update_workflow ¶

def update_workflow(
    self,
    id: "capo_omics.types.workflow_id.WorkflowId",
    *,
    config_overrides: Optional[OmicsClientConfig] = None,
    name: Optional["capo_omics.types.workflow_name.WorkflowName"] = None,
    description: Optional[
        "capo_omics.types.workflow_description.WorkflowDescription"
    ] = None,
    storage_type: Optional["capo_omics.types.storage_type.StorageType"] = None,
    storage_capacity: Optional[int] = None,
    readme_markdown: Optional[
        "capo_omics.types.readme_markdown.ReadmeMarkdown"
    ] = None,
) -> None:
    """<p>Updates information about a workflow.</p> <p>You can update the following workflow information:</p> <ul> <li> <p>Name</p> </li> <li> <p>Description</p> </li> <li> <p>Default storage type</p> </li> <li> <p>Default storage capacity (with workflow ID)</p> </li> </ul> <p>This operation returns a response with no body if the operation is successful. You can check the workflow updates by calling the <code>GetWorkflow</code> API operation.</p> <p>For more information, see <a href="https://docs.aws.amazon.com/omics/latest/dev/update-private-workflow.html">Update a private workflow</a> in the <i>Amazon Web Services HealthOmics User Guide</i>.</p>

    Args:
        id: <p>The workflow's ID.</p>
        name: <p>A name for the workflow.</p>
        description: <p>A description for the workflow.</p>
        storage_type: <p>The default storage type for runs that use this workflow. STATIC storage allocates a fixed amount of storage. DYNAMIC storage dynamically scales the storage up or down, based on file system utilization. For more information about static and dynamic storage, see <a href="https://docs.aws.amazon.com/omics/latest/dev/Using-workflows.html">Running workflows</a> in the <i>Amazon Web Services HealthOmics User Guide</i>. </p>
        storage_capacity: <p>The default static storage capacity (in gibibytes) for runs that use this workflow or workflow version. </p>
        readme_markdown: <p>The markdown content for the workflow's README file. This provides documentation and usage information for users of the workflow.</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.update_workflow_request.UpdateWorkflowRequest]",
    ) -> OperationResponse[None]:
        import capo_omics._operations.omics.update_workflow

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

    interceptors_, options_ = self.operation_options(
        config_overrides, OperationLogging("UpdateWorkflow")
    )
    input_: capo_omics.types.update_workflow_request.UpdateWorkflowRequest = {
        "id": id
    }
    if name is not None:
        input_["name"] = name
    if description is not None:
        input_["description"] = description
    if storage_type is not None:
        input_["storage_type"] = storage_type
    if storage_capacity is not None:
        input_["storage_capacity"] = storage_capacity
    if readme_markdown is not None:
        input_["readme_markdown"] = readme_markdown

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