Lists the DataBrew schedules that are defined.
Parameters:
-
job_name
(Optional[JobName], default:
None
)
–
The name of the job that these schedules apply to.
-
max_results
(Optional[MaxResults100], default:
None
)
–
The maximum number of results to return in this request.
-
next_token
(Optional[NextToken], default:
None
)
–
The token returned by a previous call to retrieve the next set of results.
Raises:
Source code in docs_src/capo_databrew/_services/data_brew.py
| def list_schedules(
self,
*,
config_overrides: Optional[DataBrewClientConfig] = None,
job_name: Optional["capo_databrew.types.job_name.JobName"] = None,
max_results: Optional[
"capo_databrew.types.max_results100.MaxResults100"
] = None,
next_token: Optional["capo_databrew.types.next_token.NextToken"] = None,
) -> "capo_databrew.types.list_schedules_response.ListSchedulesResponse":
"""<p>Lists the DataBrew schedules that are defined.</p>
Args:
job_name: <p>The name of the job that these schedules apply to.</p>
max_results: <p>The maximum number of results to return in this request. </p>
next_token: <p>The token returned by a previous call to retrieve the next set of results.</p>
Raises:
capo_databrew.errors.validation_exception.ValidationException: <p>The input parameters for this request failed validation.</p>
capo_databrew.errors.UnknownServiceError: The service returned an error code this client does not model.
"""
def _handler(
req: "OperationRequest[capo_databrew.types.list_schedules_request.ListSchedulesRequest]",
) -> OperationResponse[
"capo_databrew.types.list_schedules_response.ListSchedulesResponse"
]:
import capo_databrew._operations.aws_glue_data_brew.list_schedules
output, http_response = (
capo_databrew._operations.aws_glue_data_brew.list_schedules.list_schedules(
req.options, req.input
)
)
return OperationResponse(output=output, response=http_response)
interceptors_, options_ = self.operation_options(
config_overrides, OperationLogging("ListSchedules")
)
input_: capo_databrew.types.list_schedules_request.ListSchedulesRequest = {}
if job_name is not None:
input_["job_name"] = job_name
if max_results is not None:
input_["max_results"] = max_results
if next_token is not None:
input_["next_token"] = next_token
response = execute_pipeline(
OperationRequest(input=input_, options=options_),
handler=_handler,
interceptors=list(interceptors_),
)
response.response.close()
return response.output
|