As of January 1, 2020 this library no longer supports Python 2 on the latest released version. Library versions released prior to that date will continue to be available. For more information please visit Python 2 support on Google Cloud.

FeatureRegistryService

class google.cloud.aiplatform_v1beta1.services.feature_registry_service.FeatureRegistryServiceAsyncClient(*, credentials: ~typing.Optional[~google.auth.credentials.Credentials] = None, transport: ~typing.Optional[~typing.Union[str, ~google.cloud.aiplatform_v1beta1.services.feature_registry_service.transports.base.FeatureRegistryServiceTransport, ~typing.Callable[[...], ~google.cloud.aiplatform_v1beta1.services.feature_registry_service.transports.base.FeatureRegistryServiceTransport]]] = 'grpc_asyncio', client_options: ~typing.Optional[~google.api_core.client_options.ClientOptions] = None, client_info: ~google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)

The service that handles CRUD and List for resources for FeatureRegistry.

Instantiates the feature registry service async client.

Parameters:

• 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,FeatureRegistryServiceTransport,Callable[..., FeatureRegistryServiceTransport]]]) – The transport to use, or a Callable that constructs and returns a new transport to use. If a Callable is given, it will be called with the same set of initialization arguments as used in the FeatureRegistryServiceTransport 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 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 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.

Raises:

google.auth.exceptions.MutualTlsChannelError – If mutual TLS transport creation failed for any reason.

property api_endpoint

Return the API endpoint used by the client instance.

Returns:

The API endpoint used by the client instance.

Return type:

str

async batch_create_features(request: Optional[Union[BatchCreateFeaturesRequest, dict]] = None, *, parent: Optional[str] = None, requests: Optional[MutableSequence[CreateFeatureRequest]] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → AsyncOperation

Creates a batch of Features in a given FeatureGroup.

# 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

async def sample_batch_create_features():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceAsyncClient()

    # Initialize request argument(s)
    requests = aiplatform_v1beta1.CreateFeatureRequest()
    requests.parent = "parent_value"
    requests.feature_id = "feature_id_value"

    request = aiplatform_v1beta1.BatchCreateFeaturesRequest(
        parent="parent_value",
        requests=requests,
    )

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

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

    response = (await operation).result()

    # Handle the response
    print(response)

Parameters:

• request (Optional[Union[google.cloud.aiplatform_v1beta1.types.BatchCreateFeaturesRequest, dict]]) – The request object. Request message for [FeaturestoreService.BatchCreateFeatures][google.cloud.aiplatform.v1beta1.FeaturestoreService.BatchCreateFeatures]. Request message for [FeatureRegistryService.BatchCreateFeatures][google.cloud.aiplatform.v1beta1.FeatureRegistryService.BatchCreateFeatures].

• parent (str) –

  Required. The resource name of the EntityType/FeatureGroup to create the batch of Features under. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type} projects/{project}/locations/{location}/featureGroups/{feature_group}

  This corresponds to the parent field on the request instance; if request is provided, this should not be set.

• requests (MutableSequence[google.cloud.aiplatform_v1beta1.types.CreateFeatureRequest]) –

  Required. The request message specifying the Features to create. All Features must be created under the same parent EntityType / FeatureGroup. The parent field in each child request message can be omitted. If parent is set in a child request, then the value must match the parent value in this request message.

  This corresponds to the requests field on the request instance; if request is provided, this should not be set.

• retry (google.api_core.retry_async.AsyncRetry) – 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:

An object representing a long-running operation.

The result type for the operation will be google.cloud.aiplatform_v1beta1.types.BatchCreateFeaturesResponse Response message for

[FeaturestoreService.BatchCreateFeatures][google.cloud.aiplatform.v1beta1.FeaturestoreService.BatchCreateFeatures].

Return type:

google.api_core.operation_async.AsyncOperation

async cancel_operation(request: Optional[CancelOperationRequest] = None, *, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[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:

• request (CancelOperationRequest) – The request object. Request message for CancelOperation method.

• retry (google.api_core.retry_async.AsyncRetry) – 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:

None

static common_billing_account_path(billing_account: str) → str

Returns a fully-qualified billing_account string.

static common_folder_path(folder: str) → str

Returns a fully-qualified folder string.

static common_location_path(project: str, location: str) → str

Returns a fully-qualified location string.

static common_organization_path(organization: str) → str

Returns a fully-qualified organization string.

static common_project_path(project: str) → str

Returns a fully-qualified project string.

async create_feature(request: Optional[Union[CreateFeatureRequest, dict]] = None, *, parent: Optional[str] = None, feature: Optional[Feature] = None, feature_id: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → AsyncOperation

Creates a new Feature in a given FeatureGroup.

# 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

async def sample_create_feature():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceAsyncClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.CreateFeatureRequest(
        parent="parent_value",
        feature_id="feature_id_value",
    )

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

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

    response = (await operation).result()

    # Handle the response
    print(response)

Parameters:

• request (Optional[Union[google.cloud.aiplatform_v1beta1.types.CreateFeatureRequest, dict]]) – The request object. Request message for [FeaturestoreService.CreateFeature][google.cloud.aiplatform.v1beta1.FeaturestoreService.CreateFeature]. Request message for [FeatureRegistryService.CreateFeature][google.cloud.aiplatform.v1beta1.FeatureRegistryService.CreateFeature].

• parent (str) –

  Required. The resource name of the EntityType or FeatureGroup to create a Feature. Format for entity_type as parent: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type} Format for feature_group as parent: projects/{project}/locations/{location}/featureGroups/{feature_group}

  This corresponds to the parent field on the request instance; if request is provided, this should not be set.

• feature (google.cloud.aiplatform_v1beta1.types.Feature) – Required. The Feature to create. This corresponds to the feature field on the request instance; if request is provided, this should not be set.

• feature_id (str) –

  Required. The ID to use for the Feature, which will become the final component of the Feature’s resource name.

  This value may be up to 128 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.

  The value must be unique within an EntityType/FeatureGroup.

  This corresponds to the feature_id field on the request instance; if request is provided, this should not be set.

• retry (google.api_core.retry_async.AsyncRetry) – 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:

An object representing a long-running operation.

The result type for the operation will be google.cloud.aiplatform_v1beta1.types.Feature Feature Metadata information.

For example, color is a feature that describes an apple.

Return type:

google.api_core.operation_async.AsyncOperation

async create_feature_group(request: Optional[Union[CreateFeatureGroupRequest, dict]] = None, *, parent: Optional[str] = None, feature_group: Optional[FeatureGroup] = None, feature_group_id: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → AsyncOperation

Creates a new FeatureGroup in a given project and 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

async def sample_create_feature_group():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceAsyncClient()

    # Initialize request argument(s)
    feature_group = aiplatform_v1beta1.FeatureGroup()
    feature_group.big_query.big_query_source.input_uri = "input_uri_value"

    request = aiplatform_v1beta1.CreateFeatureGroupRequest(
        parent="parent_value",
        feature_group=feature_group,
        feature_group_id="feature_group_id_value",
    )

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

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

    response = (await operation).result()

    # Handle the response
    print(response)

Parameters:

• request (Optional[Union[google.cloud.aiplatform_v1beta1.types.CreateFeatureGroupRequest, dict]]) – The request object. Request message for [FeatureRegistryService.CreateFeatureGroup][google.cloud.aiplatform.v1beta1.FeatureRegistryService.CreateFeatureGroup].

• parent (str) –

  Required. The resource name of the Location to create FeatureGroups. Format: projects/{project}/locations/{location}

  This corresponds to the parent field on the request instance; if request is provided, this should not be set.

• feature_group (google.cloud.aiplatform_v1beta1.types.FeatureGroup) – Required. The FeatureGroup to create. This corresponds to the feature_group field on the request instance; if request is provided, this should not be set.

• feature_group_id (str) –

  Required. The ID to use for this FeatureGroup, which will become the final component of the FeatureGroup’s resource name.

  This value may be up to 128 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.

  The value must be unique within the project and location.

  This corresponds to the feature_group_id field on the request instance; if request is provided, this should not be set.

• retry (google.api_core.retry_async.AsyncRetry) – 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:

An object representing a long-running operation.

The result type for the operation will be google.cloud.aiplatform_v1beta1.types.FeatureGroup Vertex AI Feature Group.

Return type:

google.api_core.operation_async.AsyncOperation

async create_feature_monitor(request: Optional[Union[CreateFeatureMonitorRequest, dict]] = None, *, parent: Optional[str] = None, feature_monitor: Optional[FeatureMonitor] = None, feature_monitor_id: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → AsyncOperation

Creates a new FeatureMonitor in a given project, location and FeatureGroup.

# 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

async def sample_create_feature_monitor():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceAsyncClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.CreateFeatureMonitorRequest(
        parent="parent_value",
        feature_monitor_id="feature_monitor_id_value",
    )

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

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

    response = (await operation).result()

    # Handle the response
    print(response)

Parameters:

• request (Optional[Union[google.cloud.aiplatform_v1beta1.types.CreateFeatureMonitorRequest, dict]]) – The request object. Request message for [FeatureRegistryService.CreateFeatureMonitorRequest][].

• parent (str) –

  Required. The resource name of FeatureGroup to create FeatureMonitor. Format: projects/{project}/locations/{location}/featureGroups/{featuregroup}

  This corresponds to the parent field on the request instance; if request is provided, this should not be set.

• feature_monitor (google.cloud.aiplatform_v1beta1.types.FeatureMonitor) – Required. The Monitor to create. This corresponds to the feature_monitor field on the request instance; if request is provided, this should not be set.

• feature_monitor_id (str) –

  Required. The ID to use for this FeatureMonitor, which will become the final component of the FeatureGroup’s resource name.

  This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.

  The value must be unique within the FeatureGroup.

  This corresponds to the feature_monitor_id field on the request instance; if request is provided, this should not be set.

• retry (google.api_core.retry_async.AsyncRetry) – 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:

An object representing a long-running operation.

The result type for the operation will be google.cloud.aiplatform_v1beta1.types.FeatureMonitor Vertex AI Feature Monitor.

Return type:

google.api_core.operation_async.AsyncOperation

async create_feature_monitor_job(request: Optional[Union[CreateFeatureMonitorJobRequest, dict]] = None, *, parent: Optional[str] = None, feature_monitor_job: Optional[FeatureMonitorJob] = None, feature_monitor_job_id: Optional[int] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → FeatureMonitorJob

Creates a new feature monitor job.

# 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

async def sample_create_feature_monitor_job():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceAsyncClient()

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

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

    # Handle the response
    print(response)

Parameters:

• request (Optional[Union[google.cloud.aiplatform_v1beta1.types.CreateFeatureMonitorJobRequest, dict]]) – The request object. Request message for [FeatureRegistryService.CreateFeatureMonitorJobRequest][].

• parent (str) –

  Required. The resource name of FeatureMonitor to create FeatureMonitorJob. Format: projects/{project}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{feature_monitor}

  This corresponds to the parent field on the request instance; if request is provided, this should not be set.

• feature_monitor_job (google.cloud.aiplatform_v1beta1.types.FeatureMonitorJob) – Required. The Monitor to create. This corresponds to the feature_monitor_job field on the request instance; if request is provided, this should not be set.

• feature_monitor_job_id (int) –

  Optional. Output only. System-generated ID for feature monitor job.

  This corresponds to the feature_monitor_job_id field on the request instance; if request is provided, this should not be set.

• retry (google.api_core.retry_async.AsyncRetry) – 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:

Vertex AI Feature Monitor Job.

Return type:

google.cloud.aiplatform_v1beta1.types.FeatureMonitorJob

async delete_feature(request: Optional[Union[DeleteFeatureRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → AsyncOperation

Deletes a single Feature.

# 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

async def sample_delete_feature():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceAsyncClient()

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

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

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

    response = (await operation).result()

    # Handle the response
    print(response)

Parameters:

• request (Optional[Union[google.cloud.aiplatform_v1beta1.types.DeleteFeatureRequest, dict]]) – The request object. Request message for [FeaturestoreService.DeleteFeature][google.cloud.aiplatform.v1beta1.FeaturestoreService.DeleteFeature]. Request message for [FeatureRegistryService.DeleteFeature][google.cloud.aiplatform.v1beta1.FeatureRegistryService.DeleteFeature].

• name (str) –

  Required. The name of the Features to be deleted. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature} projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}

  This corresponds to the name field on the request instance; if request is provided, this should not be set.

• retry (google.api_core.retry_async.AsyncRetry) – 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:

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);

}

Return type:

google.api_core.operation_async.AsyncOperation

async delete_feature_group(request: Optional[Union[DeleteFeatureGroupRequest, dict]] = None, *, name: Optional[str] = None, force: Optional[bool] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → AsyncOperation

Deletes a single FeatureGroup.

# 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

async def sample_delete_feature_group():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceAsyncClient()

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

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

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

    response = (await operation).result()

    # Handle the response
    print(response)

Parameters:

• request (Optional[Union[google.cloud.aiplatform_v1beta1.types.DeleteFeatureGroupRequest, dict]]) – The request object. Request message for [FeatureRegistryService.DeleteFeatureGroup][google.cloud.aiplatform.v1beta1.FeatureRegistryService.DeleteFeatureGroup].

• name (str) –

  Required. The name of the FeatureGroup to be deleted. Format: projects/{project}/locations/{location}/featureGroups/{feature_group}

  This corresponds to the name field on the request instance; if request is provided, this should not be set.

• force (bool) –

  If set to true, any Features under this FeatureGroup will also be deleted. (Otherwise, the request will only work if the FeatureGroup has no Features.)

  This corresponds to the force field on the request instance; if request is provided, this should not be set.

• retry (google.api_core.retry_async.AsyncRetry) – 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:

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);

}

Return type:

google.api_core.operation_async.AsyncOperation

async delete_feature_monitor(request: Optional[Union[DeleteFeatureMonitorRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → AsyncOperation

Deletes a single FeatureMonitor.

# 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

async def sample_delete_feature_monitor():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceAsyncClient()

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

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

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

    response = (await operation).result()

    # Handle the response
    print(response)

Parameters:

• request (Optional[Union[google.cloud.aiplatform_v1beta1.types.DeleteFeatureMonitorRequest, dict]]) – The request object. Request message for [FeatureRegistryService.DeleteFeatureMonitor][google.cloud.aiplatform.v1beta1.FeatureRegistryService.DeleteFeatureMonitor].

• name (str) –

  Required. The name of the FeatureMonitor to be deleted. Format: projects/{project}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{feature_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_async.AsyncRetry) – 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:

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);

}

Return type:

google.api_core.operation_async.AsyncOperation

async delete_operation(request: Optional[DeleteOperationRequest] = None, *, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[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:

• request (DeleteOperationRequest) – The request object. Request message for DeleteOperation method.

• retry (google.api_core.retry_async.AsyncRetry) – 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:

None

static feature_group_path(project: str, location: str, feature_group: str) → str

Returns a fully-qualified feature_group string.

static feature_monitor_job_path(project: str, location: str, feature_group: str, feature_monitor: str, feature_monitor_job: str) → str

Returns a fully-qualified feature_monitor_job string.

static feature_monitor_path(project: str, location: str, feature_group: str, feature_monitor: str) → str

Returns a fully-qualified feature_monitor string.

static feature_path(project: str, location: str, featurestore: str, entity_type: str, feature: str) → str

Returns a fully-qualified feature string.

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

Creates an instance of this client using the provided credentials

file.

Parameters:

• filename (str) – The path to the service account private key json file.

• args – Additional arguments to pass to the constructor.

• kwargs – Additional arguments to pass to the constructor.

Returns:

The constructed client.

Return type:

FeatureRegistryServiceAsyncClient

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

Creates an instance of this client using the provided credentials

info.

Parameters:

• info (dict) – The service account private key info.

• args – Additional arguments to pass to the constructor.

• kwargs – Additional arguments to pass to the constructor.

Returns:

The constructed client.

Return type:

FeatureRegistryServiceAsyncClient

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

Creates an instance of this client using the provided credentials

file.

Parameters:

• filename (str) – The path to the service account private key json file.

• args – Additional arguments to pass to the constructor.

• kwargs – Additional arguments to pass to the constructor.

Returns:

The constructed client.

Return type:

FeatureRegistryServiceAsyncClient

async get_feature(request: Optional[Union[GetFeatureRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Feature

Gets details of a single Feature.

# 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

async def sample_get_feature():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceAsyncClient()

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

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

    # Handle the response
    print(response)

Parameters:

• request (Optional[Union[google.cloud.aiplatform_v1beta1.types.GetFeatureRequest, dict]]) – The request object. Request message for [FeaturestoreService.GetFeature][google.cloud.aiplatform.v1beta1.FeaturestoreService.GetFeature]. Request message for [FeatureRegistryService.GetFeature][google.cloud.aiplatform.v1beta1.FeatureRegistryService.GetFeature].

• name (str) –

  Required. The name of the Feature resource. Format for entity_type as parent: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type} Format for feature_group as parent: projects/{project}/locations/{location}/featureGroups/{feature_group}

  This corresponds to the name field on the request instance; if request is provided, this should not be set.

• retry (google.api_core.retry_async.AsyncRetry) – 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:

Feature Metadata information. For example, color is a feature that describes an apple.

Return type:

google.cloud.aiplatform_v1beta1.types.Feature

async get_feature_group(request: Optional[Union[GetFeatureGroupRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → FeatureGroup

Gets details of a single FeatureGroup.

# 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

async def sample_get_feature_group():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceAsyncClient()

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

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

    # Handle the response
    print(response)

Parameters:

• request (Optional[Union[google.cloud.aiplatform_v1beta1.types.GetFeatureGroupRequest, dict]]) – The request object. Request message for [FeatureRegistryService.GetFeatureGroup][google.cloud.aiplatform.v1beta1.FeatureRegistryService.GetFeatureGroup].

• name (str) –

  Required. The name of the FeatureGroup resource.

  This corresponds to the name field on the request instance; if request is provided, this should not be set.

• retry (google.api_core.retry_async.AsyncRetry) – 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:

Vertex AI Feature Group.

Return type:

google.cloud.aiplatform_v1beta1.types.FeatureGroup

async get_feature_monitor(request: Optional[Union[GetFeatureMonitorRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → FeatureMonitor

Gets details of a single FeatureMonitor.

# 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

async def sample_get_feature_monitor():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceAsyncClient()

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

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

    # Handle the response
    print(response)

Parameters:

• request (Optional[Union[google.cloud.aiplatform_v1beta1.types.GetFeatureMonitorRequest, dict]]) – The request object. Request message for [FeatureRegistryService.GetFeatureMonitor][google.cloud.aiplatform.v1beta1.FeatureRegistryService.GetFeatureMonitor].

• name (str) –

  Required. The name of the FeatureMonitor resource.

  This corresponds to the name field on the request instance; if request is provided, this should not be set.

• retry (google.api_core.retry_async.AsyncRetry) – 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:

Vertex AI Feature Monitor.

Return type:

google.cloud.aiplatform_v1beta1.types.FeatureMonitor

async get_feature_monitor_job(request: Optional[Union[GetFeatureMonitorJobRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → FeatureMonitorJob

Get a feature monitor job.

# 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

async def sample_get_feature_monitor_job():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceAsyncClient()

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

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

    # Handle the response
    print(response)

Parameters:

• request (Optional[Union[google.cloud.aiplatform_v1beta1.types.GetFeatureMonitorJobRequest, dict]]) – The request object. Request message for [FeatureRegistryService.GetFeatureMonitorJob][google.cloud.aiplatform.v1beta1.FeatureRegistryService.GetFeatureMonitorJob].

• name (str) –

  Required. The name of the FeatureMonitorJob resource. Format: projects/{project}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{feature_monitor}/featureMonitorJobs/{feature_monitor_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_async.AsyncRetry) – 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:

Vertex AI Feature Monitor Job.

Return type:

google.cloud.aiplatform_v1beta1.types.FeatureMonitorJob

async get_iam_policy(request: Optional[GetIamPolicyRequest] = None, *, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → 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:

• request (GetIamPolicyRequest) – The request object. Request message for GetIamPolicy method.

• retry (google.api_core.retry_async.AsyncRetry) – 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:

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.

Return type:

Policy

async get_location(request: Optional[GetLocationRequest] = None, *, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Location

Gets information about a location.

Parameters:

• request (GetLocationRequest) – The request object. Request message for GetLocation method.

• retry (google.api_core.retry_async.AsyncRetry) – 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:

Location object.

Return type:

Location

classmethod get_mtls_endpoint_and_cert_source(client_options: Optional[ClientOptions] = None)

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.

Parameters:

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.

Returns:

returns the API endpoint and the

client cert source to use.

Return type:

Tuple[str, Callable[[], Tuple[bytes, bytes]]]

Raises:

google.auth.exceptions.MutualTLSChannelError – If any errors happen.

async get_operation(request: Optional[GetOperationRequest] = None, *, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Operation

Gets the latest state of a long-running operation.

Parameters:

• request (GetOperationRequest) – The request object. Request message for GetOperation method.

• retry (google.api_core.retry_async.AsyncRetry) – 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:

An Operation object.

Return type:

Operation

classmethod get_transport_class(label: Optional[str] = None) → Type[FeatureRegistryServiceTransport]

Returns an appropriate transport class.

Parameters:

label – The name of the desired transport. If none is provided, then the first transport in the registry is used.

Returns:

The transport class to use.

async list_feature_groups(request: Optional[Union[ListFeatureGroupsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → ListFeatureGroupsAsyncPager

Lists FeatureGroups in a given project and 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

async def sample_list_feature_groups():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceAsyncClient()

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

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

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

Parameters:

• request (Optional[Union[google.cloud.aiplatform_v1beta1.types.ListFeatureGroupsRequest, dict]]) – The request object. Request message for [FeatureRegistryService.ListFeatureGroups][google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatureGroups].

• parent (str) –

  Required. The resource name of the Location to list FeatureGroups. 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_async.AsyncRetry) – 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:

Response message for

[FeatureRegistryService.ListFeatureGroups][google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatureGroups].

Iterating over this object will yield results and resolve additional pages automatically.

Return type:

google.cloud.aiplatform_v1beta1.services.feature_registry_service.pagers.ListFeatureGroupsAsyncPager

async list_feature_monitor_jobs(request: Optional[Union[ListFeatureMonitorJobsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → ListFeatureMonitorJobsAsyncPager

List feature monitor jobs.

# 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

async def sample_list_feature_monitor_jobs():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceAsyncClient()

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

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

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

Parameters:

• request (Optional[Union[google.cloud.aiplatform_v1beta1.types.ListFeatureMonitorJobsRequest, dict]]) – The request object. Request message for [FeatureRegistryService.ListFeatureMonitorJobs][google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatureMonitorJobs].

• parent (str) –

  Required. The resource name of the FeatureMonitor to list FeatureMonitorJobs. Format: projects/{project}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{feature_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_async.AsyncRetry) – 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:

Response message for

[FeatureRegistryService.ListFeatureMonitorJobs][google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatureMonitorJobs].

Iterating over this object will yield results and resolve additional pages automatically.

Return type:

google.cloud.aiplatform_v1beta1.services.feature_registry_service.pagers.ListFeatureMonitorJobsAsyncPager

async list_feature_monitors(request: Optional[Union[ListFeatureMonitorsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → ListFeatureMonitorsAsyncPager

Lists FeatureGroups in a given project and 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

async def sample_list_feature_monitors():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceAsyncClient()

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

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

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

Parameters:

• request (Optional[Union[google.cloud.aiplatform_v1beta1.types.ListFeatureMonitorsRequest, dict]]) – The request object. Request message for [FeatureRegistryService.ListFeatureMonitors][google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatureMonitors].

• parent (str) –

  Required. The resource name of the FeatureGroup to list FeatureMonitors. Format: projects/{project}/locations/{location}/featureGroups/{featureGroup}

  This corresponds to the parent field on the request instance; if request is provided, this should not be set.

• retry (google.api_core.retry_async.AsyncRetry) – 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:

Response message for

[FeatureRegistryService.ListFeatureMonitors][google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatureMonitors].

Iterating over this object will yield results and resolve additional pages automatically.

Return type:

google.cloud.aiplatform_v1beta1.services.feature_registry_service.pagers.ListFeatureMonitorsAsyncPager

async list_features(request: Optional[Union[ListFeaturesRequest, dict]] = None, *, parent: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → ListFeaturesAsyncPager

Lists Features in a given FeatureGroup.

# 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

async def sample_list_features():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceAsyncClient()

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

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

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

Parameters:

• request (Optional[Union[google.cloud.aiplatform_v1beta1.types.ListFeaturesRequest, dict]]) – The request object. Request message for [FeaturestoreService.ListFeatures][google.cloud.aiplatform.v1beta1.FeaturestoreService.ListFeatures]. Request message for [FeatureRegistryService.ListFeatures][google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatures].

• parent (str) –

  Required. The resource name of the Location to list Features. Format for entity_type as parent: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type} Format for feature_group as parent: projects/{project}/locations/{location}/featureGroups/{feature_group}

  This corresponds to the parent field on the request instance; if request is provided, this should not be set.

• retry (google.api_core.retry_async.AsyncRetry) – 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:

Response message for

[FeaturestoreService.ListFeatures][google.cloud.aiplatform.v1beta1.FeaturestoreService.ListFeatures]. Response message for [FeatureRegistryService.ListFeatures][google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatures].

Iterating over this object will yield results and resolve additional pages automatically.

Return type:

google.cloud.aiplatform_v1beta1.services.feature_registry_service.pagers.ListFeaturesAsyncPager

async list_locations(request: Optional[ListLocationsRequest] = None, *, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → ListLocationsResponse

Lists information about the supported locations for this service.

Parameters:

• request (ListLocationsRequest) – The request object. Request message for ListLocations method.

• retry (google.api_core.retry_async.AsyncRetry) – 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:

Response message for ListLocations method.

Return type:

ListLocationsResponse

async list_operations(request: Optional[ListOperationsRequest] = None, *, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → ListOperationsResponse

Lists operations that match the specified filter in the request.

Parameters:

• request (ListOperationsRequest) – The request object. Request message for ListOperations method.

• retry (google.api_core.retry_async.AsyncRetry) – 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:

Response message for ListOperations method.

Return type:

ListOperationsResponse

static parse_common_billing_account_path(path: str) → Dict[str, str]

Parse a billing_account path into its component segments.

static parse_common_folder_path(path: str) → Dict[str, str]

Parse a folder path into its component segments.

static parse_common_location_path(path: str) → Dict[str, str]

Parse a location path into its component segments.

static parse_common_organization_path(path: str) → Dict[str, str]

Parse a organization path into its component segments.

static parse_common_project_path(path: str) → Dict[str, str]

Parse a project path into its component segments.

static parse_feature_group_path(path: str) → Dict[str, str]

Parses a feature_group path into its component segments.

static parse_feature_monitor_job_path(path: str) → Dict[str, str]

Parses a feature_monitor_job path into its component segments.

static parse_feature_monitor_path(path: str) → Dict[str, str]

Parses a feature_monitor path into its component segments.

static parse_feature_path(path: str) → Dict[str, str]

Parses a feature path into its component segments.

async set_iam_policy(request: Optional[SetIamPolicyRequest] = None, *, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Policy

Sets the IAM access control policy on the specified function.

Replaces any existing policy.

Parameters:

• request (SetIamPolicyRequest) – The request object. Request message for SetIamPolicy method.

• retry (google.api_core.retry_async.AsyncRetry) – 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:

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.

Return type:

Policy

async test_iam_permissions(request: Optional[TestIamPermissionsRequest] = None, *, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → 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:

• request (TestIamPermissionsRequest) – The request object. Request message for TestIamPermissions method.

• retry (google.api_core.retry_async.AsyncRetry) – 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:

Response message for TestIamPermissions method.

Return type:

TestIamPermissionsResponse

property transport: FeatureRegistryServiceTransport

Returns the transport used by the client instance.

Returns:

The transport used by the client instance.

Return type:

FeatureRegistryServiceTransport

property universe_domain: str

Return the universe domain used by the client instance.

Returns:

The universe domain used

by the client instance.

Return type:

str

async update_feature(request: Optional[Union[UpdateFeatureRequest, dict]] = None, *, feature: Optional[Feature] = None, update_mask: Optional[FieldMask] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → AsyncOperation

Updates the parameters of a single Feature.

# 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

async def sample_update_feature():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceAsyncClient()

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

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

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

    response = (await operation).result()

    # Handle the response
    print(response)

Parameters:

• request (Optional[Union[google.cloud.aiplatform_v1beta1.types.UpdateFeatureRequest, dict]]) – The request object. Request message for [FeaturestoreService.UpdateFeature][google.cloud.aiplatform.v1beta1.FeaturestoreService.UpdateFeature]. Request message for [FeatureRegistryService.UpdateFeature][google.cloud.aiplatform.v1beta1.FeatureRegistryService.UpdateFeature].

• feature (google.cloud.aiplatform_v1beta1.types.Feature) –

  Required. The Feature’s name field is used to identify the Feature to be updated. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature} projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}

  This corresponds to the feature field on the request instance; if request is provided, this should not be set.

• update_mask (google.protobuf.field_mask_pb2.FieldMask) –

  Field mask is used to specify the fields to be overwritten in the Features resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to * to override all fields.

  Updatable fields:

  • description

  • labels

  • disable_monitoring (Not supported for FeatureRegistryService Feature)

  • point_of_contact (Not supported for FeaturestoreService FeatureStore)

  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_async.AsyncRetry) – 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:

An object representing a long-running operation.

The result type for the operation will be google.cloud.aiplatform_v1beta1.types.Feature Feature Metadata information.

For example, color is a feature that describes an apple.

Return type:

google.api_core.operation_async.AsyncOperation

async update_feature_group(request: Optional[Union[UpdateFeatureGroupRequest, dict]] = None, *, feature_group: Optional[FeatureGroup] = None, update_mask: Optional[FieldMask] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → AsyncOperation

Updates the parameters of a single FeatureGroup.

# 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

async def sample_update_feature_group():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceAsyncClient()

    # Initialize request argument(s)
    feature_group = aiplatform_v1beta1.FeatureGroup()
    feature_group.big_query.big_query_source.input_uri = "input_uri_value"

    request = aiplatform_v1beta1.UpdateFeatureGroupRequest(
        feature_group=feature_group,
    )

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

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

    response = (await operation).result()

    # Handle the response
    print(response)

Parameters:

• request (Optional[Union[google.cloud.aiplatform_v1beta1.types.UpdateFeatureGroupRequest, dict]]) – The request object. Request message for [FeatureRegistryService.UpdateFeatureGroup][google.cloud.aiplatform.v1beta1.FeatureRegistryService.UpdateFeatureGroup].

• feature_group (google.cloud.aiplatform_v1beta1.types.FeatureGroup) –

  Required. The FeatureGroup’s name field is used to identify the FeatureGroup to be updated. Format: projects/{project}/locations/{location}/featureGroups/{feature_group}

  This corresponds to the feature_group field on the request instance; if request is provided, this should not be set.

• update_mask (google.protobuf.field_mask_pb2.FieldMask) –

  Field mask is used to specify the fields to be overwritten in the FeatureGroup resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to * to override all fields.

  Updatable fields:

  • labels

  • description

  • big_query

  • big_query.entity_id_columns

  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_async.AsyncRetry) – 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:

An object representing a long-running operation.

The result type for the operation will be google.cloud.aiplatform_v1beta1.types.FeatureGroup Vertex AI Feature Group.

Return type:

google.api_core.operation_async.AsyncOperation

async wait_operation(request: Optional[WaitOperationRequest] = None, *, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → 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:

• request (WaitOperationRequest) – The request object. Request message for WaitOperation method.

• retry (google.api_core.retry_async.AsyncRetry) – 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:

An Operation object.

Return type:

Operation

class google.cloud.aiplatform_v1beta1.services.feature_registry_service.FeatureRegistryServiceClient(*, credentials: ~typing.Optional[~google.auth.credentials.Credentials] = None, transport: ~typing.Optional[~typing.Union[str, ~google.cloud.aiplatform_v1beta1.services.feature_registry_service.transports.base.FeatureRegistryServiceTransport, ~typing.Callable[[...], ~google.cloud.aiplatform_v1beta1.services.feature_registry_service.transports.base.FeatureRegistryServiceTransport]]] = 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>)

The service that handles CRUD and List for resources for FeatureRegistry.

Instantiates the feature registry service client.

Parameters:

• 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,FeatureRegistryServiceTransport,Callable[..., FeatureRegistryServiceTransport]]]) – 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 FeatureRegistryServiceTransport 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 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.

Raises:

google.auth.exceptions.MutualTLSChannelError – If mutual TLS transport creation failed for any reason.

__exit__(type, value, traceback)

Releases underlying transport’s resources.

Warning

ONLY use as a context manager if the transport is NOT shared with other clients! Exiting the with block will CLOSE the transport and may cause errors in other clients!

property api_endpoint

Return the API endpoint used by the client instance.

Returns:

The API endpoint used by the client instance.

Return type:

str

batch_create_features(request: Optional[Union[BatchCreateFeaturesRequest, dict]] = None, *, parent: Optional[str] = None, requests: Optional[MutableSequence[CreateFeatureRequest]] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Operation

Creates a batch of Features in a given FeatureGroup.

# 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_batch_create_features():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceClient()

    # Initialize request argument(s)
    requests = aiplatform_v1beta1.CreateFeatureRequest()
    requests.parent = "parent_value"
    requests.feature_id = "feature_id_value"

    request = aiplatform_v1beta1.BatchCreateFeaturesRequest(
        parent="parent_value",
        requests=requests,
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)

Parameters:

• request (Union[google.cloud.aiplatform_v1beta1.types.BatchCreateFeaturesRequest, dict]) – The request object. Request message for [FeaturestoreService.BatchCreateFeatures][google.cloud.aiplatform.v1beta1.FeaturestoreService.BatchCreateFeatures]. Request message for [FeatureRegistryService.BatchCreateFeatures][google.cloud.aiplatform.v1beta1.FeatureRegistryService.BatchCreateFeatures].

• parent (str) –

  Required. The resource name of the EntityType/FeatureGroup to create the batch of Features under. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type} projects/{project}/locations/{location}/featureGroups/{feature_group}

  This corresponds to the parent field on the request instance; if request is provided, this should not be set.

• requests (MutableSequence[google.cloud.aiplatform_v1beta1.types.CreateFeatureRequest]) –

  Required. The request message specifying the Features to create. All Features must be created under the same parent EntityType / FeatureGroup. The parent field in each child request message can be omitted. If parent is set in a child request, then the value must match the parent value in this request message.

  This corresponds to the requests 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:

An object representing a long-running operation.

The result type for the operation will be google.cloud.aiplatform_v1beta1.types.BatchCreateFeaturesResponse Response message for

[FeaturestoreService.BatchCreateFeatures][google.cloud.aiplatform.v1beta1.FeaturestoreService.BatchCreateFeatures].

Return type:

google.api_core.operation.Operation

cancel_operation(request: Optional[CancelOperationRequest] = None, *, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[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:

• request (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.

Returns:

None

static common_billing_account_path(billing_account: str) → str

Returns a fully-qualified billing_account string.

static common_folder_path(folder: str) → str

Returns a fully-qualified folder string.

static common_location_path(project: str, location: str) → str

Returns a fully-qualified location string.

static common_organization_path(organization: str) → str

Returns a fully-qualified organization string.

static common_project_path(project: str) → str

Returns a fully-qualified project string.

create_feature(request: Optional[Union[CreateFeatureRequest, dict]] = None, *, parent: Optional[str] = None, feature: Optional[Feature] = None, feature_id: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Operation

Creates a new Feature in a given FeatureGroup.

# 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_feature():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.CreateFeatureRequest(
        parent="parent_value",
        feature_id="feature_id_value",
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)

Parameters:

• request (Union[google.cloud.aiplatform_v1beta1.types.CreateFeatureRequest, dict]) – The request object. Request message for [FeaturestoreService.CreateFeature][google.cloud.aiplatform.v1beta1.FeaturestoreService.CreateFeature]. Request message for [FeatureRegistryService.CreateFeature][google.cloud.aiplatform.v1beta1.FeatureRegistryService.CreateFeature].

• parent (str) –

  Required. The resource name of the EntityType or FeatureGroup to create a Feature. Format for entity_type as parent: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type} Format for feature_group as parent: projects/{project}/locations/{location}/featureGroups/{feature_group}

  This corresponds to the parent field on the request instance; if request is provided, this should not be set.

• feature (google.cloud.aiplatform_v1beta1.types.Feature) – Required. The Feature to create. This corresponds to the feature field on the request instance; if request is provided, this should not be set.

• feature_id (str) –

  Required. The ID to use for the Feature, which will become the final component of the Feature’s resource name.

  This value may be up to 128 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.

  The value must be unique within an EntityType/FeatureGroup.

  This corresponds to the feature_id field on the request instance; if request is provided, this should not be set.

• retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.

• timeout (float) – The timeout for this request.

• metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

An object representing a long-running operation.

The result type for the operation will be google.cloud.aiplatform_v1beta1.types.Feature Feature Metadata information.

For example, color is a feature that describes an apple.

Return type:

google.api_core.operation.Operation

create_feature_group(request: Optional[Union[CreateFeatureGroupRequest, dict]] = None, *, parent: Optional[str] = None, feature_group: Optional[FeatureGroup] = None, feature_group_id: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Operation

Creates a new FeatureGroup in a given project and 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_create_feature_group():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceClient()

    # Initialize request argument(s)
    feature_group = aiplatform_v1beta1.FeatureGroup()
    feature_group.big_query.big_query_source.input_uri = "input_uri_value"

    request = aiplatform_v1beta1.CreateFeatureGroupRequest(
        parent="parent_value",
        feature_group=feature_group,
        feature_group_id="feature_group_id_value",
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)

Parameters:

• request (Union[google.cloud.aiplatform_v1beta1.types.CreateFeatureGroupRequest, dict]) – The request object. Request message for [FeatureRegistryService.CreateFeatureGroup][google.cloud.aiplatform.v1beta1.FeatureRegistryService.CreateFeatureGroup].

• parent (str) –

  Required. The resource name of the Location to create FeatureGroups. Format: projects/{project}/locations/{location}

  This corresponds to the parent field on the request instance; if request is provided, this should not be set.

• feature_group (google.cloud.aiplatform_v1beta1.types.FeatureGroup) – Required. The FeatureGroup to create. This corresponds to the feature_group field on the request instance; if request is provided, this should not be set.

• feature_group_id (str) –

  Required. The ID to use for this FeatureGroup, which will become the final component of the FeatureGroup’s resource name.

  This value may be up to 128 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.

  The value must be unique within the project and location.

  This corresponds to the feature_group_id field on the request instance; if request is provided, this should not be set.

• retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.

• timeout (float) – The timeout for this request.

• metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

An object representing a long-running operation.

The result type for the operation will be google.cloud.aiplatform_v1beta1.types.FeatureGroup Vertex AI Feature Group.

Return type:

google.api_core.operation.Operation

create_feature_monitor(request: Optional[Union[CreateFeatureMonitorRequest, dict]] = None, *, parent: Optional[str] = None, feature_monitor: Optional[FeatureMonitor] = None, feature_monitor_id: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Operation

Creates a new FeatureMonitor in a given project, location and FeatureGroup.

# 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_feature_monitor():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.CreateFeatureMonitorRequest(
        parent="parent_value",
        feature_monitor_id="feature_monitor_id_value",
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)

Parameters:

• request (Union[google.cloud.aiplatform_v1beta1.types.CreateFeatureMonitorRequest, dict]) – The request object. Request message for [FeatureRegistryService.CreateFeatureMonitorRequest][].

• parent (str) –

  Required. The resource name of FeatureGroup to create FeatureMonitor. Format: projects/{project}/locations/{location}/featureGroups/{featuregroup}

  This corresponds to the parent field on the request instance; if request is provided, this should not be set.

• feature_monitor (google.cloud.aiplatform_v1beta1.types.FeatureMonitor) – Required. The Monitor to create. This corresponds to the feature_monitor field on the request instance; if request is provided, this should not be set.

• feature_monitor_id (str) –

  Required. The ID to use for this FeatureMonitor, which will become the final component of the FeatureGroup’s resource name.

  This value may be up to 60 characters, and valid characters are [a-z0-9_]. The first character cannot be a number.

  The value must be unique within the FeatureGroup.

  This corresponds to the feature_monitor_id field on the request instance; if request is provided, this should not be set.

• retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.

• timeout (float) – The timeout for this request.

• metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

An object representing a long-running operation.

The result type for the operation will be google.cloud.aiplatform_v1beta1.types.FeatureMonitor Vertex AI Feature Monitor.

Return type:

google.api_core.operation.Operation

create_feature_monitor_job(request: Optional[Union[CreateFeatureMonitorJobRequest, dict]] = None, *, parent: Optional[str] = None, feature_monitor_job: Optional[FeatureMonitorJob] = None, feature_monitor_job_id: Optional[int] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → FeatureMonitorJob

Creates a new feature monitor job.

# 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_feature_monitor_job():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceClient()

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

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

    # Handle the response
    print(response)

Parameters:

• request (Union[google.cloud.aiplatform_v1beta1.types.CreateFeatureMonitorJobRequest, dict]) – The request object. Request message for [FeatureRegistryService.CreateFeatureMonitorJobRequest][].

• parent (str) –

  Required. The resource name of FeatureMonitor to create FeatureMonitorJob. Format: projects/{project}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{feature_monitor}

  This corresponds to the parent field on the request instance; if request is provided, this should not be set.

• feature_monitor_job (google.cloud.aiplatform_v1beta1.types.FeatureMonitorJob) – Required. The Monitor to create. This corresponds to the feature_monitor_job field on the request instance; if request is provided, this should not be set.

• feature_monitor_job_id (int) –

  Optional. Output only. System-generated ID for feature monitor job.

  This corresponds to the feature_monitor_job_id field on the request instance; if request is provided, this should not be set.

• retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.

• timeout (float) – The timeout for this request.

• metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Vertex AI Feature Monitor Job.

Return type:

google.cloud.aiplatform_v1beta1.types.FeatureMonitorJob

delete_feature(request: Optional[Union[DeleteFeatureRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Operation

Deletes a single Feature.

# 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_feature():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceClient()

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

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

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

    response = operation.result()

    # Handle the response
    print(response)

Parameters:

• request (Union[google.cloud.aiplatform_v1beta1.types.DeleteFeatureRequest, dict]) – The request object. Request message for [FeaturestoreService.DeleteFeature][google.cloud.aiplatform.v1beta1.FeaturestoreService.DeleteFeature]. Request message for [FeatureRegistryService.DeleteFeature][google.cloud.aiplatform.v1beta1.FeatureRegistryService.DeleteFeature].

• name (str) –

  Required. The name of the Features to be deleted. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature} projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}

  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:

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);

}

Return type:

google.api_core.operation.Operation

delete_feature_group(request: Optional[Union[DeleteFeatureGroupRequest, dict]] = None, *, name: Optional[str] = None, force: Optional[bool] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Operation

Deletes a single FeatureGroup.

# 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_feature_group():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceClient()

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

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

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

    response = operation.result()

    # Handle the response
    print(response)

Parameters:

• request (Union[google.cloud.aiplatform_v1beta1.types.DeleteFeatureGroupRequest, dict]) – The request object. Request message for [FeatureRegistryService.DeleteFeatureGroup][google.cloud.aiplatform.v1beta1.FeatureRegistryService.DeleteFeatureGroup].

• name (str) –

  Required. The name of the FeatureGroup to be deleted. Format: projects/{project}/locations/{location}/featureGroups/{feature_group}

  This corresponds to the name field on the request instance; if request is provided, this should not be set.

• force (bool) –

  If set to true, any Features under this FeatureGroup will also be deleted. (Otherwise, the request will only work if the FeatureGroup has no Features.)

  This corresponds to the force 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:

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);

}

Return type:

google.api_core.operation.Operation

delete_feature_monitor(request: Optional[Union[DeleteFeatureMonitorRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Operation

Deletes a single FeatureMonitor.

# 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_feature_monitor():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceClient()

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

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

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

    response = operation.result()

    # Handle the response
    print(response)

Parameters:

• request (Union[google.cloud.aiplatform_v1beta1.types.DeleteFeatureMonitorRequest, dict]) – The request object. Request message for [FeatureRegistryService.DeleteFeatureMonitor][google.cloud.aiplatform.v1beta1.FeatureRegistryService.DeleteFeatureMonitor].

• name (str) –

  Required. The name of the FeatureMonitor to be deleted. Format: projects/{project}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{feature_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:

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);

}

Return type:

google.api_core.operation.Operation

delete_operation(request: Optional[DeleteOperationRequest] = None, *, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[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:

• request (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.

Returns:

None

static feature_group_path(project: str, location: str, feature_group: str) → str

Returns a fully-qualified feature_group string.

static feature_monitor_job_path(project: str, location: str, feature_group: str, feature_monitor: str, feature_monitor_job: str) → str

Returns a fully-qualified feature_monitor_job string.

static feature_monitor_path(project: str, location: str, feature_group: str, feature_monitor: str) → str

Returns a fully-qualified feature_monitor string.

static feature_path(project: str, location: str, featurestore: str, entity_type: str, feature: str) → str

Returns a fully-qualified feature string.

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

Creates an instance of this client using the provided credentials

file.

Parameters:

• filename (str) – The path to the service account private key json file.

• args – Additional arguments to pass to the constructor.

• kwargs – Additional arguments to pass to the constructor.

Returns:

The constructed client.

Return type:

FeatureRegistryServiceClient

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

Creates an instance of this client using the provided credentials

info.

Parameters:

• info (dict) – The service account private key info.

• args – Additional arguments to pass to the constructor.

• kwargs – Additional arguments to pass to the constructor.

Returns:

The constructed client.

Return type:

FeatureRegistryServiceClient

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

Creates an instance of this client using the provided credentials

file.

Parameters:

• filename (str) – The path to the service account private key json file.

• args – Additional arguments to pass to the constructor.

• kwargs – Additional arguments to pass to the constructor.

Returns:

The constructed client.

Return type:

FeatureRegistryServiceClient

get_feature(request: Optional[Union[GetFeatureRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Feature

Gets details of a single Feature.

# 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_feature():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceClient()

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

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

    # Handle the response
    print(response)

Parameters:

• request (Union[google.cloud.aiplatform_v1beta1.types.GetFeatureRequest, dict]) – The request object. Request message for [FeaturestoreService.GetFeature][google.cloud.aiplatform.v1beta1.FeaturestoreService.GetFeature]. Request message for [FeatureRegistryService.GetFeature][google.cloud.aiplatform.v1beta1.FeatureRegistryService.GetFeature].

• name (str) –

  Required. The name of the Feature resource. Format for entity_type as parent: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type} Format for feature_group as parent: projects/{project}/locations/{location}/featureGroups/{feature_group}

  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:

Feature Metadata information. For example, color is a feature that describes an apple.

Return type:

google.cloud.aiplatform_v1beta1.types.Feature

get_feature_group(request: Optional[Union[GetFeatureGroupRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → FeatureGroup

Gets details of a single FeatureGroup.

# 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_feature_group():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceClient()

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

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

    # Handle the response
    print(response)

Parameters:

• request (Union[google.cloud.aiplatform_v1beta1.types.GetFeatureGroupRequest, dict]) – The request object. Request message for [FeatureRegistryService.GetFeatureGroup][google.cloud.aiplatform.v1beta1.FeatureRegistryService.GetFeatureGroup].

• name (str) –

  Required. The name of the FeatureGroup resource.

  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:

Vertex AI Feature Group.

Return type:

google.cloud.aiplatform_v1beta1.types.FeatureGroup

get_feature_monitor(request: Optional[Union[GetFeatureMonitorRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → FeatureMonitor

Gets details of a single FeatureMonitor.

# 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_feature_monitor():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceClient()

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

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

    # Handle the response
    print(response)

Parameters:

• request (Union[google.cloud.aiplatform_v1beta1.types.GetFeatureMonitorRequest, dict]) – The request object. Request message for [FeatureRegistryService.GetFeatureMonitor][google.cloud.aiplatform.v1beta1.FeatureRegistryService.GetFeatureMonitor].

• name (str) –

  Required. The name of the FeatureMonitor resource.

  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:

Vertex AI Feature Monitor.

Return type:

google.cloud.aiplatform_v1beta1.types.FeatureMonitor

get_feature_monitor_job(request: Optional[Union[GetFeatureMonitorJobRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → FeatureMonitorJob

Get a feature monitor job.

# 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_feature_monitor_job():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceClient()

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

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

    # Handle the response
    print(response)

Parameters:

• request (Union[google.cloud.aiplatform_v1beta1.types.GetFeatureMonitorJobRequest, dict]) – The request object. Request message for [FeatureRegistryService.GetFeatureMonitorJob][google.cloud.aiplatform.v1beta1.FeatureRegistryService.GetFeatureMonitorJob].

• name (str) –

  Required. The name of the FeatureMonitorJob resource. Format: projects/{project}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{feature_monitor}/featureMonitorJobs/{feature_monitor_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:

Vertex AI Feature Monitor Job.

Return type:

google.cloud.aiplatform_v1beta1.types.FeatureMonitorJob

get_iam_policy(request: Optional[GetIamPolicyRequest] = None, *, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → 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:

• request (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:

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.

Return type:

Policy

get_location(request: Optional[GetLocationRequest] = None, *, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Location

Gets information about a location.

Parameters:

• request (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:

Location object.

Return type:

Location

classmethod get_mtls_endpoint_and_cert_source(client_options: Optional[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.

Parameters:

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.

Returns:

returns the API endpoint and the

client cert source to use.

Return type:

Tuple[str, Callable[[], Tuple[bytes, bytes]]]

Raises:

google.auth.exceptions.MutualTLSChannelError – If any errors happen.

get_operation(request: Optional[GetOperationRequest] = None, *, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Operation

Gets the latest state of a long-running operation.

Parameters:

• request (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:

An Operation object.

Return type:

Operation

list_feature_groups(request: Optional[Union[ListFeatureGroupsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → ListFeatureGroupsPager

Lists FeatureGroups in a given project and 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_feature_groups():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceClient()

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

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

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

Parameters:

• request (Union[google.cloud.aiplatform_v1beta1.types.ListFeatureGroupsRequest, dict]) – The request object. Request message for [FeatureRegistryService.ListFeatureGroups][google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatureGroups].

• parent (str) –

  Required. The resource name of the Location to list FeatureGroups. 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:

Response message for

[FeatureRegistryService.ListFeatureGroups][google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatureGroups].

Iterating over this object will yield results and resolve additional pages automatically.

Return type:

google.cloud.aiplatform_v1beta1.services.feature_registry_service.pagers.ListFeatureGroupsPager

list_feature_monitor_jobs(request: Optional[Union[ListFeatureMonitorJobsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → ListFeatureMonitorJobsPager

List feature monitor jobs.

# 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_feature_monitor_jobs():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceClient()

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

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

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

Parameters:

• request (Union[google.cloud.aiplatform_v1beta1.types.ListFeatureMonitorJobsRequest, dict]) – The request object. Request message for [FeatureRegistryService.ListFeatureMonitorJobs][google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatureMonitorJobs].

• parent (str) –

  Required. The resource name of the FeatureMonitor to list FeatureMonitorJobs. Format: projects/{project}/locations/{location}/featureGroups/{feature_group}/featureMonitors/{feature_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:

Response message for

[FeatureRegistryService.ListFeatureMonitorJobs][google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatureMonitorJobs].

Iterating over this object will yield results and resolve additional pages automatically.

Return type:

google.cloud.aiplatform_v1beta1.services.feature_registry_service.pagers.ListFeatureMonitorJobsPager

list_feature_monitors(request: Optional[Union[ListFeatureMonitorsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → ListFeatureMonitorsPager

Lists FeatureGroups in a given project and 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_feature_monitors():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceClient()

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

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

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

Parameters:

• request (Union[google.cloud.aiplatform_v1beta1.types.ListFeatureMonitorsRequest, dict]) – The request object. Request message for [FeatureRegistryService.ListFeatureMonitors][google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatureMonitors].

• parent (str) –

  Required. The resource name of the FeatureGroup to list FeatureMonitors. Format: projects/{project}/locations/{location}/featureGroups/{featureGroup}

  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:

Response message for

[FeatureRegistryService.ListFeatureMonitors][google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatureMonitors].

Iterating over this object will yield results and resolve additional pages automatically.

Return type:

google.cloud.aiplatform_v1beta1.services.feature_registry_service.pagers.ListFeatureMonitorsPager

list_features(request: Optional[Union[ListFeaturesRequest, dict]] = None, *, parent: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → ListFeaturesPager

Lists Features in a given FeatureGroup.

# 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_features():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceClient()

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

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

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

Parameters:

• request (Union[google.cloud.aiplatform_v1beta1.types.ListFeaturesRequest, dict]) – The request object. Request message for [FeaturestoreService.ListFeatures][google.cloud.aiplatform.v1beta1.FeaturestoreService.ListFeatures]. Request message for [FeatureRegistryService.ListFeatures][google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatures].

• parent (str) –

  Required. The resource name of the Location to list Features. Format for entity_type as parent: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type} Format for feature_group as parent: projects/{project}/locations/{location}/featureGroups/{feature_group}

  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:

Response message for

[FeaturestoreService.ListFeatures][google.cloud.aiplatform.v1beta1.FeaturestoreService.ListFeatures]. Response message for [FeatureRegistryService.ListFeatures][google.cloud.aiplatform.v1beta1.FeatureRegistryService.ListFeatures].

Iterating over this object will yield results and resolve additional pages automatically.

Return type:

google.cloud.aiplatform_v1beta1.services.feature_registry_service.pagers.ListFeaturesPager

list_locations(request: Optional[ListLocationsRequest] = None, *, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → ListLocationsResponse

Lists information about the supported locations for this service.

Parameters:

• request (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:

Response message for ListLocations method.

Return type:

ListLocationsResponse

list_operations(request: Optional[ListOperationsRequest] = None, *, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → ListOperationsResponse

Lists operations that match the specified filter in the request.

Parameters:

• request (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:

Response message for ListOperations method.

Return type:

ListOperationsResponse

static parse_common_billing_account_path(path: str) → Dict[str, str]

Parse a billing_account path into its component segments.

static parse_common_folder_path(path: str) → Dict[str, str]

Parse a folder path into its component segments.

static parse_common_location_path(path: str) → Dict[str, str]

Parse a location path into its component segments.

static parse_common_organization_path(path: str) → Dict[str, str]

Parse a organization path into its component segments.

static parse_common_project_path(path: str) → Dict[str, str]

Parse a project path into its component segments.

static parse_feature_group_path(path: str) → Dict[str, str]

Parses a feature_group path into its component segments.

static parse_feature_monitor_job_path(path: str) → Dict[str, str]

Parses a feature_monitor_job path into its component segments.

static parse_feature_monitor_path(path: str) → Dict[str, str]

Parses a feature_monitor path into its component segments.

static parse_feature_path(path: str) → Dict[str, str]

Parses a feature path into its component segments.

set_iam_policy(request: Optional[SetIamPolicyRequest] = None, *, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Policy

Sets the IAM access control policy on the specified function.

Replaces any existing policy.

Parameters:

• request (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:

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.

Return type:

Policy

test_iam_permissions(request: Optional[TestIamPermissionsRequest] = None, *, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → 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:

• request (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:

Response message for TestIamPermissions method.

Return type:

TestIamPermissionsResponse

property transport: FeatureRegistryServiceTransport

Returns the transport used by the client instance.

Returns:

The transport used by the client

instance.

Return type:

FeatureRegistryServiceTransport

property universe_domain: str

Return the universe domain used by the client instance.

Returns:

The universe domain used by the client instance.

Return type:

str

update_feature(request: Optional[Union[UpdateFeatureRequest, dict]] = None, *, feature: Optional[Feature] = None, update_mask: Optional[FieldMask] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Operation

Updates the parameters of a single Feature.

# 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_feature():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceClient()

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

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

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

    response = operation.result()

    # Handle the response
    print(response)

Parameters:

• request (Union[google.cloud.aiplatform_v1beta1.types.UpdateFeatureRequest, dict]) – The request object. Request message for [FeaturestoreService.UpdateFeature][google.cloud.aiplatform.v1beta1.FeaturestoreService.UpdateFeature]. Request message for [FeatureRegistryService.UpdateFeature][google.cloud.aiplatform.v1beta1.FeatureRegistryService.UpdateFeature].

• feature (google.cloud.aiplatform_v1beta1.types.Feature) –

  Required. The Feature’s name field is used to identify the Feature to be updated. Format: projects/{project}/locations/{location}/featurestores/{featurestore}/entityTypes/{entity_type}/features/{feature} projects/{project}/locations/{location}/featureGroups/{feature_group}/features/{feature}

  This corresponds to the feature field on the request instance; if request is provided, this should not be set.

• update_mask (google.protobuf.field_mask_pb2.FieldMask) –

  Field mask is used to specify the fields to be overwritten in the Features resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to * to override all fields.

  Updatable fields:

  • description

  • labels

  • disable_monitoring (Not supported for FeatureRegistryService Feature)

  • point_of_contact (Not supported for FeaturestoreService FeatureStore)

  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:

An object representing a long-running operation.

The result type for the operation will be google.cloud.aiplatform_v1beta1.types.Feature Feature Metadata information.

For example, color is a feature that describes an apple.

Return type:

google.api_core.operation.Operation

update_feature_group(request: Optional[Union[UpdateFeatureGroupRequest, dict]] = None, *, feature_group: Optional[FeatureGroup] = None, update_mask: Optional[FieldMask] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Operation

Updates the parameters of a single FeatureGroup.

# 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_feature_group():
    # Create a client
    client = aiplatform_v1beta1.FeatureRegistryServiceClient()

    # Initialize request argument(s)
    feature_group = aiplatform_v1beta1.FeatureGroup()
    feature_group.big_query.big_query_source.input_uri = "input_uri_value"

    request = aiplatform_v1beta1.UpdateFeatureGroupRequest(
        feature_group=feature_group,
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)

Parameters:

• request (Union[google.cloud.aiplatform_v1beta1.types.UpdateFeatureGroupRequest, dict]) – The request object. Request message for [FeatureRegistryService.UpdateFeatureGroup][google.cloud.aiplatform.v1beta1.FeatureRegistryService.UpdateFeatureGroup].

• feature_group (google.cloud.aiplatform_v1beta1.types.FeatureGroup) –

  Required. The FeatureGroup’s name field is used to identify the FeatureGroup to be updated. Format: projects/{project}/locations/{location}/featureGroups/{feature_group}

  This corresponds to the feature_group field on the request instance; if request is provided, this should not be set.

• update_mask (google.protobuf.field_mask_pb2.FieldMask) –

  Field mask is used to specify the fields to be overwritten in the FeatureGroup resource by the update. The fields specified in the update_mask are relative to the resource, not the full request. A field will be overwritten if it is in the mask. If the user does not provide a mask then only the non-empty fields present in the request will be overwritten. Set the update_mask to * to override all fields.

  Updatable fields:

  • labels

  • description

  • big_query

  • big_query.entity_id_columns

  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:

An object representing a long-running operation.

The result type for the operation will be google.cloud.aiplatform_v1beta1.types.FeatureGroup Vertex AI Feature Group.

Return type:

google.api_core.operation.Operation

wait_operation(request: Optional[WaitOperationRequest] = None, *, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → 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:

• request (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:

An Operation object.

Return type:

Operation

class google.cloud.aiplatform_v1beta1.services.feature_registry_service.pagers.ListFeatureGroupsAsyncPager(method: Callable[[...], Awaitable[ListFeatureGroupsResponse]], request: ListFeatureGroupsRequest, response: ListFeatureGroupsResponse, *, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())

A pager for iterating through list_feature_groups requests.

This class thinly wraps an initial google.cloud.aiplatform_v1beta1.types.ListFeatureGroupsResponse object, and provides an __aiter__ method to iterate through its feature_groups field.

If there are more pages, the __aiter__ method will make additional ListFeatureGroups requests and continue to iterate through the feature_groups field on the corresponding responses.

All the usual google.cloud.aiplatform_v1beta1.types.ListFeatureGroupsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiates the pager.

Parameters:

• method (Callable) – The method that was originally called, and which instantiated this pager.

• request (google.cloud.aiplatform_v1beta1.types.ListFeatureGroupsRequest) – The initial request object.

• response (google.cloud.aiplatform_v1beta1.types.ListFeatureGroupsResponse) – The initial response object.

• retry (google.api_core.retry.AsyncRetry) – 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.

class google.cloud.aiplatform_v1beta1.services.feature_registry_service.pagers.ListFeatureGroupsPager(method: Callable[[...], ListFeatureGroupsResponse], request: ListFeatureGroupsRequest, response: ListFeatureGroupsResponse, *, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())

A pager for iterating through list_feature_groups requests.

This class thinly wraps an initial google.cloud.aiplatform_v1beta1.types.ListFeatureGroupsResponse object, and provides an __iter__ method to iterate through its feature_groups field.

If there are more pages, the __iter__ method will make additional ListFeatureGroups requests and continue to iterate through the feature_groups field on the corresponding responses.

All the usual google.cloud.aiplatform_v1beta1.types.ListFeatureGroupsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiate the pager.

Parameters:

• method (Callable) – The method that was originally called, and which instantiated this pager.

• request (google.cloud.aiplatform_v1beta1.types.ListFeatureGroupsRequest) – The initial request object.

• response (google.cloud.aiplatform_v1beta1.types.ListFeatureGroupsResponse) – The initial response object.

• 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.

class google.cloud.aiplatform_v1beta1.services.feature_registry_service.pagers.ListFeatureMonitorJobsAsyncPager(method: Callable[[...], Awaitable[ListFeatureMonitorJobsResponse]], request: ListFeatureMonitorJobsRequest, response: ListFeatureMonitorJobsResponse, *, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())

A pager for iterating through list_feature_monitor_jobs requests.

This class thinly wraps an initial google.cloud.aiplatform_v1beta1.types.ListFeatureMonitorJobsResponse object, and provides an __aiter__ method to iterate through its feature_monitor_jobs field.

If there are more pages, the __aiter__ method will make additional ListFeatureMonitorJobs requests and continue to iterate through the feature_monitor_jobs field on the corresponding responses.

All the usual google.cloud.aiplatform_v1beta1.types.ListFeatureMonitorJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiates the pager.

Parameters:

• method (Callable) – The method that was originally called, and which instantiated this pager.

• request (google.cloud.aiplatform_v1beta1.types.ListFeatureMonitorJobsRequest) – The initial request object.

• response (google.cloud.aiplatform_v1beta1.types.ListFeatureMonitorJobsResponse) – The initial response object.

• retry (google.api_core.retry.AsyncRetry) – 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.

class google.cloud.aiplatform_v1beta1.services.feature_registry_service.pagers.ListFeatureMonitorJobsPager(method: Callable[[...], ListFeatureMonitorJobsResponse], request: ListFeatureMonitorJobsRequest, response: ListFeatureMonitorJobsResponse, *, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())

A pager for iterating through list_feature_monitor_jobs requests.

This class thinly wraps an initial google.cloud.aiplatform_v1beta1.types.ListFeatureMonitorJobsResponse object, and provides an __iter__ method to iterate through its feature_monitor_jobs field.

If there are more pages, the __iter__ method will make additional ListFeatureMonitorJobs requests and continue to iterate through the feature_monitor_jobs field on the corresponding responses.

All the usual google.cloud.aiplatform_v1beta1.types.ListFeatureMonitorJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiate the pager.

Parameters:

• method (Callable) – The method that was originally called, and which instantiated this pager.

• request (google.cloud.aiplatform_v1beta1.types.ListFeatureMonitorJobsRequest) – The initial request object.

• response (google.cloud.aiplatform_v1beta1.types.ListFeatureMonitorJobsResponse) – The initial response object.

• 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.

class google.cloud.aiplatform_v1beta1.services.feature_registry_service.pagers.ListFeatureMonitorsAsyncPager(method: Callable[[...], Awaitable[ListFeatureMonitorsResponse]], request: ListFeatureMonitorsRequest, response: ListFeatureMonitorsResponse, *, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())

A pager for iterating through list_feature_monitors requests.

This class thinly wraps an initial google.cloud.aiplatform_v1beta1.types.ListFeatureMonitorsResponse object, and provides an __aiter__ method to iterate through its feature_monitors field.

If there are more pages, the __aiter__ method will make additional ListFeatureMonitors requests and continue to iterate through the feature_monitors field on the corresponding responses.

All the usual google.cloud.aiplatform_v1beta1.types.ListFeatureMonitorsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiates the pager.

Parameters:

• method (Callable) – The method that was originally called, and which instantiated this pager.

• request (google.cloud.aiplatform_v1beta1.types.ListFeatureMonitorsRequest) – The initial request object.

• response (google.cloud.aiplatform_v1beta1.types.ListFeatureMonitorsResponse) – The initial response object.

• retry (google.api_core.retry.AsyncRetry) – 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.

class google.cloud.aiplatform_v1beta1.services.feature_registry_service.pagers.ListFeatureMonitorsPager(method: Callable[[...], ListFeatureMonitorsResponse], request: ListFeatureMonitorsRequest, response: ListFeatureMonitorsResponse, *, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())

A pager for iterating through list_feature_monitors requests.

This class thinly wraps an initial google.cloud.aiplatform_v1beta1.types.ListFeatureMonitorsResponse object, and provides an __iter__ method to iterate through its feature_monitors field.

If there are more pages, the __iter__ method will make additional ListFeatureMonitors requests and continue to iterate through the feature_monitors field on the corresponding responses.

All the usual google.cloud.aiplatform_v1beta1.types.ListFeatureMonitorsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiate the pager.

Parameters:

• method (Callable) – The method that was originally called, and which instantiated this pager.

• request (google.cloud.aiplatform_v1beta1.types.ListFeatureMonitorsRequest) – The initial request object.

• response (google.cloud.aiplatform_v1beta1.types.ListFeatureMonitorsResponse) – The initial response object.

• 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.

class google.cloud.aiplatform_v1beta1.services.feature_registry_service.pagers.ListFeaturesAsyncPager(method: Callable[[...], Awaitable[ListFeaturesResponse]], request: ListFeaturesRequest, response: ListFeaturesResponse, *, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())

A pager for iterating through list_features requests.

This class thinly wraps an initial google.cloud.aiplatform_v1beta1.types.ListFeaturesResponse object, and provides an __aiter__ method to iterate through its features field.

If there are more pages, the __aiter__ method will make additional ListFeatures requests and continue to iterate through the features field on the corresponding responses.

All the usual google.cloud.aiplatform_v1beta1.types.ListFeaturesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiates the pager.

Parameters:

• method (Callable) – The method that was originally called, and which instantiated this pager.

• request (google.cloud.aiplatform_v1beta1.types.ListFeaturesRequest) – The initial request object.

• response (google.cloud.aiplatform_v1beta1.types.ListFeaturesResponse) – The initial response object.

• retry (google.api_core.retry.AsyncRetry) – 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.

class google.cloud.aiplatform_v1beta1.services.feature_registry_service.pagers.ListFeaturesPager(method: Callable[[...], ListFeaturesResponse], request: ListFeaturesRequest, response: ListFeaturesResponse, *, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())

A pager for iterating through list_features requests.

This class thinly wraps an initial google.cloud.aiplatform_v1beta1.types.ListFeaturesResponse object, and provides an __iter__ method to iterate through its features field.

If there are more pages, the __iter__ method will make additional ListFeatures requests and continue to iterate through the features field on the corresponding responses.

All the usual google.cloud.aiplatform_v1beta1.types.ListFeaturesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiate the pager.

Parameters:

• method (Callable) – The method that was originally called, and which instantiated this pager.

• request (google.cloud.aiplatform_v1beta1.types.ListFeaturesRequest) – The initial request object.

• response (google.cloud.aiplatform_v1beta1.types.ListFeaturesResponse) – The initial response object.

• 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.