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

# 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

[docs] class TaskEvaluatorInput(BaseModel): """ An evaluator attachment supplied when creating or updating a task. At least one entry is required on evaluation-task requests. """ # noqa: E501 evaluator_id: StrictStr = Field(description="Evaluator identifier (base64). Duplicates are not allowed.") query_filter: Optional[StrictStr] = Field(default=None, description="Per-evaluator query filter. Combined with the task-level filter (AND).") column_mappings: Optional[Dict[str, StrictStr]] = Field(default=None, description="Maps evaluator template variable names to data source column names.") __properties: ClassVar[List[str]] = ["evaluator_id", "query_filter", "column_mappings"] model_config = ConfigDict( populate_by_name=True, validate_assignment=True, protected_namespaces=(), )
[docs] def to_str(self) -> str: """Returns the string representation of the model using alias""" return pprint.pformat(self.model_dump(by_alias=True))
[docs] 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())
[docs] @classmethod def from_json(cls, json_str: str) -> Optional[Self]: """Create an instance of TaskEvaluatorInput from a JSON string""" return cls.from_dict(json.loads(json_str))
[docs] 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
[docs] @classmethod def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]: """Create an instance of TaskEvaluatorInput 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 TaskEvaluatorInput) in the input: " + _key) _obj = cls.model_validate({ "evaluator_id": obj.get("evaluator_id"), "query_filter": obj.get("query_filter"), "column_mappings": obj.get("column_mappings") }) return _obj