fix fixture naming and use

automl/cloud-client/delete_dataset_test.py

@@ -25,7 +25,7 @@
 
 
 @pytest.fixture(scope="function")
-def create_dataset():
+def dataset_id():
     client = automl.AutoMlClient()
     project_location = client.location_path(PROJECT_ID, "us-central1")
     display_name = "test_" + datetime.datetime.now().strftime("%Y%m%d%H%M%S")
@@ -39,8 +39,8 @@ def create_dataset():
     yield dataset_id
 
 
-def test_delete_dataset(capsys, create_dataset):
+def test_delete_dataset(capsys, dataset_id):
     # delete dataset
-    delete_dataset.delete_dataset(PROJECT_ID, create_dataset)
+    delete_dataset.delete_dataset(PROJECT_ID, dataset_id)
     out, _ = capsys.readouterr()
     assert "Dataset deleted." in out

automl/cloud-client/get_model_evaluation_test.py

@@ -24,7 +24,7 @@
 
 
 @pytest.fixture(scope="function")
-def get_evaluation_id():
+def model_evaluation_id():
     client = automl.AutoMlClient()
     model_full_id = client.model_path(PROJECT_ID, "us-central1", MODEL_ID)
     evaluation = None
@@ -37,9 +37,9 @@ def get_evaluation_id():
     yield model_evaluation_id
 
 
-def test_get_model_evaluation(capsys, get_evaluation_id):
+def test_get_model_evaluation(capsys, model_evaluation_id):
     get_model_evaluation.get_model_evaluation(
-        PROJECT_ID, MODEL_ID, get_evaluation_id
+        PROJECT_ID, MODEL_ID, model_evaluation_id
     )
     out, _ = capsys.readouterr()
     assert "Model evaluation name: " in out

automl/cloud-client/get_operation_status_test.py

@@ -23,7 +23,7 @@
 
 
 @pytest.fixture(scope="function")
-def get_operation_id():
+def operation_id():
     client = automl.AutoMlClient()
     project_location = client.location_path(PROJECT_ID, "us-central1")
     response = client.transport._operations_client.list_operations(
@@ -36,7 +36,7 @@ def get_operation_id():
     yield operation_id
 
 
-def test_get_operation_status(capsys, get_operation_id):
-    get_operation_status.get_operation_status(get_operation_id)
+def test_get_operation_status(capsys, operation_id):
+    get_operation_status.get_operation_status(operation_id)
     out, _ = capsys.readouterr()
     assert "Operation details" in out

automl/cloud-client/import_dataset_test.py

@@ -25,7 +25,7 @@
 
 
 @pytest.fixture(scope="function")
-def create_dataset():
+def dataset_id():
     client = automl.AutoMlClient()
     project_location = client.location_path(PROJECT_ID, "us-central1")
     display_name = "test_" + datetime.datetime.now().strftime("%Y%m%d%H%M%S")
@@ -42,19 +42,19 @@ def create_dataset():
 
 
 @pytest.mark.slow
-def test_import_dataset(capsys, create_dataset):
+def test_import_dataset(capsys, dataset_id):
     data = (
         "gs://{}/sentiment-analysis/dataset.csv".format(BUCKET_ID)
     )
-    dataset_id = create_dataset
-    import_dataset.import_dataset(PROJECT_ID, dataset_id, data)
+    created_dataset_id = dataset_id
+    import_dataset.import_dataset(PROJECT_ID, created_dataset_id, data)
     out, _ = capsys.readouterr()
     assert "Data imported." in out
 
     # delete created dataset
     client = automl.AutoMlClient()
     dataset_full_id = client.dataset_path(
-        PROJECT_ID, "us-central1", dataset_id
+        PROJECT_ID, "us-central1", created_dataset_id
     )
     response = client.delete_dataset(dataset_full_id)
     response.result()

automl/cloud-client/language_sentiment_analysis_predict_test.py

@@ -23,8 +23,9 @@
 MODEL_ID = os.environ["SENTIMENT_ANALYSIS_MODEL_ID"]
 
 
-@pytest.fixture(scope="function")
-def verify_model_state():
+@pytest.fixture(scope="function", autouse=True)
+def setup():
+    # Verify the model is deployed before trying to predict
     client = automl.AutoMlClient()
     model_full_id = client.model_path(PROJECT_ID, "us-central1", MODEL_ID)
 
@@ -35,8 +36,7 @@ def verify_model_state():
         response.result()
 
 
-def test_predict(capsys, verify_model_state):
-    verify_model_state
+def test_predict(capsys):
     text = "Hopefully this Claritin kicks in soon"
     language_sentiment_analysis_predict.predict(PROJECT_ID, MODEL_ID, text)
     out, _ = capsys.readouterr()

automl/cloud-client/translate_predict_test.py

@@ -23,8 +23,9 @@
 MODEL_ID = os.environ["TRANSLATION_MODEL_ID"]
 
 
-@pytest.fixture(scope="function")
-def verify_model_state():
+@pytest.fixture(scope="function", autouse=True)
+def setup():
+    # Verify the model is deployed before trying to predict
     client = automl.AutoMlClient()
     model_full_id = client.model_path(PROJECT_ID, "us-central1", MODEL_ID)
 
@@ -35,8 +36,7 @@ def verify_model_state():
         response.result()
 
 
-def test_predict(capsys, verify_model_state):
-    verify_model_state
+def test_predict(capsys):
     translate_predict.predict(PROJECT_ID, MODEL_ID, "resources/input.txt")
     out, _ = capsys.readouterr()
     assert "Translated content: " in out

automl/cloud-client/vision_classification_predict_test.py

@@ -23,8 +23,9 @@
 MODEL_ID = os.environ["VISION_CLASSIFICATION_MODEL_ID"]
 
 
-@pytest.fixture(scope="function")
-def verify_model_state():
+@pytest.fixture(scope="function", autouse=True)
+def setup():
+    # Verify the model is deployed before tyring to predict
     client = automl.AutoMlClient()
     model_full_id = client.model_path(PROJECT_ID, "us-central1", MODEL_ID)
 
@@ -35,8 +36,7 @@ def verify_model_state():
         response.result()
 
 
-def test_vision_classification_predict(capsys, verify_model_state):
-    verify_model_state
+def test_vision_classification_predict(capsys):
     file_path = "resources/test.png"
     vision_classification_predict.predict(PROJECT_ID, MODEL_ID, file_path)
     out, _ = capsys.readouterr()