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

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



class TaskEvaluator(BaseModel):
    """
    TaskEvaluator
    """ # noqa: E501
    evaluator_id: StrictStr = Field(description="Evaluator identifier (base64).")
    evaluator_name: StrictStr = Field(description="The name of the attached evaluator.")
    query_filter: Optional[StrictStr] = Field(description="Per-evaluator query filter, combined with the task-level filter (AND).")
    column_mappings: Optional[Dict[str, StrictStr]] = Field(description="Maps evaluator template variable names to data source column names.")
    __properties: ClassVar[List[str]] = ["evaluator_id", "evaluator_name", "query_filter", "column_mappings"]

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

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

        return _dict




    @classmethod
    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
        """Create an instance of TaskEvaluator 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 TaskEvaluator) in the input: " + _key)

        _obj = cls.model_validate({
            "evaluator_id": obj.get("evaluator_id"),
            "evaluator_name": obj.get("evaluator_name"),
            "query_filter": obj.get("query_filter"),
            "column_mappings": obj.get("column_mappings")
        })
        return _obj