Codes converted to PEP-8 model

.deepsource.toml

@@ -0,0 +1,12 @@
+version = 1
+
+[[analyzers]]
+name = "python"
+enabled = true
+
+  [analyzers.meta]
+  runtime_version = "3.x.x"
+
+[[transformers]]
+name = "autopep8"
+enabled = true

app.py

@@ -5,15 +5,17 @@
 app = Flask(__name__)
 app.static_folder = 'static'
 
+
 @app.route("/")
 def home():
     return render_template("index.html")
 
+
 @app.route("/get")
 def get_bot_response():
     userText = request.args.get('msg')
     return str(chatbot.get_response(userText))
 
 
 if __name__ == "__main__":
-    app.run()
+    app.run()

chatbot.py

@@ -1,3 +1,5 @@
+from chatterbot.trainers import ChatterBotCorpusTrainer
+from chatterbot.trainers import ListTrainer
 from chatterbot import ChatBot
 
 chatbot = ChatBot(
@@ -9,27 +11,26 @@
         'chatterbot.logic.BestMatch',
         {
             'import_path': 'chatterbot.logic.BestMatch',
-            'default_response': 'I am sorry, but I do not understand. I am still learning.',
+            'default_response': 'I am sorry, but I do not understand.\
+I am still learning.',
             'maximum_similarity_threshold': 0.90
         }
     ],
     database_uri='sqlite:///database.sqlite3'
 )
 
-# Training With Own Questions 
-from chatterbot.trainers import ListTrainer
-
+# Training With Own Questions
 trainer = ListTrainer(chatbot)
 
 training_data_quesans = open('training_data/ques_ans.txt').read().splitlines()
-training_data_personal = open('training_data/personal_ques.txt').read().splitlines()
+training_data_personal = open(
+    'training_data/personal_ques.txt').read().splitlines()
 
 training_data = training_data_quesans + training_data_personal
 
 trainer.train(training_data)
 
 # Training With Corpus
-from chatterbot.trainers import ChatterBotCorpusTrainer
 
 trainer_corpus = ChatterBotCorpusTrainer(chatbot)