ # noqa: E501
    type: Optional[StrictStr] = 'INVALID_MODEL_TYPE'
    uri: Optional[StrictStr] = None
    result: Optional[PredictionJobConfigModelResult] = None
    options: Optional[Dict[str, StrictStr]] = None
    __properties: ClassVar[List[str]] = ["type", "uri", "result", "options"]

    @field_validator('type')
    def type_validate_enum(cls, value):
        """Validates the enum"""
        if value is None:
            return value

        if value not in ('INVALID_MODEL_TYPE', 'XGBOOST', 'TENSORFLOW', 'SKLEARN', 'PYTORCH', 'ONNX', 'PYFUNC', 'PYFUNC_V2', 'CUSTOM'):
            raise ValueError("must be one of enum values ('INVALID_MODEL_TYPE', 'XGBOOST', 'TENSORFLOW', 'SKLEARN', 'PYTORCH', 'ONNX', 'PYFUNC', 'PYFUNC_V2', 'CUSTOM')")
        return value

    model_config = {
        "populate_by_name": True,
        "validate_assignment": 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) -> Self:
        """Create an instance of PredictionJobConfigModel 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.
        """
        _dict = self.model_dump(
            by_alias=True,
            exclude={
            },
            exclude_none=True,
        )
        # override the default output from pydantic by calling `to_dict()` of result
        if self.result:
            _dict['result'] = self.result.to_dict()
        return _dict

    @classmethod
    def from_dict(cls, obj: Dict) -> Self:
        """Create an instance of PredictionJobConfigModel from a dict"""
        if obj is None:
            return None

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

        _obj = cls.model_validate({
            "type": obj.get("type") if obj.get("type") is not None else 'INVALID_MODEL_TYPE',
            "uri": obj.get("uri"),
            "result": PredictionJobConfigModelResult.from_dict(obj.get("result")) if obj.get("result") is not None else None,
            "options": obj.get("options")
        })
        return _obj


