infra: address warnings about pytest custom marks, error message checking, and yaml loading

tests/integ/test_chainer_train.py

@@ -61,7 +61,6 @@ def test_training_with_additional_hyperparameters(sagemaker_local_session, chain
 
 
 @pytest.mark.canary_quick
-@pytest.mark.regional_testing
 def test_attach_deploy(sagemaker_session, chainer_full_version, cpu_instance_type):
     with timeout(minutes=TRAINING_DEFAULT_TIMEOUT_MINUTES):
         script_path = os.path.join(DATA_DIR, "chainer_mnist", "mnist.py")

tests/integ/test_inference_pipeline.py

@@ -51,8 +51,6 @@
 )
 
 
-@pytest.mark.continuous_testing
-@pytest.mark.regional_testing
 def test_inference_pipeline_batch_transform(sagemaker_session, cpu_instance_type):
     sparkml_model_data = sagemaker_session.upload_data(
         path=os.path.join(SPARKML_DATA_PATH, "mleap_model.tar.gz"),
@@ -94,7 +92,6 @@ def test_inference_pipeline_batch_transform(sagemaker_session, cpu_instance_type
 
 
 @pytest.mark.canary_quick
-@pytest.mark.regional_testing
 @pytest.mark.skip(
     reason="This test has always failed, but the failure was masked by a bug. "
     "This test should be fixed. Details in https://github.com/aws/sagemaker-python-sdk/pull/968"

tests/integ/test_mxnet_train.py

@@ -56,7 +56,6 @@ def mxnet_training_job(sagemaker_session, mxnet_full_version, cpu_instance_type)
 
 
 @pytest.mark.canary_quick
-@pytest.mark.regional_testing
 def test_attach_deploy(mxnet_training_job, sagemaker_session, cpu_instance_type):
     endpoint_name = "test-mxnet-attach-deploy-{}".format(sagemaker_timestamp())
 
@@ -238,7 +237,6 @@ def test_deploy_model_with_update_non_existing_endpoint(
 
 
 @pytest.mark.canary_quick
-@pytest.mark.regional_testing
 @pytest.mark.skipif(
     tests.integ.test_region() not in tests.integ.EI_SUPPORTED_REGIONS,
     reason="EI isn't supported in that specific region.",

tests/integ/test_neo_mxnet.py

@@ -55,7 +55,6 @@ def mxnet_training_job(sagemaker_session, cpu_instance_type):
 
 
 @pytest.mark.canary_quick
-@pytest.mark.regional_testing
 def test_attach_deploy(
     mxnet_training_job, sagemaker_session, cpu_instance_type, cpu_instance_family
 ):

tests/integ/test_pytorch_train.py

@@ -48,7 +48,6 @@ def fixture_training_job(sagemaker_session, pytorch_full_version, cpu_instance_t
 
 
 @pytest.mark.canary_quick
-@pytest.mark.regional_testing
 @pytest.mark.skipif(
     PYTHON_VERSION == "py2",
     reason="Python 2 is supported by PyTorch {} and lower versions.".format(LATEST_PY2_VERSION),

tests/integ/test_sklearn_train.py

@@ -101,7 +101,6 @@ def test_training_with_network_isolation(
 
 
 @pytest.mark.canary_quick
-@pytest.mark.regional_testing
 @pytest.mark.skipif(PYTHON_VERSION != "py3", reason="Scikit-learn image supports only python 3.")
 @pytest.mark.skip(
     reason="This test has always failed, but the failure was masked by a bug. "

tests/integ/test_sparkml_serving.py

@@ -24,7 +24,6 @@
 
 
 @pytest.mark.canary_quick
-@pytest.mark.regional_testing
 @pytest.mark.skip(
     reason="This test has always failed, but the failure was masked by a bug. "
     "This test should be fixed. Details in https://github.com/aws/sagemaker-python-sdk/pull/968"

tests/unit/sagemaker/automl/test_auto_ml.py

@@ -273,26 +273,30 @@ def test_auto_ml_invalid_input_data_format(sagemaker_session):
     )
     inputs = {}
 
-    expected_error_msg = "Cannot format input {}. Expecting one of str or list of strings."
-    with pytest.raises(ValueError, message=expected_error_msg.format(inputs)):
+    with pytest.raises(ValueError) as excinfo:
         AutoMLJob.start_new(auto_ml, inputs)
+
+    expected_error_msg = "Cannot format input {}. Expecting a string or a list of strings."
+    assert expected_error_msg.format(inputs) in str(excinfo.value)
+
     sagemaker_session.auto_ml.assert_not_called()
 
 
 def test_auto_ml_only_one_of_problem_type_and_job_objective_provided(sagemaker_session):
-    with pytest.raises(
-        ValueError,
-        message="One of problem type and objective metric provided. "
-        "Either both of them should be provided or none of "
-        "them should be provided.",
-    ):
+    with pytest.raises(ValueError) as excinfo:
         AutoML(
             role=ROLE,
             target_attribute_name=TARGET_ATTRIBUTE_NAME,
             sagemaker_session=sagemaker_session,
             problem_type=PROBLEM_TYPE,
         )
 
+    message = (
+        "One of problem type and objective metric provided. Either both of them "
+        "should be provided or none of them should be provided."
+    )
+    assert message in str(excinfo.value)
+
 
 @patch("sagemaker.automl.automl.AutoMLJob.start_new")
 def test_auto_ml_fit_set_logs_to_false(start_new, sagemaker_session, caplog):
@@ -637,15 +641,16 @@ def test_validate_and_update_inference_response():
 def test_validate_and_update_inference_response_wrong_input():
     cic = copy.copy(CLASSIFICATION_INFERENCE_CONTAINERS)
 
-    with pytest.raises(
-        ValueError,
-        message="Requested inference output keys [wrong_key, wrong_label] are unsupported. "
-        "The supported inference keys are [probability, probabilities, predicted_label, labels]",
-    ):
+    with pytest.raises(ValueError) as excinfo:
         AutoML.validate_and_update_inference_response(
             inference_containers=cic,
             inference_response_keys=["wrong_key", "wrong_label", "probabilities", "probability"],
         )
+    message = (
+        "Requested inference output keys [wrong_key, wrong_label] are unsupported. "
+        "The supported inference keys are [probability, probabilities, predicted_label, labels]"
+    )
+    assert message in str(excinfo.value)
 
 
 def test_create_model(sagemaker_session):

tests/unit/test_image.py

@@ -370,7 +370,7 @@ def test_train(
             assert call_args[i] == v
 
         with open(docker_compose_file, "r") as f:
-            config = yaml.load(f)
+            config = yaml.load(f, Loader=yaml.SafeLoader)
             assert len(config["services"]) == instance_count
             for h in sagemaker_container.hosts:
                 assert config["services"][h]["image"] == image
@@ -419,7 +419,7 @@ def test_train_with_hyperparameters_without_job_name(
         )
 
         with open(docker_compose_file, "r") as f:
-            config = yaml.load(f)
+            config = yaml.load(f, Loader=yaml.SafeLoader)
             for h in sagemaker_container.hosts:
                 assert (
                     "TRAINING_JOB_NAME={}".format(TRAINING_JOB_NAME)
@@ -491,7 +491,7 @@ def test_train_local_code(get_data_source_instance, tmpdir, sagemaker_session):
         shared_folder_path = os.path.join(sagemaker_container.container_root, "shared")
 
         with open(docker_compose_file, "r") as f:
-            config = yaml.load(f)
+            config = yaml.load(f, Loader=yaml.SafeLoader)
             assert len(config["services"]) == instance_count
 
         for h in sagemaker_container.hosts:
@@ -543,7 +543,7 @@ def test_train_local_intermediate_output(get_data_source_instance, tmpdir, sagem
         intermediate_folder_path = os.path.join(output_path, "output/intermediate")
 
         with open(docker_compose_file, "r") as f:
-            config = yaml.load(f)
+            config = yaml.load(f, Loader=yaml.SafeLoader)
             assert len(config["services"]) == instance_count
             for h in sagemaker_container.hosts:
                 assert config["services"][h]["image"] == image
@@ -596,7 +596,7 @@ def test_serve(tmpdir, sagemaker_session):
         )
 
         with open(docker_compose_file, "r") as f:
-            config = yaml.load(f)
+            config = yaml.load(f, Loader=yaml.SafeLoader)
 
             for h in sagemaker_container.hosts:
                 assert config["services"][h]["image"] == image
@@ -624,7 +624,7 @@ def test_serve_local_code(tmpdir, sagemaker_session):
         )
 
         with open(docker_compose_file, "r") as f:
-            config = yaml.load(f)
+            config = yaml.load(f, Loader=yaml.SafeLoader)
 
             for h in sagemaker_container.hosts:
                 assert config["services"][h]["image"] == image
@@ -657,7 +657,7 @@ def test_serve_local_code_no_env(tmpdir, sagemaker_session):
         )
 
         with open(docker_compose_file, "r") as f:
-            config = yaml.load(f)
+            config = yaml.load(f, Loader=yaml.SafeLoader)
 
             for h in sagemaker_container.hosts:
                 assert config["services"][h]["image"] == image

tox.ini

@@ -51,6 +51,12 @@ ignore-path=.tox,src/sagemaker.egg-info
 # TODO: fix files before enabling max-line-length (D001)
 ignore=D001
 
+[pytest]
+markers =
+    canary_quick
+    cron
+    local_mode
+
 [testenv]
 passenv =
     AWS_ACCESS_KEY_ID