Class WorkflowTemplateServiceAsyncClient (5.7.0)

The API interface for managing Workflow Templates in the Dataproc API.

Returns the transport used by the client instance.

Instantiates the workflow template service client.

Starts asynchronous cancellation on a long-running operation.

The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns google.rpc.Code.UNIMPLEMENTED.

Returns a fully-qualified billing_account string.

Returns a fully-qualified folder string.

Returns a fully-qualified location string.

Returns a fully-qualified organization string.

Returns a fully-qualified project string.

Creates new workflow template.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import dataproc_v1

async def sample_create_workflow_template():
    # Create a client
    client = dataproc_v1.WorkflowTemplateServiceAsyncClient()

    # Initialize request argument(s)
    template = dataproc_v1.WorkflowTemplate()
    template.id = "id_value"
    template.placement.managed_cluster.cluster_name = "cluster_name_value"
    template.jobs.hadoop_job.main_jar_file_uri = "main_jar_file_uri_value"
    template.jobs.step_id = "step_id_value"

    request = dataproc_v1.CreateWorkflowTemplateRequest(
        parent="parent_value",
        template=template,
    )

    # Make the request
    response = await client.create_workflow_template(request=request)

    # Handle the response
    print(response)

Deletes a long-running operation.

This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns google.rpc.Code.UNIMPLEMENTED.

Deletes a workflow template. It does not cancel in-progress workflows.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import dataproc_v1

async def sample_delete_workflow_template():
    # Create a client
    client = dataproc_v1.WorkflowTemplateServiceAsyncClient()

    # Initialize request argument(s)
    request = dataproc_v1.DeleteWorkflowTemplateRequest(
        name="name_value",
    )

    # Make the request
    await client.delete_workflow_template(request=request)

Creates an instance of this client using the provided credentials file.

Creates an instance of this client using the provided credentials info.

Creates an instance of this client using the provided credentials file.

Gets the IAM access control policy for a function.

Returns an empty policy if the function exists and does not have a policy set.

Return the API endpoint and client cert source for mutual TLS.

The client cert source is determined in the following order: (1) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is not "true", the client cert source is None. (2) if client_options.client_cert_source is provided, use the provided one; if the default client cert source exists, use the default one; otherwise the client cert source is None.

The API endpoint is determined in the following order: (1) if client_options.api_endpoint if provided, use the provided one. (2) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is "always", use the default mTLS endpoint; if the environment variable is "never", use the default API endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise use the default API endpoint.

More details can be found at https://google.aip.dev/auth/4114.

Gets the latest state of a long-running operation.

Returns an appropriate transport class.

Retrieves the latest workflow template.

Can retrieve previously instantiated template by specifying optional version parameter.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import dataproc_v1

async def sample_get_workflow_template():
    # Create a client
    client = dataproc_v1.WorkflowTemplateServiceAsyncClient()

    # Initialize request argument(s)
    request = dataproc_v1.GetWorkflowTemplateRequest(
        name="name_value",
    )

    # Make the request
    response = await client.get_workflow_template(request=request)

    # Handle the response
    print(response)

Instantiates a template and begins execution.

This method is equivalent to executing the sequence xref_CreateWorkflowTemplate, xref_InstantiateWorkflowTemplate, xref_DeleteWorkflowTemplate.

The returned Operation can be used to track execution of workflow by polling operations.get][google.longrunning.Operations.GetOperation]. The Operation will complete when entire workflow is finished.

The running workflow can be aborted via operations.cancel][google.longrunning.Operations.CancelOperation]. This will cause any inflight jobs to be cancelled and workflow-owned clusters to be deleted.

The Operation.metadata][google.longrunning.Operation.metadata] will be WorkflowMetadata <https://cloud.google.com/dataproc/docs/reference/rpc/google.cloud.dataproc.v1#workflowmetadata>. Also see Using WorkflowMetadata <https://cloud.google.com/dataproc/docs/concepts/workflows/debugging#using_workflowmetadata>.

On successful completion, Operation.response][google.longrunning.Operation.response] will be Empty][google.protobuf.Empty].

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import dataproc_v1

async def sample_instantiate_inline_workflow_template():
    # Create a client
    client = dataproc_v1.WorkflowTemplateServiceAsyncClient()

    # Initialize request argument(s)
    template = dataproc_v1.WorkflowTemplate()
    template.id = "id_value"
    template.placement.managed_cluster.cluster_name = "cluster_name_value"
    template.jobs.hadoop_job.main_jar_file_uri = "main_jar_file_uri_value"
    template.jobs.step_id = "step_id_value"

    request = dataproc_v1.InstantiateInlineWorkflowTemplateRequest(
        parent="parent_value",
        template=template,
    )

    # Make the request
    operation = client.instantiate_inline_workflow_template(request=request)

    print("Waiting for operation to complete...")

    response = (await operation).result()

    # Handle the response
    print(response)

Instantiates a template and begins execution.

The returned Operation can be used to track execution of workflow by polling operations.get][google.longrunning.Operations.GetOperation]. The Operation will complete when entire workflow is finished.

The running workflow can be aborted via operations.cancel][google.longrunning.Operations.CancelOperation]. This will cause any inflight jobs to be cancelled and workflow-owned clusters to be deleted.

The Operation.metadata][google.longrunning.Operation.metadata] will be WorkflowMetadata <https://cloud.google.com/dataproc/docs/reference/rpc/google.cloud.dataproc.v1#workflowmetadata>. Also see Using WorkflowMetadata <https://cloud.google.com/dataproc/docs/concepts/workflows/debugging#using_workflowmetadata>.

On successful completion, Operation.response][google.longrunning.Operation.response] will be Empty][google.protobuf.Empty].

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import dataproc_v1

async def sample_instantiate_workflow_template():
    # Create a client
    client = dataproc_v1.WorkflowTemplateServiceAsyncClient()

    # Initialize request argument(s)
    request = dataproc_v1.InstantiateWorkflowTemplateRequest(
        name="name_value",
    )

    # Make the request
    operation = client.instantiate_workflow_template(request=request)

    print("Waiting for operation to complete...")

    response = (await operation).result()

    # Handle the response
    print(response)

Lists operations that match the specified filter in the request.

Lists workflows that match the specified filter in the request.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import dataproc_v1

async def sample_list_workflow_templates():
    # Create a client
    client = dataproc_v1.WorkflowTemplateServiceAsyncClient()

    # Initialize request argument(s)
    request = dataproc_v1.ListWorkflowTemplatesRequest(
        parent="parent_value",
    )

    # Make the request
    page_result = client.list_workflow_templates(request=request)

    # Handle the response
    async for response in page_result:
        print(response)

Returns a fully-qualified node_group string.

Parse a billing_account path into its component segments.

Parse a folder path into its component segments.

Parse a location path into its component segments.

Parse a organization path into its component segments.

Parse a project path into its component segments.

Parses a node_group path into its component segments.

Parses a service path into its component segments.

Parses a workflow_template path into its component segments.

Returns a fully-qualified service string.

Sets the IAM access control policy on the specified function.

Replaces any existing policy.

Tests the specified IAM permissions against the IAM access control policy for a function.

If the function does not exist, this will return an empty set of permissions, not a NOT_FOUND error.

Updates (replaces) workflow template. The updated template must contain version that matches the current server version.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import dataproc_v1

async def sample_update_workflow_template():
    # Create a client
    client = dataproc_v1.WorkflowTemplateServiceAsyncClient()

    # Initialize request argument(s)
    template = dataproc_v1.WorkflowTemplate()
    template.id = "id_value"
    template.placement.managed_cluster.cluster_name = "cluster_name_value"
    template.jobs.hadoop_job.main_jar_file_uri = "main_jar_file_uri_value"
    template.jobs.step_id = "step_id_value"

    request = dataproc_v1.UpdateWorkflowTemplateRequest(
        template=template,
    )

    # Make the request
    response = await client.update_workflow_template(request=request)

    # Handle the response
    print(response)

Returns a fully-qualified workflow_template string.