def sample_get_dataset():
# Create a client
client = aiplatform_v1beta1.DatasetServiceClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.GetDatasetRequest(name="name_value", )
# Make the request
response = client.get_dataset(request=request)
# Handle the response
print(response)
def sample_list_data_items():
# Create a client
client = aiplatform_v1beta1.DatasetServiceClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.ListDataItemsRequest(parent="parent_value", )
# Make the request
page_result = client.list_data_items(request=request)
# Handle the response
for response in page_result:
print(response)
def sample_delete_dataset():
# Create a client
client = aiplatform_v1beta1.DatasetServiceClient()
# Initialize request argument(s)
request = aiplatform_v1beta1.DeleteDatasetRequest(name="name_value", )
# Make the request
operation = client.delete_dataset(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
def sample_update_dataset():
# Create a client
client = aiplatform_v1beta1.DatasetServiceClient()
# Initialize request argument(s)
dataset = aiplatform_v1beta1.Dataset()
dataset.display_name = "display_name_value"
dataset.metadata_schema_uri = "metadata_schema_uri_value"
dataset.metadata.null_value = "NULL_VALUE"
request = aiplatform_v1beta1.UpdateDatasetRequest(dataset=dataset, )
# Make the request
response = client.update_dataset(request=request)
# Handle the response
print(response)
def sample_export_data():
# Create a client
client = aiplatform_v1beta1.DatasetServiceClient()
# Initialize request argument(s)
export_config = aiplatform_v1beta1.ExportDataConfig()
export_config.gcs_destination.output_uri_prefix = "output_uri_prefix_value"
request = aiplatform_v1beta1.ExportDataRequest(
name="name_value",
export_config=export_config,
)
# Make the request
operation = client.export_data(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)
def sample_import_data():
# Create a client
client = aiplatform_v1beta1.DatasetServiceClient()
# Initialize request argument(s)
import_configs = aiplatform_v1beta1.ImportDataConfig()
import_configs.gcs_source.uris = ['uris_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 = operation.result()
# Handle the response
print(response)
def sample_create_dataset():
# Create a client
client = aiplatform_v1beta1.DatasetServiceClient()
# Initialize request argument(s)
dataset = aiplatform_v1beta1.Dataset()
dataset.display_name = "display_name_value"
dataset.metadata_schema_uri = "metadata_schema_uri_value"
dataset.metadata.null_value = "NULL_VALUE"
request = aiplatform_v1beta1.CreateDatasetRequest(
parent="parent_value",
dataset=dataset,
)
# Make the request
operation = client.create_dataset(request=request)
print("Waiting for operation to complete...")
response = operation.result()
# Handle the response
print(response)