# coding: utf-8

"""
Root Signals API

Root Signals JSON API provides a way to access Root Signals using provisioned API token

The version of the OpenAPI document: 1.0.0 (latest)
Generated by OpenAPI Generator (https://openapi-generator.tech)

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

from __future__ import annotations

import json
import pprint
import re  # noqa: F401
from typing import Any, ClassVar, Dict, List, Optional, Set

from pydantic import BaseModel, ConfigDict, Field
from typing_extensions import Annotated, Self

from root.generated.openapi_client.models.skill_test_data_request_dataset_range import SkillTestDataRequestDatasetRange


class SkillTestDataRequest(BaseModel):
    """
    SkillTestDataRequest
    """  # noqa: E501

    test_data: Optional[List[List[Annotated[str, Field(min_length=1, strict=True)]]]] = None
    test_dataset_id: Optional[Annotated[str, Field(min_length=1, strict=True)]] = None
    dataset_range: Optional[SkillTestDataRequestDatasetRange] = None
    __properties: ClassVar[List[str]] = ["test_data", "test_dataset_id", "dataset_range"]

    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 SkillTestDataRequest 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 dataset_range
        if self.dataset_range:
            _dict["dataset_range"] = self.dataset_range.to_dict()
        # set to None if test_data (nullable) is None
        # and model_fields_set contains the field
        if self.test_data is None and "test_data" in self.model_fields_set:
            _dict["test_data"] = None

        # set to None if dataset_range (nullable) is None
        # and model_fields_set contains the field
        if self.dataset_range is None and "dataset_range" in self.model_fields_set:
            _dict["dataset_range"] = None

        return _dict

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

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

        _obj = cls.model_validate(
            {
                "test_data": obj.get("test_data"),
                "test_dataset_id": obj.get("test_dataset_id"),
                "dataset_range": SkillTestDataRequestDatasetRange.from_dict(obj["dataset_range"])
                if obj.get("dataset_range") is not None
                else None,
            }
        )
        return _obj
