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

# 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, StrictStr
from typing import Any, ClassVar, Dict, List, Optional
from typing import Optional, Set
from typing_extensions import Self

[docs] class ExperimentWithRunIds(BaseModel): """ ExperimentWithRunIds """ # noqa: E501 id: StrictStr = Field(description="Unique identifier for the experiment") name: StrictStr = Field(description="Name of the experiment") dataset_id: StrictStr = Field(description="Unique identifier for the dataset this experiment belongs to") dataset_version_id: StrictStr = Field(description="Unique identifier for the dataset version this experiment belongs to") created_at: datetime = Field(description="Timestamp for when the experiment was created") updated_at: datetime = Field(description="Timestamp for the last update of the experiment") experiment_traces_project_id: Optional[StrictStr] = Field(default=None, description="Unique identifier for the experiment traces project this experiment belongs to (if it exists)") run_ids: List[StrictStr] = Field(description="IDs of the newly inserted experiment runs, in input order.") __properties: ClassVar[List[str]] = ["id", "name", "dataset_id", "dataset_version_id", "created_at", "updated_at", "experiment_traces_project_id", "run_ids"] 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 ExperimentWithRunIds 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 ExperimentWithRunIds 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 ExperimentWithRunIds) in the input: " + _key) _obj = cls.model_validate({ "id": obj.get("id"), "name": obj.get("name"), "dataset_id": obj.get("dataset_id"), "dataset_version_id": obj.get("dataset_version_id"), "created_at": obj.get("created_at"), "updated_at": obj.get("updated_at"), "experiment_traces_project_id": obj.get("experiment_traces_project_id"), "run_ids": obj.get("run_ids") }) return _obj