Class PipelineServiceClient (1.58.0) 

PipelineServiceClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.aiplatform_v1.services.pipeline_service.transports.base.PipelineServiceTransport, typing.Callable[[...], google.cloud.aiplatform_v1.services.pipeline_service.transports.base.PipelineServiceTransport]]] = None, client_options: typing.Optional[typing.Union[google.api_core.client_options.ClientOptions, dict]] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)

A service for creating and managing Vertex AI's pipelines. This includes both TrainingPipeline resources (used for AutoML and custom training) and PipelineJob resources (used for Vertex AI Pipelines).

Properties

api_endpoint

Return the API endpoint used by the client instance.

Returns
Type Description
str The API endpoint used by the client instance.

transport

Returns the transport used by the client instance.

Returns
Type Description
PipelineServiceTransport The transport used by the client instance.

universe_domain

Return the universe domain used by the client instance.

Returns
Type Description
str The universe domain used by the client instance.

Methods

PipelineServiceClient

PipelineServiceClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.aiplatform_v1.services.pipeline_service.transports.base.PipelineServiceTransport, typing.Callable[[...], google.cloud.aiplatform_v1.services.pipeline_service.transports.base.PipelineServiceTransport]]] = None, client_options: typing.Optional[typing.Union[google.api_core.client_options.ClientOptions, dict]] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)

Instantiates the pipeline service client.

Parameters
Name Description
credentials Optional[google.auth.credentials.Credentials]

The authorization credentials to attach to requests. These credentials identify the application to the service; if none are specified, the client will attempt to ascertain the credentials from the environment.
transport Optional[Union[str,PipelineServiceTransport,Callable[..., PipelineServiceTransport]]]

The transport to use, or a Callable that constructs and returns a new transport. If a Callable is given, it will be called with the same set of initialization arguments as used in the PipelineServiceTransport constructor. If set to None, a transport is chosen automatically. NOTE: "rest" transport functionality is currently in a beta state (preview). We welcome your feedback via an issue in this library's source repository.
client_options Optional[Union[google.api_core.client_options.ClientOptions, dict]]

Custom options for the client. 1. The api_endpoint property can be used to override the default endpoint provided by the client when transport is not explicitly provided. Only if this property is not set and transport was not explicitly provided, the endpoint is determined by the GOOGLE_API_USE_MTLS_ENDPOINT environment variable, which have one of the following values: "always" (always use the default mTLS endpoint), "never" (always use the default regular endpoint) and "auto" (auto-switch to the default mTLS endpoint if client certificate is present; this is the default value). 2. If the GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is "true", then the client_cert_source property can be used to provide a client certificate for mTLS transport. If not provided, the default SSL client certificate will be used if present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is "false" or not set, no client certificate will be used. 3. The universe_domain property can be used to override the default "googleapis.com" universe. Note that the api_endpoint property still takes precedence; and universe_domain is currently not supported for mTLS.
client_info google.api_core.gapic_v1.client_info.ClientInfo

The client info used to send a user-agent string along with API requests. If None, then default info will be used. Generally, you only need to set this if you're developing your own client library.
Exceptions
Type Description
google.auth.exceptions.MutualTLSChannelError If mutual TLS transport creation failed for any reason.

__exit__

__exit__(type, value, traceback)

Releases underlying transport's resources.

artifact_path

artifact_path(
    project: str, location: str, metadata_store: str, artifact: str
) -> str

Returns a fully-qualified artifact string.

batch_cancel_pipeline_jobs

batch_cancel_pipeline_jobs(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.pipeline_service.BatchCancelPipelineJobsRequest,
            dict,
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    names: typing.Optional[typing.MutableSequence[str]] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation

Batch cancel PipelineJobs. Firstly the server will check if all the jobs are in non-terminal states, and skip the jobs that are already terminated. If the operation failed, none of the pipeline jobs are cancelled. The server will poll the states of all the pipeline jobs periodically to check the cancellation status. This operation will return an LRO.

# 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 aiplatform_v1

def sample_batch_cancel_pipeline_jobs():
    # Create a client
    client = aiplatform_v1.PipelineServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.BatchCancelPipelineJobsRequest(
        parent="parent_value",
        names=['names_value1', 'names_value2'],
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.BatchCancelPipelineJobsRequest, dict]

The request object. Request message for PipelineService.BatchCancelPipelineJobs.
parent str

Required. The name of the PipelineJobs' parent resource. Format: projects/{project}/locations/{location} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
names MutableSequence[str]

Required. The names of the PipelineJobs to cancel. A maximum of 32 PipelineJobs can be cancelled in a batch. Format: projects/{project}/locations/{location}/pipelineJobs/{pipelineJob} This corresponds to the names field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.api_core.operation.Operation An object representing a long-running operation. The result type for the operation will be BatchCancelPipelineJobsResponse Response message for PipelineService.BatchCancelPipelineJobs.

batch_delete_pipeline_jobs

batch_delete_pipeline_jobs(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.pipeline_service.BatchDeletePipelineJobsRequest,
            dict,
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    names: typing.Optional[typing.MutableSequence[str]] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation

Batch deletes PipelineJobs The Operation is atomic. If it fails, none of the PipelineJobs are deleted. If it succeeds, all of the PipelineJobs are deleted.

# 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 aiplatform_v1

def sample_batch_delete_pipeline_jobs():
    # Create a client
    client = aiplatform_v1.PipelineServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.BatchDeletePipelineJobsRequest(
        parent="parent_value",
        names=['names_value1', 'names_value2'],
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.BatchDeletePipelineJobsRequest, dict]

The request object. Request message for PipelineService.BatchDeletePipelineJobs.
parent str

Required. The name of the PipelineJobs' parent resource. Format: projects/{project}/locations/{location} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
names MutableSequence[str]

Required. The names of the PipelineJobs to delete. A maximum of 32 PipelineJobs can be deleted in a batch. Format: projects/{project}/locations/{location}/pipelineJobs/{pipelineJob} This corresponds to the names field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.api_core.operation.Operation An object representing a long-running operation. The result type for the operation will be BatchDeletePipelineJobsResponse Response message for PipelineService.BatchDeletePipelineJobs.

cancel_operation

cancel_operation(
    request: typing.Optional[
        google.longrunning.operations_pb2.CancelOperationRequest
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> None

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.

Parameters
Name Description
request .operations_pb2.CancelOperationRequest

The request object. Request message for CancelOperation method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

cancel_pipeline_job

cancel_pipeline_job(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.pipeline_service.CancelPipelineJobRequest,
            dict,
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> None

Cancels a PipelineJob. Starts asynchronous cancellation on the PipelineJob. The server makes a best effort to cancel the pipeline, but success is not guaranteed. Clients can use xref_PipelineService.GetPipelineJob or other methods to check whether the cancellation succeeded or whether the pipeline completed despite cancellation. On successful cancellation, the PipelineJob is not deleted; instead it becomes a pipeline with a xref_PipelineJob.error value with a google.rpc.Status.code][google.rpc.Status.code] of 1, corresponding to Code.CANCELLED, and xref_PipelineJob.state is set to CANCELLED.

# 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 aiplatform_v1

def sample_cancel_pipeline_job():
    # Create a client
    client = aiplatform_v1.PipelineServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.CancelPipelineJobRequest(
        name="name_value",
    )

    # Make the request
    client.cancel_pipeline_job(request=request)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.CancelPipelineJobRequest, dict]

The request object. Request message for PipelineService.CancelPipelineJob.
name str

Required. The name of the PipelineJob to cancel. Format: projects/{project}/locations/{location}/pipelineJobs/{pipeline_job} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

cancel_training_pipeline

cancel_training_pipeline(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.pipeline_service.CancelTrainingPipelineRequest,
            dict,
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> None

Cancels a TrainingPipeline. Starts asynchronous cancellation on the TrainingPipeline. The server makes a best effort to cancel the pipeline, but success is not guaranteed. Clients can use xref_PipelineService.GetTrainingPipeline or other methods to check whether the cancellation succeeded or whether the pipeline completed despite cancellation. On successful cancellation, the TrainingPipeline is not deleted; instead it becomes a pipeline with a xref_TrainingPipeline.error value with a google.rpc.Status.code][google.rpc.Status.code] of 1, corresponding to Code.CANCELLED, and xref_TrainingPipeline.state is set to CANCELLED.

# 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 aiplatform_v1

def sample_cancel_training_pipeline():
    # Create a client
    client = aiplatform_v1.PipelineServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.CancelTrainingPipelineRequest(
        name="name_value",
    )

    # Make the request
    client.cancel_training_pipeline(request=request)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.CancelTrainingPipelineRequest, dict]

The request object. Request message for PipelineService.CancelTrainingPipeline.
name str

Required. The name of the TrainingPipeline to cancel. Format: projects/{project}/locations/{location}/trainingPipelines/{training_pipeline} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

common_billing_account_path

common_billing_account_path(billing_account: str) -> str

Returns a fully-qualified billing_account string.

common_folder_path

common_folder_path(folder: str) -> str

Returns a fully-qualified folder string.

common_location_path

common_location_path(project: str, location: str) -> str

Returns a fully-qualified location string.

common_organization_path

common_organization_path(organization: str) -> str

Returns a fully-qualified organization string.

common_project_path

common_project_path(project: str) -> str

Returns a fully-qualified project string.

context_path

context_path(project: str, location: str, metadata_store: str, context: str) -> str

Returns a fully-qualified context string.

create_pipeline_job

create_pipeline_job(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.pipeline_service.CreatePipelineJobRequest,
            dict,
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    pipeline_job: typing.Optional[
        google.cloud.aiplatform_v1.types.pipeline_job.PipelineJob
    ] = None,
    pipeline_job_id: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.pipeline_job.PipelineJob

Creates a PipelineJob. A PipelineJob will run immediately when created.

# 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 aiplatform_v1

def sample_create_pipeline_job():
    # Create a client
    client = aiplatform_v1.PipelineServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.CreatePipelineJobRequest(
        parent="parent_value",
    )

    # Make the request
    response = client.create_pipeline_job(request=request)

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.CreatePipelineJobRequest, dict]

The request object. Request message for PipelineService.CreatePipelineJob.
parent str

Required. The resource name of the Location to create the PipelineJob in. Format: projects/{project}/locations/{location} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
pipeline_job google.cloud.aiplatform_v1.types.PipelineJob

Required. The PipelineJob to create. This corresponds to the pipeline_job field on the request instance; if request is provided, this should not be set.
pipeline_job_id str

The ID to use for the PipelineJob, which will become the final component of the PipelineJob name. If not provided, an ID will be automatically generated. This value should be less than 128 characters, and valid characters are /a-z][0-9]-/. This corresponds to the pipeline_job_id field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1.types.PipelineJob An instance of a machine learning PipelineJob.

create_training_pipeline

create_training_pipeline(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.pipeline_service.CreateTrainingPipelineRequest,
            dict,
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    training_pipeline: typing.Optional[
        google.cloud.aiplatform_v1.types.training_pipeline.TrainingPipeline
    ] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.training_pipeline.TrainingPipeline

Creates a TrainingPipeline. A created TrainingPipeline right away will be attempted to be run.

# 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 aiplatform_v1

def sample_create_training_pipeline():
    # Create a client
    client = aiplatform_v1.PipelineServiceClient()

    # Initialize request argument(s)
    training_pipeline = aiplatform_v1.TrainingPipeline()
    training_pipeline.display_name = "display_name_value"
    training_pipeline.training_task_definition = "training_task_definition_value"
    training_pipeline.training_task_inputs.null_value = "NULL_VALUE"

    request = aiplatform_v1.CreateTrainingPipelineRequest(
        parent="parent_value",
        training_pipeline=training_pipeline,
    )

    # Make the request
    response = client.create_training_pipeline(request=request)

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.CreateTrainingPipelineRequest, dict]

The request object. Request message for PipelineService.CreateTrainingPipeline.
parent str

Required. The resource name of the Location to create the TrainingPipeline in. Format: projects/{project}/locations/{location} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
training_pipeline google.cloud.aiplatform_v1.types.TrainingPipeline

Required. The TrainingPipeline to create. This corresponds to the training_pipeline field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1.types.TrainingPipeline The TrainingPipeline orchestrates tasks associated with training a Model. It always executes the training task, and optionally may also export data from Vertex AI's Dataset which becomes the training input, upload the Model to Vertex AI, and evaluate the Model.

custom_job_path

custom_job_path(project: str, location: str, custom_job: str) -> str

Returns a fully-qualified custom_job string.

delete_operation

delete_operation(
    request: typing.Optional[
        google.longrunning.operations_pb2.DeleteOperationRequest
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> None

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.

Parameters
Name Description
request .operations_pb2.DeleteOperationRequest

The request object. Request message for DeleteOperation method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

delete_pipeline_job

delete_pipeline_job(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.pipeline_service.DeletePipelineJobRequest,
            dict,
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation

Deletes a PipelineJob.

# 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 aiplatform_v1

def sample_delete_pipeline_job():
    # Create a client
    client = aiplatform_v1.PipelineServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.DeletePipelineJobRequest(
        name="name_value",
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.DeletePipelineJobRequest, dict]

The request object. Request message for PipelineService.DeletePipelineJob.
name str

Required. The name of the PipelineJob resource to be deleted. Format: projects/{project}/locations/{location}/pipelineJobs/{pipeline_job} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.api_core.operation.Operation An object representing a long-running operation. The result type for the operation will be google.protobuf.empty_pb2.Empty A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }

delete_training_pipeline

delete_training_pipeline(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.pipeline_service.DeleteTrainingPipelineRequest,
            dict,
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation

Deletes a TrainingPipeline.

# 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 aiplatform_v1

def sample_delete_training_pipeline():
    # Create a client
    client = aiplatform_v1.PipelineServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.DeleteTrainingPipelineRequest(
        name="name_value",
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.DeleteTrainingPipelineRequest, dict]

The request object. Request message for PipelineService.DeleteTrainingPipeline.
name str

Required. The name of the TrainingPipeline resource to be deleted. Format: projects/{project}/locations/{location}/trainingPipelines/{training_pipeline} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.api_core.operation.Operation An object representing a long-running operation. The result type for the operation will be google.protobuf.empty_pb2.Empty A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }

endpoint_path

endpoint_path(project: str, location: str, endpoint: str) -> str

Returns a fully-qualified endpoint string.

execution_path

execution_path(
    project: str, location: str, metadata_store: str, execution: str
) -> str

Returns a fully-qualified execution string.

from_service_account_file

from_service_account_file(filename: str, *args, **kwargs)

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

Parameter
Name Description
filename str

The path to the service account private key json file.
Returns
Type Description
PipelineServiceClient The constructed client.

from_service_account_info

from_service_account_info(info: dict, *args, **kwargs)

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

Parameter
Name Description
info dict

The service account private key info.
Returns
Type Description
PipelineServiceClient The constructed client.

from_service_account_json

from_service_account_json(filename: str, *args, **kwargs)

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

Parameter
Name Description
filename str

The path to the service account private key json file.
Returns
Type Description
PipelineServiceClient The constructed client.

get_iam_policy

get_iam_policy(
    request: typing.Optional[google.iam.v1.iam_policy_pb2.GetIamPolicyRequest] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.iam.v1.policy_pb2.Policy

Gets the IAM access control policy for a function.

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

Parameters
Name Description
request .iam_policy_pb2.GetIamPolicyRequest

The request object. Request message for GetIamPolicy method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
.policy_pb2.Policy Defines an Identity and Access Management (IAM) policy. It is used to specify access control policies for Cloud Platform resources. A Policy is a collection of bindings. A binding binds one or more members to a single role. Members can be user accounts, service accounts, Google groups, and domains (such as G Suite). A role is a named list of permissions (defined by IAM or configured by users). A binding can optionally specify a condition, which is a logic expression that further constrains the role binding based on attributes about the request and/or target resource. **JSON Example** :: { "bindings": [ { "role": "roles/resourcemanager.organizationAdmin", "members": [ "user:mike@example.com", "group:admins@example.com", "domain:google.com", "serviceAccount:my-project-id@appspot.gserviceaccount.com" ] }, { "role": "roles/resourcemanager.organizationViewer", "members": ["user:eve@example.com"], "condition": { "title": "expirable access", "description": "Does not grant access after Sep 2020", "expression": "request.time < timestamp('2020-10-01t00:00:00.000z')",="" }="" }="" ]="" }="" **yaml="" example**="" ::="" bindings:="" -="" members:="" -="" user:mike@example.com="" -="" group:admins@example.com="" -="" domain:google.com="" -="" serviceaccount:my-project-id@appspot.gserviceaccount.com="" role:="" roles/resourcemanager.organizationadmin="" -="" members:="" -="" user:eve@example.com="" role:="" roles/resourcemanager.organizationviewer="" condition:="" title:="" expirable="" access="" description:="" does="" not="" grant="" access="" after="" sep="" 2020="" expression:="" request.time="">< timestamp('2020-10-01t00:00:00.000z')="" for="" a="" description="" of="" iam="" and="" its="" features,="" see="" the="">IAM developer's guide __.

get_location

get_location(
    request: typing.Optional[
        google.cloud.location.locations_pb2.GetLocationRequest
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.location.locations_pb2.Location

Gets information about a location.

Parameters
Name Description
request .location_pb2.GetLocationRequest

The request object. Request message for GetLocation method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
.location_pb2.Location Location object.

get_mtls_endpoint_and_cert_source

get_mtls_endpoint_and_cert_source(
    client_options: typing.Optional[
        google.api_core.client_options.ClientOptions
    ] = None,
)

Deprecated. 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.

Parameter
Name Description
client_options google.api_core.client_options.ClientOptions

Custom options for the client. Only the api_endpoint and client_cert_source properties may be used in this method.
Exceptions
Type Description
google.auth.exceptions.MutualTLSChannelError If any errors happen.
Returns
Type Description
Tuple[str, Callable[[], Tuple[bytes, bytes]]] returns the API endpoint and the client cert source to use.

get_operation

get_operation(
    request: typing.Optional[
        google.longrunning.operations_pb2.GetOperationRequest
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.longrunning.operations_pb2.Operation

Gets the latest state of a long-running operation.

Parameters
Name Description
request .operations_pb2.GetOperationRequest

The request object. Request message for GetOperation method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
.operations_pb2.Operation An Operation object.

get_pipeline_job

get_pipeline_job(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.pipeline_service.GetPipelineJobRequest,
            dict,
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.pipeline_job.PipelineJob

Gets a PipelineJob.

# 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 aiplatform_v1

def sample_get_pipeline_job():
    # Create a client
    client = aiplatform_v1.PipelineServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.GetPipelineJobRequest(
        name="name_value",
    )

    # Make the request
    response = client.get_pipeline_job(request=request)

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.GetPipelineJobRequest, dict]

The request object. Request message for PipelineService.GetPipelineJob.
name str

Required. The name of the PipelineJob resource. Format: projects/{project}/locations/{location}/pipelineJobs/{pipeline_job} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1.types.PipelineJob An instance of a machine learning PipelineJob.

get_training_pipeline

get_training_pipeline(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.pipeline_service.GetTrainingPipelineRequest,
            dict,
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.training_pipeline.TrainingPipeline

Gets a TrainingPipeline.

# 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 aiplatform_v1

def sample_get_training_pipeline():
    # Create a client
    client = aiplatform_v1.PipelineServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.GetTrainingPipelineRequest(
        name="name_value",
    )

    # Make the request
    response = client.get_training_pipeline(request=request)

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.GetTrainingPipelineRequest, dict]

The request object. Request message for PipelineService.GetTrainingPipeline.
name str

Required. The name of the TrainingPipeline resource. Format: projects/{project}/locations/{location}/trainingPipelines/{training_pipeline} This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1.types.TrainingPipeline The TrainingPipeline orchestrates tasks associated with training a Model. It always executes the training task, and optionally may also export data from Vertex AI's Dataset which becomes the training input, upload the Model to Vertex AI, and evaluate the Model.

list_locations

list_locations(
    request: typing.Optional[
        google.cloud.location.locations_pb2.ListLocationsRequest
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.location.locations_pb2.ListLocationsResponse

Lists information about the supported locations for this service.

Parameters
Name Description
request .location_pb2.ListLocationsRequest

The request object. Request message for ListLocations method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
.location_pb2.ListLocationsResponse Response message for ListLocations method.

list_operations

list_operations(
    request: typing.Optional[
        google.longrunning.operations_pb2.ListOperationsRequest
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.longrunning.operations_pb2.ListOperationsResponse

Lists operations that match the specified filter in the request.

Parameters
Name Description
request .operations_pb2.ListOperationsRequest

The request object. Request message for ListOperations method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
.operations_pb2.ListOperationsResponse Response message for ListOperations method.

list_pipeline_jobs

list_pipeline_jobs(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.pipeline_service.ListPipelineJobsRequest,
            dict,
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.services.pipeline_service.pagers.ListPipelineJobsPager

Lists PipelineJobs in a Location.

# 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 aiplatform_v1

def sample_list_pipeline_jobs():
    # Create a client
    client = aiplatform_v1.PipelineServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.ListPipelineJobsRequest(
        parent="parent_value",
    )

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

    # Handle the response
    for response in page_result:
        print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.ListPipelineJobsRequest, dict]

The request object. Request message for PipelineService.ListPipelineJobs.
parent str

Required. The resource name of the Location to list the PipelineJobs from. Format: projects/{project}/locations/{location} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1.services.pipeline_service.pagers.ListPipelineJobsPager Response message for PipelineService.ListPipelineJobs Iterating over this object will yield results and resolve additional pages automatically.

list_training_pipelines

list_training_pipelines(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.pipeline_service.ListTrainingPipelinesRequest,
            dict,
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> (
    google.cloud.aiplatform_v1.services.pipeline_service.pagers.ListTrainingPipelinesPager
)

Lists TrainingPipelines in a Location.

# 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 aiplatform_v1

def sample_list_training_pipelines():
    # Create a client
    client = aiplatform_v1.PipelineServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.ListTrainingPipelinesRequest(
        parent="parent_value",
    )

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

    # Handle the response
    for response in page_result:
        print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.ListTrainingPipelinesRequest, dict]

The request object. Request message for PipelineService.ListTrainingPipelines.
parent str

Required. The resource name of the Location to list the TrainingPipelines from. Format: projects/{project}/locations/{location} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
google.cloud.aiplatform_v1.services.pipeline_service.pagers.ListTrainingPipelinesPager Response message for PipelineService.ListTrainingPipelines Iterating over this object will yield results and resolve additional pages automatically.

model_path

model_path(project: str, location: str, model: str) -> str

Returns a fully-qualified model string.

network_path

network_path(project: str, network: str) -> str

Returns a fully-qualified network string.

parse_artifact_path

parse_artifact_path(path: str) -> typing.Dict[str, str]

Parses a artifact path into its component segments.

parse_common_billing_account_path

parse_common_billing_account_path(path: str) -> typing.Dict[str, str]

Parse a billing_account path into its component segments.

parse_common_folder_path

parse_common_folder_path(path: str) -> typing.Dict[str, str]

Parse a folder path into its component segments.

parse_common_location_path

parse_common_location_path(path: str) -> typing.Dict[str, str]

Parse a location path into its component segments.

parse_common_organization_path

parse_common_organization_path(path: str) -> typing.Dict[str, str]

Parse a organization path into its component segments.

parse_common_project_path

parse_common_project_path(path: str) -> typing.Dict[str, str]

Parse a project path into its component segments.

parse_context_path

parse_context_path(path: str) -> typing.Dict[str, str]

Parses a context path into its component segments.

parse_custom_job_path

parse_custom_job_path(path: str) -> typing.Dict[str, str]

Parses a custom_job path into its component segments.

parse_endpoint_path

parse_endpoint_path(path: str) -> typing.Dict[str, str]

Parses a endpoint path into its component segments.

parse_execution_path

parse_execution_path(path: str) -> typing.Dict[str, str]

Parses a execution path into its component segments.

parse_model_path

parse_model_path(path: str) -> typing.Dict[str, str]

Parses a model path into its component segments.

parse_network_path

parse_network_path(path: str) -> typing.Dict[str, str]

Parses a network path into its component segments.

parse_pipeline_job_path

parse_pipeline_job_path(path: str) -> typing.Dict[str, str]

Parses a pipeline_job path into its component segments.

parse_training_pipeline_path

parse_training_pipeline_path(path: str) -> typing.Dict[str, str]

Parses a training_pipeline path into its component segments.

pipeline_job_path

pipeline_job_path(project: str, location: str, pipeline_job: str) -> str

Returns a fully-qualified pipeline_job string.

set_iam_policy

set_iam_policy(
    request: typing.Optional[google.iam.v1.iam_policy_pb2.SetIamPolicyRequest] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.iam.v1.policy_pb2.Policy

Sets the IAM access control policy on the specified function.

Replaces any existing policy.

Parameters
Name Description
request .iam_policy_pb2.SetIamPolicyRequest

The request object. Request message for SetIamPolicy method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
.policy_pb2.Policy Defines an Identity and Access Management (IAM) policy. It is used to specify access control policies for Cloud Platform resources. A Policy is a collection of bindings. A binding binds one or more members to a single role. Members can be user accounts, service accounts, Google groups, and domains (such as G Suite). A role is a named list of permissions (defined by IAM or configured by users). A binding can optionally specify a condition, which is a logic expression that further constrains the role binding based on attributes about the request and/or target resource. **JSON Example** :: { "bindings": [ { "role": "roles/resourcemanager.organizationAdmin", "members": [ "user:mike@example.com", "group:admins@example.com", "domain:google.com", "serviceAccount:my-project-id@appspot.gserviceaccount.com" ] }, { "role": "roles/resourcemanager.organizationViewer", "members": ["user:eve@example.com"], "condition": { "title": "expirable access", "description": "Does not grant access after Sep 2020", "expression": "request.time < timestamp('2020-10-01t00:00:00.000z')",="" }="" }="" ]="" }="" **yaml="" example**="" ::="" bindings:="" -="" members:="" -="" user:mike@example.com="" -="" group:admins@example.com="" -="" domain:google.com="" -="" serviceaccount:my-project-id@appspot.gserviceaccount.com="" role:="" roles/resourcemanager.organizationadmin="" -="" members:="" -="" user:eve@example.com="" role:="" roles/resourcemanager.organizationviewer="" condition:="" title:="" expirable="" access="" description:="" does="" not="" grant="" access="" after="" sep="" 2020="" expression:="" request.time="">< timestamp('2020-10-01t00:00:00.000z')="" for="" a="" description="" of="" iam="" and="" its="" features,="" see="" the="">IAM developer's guide __.

test_iam_permissions

test_iam_permissions(
    request: typing.Optional[
        google.iam.v1.iam_policy_pb2.TestIamPermissionsRequest
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.iam.v1.iam_policy_pb2.TestIamPermissionsResponse

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.

Parameters
Name Description
request .iam_policy_pb2.TestIamPermissionsRequest

The request object. Request message for TestIamPermissions method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
.iam_policy_pb2.TestIamPermissionsResponse Response message for TestIamPermissions method.

training_pipeline_path

training_pipeline_path(project: str, location: str, training_pipeline: str) -> str

Returns a fully-qualified training_pipeline string.

wait_operation

wait_operation(
    request: typing.Optional[
        google.longrunning.operations_pb2.WaitOperationRequest
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.longrunning.operations_pb2.Operation

Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state.

If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns google.rpc.Code.UNIMPLEMENTED.

Parameters
Name Description
request .operations_pb2.WaitOperationRequest

The request object. Request message for WaitOperation method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
.operations_pb2.Operation An Operation object.