Merge branch 'master' into 'IT19079264'

Master

See merge request !105

backend/services/class_diagram_generation_service.py

@@ -53,7 +53,7 @@ def generate_diagram(filename):
         print(Exception)
 
 
-# generate python file for the class
+# generate python file for the class (pyreverse)
 def generate_class(actors, data):
     res = create_class_methods(data)
     class_string_arr = generate_class_string_array(actors, res)

backend/services/question_preprocess_service.py

@@ -11,15 +11,10 @@ def remove_unwanted_values(data):
     return data
 
 
-# removing duplicates
-def remove_duplicates(data):
-    return list(set(data))
-
-
-# punctuation removal
+# punctuation removing
 def remove_punctuation(sentence):
-    text_no_punct = [token for token in sentence if not token.is_punct]
-    cleaned_sentence = ' '.join(token.text for token in text_no_punct)
+    text_without_punctuation = [token for token in sentence if not token.is_punct]
+    cleaned_sentence = ' '.join(token.text for token in text_without_punctuation)
     return cleaned_sentence
 
 
@@ -37,44 +32,45 @@ def main(scenario, assignment_type):
     del sentences[-1]
 
     # creating required lists
-    nc = []
+    nouns_pronouns = []
     cleaned_extracted_actions = []
     cleaned_sentences = []
-    splitted_actions_array = []
+    splitted_actions_and_actor_array = []
 
     # looping through each sentence
     for sentence in sentences:
+        # getting actors using nouns pronouns
         res = get_nouns_pronouns(sentence)
-        nc.append(str(res))
+        nouns_pronouns.append(str(res))
         cleaned_sentence = remove_punctuation(sentence)
         cleaned_sentences.append(cleaned_sentence)
 
-        splitted_actions = split_actions(str(cleaned_sentence))
-        splitted_actions_array.append(splitted_actions)
+        splitted_actions_and_actor = split_actions(str(cleaned_sentence))
+        splitted_actions_and_actor_array.append(splitted_actions_and_actor)
 
-        extracted_actions = get_actions(splitted_actions)
+        extracted_actions = get_actions(splitted_actions_and_actor)
 
         if extracted_actions is not None:
             cleaned_extracted_actions.append(extracted_actions)
 
     # remove duplicates of the actors
-    nc = list(dict.fromkeys(nc))
-    data = remove_unwanted_values(nc)
+    nouns_pronouns = list(dict.fromkeys(nouns_pronouns))
+    actors = remove_unwanted_values(nouns_pronouns)
 
-    extracted_relationships = get_include_extend_relationships(splitted_actions_array)
+    extracted_relationships = get_include_extend_relationships(splitted_actions_and_actor_array)
     actors_and_use_cases_array = identify_use_cases(cleaned_extracted_actions)
 
     if assignment_type == 1:
-        generated_usecase_diagram_path = generate_use_case_diagram(data, extracted_relationships,
+        generated_usecase_diagram_path = generate_use_case_diagram(actors, extracted_relationships,
                                                                    actors_and_use_cases_array)
         return generated_usecase_diagram_path
 
     elif assignment_type == 2:
-        generated_class_diagram_path = generate_class(data, cleaned_extracted_actions)
+        generated_class_diagram_path = generate_class(actors, cleaned_extracted_actions)
         return generated_class_diagram_path
 
     elif assignment_type == 3:
-        generated_class_diagram_path = generate_class(data, cleaned_extracted_actions)
-        generated_usecase_diagram_path = generate_use_case_diagram(data, extracted_relationships,
+        generated_class_diagram_path = generate_class(actors, cleaned_extracted_actions)
+        generated_usecase_diagram_path = generate_use_case_diagram(actors, extracted_relationships,
                                                                    actors_and_use_cases_array)
         return generated_class_diagram_path, generated_usecase_diagram_path

backend/services/tokenization_service.py

@@ -24,12 +24,14 @@ def get_nouns_pronouns(sentence):
             return token
 
 
+# removing punctuations
 def remove_punctuation(sentence):
     text_no_punct = [token for token in sentence if not token.is_punct]
     cleaned_sentence = ' '.join(token.text for token in text_no_punct)
     return cleaned_sentence
 
 
+# get actions and actors
 def split_actions(sentence):
     split_string = "should be able to "
     if split_string in sentence:
@@ -37,16 +39,18 @@ def split_actions(sentence):
         return extracted_string
 
 
-def get_actions(splitted_action):
+# get
+def get_actions(splitted_action_and_actor):
     temp_array = []
-    if splitted_action is not None and '|' in splitted_action[1]:
-        res = splitted_action[1].split(' | ')
-        # print('res',res)
-        temp_array.append(splitted_action[0])
+    if splitted_action_and_actor is not None and '|' in splitted_action_and_actor[1]:
+        res = splitted_action_and_actor[1].split(' | ')
+
+        temp_array.append(splitted_action_and_actor[0])
         temp_array.append(res[0])
+        print(temp_array)
         return temp_array
     else:
-        return splitted_action
+        return splitted_action_and_actor
 
 
 def get_sentences(text):