DatasetService¶

async create_dataset_version(request: Optional[Union[CreateDatasetVersionRequest, dict]] = None, *, parent: Optional[str] = None, dataset_version: Optional[DatasetVersion] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → AsyncOperation[source]¶

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_v1beta1

async def sample_create_dataset_version():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

    # Initialize request argument(s)
    dataset_version = aiplatform_v1beta1.DatasetVersion()
    dataset_version.metadata.null_value = "NULL_VALUE"

    request = aiplatform_v1beta1.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:

request (Optional[Union[google.cloud.aiplatform_v1beta1.types.CreateDatasetVersionRequest, dict]]) – The request object. Request message for [DatasetService.CreateDatasetVersion][google.cloud.aiplatform.v1beta1.DatasetService.CreateDatasetVersion].
parent (str) –
Required. The name of the Dataset resource. Format: projects/{project}/locations/{location}/datasets/{dataset}

This corresponds to the parent field on the request instance; if request is provided, this should not be set.
dataset_version (google.cloud.aiplatform_v1beta1.types.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 dataset_version field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry_async.AsyncRetry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

An object representing a long-running operation.

The result type for the operation will be google.cloud.aiplatform_v1beta1.types.DatasetVersion Describes the dataset version.

Return type:

static data_item_path(project: str, location: str, dataset: str, data_item: str) → str¶: Returns a fully-qualified data_item string.

static dataset_path(project: str, location: str, dataset: str) → str¶: Returns a fully-qualified dataset string.

static dataset_version_path(project: str, location: str, dataset: str, dataset_version: str) → str¶: Returns a fully-qualified dataset_version string.

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

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_v1beta1

async def sample_delete_dataset():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

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

request (Optional[Union[google.cloud.aiplatform_v1beta1.types.DeleteDatasetRequest, dict]]) – The request object. Request message for [DatasetService.DeleteDataset][google.cloud.aiplatform.v1beta1.DatasetService.DeleteDataset].
name (str) –
Required. The resource name of the Dataset to delete. Format: projects/{project}/locations/{location}/datasets/{dataset}

This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry_async.AsyncRetry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

An object representing a long-running operation.

The result type for the operation will be google.protobuf.empty_pb2.Empty A generic empty message that you can re-use to avoid defining duplicated

empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance:

service Foo {
rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty);

}

Return type:

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

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_v1beta1

async def sample_delete_dataset_version():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

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

request (Optional[Union[google.cloud.aiplatform_v1beta1.types.DeleteDatasetVersionRequest, dict]]) – The request object. Request message for [DatasetService.DeleteDatasetVersion][google.cloud.aiplatform.v1beta1.DatasetService.DeleteDatasetVersion].
name (str) –
Required. The resource name of the Dataset version to delete. Format: projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}

This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry_async.AsyncRetry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

An object representing a long-running operation.

The result type for the operation will be google.protobuf.empty_pb2.Empty A generic empty message that you can re-use to avoid defining duplicated

empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance:

service Foo {
rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty);

}

Return type:

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

Deletes a long-running operation.

This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn’t support this method, it returns google.rpc.Code.UNIMPLEMENTED.

Parameters:

request (DeleteOperationRequest) – The request object. Request message for DeleteOperation method.
retry (google.api_core.retry_async.AsyncRetry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

None

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

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_v1beta1

async def sample_delete_saved_query():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

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

request (Optional[Union[google.cloud.aiplatform_v1beta1.types.DeleteSavedQueryRequest, dict]]) – The request object. Request message for [DatasetService.DeleteSavedQuery][google.cloud.aiplatform.v1beta1.DatasetService.DeleteSavedQuery].
name (str) –
Required. The resource name of the SavedQuery to delete. Format: projects/{project}/locations/{location}/datasets/{dataset}/savedQueries/{saved_query}

This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry_async.AsyncRetry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

An object representing a long-running operation.

The result type for the operation will be google.protobuf.empty_pb2.Empty A generic empty message that you can re-use to avoid defining duplicated

empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance:

service Foo {
rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty);

}

Return type:

async export_data(request: Optional[Union[ExportDataRequest, dict]] = None, *, name: Optional[str] = None, export_config: Optional[ExportDataConfig] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → AsyncOperation[source]¶

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_v1beta1

async def sample_export_data():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

    # Initialize request argument(s)
    export_config = aiplatform_v1beta1.ExportDataConfig()
    export_config.gcs_destination.output_uri_prefix = "output_uri_prefix_value"

    request = aiplatform_v1beta1.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:

request (Optional[Union[google.cloud.aiplatform_v1beta1.types.ExportDataRequest, dict]]) – The request object. Request message for [DatasetService.ExportData][google.cloud.aiplatform.v1beta1.DatasetService.ExportData].
name (str) –
Required. The name of the Dataset resource. Format: projects/{project}/locations/{location}/datasets/{dataset}

This corresponds to the name field on the request instance; if request is provided, this should not be set.
export_config (google.cloud.aiplatform_v1beta1.types.ExportDataConfig) –
Required. The desired output location.

This corresponds to the export_config field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry_async.AsyncRetry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

An object representing a long-running operation.

The result type for the operation will be google.cloud.aiplatform_v1beta1.types.ExportDataResponse Response message for: [DatasetService.ExportData][google.cloud.aiplatform.v1beta1.DatasetService.ExportData].

Return type:

DatasetServiceAsyncClient

classmethod from_service_account_file(filename: str, *args, **kwargs)[source]¶

Creates an instance of this client using the provided credentials: file.

Parameters:

filename (str) – The path to the service account private key json file.
args – Additional arguments to pass to the constructor.
kwargs – Additional arguments to pass to the constructor.

Returns:

The constructed client.

Return type:

classmethod from_service_account_info(info: dict, *args, **kwargs)[source]¶

Creates an instance of this client using the provided credentials: info.

Parameters:

info (dict) – The service account private key info.
args – Additional arguments to pass to the constructor.
kwargs – Additional arguments to pass to the constructor.

Returns:

The constructed client.

Return type:

DatasetServiceAsyncClient

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

Creates an instance of this client using the provided credentials: file.

Parameters:

filename (str) – The path to the service account private key json file.
args – Additional arguments to pass to the constructor.
kwargs – Additional arguments to pass to the constructor.

Returns:

The constructed client.

Return type:

DatasetServiceAsyncClient

async get_annotation_spec(request: Optional[Union[GetAnnotationSpecRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → AnnotationSpec[source]¶

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_v1beta1

async def sample_get_annotation_spec():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

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

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

    # Handle the response
    print(response)

Parameters:

request (Optional[Union[google.cloud.aiplatform_v1beta1.types.GetAnnotationSpecRequest, dict]]) – The request object. Request message for [DatasetService.GetAnnotationSpec][google.cloud.aiplatform.v1beta1.DatasetService.GetAnnotationSpec].
name (str) –
Required. The name of the AnnotationSpec resource. Format: projects/{project}/locations/{location}/datasets/{dataset}/annotationSpecs/{annotation_spec}

This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry_async.AsyncRetry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Identifies a concept with which DataItems may be annotated with.

Return type:

google.cloud.aiplatform_v1beta1.types.AnnotationSpec

async get_dataset(request: Optional[Union[GetDatasetRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Dataset[source]¶

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_v1beta1

async def sample_get_dataset():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

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

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

    # Handle the response
    print(response)

Parameters:

request (Optional[Union[google.cloud.aiplatform_v1beta1.types.GetDatasetRequest, dict]]) – The request object. Request message for [DatasetService.GetDataset][google.cloud.aiplatform.v1beta1.DatasetService.GetDataset].
name (str) –
Required. The name of the Dataset resource.

This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry_async.AsyncRetry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

A collection of DataItems and Annotations on them.

Return type:

google.cloud.aiplatform_v1beta1.types.DatasetVersion

async get_dataset_version(request: Optional[Union[GetDatasetVersionRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → DatasetVersion[source]¶

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_v1beta1

async def sample_get_dataset_version():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

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

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

    # Handle the response
    print(response)

Parameters:

request (Optional[Union[google.cloud.aiplatform_v1beta1.types.GetDatasetVersionRequest, dict]]) – The request object. Request message for [DatasetService.GetDatasetVersion][google.cloud.aiplatform.v1beta1.DatasetService.GetDatasetVersion].
name (str) –
Required. The resource name of the Dataset version to delete. Format: projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}

This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry_async.AsyncRetry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Describes the dataset version.

Return type:

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

Gets the IAM access control policy for a function.

Returns an empty policy if the function exists and does not have a policy set.

Parameters:

request (GetIamPolicyRequest) – The request object. Request message for GetIamPolicy method.
retry (google.api_core.retry_async.AsyncRetry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Defines an Identity and Access Management (IAM) policy. It is used to specify access control policies for Cloud Platform resources. A Policy is a collection of bindings. A binding binds one or more members to a single role. Members can be user accounts, service accounts, Google groups, and domains (such as G Suite). A role is a named list of permissions (defined by IAM or configured by users). A binding can optionally specify a condition, which is a logic expression that further constrains the role binding based on attributes about the request and/or target resource.

JSON Example

{
  "bindings": [
    {
      "role": "roles/resourcemanager.organizationAdmin",
      "members": [
        "user:mike@example.com",
        "group:admins@example.com",
        "domain:google.com",
        "serviceAccount:my-project-id@appspot.gserviceaccount.com"
      ]
    },
    {
      "role": "roles/resourcemanager.organizationViewer",
      "members": ["user:eve@example.com"],
      "condition": {
        "title": "expirable access",
        "description": "Does not grant access after Sep 2020",
        "expression": "request.time <
        timestamp('2020-10-01T00:00:00.000Z')",
      }
    }
  ]
}

YAML Example

bindings:
- members:
  - user:mike@example.com
  - group:admins@example.com
  - domain:google.com
  - serviceAccount:my-project-id@appspot.gserviceaccount.com
  role: roles/resourcemanager.organizationAdmin
- members:
  - user:eve@example.com
  role: roles/resourcemanager.organizationViewer
  condition:
    title: expirable access
    description: Does not grant access after Sep 2020
    expression: request.time < timestamp('2020-10-01T00:00:00.000Z')

For a description of IAM and its features, see the IAM developer’s guide.

Return type:

Policy

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

Gets information about a location.

Parameters:

request (GetLocationRequest) – The request object. Request message for GetLocation method.
retry (google.api_core.retry_async.AsyncRetry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Location object.

Return type:

Location

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

Return the API endpoint and client cert source for mutual TLS.

The client cert source is determined in the following order: (1) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is not “true”, the client cert source is None. (2) if client_options.client_cert_source is provided, use the provided one; if the default client cert source exists, use the default one; otherwise the client cert source is None.

The API endpoint is determined in the following order: (1) if client_options.api_endpoint if provided, use the provided one. (2) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is “always”, use the default mTLS endpoint; if the environment variable is “never”, use the default API endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise use the default API endpoint.

More details can be found at https://google.aip.dev/auth/4114.

Parameters:

client_options (google.api_core.client_options.ClientOptions) – Custom options for the client. Only the api_endpoint and client_cert_source properties may be used in this method.

Returns:

returns the API endpoint and the: client cert source to use.

Return type:

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

Raises:

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

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

Gets the latest state of a long-running operation.

Parameters:

request (GetOperationRequest) – The request object. Request message for GetOperation method.
retry (google.api_core.retry_async.AsyncRetry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

An Operation object.

Return type:

Operation

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

Returns an appropriate transport class.

Parameters:: label – The name of the desired transport. If none is provided, then the first transport in the registry is used.
Returns:: The transport class to use.

async import_data(request: Optional[Union[ImportDataRequest, dict]] = None, *, name: Optional[str] = None, import_configs: Optional[MutableSequence[ImportDataConfig]] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → AsyncOperation[source]¶

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_v1beta1

async def sample_import_data():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

    # Initialize request argument(s)
    import_configs = aiplatform_v1beta1.ImportDataConfig()
    import_configs.gcs_source.uris = ['uris_value1', 'uris_value2']
    import_configs.import_schema_uri = "import_schema_uri_value"

    request = aiplatform_v1beta1.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:

request (Optional[Union[google.cloud.aiplatform_v1beta1.types.ImportDataRequest, dict]]) – The request object. Request message for [DatasetService.ImportData][google.cloud.aiplatform.v1beta1.DatasetService.ImportData].
name (str) –
Required. The name of the Dataset resource. Format: projects/{project}/locations/{location}/datasets/{dataset}

This corresponds to the name field on the request instance; if request is provided, this should not be set.
import_configs (MutableSequence[google.cloud.aiplatform_v1beta1.types.ImportDataConfig]) –
Required. The desired input locations. The contents of all input locations will be imported in one batch.

This corresponds to the import_configs field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry_async.AsyncRetry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

An object representing a long-running operation.

The result type for the operation will be google.cloud.aiplatform_v1beta1.types.ImportDataResponse Response message for: [DatasetService.ImportData][google.cloud.aiplatform.v1beta1.DatasetService.ImportData].

Return type:

google.cloud.aiplatform_v1beta1.services.dataset_service.pagers.ListAnnotationsAsyncPager

async list_annotations(request: Optional[Union[ListAnnotationsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → ListAnnotationsAsyncPager[source]¶

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_v1beta1

async def sample_list_annotations():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

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

request (Optional[Union[google.cloud.aiplatform_v1beta1.types.ListAnnotationsRequest, dict]]) – The request object. Request message for [DatasetService.ListAnnotations][google.cloud.aiplatform.v1beta1.DatasetService.ListAnnotations].
parent (str) –
Required. The resource name of the DataItem to list Annotations from. Format: projects/{project}/locations/{location}/datasets/{dataset}/dataItems/{data_item}

This corresponds to the parent field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry_async.AsyncRetry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Response message for: [DatasetService.ListAnnotations][google.cloud.aiplatform.v1beta1.DatasetService.ListAnnotations].

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

Return type:

async list_data_items(request: Optional[Union[ListDataItemsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → ListDataItemsAsyncPager[source]¶

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_v1beta1

async def sample_list_data_items():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

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

request (Optional[Union[google.cloud.aiplatform_v1beta1.types.ListDataItemsRequest, dict]]) – The request object. Request message for [DatasetService.ListDataItems][google.cloud.aiplatform.v1beta1.DatasetService.ListDataItems].
parent (str) –
Required. The resource name of the Dataset to list DataItems from. Format: projects/{project}/locations/{location}/datasets/{dataset}

This corresponds to the parent field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry_async.AsyncRetry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Response message for: [DatasetService.ListDataItems][google.cloud.aiplatform.v1beta1.DatasetService.ListDataItems].

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

Return type:

google.cloud.aiplatform_v1beta1.services.dataset_service.pagers.ListDataItemsAsyncPager

async list_dataset_versions(request: Optional[Union[ListDatasetVersionsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → ListDatasetVersionsAsyncPager[source]¶

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_v1beta1

async def sample_list_dataset_versions():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

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

request (Optional[Union[google.cloud.aiplatform_v1beta1.types.ListDatasetVersionsRequest, dict]]) – The request object. Request message for [DatasetService.ListDatasetVersions][google.cloud.aiplatform.v1beta1.DatasetService.ListDatasetVersions].
parent (str) –
Required. The resource name of the Dataset to list DatasetVersions from. Format: projects/{project}/locations/{location}/datasets/{dataset}

This corresponds to the parent field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry_async.AsyncRetry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Response message for: [DatasetService.ListDatasetVersions][google.cloud.aiplatform.v1beta1.DatasetService.ListDatasetVersions].

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

Return type:

google.cloud.aiplatform_v1beta1.services.dataset_service.pagers.ListDatasetVersionsAsyncPager

async list_datasets(request: Optional[Union[ListDatasetsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → ListDatasetsAsyncPager[source]¶

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_v1beta1

async def sample_list_datasets():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

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

request (Optional[Union[google.cloud.aiplatform_v1beta1.types.ListDatasetsRequest, dict]]) – The request object. Request message for [DatasetService.ListDatasets][google.cloud.aiplatform.v1beta1.DatasetService.ListDatasets].
parent (str) –
Required. The name of the Dataset’s parent resource. Format: projects/{project}/locations/{location}

This corresponds to the parent field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry_async.AsyncRetry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Response message for: [DatasetService.ListDatasets][google.cloud.aiplatform.v1beta1.DatasetService.ListDatasets].

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

Return type:

google.cloud.aiplatform_v1beta1.services.dataset_service.pagers.ListDatasetsAsyncPager

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

Lists information about the supported locations for this service.

Parameters:

request (ListLocationsRequest) – The request object. Request message for ListLocations method.
retry (google.api_core.retry_async.AsyncRetry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Response message for ListLocations method.

Return type:

ListLocationsResponse

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

Lists operations that match the specified filter in the request.

Parameters:

request (ListOperationsRequest) – The request object. Request message for ListOperations method.
retry (google.api_core.retry_async.AsyncRetry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Response message for ListOperations method.

Return type:

ListOperationsResponse

async list_saved_queries(request: Optional[Union[ListSavedQueriesRequest, dict]] = None, *, parent: Optional[str] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → ListSavedQueriesAsyncPager[source]¶

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_v1beta1

async def sample_list_saved_queries():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

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

request (Optional[Union[google.cloud.aiplatform_v1beta1.types.ListSavedQueriesRequest, dict]]) – The request object. Request message for [DatasetService.ListSavedQueries][google.cloud.aiplatform.v1beta1.DatasetService.ListSavedQueries].
parent (str) –
Required. The resource name of the Dataset to list SavedQueries from. Format: projects/{project}/locations/{location}/datasets/{dataset}

This corresponds to the parent field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry_async.AsyncRetry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Response message for: [DatasetService.ListSavedQueries][google.cloud.aiplatform.v1beta1.DatasetService.ListSavedQueries].

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

Return type:

google.cloud.aiplatform_v1beta1.services.dataset_service.pagers.ListSavedQueriesAsyncPager

static parse_annotation_path(path: str) → Dict[str, str]¶: Parses a annotation path into its component segments.

static parse_annotation_spec_path(path: str) → Dict[str, str]¶: Parses a annotation_spec path into its component segments.

static parse_common_billing_account_path(path: str) → Dict[str, str]¶: Parse a billing_account path into its component segments.

static parse_common_folder_path(path: str) → Dict[str, str]¶: Parse a folder path into its component segments.

static parse_common_location_path(path: str) → Dict[str, str]¶: Parse a location path into its component segments.

static parse_common_organization_path(path: str) → Dict[str, str]¶: Parse a organization path into its component segments.

static parse_common_project_path(path: str) → Dict[str, str]¶: Parse a project path into its component segments.

static parse_data_item_path(path: str) → Dict[str, str]¶: Parses a data_item path into its component segments.

static parse_dataset_path(path: str) → Dict[str, str]¶: Parses a dataset path into its component segments.

static parse_dataset_version_path(path: str) → Dict[str, str]¶: Parses a dataset_version path into its component segments.

static parse_saved_query_path(path: str) → Dict[str, str]¶: Parses a saved_query path into its component segments.

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

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_v1beta1

async def sample_restore_dataset_version():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

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

request (Optional[Union[google.cloud.aiplatform_v1beta1.types.RestoreDatasetVersionRequest, dict]]) – The request object. Request message for [DatasetService.RestoreDatasetVersion][google.cloud.aiplatform.v1beta1.DatasetService.RestoreDatasetVersion].
name (str) –
Required. The name of the DatasetVersion resource. Format: projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}

This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry_async.AsyncRetry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

An object representing a long-running operation.

The result type for the operation will be google.cloud.aiplatform_v1beta1.types.DatasetVersion Describes the dataset version.

Return type:

google.cloud.aiplatform_v1beta1.services.dataset_service.pagers.SearchDataItemsAsyncPager

static saved_query_path(project: str, location: str, dataset: str, saved_query: str) → str¶: Returns a fully-qualified saved_query string.

async search_data_items(request: Optional[Union[SearchDataItemsRequest, dict]] = None, *, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → SearchDataItemsAsyncPager[source]¶

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_v1beta1

async def sample_search_data_items():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

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

request (Optional[Union[google.cloud.aiplatform_v1beta1.types.SearchDataItemsRequest, dict]]) – The request object. Request message for [DatasetService.SearchDataItems][google.cloud.aiplatform.v1beta1.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:

Response message for: [DatasetService.SearchDataItems][google.cloud.aiplatform.v1beta1.DatasetService.SearchDataItems].

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

Return type:

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

Sets the IAM access control policy on the specified function.

Replaces any existing policy.

Parameters:

request (SetIamPolicyRequest) – The request object. Request message for SetIamPolicy method.
retry (google.api_core.retry_async.AsyncRetry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Defines an Identity and Access Management (IAM) policy. It is used to specify access control policies for Cloud Platform resources. A Policy is a collection of bindings. A binding binds one or more members to a single role. Members can be user accounts, service accounts, Google groups, and domains (such as G Suite). A role is a named list of permissions (defined by IAM or configured by users). A binding can optionally specify a condition, which is a logic expression that further constrains the role binding based on attributes about the request and/or target resource.

JSON Example

{
  "bindings": [
    {
      "role": "roles/resourcemanager.organizationAdmin",
      "members": [
        "user:mike@example.com",
        "group:admins@example.com",
        "domain:google.com",
        "serviceAccount:my-project-id@appspot.gserviceaccount.com"
      ]
    },
    {
      "role": "roles/resourcemanager.organizationViewer",
      "members": ["user:eve@example.com"],
      "condition": {
        "title": "expirable access",
        "description": "Does not grant access after Sep 2020",
        "expression": "request.time <
        timestamp('2020-10-01T00:00:00.000Z')",
      }
    }
  ]
}

YAML Example

bindings:
- members:
  - user:mike@example.com
  - group:admins@example.com
  - domain:google.com
  - serviceAccount:my-project-id@appspot.gserviceaccount.com
  role: roles/resourcemanager.organizationAdmin
- members:
  - user:eve@example.com
  role: roles/resourcemanager.organizationViewer
  condition:
    title: expirable access
    description: Does not grant access after Sep 2020
    expression: request.time < timestamp('2020-10-01T00:00:00.000Z')

For a description of IAM and its features, see the IAM developer’s guide.

Return type:

Policy

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

Tests the specified IAM permissions against the IAM access control: policy for a function.

If the function does not exist, this will return an empty set of permissions, not a NOT_FOUND error.

Parameters:

request (TestIamPermissionsRequest) – The request object. Request message for TestIamPermissions method.
retry (google.api_core.retry_async.AsyncRetry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Response message for TestIamPermissions method.

Return type:

TestIamPermissionsResponse

property transport: DatasetServiceTransport¶

Returns the transport used by the client instance.

Returns:: The transport used by the client instance.
Return type:: DatasetServiceTransport

property universe_domain: str¶

Return the universe domain used by the client instance.

Returns:

The universe domain used: by the client instance.

Return type:

str

async update_dataset(request: Optional[Union[UpdateDatasetRequest, dict]] = None, *, dataset: Optional[Dataset] = None, update_mask: Optional[FieldMask] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Dataset[source]¶

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_v1beta1

async def sample_update_dataset():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

    # Initialize request argument(s)
    dataset = aiplatform_v1beta1.Dataset()
    dataset.display_name = "display_name_value"
    dataset.metadata_schema_uri = "metadata_schema_uri_value"
    dataset.metadata.null_value = "NULL_VALUE"

    request = aiplatform_v1beta1.UpdateDatasetRequest(
        dataset=dataset,
    )

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

    # Handle the response
    print(response)

Parameters:

request (Optional[Union[google.cloud.aiplatform_v1beta1.types.UpdateDatasetRequest, dict]]) – The request object. Request message for [DatasetService.UpdateDataset][google.cloud.aiplatform.v1beta1.DatasetService.UpdateDataset].
dataset (google.cloud.aiplatform_v1beta1.types.Dataset) –
Required. The Dataset which replaces the resource on the server.

This corresponds to the dataset field on the request instance; if request is provided, this should not be set.
update_mask (google.protobuf.field_mask_pb2.FieldMask) –
Required. The update mask applies to the resource. For the FieldMask definition, see [google.protobuf.FieldMask][google.protobuf.FieldMask]. Updatable fields:
- display_name
- description
- labels
This corresponds to the update_mask field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry_async.AsyncRetry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

A collection of DataItems and Annotations on them.

Return type:

google.cloud.aiplatform_v1beta1.types.DatasetVersion

async update_dataset_version(request: Optional[Union[UpdateDatasetVersionRequest, dict]] = None, *, dataset_version: Optional[DatasetVersion] = None, update_mask: Optional[FieldMask] = None, retry: Optional[Union[AsyncRetry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → DatasetVersion[source]¶

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_v1beta1

async def sample_update_dataset_version():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

    # Initialize request argument(s)
    dataset_version = aiplatform_v1beta1.DatasetVersion()
    dataset_version.metadata.null_value = "NULL_VALUE"

    request = aiplatform_v1beta1.UpdateDatasetVersionRequest(
        dataset_version=dataset_version,
    )

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

    # Handle the response
    print(response)

Parameters:

request (Optional[Union[google.cloud.aiplatform_v1beta1.types.UpdateDatasetVersionRequest, dict]]) – The request object. Request message for [DatasetService.UpdateDatasetVersion][google.cloud.aiplatform.v1beta1.DatasetService.UpdateDatasetVersion].
dataset_version (google.cloud.aiplatform_v1beta1.types.DatasetVersion) –
Required. The DatasetVersion which replaces the resource on the server.

This corresponds to the dataset_version field on the request instance; if request is provided, this should not be set.
update_mask (google.protobuf.field_mask_pb2.FieldMask) –
Required. The update mask applies to the resource. For the FieldMask definition, see [google.protobuf.FieldMask][google.protobuf.FieldMask]. Updatable fields:
- display_name
This corresponds to the update_mask field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry_async.AsyncRetry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Describes the dataset version.

Return type:

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

Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state.

If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns google.rpc.Code.UNIMPLEMENTED.

Parameters:

request (WaitOperationRequest) – The request object. Request message for WaitOperation method.
retry (google.api_core.retry_async.AsyncRetry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

An Operation object.

Return type:

Operation

class google.cloud.aiplatform_v1beta1.services.dataset_service.DatasetServiceClient(*, credentials: ~typing.Optional[~google.auth.credentials.Credentials] = None, transport: ~typing.Optional[~typing.Union[str, ~google.cloud.aiplatform_v1beta1.services.dataset_service.transports.base.DatasetServiceTransport, ~typing.Callable[[...], ~google.cloud.aiplatform_v1beta1.services.dataset_service.transports.base.DatasetServiceTransport]]] = None, client_options: ~typing.Optional[~typing.Union[~google.api_core.client_options.ClientOptions, dict]] = None, client_info: ~google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)[source]¶

The service that manages Vertex AI Dataset and its child resources.

Instantiates the dataset service client.

Parameters:

credentials (Optional[google.auth.credentials.Credentials]) – The authorization credentials to attach to requests. These credentials identify the application to the service; if none are specified, the client will attempt to ascertain the credentials from the environment.
transport (Optional[Union[str,DatasetServiceTransport,Callable[..., DatasetServiceTransport]]]) – The transport to use, or a Callable that constructs and returns a new transport. If a Callable is given, it will be called with the same set of initialization arguments as used in the DatasetServiceTransport constructor. If set to None, a transport is chosen automatically.
client_options (Optional[Union[google.api_core.client_options.ClientOptions, dict]]) –
Custom options for the client.

1. The api_endpoint property can be used to override the default endpoint provided by the client when transport is not explicitly provided. Only if this property is not set and transport was not explicitly provided, the endpoint is determined by the GOOGLE_API_USE_MTLS_ENDPOINT environment variable, which have one of the following values: “always” (always use the default mTLS endpoint), “never” (always use the default regular endpoint) and “auto” (auto-switch to the default mTLS endpoint if client certificate is present; this is the default value).

2. If the GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is “true”, then the client_cert_source property can be used to provide a client certificate for mTLS transport. If not provided, the default SSL client certificate will be used if present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is “false” or not set, no client certificate will be used.

3. The universe_domain property can be used to override the default “googleapis.com” universe. Note that the api_endpoint property still takes precedence; and universe_domain is currently not supported for mTLS.
client_info (google.api_core.gapic_v1.client_info.ClientInfo) – The client info used to send a user-agent string along with API requests. If None, then default info will be used. Generally, you only need to set this if you’re developing your own client library.

Raises:

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

__exit__(type, value, traceback)[source]¶: Releases underlying transport’s resources.

Warning

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

static annotation_path(project: str, location: str, dataset: str, data_item: str, annotation: str) → str[source]¶: Returns a fully-qualified annotation string.

static annotation_spec_path(project: str, location: str, dataset: str, annotation_spec: str) → str[source]¶: Returns a fully-qualified annotation_spec string.

property api_endpoint¶

Return the API endpoint used by the client instance.

Returns:: The API endpoint used by the client instance.
Return type:: str

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

Starts asynchronous cancellation on a long-running operation.

The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn’t support this method, it returns google.rpc.Code.UNIMPLEMENTED.

Parameters:

request (CancelOperationRequest) – The request object. Request message for CancelOperation method.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

None

static common_billing_account_path(billing_account: str) → str[source]¶: Returns a fully-qualified billing_account string.

static common_folder_path(folder: str) → str[source]¶: Returns a fully-qualified folder string.

static common_location_path(project: str, location: str) → str[source]¶: Returns a fully-qualified location string.

static common_organization_path(organization: str) → str[source]¶: Returns a fully-qualified organization string.

static common_project_path(project: str) → str[source]¶: Returns a fully-qualified project string.

create_dataset(request: Optional[Union[CreateDatasetRequest, dict]] = None, *, parent: Optional[str] = None, dataset: Optional[Dataset] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Operation[source]¶

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_v1beta1

def sample_create_dataset():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceClient()

    # Initialize request argument(s)
    dataset = aiplatform_v1beta1.Dataset()
    dataset.display_name = "display_name_value"
    dataset.metadata_schema_uri = "metadata_schema_uri_value"
    dataset.metadata.null_value = "NULL_VALUE"

    request = aiplatform_v1beta1.CreateDatasetRequest(
        parent="parent_value",
        dataset=dataset,
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)

Parameters:

request (Union[google.cloud.aiplatform_v1beta1.types.CreateDatasetRequest, dict]) – The request object. Request message for [DatasetService.CreateDataset][google.cloud.aiplatform.v1beta1.DatasetService.CreateDataset].
parent (str) –
Required. The resource name of the Location to create the Dataset in. Format: projects/{project}/locations/{location}

This corresponds to the parent field on the request instance; if request is provided, this should not be set.
dataset (google.cloud.aiplatform_v1beta1.types.Dataset) – Required. The Dataset to create. This corresponds to the dataset field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

An object representing a long-running operation.

The result type for the operation will be google.cloud.aiplatform_v1beta1.types.Dataset A collection of DataItems and Annotations on them.

Return type:

create_dataset_version(request: Optional[Union[CreateDatasetVersionRequest, dict]] = None, *, parent: Optional[str] = None, dataset_version: Optional[DatasetVersion] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Operation[source]¶

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_v1beta1

def sample_create_dataset_version():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceClient()

    # Initialize request argument(s)
    dataset_version = aiplatform_v1beta1.DatasetVersion()
    dataset_version.metadata.null_value = "NULL_VALUE"

    request = aiplatform_v1beta1.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 = operation.result()

    # Handle the response
    print(response)

Parameters:

request (Union[google.cloud.aiplatform_v1beta1.types.CreateDatasetVersionRequest, dict]) – The request object. Request message for [DatasetService.CreateDatasetVersion][google.cloud.aiplatform.v1beta1.DatasetService.CreateDatasetVersion].
parent (str) –
Required. The name of the Dataset resource. Format: projects/{project}/locations/{location}/datasets/{dataset}

This corresponds to the parent field on the request instance; if request is provided, this should not be set.
dataset_version (google.cloud.aiplatform_v1beta1.types.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 dataset_version field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

An object representing a long-running operation.

The result type for the operation will be google.cloud.aiplatform_v1beta1.types.DatasetVersion Describes the dataset version.

Return type:

static data_item_path(project: str, location: str, dataset: str, data_item: str) → str[source]¶: Returns a fully-qualified data_item string.

static dataset_path(project: str, location: str, dataset: str) → str[source]¶: Returns a fully-qualified dataset string.

static dataset_version_path(project: str, location: str, dataset: str, dataset_version: str) → str[source]¶: Returns a fully-qualified dataset_version string.

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

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_v1beta1

def sample_delete_dataset():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceClient()

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

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

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

    response = operation.result()

    # Handle the response
    print(response)

Parameters:

request (Union[google.cloud.aiplatform_v1beta1.types.DeleteDatasetRequest, dict]) – The request object. Request message for [DatasetService.DeleteDataset][google.cloud.aiplatform.v1beta1.DatasetService.DeleteDataset].
name (str) –
Required. The resource name of the Dataset to delete. Format: projects/{project}/locations/{location}/datasets/{dataset}

This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

An object representing a long-running operation.

The result type for the operation will be google.protobuf.empty_pb2.Empty A generic empty message that you can re-use to avoid defining duplicated

empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance:

service Foo {
rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty);

}

Return type:

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

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_v1beta1

def sample_delete_dataset_version():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceClient()

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

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

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

    response = operation.result()

    # Handle the response
    print(response)

Parameters:

request (Union[google.cloud.aiplatform_v1beta1.types.DeleteDatasetVersionRequest, dict]) – The request object. Request message for [DatasetService.DeleteDatasetVersion][google.cloud.aiplatform.v1beta1.DatasetService.DeleteDatasetVersion].
name (str) –
Required. The resource name of the Dataset version to delete. Format: projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}

This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

An object representing a long-running operation.

The result type for the operation will be google.protobuf.empty_pb2.Empty A generic empty message that you can re-use to avoid defining duplicated

empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance:

service Foo {
rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty);

}

Return type:

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

Deletes a long-running operation.

This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn’t support this method, it returns google.rpc.Code.UNIMPLEMENTED.

Parameters:

request (DeleteOperationRequest) – The request object. Request message for DeleteOperation method.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

None

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

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_v1beta1

def sample_delete_saved_query():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceClient()

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

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

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

    response = operation.result()

    # Handle the response
    print(response)

Parameters:

request (Union[google.cloud.aiplatform_v1beta1.types.DeleteSavedQueryRequest, dict]) – The request object. Request message for [DatasetService.DeleteSavedQuery][google.cloud.aiplatform.v1beta1.DatasetService.DeleteSavedQuery].
name (str) –
Required. The resource name of the SavedQuery to delete. Format: projects/{project}/locations/{location}/datasets/{dataset}/savedQueries/{saved_query}

This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

An object representing a long-running operation.

The result type for the operation will be google.protobuf.empty_pb2.Empty A generic empty message that you can re-use to avoid defining duplicated

empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance:

service Foo {
rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty);

}

Return type:

export_data(request: Optional[Union[ExportDataRequest, dict]] = None, *, name: Optional[str] = None, export_config: Optional[ExportDataConfig] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Operation[source]¶

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_v1beta1

def sample_export_data():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceClient()

    # Initialize request argument(s)
    export_config = aiplatform_v1beta1.ExportDataConfig()
    export_config.gcs_destination.output_uri_prefix = "output_uri_prefix_value"

    request = aiplatform_v1beta1.ExportDataRequest(
        name="name_value",
        export_config=export_config,
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)

Parameters:

request (Union[google.cloud.aiplatform_v1beta1.types.ExportDataRequest, dict]) – The request object. Request message for [DatasetService.ExportData][google.cloud.aiplatform.v1beta1.DatasetService.ExportData].
name (str) –
Required. The name of the Dataset resource. Format: projects/{project}/locations/{location}/datasets/{dataset}

This corresponds to the name field on the request instance; if request is provided, this should not be set.
export_config (google.cloud.aiplatform_v1beta1.types.ExportDataConfig) –
Required. The desired output location.

This corresponds to the export_config field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

An object representing a long-running operation.

The result type for the operation will be google.cloud.aiplatform_v1beta1.types.ExportDataResponse Response message for: [DatasetService.ExportData][google.cloud.aiplatform.v1beta1.DatasetService.ExportData].

Return type:

google.cloud.aiplatform_v1beta1.types.AnnotationSpec

classmethod from_service_account_file(filename: str, *args, **kwargs)[source]¶

Creates an instance of this client using the provided credentials: file.

Parameters:

filename (str) – The path to the service account private key json file.
args – Additional arguments to pass to the constructor.
kwargs – Additional arguments to pass to the constructor.

Returns:

The constructed client.

Return type:

DatasetServiceClient

classmethod from_service_account_info(info: dict, *args, **kwargs)[source]¶

Creates an instance of this client using the provided credentials: info.

Parameters:

info (dict) – The service account private key info.
args – Additional arguments to pass to the constructor.
kwargs – Additional arguments to pass to the constructor.

Returns:

The constructed client.

Return type:

DatasetServiceClient

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

Creates an instance of this client using the provided credentials: file.

Parameters:

filename (str) – The path to the service account private key json file.
args – Additional arguments to pass to the constructor.
kwargs – Additional arguments to pass to the constructor.

Returns:

The constructed client.

Return type:

DatasetServiceClient

get_annotation_spec(request: Optional[Union[GetAnnotationSpecRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → AnnotationSpec[source]¶

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_v1beta1

def sample_get_annotation_spec():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceClient()

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

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

    # Handle the response
    print(response)

Parameters:

request (Union[google.cloud.aiplatform_v1beta1.types.GetAnnotationSpecRequest, dict]) – The request object. Request message for [DatasetService.GetAnnotationSpec][google.cloud.aiplatform.v1beta1.DatasetService.GetAnnotationSpec].
name (str) –
Required. The name of the AnnotationSpec resource. Format: projects/{project}/locations/{location}/datasets/{dataset}/annotationSpecs/{annotation_spec}

This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Identifies a concept with which DataItems may be annotated with.

Return type:

get_dataset(request: Optional[Union[GetDatasetRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Dataset[source]¶

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_v1beta1

def sample_get_dataset():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceClient()

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

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

    # Handle the response
    print(response)

Parameters:

request (Union[google.cloud.aiplatform_v1beta1.types.GetDatasetRequest, dict]) – The request object. Request message for [DatasetService.GetDataset][google.cloud.aiplatform.v1beta1.DatasetService.GetDataset].
name (str) –
Required. The name of the Dataset resource.

This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

A collection of DataItems and Annotations on them.

Return type:

google.cloud.aiplatform_v1beta1.types.DatasetVersion

get_dataset_version(request: Optional[Union[GetDatasetVersionRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → DatasetVersion[source]¶

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_v1beta1

def sample_get_dataset_version():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceClient()

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

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

    # Handle the response
    print(response)

Parameters:

request (Union[google.cloud.aiplatform_v1beta1.types.GetDatasetVersionRequest, dict]) – The request object. Request message for [DatasetService.GetDatasetVersion][google.cloud.aiplatform.v1beta1.DatasetService.GetDatasetVersion].
name (str) –
Required. The resource name of the Dataset version to delete. Format: projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}

This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Describes the dataset version.

Return type:

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

Gets the IAM access control policy for a function.

Returns an empty policy if the function exists and does not have a policy set.

Parameters:

request (GetIamPolicyRequest) – The request object. Request message for GetIamPolicy method.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Defines an Identity and Access Management (IAM) policy. It is used to specify access control policies for Cloud Platform resources. A Policy is a collection of bindings. A binding binds one or more members to a single role. Members can be user accounts, service accounts, Google groups, and domains (such as G Suite). A role is a named list of permissions (defined by IAM or configured by users). A binding can optionally specify a condition, which is a logic expression that further constrains the role binding based on attributes about the request and/or target resource.

JSON Example

{
  "bindings": [
    {
      "role": "roles/resourcemanager.organizationAdmin",
      "members": [
        "user:mike@example.com",
        "group:admins@example.com",
        "domain:google.com",
        "serviceAccount:my-project-id@appspot.gserviceaccount.com"
      ]
    },
    {
      "role": "roles/resourcemanager.organizationViewer",
      "members": ["user:eve@example.com"],
      "condition": {
        "title": "expirable access",
        "description": "Does not grant access after Sep 2020",
        "expression": "request.time <
        timestamp('2020-10-01T00:00:00.000Z')",
      }
    }
  ]
}

YAML Example

bindings:
- members:
  - user:mike@example.com
  - group:admins@example.com
  - domain:google.com
  - serviceAccount:my-project-id@appspot.gserviceaccount.com
  role: roles/resourcemanager.organizationAdmin
- members:
  - user:eve@example.com
  role: roles/resourcemanager.organizationViewer
  condition:
    title: expirable access
    description: Does not grant access after Sep 2020
    expression: request.time < timestamp('2020-10-01T00:00:00.000Z')

For a description of IAM and its features, see the IAM developer’s guide.

Return type:

Policy

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

Gets information about a location.

Parameters:

request (GetLocationRequest) – The request object. Request message for GetLocation method.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Location object.

Return type:

Location

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

Deprecated. Return the API endpoint and client cert source for mutual TLS.

The client cert source is determined in the following order: (1) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is not “true”, the client cert source is None. (2) if client_options.client_cert_source is provided, use the provided one; if the default client cert source exists, use the default one; otherwise the client cert source is None.

The API endpoint is determined in the following order: (1) if client_options.api_endpoint if provided, use the provided one. (2) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is “always”, use the default mTLS endpoint; if the environment variable is “never”, use the default API endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise use the default API endpoint.

More details can be found at https://google.aip.dev/auth/4114.

Parameters:

client_options (google.api_core.client_options.ClientOptions) – Custom options for the client. Only the api_endpoint and client_cert_source properties may be used in this method.

Returns:

returns the API endpoint and the: client cert source to use.

Return type:

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

Raises:

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

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

Gets the latest state of a long-running operation.

Parameters:

request (GetOperationRequest) – The request object. Request message for GetOperation method.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

An Operation object.

Return type:

Operation

import_data(request: Optional[Union[ImportDataRequest, dict]] = None, *, name: Optional[str] = None, import_configs: Optional[MutableSequence[ImportDataConfig]] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Operation[source]¶

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_v1beta1

def sample_import_data():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceClient()

    # Initialize request argument(s)
    import_configs = aiplatform_v1beta1.ImportDataConfig()
    import_configs.gcs_source.uris = ['uris_value1', 'uris_value2']
    import_configs.import_schema_uri = "import_schema_uri_value"

    request = aiplatform_v1beta1.ImportDataRequest(
        name="name_value",
        import_configs=import_configs,
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)

Parameters:

request (Union[google.cloud.aiplatform_v1beta1.types.ImportDataRequest, dict]) – The request object. Request message for [DatasetService.ImportData][google.cloud.aiplatform.v1beta1.DatasetService.ImportData].
name (str) –
Required. The name of the Dataset resource. Format: projects/{project}/locations/{location}/datasets/{dataset}

This corresponds to the name field on the request instance; if request is provided, this should not be set.
import_configs (MutableSequence[google.cloud.aiplatform_v1beta1.types.ImportDataConfig]) –
Required. The desired input locations. The contents of all input locations will be imported in one batch.

This corresponds to the import_configs field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

An object representing a long-running operation.

The result type for the operation will be google.cloud.aiplatform_v1beta1.types.ImportDataResponse Response message for: [DatasetService.ImportData][google.cloud.aiplatform.v1beta1.DatasetService.ImportData].

Return type:

google.cloud.aiplatform_v1beta1.services.dataset_service.pagers.ListAnnotationsPager

list_annotations(request: Optional[Union[ListAnnotationsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → ListAnnotationsPager[source]¶

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_v1beta1

def sample_list_annotations():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceClient()

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

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

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

Parameters:

request (Union[google.cloud.aiplatform_v1beta1.types.ListAnnotationsRequest, dict]) – The request object. Request message for [DatasetService.ListAnnotations][google.cloud.aiplatform.v1beta1.DatasetService.ListAnnotations].
parent (str) –
Required. The resource name of the DataItem to list Annotations from. Format: projects/{project}/locations/{location}/datasets/{dataset}/dataItems/{data_item}

This corresponds to the parent field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Response message for: [DatasetService.ListAnnotations][google.cloud.aiplatform.v1beta1.DatasetService.ListAnnotations].

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

Return type:

list_data_items(request: Optional[Union[ListDataItemsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → ListDataItemsPager[source]¶

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_v1beta1

def sample_list_data_items():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceClient()

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

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

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

Parameters:

request (Union[google.cloud.aiplatform_v1beta1.types.ListDataItemsRequest, dict]) – The request object. Request message for [DatasetService.ListDataItems][google.cloud.aiplatform.v1beta1.DatasetService.ListDataItems].
parent (str) –
Required. The resource name of the Dataset to list DataItems from. Format: projects/{project}/locations/{location}/datasets/{dataset}

This corresponds to the parent field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Response message for: [DatasetService.ListDataItems][google.cloud.aiplatform.v1beta1.DatasetService.ListDataItems].

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

Return type:

google.cloud.aiplatform_v1beta1.services.dataset_service.pagers.ListDataItemsPager

list_dataset_versions(request: Optional[Union[ListDatasetVersionsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → ListDatasetVersionsPager[source]¶

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_v1beta1

def sample_list_dataset_versions():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceClient()

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

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

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

Parameters:

request (Union[google.cloud.aiplatform_v1beta1.types.ListDatasetVersionsRequest, dict]) – The request object. Request message for [DatasetService.ListDatasetVersions][google.cloud.aiplatform.v1beta1.DatasetService.ListDatasetVersions].
parent (str) –
Required. The resource name of the Dataset to list DatasetVersions from. Format: projects/{project}/locations/{location}/datasets/{dataset}

This corresponds to the parent field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Response message for: [DatasetService.ListDatasetVersions][google.cloud.aiplatform.v1beta1.DatasetService.ListDatasetVersions].

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

Return type:

google.cloud.aiplatform_v1beta1.services.dataset_service.pagers.ListDatasetVersionsPager

list_datasets(request: Optional[Union[ListDatasetsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → ListDatasetsPager[source]¶

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_v1beta1

def sample_list_datasets():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceClient()

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

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

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

Parameters:

request (Union[google.cloud.aiplatform_v1beta1.types.ListDatasetsRequest, dict]) – The request object. Request message for [DatasetService.ListDatasets][google.cloud.aiplatform.v1beta1.DatasetService.ListDatasets].
parent (str) –
Required. The name of the Dataset’s parent resource. Format: projects/{project}/locations/{location}

This corresponds to the parent field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Response message for: [DatasetService.ListDatasets][google.cloud.aiplatform.v1beta1.DatasetService.ListDatasets].

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

Return type:

google.cloud.aiplatform_v1beta1.services.dataset_service.pagers.ListDatasetsPager

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

Lists information about the supported locations for this service.

Parameters:

request (ListLocationsRequest) – The request object. Request message for ListLocations method.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Response message for ListLocations method.

Return type:

ListLocationsResponse

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

Lists operations that match the specified filter in the request.

Parameters:

request (ListOperationsRequest) – The request object. Request message for ListOperations method.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Response message for ListOperations method.

Return type:

ListOperationsResponse

list_saved_queries(request: Optional[Union[ListSavedQueriesRequest, dict]] = None, *, parent: Optional[str] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → ListSavedQueriesPager[source]¶

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_v1beta1

def sample_list_saved_queries():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceClient()

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

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

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

Parameters:

request (Union[google.cloud.aiplatform_v1beta1.types.ListSavedQueriesRequest, dict]) – The request object. Request message for [DatasetService.ListSavedQueries][google.cloud.aiplatform.v1beta1.DatasetService.ListSavedQueries].
parent (str) –
Required. The resource name of the Dataset to list SavedQueries from. Format: projects/{project}/locations/{location}/datasets/{dataset}

This corresponds to the parent field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Response message for: [DatasetService.ListSavedQueries][google.cloud.aiplatform.v1beta1.DatasetService.ListSavedQueries].

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

Return type:

google.cloud.aiplatform_v1beta1.services.dataset_service.pagers.ListSavedQueriesPager

static parse_annotation_path(path: str) → Dict[str, str][source]¶: Parses a annotation path into its component segments.

static parse_annotation_spec_path(path: str) → Dict[str, str][source]¶: Parses a annotation_spec path into its component segments.

static parse_common_billing_account_path(path: str) → Dict[str, str][source]¶: Parse a billing_account path into its component segments.

static parse_common_folder_path(path: str) → Dict[str, str][source]¶: Parse a folder path into its component segments.

static parse_common_location_path(path: str) → Dict[str, str][source]¶: Parse a location path into its component segments.

static parse_common_organization_path(path: str) → Dict[str, str][source]¶: Parse a organization path into its component segments.

static parse_common_project_path(path: str) → Dict[str, str][source]¶: Parse a project path into its component segments.

static parse_data_item_path(path: str) → Dict[str, str][source]¶: Parses a data_item path into its component segments.

static parse_dataset_path(path: str) → Dict[str, str][source]¶: Parses a dataset path into its component segments.

static parse_dataset_version_path(path: str) → Dict[str, str][source]¶: Parses a dataset_version path into its component segments.

static parse_saved_query_path(path: str) → Dict[str, str][source]¶: Parses a saved_query path into its component segments.

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

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_v1beta1

def sample_restore_dataset_version():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceClient()

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

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

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

    response = operation.result()

    # Handle the response
    print(response)

Parameters:

request (Union[google.cloud.aiplatform_v1beta1.types.RestoreDatasetVersionRequest, dict]) – The request object. Request message for [DatasetService.RestoreDatasetVersion][google.cloud.aiplatform.v1beta1.DatasetService.RestoreDatasetVersion].
name (str) –
Required. The name of the DatasetVersion resource. Format: projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}

This corresponds to the name field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

An object representing a long-running operation.

The result type for the operation will be google.cloud.aiplatform_v1beta1.types.DatasetVersion Describes the dataset version.

Return type:

google.cloud.aiplatform_v1beta1.services.dataset_service.pagers.SearchDataItemsPager

static saved_query_path(project: str, location: str, dataset: str, saved_query: str) → str[source]¶: Returns a fully-qualified saved_query string.

search_data_items(request: Optional[Union[SearchDataItemsRequest, dict]] = None, *, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → SearchDataItemsPager[source]¶

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_v1beta1

def sample_search_data_items():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.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
    for response in page_result:
        print(response)

Parameters:

request (Union[google.cloud.aiplatform_v1beta1.types.SearchDataItemsRequest, dict]) – The request object. Request message for [DatasetService.SearchDataItems][google.cloud.aiplatform.v1beta1.DatasetService.SearchDataItems].
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Response message for: [DatasetService.SearchDataItems][google.cloud.aiplatform.v1beta1.DatasetService.SearchDataItems].

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

Return type:

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

Sets the IAM access control policy on the specified function.

Replaces any existing policy.

Parameters:

request (SetIamPolicyRequest) – The request object. Request message for SetIamPolicy method.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Defines an Identity and Access Management (IAM) policy. It is used to specify access control policies for Cloud Platform resources. A Policy is a collection of bindings. A binding binds one or more members to a single role. Members can be user accounts, service accounts, Google groups, and domains (such as G Suite). A role is a named list of permissions (defined by IAM or configured by users). A binding can optionally specify a condition, which is a logic expression that further constrains the role binding based on attributes about the request and/or target resource.

JSON Example

{
  "bindings": [
    {
      "role": "roles/resourcemanager.organizationAdmin",
      "members": [
        "user:mike@example.com",
        "group:admins@example.com",
        "domain:google.com",
        "serviceAccount:my-project-id@appspot.gserviceaccount.com"
      ]
    },
    {
      "role": "roles/resourcemanager.organizationViewer",
      "members": ["user:eve@example.com"],
      "condition": {
        "title": "expirable access",
        "description": "Does not grant access after Sep 2020",
        "expression": "request.time <
        timestamp('2020-10-01T00:00:00.000Z')",
      }
    }
  ]
}

YAML Example

bindings:
- members:
  - user:mike@example.com
  - group:admins@example.com
  - domain:google.com
  - serviceAccount:my-project-id@appspot.gserviceaccount.com
  role: roles/resourcemanager.organizationAdmin
- members:
  - user:eve@example.com
  role: roles/resourcemanager.organizationViewer
  condition:
    title: expirable access
    description: Does not grant access after Sep 2020
    expression: request.time < timestamp('2020-10-01T00:00:00.000Z')

For a description of IAM and its features, see the IAM developer’s guide.

Return type:

Policy

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

Tests the specified IAM permissions against the IAM access control: policy for a function.

If the function does not exist, this will return an empty set of permissions, not a NOT_FOUND error.

Parameters:

request (TestIamPermissionsRequest) – The request object. Request message for TestIamPermissions method.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

Response message for TestIamPermissions method.

Return type:

TestIamPermissionsResponse

property transport: DatasetServiceTransport¶

Returns the transport used by the client instance.

Returns:

The transport used by the client: instance.

Return type:

DatasetServiceTransport

property universe_domain: str¶

Return the universe domain used by the client instance.

Returns:: The universe domain used by the client instance.
Return type:: str

update_dataset(request: Optional[Union[UpdateDatasetRequest, dict]] = None, *, dataset: Optional[Dataset] = None, update_mask: Optional[FieldMask] = None, retry: Optional[Union[Retry, _MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → Dataset[source]¶

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_v1beta1

def sample_update_dataset():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceClient()

    # Initialize request argument(s)
    dataset = aiplatform_v1beta1.Dataset()
    dataset.display_name = "display_name_value"
    dataset.metadata_schema_uri = "metadata_schema_uri_value"
    dataset.metadata.null_value = "NULL_VALUE"

    request = aiplatform_v1beta1.UpdateDatasetRequest(
        dataset=dataset,
    )

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

    # Handle the response
    print(response)

Parameters:

request (Union[google.cloud.aiplatform_v1beta1.types.UpdateDatasetRequest, dict]) – The request object. Request message for [DatasetService.UpdateDataset][google.cloud.aiplatform.v1beta1.DatasetService.UpdateDataset].
dataset (google.cloud.aiplatform_v1beta1.types.Dataset) –
Required. The Dataset which replaces the resource on the server.

This corresponds to the dataset field on the request instance; if request is provided, this should not be set.
update_mask (google.protobuf.field_mask_pb2.FieldMask) –
Required. The update mask applies to the resource. For the FieldMask definition, see [google.protobuf.FieldMask][google.protobuf.FieldMask]. Updatable fields:
- display_name
- description
- labels
This corresponds to the update_mask field on the request instance; if request is provided, this should not be set.
retry (google.api_core.retry.Retry) – Designation of what errors, if any, should be retried.
timeout (float) – The timeout for this request.
metadata (Sequence[Tuple[str, str]]) – Strings which should be sent along with the request as metadata.

Returns:

A collection of DataItems and Annotations on them.

Return type: