Coverage report and related files finalized

test_main.py

@@ -3,6 +3,7 @@ import sentiment
 from sentiment import get_tokens, score_compute, save_stop_words
 import os
 
+
 class TestGetTokens(unittest.TestCase):
 
     # creates file path to sentiment.txt file
@@ -47,8 +48,10 @@ class TestGetTokens(unittest.TestCase):
 
         manual_count = sum(1 for token in self.review_tokens_list if token == target_token)
 
-        self.assertEqual(manual_count, expected_count, f"Expected {expected_count} occurrences of '{target_token}', but got {manual_count}.")
-        print(f"""\nTest 2 - Word Frequencies: \nThe training data contains {manual_count} appearances of the token "too".""")
+        self.assertEqual(manual_count, expected_count,
+                         f"Expected {expected_count} occurrences of '{target_token}', but got {manual_count}.")
+        print(
+            f"""\nTest 2 - Word Frequencies: \nThe training data contains {manual_count} appearances of the token "too".""")
 
     def test_03_token_statistics(self):
         target_token = "too"
@@ -162,7 +165,8 @@ class TestGetTokens(unittest.TestCase):
         avg_score = total_score / valid_tokens if valid_tokens > 0 else 0
 
         self.assertAlmostEqual(avg_score, expected_score, places=10, msg="Incorrect average tf-idf score for sentence.")
-        print(f'\nTest 7 - Sentence Statistics Score: \nThe sentence "{target_sentence}" has an average tf-idf score of {avg_score}.')
+        print(
+            f'\nTest 7 - Sentence Statistics Score: \nThe sentence "{target_sentence}" has an average tf-idf score of {avg_score}.')
 
     def test_08_save_stop_words(self):
         save_stop_words(self.negative_reviews_list, self.neutral_reviews_list, self.positive_reviews_list)
@@ -263,8 +267,8 @@ class TestGetTokens(unittest.TestCase):
 
         self.assertAlmostEqual(avg_score, expected_avg_tfidf, places=5, msg="Incorrect adjusted average tf-idf score.")
 
-        print(f'\nTest 10 - Non-Stop-Words Statistics Score: \nThe sentence "{target_sentence}" has an adjusted average tf-idf score of {avg_score}.')
-
+        print(
+            f'\nTest 10 - Non-Stop-Words Statistics Score: \nThe sentence "{target_sentence}" has an adjusted average tf-idf score of {avg_score}.')
 
 
 if __name__ == '__main__':