list_fhir_export_jobs async ¶

async def list_fhir_export_jobs(
    self,
    datastore_id: "capo_healthlake.types.datastore_id.DatastoreId",
    *,
    config_overrides: Optional[AsyncHealthLakeClientConfig] = None,
    next_token: Optional["capo_healthlake.types.next_token.NextToken"] = None,
    max_results: Optional[
        "capo_healthlake.types.max_results_integer.MaxResultsInteger"
    ] = None,
    job_name: Optional["capo_healthlake.types.job_name.JobName"] = None,
    job_status: Optional["capo_healthlake.types.job_status.JobStatus"] = None,
    submitted_before: Optional[
        "capo_healthlake.types.health_lake_timestamp.HealthLakeTimestamp"
    ] = None,
    submitted_after: Optional[
        "capo_healthlake.types.health_lake_timestamp.HealthLakeTimestamp"
    ] = None,
) -> "capo_healthlake.types.list_fhir_export_jobs_response.ListFHIRExportJobsResponse":
    """<p>Lists all FHIR export jobs associated with an account and their statuses.</p>

    Args:
        datastore_id: <p>Limits the response to the export job with the specified data store ID. </p>
        next_token: <p>A pagination token used to identify the next page of results to return.</p>
        max_results: <p>Limits the number of results returned for a ListFHIRExportJobs to a maximum quantity specified by the user.</p>
        job_name: <p>Limits the response to the export job with the specified job name. </p>
        job_status: <p>Limits the response to export jobs with the specified job status. </p>
        submitted_before: <p>Limits the response to FHIR export jobs submitted before a user- specified date.</p>
        submitted_after: <p>Limits the response to FHIR export jobs submitted after a user-specified date.</p>

    Raises:
        capo_healthlake.errors.access_denied_exception.AccessDeniedException: <p>Access is denied. Your account is not authorized to perform this operation.</p>
        capo_healthlake.errors.internal_server_exception.InternalServerException: <p>An unknown internal error occurred in the service.</p>
        capo_healthlake.errors.resource_not_found_exception.ResourceNotFoundException: <p>The requested data store was not found.</p>
        capo_healthlake.errors.throttling_exception.ThrottlingException: <p>The user has exceeded their maximum number of allowed calls to the given API. </p>
        capo_healthlake.errors.validation_exception.ValidationException: <p>The user input parameter was invalid.</p>
        capo_healthlake.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    async def _handler(
        req: "AsyncOperationRequest[capo_healthlake.types.list_fhir_export_jobs_request.ListFHIRExportJobsRequest]",
    ) -> AsyncOperationResponse[
        "capo_healthlake.types.list_fhir_export_jobs_response.ListFHIRExportJobsResponse"
    ]:
        import capo_healthlake._operations.health_lake.list_fhir_export_jobs

        (
            output,
            http_response,
        ) = await capo_healthlake._operations.health_lake.list_fhir_export_jobs.async_list_fhir_export_jobs(
            req.options, req.input
        )
        return AsyncOperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("ListFHIRExportJobs")
    )
    input_: capo_healthlake.types.list_fhir_export_jobs_request.ListFHIRExportJobsRequest = {
        "datastore_id": datastore_id
    }
    if next_token is not None:
        input_["next_token"] = next_token
    if max_results is not None:
        input_["max_results"] = max_results
    if job_name is not None:
        input_["job_name"] = job_name
    if job_status is not None:
        input_["job_status"] = job_status
    if submitted_before is not None:
        input_["submitted_before"] = submitted_before
    if submitted_after is not None:
        input_["submitted_after"] = submitted_after

    response = await aexecute_pipeline(
        AsyncOperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    await response.response.aclose()
    return response.output