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FeaturestoreServiceAsyncClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Union[str, google.cloud.aiplatform_v1beta1.services.featurestore_service.transports.base.FeaturestoreServiceTransport] = '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 Featurestore.
Properties
api_endpoint
Return the API endpoint used by the client instance.
Returns | |
---|---|
Type | Description |
str |
The API endpoint used by the client instance. |
transport
Returns the transport used by the client instance.
Returns | |
---|---|
Type | Description |
FeaturestoreServiceTransport |
The transport used by the client instance. |
universe_domain
Return the universe domain used by the client instance.
Returns | |
---|---|
Type | Description |
str |
The universe domain used by the client instance. |
Methods
FeaturestoreServiceAsyncClient
FeaturestoreServiceAsyncClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Union[str, google.cloud.aiplatform_v1beta1.services.featurestore_service.transports.base.FeaturestoreServiceTransport] = '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>)
Instantiates the featurestore service async client.
Parameters | |
---|---|
Name | Description |
credentials |
Optional[google.auth.credentials.Credentials]
The authorization credentials to attach to requests. These credentials identify the application to the service; if none are specified, the client will attempt to ascertain the credentials from the environment. |
transport |
Union[str,
The transport to use. If set to None, a transport is chosen automatically. NOTE: "rest" transport functionality is currently in a beta state (preview). We welcome your feedback via an issue in this library's source repository. |
client_options |
Optional[Union[google.api_core.client_options.ClientOptions, dict]]
Custom options for the client. 1. The |
client_info |
google.api_core.gapic_v1.client_info.ClientInfo
The client info used to send a user-agent string along with API requests. If |
Exceptions | |
---|---|
Type | Description |
google.auth.exceptions.MutualTlsChannelError |
If mutual TLS transport creation failed for any reason. |
batch_create_features
batch_create_features(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.featurestore_service.BatchCreateFeaturesRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
requests: typing.Optional[
typing.MutableSequence[
google.cloud.aiplatform_v1beta1.types.featurestore_service.CreateFeatureRequest
]
] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation_async.AsyncOperation
Creates a batch of Features in a given EntityType.
# 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.FeaturestoreServiceAsyncClient()
# 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 | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1beta1.types.BatchCreateFeaturesRequest, dict]]
The request object. Request message for FeaturestoreService.BatchCreateFeatures. |
parent |
Required. The resource name of the EntityType to create the batch of Features under. Format: |
requests |
:class:
Required. The request message specifying the Features to create. All Features must be created under the same parent EntityType. The |
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 | |
---|---|
Type | Description |
google.api_core.operation_async.AsyncOperation |
An object representing a long-running operation. The result type for the operation will be BatchCreateFeaturesResponse Response message for FeaturestoreService.BatchCreateFeatures. |
batch_read_feature_values
batch_read_feature_values(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.featurestore_service.BatchReadFeatureValuesRequest,
dict,
]
] = None,
*,
featurestore: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation_async.AsyncOperation
Batch reads Feature values from a Featurestore.
This API enables batch reading Feature values, where each read instance in the batch may read Feature values of entities from one or more EntityTypes. Point-in-time correctness is guaranteed for Feature values of each read instance as of each instance's read timestamp.
# 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_read_feature_values():
# Create a client
client = aiplatform_v1beta1.FeaturestoreServiceAsyncClient()
# Initialize request argument(s)
csv_read_instances = aiplatform_v1beta1.CsvSource()
csv_read_instances.gcs_source.uris = ['uris_value1', 'uris_value2']
destination = aiplatform_v1beta1.FeatureValueDestination()
destination.bigquery_destination.output_uri = "output_uri_value"
entity_type_specs = aiplatform_v1beta1.EntityTypeSpec()
entity_type_specs.entity_type_id = "entity_type_id_value"
entity_type_specs.feature_selector.id_matcher.ids = ['ids_value1', 'ids_value2']
request = aiplatform_v1beta1.BatchReadFeatureValuesRequest(
csv_read_instances=csv_read_instances,
featurestore="featurestore_value",
destination=destination,
entity_type_specs=entity_type_specs,
)
# Make the request
operation = client.batch_read_feature_values(request=request)
print("Waiting for operation to complete...")
response = (await operation).result()
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1beta1.types.BatchReadFeatureValuesRequest, dict]]
The request object. Request message for FeaturestoreService.BatchReadFeatureValues. |
featurestore |
Required. The resource name of the Featurestore from which to query Feature values. Format: |
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 | |
---|---|
Type | Description |
google.api_core.operation_async.AsyncOperation |
An object representing a long-running operation. The result type for the operation will be BatchReadFeatureValuesResponse Response message for FeaturestoreService.BatchReadFeatureValues. |
cancel_operation
cancel_operation(
request: typing.Optional[
google.longrunning.operations_pb2.CancelOperationRequest
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> None
Starts asynchronous cancellation on a long-running operation.
The server makes a best effort to cancel the operation, but success
is not guaranteed. If the server doesn't support this method, it returns
google.rpc.Code.UNIMPLEMENTED
.
Parameters | |
---|---|
Name | Description |
request |
The request object. Request message for |
retry |
google.api_core.retry_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. |
common_billing_account_path
common_billing_account_path(billing_account: str) -> str
Returns a fully-qualified billing_account string.
common_folder_path
common_folder_path(folder: str) -> str
Returns a fully-qualified folder string.
common_location_path
common_location_path(project: str, location: str) -> str
Returns a fully-qualified location string.
common_organization_path
common_organization_path(organization: str) -> str
Returns a fully-qualified organization string.
common_project_path
common_project_path(project: str) -> str
Returns a fully-qualified project string.
create_entity_type
create_entity_type(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.featurestore_service.CreateEntityTypeRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
entity_type: typing.Optional[
google.cloud.aiplatform_v1beta1.types.entity_type.EntityType
] = None,
entity_type_id: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation_async.AsyncOperation
Creates a new EntityType in a given Featurestore.
# 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_entity_type():
# Create a client
client = aiplatform_v1beta1.FeaturestoreServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.CreateEntityTypeRequest(
parent="parent_value",
entity_type_id="entity_type_id_value",
)
# Make the request
operation = client.create_entity_type(request=request)
print("Waiting for operation to complete...")
response = (await operation).result()
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1beta1.types.CreateEntityTypeRequest, dict]]
The request object. Request message for FeaturestoreService.CreateEntityType. |
parent |
Required. The resource name of the Featurestore to create EntityTypes. Format: |
entity_type |
EntityType
The EntityType to create. This corresponds to the |
entity_type_id |
Required. The ID to use for the EntityType, which will become the final component of the EntityType's resource name. This value may be up to 60 characters, and valid characters are |
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 | |
---|---|
Type | Description |
google.api_core.operation_async.AsyncOperation |
An object representing a long-running operation. The result type for the operation will be EntityType An entity type is a type of object in a system that needs to be modeled and have stored information about. For example, driver is an entity type, and driver0 is an instance of an entity type driver. |
create_feature
create_feature(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.featurestore_service.CreateFeatureRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
feature: typing.Optional[
google.cloud.aiplatform_v1beta1.types.feature.Feature
] = None,
feature_id: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation_async.AsyncOperation
Creates a new Feature in a given EntityType.
# 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.FeaturestoreServiceAsyncClient()
# 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 | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1beta1.types.CreateFeatureRequest, dict]]
The request object. Request message for FeaturestoreService.CreateFeature. Request message for FeatureRegistryService.CreateFeature. |
parent |
Required. The resource name of the EntityType or FeatureGroup to create a Feature. Format for entity_type as parent: |
feature |
Feature
Required. The Feature to create. This corresponds to the |
feature_id |
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 |
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 | |
---|---|
Type | Description |
google.api_core.operation_async.AsyncOperation |
An object representing a long-running operation. The result type for the operation will be Feature Feature Metadata information. For example, color is a feature that describes an apple. |
create_featurestore
create_featurestore(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.featurestore_service.CreateFeaturestoreRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
featurestore: typing.Optional[
google.cloud.aiplatform_v1beta1.types.featurestore.Featurestore
] = None,
featurestore_id: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation_async.AsyncOperation
Creates a new Featurestore 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_featurestore():
# Create a client
client = aiplatform_v1beta1.FeaturestoreServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.CreateFeaturestoreRequest(
parent="parent_value",
featurestore_id="featurestore_id_value",
)
# Make the request
operation = client.create_featurestore(request=request)
print("Waiting for operation to complete...")
response = (await operation).result()
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1beta1.types.CreateFeaturestoreRequest, dict]]
The request object. Request message for FeaturestoreService.CreateFeaturestore. |
parent |
Required. The resource name of the Location to create Featurestores. Format: |
featurestore |
Featurestore
Required. The Featurestore to create. This corresponds to the |
featurestore_id |
Required. The ID to use for this Featurestore, which will become the final component of the Featurestore's resource name. This value may be up to 60 characters, and valid characters are |
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 | |
---|---|
Type | Description |
google.api_core.operation_async.AsyncOperation |
An object representing a long-running operation. The result type for the operation will be Featurestore Vertex AI Feature Store provides a centralized repository for organizing, storing, and serving ML features. The Featurestore is a top-level container for your features and their values. |
delete_entity_type
delete_entity_type(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.featurestore_service.DeleteEntityTypeRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
force: typing.Optional[bool] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation_async.AsyncOperation
Deletes a single EntityType. The EntityType must not have any
Features or force
must be set to true for the request to
succeed.
# 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_entity_type():
# Create a client
client = aiplatform_v1beta1.FeaturestoreServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.DeleteEntityTypeRequest(
name="name_value",
)
# Make the request
operation = client.delete_entity_type(request=request)
print("Waiting for operation to complete...")
response = (await operation).result()
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1beta1.types.DeleteEntityTypeRequest, dict]]
The request object. Request message for [FeaturestoreService.DeleteEntityTypes][]. |
name |
Required. The name of the EntityType to be deleted. Format: |
force |
If set to true, any Features for this EntityType will also be deleted. (Otherwise, the request will only work if the EntityType has no Features.) This corresponds to the |
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 | |
---|---|
Type | Description |
google.api_core.operation_async.AsyncOperation |
An object representing a long-running operation. The result type for the operation will be google.protobuf.empty_pb2.Empty A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } |
delete_feature
delete_feature(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.featurestore_service.DeleteFeatureRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation_async.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.FeaturestoreServiceAsyncClient()
# 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 | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1beta1.types.DeleteFeatureRequest, dict]]
The request object. Request message for FeaturestoreService.DeleteFeature. Request message for FeatureRegistryService.DeleteFeature. |
name |
Required. The name of the Features to be deleted. Format: |
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 | |
---|---|
Type | Description |
google.api_core.operation_async.AsyncOperation |
An object representing a long-running operation. The result type for the operation will be google.protobuf.empty_pb2.Empty A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } |
delete_feature_values
delete_feature_values(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.featurestore_service.DeleteFeatureValuesRequest,
dict,
]
] = None,
*,
entity_type: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation_async.AsyncOperation
Delete Feature values from Featurestore.
The progress of the deletion is tracked by the returned operation. The deleted feature values are guaranteed to be invisible to subsequent read operations after the operation is marked as successfully done.
If a delete feature values operation fails, the feature values returned from reads and exports may be inconsistent. If consistency is required, the caller must retry the same delete request again and wait till the new operation returned is marked as successfully done.
# 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_values():
# Create a client
client = aiplatform_v1beta1.FeaturestoreServiceAsyncClient()
# Initialize request argument(s)
select_entity = aiplatform_v1beta1.SelectEntity()
select_entity.entity_id_selector.csv_source.gcs_source.uris = ['uris_value1', 'uris_value2']
request = aiplatform_v1beta1.DeleteFeatureValuesRequest(
select_entity=select_entity,
entity_type="entity_type_value",
)
# Make the request
operation = client.delete_feature_values(request=request)
print("Waiting for operation to complete...")
response = (await operation).result()
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1beta1.types.DeleteFeatureValuesRequest, dict]]
The request object. Request message for FeaturestoreService.DeleteFeatureValues. |
entity_type |
Required. The resource name of the EntityType grouping the Features for which values are being deleted from. Format: |
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 | |
---|---|
Type | Description |
google.api_core.operation_async.AsyncOperation |
An object representing a long-running operation. The result type for the operation will be DeleteFeatureValuesResponse Response message for FeaturestoreService.DeleteFeatureValues. |
delete_featurestore
delete_featurestore(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.featurestore_service.DeleteFeaturestoreRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
force: typing.Optional[bool] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation_async.AsyncOperation
Deletes a single Featurestore. The Featurestore must not contain
any EntityTypes or force
must be set to true for the request
to succeed.
# 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_featurestore():
# Create a client
client = aiplatform_v1beta1.FeaturestoreServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.DeleteFeaturestoreRequest(
name="name_value",
)
# Make the request
operation = client.delete_featurestore(request=request)
print("Waiting for operation to complete...")
response = (await operation).result()
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1beta1.types.DeleteFeaturestoreRequest, dict]]
The request object. Request message for FeaturestoreService.DeleteFeaturestore. |
name |
Required. The name of the Featurestore to be deleted. Format: |
force |
If set to true, any EntityTypes and Features for this Featurestore will also be deleted. (Otherwise, the request will only work if the Featurestore has no EntityTypes.) This corresponds to the |
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 | |
---|---|
Type | Description |
google.api_core.operation_async.AsyncOperation |
An object representing a long-running operation. The result type for the operation will be google.protobuf.empty_pb2.Empty A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } |
delete_operation
delete_operation(
request: typing.Optional[
google.longrunning.operations_pb2.DeleteOperationRequest
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> None
Deletes a long-running operation.
This method indicates that the client is no longer interested
in the operation result. It does not cancel the operation.
If the server doesn't support this method, it returns
google.rpc.Code.UNIMPLEMENTED
.
Parameters | |
---|---|
Name | Description |
request |
The request object. Request message for |
retry |
google.api_core.retry_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. |
entity_type_path
entity_type_path(
project: str, location: str, featurestore: str, entity_type: str
) -> str
Returns a fully-qualified entity_type string.
export_feature_values
export_feature_values(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.featurestore_service.ExportFeatureValuesRequest,
dict,
]
] = None,
*,
entity_type: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation_async.AsyncOperation
Exports Feature values from all the entities of a target EntityType.
# 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_export_feature_values():
# Create a client
client = aiplatform_v1beta1.FeaturestoreServiceAsyncClient()
# Initialize request argument(s)
destination = aiplatform_v1beta1.FeatureValueDestination()
destination.bigquery_destination.output_uri = "output_uri_value"
feature_selector = aiplatform_v1beta1.FeatureSelector()
feature_selector.id_matcher.ids = ['ids_value1', 'ids_value2']
request = aiplatform_v1beta1.ExportFeatureValuesRequest(
entity_type="entity_type_value",
destination=destination,
feature_selector=feature_selector,
)
# Make the request
operation = client.export_feature_values(request=request)
print("Waiting for operation to complete...")
response = (await operation).result()
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1beta1.types.ExportFeatureValuesRequest, dict]]
The request object. Request message for FeaturestoreService.ExportFeatureValues. |
entity_type |
Required. The resource name of the EntityType from which to export Feature values. Format: |
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 | |
---|---|
Type | Description |
google.api_core.operation_async.AsyncOperation |
An object representing a long-running operation. The result type for the operation will be ExportFeatureValuesResponse Response message for FeaturestoreService.ExportFeatureValues. |
feature_path
feature_path(
project: str, location: str, featurestore: str, entity_type: str, feature: str
) -> str
Returns a fully-qualified feature string.
featurestore_path
featurestore_path(project: str, location: str, featurestore: str) -> str
Returns a fully-qualified featurestore string.
from_service_account_file
from_service_account_file(filename: str, *args, **kwargs)
Creates an instance of this client using the provided credentials file.
Parameter | |
---|---|
Name | Description |
filename |
str
The path to the service account private key json file. |
Returns | |
---|---|
Type | Description |
FeaturestoreServiceAsyncClient |
The constructed client. |
from_service_account_info
from_service_account_info(info: dict, *args, **kwargs)
Creates an instance of this client using the provided credentials info.
Parameter | |
---|---|
Name | Description |
info |
dict
The service account private key info. |
Returns | |
---|---|
Type | Description |
FeaturestoreServiceAsyncClient |
The constructed client. |
from_service_account_json
from_service_account_json(filename: str, *args, **kwargs)
Creates an instance of this client using the provided credentials file.
Parameter | |
---|---|
Name | Description |
filename |
str
The path to the service account private key json file. |
Returns | |
---|---|
Type | Description |
FeaturestoreServiceAsyncClient |
The constructed client. |
get_entity_type
get_entity_type(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.featurestore_service.GetEntityTypeRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1beta1.types.entity_type.EntityType
Gets details of a single EntityType.
# 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_entity_type():
# Create a client
client = aiplatform_v1beta1.FeaturestoreServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.GetEntityTypeRequest(
name="name_value",
)
# Make the request
response = await client.get_entity_type(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1beta1.types.GetEntityTypeRequest, dict]]
The request object. Request message for FeaturestoreService.GetEntityType. |
name |
Required. The name of the EntityType resource. Format: |
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 | |
---|---|
Type | Description |
google.cloud.aiplatform_v1beta1.types.EntityType |
An entity type is a type of object in a system that needs to be modeled and have stored information about. For example, driver is an entity type, and driver0 is an instance of an entity type driver. |
get_feature
get_feature(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.featurestore_service.GetFeatureRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1beta1.types.feature.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.FeaturestoreServiceAsyncClient()
# 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 | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1beta1.types.GetFeatureRequest, dict]]
The request object. Request message for FeaturestoreService.GetFeature. Request message for FeatureRegistryService.GetFeature. |
name |
Required. The name of the Feature resource. Format for entity_type as parent: |
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 | |
---|---|
Type | Description |
google.cloud.aiplatform_v1beta1.types.Feature |
Feature Metadata information. For example, color is a feature that describes an apple. |
get_featurestore
get_featurestore(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.featurestore_service.GetFeaturestoreRequest,
dict,
]
] = None,
*,
name: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1beta1.types.featurestore.Featurestore
Gets details of a single Featurestore.
# 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_featurestore():
# Create a client
client = aiplatform_v1beta1.FeaturestoreServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.GetFeaturestoreRequest(
name="name_value",
)
# Make the request
response = await client.get_featurestore(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1beta1.types.GetFeaturestoreRequest, dict]]
The request object. Request message for FeaturestoreService.GetFeaturestore. |
name |
Required. The name of the Featurestore resource. This corresponds to the |
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 | |
---|---|
Type | Description |
google.cloud.aiplatform_v1beta1.types.Featurestore |
Vertex AI Feature Store provides a centralized repository for organizing, storing, and serving ML features. The Featurestore is a top-level container for your features and their values. |
get_iam_policy
get_iam_policy(
request: typing.Optional[google.iam.v1.iam_policy_pb2.GetIamPolicyRequest] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.iam.v1.policy_pb2.Policy
Gets the IAM access control policy for a function.
Returns an empty policy if the function exists and does not have a policy set.
Parameters | |
---|---|
Name | Description |
request |
The request object. Request message for |
retry |
google.api_core.retry_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 | |
---|---|
Type | Description |
|
Defines an Identity and Access Management (IAM) policy. It is used to specify access control policies for Cloud Platform resources. A Policy is a collection of bindings . A binding binds one or more members to a single role . Members can be user accounts, service accounts, Google groups, and domains (such as G Suite). A role is a named list of permissions (defined by IAM or configured by users). A binding can optionally specify a condition , which is a logic expression that further constrains the role binding based on attributes about the request and/or target resource. **JSON Example** :: { "bindings": [ { "role": "roles/resourcemanager.organizationAdmin", "members": [ "user:mike@example.com", "group:admins@example.com", "domain:google.com", "serviceAccount:my-project-id@appspot.gserviceaccount.com" ] }, { "role": "roles/resourcemanager.organizationViewer", "members": ["user:eve@example.com"], "condition": { "title": "expirable access", "description": "Does not grant access after Sep 2020", "expression": "request.time < timestamp('2020-10-01t00:00:00.000z')",="" }="" }="" ]="" }="" **yaml="" example**="" ::="" bindings:="" -="" members:="" -="" user:mike@example.com="" -="" group:admins@example.com="" -="" domain:google.com="" -="" serviceaccount:my-project-id@appspot.gserviceaccount.com="" role:="" roles/resourcemanager.organizationadmin="" -="" members:="" -="" user:eve@example.com="" role:="" roles/resourcemanager.organizationviewer="" condition:="" title:="" expirable="" access="" description:="" does="" not="" grant="" access="" after="" sep="" 2020="" expression:="" request.time="">< timestamp('2020-10-01t00:00:00.000z')="" for="" a="" description="" of="" iam="" and="" its="" features,="" see="" the="">IAM developer's guide __. |
get_location
get_location(
request: typing.Optional[
google.cloud.location.locations_pb2.GetLocationRequest
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.location.locations_pb2.Location
Gets information about a location.
Parameters | |
---|---|
Name | Description |
request |
The request object. Request message for |
retry |
google.api_core.retry_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 | |
---|---|
Type | Description |
|
Location object. |
get_mtls_endpoint_and_cert_source
get_mtls_endpoint_and_cert_source(
client_options: typing.Optional[
google.api_core.client_options.ClientOptions
] = None,
)
Return the API endpoint and client cert source for mutual TLS.
The client cert source is determined in the following order:
(1) if GOOGLE_API_USE_CLIENT_CERTIFICATE
environment variable is not "true", the
client cert source is None.
(2) if client_options.client_cert_source
is provided, use the provided one; if the
default client cert source exists, use the default one; otherwise the client cert
source is None.
The API endpoint is determined in the following order:
(1) if client_options.api_endpoint
if provided, use the provided one.
(2) if GOOGLE_API_USE_CLIENT_CERTIFICATE
environment variable is "always", use the
default mTLS endpoint; if the environment variable is "never", use the default API
endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise
use the default API endpoint.
More details can be found at https://google.aip.dev/auth/4114.
Parameter | |
---|---|
Name | Description |
client_options |
google.api_core.client_options.ClientOptions
Custom options for the client. Only the |
Exceptions | |
---|---|
Type | Description |
google.auth.exceptions.MutualTLSChannelError |
If any errors happen. |
Returns | |
---|---|
Type | Description |
Tuple[str, Callable[[], Tuple[bytes, bytes]]] |
returns the API endpoint and the client cert source to use. |
get_operation
get_operation(
request: typing.Optional[
google.longrunning.operations_pb2.GetOperationRequest
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.longrunning.operations_pb2.Operation
Gets the latest state of a long-running operation.
Parameters | |
---|---|
Name | Description |
request |
The request object. Request message for |
retry |
google.api_core.retry_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 | |
---|---|
Type | Description |
|
An Operation object. |
get_transport_class
get_transport_class() -> (
typing.Type[
google.cloud.aiplatform_v1beta1.services.featurestore_service.transports.base.FeaturestoreServiceTransport
]
)
Returns an appropriate transport class.
Parameter | |
---|---|
Name | Description |
label |
typing.Optional[str]
The name of the desired transport. If none is provided, then the first transport in the registry is used. |
import_feature_values
import_feature_values(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.featurestore_service.ImportFeatureValuesRequest,
dict,
]
] = None,
*,
entity_type: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation_async.AsyncOperation
Imports Feature values into the Featurestore from a source storage. The progress of the import is tracked by the returned operation. The imported features are guaranteed to be visible to subsequent read operations after the operation is marked as successfully done.
If an import operation fails, the Feature values returned from reads and exports may be inconsistent. If consistency is required, the caller must retry the same import request again and wait till the new operation returned is marked as successfully done.
There are also scenarios where the caller can cause inconsistency.
- Source data for import contains multiple distinct Feature values for the same entity ID and timestamp.
- Source is modified during an import. This includes adding, updating, or removing source data and/or metadata. Examples of updating metadata include but are not limited to changing storage location, storage class, or retention policy.
- Online serving cluster is under-provisioned.
# 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_import_feature_values():
# Create a client
client = aiplatform_v1beta1.FeaturestoreServiceAsyncClient()
# Initialize request argument(s)
avro_source = aiplatform_v1beta1.AvroSource()
avro_source.gcs_source.uris = ['uris_value1', 'uris_value2']
feature_specs = aiplatform_v1beta1.FeatureSpec()
feature_specs.id = "id_value"
request = aiplatform_v1beta1.ImportFeatureValuesRequest(
avro_source=avro_source,
feature_time_field="feature_time_field_value",
entity_type="entity_type_value",
feature_specs=feature_specs,
)
# Make the request
operation = client.import_feature_values(request=request)
print("Waiting for operation to complete...")
response = (await operation).result()
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1beta1.types.ImportFeatureValuesRequest, dict]]
The request object. Request message for FeaturestoreService.ImportFeatureValues. |
entity_type |
Required. The resource name of the EntityType grouping the Features for which values are being imported. Format: |
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 | |
---|---|
Type | Description |
google.api_core.operation_async.AsyncOperation |
An object representing a long-running operation. The result type for the operation will be ImportFeatureValuesResponse Response message for FeaturestoreService.ImportFeatureValues. |
list_entity_types
list_entity_types(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.featurestore_service.ListEntityTypesRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> (
google.cloud.aiplatform_v1beta1.services.featurestore_service.pagers.ListEntityTypesAsyncPager
)
Lists EntityTypes in a given Featurestore.
# 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_entity_types():
# Create a client
client = aiplatform_v1beta1.FeaturestoreServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.ListEntityTypesRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_entity_types(request=request)
# Handle the response
async for response in page_result:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1beta1.types.ListEntityTypesRequest, dict]]
The request object. Request message for FeaturestoreService.ListEntityTypes. |
parent |
Required. The resource name of the Featurestore to list EntityTypes. Format: |
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 | |
---|---|
Type | Description |
google.cloud.aiplatform_v1beta1.services.featurestore_service.pagers.ListEntityTypesAsyncPager |
Response message for FeaturestoreService.ListEntityTypes. Iterating over this object will yield results and resolve additional pages automatically. |
list_features
list_features(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.featurestore_service.ListFeaturesRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> (
google.cloud.aiplatform_v1beta1.services.featurestore_service.pagers.ListFeaturesAsyncPager
)
Lists Features in a given EntityType.
# 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.FeaturestoreServiceAsyncClient()
# 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 | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1beta1.types.ListFeaturesRequest, dict]]
The request object. Request message for FeaturestoreService.ListFeatures. Request message for FeatureRegistryService.ListFeatures. |
parent |
Required. The resource name of the Location to list Features. Format for entity_type as parent: |
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 | |
---|---|
Type | Description |
google.cloud.aiplatform_v1beta1.services.featurestore_service.pagers.ListFeaturesAsyncPager |
Response message for FeaturestoreService.ListFeatures. Response message for FeatureRegistryService.ListFeatures. Iterating over this object will yield results and resolve additional pages automatically. |
list_featurestores
list_featurestores(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.featurestore_service.ListFeaturestoresRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> (
google.cloud.aiplatform_v1beta1.services.featurestore_service.pagers.ListFeaturestoresAsyncPager
)
Lists Featurestores 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_featurestores():
# Create a client
client = aiplatform_v1beta1.FeaturestoreServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.ListFeaturestoresRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_featurestores(request=request)
# Handle the response
async for response in page_result:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1beta1.types.ListFeaturestoresRequest, dict]]
The request object. Request message for FeaturestoreService.ListFeaturestores. |
parent |
Required. The resource name of the Location to list Featurestores. Format: |
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 | |
---|---|
Type | Description |
google.cloud.aiplatform_v1beta1.services.featurestore_service.pagers.ListFeaturestoresAsyncPager |
Response message for FeaturestoreService.ListFeaturestores. Iterating over this object will yield results and resolve additional pages automatically. |
list_locations
list_locations(
request: typing.Optional[
google.cloud.location.locations_pb2.ListLocationsRequest
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.location.locations_pb2.ListLocationsResponse
Lists information about the supported locations for this service.
Parameters | |
---|---|
Name | Description |
request |
The request object. Request message for |
retry |
google.api_core.retry_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 | |
---|---|
Type | Description |
|
Response message for ListLocations method. |
list_operations
list_operations(
request: typing.Optional[
google.longrunning.operations_pb2.ListOperationsRequest
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.longrunning.operations_pb2.ListOperationsResponse
Lists operations that match the specified filter in the request.
Parameters | |
---|---|
Name | Description |
request |
The request object. Request message for |
retry |
google.api_core.retry_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 | |
---|---|
Type | Description |
|
Response message for ListOperations method. |
parse_common_billing_account_path
parse_common_billing_account_path(path: str) -> typing.Dict[str, str]
Parse a billing_account path into its component segments.
parse_common_folder_path
parse_common_folder_path(path: str) -> typing.Dict[str, str]
Parse a folder path into its component segments.
parse_common_location_path
parse_common_location_path(path: str) -> typing.Dict[str, str]
Parse a location path into its component segments.
parse_common_organization_path
parse_common_organization_path(path: str) -> typing.Dict[str, str]
Parse a organization path into its component segments.
parse_common_project_path
parse_common_project_path(path: str) -> typing.Dict[str, str]
Parse a project path into its component segments.
parse_entity_type_path
parse_entity_type_path(path: str) -> typing.Dict[str, str]
Parses a entity_type path into its component segments.
parse_feature_path
parse_feature_path(path: str) -> typing.Dict[str, str]
Parses a feature path into its component segments.
parse_featurestore_path
parse_featurestore_path(path: str) -> typing.Dict[str, str]
Parses a featurestore path into its component segments.
search_features
search_features(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.featurestore_service.SearchFeaturesRequest,
dict,
]
] = None,
*,
location: typing.Optional[str] = None,
query: typing.Optional[str] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> (
google.cloud.aiplatform_v1beta1.services.featurestore_service.pagers.SearchFeaturesAsyncPager
)
Searches Features matching a query in a given project.
# 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_search_features():
# Create a client
client = aiplatform_v1beta1.FeaturestoreServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.SearchFeaturesRequest(
location="location_value",
)
# Make the request
page_result = client.search_features(request=request)
# Handle the response
async for response in page_result:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1beta1.types.SearchFeaturesRequest, dict]]
The request object. Request message for FeaturestoreService.SearchFeatures. |
location |
Required. The resource name of the Location to search Features. Format: |
query |
Query string that is a conjunction of field-restricted queries and/or field-restricted filters. Field-restricted queries and filters can be combined using |
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 | |
---|---|
Type | Description |
google.cloud.aiplatform_v1beta1.services.featurestore_service.pagers.SearchFeaturesAsyncPager |
Response message for FeaturestoreService.SearchFeatures. Iterating over this object will yield results and resolve additional pages automatically. |
set_iam_policy
set_iam_policy(
request: typing.Optional[google.iam.v1.iam_policy_pb2.SetIamPolicyRequest] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.iam.v1.policy_pb2.Policy
Sets the IAM access control policy on the specified function.
Replaces any existing policy.
Parameters | |
---|---|
Name | Description |
request |
The request object. Request message for |
retry |
google.api_core.retry_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 | |
---|---|
Type | Description |
|
Defines an Identity and Access Management (IAM) policy. It is used to specify access control policies for Cloud Platform resources. A Policy is a collection of bindings . A binding binds one or more members to a single role . Members can be user accounts, service accounts, Google groups, and domains (such as G Suite). A role is a named list of permissions (defined by IAM or configured by users). A binding can optionally specify a condition , which is a logic expression that further constrains the role binding based on attributes about the request and/or target resource. **JSON Example** :: { "bindings": [ { "role": "roles/resourcemanager.organizationAdmin", "members": [ "user:mike@example.com", "group:admins@example.com", "domain:google.com", "serviceAccount:my-project-id@appspot.gserviceaccount.com" ] }, { "role": "roles/resourcemanager.organizationViewer", "members": ["user:eve@example.com"], "condition": { "title": "expirable access", "description": "Does not grant access after Sep 2020", "expression": "request.time < timestamp('2020-10-01t00:00:00.000z')",="" }="" }="" ]="" }="" **yaml="" example**="" ::="" bindings:="" -="" members:="" -="" user:mike@example.com="" -="" group:admins@example.com="" -="" domain:google.com="" -="" serviceaccount:my-project-id@appspot.gserviceaccount.com="" role:="" roles/resourcemanager.organizationadmin="" -="" members:="" -="" user:eve@example.com="" role:="" roles/resourcemanager.organizationviewer="" condition:="" title:="" expirable="" access="" description:="" does="" not="" grant="" access="" after="" sep="" 2020="" expression:="" request.time="">< timestamp('2020-10-01t00:00:00.000z')="" for="" a="" description="" of="" iam="" and="" its="" features,="" see="" the="">IAM developer's guide __. |
test_iam_permissions
test_iam_permissions(
request: typing.Optional[
google.iam.v1.iam_policy_pb2.TestIamPermissionsRequest
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.iam.v1.iam_policy_pb2.TestIamPermissionsResponse
Tests the specified IAM permissions against the IAM access control policy for a function.
If the function does not exist, this will return an empty set of permissions, not a NOT_FOUND error.
Parameters | |
---|---|
Name | Description |
request |
The request object. Request message for |
retry |
google.api_core.retry_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 | |
---|---|
Type | Description |
|
Response message for TestIamPermissions method. |
update_entity_type
update_entity_type(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.featurestore_service.UpdateEntityTypeRequest,
dict,
]
] = None,
*,
entity_type: typing.Optional[
google.cloud.aiplatform_v1beta1.types.entity_type.EntityType
] = None,
update_mask: typing.Optional[google.protobuf.field_mask_pb2.FieldMask] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1beta1.types.entity_type.EntityType
Updates the parameters of a single EntityType.
# 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_entity_type():
# Create a client
client = aiplatform_v1beta1.FeaturestoreServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.UpdateEntityTypeRequest(
)
# Make the request
response = await client.update_entity_type(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1beta1.types.UpdateEntityTypeRequest, dict]]
The request object. Request message for FeaturestoreService.UpdateEntityType. |
entity_type |
EntityType
Required. The EntityType's |
update_mask |
Field mask is used to specify the fields to be overwritten in the EntityType 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 |
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 | |
---|---|
Type | Description |
google.cloud.aiplatform_v1beta1.types.EntityType |
An entity type is a type of object in a system that needs to be modeled and have stored information about. For example, driver is an entity type, and driver0 is an instance of an entity type driver. |
update_feature
update_feature(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.featurestore_service.UpdateFeatureRequest,
dict,
]
] = None,
*,
feature: typing.Optional[
google.cloud.aiplatform_v1beta1.types.feature.Feature
] = None,
update_mask: typing.Optional[google.protobuf.field_mask_pb2.FieldMask] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1beta1.types.feature.Feature
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.FeaturestoreServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.UpdateFeatureRequest(
)
# Make the request
response = await client.update_feature(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1beta1.types.UpdateFeatureRequest, dict]]
The request object. Request message for FeaturestoreService.UpdateFeature. Request message for FeatureRegistryService.UpdateFeature. |
feature |
Feature
Required. The Feature's |
update_mask |
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 |
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 | |
---|---|
Type | Description |
google.cloud.aiplatform_v1beta1.types.Feature |
Feature Metadata information. For example, color is a feature that describes an apple. |
update_featurestore
update_featurestore(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1beta1.types.featurestore_service.UpdateFeaturestoreRequest,
dict,
]
] = None,
*,
featurestore: typing.Optional[
google.cloud.aiplatform_v1beta1.types.featurestore.Featurestore
] = None,
update_mask: typing.Optional[google.protobuf.field_mask_pb2.FieldMask] = None,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation_async.AsyncOperation
Updates the parameters of a single Featurestore.
# 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_featurestore():
# Create a client
client = aiplatform_v1beta1.FeaturestoreServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.UpdateFeaturestoreRequest(
)
# Make the request
operation = client.update_featurestore(request=request)
print("Waiting for operation to complete...")
response = (await operation).result()
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1beta1.types.UpdateFeaturestoreRequest, dict]]
The request object. Request message for FeaturestoreService.UpdateFeaturestore. |
featurestore |
Featurestore
Required. The Featurestore's |
update_mask |
Field mask is used to specify the fields to be overwritten in the Featurestore 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 |
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 | |
---|---|
Type | Description |
google.api_core.operation_async.AsyncOperation |
An object representing a long-running operation. The result type for the operation will be Featurestore Vertex AI Feature Store provides a centralized repository for organizing, storing, and serving ML features. The Featurestore is a top-level container for your features and their values. |
wait_operation
wait_operation(
request: typing.Optional[
google.longrunning.operations_pb2.WaitOperationRequest
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_async.AsyncRetry,
google.api_core.gapic_v1.method._MethodDefault,
]
] = _MethodDefault._DEFAULT_VALUE,
timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.longrunning.operations_pb2.Operation
Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state.
If the operation is already done, the latest state is immediately returned.
If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC
timeout is used. If the server does not support this method, it returns
google.rpc.Code.UNIMPLEMENTED
.
Parameters | |
---|---|
Name | Description |
request |
The request object. Request message for |
retry |
google.api_core.retry_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 | |
---|---|
Type | Description |
|
An Operation object. |