feat!: migrate to use microgen (#34)

* feat!: migrate to use microgen

* update sample

* update sample

* update sample

* Update UPGRADING.md

Co-authored-by: Bu Sun Kim <[email protected]>

Co-authored-by: Bu Sun Kim <[email protected]>

Author: arithmetic1728

datalabeling/snippets/create_annotation_spec_set.py

@@ -26,61 +26,58 @@ def create_annotation_spec_set(project_id):
     Google Cloud project.
     """
     from google.cloud import datalabeling_v1beta1 as datalabeling
+
     client = datalabeling.DataLabelingServiceClient()
     # [END datalabeling_create_annotation_spec_set_beta]
     # If provided, use a provided test endpoint - this will prevent tests on
     # this snippet from triggering any action by a real human
-    if 'DATALABELING_ENDPOINT' in os.environ:
-        opts = ClientOptions(api_endpoint=os.getenv('DATALABELING_ENDPOINT'))
+    if "DATALABELING_ENDPOINT" in os.environ:
+        opts = ClientOptions(api_endpoint=os.getenv("DATALABELING_ENDPOINT"))
         client = datalabeling.DataLabelingServiceClient(client_options=opts)
     # [START datalabeling_create_annotation_spec_set_beta]
 
-    project_path = client.project_path(project_id)
+    project_path = f"projects/{project_id}"
 
-    annotation_spec_1 = datalabeling.types.AnnotationSpec(
-        display_name='label_1',
-        description='label_description_1'
+    annotation_spec_1 = datalabeling.AnnotationSpec(
+        display_name="label_1", description="label_description_1"
     )
 
-    annotation_spec_2 = datalabeling.types.AnnotationSpec(
-        display_name='label_2',
-        description='label_description_2'
+    annotation_spec_2 = datalabeling.AnnotationSpec(
+        display_name="label_2", description="label_description_2"
     )
 
-    annotation_spec_set = datalabeling.types.AnnotationSpecSet(
-        display_name='YOUR_ANNOTATION_SPEC_SET_DISPLAY_NAME',
-        description='YOUR_DESCRIPTION',
-        annotation_specs=[annotation_spec_1, annotation_spec_2]
+    annotation_spec_set = datalabeling.AnnotationSpecSet(
+        display_name="YOUR_ANNOTATION_SPEC_SET_DISPLAY_NAME",
+        description="YOUR_DESCRIPTION",
+        annotation_specs=[annotation_spec_1, annotation_spec_2],
     )
 
     response = client.create_annotation_spec_set(
-        project_path, annotation_spec_set)
+        request={"parent": project_path, "annotation_spec_set": annotation_spec_set}
+    )
 
     # The format of the resource name:
     # project_id/{project_id}/annotationSpecSets/{annotationSpecSets_id}
-    print('The annotation_spec_set resource name: {}'.format(response.name))
-    print('Display name: {}'.format(response.display_name))
-    print('Description: {}'.format(response.description))
-    print('Annotation specs:')
+    print("The annotation_spec_set resource name: {}".format(response.name))
+    print("Display name: {}".format(response.display_name))
+    print("Description: {}".format(response.description))
+    print("Annotation specs:")
     for annotation_spec in response.annotation_specs:
-        print('\tDisplay name: {}'.format(annotation_spec.display_name))
-        print('\tDescription: {}\n'.format(annotation_spec.description))
+        print("\tDisplay name: {}".format(annotation_spec.display_name))
+        print("\tDescription: {}\n".format(annotation_spec.description))
 
     return response
+
+
 # [END datalabeling_create_annotation_spec_set_beta]
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     parser = argparse.ArgumentParser(
-        description=__doc__,
-        formatter_class=argparse.RawDescriptionHelpFormatter
+        description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter
     )
 
-    parser.add_argument(
-        '--project-id',
-        help='Project ID. Required.',
-        required=True
-    )
+    parser.add_argument("--project-id", help="Project ID. Required.", required=True)
 
     args = parser.parse_args()
 

datalabeling/snippets/create_annotation_spec_set_test.py

@@ -24,10 +24,10 @@
 import testing_lib
 
 
-PROJECT_ID = os.getenv('GOOGLE_CLOUD_PROJECT')
+PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT")
 
 
-@pytest.fixture(scope='module')
+@pytest.fixture(scope="module")
 def cleaner():
     resource_names = []
 
@@ -38,9 +38,9 @@ def cleaner():
 
 
 def test_create_annotation_spec_set(cleaner, capsys):
-
     @backoff.on_exception(
-        backoff.expo, ServerError, max_time=testing_lib.RETRY_DEADLINE)
+        backoff.expo, ServerError, max_time=testing_lib.RETRY_DEADLINE
+    )
     def run_sample():
         return create_annotation_spec_set.create_annotation_spec_set(PROJECT_ID)
 
@@ -50,4 +50,4 @@ def run_sample():
     cleaner.append(response.name)
 
     out, _ = capsys.readouterr()
-    assert 'The annotation_spec_set resource name:' in out
+    assert "The annotation_spec_set resource name:" in out

datalabeling/snippets/create_instruction.py

@@ -27,77 +27,70 @@ def create_instruction(project_id, data_type, instruction_gcs_uri):
     Google Cloud Storage.
     """
     from google.cloud import datalabeling_v1beta1 as datalabeling
+
     client = datalabeling.DataLabelingServiceClient()
     # [END datalabeling_create_instruction_beta]
     # If provided, use a provided test endpoint - this will prevent tests on
     # this snippet from triggering any action by a real human
-    if 'DATALABELING_ENDPOINT' in os.environ:
-        opts = ClientOptions(api_endpoint=os.getenv('DATALABELING_ENDPOINT'))
+    if "DATALABELING_ENDPOINT" in os.environ:
+        opts = ClientOptions(api_endpoint=os.getenv("DATALABELING_ENDPOINT"))
         client = datalabeling.DataLabelingServiceClient(client_options=opts)
     # [START datalabeling_create_instruction_beta]
 
-    project_path = client.project_path(project_id)
+    project_path = f"projects/{project_id}"
 
-    pdf_instruction = datalabeling.types.PdfInstruction(
-        gcs_file_uri=instruction_gcs_uri)
+    pdf_instruction = datalabeling.PdfInstruction(gcs_file_uri=instruction_gcs_uri)
 
-    instruction = datalabeling.types.Instruction(
-        display_name='YOUR_INSTRUCTION_DISPLAY_NAME',
-        description='YOUR_DESCRIPTION',
+    instruction = datalabeling.Instruction(
+        display_name="YOUR_INSTRUCTION_DISPLAY_NAME",
+        description="YOUR_DESCRIPTION",
         data_type=data_type,
-        pdf_instruction=pdf_instruction
+        pdf_instruction=pdf_instruction,
     )
 
-    operation = client.create_instruction(project_path, instruction)
+    operation = client.create_instruction(
+        request={"parent": project_path, "instruction": instruction}
+    )
 
     result = operation.result()
 
     # The format of the resource name:
     # project_id/{project_id}/instruction/{instruction_id}
-    print('The instruction resource name: {}'.format(result.name))
-    print('Display name: {}'.format(result.display_name))
-    print('Description: {}'.format(result.description))
-    print('Create time:')
-    print('\tseconds: {}'.format(result.create_time.seconds))
-    print('\tnanos: {}'.format(result.create_time.nanos))
-    print('Data type: {}'.format(
-        datalabeling.enums.DataType(result.data_type).name))
-    print('Pdf instruction:')
-    print('\tGcs file uri: {}\n'.format(
-        result.pdf_instruction.gcs_file_uri))
+    print("The instruction resource name: {}".format(result.name))
+    print("Display name: {}".format(result.display_name))
+    print("Description: {}".format(result.description))
+    print("Create time:")
+    print("\tseconds: {}".format(result.create_time.timestamp_pb().seconds))
+    print("\tnanos: {}".format(result.create_time.timestamp_pb().nanos))
+    print("Data type: {}".format(datalabeling.DataType(result.data_type).name))
+    print("Pdf instruction:")
+    print("\tGcs file uri: {}\n".format(result.pdf_instruction.gcs_file_uri))
 
     return result
+
+
 # [END datalabeling_create_instruction_beta]
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     parser = argparse.ArgumentParser(
-        description=__doc__,
-        formatter_class=argparse.RawDescriptionHelpFormatter
+        description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter
     )
 
-    parser.add_argument(
-        '--project-id',
-        help='Project ID. Required.',
-        required=True
-    )
+    parser.add_argument("--project-id", help="Project ID. Required.", required=True)
 
     parser.add_argument(
-        '--data-type',
-        help='Data type. Only support IMAGE, VIDEO, TEXT and AUDIO. Required.',
-        required=True
+        "--data-type",
+        help="Data type. Only support IMAGE, VIDEO, TEXT and AUDIO. Required.",
+        required=True,
     )
 
     parser.add_argument(
-        '--instruction-gcs-uri',
-        help='The URI of Google Cloud Storage of the instruction. Required.',
-        required=True
+        "--instruction-gcs-uri",
+        help="The URI of Google Cloud Storage of the instruction. Required.",
+        required=True,
     )
 
     args = parser.parse_args()
 
-    create_instruction(
-        args.project_id,
-        args.data_type,
-        args.instruction_gcs_uri
-    )
+    create_instruction(args.project_id, args.data_type, args.instruction_gcs_uri)

datalabeling/snippets/create_instruction_test.py

@@ -18,18 +18,18 @@
 
 import backoff
 from google.api_core.exceptions import ServerError
+from google.cloud import datalabeling
 import pytest
 
 import create_instruction
 import testing_lib
 
 
-PROJECT_ID = os.getenv('GOOGLE_CLOUD_PROJECT')
-INSTRUCTION_GCS_URI = ('gs://cloud-samples-data/datalabeling'
-                       '/instruction/test.pdf')
+PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT")
+INSTRUCTION_GCS_URI = "gs://cloud-samples-data/datalabeling" "/instruction/test.pdf"
 
 
-@pytest.fixture(scope='module')
+@pytest.fixture(scope="module")
 def cleaner():
     resource_names = []
 
@@ -40,15 +40,16 @@ def cleaner():
 
 
 def test_create_instruction(cleaner, capsys):
-
     @backoff.on_exception(
-        backoff.expo, ServerError, max_time=testing_lib.RETRY_DEADLINE)
+        backoff.expo, ServerError, max_time=testing_lib.RETRY_DEADLINE
+    )
     def run_sample():
         return create_instruction.create_instruction(
-            PROJECT_ID, 'IMAGE', INSTRUCTION_GCS_URI)
+            PROJECT_ID, datalabeling.DataType.IMAGE, INSTRUCTION_GCS_URI
+        )
 
     instruction = run_sample()
     cleaner.append(instruction.name)
 
     out, _ = capsys.readouterr()
-    assert 'The instruction resource name: ' in out
+    assert "The instruction resource name: " in out

datalabeling/snippets/export_data.py

@@ -21,67 +21,71 @@
 
 
 # [START datalabeling_export_data_beta]
-def export_data(dataset_resource_name, annotated_dataset_resource_name,
-                export_gcs_uri):
+def export_data(dataset_resource_name, annotated_dataset_resource_name, export_gcs_uri):
     """Exports a dataset from the given Google Cloud project."""
     from google.cloud import datalabeling_v1beta1 as datalabeling
+
     client = datalabeling.DataLabelingServiceClient()
     # [END datalabeling_export_data_beta]
     # If provided, use a provided test endpoint - this will prevent tests on
     # this snippet from triggering any action by a real human
-    if 'DATALABELING_ENDPOINT' in os.environ:
-        opts = ClientOptions(api_endpoint=os.getenv('DATALABELING_ENDPOINT'))
+    if "DATALABELING_ENDPOINT" in os.environ:
+        opts = ClientOptions(api_endpoint=os.getenv("DATALABELING_ENDPOINT"))
         client = datalabeling.DataLabelingServiceClient(client_options=opts)
     # [START datalabeling_export_data_beta]
 
-    gcs_destination = datalabeling.types.GcsDestination(
-        output_uri=export_gcs_uri, mime_type='text/csv')
+    gcs_destination = datalabeling.GcsDestination(
+        output_uri=export_gcs_uri, mime_type="text/csv"
+    )
 
-    output_config = datalabeling.types.OutputConfig(
-        gcs_destination=gcs_destination)
+    output_config = datalabeling.OutputConfig(gcs_destination=gcs_destination)
 
     response = client.export_data(
-        dataset_resource_name,
-        annotated_dataset_resource_name,
-        output_config
+        request={
+            "name": dataset_resource_name,
+            "annotated_dataset": annotated_dataset_resource_name,
+            "output_config": output_config,
+        }
     )
 
-    print('Dataset ID: {}\n'.format(response.result().dataset))
-    print('Output config:')
-    print('\tGcs destination:')
-    print('\t\tOutput URI: {}\n'.format(
-        response.result().output_config.gcs_destination.output_uri))
+    print("Dataset ID: {}\n".format(response.result().dataset))
+    print("Output config:")
+    print("\tGcs destination:")
+    print(
+        "\t\tOutput URI: {}\n".format(
+            response.result().output_config.gcs_destination.output_uri
+        )
+    )
+
+
 # [END datalabeling_export_data_beta]
 
 
-if __name__ == '__main__':
+if __name__ == "__main__":
     parser = argparse.ArgumentParser(
-        description=__doc__,
-        formatter_class=argparse.RawDescriptionHelpFormatter
+        description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter
     )
 
     parser.add_argument(
-        '--dataset-resource-name',
-        help='Dataset resource name. Required.',
-        required=True
+        "--dataset-resource-name",
+        help="Dataset resource name. Required.",
+        required=True,
     )
 
     parser.add_argument(
-        '--annotated-dataset-resource-name',
-        help='Annotated Dataset resource name. Required.',
-        required=True
+        "--annotated-dataset-resource-name",
+        help="Annotated Dataset resource name. Required.",
+        required=True,
     )
 
     parser.add_argument(
-        '--export-gcs-uri',
-        help='The export GCS URI. Required.',
-        required=True
+        "--export-gcs-uri", help="The export GCS URI. Required.", required=True
     )
 
     args = parser.parse_args()
 
     export_data(
         args.dataset_resource_name,
         args.annotated_dataset_resource_name,
-        args.export_gcs_uri
+        args.export_gcs_uri,
     )