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

DataLabelingService

class google.cloud.datalabeling_v1beta1.services.data_labeling_service.DataLabelingServiceAsyncClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.datalabeling_v1beta1.services.data_labeling_service.transports.base.DataLabelingServiceTransport, typing.Callable[[...], google.cloud.datalabeling_v1beta1.services.data_labeling_service.transports.base.DataLabelingServiceTransport]]] = 'grpc_asyncio', client_options: typing.Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)[source]

Service for the AI Platform Data Labeling API.

Instantiates the data labeling service async client.

Parameters

  • credentials (Optional[google.auth.credentials.Credentials]) – The authorization credentials to attach to requests. These credentials identify the application to the service; if none are specified, the client will attempt to ascertain the credentials from the environment.

  • transport (Optional[Union[str,DataLabelingServiceTransport,Callable[..., DataLabelingServiceTransport]]]) – The transport to use, or a Callable that constructs and returns a new transport to use. If a Callable is given, it will be called with the same set of initialization arguments as used in the DataLabelingServiceTransport constructor. If set to None, a transport is chosen automatically.

  • client_options (Optional[Union[google.api_core.client_options.ClientOptions, dict]]) –

    Custom options for the client.

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

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

    3. The universe_domain property can be used to override the default “googleapis.com” universe. Note that api_endpoint property still takes precedence; and universe_domain is currently not supported for mTLS.

  • client_info (google.api_core.gapic_v1.client_info.ClientInfo) – The client info used to send a user-agent string along with API requests. If None, then default info will be used. Generally, you only need to set this if you’re developing your own client library.

Raises

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

static annotated_dataset_path(project: str, dataset: str, annotated_dataset: str) → str

Returns a fully-qualified annotated_dataset string.

static annotation_spec_set_path(project: str, annotation_spec_set: str) → str

Returns a fully-qualified annotation_spec_set 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

static common_billing_account_path(billing_account: str) → str

Returns a fully-qualified billing_account string.

static common_folder_path(folder: str) → str

Returns a fully-qualified folder string.

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

Returns a fully-qualified location string.

static common_organization_path(organization: str) → str

Returns a fully-qualified organization string.

static common_project_path(project: str) → str

Returns a fully-qualified project string.

async create_annotation_spec_set(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.CreateAnnotationSpecSetRequest, dict]] = None, *, parent: Optional[str] = None, annotation_spec_set: Optional[google.cloud.datalabeling_v1beta1.types.annotation_spec_set.AnnotationSpecSet] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.types.annotation_spec_set.AnnotationSpecSet[source]

Creates an annotation spec set by providing a set of labels.

# 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 datalabeling_v1beta1

async def sample_create_annotation_spec_set():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.CreateAnnotationSpecSetRequest(
        parent="parent_value",
    )

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

    # Handle the response
    print(response)
Parameters

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.CreateAnnotationSpecSetRequest, dict]]) – The request object. Request message for CreateAnnotationSpecSet.

  • parent (str) –

    Required. AnnotationSpecSet resource parent, format: projects/{project_id}

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

  • annotation_spec_set (google.cloud.datalabeling_v1beta1.types.AnnotationSpecSet) –

    Required. Annotation spec set to create. Annotation specs must be included. Only one annotation spec will be accepted for annotation specs with same display_name.

    This corresponds to the annotation_spec_set 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 AnnotationSpecSet is a collection of label definitions. For example, in image classification tasks, you define a set of possible labels for images as an AnnotationSpecSet. An AnnotationSpecSet is immutable upon creation.

Return type

google.cloud.datalabeling_v1beta1.types.AnnotationSpecSet

async create_dataset(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.CreateDatasetRequest, dict]] = None, *, parent: Optional[str] = None, dataset: Optional[google.cloud.datalabeling_v1beta1.types.dataset.Dataset] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.types.dataset.Dataset[source]

Creates dataset. If success return a Dataset resource.

# 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 datalabeling_v1beta1

async def sample_create_dataset():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.CreateDatasetRequest(
        parent="parent_value",
    )

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

    # Handle the response
    print(response)
Parameters

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.CreateDatasetRequest, dict]]) – The request object. Request message for CreateDataset.

  • parent (str) –

    Required. Dataset resource parent, format: projects/{project_id}

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

  • dataset (google.cloud.datalabeling_v1beta1.types.Dataset) – Required. The dataset to be created. This corresponds to the dataset 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

Dataset is the resource to hold your data. You can request multiple labeling tasks for a dataset while each one will generate an AnnotatedDataset.

Return type

google.cloud.datalabeling_v1beta1.types.Dataset

async create_evaluation_job(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.CreateEvaluationJobRequest, dict]] = None, *, parent: Optional[str] = None, job: Optional[google.cloud.datalabeling_v1beta1.types.evaluation_job.EvaluationJob] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.types.evaluation_job.EvaluationJob[source]

Creates an evaluation job.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1

async def sample_create_evaluation_job():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.CreateEvaluationJobRequest(
        parent="parent_value",
    )

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

    # Handle the response
    print(response)
Parameters

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.CreateEvaluationJobRequest, dict]]) – The request object. Request message for CreateEvaluationJob.

  • parent (str) –

    Required. Evaluation job resource parent. Format: “projects/{project_id}”

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

  • job (google.cloud.datalabeling_v1beta1.types.EvaluationJob) –

    Required. The evaluation job to create.

    This corresponds to the job 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

Defines an evaluation job that runs periodically to generate

[Evaluations][google.cloud.datalabeling.v1beta1.Evaluation]. [Creating an evaluation job](/ml-engine/docs/continuous-evaluation/create-job) is the starting point for using continuous evaluation.

Return type

google.cloud.datalabeling_v1beta1.types.EvaluationJob

async create_instruction(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.CreateInstructionRequest, dict]] = None, *, parent: Optional[str] = None, instruction: Optional[google.cloud.datalabeling_v1beta1.types.instruction.Instruction] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.api_core.operation_async.AsyncOperation[source]

Creates an instruction for how data should be labeled.

# 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 datalabeling_v1beta1

async def sample_create_instruction():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.CreateInstructionRequest(
        parent="parent_value",
    )

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

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

    response = (await operation).result()

    # Handle the response
    print(response)
Parameters

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.CreateInstructionRequest, dict]]) – The request object. Request message for CreateInstruction.

  • parent (str) –

    Required. Instruction resource parent, format: projects/{project_id}

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

  • instruction (google.cloud.datalabeling_v1beta1.types.Instruction) –

    Required. Instruction of how to perform the labeling task.

    This corresponds to the instruction 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.datalabeling_v1beta1.types.Instruction Instruction of how to perform the labeling task for human operators.

Currently only PDF instruction is supported.

Return type

google.api_core.operation_async.AsyncOperation

static data_item_path(project: str, dataset: str, data_item: str) → str

Returns a fully-qualified data_item string.

static dataset_path(project: str, dataset: str) → str

Returns a fully-qualified dataset string.

async delete_annotated_dataset(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.DeleteAnnotatedDatasetRequest, dict]] = None, *, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → None[source]

Deletes an annotated dataset by resource name.

# 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 datalabeling_v1beta1

async def sample_delete_annotated_dataset():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.DeleteAnnotatedDatasetRequest(
        name="name_value",
    )

    # Make the request
    await client.delete_annotated_dataset(request=request)
Parameters

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.DeleteAnnotatedDatasetRequest, dict]]) – The request object. Request message for DeleteAnnotatedDataset.

  • 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.

async delete_annotation_spec_set(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.DeleteAnnotationSpecSetRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → None[source]

Deletes an annotation spec set by resource name.

# 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 datalabeling_v1beta1

async def sample_delete_annotation_spec_set():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.DeleteAnnotationSpecSetRequest(
        name="name_value",
    )

    # Make the request
    await client.delete_annotation_spec_set(request=request)
Parameters

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.DeleteAnnotationSpecSetRequest, dict]]) – The request object. Request message for DeleteAnnotationSpecSet.

  • name (str) –

    Required. AnnotationSpec resource name, format: projects/{project_id}/annotationSpecSets/{annotation_spec_set_id}.

    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.

async delete_dataset(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.DeleteDatasetRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → None[source]

Deletes a dataset by resource name.

# 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 datalabeling_v1beta1

async def sample_delete_dataset():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.DeleteDatasetRequest(
        name="name_value",
    )

    # Make the request
    await client.delete_dataset(request=request)
Parameters

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.DeleteDatasetRequest, dict]]) – The request object. Request message for DeleteDataset.

  • name (str) –

    Required. Dataset resource name, format: projects/{project_id}/datasets/{dataset_id}

    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.

async delete_evaluation_job(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.DeleteEvaluationJobRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → None[source]

Stops and deletes an evaluation job.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1

async def sample_delete_evaluation_job():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.DeleteEvaluationJobRequest(
        name="name_value",
    )

    # Make the request
    await client.delete_evaluation_job(request=request)
Parameters

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.DeleteEvaluationJobRequest, dict]]) – The request object. Request message DeleteEvaluationJob.

  • name (str) –

    Required. Name of the evaluation job that is going to be deleted. Format:

    ”projects/{project_id}/evaluationJobs/{evaluation_job_id}”

    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.

async delete_instruction(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.DeleteInstructionRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → None[source]

Deletes an instruction object by resource name.

# 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 datalabeling_v1beta1

async def sample_delete_instruction():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.DeleteInstructionRequest(
        name="name_value",
    )

    # Make the request
    await client.delete_instruction(request=request)
Parameters

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.DeleteInstructionRequest, dict]]) – The request object. Request message for DeleteInstruction.

  • name (str) –

    Required. Instruction resource name, format: projects/{project_id}/instructions/{instruction_id}

    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.

static evaluation_job_path(project: str, evaluation_job: str) → str

Returns a fully-qualified evaluation_job string.

static evaluation_path(project: str, dataset: str, evaluation: str) → str

Returns a fully-qualified evaluation string.

static example_path(project: str, dataset: str, annotated_dataset: str, example: str) → str

Returns a fully-qualified example string.

async export_data(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ExportDataRequest, dict]] = None, *, name: Optional[str] = None, annotated_dataset: Optional[str] = None, filter: Optional[str] = None, output_config: Optional[google.cloud.datalabeling_v1beta1.types.dataset.OutputConfig] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.api_core.operation_async.AsyncOperation[source]

Exports data and annotations from 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 datalabeling_v1beta1

async def sample_export_data():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.ExportDataRequest(
        name="name_value",
        annotated_dataset="annotated_dataset_value",
    )

    # 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.datalabeling_v1beta1.types.ExportDataRequest, dict]]) – The request object. Request message for ExportData API.

  • name (str) –

    Required. Dataset resource name, format: projects/{project_id}/datasets/{dataset_id}

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

  • annotated_dataset (str) –

    Required. Annotated dataset resource name. DataItem in Dataset and their annotations in specified annotated dataset will be exported. It’s in format of projects/{project_id}/datasets/{dataset_id}/annotatedDatasets/ {annotated_dataset_id}

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

  • filter (str) –

    Optional. Filter is not supported at this moment.

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

  • output_config (google.cloud.datalabeling_v1beta1.types.OutputConfig) –

    Required. Specify the output destination.

    This corresponds to the output_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.datalabeling_v1beta1.types.ExportDataOperationResponse Response used for ExportDataset longrunning operation.

Return type

google.api_core.operation_async.AsyncOperation

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

DataLabelingServiceAsyncClient

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

DataLabelingServiceAsyncClient

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

DataLabelingServiceAsyncClient

async get_annotated_dataset(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.GetAnnotatedDatasetRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.types.dataset.AnnotatedDataset[source]

Gets an annotated dataset by resource name.

# 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 datalabeling_v1beta1

async def sample_get_annotated_dataset():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.GetAnnotatedDatasetRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)
Parameters

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.GetAnnotatedDatasetRequest, dict]]) – The request object. Request message for GetAnnotatedDataset.

  • name (str) –

    Required. Name of the annotated dataset to get, format: projects/{project_id}/datasets/{dataset_id}/annotatedDatasets/ {annotated_dataset_id}

    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

AnnotatedDataset is a set holding annotations for data in a Dataset. Each labeling task will generate an AnnotatedDataset under the Dataset that the task is requested for.

Return type

google.cloud.datalabeling_v1beta1.types.AnnotatedDataset

async get_annotation_spec_set(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.GetAnnotationSpecSetRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.types.annotation_spec_set.AnnotationSpecSet[source]

Gets an annotation spec set by resource name.

# 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 datalabeling_v1beta1

async def sample_get_annotation_spec_set():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.GetAnnotationSpecSetRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)
Parameters

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.GetAnnotationSpecSetRequest, dict]]) – The request object. Request message for GetAnnotationSpecSet.

  • name (str) –

    Required. AnnotationSpecSet resource name, format: projects/{project_id}/annotationSpecSets/{annotation_spec_set_id}

    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 AnnotationSpecSet is a collection of label definitions. For example, in image classification tasks, you define a set of possible labels for images as an AnnotationSpecSet. An AnnotationSpecSet is immutable upon creation.

Return type

google.cloud.datalabeling_v1beta1.types.AnnotationSpecSet

async get_data_item(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.GetDataItemRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.types.dataset.DataItem[source]

Gets a data item in a dataset by resource name. This API can be called after data are imported into 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 datalabeling_v1beta1

async def sample_get_data_item():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.GetDataItemRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)
Parameters

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.GetDataItemRequest, dict]]) – The request object. Request message for GetDataItem.

  • name (str) –

    Required. The name of the data item to get, format: projects/{project_id}/datasets/{dataset_id}/dataItems/{data_item_id}

    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

DataItem is a piece of data, without annotation. For example, an image.

Return type

google.cloud.datalabeling_v1beta1.types.DataItem

async get_dataset(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.GetDatasetRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.types.dataset.Dataset[source]

Gets dataset by resource name.

# 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 datalabeling_v1beta1

async def sample_get_dataset():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_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.datalabeling_v1beta1.types.GetDatasetRequest, dict]]) – The request object. Request message for GetDataSet.

  • name (str) –

    Required. Dataset resource name, format: projects/{project_id}/datasets/{dataset_id}

    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

Dataset is the resource to hold your data. You can request multiple labeling tasks for a dataset while each one will generate an AnnotatedDataset.

Return type

google.cloud.datalabeling_v1beta1.types.Dataset

async get_evaluation(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.GetEvaluationRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.types.evaluation.Evaluation[source]

Gets an evaluation by resource name (to search, use [projects.evaluations.search][google.cloud.datalabeling.v1beta1.DataLabelingService.SearchEvaluations]).

# 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 datalabeling_v1beta1

async def sample_get_evaluation():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.GetEvaluationRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)
Parameters

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.GetEvaluationRequest, dict]]) – The request object. Request message for GetEvaluation.

  • name (str) –

    Required. Name of the evaluation. Format:

    ”projects/{project_id}/datasets/{dataset_id}/evaluations/{evaluation_id}’

    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 an evaluation between a machine learning model’s predictions and

ground truth labels. Created when an [EvaluationJob][google.cloud.datalabeling.v1beta1.EvaluationJob] runs successfully.

Return type

google.cloud.datalabeling_v1beta1.types.Evaluation

async get_evaluation_job(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.GetEvaluationJobRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.types.evaluation_job.EvaluationJob[source]

Gets an evaluation job by resource name.

# 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 datalabeling_v1beta1

async def sample_get_evaluation_job():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.GetEvaluationJobRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)
Parameters

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.GetEvaluationJobRequest, dict]]) – The request object. Request message for GetEvaluationJob.

  • name (str) –

    Required. Name of the evaluation job. Format:

    ”projects/{project_id}/evaluationJobs/{evaluation_job_id}”

    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

Defines an evaluation job that runs periodically to generate

[Evaluations][google.cloud.datalabeling.v1beta1.Evaluation]. [Creating an evaluation job](/ml-engine/docs/continuous-evaluation/create-job) is the starting point for using continuous evaluation.

Return type

google.cloud.datalabeling_v1beta1.types.EvaluationJob

async get_example(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.GetExampleRequest, dict]] = None, *, name: Optional[str] = None, filter: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.types.dataset.Example[source]

Gets an example by resource name, including both data and annotation.

# 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 datalabeling_v1beta1

async def sample_get_example():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.GetExampleRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)
Parameters

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.GetExampleRequest, dict]]) – The request object. Request message for GetExample

  • name (str) –

    Required. Name of example, format: projects/{project_id}/datasets/{dataset_id}/annotatedDatasets/ {annotated_dataset_id}/examples/{example_id}

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

  • filter (str) –

    Optional. An expression for filtering Examples. Filter by annotation_spec.display_name is supported. Format “annotation_spec.display_name = {display_name}”

    This corresponds to the filter 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 Example is a piece of data and its annotation. For example, an image with label “house”.

Return type

google.cloud.datalabeling_v1beta1.types.Example

async get_instruction(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.GetInstructionRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.types.instruction.Instruction[source]

Gets an instruction by resource name.

# 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 datalabeling_v1beta1

async def sample_get_instruction():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.GetInstructionRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)
Parameters

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.GetInstructionRequest, dict]]) – The request object. Request message for GetInstruction.

  • name (str) –

    Required. Instruction resource name, format: projects/{project_id}/instructions/{instruction_id}

    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

Instruction of how to perform the labeling task for human operators. Currently only PDF instruction is supported.

Return type

google.cloud.datalabeling_v1beta1.types.Instruction

classmethod get_mtls_endpoint_and_cert_source(client_options: Optional[google.api_core.client_options.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.

classmethod get_transport_class(label: Optional[str] = None) → Type[google.cloud.datalabeling_v1beta1.services.data_labeling_service.transports.base.DataLabelingServiceTransport]

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[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ImportDataRequest, dict]] = None, *, name: Optional[str] = None, input_config: Optional[google.cloud.datalabeling_v1beta1.types.dataset.InputConfig] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.api_core.operation_async.AsyncOperation[source]

Imports data into dataset based on source locations defined in request. It can be called multiple times for the same dataset. Each dataset can only have one long running operation running on it. For example, no labeling task (also long running operation) can be started while importing is still ongoing. Vice versa.

# 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 datalabeling_v1beta1

async def sample_import_data():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.ImportDataRequest(
        name="name_value",
    )

    # 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.datalabeling_v1beta1.types.ImportDataRequest, dict]]) – The request object. Request message for ImportData API.

  • name (str) –

    Required. Dataset resource name, format: projects/{project_id}/datasets/{dataset_id}

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

  • input_config (google.cloud.datalabeling_v1beta1.types.InputConfig) –

    Required. Specify the input source of the data.

    This corresponds to the input_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.datalabeling_v1beta1.types.ImportDataOperationResponse Response used for ImportData longrunning operation.

Return type

google.api_core.operation_async.AsyncOperation

static instruction_path(project: str, instruction: str) → str

Returns a fully-qualified instruction string.

async label_image(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.LabelImageRequest, dict]] = None, *, parent: Optional[str] = None, basic_config: Optional[google.cloud.datalabeling_v1beta1.types.human_annotation_config.HumanAnnotationConfig] = None, feature: Optional[google.cloud.datalabeling_v1beta1.types.data_labeling_service.LabelImageRequest.Feature] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.api_core.operation_async.AsyncOperation[source]

Starts a labeling task for image. The type of image labeling task is configured by feature in the request.

# 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 datalabeling_v1beta1

async def sample_label_image():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    image_classification_config = datalabeling_v1beta1.ImageClassificationConfig()
    image_classification_config.annotation_spec_set = "annotation_spec_set_value"

    basic_config = datalabeling_v1beta1.HumanAnnotationConfig()
    basic_config.instruction = "instruction_value"
    basic_config.annotated_dataset_display_name = "annotated_dataset_display_name_value"

    request = datalabeling_v1beta1.LabelImageRequest(
        image_classification_config=image_classification_config,
        parent="parent_value",
        basic_config=basic_config,
        feature="SEGMENTATION",
    )

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

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

    response = (await operation).result()

    # Handle the response
    print(response)
Parameters

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.LabelImageRequest, dict]]) – The request object. Request message for starting an image labeling task.

  • parent (str) –

    Required. Name of the dataset to request labeling task, format: projects/{project_id}/datasets/{dataset_id}

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

  • basic_config (google.cloud.datalabeling_v1beta1.types.HumanAnnotationConfig) –

    Required. Basic human annotation config.

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

  • feature (google.cloud.datalabeling_v1beta1.types.LabelImageRequest.Feature) –

    Required. The type of image labeling task.

    This corresponds to the feature 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.datalabeling_v1beta1.types.AnnotatedDataset AnnotatedDataset is a set holding annotations for data in a Dataset. Each

labeling task will generate an AnnotatedDataset under the Dataset that the task is requested for.

Return type

google.api_core.operation_async.AsyncOperation

async label_text(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.LabelTextRequest, dict]] = None, *, parent: Optional[str] = None, basic_config: Optional[google.cloud.datalabeling_v1beta1.types.human_annotation_config.HumanAnnotationConfig] = None, feature: Optional[google.cloud.datalabeling_v1beta1.types.data_labeling_service.LabelTextRequest.Feature] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.api_core.operation_async.AsyncOperation[source]

Starts a labeling task for text. The type of text labeling task is configured by feature in the request.

# 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 datalabeling_v1beta1

async def sample_label_text():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    text_classification_config = datalabeling_v1beta1.TextClassificationConfig()
    text_classification_config.annotation_spec_set = "annotation_spec_set_value"

    basic_config = datalabeling_v1beta1.HumanAnnotationConfig()
    basic_config.instruction = "instruction_value"
    basic_config.annotated_dataset_display_name = "annotated_dataset_display_name_value"

    request = datalabeling_v1beta1.LabelTextRequest(
        text_classification_config=text_classification_config,
        parent="parent_value",
        basic_config=basic_config,
        feature="TEXT_ENTITY_EXTRACTION",
    )

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

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

    response = (await operation).result()

    # Handle the response
    print(response)
Parameters

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.LabelTextRequest, dict]]) – The request object. Request message for LabelText.

  • parent (str) –

    Required. Name of the data set to request labeling task, format: projects/{project_id}/datasets/{dataset_id}

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

  • basic_config (google.cloud.datalabeling_v1beta1.types.HumanAnnotationConfig) –

    Required. Basic human annotation config.

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

  • feature (google.cloud.datalabeling_v1beta1.types.LabelTextRequest.Feature) –

    Required. The type of text labeling task.

    This corresponds to the feature 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.datalabeling_v1beta1.types.AnnotatedDataset AnnotatedDataset is a set holding annotations for data in a Dataset. Each

labeling task will generate an AnnotatedDataset under the Dataset that the task is requested for.

Return type

google.api_core.operation_async.AsyncOperation

async label_video(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.LabelVideoRequest, dict]] = None, *, parent: Optional[str] = None, basic_config: Optional[google.cloud.datalabeling_v1beta1.types.human_annotation_config.HumanAnnotationConfig] = None, feature: Optional[google.cloud.datalabeling_v1beta1.types.data_labeling_service.LabelVideoRequest.Feature] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.api_core.operation_async.AsyncOperation[source]

Starts a labeling task for video. The type of video labeling task is configured by feature in the request.

# 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 datalabeling_v1beta1

async def sample_label_video():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    video_classification_config = datalabeling_v1beta1.VideoClassificationConfig()
    video_classification_config.annotation_spec_set_configs.annotation_spec_set = "annotation_spec_set_value"

    basic_config = datalabeling_v1beta1.HumanAnnotationConfig()
    basic_config.instruction = "instruction_value"
    basic_config.annotated_dataset_display_name = "annotated_dataset_display_name_value"

    request = datalabeling_v1beta1.LabelVideoRequest(
        video_classification_config=video_classification_config,
        parent="parent_value",
        basic_config=basic_config,
        feature="EVENT",
    )

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

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

    response = (await operation).result()

    # Handle the response
    print(response)
Parameters

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.LabelVideoRequest, dict]]) – The request object. Request message for LabelVideo.

  • parent (str) –

    Required. Name of the dataset to request labeling task, format: projects/{project_id}/datasets/{dataset_id}

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

  • basic_config (google.cloud.datalabeling_v1beta1.types.HumanAnnotationConfig) –

    Required. Basic human annotation config.

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

  • feature (google.cloud.datalabeling_v1beta1.types.LabelVideoRequest.Feature) –

    Required. The type of video labeling task.

    This corresponds to the feature 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.datalabeling_v1beta1.types.AnnotatedDataset AnnotatedDataset is a set holding annotations for data in a Dataset. Each

labeling task will generate an AnnotatedDataset under the Dataset that the task is requested for.

Return type

google.api_core.operation_async.AsyncOperation

async list_annotated_datasets(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListAnnotatedDatasetsRequest, dict]] = None, *, parent: Optional[str] = None, filter: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListAnnotatedDatasetsAsyncPager[source]

Lists annotated datasets for a dataset. Pagination is supported.

# 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 datalabeling_v1beta1

async def sample_list_annotated_datasets():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.ListAnnotatedDatasetsRequest(
        parent="parent_value",
    )

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

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

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.ListAnnotatedDatasetsRequest, dict]]) – The request object. Request message for ListAnnotatedDatasets.

  • parent (str) –

    Required. Name of the dataset to list annotated datasets, format: projects/{project_id}/datasets/{dataset_id}

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

  • filter (str) –

    Optional. Filter is not supported at this moment.

    This corresponds to the filter 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

Results of listing annotated datasets for a dataset. Iterating over this object will yield results and resolve additional pages automatically.

Return type

google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListAnnotatedDatasetsAsyncPager

async list_annotation_spec_sets(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListAnnotationSpecSetsRequest, dict]] = None, *, parent: Optional[str] = None, filter: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListAnnotationSpecSetsAsyncPager[source]

Lists annotation spec sets for a project. Pagination is supported.

# 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 datalabeling_v1beta1

async def sample_list_annotation_spec_sets():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.ListAnnotationSpecSetsRequest(
        parent="parent_value",
    )

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

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

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.ListAnnotationSpecSetsRequest, dict]]) – The request object. Request message for ListAnnotationSpecSets.

  • parent (str) –

    Required. Parent of AnnotationSpecSet resource, format: projects/{project_id}

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

  • filter (str) –

    Optional. Filter is not supported at this moment.

    This corresponds to the filter 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

Results of listing annotation spec set under a project. Iterating over this object will yield results and resolve additional pages automatically.

Return type

google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListAnnotationSpecSetsAsyncPager

async list_data_items(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListDataItemsRequest, dict]] = None, *, parent: Optional[str] = None, filter: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListDataItemsAsyncPager[source]

Lists data items in a dataset. This API can be called after data are imported into dataset. Pagination is supported.

# 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 datalabeling_v1beta1

async def sample_list_data_items():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_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.datalabeling_v1beta1.types.ListDataItemsRequest, dict]]) – The request object. Request message for ListDataItems.

  • parent (str) –

    Required. Name of the dataset to list data items, format: projects/{project_id}/datasets/{dataset_id}

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

  • filter (str) –

    Optional. Filter is not supported at this moment.

    This corresponds to the filter 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

Results of listing data items in a dataset. Iterating over this object will yield results and resolve additional pages automatically.

Return type

google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListDataItemsAsyncPager

async list_datasets(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListDatasetsRequest, dict]] = None, *, parent: Optional[str] = None, filter: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListDatasetsAsyncPager[source]

Lists datasets under a project. Pagination is supported.

# 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 datalabeling_v1beta1

async def sample_list_datasets():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_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.datalabeling_v1beta1.types.ListDatasetsRequest, dict]]) – The request object. Request message for ListDataset.

  • parent (str) –

    Required. Dataset resource parent, format: projects/{project_id}

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

  • filter (str) –

    Optional. Filter on dataset is not supported at this moment.

    This corresponds to the filter 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

Results of listing datasets within a project. Iterating over this object will yield results and resolve additional pages automatically.

Return type

google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListDatasetsAsyncPager

async list_evaluation_jobs(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListEvaluationJobsRequest, dict]] = None, *, parent: Optional[str] = None, filter: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListEvaluationJobsAsyncPager[source]

Lists all evaluation jobs within a project with possible filters. Pagination is supported.

# 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 datalabeling_v1beta1

async def sample_list_evaluation_jobs():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.ListEvaluationJobsRequest(
        parent="parent_value",
    )

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

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

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.ListEvaluationJobsRequest, dict]]) – The request object. Request message for ListEvaluationJobs.

  • parent (str) –

    Required. Evaluation job resource parent. Format: “projects/{project_id}”

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

  • filter (str) –

    Optional. You can filter the jobs to list by model_id (also known as model_name, as described in [EvaluationJob.modelVersion][google.cloud.datalabeling.v1beta1.EvaluationJob.model_version]) or by evaluation job state (as described in [EvaluationJob.state][google.cloud.datalabeling.v1beta1.EvaluationJob.state]). To filter by both criteria, use the AND operator or the OR operator. For example, you can use the following string for your filter: “evaluationjob.model_id = {model_name} AND evaluationjob.state = {evaluation_job_state}”

    This corresponds to the filter 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

Results for listing evaluation jobs.

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

Return type

google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListEvaluationJobsAsyncPager

async list_examples(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListExamplesRequest, dict]] = None, *, parent: Optional[str] = None, filter: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListExamplesAsyncPager[source]

Lists examples in an annotated dataset. Pagination is supported.

# 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 datalabeling_v1beta1

async def sample_list_examples():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.ListExamplesRequest(
        parent="parent_value",
    )

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

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

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.ListExamplesRequest, dict]]) – The request object. Request message for ListExamples.

  • parent (str) – Required. Example resource parent. This corresponds to the parent field on the request instance; if request is provided, this should not be set.

  • filter (str) –

    Optional. An expression for filtering Examples. For annotated datasets that have annotation spec set, filter by annotation_spec.display_name is supported. Format “annotation_spec.display_name = {display_name}”

    This corresponds to the filter 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

Results of listing Examples in and annotated dataset. Iterating over this object will yield results and resolve additional pages automatically.

Return type

google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListExamplesAsyncPager

async list_instructions(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListInstructionsRequest, dict]] = None, *, parent: Optional[str] = None, filter: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListInstructionsAsyncPager[source]

Lists instructions for a project. Pagination is supported.

# 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 datalabeling_v1beta1

async def sample_list_instructions():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.ListInstructionsRequest(
        parent="parent_value",
    )

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

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

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.ListInstructionsRequest, dict]]) – The request object. Request message for ListInstructions.

  • parent (str) –

    Required. Instruction resource parent, format: projects/{project_id}

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

  • filter (str) –

    Optional. Filter is not supported at this moment.

    This corresponds to the filter 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

Results of listing instructions under a project. Iterating over this object will yield results and resolve additional pages automatically.

Return type

google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListInstructionsAsyncPager

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

Parses a annotated_dataset path into its component segments.

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

Parses a annotation_spec_set 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_evaluation_job_path(path: str) → Dict[str, str]

Parses a evaluation_job path into its component segments.

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

Parses a evaluation path into its component segments.

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

Parses a example path into its component segments.

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

Parses a instruction path into its component segments.

async pause_evaluation_job(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.PauseEvaluationJobRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → None[source]

Pauses an evaluation job. Pausing an evaluation job that is already in a PAUSED state is a no-op.

# 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 datalabeling_v1beta1

async def sample_pause_evaluation_job():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.PauseEvaluationJobRequest(
        name="name_value",
    )

    # Make the request
    await client.pause_evaluation_job(request=request)
Parameters

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.PauseEvaluationJobRequest, dict]]) – The request object. Request message for PauseEvaluationJob.

  • name (str) –

    Required. Name of the evaluation job that is going to be paused. Format:

    ”projects/{project_id}/evaluationJobs/{evaluation_job_id}”

    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.

async resume_evaluation_job(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ResumeEvaluationJobRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → None[source]

Resumes a paused evaluation job. A deleted evaluation job can’t be resumed. Resuming a running or scheduled evaluation job is a no-op.

# 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 datalabeling_v1beta1

async def sample_resume_evaluation_job():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.ResumeEvaluationJobRequest(
        name="name_value",
    )

    # Make the request
    await client.resume_evaluation_job(request=request)
Parameters

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.ResumeEvaluationJobRequest, dict]]) – The request object. Request message ResumeEvaluationJob.

  • name (str) –

    Required. Name of the evaluation job that is going to be resumed. Format:

    ”projects/{project_id}/evaluationJobs/{evaluation_job_id}”

    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.

async search_evaluations(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.SearchEvaluationsRequest, dict]] = None, *, parent: Optional[str] = None, filter: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.SearchEvaluationsAsyncPager[source]

Searches [evaluations][google.cloud.datalabeling.v1beta1.Evaluation] within a project.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1

async def sample_search_evaluations():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.SearchEvaluationsRequest(
        parent="parent_value",
    )

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

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

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.SearchEvaluationsRequest, dict]]) – The request object. Request message for SearchEvaluation.

  • parent (str) –

    Required. Evaluation search parent (project ID). Format: “projects/{project_id}”

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

  • filter (str) –

    Optional. To search evaluations, you can filter by the following:

    • evaluation_job.evaluation_job_id (the last part of [EvaluationJob.name][google.cloud.datalabeling.v1beta1.EvaluationJob.name])

    • evaluation_job.model_id (the {model_name} portion of [EvaluationJob.modelVersion][google.cloud.datalabeling.v1beta1.EvaluationJob.model_version])

    • evaluation_job.evaluation_job_run_time_start (Minimum threshold for the [evaluationJobRunTime][google.cloud.datalabeling.v1beta1.Evaluation.evaluation_job_run_time] that created the evaluation)

    • evaluation_job.evaluation_job_run_time_end (Maximum threshold for the [evaluationJobRunTime][google.cloud.datalabeling.v1beta1.Evaluation.evaluation_job_run_time] that created the evaluation)

    • evaluation_job.job_state ([EvaluationJob.state][google.cloud.datalabeling.v1beta1.EvaluationJob.state])

    • annotation_spec.display_name (the Evaluation contains a metric for the annotation spec with this [displayName][google.cloud.datalabeling.v1beta1.AnnotationSpec.display_name])

    To filter by multiple critiera, use the AND operator or the OR operator. The following examples shows a string that filters by several critiera:

    ”evaluationjob.evaluation_job_id = {evaluation_job_id} AND evaluationjob.model_id = {model_name} AND evaluationjob.evaluation_job_run_time_start = {timestamp_1} AND evaluationjob.evaluation_job_run_time_end = {timestamp_2} AND annotation_spec.display_name = {display_name}”

    This corresponds to the filter 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

Results of searching evaluations.

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

Return type

google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.SearchEvaluationsAsyncPager

async search_example_comparisons(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.SearchExampleComparisonsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.SearchExampleComparisonsAsyncPager[source]

Searches example comparisons from an evaluation. The return format is a list of example comparisons that show ground truth and prediction(s) for a single input. Search by providing an evaluation ID.

# 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 datalabeling_v1beta1

async def sample_search_example_comparisons():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.SearchExampleComparisonsRequest(
        parent="parent_value",
    )

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

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

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.SearchExampleComparisonsRequest, dict]]) – The request object. Request message of SearchExampleComparisons.

  • parent (str) –

    Required. Name of the [Evaluation][google.cloud.datalabeling.v1beta1.Evaluation] resource to search for example comparisons from. Format:

    ”projects/{project_id}/datasets/{dataset_id}/evaluations/{evaluation_id}”

    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

Results of searching example comparisons. Iterating over this object will yield results and resolve additional pages automatically.

Return type

google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.SearchExampleComparisonsAsyncPager

property transport: google.cloud.datalabeling_v1beta1.services.data_labeling_service.transports.base.DataLabelingServiceTransport

Returns the transport used by the client instance.

Returns

The transport used by the client instance.

Return type

DataLabelingServiceTransport

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_evaluation_job(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.UpdateEvaluationJobRequest, dict]] = None, *, evaluation_job: Optional[google.cloud.datalabeling_v1beta1.types.evaluation_job.EvaluationJob] = None, update_mask: Optional[google.protobuf.field_mask_pb2.FieldMask] = None, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.types.evaluation_job.EvaluationJob[source]

Updates an evaluation job. You can only update certain fields of the job’s [EvaluationJobConfig][google.cloud.datalabeling.v1beta1.EvaluationJobConfig]: humanAnnotationConfig.instruction, exampleCount, and exampleSamplePercentage.

If you want to change any other aspect of the evaluation job, you must delete the job and create a new one.

# 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 datalabeling_v1beta1

async def sample_update_evaluation_job():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceAsyncClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.UpdateEvaluationJobRequest(
    )

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

    # Handle the response
    print(response)
Parameters

  • request (Optional[Union[google.cloud.datalabeling_v1beta1.types.UpdateEvaluationJobRequest, dict]]) – The request object. Request message for UpdateEvaluationJob.

  • evaluation_job (google.cloud.datalabeling_v1beta1.types.EvaluationJob) –

    Required. Evaluation job that is going to be updated.

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

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

    Optional. Mask for which fields to update. You can only provide the following fields:

    • evaluationJobConfig.humanAnnotationConfig.instruction

    • evaluationJobConfig.exampleCount

    • evaluationJobConfig.exampleSamplePercentage

    You can provide more than one of these fields by separating them with commas.

    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

Defines an evaluation job that runs periodically to generate

[Evaluations][google.cloud.datalabeling.v1beta1.Evaluation]. [Creating an evaluation job](/ml-engine/docs/continuous-evaluation/create-job) is the starting point for using continuous evaluation.

Return type

google.cloud.datalabeling_v1beta1.types.EvaluationJob

class google.cloud.datalabeling_v1beta1.services.data_labeling_service.DataLabelingServiceClient(*, credentials: typing.Optional[google.auth.credentials.Credentials] = None, transport: typing.Optional[typing.Union[str, google.cloud.datalabeling_v1beta1.services.data_labeling_service.transports.base.DataLabelingServiceTransport, typing.Callable[[...], google.cloud.datalabeling_v1beta1.services.data_labeling_service.transports.base.DataLabelingServiceTransport]]] = 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]

Service for the AI Platform Data Labeling API.

Instantiates the data labeling 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,DataLabelingServiceTransport,Callable[..., DataLabelingServiceTransport]]]) – 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 DataLabelingServiceTransport 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 annotated_dataset_path(project: str, dataset: str, annotated_dataset: str) → str[source]

Returns a fully-qualified annotated_dataset string.

static annotation_spec_set_path(project: str, annotation_spec_set: str) → str[source]

Returns a fully-qualified annotation_spec_set 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

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_annotation_spec_set(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.CreateAnnotationSpecSetRequest, dict]] = None, *, parent: Optional[str] = None, annotation_spec_set: Optional[google.cloud.datalabeling_v1beta1.types.annotation_spec_set.AnnotationSpecSet] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.types.annotation_spec_set.AnnotationSpecSet[source]

Creates an annotation spec set by providing a set of labels.

# 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 datalabeling_v1beta1

def sample_create_annotation_spec_set():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.CreateAnnotationSpecSetRequest(
        parent="parent_value",
    )

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

    # Handle the response
    print(response)
Parameters

  • request (Union[google.cloud.datalabeling_v1beta1.types.CreateAnnotationSpecSetRequest, dict]) – The request object. Request message for CreateAnnotationSpecSet.

  • parent (str) –

    Required. AnnotationSpecSet resource parent, format: projects/{project_id}

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

  • annotation_spec_set (google.cloud.datalabeling_v1beta1.types.AnnotationSpecSet) –

    Required. Annotation spec set to create. Annotation specs must be included. Only one annotation spec will be accepted for annotation specs with same display_name.

    This corresponds to the annotation_spec_set 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 AnnotationSpecSet is a collection of label definitions. For example, in image classification tasks, you define a set of possible labels for images as an AnnotationSpecSet. An AnnotationSpecSet is immutable upon creation.

Return type

google.cloud.datalabeling_v1beta1.types.AnnotationSpecSet

create_dataset(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.CreateDatasetRequest, dict]] = None, *, parent: Optional[str] = None, dataset: Optional[google.cloud.datalabeling_v1beta1.types.dataset.Dataset] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.types.dataset.Dataset[source]

Creates dataset. If success return a Dataset resource.

# 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 datalabeling_v1beta1

def sample_create_dataset():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.CreateDatasetRequest(
        parent="parent_value",
    )

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

    # Handle the response
    print(response)
Parameters

  • request (Union[google.cloud.datalabeling_v1beta1.types.CreateDatasetRequest, dict]) – The request object. Request message for CreateDataset.

  • parent (str) –

    Required. Dataset resource parent, format: projects/{project_id}

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

  • dataset (google.cloud.datalabeling_v1beta1.types.Dataset) – Required. The dataset to be created. 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

Dataset is the resource to hold your data. You can request multiple labeling tasks for a dataset while each one will generate an AnnotatedDataset.

Return type

google.cloud.datalabeling_v1beta1.types.Dataset

create_evaluation_job(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.CreateEvaluationJobRequest, dict]] = None, *, parent: Optional[str] = None, job: Optional[google.cloud.datalabeling_v1beta1.types.evaluation_job.EvaluationJob] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.types.evaluation_job.EvaluationJob[source]

Creates an evaluation job.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1

def sample_create_evaluation_job():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.CreateEvaluationJobRequest(
        parent="parent_value",
    )

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

    # Handle the response
    print(response)
Parameters

  • request (Union[google.cloud.datalabeling_v1beta1.types.CreateEvaluationJobRequest, dict]) – The request object. Request message for CreateEvaluationJob.

  • parent (str) –

    Required. Evaluation job resource parent. Format: “projects/{project_id}”

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

  • job (google.cloud.datalabeling_v1beta1.types.EvaluationJob) –

    Required. The evaluation job to create.

    This corresponds to the job 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

Defines an evaluation job that runs periodically to generate

[Evaluations][google.cloud.datalabeling.v1beta1.Evaluation]. [Creating an evaluation job](/ml-engine/docs/continuous-evaluation/create-job) is the starting point for using continuous evaluation.

Return type

google.cloud.datalabeling_v1beta1.types.EvaluationJob

create_instruction(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.CreateInstructionRequest, dict]] = None, *, parent: Optional[str] = None, instruction: Optional[google.cloud.datalabeling_v1beta1.types.instruction.Instruction] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.api_core.operation.Operation[source]

Creates an instruction for how data should be labeled.

# 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 datalabeling_v1beta1

def sample_create_instruction():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.CreateInstructionRequest(
        parent="parent_value",
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)
Parameters

  • request (Union[google.cloud.datalabeling_v1beta1.types.CreateInstructionRequest, dict]) – The request object. Request message for CreateInstruction.

  • parent (str) –

    Required. Instruction resource parent, format: projects/{project_id}

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

  • instruction (google.cloud.datalabeling_v1beta1.types.Instruction) –

    Required. Instruction of how to perform the labeling task.

    This corresponds to the instruction 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.datalabeling_v1beta1.types.Instruction Instruction of how to perform the labeling task for human operators.

Currently only PDF instruction is supported.

Return type

google.api_core.operation.Operation

static data_item_path(project: str, dataset: str, data_item: str) → str[source]

Returns a fully-qualified data_item string.

static dataset_path(project: str, dataset: str) → str[source]

Returns a fully-qualified dataset string.

delete_annotated_dataset(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.DeleteAnnotatedDatasetRequest, dict]] = None, *, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → None[source]

Deletes an annotated dataset by resource name.

# 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 datalabeling_v1beta1

def sample_delete_annotated_dataset():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.DeleteAnnotatedDatasetRequest(
        name="name_value",
    )

    # Make the request
    client.delete_annotated_dataset(request=request)
Parameters
delete_annotation_spec_set(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.DeleteAnnotationSpecSetRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → None[source]

Deletes an annotation spec set by resource name.

# 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 datalabeling_v1beta1

def sample_delete_annotation_spec_set():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.DeleteAnnotationSpecSetRequest(
        name="name_value",
    )

    # Make the request
    client.delete_annotation_spec_set(request=request)
Parameters

  • request (Union[google.cloud.datalabeling_v1beta1.types.DeleteAnnotationSpecSetRequest, dict]) – The request object. Request message for DeleteAnnotationSpecSet.

  • name (str) –

    Required. AnnotationSpec resource name, format: projects/{project_id}/annotationSpecSets/{annotation_spec_set_id}.

    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.

delete_dataset(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.DeleteDatasetRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → None[source]

Deletes a dataset by resource name.

# 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 datalabeling_v1beta1

def sample_delete_dataset():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.DeleteDatasetRequest(
        name="name_value",
    )

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

  • request (Union[google.cloud.datalabeling_v1beta1.types.DeleteDatasetRequest, dict]) – The request object. Request message for DeleteDataset.

  • name (str) –

    Required. Dataset resource name, format: projects/{project_id}/datasets/{dataset_id}

    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.

delete_evaluation_job(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.DeleteEvaluationJobRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → None[source]

Stops and deletes an evaluation job.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1

def sample_delete_evaluation_job():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.DeleteEvaluationJobRequest(
        name="name_value",
    )

    # Make the request
    client.delete_evaluation_job(request=request)
Parameters

  • request (Union[google.cloud.datalabeling_v1beta1.types.DeleteEvaluationJobRequest, dict]) – The request object. Request message DeleteEvaluationJob.

  • name (str) –

    Required. Name of the evaluation job that is going to be deleted. Format:

    ”projects/{project_id}/evaluationJobs/{evaluation_job_id}”

    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.

delete_instruction(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.DeleteInstructionRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → None[source]

Deletes an instruction object by resource name.

# 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 datalabeling_v1beta1

def sample_delete_instruction():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.DeleteInstructionRequest(
        name="name_value",
    )

    # Make the request
    client.delete_instruction(request=request)
Parameters

  • request (Union[google.cloud.datalabeling_v1beta1.types.DeleteInstructionRequest, dict]) – The request object. Request message for DeleteInstruction.

  • name (str) –

    Required. Instruction resource name, format: projects/{project_id}/instructions/{instruction_id}

    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.

static evaluation_job_path(project: str, evaluation_job: str) → str[source]

Returns a fully-qualified evaluation_job string.

static evaluation_path(project: str, dataset: str, evaluation: str) → str[source]

Returns a fully-qualified evaluation string.

static example_path(project: str, dataset: str, annotated_dataset: str, example: str) → str[source]

Returns a fully-qualified example string.

export_data(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ExportDataRequest, dict]] = None, *, name: Optional[str] = None, annotated_dataset: Optional[str] = None, filter: Optional[str] = None, output_config: Optional[google.cloud.datalabeling_v1beta1.types.dataset.OutputConfig] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.api_core.operation.Operation[source]

Exports data and annotations from 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 datalabeling_v1beta1

def sample_export_data():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.ExportDataRequest(
        name="name_value",
        annotated_dataset="annotated_dataset_value",
    )

    # 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.datalabeling_v1beta1.types.ExportDataRequest, dict]) – The request object. Request message for ExportData API.

  • name (str) –

    Required. Dataset resource name, format: projects/{project_id}/datasets/{dataset_id}

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

  • annotated_dataset (str) –

    Required. Annotated dataset resource name. DataItem in Dataset and their annotations in specified annotated dataset will be exported. It’s in format of projects/{project_id}/datasets/{dataset_id}/annotatedDatasets/ {annotated_dataset_id}

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

  • filter (str) –

    Optional. Filter is not supported at this moment.

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

  • output_config (google.cloud.datalabeling_v1beta1.types.OutputConfig) –

    Required. Specify the output destination.

    This corresponds to the output_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.datalabeling_v1beta1.types.ExportDataOperationResponse Response used for ExportDataset longrunning operation.

Return type

google.api_core.operation.Operation

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

DataLabelingServiceClient

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

DataLabelingServiceClient

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

DataLabelingServiceClient

get_annotated_dataset(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.GetAnnotatedDatasetRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.types.dataset.AnnotatedDataset[source]

Gets an annotated dataset by resource name.

# 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 datalabeling_v1beta1

def sample_get_annotated_dataset():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.GetAnnotatedDatasetRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)
Parameters

  • request (Union[google.cloud.datalabeling_v1beta1.types.GetAnnotatedDatasetRequest, dict]) – The request object. Request message for GetAnnotatedDataset.

  • name (str) –

    Required. Name of the annotated dataset to get, format: projects/{project_id}/datasets/{dataset_id}/annotatedDatasets/ {annotated_dataset_id}

    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

AnnotatedDataset is a set holding annotations for data in a Dataset. Each labeling task will generate an AnnotatedDataset under the Dataset that the task is requested for.

Return type

google.cloud.datalabeling_v1beta1.types.AnnotatedDataset

get_annotation_spec_set(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.GetAnnotationSpecSetRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.types.annotation_spec_set.AnnotationSpecSet[source]

Gets an annotation spec set by resource name.

# 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 datalabeling_v1beta1

def sample_get_annotation_spec_set():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.GetAnnotationSpecSetRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)
Parameters

  • request (Union[google.cloud.datalabeling_v1beta1.types.GetAnnotationSpecSetRequest, dict]) – The request object. Request message for GetAnnotationSpecSet.

  • name (str) –

    Required. AnnotationSpecSet resource name, format: projects/{project_id}/annotationSpecSets/{annotation_spec_set_id}

    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 AnnotationSpecSet is a collection of label definitions. For example, in image classification tasks, you define a set of possible labels for images as an AnnotationSpecSet. An AnnotationSpecSet is immutable upon creation.

Return type

google.cloud.datalabeling_v1beta1.types.AnnotationSpecSet

get_data_item(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.GetDataItemRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.types.dataset.DataItem[source]

Gets a data item in a dataset by resource name. This API can be called after data are imported into 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 datalabeling_v1beta1

def sample_get_data_item():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.GetDataItemRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)
Parameters

  • request (Union[google.cloud.datalabeling_v1beta1.types.GetDataItemRequest, dict]) – The request object. Request message for GetDataItem.

  • name (str) –

    Required. The name of the data item to get, format: projects/{project_id}/datasets/{dataset_id}/dataItems/{data_item_id}

    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

DataItem is a piece of data, without annotation. For example, an image.

Return type

google.cloud.datalabeling_v1beta1.types.DataItem

get_dataset(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.GetDatasetRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.types.dataset.Dataset[source]

Gets dataset by resource name.

# 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 datalabeling_v1beta1

def sample_get_dataset():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.GetDatasetRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)
Parameters

  • request (Union[google.cloud.datalabeling_v1beta1.types.GetDatasetRequest, dict]) – The request object. Request message for GetDataSet.

  • name (str) –

    Required. Dataset resource name, format: projects/{project_id}/datasets/{dataset_id}

    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

Dataset is the resource to hold your data. You can request multiple labeling tasks for a dataset while each one will generate an AnnotatedDataset.

Return type

google.cloud.datalabeling_v1beta1.types.Dataset

get_evaluation(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.GetEvaluationRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.types.evaluation.Evaluation[source]

Gets an evaluation by resource name (to search, use [projects.evaluations.search][google.cloud.datalabeling.v1beta1.DataLabelingService.SearchEvaluations]).

# 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 datalabeling_v1beta1

def sample_get_evaluation():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.GetEvaluationRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)
Parameters

  • request (Union[google.cloud.datalabeling_v1beta1.types.GetEvaluationRequest, dict]) – The request object. Request message for GetEvaluation.

  • name (str) –

    Required. Name of the evaluation. Format:

    ”projects/{project_id}/datasets/{dataset_id}/evaluations/{evaluation_id}’

    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 an evaluation between a machine learning model’s predictions and

ground truth labels. Created when an [EvaluationJob][google.cloud.datalabeling.v1beta1.EvaluationJob] runs successfully.

Return type

google.cloud.datalabeling_v1beta1.types.Evaluation

get_evaluation_job(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.GetEvaluationJobRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.types.evaluation_job.EvaluationJob[source]

Gets an evaluation job by resource name.

# 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 datalabeling_v1beta1

def sample_get_evaluation_job():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.GetEvaluationJobRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)
Parameters

  • request (Union[google.cloud.datalabeling_v1beta1.types.GetEvaluationJobRequest, dict]) – The request object. Request message for GetEvaluationJob.

  • name (str) –

    Required. Name of the evaluation job. Format:

    ”projects/{project_id}/evaluationJobs/{evaluation_job_id}”

    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

Defines an evaluation job that runs periodically to generate

[Evaluations][google.cloud.datalabeling.v1beta1.Evaluation]. [Creating an evaluation job](/ml-engine/docs/continuous-evaluation/create-job) is the starting point for using continuous evaluation.

Return type

google.cloud.datalabeling_v1beta1.types.EvaluationJob

get_example(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.GetExampleRequest, dict]] = None, *, name: Optional[str] = None, filter: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.types.dataset.Example[source]

Gets an example by resource name, including both data and annotation.

# 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 datalabeling_v1beta1

def sample_get_example():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.GetExampleRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)
Parameters

  • request (Union[google.cloud.datalabeling_v1beta1.types.GetExampleRequest, dict]) – The request object. Request message for GetExample

  • name (str) –

    Required. Name of example, format: projects/{project_id}/datasets/{dataset_id}/annotatedDatasets/ {annotated_dataset_id}/examples/{example_id}

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

  • filter (str) –

    Optional. An expression for filtering Examples. Filter by annotation_spec.display_name is supported. Format “annotation_spec.display_name = {display_name}”

    This corresponds to the filter 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 Example is a piece of data and its annotation. For example, an image with label “house”.

Return type

google.cloud.datalabeling_v1beta1.types.Example

get_instruction(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.GetInstructionRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.types.instruction.Instruction[source]

Gets an instruction by resource name.

# 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 datalabeling_v1beta1

def sample_get_instruction():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.GetInstructionRequest(
        name="name_value",
    )

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

    # Handle the response
    print(response)
Parameters

  • request (Union[google.cloud.datalabeling_v1beta1.types.GetInstructionRequest, dict]) – The request object. Request message for GetInstruction.

  • name (str) –

    Required. Instruction resource name, format: projects/{project_id}/instructions/{instruction_id}

    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

Instruction of how to perform the labeling task for human operators. Currently only PDF instruction is supported.

Return type

google.cloud.datalabeling_v1beta1.types.Instruction

classmethod get_mtls_endpoint_and_cert_source(client_options: Optional[google.api_core.client_options.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.

import_data(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ImportDataRequest, dict]] = None, *, name: Optional[str] = None, input_config: Optional[google.cloud.datalabeling_v1beta1.types.dataset.InputConfig] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.api_core.operation.Operation[source]

Imports data into dataset based on source locations defined in request. It can be called multiple times for the same dataset. Each dataset can only have one long running operation running on it. For example, no labeling task (also long running operation) can be started while importing is still ongoing. Vice versa.

# 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 datalabeling_v1beta1

def sample_import_data():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.ImportDataRequest(
        name="name_value",
    )

    # 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.datalabeling_v1beta1.types.ImportDataRequest, dict]) – The request object. Request message for ImportData API.

  • name (str) –

    Required. Dataset resource name, format: projects/{project_id}/datasets/{dataset_id}

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

  • input_config (google.cloud.datalabeling_v1beta1.types.InputConfig) –

    Required. Specify the input source of the data.

    This corresponds to the input_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.datalabeling_v1beta1.types.ImportDataOperationResponse Response used for ImportData longrunning operation.

Return type

google.api_core.operation.Operation

static instruction_path(project: str, instruction: str) → str[source]

Returns a fully-qualified instruction string.

label_image(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.LabelImageRequest, dict]] = None, *, parent: Optional[str] = None, basic_config: Optional[google.cloud.datalabeling_v1beta1.types.human_annotation_config.HumanAnnotationConfig] = None, feature: Optional[google.cloud.datalabeling_v1beta1.types.data_labeling_service.LabelImageRequest.Feature] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.api_core.operation.Operation[source]

Starts a labeling task for image. The type of image labeling task is configured by feature in the request.

# 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 datalabeling_v1beta1

def sample_label_image():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    image_classification_config = datalabeling_v1beta1.ImageClassificationConfig()
    image_classification_config.annotation_spec_set = "annotation_spec_set_value"

    basic_config = datalabeling_v1beta1.HumanAnnotationConfig()
    basic_config.instruction = "instruction_value"
    basic_config.annotated_dataset_display_name = "annotated_dataset_display_name_value"

    request = datalabeling_v1beta1.LabelImageRequest(
        image_classification_config=image_classification_config,
        parent="parent_value",
        basic_config=basic_config,
        feature="SEGMENTATION",
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)
Parameters
Returns

An object representing a long-running operation.

The result type for the operation will be google.cloud.datalabeling_v1beta1.types.AnnotatedDataset AnnotatedDataset is a set holding annotations for data in a Dataset. Each

labeling task will generate an AnnotatedDataset under the Dataset that the task is requested for.

Return type

google.api_core.operation.Operation

label_text(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.LabelTextRequest, dict]] = None, *, parent: Optional[str] = None, basic_config: Optional[google.cloud.datalabeling_v1beta1.types.human_annotation_config.HumanAnnotationConfig] = None, feature: Optional[google.cloud.datalabeling_v1beta1.types.data_labeling_service.LabelTextRequest.Feature] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.api_core.operation.Operation[source]

Starts a labeling task for text. The type of text labeling task is configured by feature in the request.

# 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 datalabeling_v1beta1

def sample_label_text():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    text_classification_config = datalabeling_v1beta1.TextClassificationConfig()
    text_classification_config.annotation_spec_set = "annotation_spec_set_value"

    basic_config = datalabeling_v1beta1.HumanAnnotationConfig()
    basic_config.instruction = "instruction_value"
    basic_config.annotated_dataset_display_name = "annotated_dataset_display_name_value"

    request = datalabeling_v1beta1.LabelTextRequest(
        text_classification_config=text_classification_config,
        parent="parent_value",
        basic_config=basic_config,
        feature="TEXT_ENTITY_EXTRACTION",
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)
Parameters
Returns

An object representing a long-running operation.

The result type for the operation will be google.cloud.datalabeling_v1beta1.types.AnnotatedDataset AnnotatedDataset is a set holding annotations for data in a Dataset. Each

labeling task will generate an AnnotatedDataset under the Dataset that the task is requested for.

Return type

google.api_core.operation.Operation

label_video(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.LabelVideoRequest, dict]] = None, *, parent: Optional[str] = None, basic_config: Optional[google.cloud.datalabeling_v1beta1.types.human_annotation_config.HumanAnnotationConfig] = None, feature: Optional[google.cloud.datalabeling_v1beta1.types.data_labeling_service.LabelVideoRequest.Feature] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.api_core.operation.Operation[source]

Starts a labeling task for video. The type of video labeling task is configured by feature in the request.

# 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 datalabeling_v1beta1

def sample_label_video():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    video_classification_config = datalabeling_v1beta1.VideoClassificationConfig()
    video_classification_config.annotation_spec_set_configs.annotation_spec_set = "annotation_spec_set_value"

    basic_config = datalabeling_v1beta1.HumanAnnotationConfig()
    basic_config.instruction = "instruction_value"
    basic_config.annotated_dataset_display_name = "annotated_dataset_display_name_value"

    request = datalabeling_v1beta1.LabelVideoRequest(
        video_classification_config=video_classification_config,
        parent="parent_value",
        basic_config=basic_config,
        feature="EVENT",
    )

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

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

    response = operation.result()

    # Handle the response
    print(response)
Parameters
Returns

An object representing a long-running operation.

The result type for the operation will be google.cloud.datalabeling_v1beta1.types.AnnotatedDataset AnnotatedDataset is a set holding annotations for data in a Dataset. Each

labeling task will generate an AnnotatedDataset under the Dataset that the task is requested for.

Return type

google.api_core.operation.Operation

list_annotated_datasets(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListAnnotatedDatasetsRequest, dict]] = None, *, parent: Optional[str] = None, filter: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListAnnotatedDatasetsPager[source]

Lists annotated datasets for a dataset. Pagination is supported.

# 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 datalabeling_v1beta1

def sample_list_annotated_datasets():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.ListAnnotatedDatasetsRequest(
        parent="parent_value",
    )

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

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

  • request (Union[google.cloud.datalabeling_v1beta1.types.ListAnnotatedDatasetsRequest, dict]) – The request object. Request message for ListAnnotatedDatasets.

  • parent (str) –

    Required. Name of the dataset to list annotated datasets, format: projects/{project_id}/datasets/{dataset_id}

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

  • filter (str) –

    Optional. Filter is not supported at this moment.

    This corresponds to the filter 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

Results of listing annotated datasets for a dataset. Iterating over this object will yield results and resolve additional pages automatically.

Return type

google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListAnnotatedDatasetsPager

list_annotation_spec_sets(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListAnnotationSpecSetsRequest, dict]] = None, *, parent: Optional[str] = None, filter: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListAnnotationSpecSetsPager[source]

Lists annotation spec sets for a project. Pagination is supported.

# 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 datalabeling_v1beta1

def sample_list_annotation_spec_sets():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.ListAnnotationSpecSetsRequest(
        parent="parent_value",
    )

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

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

  • request (Union[google.cloud.datalabeling_v1beta1.types.ListAnnotationSpecSetsRequest, dict]) – The request object. Request message for ListAnnotationSpecSets.

  • parent (str) –

    Required. Parent of AnnotationSpecSet resource, format: projects/{project_id}

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

  • filter (str) –

    Optional. Filter is not supported at this moment.

    This corresponds to the filter 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

Results of listing annotation spec set under a project. Iterating over this object will yield results and resolve additional pages automatically.

Return type

google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListAnnotationSpecSetsPager

list_data_items(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListDataItemsRequest, dict]] = None, *, parent: Optional[str] = None, filter: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListDataItemsPager[source]

Lists data items in a dataset. This API can be called after data are imported into dataset. Pagination is supported.

# 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 datalabeling_v1beta1

def sample_list_data_items():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_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.datalabeling_v1beta1.types.ListDataItemsRequest, dict]) – The request object. Request message for ListDataItems.

  • parent (str) –

    Required. Name of the dataset to list data items, format: projects/{project_id}/datasets/{dataset_id}

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

  • filter (str) –

    Optional. Filter is not supported at this moment.

    This corresponds to the filter 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

Results of listing data items in a dataset. Iterating over this object will yield results and resolve additional pages automatically.

Return type

google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListDataItemsPager

list_datasets(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListDatasetsRequest, dict]] = None, *, parent: Optional[str] = None, filter: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListDatasetsPager[source]

Lists datasets under a project. Pagination is supported.

# 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 datalabeling_v1beta1

def sample_list_datasets():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_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.datalabeling_v1beta1.types.ListDatasetsRequest, dict]) – The request object. Request message for ListDataset.

  • parent (str) –

    Required. Dataset resource parent, format: projects/{project_id}

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

  • filter (str) –

    Optional. Filter on dataset is not supported at this moment.

    This corresponds to the filter 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

Results of listing datasets within a project. Iterating over this object will yield results and resolve additional pages automatically.

Return type

google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListDatasetsPager

list_evaluation_jobs(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListEvaluationJobsRequest, dict]] = None, *, parent: Optional[str] = None, filter: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListEvaluationJobsPager[source]

Lists all evaluation jobs within a project with possible filters. Pagination is supported.

# 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 datalabeling_v1beta1

def sample_list_evaluation_jobs():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.ListEvaluationJobsRequest(
        parent="parent_value",
    )

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

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

  • request (Union[google.cloud.datalabeling_v1beta1.types.ListEvaluationJobsRequest, dict]) – The request object. Request message for ListEvaluationJobs.

  • parent (str) –

    Required. Evaluation job resource parent. Format: “projects/{project_id}”

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

  • filter (str) –

    Optional. You can filter the jobs to list by model_id (also known as model_name, as described in [EvaluationJob.modelVersion][google.cloud.datalabeling.v1beta1.EvaluationJob.model_version]) or by evaluation job state (as described in [EvaluationJob.state][google.cloud.datalabeling.v1beta1.EvaluationJob.state]). To filter by both criteria, use the AND operator or the OR operator. For example, you can use the following string for your filter: “evaluationjob.model_id = {model_name} AND evaluationjob.state = {evaluation_job_state}”

    This corresponds to the filter 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

Results for listing evaluation jobs.

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

Return type

google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListEvaluationJobsPager

list_examples(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListExamplesRequest, dict]] = None, *, parent: Optional[str] = None, filter: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListExamplesPager[source]

Lists examples in an annotated dataset. Pagination is supported.

# 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 datalabeling_v1beta1

def sample_list_examples():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.ListExamplesRequest(
        parent="parent_value",
    )

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

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

  • request (Union[google.cloud.datalabeling_v1beta1.types.ListExamplesRequest, dict]) – The request object. Request message for ListExamples.

  • parent (str) – Required. Example resource parent. This corresponds to the parent field on the request instance; if request is provided, this should not be set.

  • filter (str) –

    Optional. An expression for filtering Examples. For annotated datasets that have annotation spec set, filter by annotation_spec.display_name is supported. Format “annotation_spec.display_name = {display_name}”

    This corresponds to the filter 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

Results of listing Examples in and annotated dataset. Iterating over this object will yield results and resolve additional pages automatically.

Return type

google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListExamplesPager

list_instructions(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListInstructionsRequest, dict]] = None, *, parent: Optional[str] = None, filter: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListInstructionsPager[source]

Lists instructions for a project. Pagination is supported.

# 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 datalabeling_v1beta1

def sample_list_instructions():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.ListInstructionsRequest(
        parent="parent_value",
    )

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

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

  • request (Union[google.cloud.datalabeling_v1beta1.types.ListInstructionsRequest, dict]) – The request object. Request message for ListInstructions.

  • parent (str) –

    Required. Instruction resource parent, format: projects/{project_id}

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

  • filter (str) –

    Optional. Filter is not supported at this moment.

    This corresponds to the filter 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

Results of listing instructions under a project. Iterating over this object will yield results and resolve additional pages automatically.

Return type

google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListInstructionsPager

static parse_annotated_dataset_path(path: str) → Dict[str, str][source]

Parses a annotated_dataset path into its component segments.

static parse_annotation_spec_set_path(path: str) → Dict[str, str][source]

Parses a annotation_spec_set 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_evaluation_job_path(path: str) → Dict[str, str][source]

Parses a evaluation_job path into its component segments.

static parse_evaluation_path(path: str) → Dict[str, str][source]

Parses a evaluation path into its component segments.

static parse_example_path(path: str) → Dict[str, str][source]

Parses a example path into its component segments.

static parse_instruction_path(path: str) → Dict[str, str][source]

Parses a instruction path into its component segments.

pause_evaluation_job(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.PauseEvaluationJobRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → None[source]

Pauses an evaluation job. Pausing an evaluation job that is already in a PAUSED state is a no-op.

# 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 datalabeling_v1beta1

def sample_pause_evaluation_job():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.PauseEvaluationJobRequest(
        name="name_value",
    )

    # Make the request
    client.pause_evaluation_job(request=request)
Parameters

  • request (Union[google.cloud.datalabeling_v1beta1.types.PauseEvaluationJobRequest, dict]) – The request object. Request message for PauseEvaluationJob.

  • name (str) –

    Required. Name of the evaluation job that is going to be paused. Format:

    ”projects/{project_id}/evaluationJobs/{evaluation_job_id}”

    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.

resume_evaluation_job(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ResumeEvaluationJobRequest, dict]] = None, *, name: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → None[source]

Resumes a paused evaluation job. A deleted evaluation job can’t be resumed. Resuming a running or scheduled evaluation job is a no-op.

# 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 datalabeling_v1beta1

def sample_resume_evaluation_job():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.ResumeEvaluationJobRequest(
        name="name_value",
    )

    # Make the request
    client.resume_evaluation_job(request=request)
Parameters

  • request (Union[google.cloud.datalabeling_v1beta1.types.ResumeEvaluationJobRequest, dict]) – The request object. Request message ResumeEvaluationJob.

  • name (str) –

    Required. Name of the evaluation job that is going to be resumed. Format:

    ”projects/{project_id}/evaluationJobs/{evaluation_job_id}”

    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.

search_evaluations(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.SearchEvaluationsRequest, dict]] = None, *, parent: Optional[str] = None, filter: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.SearchEvaluationsPager[source]

Searches [evaluations][google.cloud.datalabeling.v1beta1.Evaluation] within a project.

# This snippet has been automatically generated and should be regarded as a
# code template only.
# It will require modifications to work:
# - It may require correct/in-range values for request initialization.
# - It may require specifying regional endpoints when creating the service
#   client as shown in:
#   https://googleapis.dev/python/google-api-core/latest/client_options.html
from google.cloud import datalabeling_v1beta1

def sample_search_evaluations():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.SearchEvaluationsRequest(
        parent="parent_value",
    )

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

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

  • request (Union[google.cloud.datalabeling_v1beta1.types.SearchEvaluationsRequest, dict]) – The request object. Request message for SearchEvaluation.

  • parent (str) –

    Required. Evaluation search parent (project ID). Format: “projects/{project_id}”

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

  • filter (str) –

    Optional. To search evaluations, you can filter by the following:

    • evaluation_job.evaluation_job_id (the last part of [EvaluationJob.name][google.cloud.datalabeling.v1beta1.EvaluationJob.name])

    • evaluation_job.model_id (the {model_name} portion of [EvaluationJob.modelVersion][google.cloud.datalabeling.v1beta1.EvaluationJob.model_version])

    • evaluation_job.evaluation_job_run_time_start (Minimum threshold for the [evaluationJobRunTime][google.cloud.datalabeling.v1beta1.Evaluation.evaluation_job_run_time] that created the evaluation)

    • evaluation_job.evaluation_job_run_time_end (Maximum threshold for the [evaluationJobRunTime][google.cloud.datalabeling.v1beta1.Evaluation.evaluation_job_run_time] that created the evaluation)

    • evaluation_job.job_state ([EvaluationJob.state][google.cloud.datalabeling.v1beta1.EvaluationJob.state])

    • annotation_spec.display_name (the Evaluation contains a metric for the annotation spec with this [displayName][google.cloud.datalabeling.v1beta1.AnnotationSpec.display_name])

    To filter by multiple critiera, use the AND operator or the OR operator. The following examples shows a string that filters by several critiera:

    ”evaluationjob.evaluation_job_id = {evaluation_job_id} AND evaluationjob.model_id = {model_name} AND evaluationjob.evaluation_job_run_time_start = {timestamp_1} AND evaluationjob.evaluation_job_run_time_end = {timestamp_2} AND annotation_spec.display_name = {display_name}”

    This corresponds to the filter 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

Results of searching evaluations.

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

Return type

google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.SearchEvaluationsPager

search_example_comparisons(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.SearchExampleComparisonsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.SearchExampleComparisonsPager[source]

Searches example comparisons from an evaluation. The return format is a list of example comparisons that show ground truth and prediction(s) for a single input. Search by providing an evaluation ID.

# 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 datalabeling_v1beta1

def sample_search_example_comparisons():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.SearchExampleComparisonsRequest(
        parent="parent_value",
    )

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

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

  • request (Union[google.cloud.datalabeling_v1beta1.types.SearchExampleComparisonsRequest, dict]) – The request object. Request message of SearchExampleComparisons.

  • parent (str) –

    Required. Name of the [Evaluation][google.cloud.datalabeling.v1beta1.Evaluation] resource to search for example comparisons from. Format:

    ”projects/{project_id}/datasets/{dataset_id}/evaluations/{evaluation_id}”

    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

Results of searching example comparisons. Iterating over this object will yield results and resolve additional pages automatically.

Return type

google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.SearchExampleComparisonsPager

property transport: google.cloud.datalabeling_v1beta1.services.data_labeling_service.transports.base.DataLabelingServiceTransport

Returns the transport used by the client instance.

Returns

The transport used by the client

instance.

Return type

DataLabelingServiceTransport

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_evaluation_job(request: Optional[Union[google.cloud.datalabeling_v1beta1.types.data_labeling_service.UpdateEvaluationJobRequest, dict]] = None, *, evaluation_job: Optional[google.cloud.datalabeling_v1beta1.types.evaluation_job.EvaluationJob] = None, update_mask: Optional[google.protobuf.field_mask_pb2.FieldMask] = None, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ()) → google.cloud.datalabeling_v1beta1.types.evaluation_job.EvaluationJob[source]

Updates an evaluation job. You can only update certain fields of the job’s [EvaluationJobConfig][google.cloud.datalabeling.v1beta1.EvaluationJobConfig]: humanAnnotationConfig.instruction, exampleCount, and exampleSamplePercentage.

If you want to change any other aspect of the evaluation job, you must delete the job and create a new one.

# 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 datalabeling_v1beta1

def sample_update_evaluation_job():
    # Create a client
    client = datalabeling_v1beta1.DataLabelingServiceClient()

    # Initialize request argument(s)
    request = datalabeling_v1beta1.UpdateEvaluationJobRequest(
    )

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

    # Handle the response
    print(response)
Parameters

  • request (Union[google.cloud.datalabeling_v1beta1.types.UpdateEvaluationJobRequest, dict]) – The request object. Request message for UpdateEvaluationJob.

  • evaluation_job (google.cloud.datalabeling_v1beta1.types.EvaluationJob) –

    Required. Evaluation job that is going to be updated.

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

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

    Optional. Mask for which fields to update. You can only provide the following fields:

    • evaluationJobConfig.humanAnnotationConfig.instruction

    • evaluationJobConfig.exampleCount

    • evaluationJobConfig.exampleSamplePercentage

    You can provide more than one of these fields by separating them with commas.

    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

Defines an evaluation job that runs periodically to generate

[Evaluations][google.cloud.datalabeling.v1beta1.Evaluation]. [Creating an evaluation job](/ml-engine/docs/continuous-evaluation/create-job) is the starting point for using continuous evaluation.

Return type

google.cloud.datalabeling_v1beta1.types.EvaluationJob

class google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListAnnotatedDatasetsAsyncPager(method: Callable[[...], Awaitable[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListAnnotatedDatasetsResponse]], request: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListAnnotatedDatasetsRequest, response: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListAnnotatedDatasetsResponse, *, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through list_annotated_datasets requests.

This class thinly wraps an initial google.cloud.datalabeling_v1beta1.types.ListAnnotatedDatasetsResponse object, and provides an __aiter__ method to iterate through its annotated_datasets field.

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

All the usual google.cloud.datalabeling_v1beta1.types.ListAnnotatedDatasetsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiates the pager.

Parameters
class google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListAnnotatedDatasetsPager(method: Callable[[...], google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListAnnotatedDatasetsResponse], request: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListAnnotatedDatasetsRequest, response: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListAnnotatedDatasetsResponse, *, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through list_annotated_datasets requests.

This class thinly wraps an initial google.cloud.datalabeling_v1beta1.types.ListAnnotatedDatasetsResponse object, and provides an __iter__ method to iterate through its annotated_datasets field.

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

All the usual google.cloud.datalabeling_v1beta1.types.ListAnnotatedDatasetsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiate the pager.

Parameters
class google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListAnnotationSpecSetsAsyncPager(method: Callable[[...], Awaitable[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListAnnotationSpecSetsResponse]], request: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListAnnotationSpecSetsRequest, response: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListAnnotationSpecSetsResponse, *, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through list_annotation_spec_sets requests.

This class thinly wraps an initial google.cloud.datalabeling_v1beta1.types.ListAnnotationSpecSetsResponse object, and provides an __aiter__ method to iterate through its annotation_spec_sets field.

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

All the usual google.cloud.datalabeling_v1beta1.types.ListAnnotationSpecSetsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiates the pager.

Parameters
class google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListAnnotationSpecSetsPager(method: Callable[[...], google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListAnnotationSpecSetsResponse], request: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListAnnotationSpecSetsRequest, response: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListAnnotationSpecSetsResponse, *, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through list_annotation_spec_sets requests.

This class thinly wraps an initial google.cloud.datalabeling_v1beta1.types.ListAnnotationSpecSetsResponse object, and provides an __iter__ method to iterate through its annotation_spec_sets field.

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

All the usual google.cloud.datalabeling_v1beta1.types.ListAnnotationSpecSetsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiate the pager.

Parameters
class google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListDataItemsAsyncPager(method: Callable[[...], Awaitable[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListDataItemsResponse]], request: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListDataItemsRequest, response: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListDataItemsResponse, *, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through list_data_items requests.

This class thinly wraps an initial google.cloud.datalabeling_v1beta1.types.ListDataItemsResponse object, and provides an __aiter__ method to iterate through its data_items field.

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

All the usual google.cloud.datalabeling_v1beta1.types.ListDataItemsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiates the pager.

Parameters
class google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListDataItemsPager(method: Callable[[...], google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListDataItemsResponse], request: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListDataItemsRequest, response: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListDataItemsResponse, *, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through list_data_items requests.

This class thinly wraps an initial google.cloud.datalabeling_v1beta1.types.ListDataItemsResponse object, and provides an __iter__ method to iterate through its data_items field.

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

All the usual google.cloud.datalabeling_v1beta1.types.ListDataItemsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiate the pager.

Parameters
class google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListDatasetsAsyncPager(method: Callable[[...], Awaitable[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListDatasetsResponse]], request: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListDatasetsRequest, response: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListDatasetsResponse, *, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through list_datasets requests.

This class thinly wraps an initial google.cloud.datalabeling_v1beta1.types.ListDatasetsResponse object, and provides an __aiter__ method to iterate through its datasets field.

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

All the usual google.cloud.datalabeling_v1beta1.types.ListDatasetsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiates the pager.

Parameters
class google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListDatasetsPager(method: Callable[[...], google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListDatasetsResponse], request: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListDatasetsRequest, response: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListDatasetsResponse, *, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through list_datasets requests.

This class thinly wraps an initial google.cloud.datalabeling_v1beta1.types.ListDatasetsResponse object, and provides an __iter__ method to iterate through its datasets field.

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

All the usual google.cloud.datalabeling_v1beta1.types.ListDatasetsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiate the pager.

Parameters
class google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListEvaluationJobsAsyncPager(method: Callable[[...], Awaitable[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListEvaluationJobsResponse]], request: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListEvaluationJobsRequest, response: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListEvaluationJobsResponse, *, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through list_evaluation_jobs requests.

This class thinly wraps an initial google.cloud.datalabeling_v1beta1.types.ListEvaluationJobsResponse object, and provides an __aiter__ method to iterate through its evaluation_jobs field.

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

All the usual google.cloud.datalabeling_v1beta1.types.ListEvaluationJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiates the pager.

Parameters
class google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListEvaluationJobsPager(method: Callable[[...], google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListEvaluationJobsResponse], request: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListEvaluationJobsRequest, response: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListEvaluationJobsResponse, *, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through list_evaluation_jobs requests.

This class thinly wraps an initial google.cloud.datalabeling_v1beta1.types.ListEvaluationJobsResponse object, and provides an __iter__ method to iterate through its evaluation_jobs field.

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

All the usual google.cloud.datalabeling_v1beta1.types.ListEvaluationJobsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiate the pager.

Parameters
class google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListExamplesAsyncPager(method: Callable[[...], Awaitable[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListExamplesResponse]], request: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListExamplesRequest, response: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListExamplesResponse, *, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through list_examples requests.

This class thinly wraps an initial google.cloud.datalabeling_v1beta1.types.ListExamplesResponse object, and provides an __aiter__ method to iterate through its examples field.

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

All the usual google.cloud.datalabeling_v1beta1.types.ListExamplesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiates the pager.

Parameters
class google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListExamplesPager(method: Callable[[...], google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListExamplesResponse], request: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListExamplesRequest, response: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListExamplesResponse, *, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through list_examples requests.

This class thinly wraps an initial google.cloud.datalabeling_v1beta1.types.ListExamplesResponse object, and provides an __iter__ method to iterate through its examples field.

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

All the usual google.cloud.datalabeling_v1beta1.types.ListExamplesResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiate the pager.

Parameters
class google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListInstructionsAsyncPager(method: Callable[[...], Awaitable[google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListInstructionsResponse]], request: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListInstructionsRequest, response: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListInstructionsResponse, *, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through list_instructions requests.

This class thinly wraps an initial google.cloud.datalabeling_v1beta1.types.ListInstructionsResponse object, and provides an __aiter__ method to iterate through its instructions field.

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

All the usual google.cloud.datalabeling_v1beta1.types.ListInstructionsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiates the pager.

Parameters
class google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.ListInstructionsPager(method: Callable[[...], google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListInstructionsResponse], request: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListInstructionsRequest, response: google.cloud.datalabeling_v1beta1.types.data_labeling_service.ListInstructionsResponse, *, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through list_instructions requests.

This class thinly wraps an initial google.cloud.datalabeling_v1beta1.types.ListInstructionsResponse object, and provides an __iter__ method to iterate through its instructions field.

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

All the usual google.cloud.datalabeling_v1beta1.types.ListInstructionsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiate the pager.

Parameters
class google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.SearchEvaluationsAsyncPager(method: Callable[[...], Awaitable[google.cloud.datalabeling_v1beta1.types.data_labeling_service.SearchEvaluationsResponse]], request: google.cloud.datalabeling_v1beta1.types.data_labeling_service.SearchEvaluationsRequest, response: google.cloud.datalabeling_v1beta1.types.data_labeling_service.SearchEvaluationsResponse, *, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through search_evaluations requests.

This class thinly wraps an initial google.cloud.datalabeling_v1beta1.types.SearchEvaluationsResponse object, and provides an __aiter__ method to iterate through its evaluations field.

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

All the usual google.cloud.datalabeling_v1beta1.types.SearchEvaluationsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiates the pager.

Parameters
class google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.SearchEvaluationsPager(method: Callable[[...], google.cloud.datalabeling_v1beta1.types.data_labeling_service.SearchEvaluationsResponse], request: google.cloud.datalabeling_v1beta1.types.data_labeling_service.SearchEvaluationsRequest, response: google.cloud.datalabeling_v1beta1.types.data_labeling_service.SearchEvaluationsResponse, *, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through search_evaluations requests.

This class thinly wraps an initial google.cloud.datalabeling_v1beta1.types.SearchEvaluationsResponse object, and provides an __iter__ method to iterate through its evaluations field.

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

All the usual google.cloud.datalabeling_v1beta1.types.SearchEvaluationsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiate the pager.

Parameters
class google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.SearchExampleComparisonsAsyncPager(method: Callable[[...], Awaitable[google.cloud.datalabeling_v1beta1.types.data_labeling_service.SearchExampleComparisonsResponse]], request: google.cloud.datalabeling_v1beta1.types.data_labeling_service.SearchExampleComparisonsRequest, response: google.cloud.datalabeling_v1beta1.types.data_labeling_service.SearchExampleComparisonsResponse, *, retry: Optional[Union[google.api_core.retry.retry_unary_async.AsyncRetry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through search_example_comparisons requests.

This class thinly wraps an initial google.cloud.datalabeling_v1beta1.types.SearchExampleComparisonsResponse object, and provides an __aiter__ method to iterate through its example_comparisons field.

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

All the usual google.cloud.datalabeling_v1beta1.types.SearchExampleComparisonsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiates the pager.

Parameters
class google.cloud.datalabeling_v1beta1.services.data_labeling_service.pagers.SearchExampleComparisonsPager(method: Callable[[...], google.cloud.datalabeling_v1beta1.types.data_labeling_service.SearchExampleComparisonsResponse], request: google.cloud.datalabeling_v1beta1.types.data_labeling_service.SearchExampleComparisonsRequest, response: google.cloud.datalabeling_v1beta1.types.data_labeling_service.SearchExampleComparisonsResponse, *, retry: Optional[Union[google.api_core.retry.retry_unary.Retry, google.api_core.gapic_v1.method._MethodDefault]] = _MethodDefault._DEFAULT_VALUE, timeout: Union[float, object] = _MethodDefault._DEFAULT_VALUE, metadata: Sequence[Tuple[str, str]] = ())[source]

A pager for iterating through search_example_comparisons requests.

This class thinly wraps an initial google.cloud.datalabeling_v1beta1.types.SearchExampleComparisonsResponse object, and provides an __iter__ method to iterate through its example_comparisons field.

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

All the usual google.cloud.datalabeling_v1beta1.types.SearchExampleComparisonsResponse attributes are available on the pager. If multiple requests are made, only the most recent response is retained, and thus used for attribute lookup.

Instantiate the pager.

Parameters