Source code for arize._generated.api_client.models.continuous_annotation_config

# coding: utf-8

"""
    Arize REST API

    API specification for the backend data server. The API is hosted globally at https://api.arize.com/v2 or in your own environment. 

    The version of the OpenAPI document: 2.0.0
    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, StrictFloat, StrictInt, StrictStr, field_validator
from typing import Any, ClassVar, Dict, List, Optional, Union
from arize._generated.api_client.models.optimization_direction import OptimizationDirection
from typing import Optional, Set
from typing_extensions import Self



class ContinuousAnnotationConfig(BaseModel):
    """
    ContinuousAnnotationConfig
    """ # noqa: E501
    id: StrictStr = Field(description="The unique identifier for the annotation config")
    name: StrictStr = Field(description="The name of the annotation config")
    created_at: datetime = Field(description="The timestamp for when the annotation config was created")
    space_id: StrictStr = Field(description="The space id the annotation config belongs to")
    type: StrictStr = Field(description="Discriminator value identifying a continuous annotation config.")
    minimum_score: Union[StrictFloat, StrictInt] = Field(description="The minimum score value")
    maximum_score: Union[StrictFloat, StrictInt] = Field(description="The maximum score value")
    optimization_direction: Optional[OptimizationDirection] = Field(default=None, description="Direction for optimization. When absent, the server treats the value as `none`.")
    __properties: ClassVar[List[str]] = ["id", "name", "created_at", "space_id", "type", "minimum_score", "maximum_score", "optimization_direction"]



    @field_validator('type')
    def type_validate_enum(cls, value):
        """Validates the enum"""
        if value not in set(['continuous']):
            raise ValueError("must be one of enum values ('continuous')")
        return value


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

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

        # raise errors for additional fields in the input
        for _key in obj.keys():
            if _key not in cls.__properties:
                raise ValueError("Error due to additional fields (not defined in ContinuousAnnotationConfig) in the input: " + _key)

        _obj = cls.model_validate({
            "id": obj.get("id"),
            "name": obj.get("name"),
            "created_at": obj.get("created_at"),
            "space_id": obj.get("space_id"),
            "type": obj.get("type"),
            "minimum_score": obj.get("minimum_score"),
            "maximum_score": obj.get("maximum_score"),
            "optimization_direction": obj.get("optimization_direction")
        })
        return _obj