chore: Fix lint

PiperOrigin-RevId: 552860665

Author: yinghsienwu

.pre-commit-config.yaml

@@ -26,6 +26,6 @@ repos:
     hooks:
     - id: black
 -   repo: https://github.com/pycqa/flake8
-    rev: 3.9.2
+    rev: 6.1.0
     hooks:
     - id: flake8

google/cloud/aiplatform/jobs.py

@@ -685,7 +685,7 @@ def create(
         else:
             input_config.instances_format = instances_format
             input_config.gcs_source = gca_io_compat.GcsSource(
-                uris=gcs_source if type(gcs_source) == list else [gcs_source]
+                uris=gcs_source if isinstance(gcs_source, list) else [gcs_source]
             )
 
         if bigquery_destination_prefix:

noxfile.py

@@ -25,6 +25,7 @@
 
 import nox
 
+FLAKE8_VERSION = "flake8==6.1.0"
 BLACK_VERSION = "black==22.3.0"
 ISORT_VERSION = "isort==5.10.1"
 LINT_PATHS = ["docs", "google", "tests", "noxfile.py", "setup.py"]
@@ -85,7 +86,7 @@ def lint(session):
     Returns a failure if the linters find linting errors or sufficiently
     serious code quality issues.
     """
-    session.install("flake8", BLACK_VERSION)
+    session.install(FLAKE8_VERSION, BLACK_VERSION)
     session.run(
         "black",
         "--check",

samples/snippets/conftest.py

@@ -282,7 +282,9 @@ def teardown_batch_read_feature_values(shared_state, bigquery_client):
 def create_endpoint(shared_state, endpoint_client):
     def create(project, location, test_name="temp_deploy_model_test"):
         parent = f"projects/{project}/locations/{location}"
-        endpoint = aiplatform.gapic.Endpoint(display_name=f"{test_name}_{uuid4()}",)
+        endpoint = aiplatform.gapic.Endpoint(
+            display_name=f"{test_name}_{uuid4()}",
+        )
         create_endpoint_response = endpoint_client.create_endpoint(
             parent=parent, endpoint=endpoint
         )

samples/snippets/helpers.py

@@ -24,7 +24,7 @@
 
 
 def get_name(out, key="name"):
-    pattern = re.compile(fr'{key}:\s*"([\-a-zA-Z0-9/]+)"')
+    pattern = re.compile(rf'{key}:\s*"([\-a-zA-Z0-9/]+)"')
     name = re.search(pattern, out).group(1)
 
     return name
@@ -38,7 +38,7 @@ def get_state(out):
 
 
 def get_featurestore_resource_name(out, key="name"):
-    pattern = re.compile(fr'{key}:\s*"([\_\-a-zA-Z0-9/]+)"')
+    pattern = re.compile(rf'{key}:\s*"([\_\-a-zA-Z0-9/]+)"')
     name = re.search(pattern, out).group(1)
 
     return name
@@ -51,7 +51,7 @@ def wait_for_job_state(
     timeout: int = 90,
     freq: float = 1.5,
 ) -> None:
-    """ Waits until the Job state of provided resource name is a particular state.
+    """Waits until the Job state of provided resource name is a particular state.
 
     Args:
         get_job_method: Callable[[str], "proto.Message"]
@@ -91,12 +91,12 @@ def flaky_test_diagnostic(file_name, test_name, N=20):
     timing_dict = collections.defaultdict(list)
     for ri in range(N):
         start = timer()
-        result = pytest.main(['-s', f'{file_name}::{test_name}'])
+        result = pytest.main(["-s", f"{file_name}::{test_name}"])
         end = timer()
-        delta = end-start
+        delta = end - start
         if result == pytest.ExitCode.OK:
-            timing_dict['SUCCESS'].append(delta)
+            timing_dict["SUCCESS"].append(delta)
         else:
-            timing_dict['FAILURE'].append(delta)
+            timing_dict["FAILURE"].append(delta)
 
     return timing_dict

samples/snippets/noxfile.py

@@ -160,6 +160,7 @@ def blacken(session: nox.sessions.Session) -> None:
 # format = isort + black
 #
 
+
 @nox.session
 def format(session: nox.sessions.Session) -> None:
     """
@@ -187,7 +188,9 @@ def _session_tests(
     session: nox.sessions.Session, post_install: Callable = None
 ) -> None:
     # check for presence of tests
-    test_list = glob.glob("**/*_test.py", recursive=True) + glob.glob("**/test_*.py", recursive=True)
+    test_list = glob.glob("**/*_test.py", recursive=True) + glob.glob(
+        "**/test_*.py", recursive=True
+    )
     test_list.extend(glob.glob("**/tests", recursive=True))
 
     if len(test_list) == 0:
@@ -209,9 +212,7 @@ def _session_tests(
 
     if os.path.exists("requirements-test.txt"):
         if os.path.exists("constraints-test.txt"):
-            session.install(
-                "-r", "requirements-test.txt", "-c", "constraints-test.txt"
-            )
+            session.install("-r", "requirements-test.txt", "-c", "constraints-test.txt")
         else:
             session.install("-r", "requirements-test.txt")
         with open("requirements-test.txt") as rtfile:
@@ -224,9 +225,9 @@ def _session_tests(
         post_install(session)
 
     if "pytest-parallel" in packages:
-        concurrent_args.extend(['--workers', 'auto', '--tests-per-worker', 'auto'])
+        concurrent_args.extend(["--workers", "auto", "--tests-per-worker", "auto"])
     elif "pytest-xdist" in packages:
-        concurrent_args.extend(['-n', 'auto'])
+        concurrent_args.extend(["-n", "auto"])
 
     session.run(
         "pytest",
@@ -256,7 +257,7 @@ def py(session: nox.sessions.Session) -> None:
 
 
 def _get_repo_root() -> Optional[str]:
-    """ Returns the root folder of the project. """
+    """Returns the root folder of the project."""
     # Get root of this repository. Assume we don't have directories nested deeper than 10 items.
     p = Path(os.getcwd())
     for i in range(10):

samples/snippets/noxfile_config.py

@@ -30,6 +30,6 @@
     # secrets here. These values will override predefined values.
     "envs": {
         "DATA_LABELING_API_ENDPOINT": "us-central1-autopush-aiplatform.sandbox.googleapis.com",
-        "PYTEST_ADDOPTS": "-n=auto"  # Run tests parallel using all available CPUs
+        "PYTEST_ADDOPTS": "-n=auto",  # Run tests parallel using all available CPUs
     },
 }

samples/snippets/prediction_service/explain_tabular_sample_test.py

@@ -34,4 +34,4 @@ def test_ucaip_generated_explain_tabular_sample(capsys):
     )
 
     out, _ = capsys.readouterr()
-    assert 'attribution' in out
+    assert "attribution" in out

samples/snippets/prediction_service/predict_custom_trained_model_sample.py

@@ -37,7 +37,7 @@ def predict_custom_trained_model_sample(
     # This client only needs to be created once, and can be reused for multiple requests.
     client = aiplatform.gapic.PredictionServiceClient(client_options=client_options)
     # The format of each instance should conform to the deployed model's prediction input schema.
-    instances = instances if type(instances) == list else [instances]
+    instances = instances if isinstance(instances, list) else [instances]
     instances = [
         json_format.ParseDict(instance_dict, Value()) for instance_dict in instances
     ]

samples/snippets/prediction_service/predict_image_classification_sample.py

@@ -42,7 +42,8 @@ def predict_image_classification_sample(
     instances = [instance]
     # See gs://google-cloud-aiplatform/schema/predict/params/image_classification_1.0.0.yaml for the format of the parameters.
     parameters = predict.params.ImageClassificationPredictionParams(
-        confidence_threshold=0.5, max_predictions=5,
+        confidence_threshold=0.5,
+        max_predictions=5,
     ).to_value()
     endpoint = client.endpoint_path(
         project=project, location=location, endpoint=endpoint_id

samples/snippets/prediction_service/predict_image_classification_sample_test.py

@@ -31,4 +31,4 @@ def test_ucaip_generated_predict_image_classification_sample(capsys):
     )
 
     out, _ = capsys.readouterr()
-    assert 'deployed_model_id:' in out
+    assert "deployed_model_id:" in out

samples/snippets/prediction_service/predict_image_object_detection_sample.py

@@ -42,7 +42,8 @@ def predict_image_object_detection_sample(
     instances = [instance]
     # See gs://google-cloud-aiplatform/schema/predict/params/image_object_detection_1.0.0.yaml for the format of the parameters.
     parameters = predict.params.ImageObjectDetectionPredictionParams(
-        confidence_threshold=0.5, max_predictions=5,
+        confidence_threshold=0.5,
+        max_predictions=5,
     ).to_value()
     endpoint = client.endpoint_path(
         project=project, location=location, endpoint=endpoint_id

samples/snippets/prediction_service/predict_image_object_detection_sample_test.py

@@ -31,4 +31,4 @@ def test_ucaip_generated_predict_image_object_detection_sample(capsys):
     )
 
     out, _ = capsys.readouterr()
-    assert 'Salad' in out
+    assert "Salad" in out

samples/snippets/prediction_service/predict_tabular_classification_sample_test.py

@@ -35,4 +35,4 @@ def test_ucaip_generated_predict_tabular_classification_sample(capsys):
     )
 
     out, _ = capsys.readouterr()
-    assert 'setosa' in out
+    assert "setosa" in out

tests/system/aiplatform/test_featurestore.py

@@ -583,7 +583,7 @@ def test_batch_serve_to_df(self, shared_state, caplog):
             "average_rating",
         ]
 
-        assert type(df) == pd.DataFrame
+        assert isinstance(df, pd.DataFrame)
         assert list(df.columns) == expected_df_columns
         assert df.size == 54
         assert "Featurestore feature values served." in caplog.text
@@ -699,16 +699,16 @@ def test_online_reads(self, shared_state):
         movie_entity_type = shared_state["movie_entity_type"]
 
         user_entity_views = user_entity_type.read(entity_ids="alice")
-        assert type(user_entity_views) == pd.DataFrame
+        assert isinstance(user_entity_views, pd.DataFrame)
 
         movie_entity_views = movie_entity_type.read(
             entity_ids=["movie_01", "movie_04"],
             feature_ids=[_TEST_MOVIE_TITLE_FEATURE_ID, _TEST_MOVIE_GENRES_FEATURE_ID],
         )
-        assert type(movie_entity_views) == pd.DataFrame
+        assert isinstance(movie_entity_views, pd.DataFrame)
 
         movie_entity_views = movie_entity_type.read(
             entity_ids="movie_01",
             feature_ids=[_TEST_MOVIE_TITLE_FEATURE_ID, _TEST_MOVIE_GENRES_FEATURE_ID],
         )
-        assert type(movie_entity_views) == pd.DataFrame
+        assert isinstance(movie_entity_views, pd.DataFrame)

tests/unit/aiplatform/test_autologging.py

@@ -35,7 +35,6 @@
 from google.cloud.aiplatform import initializer
 from google.cloud.aiplatform import base
 from google.cloud.aiplatform_v1 import (
-    AddContextArtifactsAndExecutionsResponse,
     Artifact as GapicArtifact,
     Context as GapicContext,
     Execution as GapicExecution,
@@ -395,17 +394,6 @@ def add_context_children_mock():
         yield add_context_children_mock
 
 
-@pytest.fixture
-def add_context_artifacts_and_executions_mock():
-    with patch.object(
-        MetadataServiceClient, "add_context_artifacts_and_executions"
-    ) as add_context_artifacts_and_executions_mock:
-        add_context_artifacts_and_executions_mock.return_value = (
-            AddContextArtifactsAndExecutionsResponse()
-        )
-        yield add_context_artifacts_and_executions_mock
-
-
 @pytest.fixture
 def get_tensorboard_run_not_found_mock():
     with patch.object(

tests/unit/aiplatform/test_datasets.py

@@ -1444,7 +1444,7 @@ def test_list_dataset(self, list_datasets_mock):
         assert len(ds_list) < len(_TEST_DATASET_LIST)
 
         for ds in ds_list:
-            assert type(ds) == aiplatform.TabularDataset
+            assert isinstance(ds, aiplatform.TabularDataset)
 
     def test_list_dataset_no_order_or_filter(self, list_datasets_mock):
 
@@ -1456,7 +1456,7 @@ def test_list_dataset_no_order_or_filter(self, list_datasets_mock):
         assert len(ds_list) < len(_TEST_DATASET_LIST)
 
         for ds in ds_list:
-            assert type(ds) == aiplatform.TabularDataset
+            assert isinstance(ds, aiplatform.TabularDataset)
 
     @pytest.mark.usefixtures("get_dataset_tabular_missing_metadata_mock")
     def test_tabular_dataset_column_name_missing_metadata(self):

tests/unit/aiplatform/test_deployment_resource_pools.py

@@ -324,7 +324,7 @@ def test_list(self, list_drp_mock):
         list_drp_mock.assert_called_once()
 
         for drp in drp_list:
-            assert type(drp) == models.DeploymentResourcePool
+            assert isinstance(drp, models.DeploymentResourcePool)
 
     @pytest.mark.usefixtures("delete_drp_mock", "get_drp_mock")
     @pytest.mark.parametrize("sync", [True, False])

tests/unit/aiplatform/test_endpoints.py

@@ -1999,7 +1999,7 @@ def test_list_endpoint_order_by_time(self, list_endpoints_mock):
         assert len(ep_list) == len(_TEST_ENDPOINT_LIST)
 
         for ep in ep_list:
-            assert type(ep) == aiplatform.Endpoint
+            assert isinstance(ep, aiplatform.Endpoint)
 
         assert ep_list[0].create_time > ep_list[1].create_time > ep_list[2].create_time
 
@@ -2018,7 +2018,7 @@ def test_list_endpoint_order_by_display_name(self, list_endpoints_mock):
         assert len(ep_list) == len(_TEST_ENDPOINT_LIST)
 
         for ep in ep_list:
-            assert type(ep) == aiplatform.Endpoint
+            assert isinstance(ep, aiplatform.Endpoint)
 
         assert (
             ep_list[0].display_name < ep_list[1].display_name < ep_list[2].display_name