Class ModelMonitoringServiceClient (1.49.0) 

ModelMonitoringServiceClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.aiplatform_v1beta1.services.model_monitoring_service.transports.base.ModelMonitoringServiceTransport]] = 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 Model moitoring. This includes ModelMonitor resources, ModelMonitoringJob resources.

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
ModelMonitoringServiceTransport 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

ModelMonitoringServiceClient

ModelMonitoringServiceClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.aiplatform_v1beta1.services.model_monitoring_service.transports.base.ModelMonitoringServiceTransport]] = 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 model monitoring 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 Union[str, ModelMonitoringServiceTransport]

The transport to use. 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.

batch_prediction_job_path

batch_prediction_job_path(
    project: str, location: str, batch_prediction_job: str
) -> str

Returns a fully-qualified batch_prediction_job string.

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.

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.

create_model_monitor

create_model_monitor(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1beta1.types.model_monitoring_service.CreateModelMonitorRequest,
            dict,
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    model_monitor: typing.Optional[
        google.cloud.aiplatform_v1beta1.types.model_monitor.ModelMonitor
    ] = 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

Creates a ModelMonitor.

# 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_v1beta1

def sample_create_model_monitor():
    # Create a client
    client = aiplatform_v1beta1.ModelMonitoringServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.CreateModelMonitorRequest(
        parent="parent_value",
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1beta1.types.CreateModelMonitorRequest, dict]

The request object. Request message for ModelMonitoringService.CreateModelMonitor.
parent str

Required. The resource name of the Location to create the ModelMonitor 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.
model_monitor google.cloud.aiplatform_v1beta1.types.ModelMonitor

Required. The ModelMonitor to create. This corresponds to the model_monitor 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 ModelMonitor Vertex AI Model Monitoring Service serves as a central hub for the analysis and visualization of data quality and performance related to models. ModelMonitor stands as a top level resource for overseeing your model monitoring tasks.

create_model_monitoring_job

create_model_monitoring_job(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1beta1.types.model_monitoring_service.CreateModelMonitoringJobRequest,
            dict,
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    model_monitoring_job: typing.Optional[
        google.cloud.aiplatform_v1beta1.types.model_monitoring_job.ModelMonitoringJob
    ] = 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_v1beta1.types.model_monitoring_job.ModelMonitoringJob

Creates a ModelMonitoringJob.

# 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_v1beta1

def sample_create_model_monitoring_job():
    # Create a client
    client = aiplatform_v1beta1.ModelMonitoringServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.CreateModelMonitoringJobRequest(
        parent="parent_value",
    )

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

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1beta1.types.CreateModelMonitoringJobRequest, dict]

The request object. Request message for ModelMonitoringService.CreateModelMonitoringJob.
parent str

Required. The parent of the ModelMonitoringJob. Format: projects/{project}/locations/{location}/modelMoniitors/{model_monitor} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
model_monitoring_job google.cloud.aiplatform_v1beta1.types.ModelMonitoringJob

Required. The ModelMonitoringJob to create This corresponds to the model_monitoring_job 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_v1beta1.types.ModelMonitoringJob Represents a model monitoring job that analyze dataset using different monitoring algorithm.

dataset_path

dataset_path(project: str, location: str, dataset: str) -> str

Returns a fully-qualified dataset string.

delete_model_monitor

delete_model_monitor(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1beta1.types.model_monitoring_service.DeleteModelMonitorRequest,
            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 ModelMonitor.

# 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_v1beta1

def sample_delete_model_monitor():
    # Create a client
    client = aiplatform_v1beta1.ModelMonitoringServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.DeleteModelMonitorRequest(
        name="name_value",
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1beta1.types.DeleteModelMonitorRequest, dict]

The request object. Request message for ModelMonitoringService.DeleteModelMonitor.
name str

Required. The name of the ModelMonitor resource to be deleted. Format: projects/{project}/locations/{location}/modelMonitords/{model_monitor} 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_model_monitoring_job

delete_model_monitoring_job(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1beta1.types.model_monitoring_service.DeleteModelMonitoringJobRequest,
            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 ModelMonitoringJob.

# 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_v1beta1

def sample_delete_model_monitoring_job():
    # Create a client
    client = aiplatform_v1beta1.ModelMonitoringServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.DeleteModelMonitoringJobRequest(
        name="name_value",
    )

    # Make the request
    operation = client.delete_model_monitoring_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_v1beta1.types.DeleteModelMonitoringJobRequest, dict]

The request object. Request message for ModelMonitoringService.DeleteModelMonitoringJob.
name str

Required. The resource name of the model monitoring job to delete. Format: projects/{project}/locations/{location}/modelMonitors/{model_monitor}/modelMonitoringJobs/{model_monitoring_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_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.

endpoint_path

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

Returns a fully-qualified endpoint 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
ModelMonitoringServiceClient 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
ModelMonitoringServiceClient 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
ModelMonitoringServiceClient 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_model_monitor

get_model_monitor(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1beta1.types.model_monitoring_service.GetModelMonitorRequest,
            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_v1beta1.types.model_monitor.ModelMonitor

Gets a ModelMonitor.

# 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_v1beta1

def sample_get_model_monitor():
    # Create a client
    client = aiplatform_v1beta1.ModelMonitoringServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.GetModelMonitorRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1beta1.types.GetModelMonitorRequest, dict]

The request object. Request message for ModelMonitoringService.GetModelMonitor.
name str

Required. The name of the ModelMonitor resource. Format: projects/{project}/locations/{location}/modelMonitors/{model_monitor} 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_v1beta1.types.ModelMonitor Vertex AI Model Monitoring Service serves as a central hub for the analysis and visualization of data quality and performance related to models. ModelMonitor stands as a top level resource for overseeing your model monitoring tasks.

get_model_monitoring_job

get_model_monitoring_job(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1beta1.types.model_monitoring_service.GetModelMonitoringJobRequest,
            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_v1beta1.types.model_monitoring_job.ModelMonitoringJob

Gets a ModelMonitoringJob.

# 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_v1beta1

def sample_get_model_monitoring_job():
    # Create a client
    client = aiplatform_v1beta1.ModelMonitoringServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.GetModelMonitoringJobRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1beta1.types.GetModelMonitoringJobRequest, dict]

The request object. Request message for ModelMonitoringService.GetModelMonitoringJob.
name str

Required. The resource name of the ModelMonitoringJob. Format: projects/{project}/locations/{location}/modelMonitors/{model_monitor}/modelMonitoringJobs/{model_monitoring_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_v1beta1.types.ModelMonitoringJob Represents a model monitoring job that analyze dataset using different monitoring algorithm.

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.

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_model_monitoring_jobs

list_model_monitoring_jobs(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1beta1.types.model_monitoring_service.ListModelMonitoringJobsRequest,
            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_v1beta1.services.model_monitoring_service.pagers.ListModelMonitoringJobsPager
)

Lists ModelMonitoringJobs. Callers may choose to read across multiple Monitors as per AIP-159 <https://google.aip.dev/159>__ by using '-' (the hyphen or dash character) as a wildcard character instead of modelMonitor id in the parent. Format projects/{project_id}/locations/{location}/moodelMonitors/-/modelMonitoringJobs

# 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_v1beta1

def sample_list_model_monitoring_jobs():
    # Create a client
    client = aiplatform_v1beta1.ModelMonitoringServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.ListModelMonitoringJobsRequest(
        parent="parent_value",
    )

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

    # Handle the response
    for response in page_result:
        print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1beta1.types.ListModelMonitoringJobsRequest, dict]

The request object. Request message for ModelMonitoringService.ListModelMonitoringJobs.
parent str

Required. The parent of the ModelMonitoringJob. Format: projects/{project}/locations/{location}/modelMonitors/{model_monitor} 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_v1beta1.services.model_monitoring_service.pagers.ListModelMonitoringJobsPager Response message for ModelMonitoringService.ListModelMonitoringJobs. Iterating over this object will yield results and resolve additional pages automatically.

list_model_monitors

list_model_monitors(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1beta1.types.model_monitoring_service.ListModelMonitorsRequest,
            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_v1beta1.services.model_monitoring_service.pagers.ListModelMonitorsPager
)

Lists ModelMonitors 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_v1beta1

def sample_list_model_monitors():
    # Create a client
    client = aiplatform_v1beta1.ModelMonitoringServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.ListModelMonitorsRequest(
        parent="parent_value",
    )

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

    # Handle the response
    for response in page_result:
        print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1beta1.types.ListModelMonitorsRequest, dict]

The request object. Request message for ModelMonitoringService.ListModelMonitors.
parent str

Required. The resource name of the Location to list the ModelMonitors 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_v1beta1.services.model_monitoring_service.pagers.ListModelMonitorsPager Response message for ModelMonitoringService.ListModelMonitors Iterating over this object will yield results and resolve additional pages automatically.

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.

model_monitor_path

model_monitor_path(project: str, location: str, model_monitor: str) -> str

Returns a fully-qualified model_monitor string.

model_monitoring_job_path

model_monitoring_job_path(
    project: str, location: str, model_monitor: str, model_monitoring_job: str
) -> str

Returns a fully-qualified model_monitoring_job string.

model_path

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

Returns a fully-qualified model string.

parse_batch_prediction_job_path

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

Parses a batch_prediction_job 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_dataset_path

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

Parses a dataset 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_model_monitor_path

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

Parses a model_monitor path into its component segments.

parse_model_monitoring_job_path

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

Parses a model_monitoring_job 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_schedule_path

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

Parses a schedule path into its component segments.

schedule_path

schedule_path(project: str, location: str, schedule: str) -> str

Returns a fully-qualified schedule string.

search_model_monitoring_alerts

search_model_monitoring_alerts(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1beta1.types.model_monitoring_service.SearchModelMonitoringAlertsRequest,
            dict,
        ]
    ] = None,
    *,
    model_monitor: 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_v1beta1.services.model_monitoring_service.pagers.SearchModelMonitoringAlertsPager
)

Returns the Model Monitoring alerts.

# 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_v1beta1

def sample_search_model_monitoring_alerts():
    # Create a client
    client = aiplatform_v1beta1.ModelMonitoringServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.SearchModelMonitoringAlertsRequest(
        model_monitor="model_monitor_value",
    )

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

    # Handle the response
    for response in page_result:
        print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1beta1.types.SearchModelMonitoringAlertsRequest, dict]

The request object. Request message for ModelMonitoringService.SearchModelMonitoringAlerts.
model_monitor str

Required. ModelMonitor resource name. Format: projects/{project}/locations/{location}/modelMonitors/{model_monitor} This corresponds to the model_monitor 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_v1beta1.services.model_monitoring_service.pagers.SearchModelMonitoringAlertsPager Response message for ModelMonitoringService.SearchModelMonitoringAlerts. Iterating over this object will yield results and resolve additional pages automatically.

search_model_monitoring_stats

search_model_monitoring_stats(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1beta1.types.model_monitoring_service.SearchModelMonitoringStatsRequest,
            dict,
        ]
    ] = None,
    *,
    model_monitor: 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_v1beta1.services.model_monitoring_service.pagers.SearchModelMonitoringStatsPager
)

Searches Model Monitoring Stats generated within a given time window.

# 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_v1beta1

def sample_search_model_monitoring_stats():
    # Create a client
    client = aiplatform_v1beta1.ModelMonitoringServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.SearchModelMonitoringStatsRequest(
        model_monitor="model_monitor_value",
    )

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

    # Handle the response
    for response in page_result:
        print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1beta1.types.SearchModelMonitoringStatsRequest, dict]

The request object. Request message for ModelMonitoringService.SearchModelMonitoringStats.
model_monitor str

Required. ModelMonitor resource name. Format: projects/{project}/locations/{location}/modelMonitors/{model_monitor} This corresponds to the model_monitor 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_v1beta1.services.model_monitoring_service.pagers.SearchModelMonitoringStatsPager Response message for ModelMonitoringService.SearchModelMonitoringStats. Iterating over this object will yield results and resolve additional pages automatically.

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.

update_model_monitor

update_model_monitor(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1beta1.types.model_monitoring_service.UpdateModelMonitorRequest,
            dict,
        ]
    ] = None,
    *,
    model_monitor: typing.Optional[
        google.cloud.aiplatform_v1beta1.types.model_monitor.ModelMonitor
    ] = None,
    update_mask: typing.Optional[google.protobuf.field_mask_pb2.FieldMask] = 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

Updates a ModelMonitor.

# 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_v1beta1

def sample_update_model_monitor():
    # Create a client
    client = aiplatform_v1beta1.ModelMonitoringServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.UpdateModelMonitorRequest(
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1beta1.types.UpdateModelMonitorRequest, dict]

The request object. Request message for ModelMonitoringService.UpdateModelMonitor.
model_monitor google.cloud.aiplatform_v1beta1.types.ModelMonitor

Required. The model monitoring configuration which replaces the resource on the server. This corresponds to the model_monitor field on the request instance; if request is provided, this should not be set.
update_mask google.protobuf.field_mask_pb2.FieldMask

Required. Mask specifying which fields to update. This corresponds to the update_mask 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 ModelMonitor Vertex AI Model Monitoring Service serves as a central hub for the analysis and visualization of data quality and performance related to models. ModelMonitor stands as a top level resource for overseeing your model monitoring tasks.

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.