Class DatasetServiceClient (1.48.0) 

DatasetServiceClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.aiplatform_v1.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>)

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

Properties

api_endpoint

Return the API endpoint used by the client instance.

Returns
Type Description
str The API endpoint used by the client instance.

transport

Returns the transport used by the client instance.

Returns
Type Description
DatasetServiceTransport The transport used by the client instance.

universe_domain

Return the universe domain used by the client instance.

Returns
Type Description
str The universe domain used by the client instance.

Methods

DatasetServiceClient

DatasetServiceClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.aiplatform_v1.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>)

Instantiates the dataset service client.

Parameters
Name Description
credentials Optional[google.auth.credentials.Credentials]

The authorization credentials to attach to requests. These credentials identify the application to the service; if none are specified, the client will attempt to ascertain the credentials from the environment.
transport Union[str, DatasetServiceTransport]

The transport to use. If set to None, a transport is chosen automatically. NOTE: "rest" transport functionality is currently in a beta state (preview). We welcome your feedback via an issue in this library's source repository.
client_options Optional[Union[google.api_core.client_options.ClientOptions, dict]]

Custom options for the client. 1. The api_endpoint property can be used to override the default endpoint provided by the client when transport is not explicitly provided. Only if this property is not set and transport was not explicitly provided, the endpoint is determined by the GOOGLE_API_USE_MTLS_ENDPOINT environment variable, which have one of the following values: "always" (always use the default mTLS endpoint), "never" (always use the default regular endpoint) and "auto" (auto-switch to the default mTLS endpoint if client certificate is present; this is the default value). 2. If the GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is "true", then the client_cert_source property can be used to provide a client certificate for mTLS transport. If not provided, the default SSL client certificate will be used if present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is "false" or not set, no client certificate will be used. 3. The universe_domain property can be used to override the default "googleapis.com" universe. Note that the api_endpoint property still takes precedence; and universe_domain is currently not supported for mTLS.
client_info google.api_core.gapic_v1.client_info.ClientInfo

The client info used to send a user-agent string along with API requests. If None, then default info will be used. Generally, you only need to set this if you're developing your own client library.
Exceptions
Type Description
google.auth.exceptions.MutualTLSChannelError If mutual TLS transport creation failed for any reason.

__exit__

__exit__(type, value, traceback)

Releases underlying transport's resources.

annotation_path

annotation_path(
    project: str, location: str, dataset: str, data_item: str, annotation: str
) -> str

Returns a fully-qualified annotation string.

annotation_spec_path

annotation_spec_path(
    project: str, location: str, dataset: str, annotation_spec: str
) -> str

Returns a fully-qualified annotation_spec string.

cancel_operation

cancel_operation(
    request: typing.Optional[
        google.longrunning.operations_pb2.CancelOperationRequest
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> None

Starts asynchronous cancellation on a long-running operation.

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

Parameters
Name Description
request .operations_pb2.CancelOperationRequest

The request object. Request message for CancelOperation method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

common_billing_account_path

common_billing_account_path(billing_account: str) -> str

Returns a fully-qualified billing_account string.

common_folder_path

common_folder_path(folder: str) -> str

Returns a fully-qualified folder string.

common_location_path

common_location_path(project: str, location: str) -> str

Returns a fully-qualified location string.

common_organization_path

common_organization_path(organization: str) -> str

Returns a fully-qualified organization string.

common_project_path

common_project_path(project: str) -> str

Returns a fully-qualified project string.

create_dataset

create_dataset(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.dataset_service.CreateDatasetRequest, dict
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    dataset: typing.Optional[google.cloud.aiplatform_v1.types.dataset.Dataset] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation

Creates a Dataset.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_create_dataset():
    # Create a client
    client = aiplatform_v1.DatasetServiceClient()

    # Initialize request argument(s)
    dataset = aiplatform_v1.Dataset()
    dataset.display_name = "display_name_value"
    dataset.metadata_schema_uri = "metadata_schema_uri_value"
    dataset.metadata.null_value = "NULL_VALUE"

    request = aiplatform_v1.CreateDatasetRequest(
        parent="parent_value",
        dataset=dataset,
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.CreateDatasetRequest, dict]

The request object. Request message for 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_v1.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
Type Description
google.api_core.operation.Operation An object representing a long-running operation. The result type for the operation will be Dataset A collection of DataItems and Annotations on them.

create_dataset_version

create_dataset_version(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.dataset_service.CreateDatasetVersionRequest,
            dict,
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    dataset_version: typing.Optional[
        google.cloud.aiplatform_v1.types.dataset_version.DatasetVersion
    ] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation

Create a version from a Dataset.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_create_dataset_version():
    # Create a client
    client = aiplatform_v1.DatasetServiceClient()

    # Initialize request argument(s)
    dataset_version = aiplatform_v1.DatasetVersion()
    dataset_version.metadata.null_value = "NULL_VALUE"

    request = aiplatform_v1.CreateDatasetVersionRequest(
        parent="parent_value",
        dataset_version=dataset_version,
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.CreateDatasetVersionRequest, dict]

The request object. Request message for 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_v1.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
Type Description
google.api_core.operation.Operation An object representing a long-running operation. The result type for the operation will be DatasetVersion Describes the dataset version.

data_item_path

data_item_path(project: str, location: str, dataset: str, data_item: str) -> str

Returns a fully-qualified data_item string.

dataset_path

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

Returns a fully-qualified dataset string.

dataset_version_path

dataset_version_path(
    project: str, location: str, dataset: str, dataset_version: str
) -> str

Returns a fully-qualified dataset_version string.

delete_dataset

delete_dataset(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.dataset_service.DeleteDatasetRequest, dict
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation

Deletes a Dataset.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_delete_dataset():
    # Create a client
    client = aiplatform_v1.DatasetServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.DeleteDatasetRequest(
        name="name_value",
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.DeleteDatasetRequest, dict]

The request object. Request message for 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
Type Description
google.api_core.operation.Operation An object representing a long-running operation. The result type for the operation will be google.protobuf.empty_pb2.Empty A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }

delete_dataset_version

delete_dataset_version(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.dataset_service.DeleteDatasetVersionRequest,
            dict,
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation

Deletes a Dataset version.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_delete_dataset_version():
    # Create a client
    client = aiplatform_v1.DatasetServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.DeleteDatasetVersionRequest(
        name="name_value",
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.DeleteDatasetVersionRequest, dict]

The request object. Request message for 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
Type Description
google.api_core.operation.Operation An object representing a long-running operation. The result type for the operation will be google.protobuf.empty_pb2.Empty A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }

delete_operation

delete_operation(
    request: typing.Optional[
        google.longrunning.operations_pb2.DeleteOperationRequest
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> None

Deletes a long-running operation.

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

Parameters
Name Description
request .operations_pb2.DeleteOperationRequest

The request object. Request message for DeleteOperation method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

delete_saved_query

delete_saved_query(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.dataset_service.DeleteSavedQueryRequest,
            dict,
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation

Deletes a SavedQuery.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_delete_saved_query():
    # Create a client
    client = aiplatform_v1.DatasetServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.DeleteSavedQueryRequest(
        name="name_value",
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.DeleteSavedQueryRequest, dict]

The request object. Request message for 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
Type Description
google.api_core.operation.Operation An object representing a long-running operation. The result type for the operation will be google.protobuf.empty_pb2.Empty A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }

export_data

export_data(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.dataset_service.ExportDataRequest, dict
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    export_config: typing.Optional[
        google.cloud.aiplatform_v1.types.dataset.ExportDataConfig
    ] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation

Exports data from a Dataset.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_export_data():
    # Create a client
    client = aiplatform_v1.DatasetServiceClient()

    # Initialize request argument(s)
    export_config = aiplatform_v1.ExportDataConfig()
    export_config.gcs_destination.output_uri_prefix = "output_uri_prefix_value"

    request = aiplatform_v1.ExportDataRequest(
        name="name_value",
        export_config=export_config,
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.ExportDataRequest, dict]

The request object. Request message for 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_v1.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
Type Description
google.api_core.operation.Operation An object representing a long-running operation. The result type for the operation will be ExportDataResponse Response message for DatasetService.ExportData.

from_service_account_file

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

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

Parameter
Name Description
filename str

The path to the service account private key json file.
Returns
Type Description
DatasetServiceClient The constructed client.

from_service_account_info

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

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

Parameter
Name Description
info dict

The service account private key info.
Returns
Type Description
DatasetServiceClient The constructed client.

from_service_account_json

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

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

Parameter
Name Description
filename str

The path to the service account private key json file.
Returns
Type Description
DatasetServiceClient The constructed client.

get_annotation_spec

get_annotation_spec(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.dataset_service.GetAnnotationSpecRequest,
            dict,
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.annotation_spec.AnnotationSpec

Gets an AnnotationSpec.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_get_annotation_spec():
    # Create a client
    client = aiplatform_v1.DatasetServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.GetAnnotationSpecRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.GetAnnotationSpecRequest, dict]

The request object. Request message for 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
Type Description
google.cloud.aiplatform_v1.types.AnnotationSpec Identifies a concept with which DataItems may be annotated with.

get_dataset

get_dataset(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.dataset_service.GetDatasetRequest, dict
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.dataset.Dataset

Gets a Dataset.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_get_dataset():
    # Create a client
    client = aiplatform_v1.DatasetServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.GetDatasetRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.GetDatasetRequest, dict]

The request object. Request message for 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
Type Description
google.cloud.aiplatform_v1.types.Dataset A collection of DataItems and Annotations on them.

get_dataset_version

get_dataset_version(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.dataset_service.GetDatasetVersionRequest,
            dict,
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.dataset_version.DatasetVersion

Gets a Dataset version.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_get_dataset_version():
    # Create a client
    client = aiplatform_v1.DatasetServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.GetDatasetVersionRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.GetDatasetVersionRequest, dict]

The request object. Request message for 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
Type Description
google.cloud.aiplatform_v1.types.DatasetVersion Describes the dataset version.

get_iam_policy

get_iam_policy(
    request: typing.Optional[google.iam.v1.iam_policy_pb2.GetIamPolicyRequest] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.iam.v1.policy_pb2.Policy

Gets the IAM access control policy for a function.

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

Parameters
Name Description
request .iam_policy_pb2.GetIamPolicyRequest

The request object. Request message for GetIamPolicy method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
.policy_pb2.Policy Defines an Identity and Access Management (IAM) policy. It is used to specify access control policies for Cloud Platform resources. A Policy is a collection of bindings. A binding binds one or more members to a single role. Members can be user accounts, service accounts, Google groups, and domains (such as G Suite). A role is a named list of permissions (defined by IAM or configured by users). A binding can optionally specify a condition, which is a logic expression that further constrains the role binding based on attributes about the request and/or target resource. **JSON Example** :: { "bindings": [ { "role": "roles/resourcemanager.organizationAdmin", "members": [ "user:mike@example.com", "group:admins@example.com", "domain:google.com", "serviceAccount:my-project-id@appspot.gserviceaccount.com" ] }, { "role": "roles/resourcemanager.organizationViewer", "members": ["user:eve@example.com"], "condition": { "title": "expirable access", "description": "Does not grant access after Sep 2020", "expression": "request.time < timestamp('2020-10-01t00:00:00.000z')",="" }="" }="" ]="" }="" **yaml="" example**="" ::="" bindings:="" -="" members:="" -="" user:mike@example.com="" -="" group:admins@example.com="" -="" domain:google.com="" -="" serviceaccount:my-project-id@appspot.gserviceaccount.com="" role:="" roles/resourcemanager.organizationadmin="" -="" members:="" -="" user:eve@example.com="" role:="" roles/resourcemanager.organizationviewer="" condition:="" title:="" expirable="" access="" description:="" does="" not="" grant="" access="" after="" sep="" 2020="" expression:="" request.time="">< timestamp('2020-10-01t00:00:00.000z')="" for="" a="" description="" of="" iam="" and="" its="" features,="" see="" the="">IAM developer's guide __.

get_location

get_location(
    request: typing.Optional[
        google.cloud.location.locations_pb2.GetLocationRequest
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.location.locations_pb2.Location

Gets information about a location.

Parameters
Name Description
request .location_pb2.GetLocationRequest

The request object. Request message for GetLocation method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
.location_pb2.Location Location object.

get_mtls_endpoint_and_cert_source

get_mtls_endpoint_and_cert_source(
    client_options: typing.Optional[
        google.api_core.client_options.ClientOptions
    ] = None,
)

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

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

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

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

Parameter
Name Description
client_options google.api_core.client_options.ClientOptions

Custom options for the client. Only the api_endpoint and client_cert_source properties may be used in this method.
Exceptions
Type Description
google.auth.exceptions.MutualTLSChannelError If any errors happen.
Returns
Type Description
Tuple[str, Callable[[], Tuple[bytes, bytes]]] returns the API endpoint and the client cert source to use.

get_operation

get_operation(
    request: typing.Optional[
        google.longrunning.operations_pb2.GetOperationRequest
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.longrunning.operations_pb2.Operation

Gets the latest state of a long-running operation.

Parameters
Name Description
request .operations_pb2.GetOperationRequest

The request object. Request message for GetOperation method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
.operations_pb2.Operation An Operation object.

import_data

import_data(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.dataset_service.ImportDataRequest, dict
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    import_configs: typing.Optional[
        typing.MutableSequence[
            google.cloud.aiplatform_v1.types.dataset.ImportDataConfig
        ]
    ] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation

Imports data into a Dataset.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_import_data():
    # Create a client
    client = aiplatform_v1.DatasetServiceClient()

    # Initialize request argument(s)
    import_configs = aiplatform_v1.ImportDataConfig()
    import_configs.gcs_source.uris = ['uris_value1', 'uris_value2']
    import_configs.import_schema_uri = "import_schema_uri_value"

    request = aiplatform_v1.ImportDataRequest(
        name="name_value",
        import_configs=import_configs,
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.ImportDataRequest, dict]

The request object. Request message for 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_v1.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
Type Description
google.api_core.operation.Operation An object representing a long-running operation. The result type for the operation will be ImportDataResponse Response message for DatasetService.ImportData.

list_annotations

list_annotations(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.dataset_service.ListAnnotationsRequest,
            dict,
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.services.dataset_service.pagers.ListAnnotationsPager

Lists Annotations belongs to a dataitem

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_list_annotations():
    # Create a client
    client = aiplatform_v1.DatasetServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.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
Name Description
request Union[google.cloud.aiplatform_v1.types.ListAnnotationsRequest, dict]

The request object. Request message for 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
Type Description
google.cloud.aiplatform_v1.services.dataset_service.pagers.ListAnnotationsPager Response message for DatasetService.ListAnnotations. Iterating over this object will yield results and resolve additional pages automatically.

list_data_items

list_data_items(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.dataset_service.ListDataItemsRequest, dict
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.services.dataset_service.pagers.ListDataItemsPager

Lists DataItems in a Dataset.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_list_data_items():
    # Create a client
    client = aiplatform_v1.DatasetServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.ListDataItemsRequest(
        parent="parent_value",
    )

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

    # Handle the response
    for response in page_result:
        print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.ListDataItemsRequest, dict]

The request object. Request message for 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
Type Description
google.cloud.aiplatform_v1.services.dataset_service.pagers.ListDataItemsPager Response message for DatasetService.ListDataItems. Iterating over this object will yield results and resolve additional pages automatically.

list_dataset_versions

list_dataset_versions(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.dataset_service.ListDatasetVersionsRequest,
            dict,
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> (
    google.cloud.aiplatform_v1.services.dataset_service.pagers.ListDatasetVersionsPager
)

Lists DatasetVersions in a Dataset.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_list_dataset_versions():
    # Create a client
    client = aiplatform_v1.DatasetServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.ListDatasetVersionsRequest(
        parent="parent_value",
    )

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

    # Handle the response
    for response in page_result:
        print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.ListDatasetVersionsRequest, dict]

The request object. Request message for 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
Type Description
google.cloud.aiplatform_v1.services.dataset_service.pagers.ListDatasetVersionsPager Response message for DatasetService.ListDatasetVersions. Iterating over this object will yield results and resolve additional pages automatically.

list_datasets

list_datasets(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.dataset_service.ListDatasetsRequest, dict
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.services.dataset_service.pagers.ListDatasetsPager

Lists Datasets in a Location.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_list_datasets():
    # Create a client
    client = aiplatform_v1.DatasetServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.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
Name Description
request Union[google.cloud.aiplatform_v1.types.ListDatasetsRequest, dict]

The request object. Request message for 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
Type Description
google.cloud.aiplatform_v1.services.dataset_service.pagers.ListDatasetsPager Response message for DatasetService.ListDatasets. Iterating over this object will yield results and resolve additional pages automatically.

list_locations

list_locations(
    request: typing.Optional[
        google.cloud.location.locations_pb2.ListLocationsRequest
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.location.locations_pb2.ListLocationsResponse

Lists information about the supported locations for this service.

Parameters
Name Description
request .location_pb2.ListLocationsRequest

The request object. Request message for ListLocations method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
.location_pb2.ListLocationsResponse Response message for ListLocations method.

list_operations

list_operations(
    request: typing.Optional[
        google.longrunning.operations_pb2.ListOperationsRequest
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.longrunning.operations_pb2.ListOperationsResponse

Lists operations that match the specified filter in the request.

Parameters
Name Description
request .operations_pb2.ListOperationsRequest

The request object. Request message for ListOperations method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
.operations_pb2.ListOperationsResponse Response message for ListOperations method.

list_saved_queries

list_saved_queries(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.dataset_service.ListSavedQueriesRequest,
            dict,
        ]
    ] = None,
    *,
    parent: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.services.dataset_service.pagers.ListSavedQueriesPager

Lists SavedQueries in a Dataset.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_list_saved_queries():
    # Create a client
    client = aiplatform_v1.DatasetServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.ListSavedQueriesRequest(
        parent="parent_value",
    )

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

    # Handle the response
    for response in page_result:
        print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.ListSavedQueriesRequest, dict]

The request object. Request message for 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
Type Description
google.cloud.aiplatform_v1.services.dataset_service.pagers.ListSavedQueriesPager Response message for DatasetService.ListSavedQueries. Iterating over this object will yield results and resolve additional pages automatically.

parse_annotation_path

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

Parses a annotation path into its component segments.

parse_annotation_spec_path

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

Parses a annotation_spec path into its component segments.

parse_common_billing_account_path

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

Parse a billing_account path into its component segments.

parse_common_folder_path

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

Parse a folder path into its component segments.

parse_common_location_path

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

Parse a location path into its component segments.

parse_common_organization_path

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

Parse a organization path into its component segments.

parse_common_project_path

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

Parse a project path into its component segments.

parse_data_item_path

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

Parses a data_item path into its component segments.

parse_dataset_path

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

Parses a dataset path into its component segments.

parse_dataset_version_path

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

Parses a dataset_version path into its component segments.

parse_saved_query_path

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

Parses a saved_query path into its component segments.

restore_dataset_version

restore_dataset_version(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.dataset_service.RestoreDatasetVersionRequest,
            dict,
        ]
    ] = None,
    *,
    name: typing.Optional[str] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.api_core.operation.Operation

Restores a dataset version.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_restore_dataset_version():
    # Create a client
    client = aiplatform_v1.DatasetServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.RestoreDatasetVersionRequest(
        name="name_value",
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.RestoreDatasetVersionRequest, dict]

The request object. Request message for 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
Type Description
google.api_core.operation.Operation An object representing a long-running operation. The result type for the operation will be DatasetVersion Describes the dataset version.

saved_query_path

saved_query_path(
    project: str, location: str, dataset: str, saved_query: str
) -> str

Returns a fully-qualified saved_query string.

search_data_items

search_data_items(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.dataset_service.SearchDataItemsRequest,
            dict,
        ]
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.services.dataset_service.pagers.SearchDataItemsPager

Searches DataItems in a Dataset.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_search_data_items():
    # Create a client
    client = aiplatform_v1.DatasetServiceClient()

    # Initialize request argument(s)
    request = aiplatform_v1.SearchDataItemsRequest(
        order_by_data_item="order_by_data_item_value",
        dataset="dataset_value",
    )

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

    # Handle the response
    for response in page_result:
        print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.SearchDataItemsRequest, dict]

The request object. Request message for 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
Type Description
google.cloud.aiplatform_v1.services.dataset_service.pagers.SearchDataItemsPager Response message for DatasetService.SearchDataItems. Iterating over this object will yield results and resolve additional pages automatically.

set_iam_policy

set_iam_policy(
    request: typing.Optional[google.iam.v1.iam_policy_pb2.SetIamPolicyRequest] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.iam.v1.policy_pb2.Policy

Sets the IAM access control policy on the specified function.

Replaces any existing policy.

Parameters
Name Description
request .iam_policy_pb2.SetIamPolicyRequest

The request object. Request message for SetIamPolicy method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
.policy_pb2.Policy Defines an Identity and Access Management (IAM) policy. It is used to specify access control policies for Cloud Platform resources. A Policy is a collection of bindings. A binding binds one or more members to a single role. Members can be user accounts, service accounts, Google groups, and domains (such as G Suite). A role is a named list of permissions (defined by IAM or configured by users). A binding can optionally specify a condition, which is a logic expression that further constrains the role binding based on attributes about the request and/or target resource. **JSON Example** :: { "bindings": [ { "role": "roles/resourcemanager.organizationAdmin", "members": [ "user:mike@example.com", "group:admins@example.com", "domain:google.com", "serviceAccount:my-project-id@appspot.gserviceaccount.com" ] }, { "role": "roles/resourcemanager.organizationViewer", "members": ["user:eve@example.com"], "condition": { "title": "expirable access", "description": "Does not grant access after Sep 2020", "expression": "request.time < timestamp('2020-10-01t00:00:00.000z')",="" }="" }="" ]="" }="" **yaml="" example**="" ::="" bindings:="" -="" members:="" -="" user:mike@example.com="" -="" group:admins@example.com="" -="" domain:google.com="" -="" serviceaccount:my-project-id@appspot.gserviceaccount.com="" role:="" roles/resourcemanager.organizationadmin="" -="" members:="" -="" user:eve@example.com="" role:="" roles/resourcemanager.organizationviewer="" condition:="" title:="" expirable="" access="" description:="" does="" not="" grant="" access="" after="" sep="" 2020="" expression:="" request.time="">< timestamp('2020-10-01t00:00:00.000z')="" for="" a="" description="" of="" iam="" and="" its="" features,="" see="" the="">IAM developer's guide __.

test_iam_permissions

test_iam_permissions(
    request: typing.Optional[
        google.iam.v1.iam_policy_pb2.TestIamPermissionsRequest
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.iam.v1.iam_policy_pb2.TestIamPermissionsResponse

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

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

Parameters
Name Description
request .iam_policy_pb2.TestIamPermissionsRequest

The request object. Request message for TestIamPermissions method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
.iam_policy_pb2.TestIamPermissionsResponse Response message for TestIamPermissions method.

update_dataset

update_dataset(
    request: typing.Optional[
        typing.Union[
            google.cloud.aiplatform_v1.types.dataset_service.UpdateDatasetRequest, dict
        ]
    ] = None,
    *,
    dataset: typing.Optional[google.cloud.aiplatform_v1.types.dataset.Dataset] = None,
    update_mask: typing.Optional[google.protobuf.field_mask_pb2.FieldMask] = None,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.cloud.aiplatform_v1.types.dataset.Dataset

Updates a Dataset.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import aiplatform_v1

def sample_update_dataset():
    # Create a client
    client = aiplatform_v1.DatasetServiceClient()

    # Initialize request argument(s)
    dataset = aiplatform_v1.Dataset()
    dataset.display_name = "display_name_value"
    dataset.metadata_schema_uri = "metadata_schema_uri_value"
    dataset.metadata.null_value = "NULL_VALUE"

    request = aiplatform_v1.UpdateDatasetRequest(
        dataset=dataset,
    )

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

    # Handle the response
    print(response)
Parameters
Name Description
request Union[google.cloud.aiplatform_v1.types.UpdateDatasetRequest, dict]

The request object. Request message for DatasetService.UpdateDataset.
dataset google.cloud.aiplatform_v1.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
Type Description
google.cloud.aiplatform_v1.types.Dataset A collection of DataItems and Annotations on them.

wait_operation

wait_operation(
    request: typing.Optional[
        google.longrunning.operations_pb2.WaitOperationRequest
    ] = None,
    *,
    retry: typing.Optional[
        typing.Union[
            google.api_core.retry.retry_unary.Retry,
            google.api_core.gapic_v1.method._MethodDefault,
        ]
    ] = _MethodDefault._DEFAULT_VALUE,
    timeout: typing.Union[float, object] = _MethodDefault._DEFAULT_VALUE,
    metadata: typing.Sequence[typing.Tuple[str, str]] = ()
) -> google.longrunning.operations_pb2.Operation

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

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

Parameters
Name Description
request .operations_pb2.WaitOperationRequest

The request object. Request message for WaitOperation method.
retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.
timeout float

The timeout for this request.
metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.
Returns
Type Description
.operations_pb2.Operation An Operation object.