Delete test_main.py

test_main.py

@@ -1,70 +0,0 @@
-from fastapi.testclient import TestClient
-from main import app
-from main import TextInput
-from fastapi.encoders import jsonable_encoder
-
-client = TestClient(app)
-
-# Test the welcome endpoint
-def test_welcome():
-    # Test the welcome endpoint
-    response = client.get("/")
-    assert response.status_code == 200
-    assert response.json() == "Welcome to our Text Classification API"
-
-# Test the sentiment analysis endpoint for positive sentiment
-def test_positive_sentiment():
-    with client:
-        # Define the request payload 
-        # Initialize payload as a TextInput object
-        payload = TextInput(text="I love this product! It's amazing!")
-
-        # Convert TextInput object to JSON-serializable dictionary
-        payload_dict = jsonable_encoder(payload)
-        
-        # Send a POST request to the sentiment analysis endpoint
-        response = client.post("/analyze/{text}", json=payload_dict)
-
-        # Assert that the response status code is 200 OK
-        assert response.status_code == 200
-        
-        # Assert that the sentiment returned is positive
-        assert response.json()[0]['label'] == "positive"
-
-# Test the sentiment analysis endpoint for negative sentiment
-def test_negative_sentiment():
-    with client:
-        # Define the request payload 
-        # Initialize payload as a TextInput object
-        payload = TextInput(text="I'm really disappointed with this service. It's terrible.")
-
-        # Convert TextInput object to JSON-serializable dictionary
-        payload_dict = jsonable_encoder(payload)
-        
-        # Send a POST request to the sentiment analysis endpoint
-        response = client.post("/analyze/{text}", json=payload_dict)
-
-        # Assert that the response status code is 200 OK
-        assert response.status_code == 200
-        
-        # Assert that the sentiment returned is positive
-        assert response.json()[0]['label'] == "negative"
-
-# Test the sentiment analysis endpoint for neutral sentiment
-def test_neutral_sentiment():
-    with client:
-        # Define the request payload 
-        # Initialize payload as a TextInput object
-        payload = TextInput(text="This is a neutral statement.")
-
-        # Convert TextInput object to JSON-serializable dictionary
-        payload_dict = jsonable_encoder(payload)
-        
-        # Send a POST request to the sentiment analysis endpoint
-        response = client.post("/analyze/{text}", json=payload_dict)
-
-        # Assert that the response status code is 200 OK
-        assert response.status_code == 200
-        
-        # Assert that the sentiment returned is positive
-        assert response.json()[0]['label'] == "neutral"