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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. |
client_options |
Optional[Union[google.api_core.client_options.ClientOptions, dict]]
Custom options for the client. 1. The |
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 |
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: |
names |
MutableSequence[str]
Required. The names of the PipelineJobs to cancel. A maximum of 32 PipelineJobs can be cancelled in a batch. Format: |
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: |
names |
MutableSequence[str]
Required. The names of the PipelineJobs to delete. A maximum of 32 PipelineJobs can be deleted in a batch. Format: |
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 |
The request object. Request message for |
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: |
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: |
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: |
pipeline_job |
google.cloud.aiplatform_v1.types.PipelineJob
Required. The PipelineJob to create. This corresponds to the |
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 |
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: |
training_pipeline |
google.cloud.aiplatform_v1.types.TrainingPipeline
Required. The TrainingPipeline to create. This corresponds to the |
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 |
The request object. Request message for |
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: |
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: |
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 |
The request object. Request message for |
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 |
|
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 |
The request object. Request message for |
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 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 |
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 |
The request object. Request message for |
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 |
|
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: |
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: |
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 |
The request object. Request message for |
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 |
|
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 |
The request object. Request message for |
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 |
|
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: |
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: |
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 |
The request object. Request message for |
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 |
|
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 |
The request object. Request message for |
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 |
|
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 |
The request object. Request message for |
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 |
|
An Operation object. |