Describes the dataset export job created by CreateDatasetExportJob, including the export job status.
Parameters:
-
dataset_export_job_arn
(Arn)
–
The Amazon Resource Name (ARN) of the dataset export job to describe.
Raises:
Source code in docs_src/capo_personalize/_services/personalize.py
| def describe_dataset_export_job(
self,
dataset_export_job_arn: "capo_personalize.types.arn.Arn",
*,
config_overrides: Optional[PersonalizeClientConfig] = None,
) -> "capo_personalize.types.describe_dataset_export_job_response.DescribeDatasetExportJobResponse":
"""<p>Describes the dataset export job created by <a href="https://docs.aws.amazon.com/personalize/latest/dg/API_CreateDatasetExportJob.html">CreateDatasetExportJob</a>, including the export job status.</p>
Args:
dataset_export_job_arn: <p>The Amazon Resource Name (ARN) of the dataset export job to describe.</p>
Raises:
capo_personalize.errors.invalid_input_exception.InvalidInputException: <p>Provide a valid value for the field or parameter.</p>
capo_personalize.errors.resource_not_found_exception.ResourceNotFoundException: <p>Could not find the specified resource.</p>
capo_personalize.errors.UnknownServiceError: The service returned an error code this client does not model.
"""
def _handler(
req: "OperationRequest[capo_personalize.types.describe_dataset_export_job_request.DescribeDatasetExportJobRequest]",
) -> OperationResponse[
"capo_personalize.types.describe_dataset_export_job_response.DescribeDatasetExportJobResponse"
]:
import capo_personalize._operations.amazon_personalize.describe_dataset_export_job
output, http_response = (
capo_personalize._operations.amazon_personalize.describe_dataset_export_job.describe_dataset_export_job(
req.options, req.input
)
)
return OperationResponse(output=output, response=http_response)
interceptors_, options_ = self.operation_options(
config_overrides, OperationLogging("DescribeDatasetExportJob")
)
input_: capo_personalize.types.describe_dataset_export_job_request.DescribeDatasetExportJobRequest = {
"dataset_export_job_arn": dataset_export_job_arn
}
response = execute_pipeline(
OperationRequest(input=input_, options=options_),
handler=_handler,
interceptors=list(interceptors_),
)
response.response.close()
return response.output
|