cancel_run_batch ¶

cancel_run_batch(
    batch_id: BatchId, *, config_overrides: Optional[OmicsClientConfig] = None
) -> CancelRunBatchResponse

Cancels all runs within a specified batch. This operation prevents not-yet-submitted runs from starting and submits CancelRun requests for runs that have already started.

Cancel is only allowed on batches in PENDING, SUBMITTING, or INPROGRESS state. Cancel operations are non-atomic and may be partially successful. Use GetBatch to review successfulCancelSubmissionCount and failedCancelSubmissionCount in the submissionSummary. Only one cancel or delete operation per batch is allowed at a time.

Parameters:

batch_id (BatchId) –

The identifier portion of the run batch ARN.

Raises:

AccessDeniedException –

You do not have sufficient access to perform this action.
ConflictException –

The request cannot be applied to the target resource in its current state.
InternalServerException –

An unexpected error occurred. Try the request again.
RequestTimeoutException –

The request timed out.
ResourceNotFoundException –

The target resource was not found in the current Region.
ServiceQuotaExceededException –

The request exceeds a service quota.
ThrottlingException –

The request was denied due to request throttling.
ValidationException –

The input fails to satisfy the constraints specified by an Amazon Web Services service.
UnknownServiceError –

The service returned an error code this client does not model.

Source code in docs_src/capo_omics/_services/omics.py

def cancel_run_batch(
    self,
    batch_id: "capo_omics.types.batch_id.BatchId",
    *,
    config_overrides: Optional[OmicsClientConfig] = None,
) -> "capo_omics.types.cancel_run_batch_response.CancelRunBatchResponse":
    """<p>Cancels all runs within a specified batch. This operation prevents not-yet-submitted runs from starting and submits <code>CancelRun</code> requests for runs that have already started.</p> <p>Cancel is only allowed on batches in <code>PENDING</code>, <code>SUBMITTING</code>, or <code>INPROGRESS</code> state. Cancel operations are non-atomic and may be partially successful. Use <code>GetBatch</code> to review <code>successfulCancelSubmissionCount</code> and <code>failedCancelSubmissionCount</code> in the <code>submissionSummary</code>. Only one cancel or delete operation per batch is allowed at a time.</p>

    Args:
        batch_id: <p>The identifier portion of the run batch ARN.</p>

    Raises:
        capo_omics.errors.access_denied_exception.AccessDeniedException: <p>You do not have sufficient access to perform this action.</p>
        capo_omics.errors.conflict_exception.ConflictException: <p>The request cannot be applied to the target resource in its current state.</p>
        capo_omics.errors.internal_server_exception.InternalServerException: <p>An unexpected error occurred. Try the request again.</p>
        capo_omics.errors.request_timeout_exception.RequestTimeoutException: <p>The request timed out.</p>
        capo_omics.errors.resource_not_found_exception.ResourceNotFoundException: <p>The target resource was not found in the current Region.</p>
        capo_omics.errors.service_quota_exceeded_exception.ServiceQuotaExceededException: <p>The request exceeds a service quota.</p>
        capo_omics.errors.throttling_exception.ThrottlingException: <p>The request was denied due to request throttling.</p>
        capo_omics.errors.validation_exception.ValidationException: <p>The input fails to satisfy the constraints specified by an Amazon Web Services service.</p>
        capo_omics.errors.UnknownServiceError: The service returned an error code this client does not model.
    """

    def _handler(
        req: "OperationRequest[capo_omics.types.cancel_run_batch_request.CancelRunBatchRequest]",
    ) -> OperationResponse[
        "capo_omics.types.cancel_run_batch_response.CancelRunBatchResponse"
    ]:
        import capo_omics._operations.omics.cancel_run_batch

        output, http_response = (
            capo_omics._operations.omics.cancel_run_batch.cancel_run_batch(
                req.options, req.input
            )
        )
        return OperationResponse(output=output, response=http_response)

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("CancelRunBatch")
    )
    input_: capo_omics.types.cancel_run_batch_request.CancelRunBatchRequest = {
        "batch_id": batch_id
    }

    response = execute_pipeline(
        OperationRequest(input=input_, options=options_),
        handler=_handler,
        interceptors=list(interceptors_),
    )
    response.response.close()
    return response.output