MLModelsRunStatusesModelrun

pydantic model openapi_client.models.ml_models_run_statuses_modelrun.MLModelsRunStatusesModelrun

Aggregate status when filtering by ModelRunId.

Fields:

• batch_transformation_jobs (List[openapi_client.models.ml_models_run_statuses_modelrun_batch_transformation_jobs_inner.MLModelsRunStatusesModelrunBatchTransformationJobsInner] | None)

• dataset_processing_mode (str | None)

• model_run_id (str | None)

• run_status (str | None)

field model_run_id: Optional[StrictStr] = None (alias 'ModelRunId')

field dataset_processing_mode: Optional[StrictStr] = None (alias 'DatasetProcessingMode')

field run_status: Optional[StrictStr] = None (alias 'RunStatus')

Aggregate status SUCCESS|FAILED|INPROGRESS.

field batch_transformation_jobs: Optional[List[MLModelsRunStatusesModelrunBatchTransformationJobsInner]] = None (alias 'BatchTransformationJobs')

to_str()

Returns the string representation of the model using alias

Return type:

str

to_json()

Returns the JSON representation of the model using alias

Return type:

str

classmethod from_json(json_str)

Create an instance of MLModelsRunStatusesModelrun from a JSON string

Return type:

Optional[Self]

to_dict()

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.

Return type:

Dict[str, Any]

classmethod from_dict(obj)

Create an instance of MLModelsRunStatusesModelrun from a dict

Return type:

Optional[Self]