# coding: utf-8

"""
    Arthur Scope

    No description provided (generated by Openapi Generator https://github.com/openapitools/openapi-generator)

    The version of the OpenAPI document: 0.1.0
    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 datetime import datetime
from pydantic import BaseModel, ConfigDict, Field, StrictBool, StrictInt, StrictStr
from typing import Any, ClassVar, Dict, List, Optional
from arthur_client.api_bindings.models.continuous_eval_transform_variable_mapping_response import ContinuousEvalTransformVariableMappingResponse
from typing import Optional, Set
from typing_extensions import Self

class ContinuousEvalResponse(BaseModel):
    """
    ContinuousEvalResponse
    """ # noqa: E501
    id: StrictStr = Field(description="ID of the transform.")
    name: StrictStr = Field(description="Name of the continuous eval.")
    description: Optional[StrictStr] = None
    task_id: StrictStr = Field(description="ID of the parent task.")
    llm_eval_name: StrictStr = Field(description="Name of the llm eval.")
    llm_eval_version: StrictInt = Field(description="Version of the llm eval.")
    transform_id: StrictStr = Field(description="ID of the transform.")
    transform_variable_mapping: Optional[List[ContinuousEvalTransformVariableMappingResponse]] = Field(default=None, description="Mapping of transform variables to eval variables.")
    enabled: Optional[StrictBool] = Field(default=True, description="Whether the continuous eval is enabled.")
    created_at: datetime = Field(description="Timestamp representing the time the transform was added to the llm eval.")
    updated_at: datetime = Field(description="Timestamp representing the time the continuous eval was last updated.")
    __properties: ClassVar[List[str]] = ["id", "name", "description", "task_id", "llm_eval_name", "llm_eval_version", "transform_id", "transform_variable_mapping", "enabled", "created_at", "updated_at"]

    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 ContinuousEvalResponse 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 transform_variable_mapping (list)
        _items = []
        if self.transform_variable_mapping:
            for _item_transform_variable_mapping in self.transform_variable_mapping:
                if _item_transform_variable_mapping:
                    _items.append(_item_transform_variable_mapping.to_dict())
            _dict['transform_variable_mapping'] = _items
        # set to None if description (nullable) is None
        # and model_fields_set contains the field
        if self.description is None and "description" in self.model_fields_set:
            _dict['description'] = None

        return _dict

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

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

        _obj = cls.model_validate({
            "id": obj.get("id"),
            "name": obj.get("name"),
            "description": obj.get("description"),
            "task_id": obj.get("task_id"),
            "llm_eval_name": obj.get("llm_eval_name"),
            "llm_eval_version": obj.get("llm_eval_version"),
            "transform_id": obj.get("transform_id"),
            "transform_variable_mapping": [ContinuousEvalTransformVariableMappingResponse.from_dict(_item) for _item in obj["transform_variable_mapping"]] if obj.get("transform_variable_mapping") is not None else None,
            "enabled": obj.get("enabled") if obj.get("enabled") is not None else True,
            "created_at": obj.get("created_at"),
            "updated_at": obj.get("updated_at")
        })
        return _obj


