async def sample_get_annotation_spec(): # Create a client client = aiplatform_v1beta1.DatasetServiceAsyncClient() # Initialize request argument(s) request = aiplatform_v1beta1.GetAnnotationSpecRequest(name="name_value", ) # Make the request response = await client.get_annotation_spec(request=request) # Handle the response print(response)
async def sample_list_data_items(): # Create a client client = aiplatform_v1beta1.DatasetServiceAsyncClient() # Initialize request argument(s) request = aiplatform_v1beta1.ListDataItemsRequest(parent="parent_value", ) # Make the request page_result = client.list_data_items(request=request) # Handle the response async for response in page_result: print(response)
async def sample_delete_dataset(): # Create a client client = aiplatform_v1beta1.DatasetServiceAsyncClient() # Initialize request argument(s) request = aiplatform_v1beta1.DeleteDatasetRequest(name="name_value", ) # Make the request operation = client.delete_dataset(request=request) print("Waiting for operation to complete...") response = await operation.result() # Handle the response print(response)
async def sample_update_dataset(): # Create a client client = aiplatform_v1beta1.DatasetServiceAsyncClient() # Initialize request argument(s) dataset = aiplatform_v1beta1.Dataset() dataset.display_name = "display_name_value" dataset.metadata_schema_uri = "metadata_schema_uri_value" dataset.metadata.null_value = "NULL_VALUE" request = aiplatform_v1beta1.UpdateDatasetRequest(dataset=dataset, ) # Make the request response = await client.update_dataset(request=request) # Handle the response print(response)
async def sample_export_data(): # Create a client client = aiplatform_v1beta1.DatasetServiceAsyncClient() # Initialize request argument(s) export_config = aiplatform_v1beta1.ExportDataConfig() export_config.gcs_destination.output_uri_prefix = "output_uri_prefix_value" request = aiplatform_v1beta1.ExportDataRequest( name="name_value", export_config=export_config, ) # Make the request operation = client.export_data(request=request) print("Waiting for operation to complete...") response = await operation.result() # Handle the response print(response)
async def sample_import_data(): # Create a client client = aiplatform_v1beta1.DatasetServiceAsyncClient() # Initialize request argument(s) import_configs = aiplatform_v1beta1.ImportDataConfig() import_configs.gcs_source.uris = ['uris_value_1', 'uris_value_2'] import_configs.import_schema_uri = "import_schema_uri_value" request = aiplatform_v1beta1.ImportDataRequest( name="name_value", import_configs=import_configs, ) # Make the request operation = client.import_data(request=request) print("Waiting for operation to complete...") response = await operation.result() # Handle the response print(response)
async def sample_create_dataset(): # Create a client client = aiplatform_v1beta1.DatasetServiceAsyncClient() # Initialize request argument(s) dataset = aiplatform_v1beta1.Dataset() dataset.display_name = "display_name_value" dataset.metadata_schema_uri = "metadata_schema_uri_value" dataset.metadata.null_value = "NULL_VALUE" request = aiplatform_v1beta1.CreateDatasetRequest( parent="parent_value", dataset=dataset, ) # Make the request operation = client.create_dataset(request=request) print("Waiting for operation to complete...") response = await operation.result() # Handle the response print(response)