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DatasetServiceAsyncClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.aiplatform_v1.services.dataset_service.transports.base.DatasetServiceTransport, typing.Callable[[...], google.cloud.aiplatform_v1.services.dataset_service.transports.base.DatasetServiceTransport]]] = '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 manages Vertex AI Dataset and its child resources.
Properties
api_endpoint
Return the API endpoint used by the client instance.
Returns | |
---|---|
Type | Description |
str |
The API endpoint used by the client instance. |
transport
Returns the transport used by the client instance.
Returns | |
---|---|
Type | Description |
DatasetServiceTransport |
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
DatasetServiceAsyncClient
DatasetServiceAsyncClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.aiplatform_v1.services.dataset_service.transports.base.DatasetServiceTransport, typing.Callable[[...], google.cloud.aiplatform_v1.services.dataset_service.transports.base.DatasetServiceTransport]]] = '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 dataset 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 |
Optional[Union[str,DatasetServiceTransport,Callable[..., DatasetServiceTransport]]]
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 DatasetServiceTransport constructor. If set to None, a transport is chosen automatically. NOTE: "rest" transport functionality is currently in a beta state (preview). We welcome your feedback via an issue in this library's source repository. |
client_options |
Optional[Union[google.api_core.client_options.ClientOptions, dict]]
Custom options for the client. 1. The |
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. |
annotation_path
annotation_path(
project: str, location: str, dataset: str, data_item: str, annotation: str
) -> str
Returns a fully-qualified annotation string.
annotation_spec_path
annotation_spec_path(
project: str, location: str, dataset: str, annotation_spec: str
) -> str
Returns a fully-qualified annotation_spec string.
cancel_operation
cancel_operation(
request: typing.Optional[
google.longrunning.operations_pb2.CancelOperationRequest
] = None,
*,
retry: typing.Optional[
typing.Union[
google.api_core.retry.retry_unary_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_dataset
create_dataset(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1.types.dataset_service.CreateDatasetRequest, dict
]
] = None,
*,
parent: typing.Optional[str] = None,
dataset: typing.Optional[google.cloud.aiplatform_v1.types.dataset.Dataset] = 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 Dataset.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1
async def sample_create_dataset():
# Create a client
client = aiplatform_v1.DatasetServiceAsyncClient()
# Initialize request argument(s)
dataset = aiplatform_v1.Dataset()
dataset.display_name = "display_name_value"
dataset.metadata_schema_uri = "metadata_schema_uri_value"
dataset.metadata.null_value = "NULL_VALUE"
request = aiplatform_v1.CreateDatasetRequest(
parent="parent_value",
dataset=dataset,
)
# Make the request
operation = client.create_dataset(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_v1.types.CreateDatasetRequest, dict]]
The request object. Request message for DatasetService.CreateDataset. |
parent |
Required. The resource name of the Location to create the Dataset in. Format: |
dataset |
Dataset
Required. The Dataset to create. 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 Dataset A collection of DataItems and Annotations on them. |
create_dataset_version
create_dataset_version(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1.types.dataset_service.CreateDatasetVersionRequest,
dict,
]
] = None,
*,
parent: typing.Optional[str] = None,
dataset_version: typing.Optional[
google.cloud.aiplatform_v1.types.dataset_version.DatasetVersion
] = 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
Create a version from a Dataset.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1
async def sample_create_dataset_version():
# Create a client
client = aiplatform_v1.DatasetServiceAsyncClient()
# Initialize request argument(s)
dataset_version = aiplatform_v1.DatasetVersion()
dataset_version.metadata.null_value = "NULL_VALUE"
request = aiplatform_v1.CreateDatasetVersionRequest(
parent="parent_value",
dataset_version=dataset_version,
)
# Make the request
operation = client.create_dataset_version(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_v1.types.CreateDatasetVersionRequest, dict]]
The request object. Request message for DatasetService.CreateDatasetVersion. |
parent |
Required. The name of the Dataset resource. Format: |
dataset_version |
DatasetVersion
Required. The version to be created. The same CMEK policies with the original Dataset will be applied the dataset version. So here we don't need to specify the EncryptionSpecType here. 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 DatasetVersion Describes the dataset version. |
data_item_path
data_item_path(project: str, location: str, dataset: str, data_item: str) -> str
Returns a fully-qualified data_item string.
dataset_path
dataset_path(project: str, location: str, dataset: str) -> str
Returns a fully-qualified dataset string.
dataset_version_path
dataset_version_path(
project: str, location: str, dataset: str, dataset_version: str
) -> str
Returns a fully-qualified dataset_version string.
delete_dataset
delete_dataset(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1.types.dataset_service.DeleteDatasetRequest, 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 Dataset.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1
async def sample_delete_dataset():
# Create a client
client = aiplatform_v1.DatasetServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.DeleteDatasetRequest(
name="name_value",
)
# Make the request
operation = client.delete_dataset(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_v1.types.DeleteDatasetRequest, dict]]
The request object. Request message for DatasetService.DeleteDataset. |
name |
Required. The resource name of the Dataset to delete. 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_dataset_version
delete_dataset_version(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1.types.dataset_service.DeleteDatasetVersionRequest,
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 Dataset version.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1
async def sample_delete_dataset_version():
# Create a client
client = aiplatform_v1.DatasetServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.DeleteDatasetVersionRequest(
name="name_value",
)
# Make the request
operation = client.delete_dataset_version(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_v1.types.DeleteDatasetVersionRequest, dict]]
The request object. Request message for DatasetService.DeleteDatasetVersion. |
name |
Required. The resource name of the Dataset version to delete. 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_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. |
delete_saved_query
delete_saved_query(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1.types.dataset_service.DeleteSavedQueryRequest,
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 SavedQuery.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1
async def sample_delete_saved_query():
# Create a client
client = aiplatform_v1.DatasetServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.DeleteSavedQueryRequest(
name="name_value",
)
# Make the request
operation = client.delete_saved_query(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_v1.types.DeleteSavedQueryRequest, dict]]
The request object. Request message for DatasetService.DeleteSavedQuery. |
name |
Required. The resource name of the SavedQuery to delete. 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); } |
export_data
export_data(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1.types.dataset_service.ExportDataRequest, dict
]
] = None,
*,
name: typing.Optional[str] = None,
export_config: typing.Optional[
google.cloud.aiplatform_v1.types.dataset.ExportDataConfig
] = 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 data from a Dataset.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1
async def sample_export_data():
# Create a client
client = aiplatform_v1.DatasetServiceAsyncClient()
# Initialize request argument(s)
export_config = aiplatform_v1.ExportDataConfig()
export_config.gcs_destination.output_uri_prefix = "output_uri_prefix_value"
request = aiplatform_v1.ExportDataRequest(
name="name_value",
export_config=export_config,
)
# Make the request
operation = client.export_data(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_v1.types.ExportDataRequest, dict]]
The request object. Request message for DatasetService.ExportData. |
name |
Required. The name of the Dataset resource. Format: |
export_config |
ExportDataConfig
Required. The desired output location. 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 ExportDataResponse Response message for DatasetService.ExportData. |
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 |
DatasetServiceAsyncClient |
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 |
DatasetServiceAsyncClient |
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 |
DatasetServiceAsyncClient |
The constructed client. |
get_annotation_spec
get_annotation_spec(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1.types.dataset_service.GetAnnotationSpecRequest,
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_v1.types.annotation_spec.AnnotationSpec
Gets an AnnotationSpec.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1
async def sample_get_annotation_spec():
# Create a client
client = aiplatform_v1.DatasetServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.GetAnnotationSpecRequest(
name="name_value",
)
# Make the request
response = await client.get_annotation_spec(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1.types.GetAnnotationSpecRequest, dict]]
The request object. Request message for DatasetService.GetAnnotationSpec. |
name |
Required. The name of the AnnotationSpec 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_v1.types.AnnotationSpec |
Identifies a concept with which DataItems may be annotated with. |
get_dataset
get_dataset(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1.types.dataset_service.GetDatasetRequest, 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_v1.types.dataset.Dataset
Gets a Dataset.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1
async def sample_get_dataset():
# Create a client
client = aiplatform_v1.DatasetServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.GetDatasetRequest(
name="name_value",
)
# Make the request
response = await client.get_dataset(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1.types.GetDatasetRequest, dict]]
The request object. Request message for DatasetService.GetDataset. |
name |
Required. The name of the Dataset 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_v1.types.Dataset |
A collection of DataItems and Annotations on them. |
get_dataset_version
get_dataset_version(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1.types.dataset_service.GetDatasetVersionRequest,
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_v1.types.dataset_version.DatasetVersion
Gets a Dataset version.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1
async def sample_get_dataset_version():
# Create a client
client = aiplatform_v1.DatasetServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.GetDatasetVersionRequest(
name="name_value",
)
# Make the request
response = await client.get_dataset_version(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1.types.GetDatasetVersionRequest, dict]]
The request object. Request message for DatasetService.GetDatasetVersion. |
name |
Required. The resource name of the Dataset version to delete. 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_v1.types.DatasetVersion |
Describes the dataset version. |
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_v1.services.dataset_service.transports.base.DatasetServiceTransport
]
)
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_data
import_data(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1.types.dataset_service.ImportDataRequest, dict
]
] = None,
*,
name: typing.Optional[str] = None,
import_configs: typing.Optional[
typing.MutableSequence[
google.cloud.aiplatform_v1.types.dataset.ImportDataConfig
]
] = 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 data into a Dataset.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1
async def sample_import_data():
# Create a client
client = aiplatform_v1.DatasetServiceAsyncClient()
# Initialize request argument(s)
import_configs = aiplatform_v1.ImportDataConfig()
import_configs.gcs_source.uris = ['uris_value1', 'uris_value2']
import_configs.import_schema_uri = "import_schema_uri_value"
request = aiplatform_v1.ImportDataRequest(
name="name_value",
import_configs=import_configs,
)
# Make the request
operation = client.import_data(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_v1.types.ImportDataRequest, dict]]
The request object. Request message for DatasetService.ImportData. |
name |
Required. The name of the Dataset resource. Format: |
import_configs |
:class:
Required. The desired input locations. The contents of all input locations will be imported in one batch. 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 ImportDataResponse Response message for DatasetService.ImportData. |
list_annotations
list_annotations(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1.types.dataset_service.ListAnnotationsRequest,
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_v1.services.dataset_service.pagers.ListAnnotationsAsyncPager
)
Lists Annotations belongs to a dataitem
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1
async def sample_list_annotations():
# Create a client
client = aiplatform_v1.DatasetServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.ListAnnotationsRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_annotations(request=request)
# Handle the response
async for response in page_result:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1.types.ListAnnotationsRequest, dict]]
The request object. Request message for DatasetService.ListAnnotations. |
parent |
Required. The resource name of the DataItem to list Annotations 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.cloud.aiplatform_v1.services.dataset_service.pagers.ListAnnotationsAsyncPager |
Response message for DatasetService.ListAnnotations. Iterating over this object will yield results and resolve additional pages automatically. |
list_data_items
list_data_items(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1.types.dataset_service.ListDataItemsRequest, 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_v1.services.dataset_service.pagers.ListDataItemsAsyncPager
Lists DataItems in a Dataset.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1
async def sample_list_data_items():
# Create a client
client = aiplatform_v1.DatasetServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.ListDataItemsRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_data_items(request=request)
# Handle the response
async for response in page_result:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1.types.ListDataItemsRequest, dict]]
The request object. Request message for DatasetService.ListDataItems. |
parent |
Required. The resource name of the Dataset to list DataItems 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.cloud.aiplatform_v1.services.dataset_service.pagers.ListDataItemsAsyncPager |
Response message for DatasetService.ListDataItems. Iterating over this object will yield results and resolve additional pages automatically. |
list_dataset_versions
list_dataset_versions(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1.types.dataset_service.ListDatasetVersionsRequest,
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_v1.services.dataset_service.pagers.ListDatasetVersionsAsyncPager
)
Lists DatasetVersions in a Dataset.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1
async def sample_list_dataset_versions():
# Create a client
client = aiplatform_v1.DatasetServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.ListDatasetVersionsRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_dataset_versions(request=request)
# Handle the response
async for response in page_result:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1.types.ListDatasetVersionsRequest, dict]]
The request object. Request message for DatasetService.ListDatasetVersions. |
parent |
Required. The resource name of the Dataset to list DatasetVersions 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.cloud.aiplatform_v1.services.dataset_service.pagers.ListDatasetVersionsAsyncPager |
Response message for DatasetService.ListDatasetVersions. Iterating over this object will yield results and resolve additional pages automatically. |
list_datasets
list_datasets(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1.types.dataset_service.ListDatasetsRequest, 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_v1.services.dataset_service.pagers.ListDatasetsAsyncPager
Lists Datasets in a Location.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1
async def sample_list_datasets():
# Create a client
client = aiplatform_v1.DatasetServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.ListDatasetsRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_datasets(request=request)
# Handle the response
async for response in page_result:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1.types.ListDatasetsRequest, dict]]
The request object. Request message for DatasetService.ListDatasets. |
parent |
Required. The name of the Dataset's parent 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_v1.services.dataset_service.pagers.ListDatasetsAsyncPager |
Response message for DatasetService.ListDatasets. 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. |
list_saved_queries
list_saved_queries(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1.types.dataset_service.ListSavedQueriesRequest,
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_v1.services.dataset_service.pagers.ListSavedQueriesAsyncPager
)
Lists SavedQueries in a Dataset.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1
async def sample_list_saved_queries():
# Create a client
client = aiplatform_v1.DatasetServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.ListSavedQueriesRequest(
parent="parent_value",
)
# Make the request
page_result = client.list_saved_queries(request=request)
# Handle the response
async for response in page_result:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1.types.ListSavedQueriesRequest, dict]]
The request object. Request message for DatasetService.ListSavedQueries. |
parent |
Required. The resource name of the Dataset to list SavedQueries 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.cloud.aiplatform_v1.services.dataset_service.pagers.ListSavedQueriesAsyncPager |
Response message for DatasetService.ListSavedQueries. Iterating over this object will yield results and resolve additional pages automatically. |
parse_annotation_path
parse_annotation_path(path: str) -> typing.Dict[str, str]
Parses a annotation path into its component segments.
parse_annotation_spec_path
parse_annotation_spec_path(path: str) -> typing.Dict[str, str]
Parses a annotation_spec path into its component segments.
parse_common_billing_account_path
parse_common_billing_account_path(path: str) -> typing.Dict[str, str]
Parse a billing_account path into its component segments.
parse_common_folder_path
parse_common_folder_path(path: str) -> typing.Dict[str, str]
Parse a folder path into its component segments.
parse_common_location_path
parse_common_location_path(path: str) -> typing.Dict[str, str]
Parse a location path into its component segments.
parse_common_organization_path
parse_common_organization_path(path: str) -> typing.Dict[str, str]
Parse a organization path into its component segments.
parse_common_project_path
parse_common_project_path(path: str) -> typing.Dict[str, str]
Parse a project path into its component segments.
parse_data_item_path
parse_data_item_path(path: str) -> typing.Dict[str, str]
Parses a data_item path into its component segments.
parse_dataset_path
parse_dataset_path(path: str) -> typing.Dict[str, str]
Parses a dataset path into its component segments.
parse_dataset_version_path
parse_dataset_version_path(path: str) -> typing.Dict[str, str]
Parses a dataset_version path into its component segments.
parse_saved_query_path
parse_saved_query_path(path: str) -> typing.Dict[str, str]
Parses a saved_query path into its component segments.
restore_dataset_version
restore_dataset_version(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1.types.dataset_service.RestoreDatasetVersionRequest,
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
Restores a dataset version.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1
async def sample_restore_dataset_version():
# Create a client
client = aiplatform_v1.DatasetServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.RestoreDatasetVersionRequest(
name="name_value",
)
# Make the request
operation = client.restore_dataset_version(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_v1.types.RestoreDatasetVersionRequest, dict]]
The request object. Request message for DatasetService.RestoreDatasetVersion. |
name |
Required. The name of the DatasetVersion 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.api_core.operation_async.AsyncOperation |
An object representing a long-running operation. The result type for the operation will be DatasetVersion Describes the dataset version. |
saved_query_path
saved_query_path(
project: str, location: str, dataset: str, saved_query: str
) -> str
Returns a fully-qualified saved_query string.
search_data_items
search_data_items(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1.types.dataset_service.SearchDataItemsRequest,
dict,
]
] = 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_v1.services.dataset_service.pagers.SearchDataItemsAsyncPager
)
Searches DataItems in a Dataset.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1
async def sample_search_data_items():
# Create a client
client = aiplatform_v1.DatasetServiceAsyncClient()
# Initialize request argument(s)
request = aiplatform_v1.SearchDataItemsRequest(
order_by_data_item="order_by_data_item_value",
dataset="dataset_value",
)
# Make the request
page_result = client.search_data_items(request=request)
# Handle the response
async for response in page_result:
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1.types.SearchDataItemsRequest, dict]]
The request object. Request message for DatasetService.SearchDataItems. |
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_v1.services.dataset_service.pagers.SearchDataItemsAsyncPager |
Response message for DatasetService.SearchDataItems. 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_dataset
update_dataset(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1.types.dataset_service.UpdateDatasetRequest, dict
]
] = None,
*,
dataset: typing.Optional[google.cloud.aiplatform_v1.types.dataset.Dataset] = 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_v1.types.dataset.Dataset
Updates a Dataset.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1
async def sample_update_dataset():
# Create a client
client = aiplatform_v1.DatasetServiceAsyncClient()
# Initialize request argument(s)
dataset = aiplatform_v1.Dataset()
dataset.display_name = "display_name_value"
dataset.metadata_schema_uri = "metadata_schema_uri_value"
dataset.metadata.null_value = "NULL_VALUE"
request = aiplatform_v1.UpdateDatasetRequest(
dataset=dataset,
)
# Make the request
response = await client.update_dataset(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1.types.UpdateDatasetRequest, dict]]
The request object. Request message for DatasetService.UpdateDataset. |
dataset |
Dataset
Required. The Dataset which replaces the resource on the server. This corresponds to the |
update_mask |
Required. The update mask applies to the resource. For 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_v1.types.Dataset |
A collection of DataItems and Annotations on them. |
update_dataset_version
update_dataset_version(
request: typing.Optional[
typing.Union[
google.cloud.aiplatform_v1.types.dataset_service.UpdateDatasetVersionRequest,
dict,
]
] = None,
*,
dataset_version: typing.Optional[
google.cloud.aiplatform_v1.types.dataset_version.DatasetVersion
] = 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_v1.types.dataset_version.DatasetVersion
Updates a DatasetVersion.
# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
# client as shown in:
# https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1
async def sample_update_dataset_version():
# Create a client
client = aiplatform_v1.DatasetServiceAsyncClient()
# Initialize request argument(s)
dataset_version = aiplatform_v1.DatasetVersion()
dataset_version.metadata.null_value = "NULL_VALUE"
request = aiplatform_v1.UpdateDatasetVersionRequest(
dataset_version=dataset_version,
)
# Make the request
response = await client.update_dataset_version(request=request)
# Handle the response
print(response)
Parameters | |
---|---|
Name | Description |
request |
Optional[Union[google.cloud.aiplatform_v1.types.UpdateDatasetVersionRequest, dict]]
The request object. Request message for DatasetService.UpdateDatasetVersion. |
dataset_version |
DatasetVersion
Required. The DatasetVersion which replaces the resource on the server. This corresponds to the |
update_mask |
Required. The update mask applies to the resource. For 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_v1.types.DatasetVersion |
Describes the dataset version. |
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. |