black and linted

machine-learning-client/machine_learning_client.py

@@ -1,49 +1,60 @@
+"""
+Machine Learning python file providing conversion of audio 
+to text transcription and analysis of audio transcription
+"""
 import os
-from pymongo import MongoClient
-import pymongo
 import datetime
+import sys
+import pymongo
+from pymongo import MongoClient
 import pyaudio
 import speech_recognition as sr
-import sys
 
 r = sr.Recognizer()
 pa = pyaudio.PyAudio()
-def listAllMic():
+
+
+def list_all_mic():
     """
     List all available microphone device
     """
-    if (len(sr.Microphone.list_microphone_names()) == 0):
+    if len(sr.Microphone.list_microphone_names()) == 0:
         print("no device available")
         return
-    
+
     for index, name in enumerate(sr.Microphone.list_microphone_names()):
-        print("Microphone with name \"{1}\" found for `Microphone(device_index={0})`".format(index, name))
+        print(f'Microphone with name "{name}"')
+        print(f" found for `Microphone(device_index={index})`")
+
 
 def record_microphone():
-    listAllMic()                 #Use for debug
+    """Function for recording microphone input"""
+    list_all_mic()  # Use for debug
     mc = None
     try:
         mc = sr.Microphone()
         print("Mic init successful")
     except OSError:
         mc = sr.Microphone(0)
         print("no default mic")
-
-
     with mc as source:
         print("Please give your answer:")
         audio = r.listen(source)
     return audio
 
+
 def audio_to_text(audio):
+    """Function for converting audio file to text transcription"""
     try:
         transcription = r.recognize_google(audio)
         print(transcription)
         print(type(transcription))
     except sr.UnknownValueError:
         print("Sorry, we could not recognize your response.")
-    except sr.RequestError as e:
+    except sr.RequestError:
         print("Sorry, there appears to be an error with Google Speech to Text")
+    return transcription
+
 
 def grade_response(transcription):
     """
@@ -54,13 +65,18 @@ def grade_response(transcription):
         transcription (str): transcribed audio
     """
     print("working on it...")
-
+    grade = transcription
+    return grade
+
 
 def main():
+    """Main Method"""
     print("Tell me a little bit about yourself")
     audio = record_microphone()
     transcription = audio_to_text(audio)
     result = grade_response(transcription)
+    print(result)
+
 
 if __name__ == "__main__":
-    main()
+    main()

web-app/app.py

@@ -1,21 +1,35 @@
-from flask import Flask, render_template, request, redirect, url_for, make_response, session
+"""Module designed to supplement front end webpage"""
 import os
+import datetime
+import sys
+from flask import (
+    Flask,
+    render_template,
+    request,
+    redirect,
+    url_for,
+    make_response,
+    session,
+)
 from pymongo import MongoClient
 import pymongo
-import datetime
 from bson.objectid import ObjectId
-import sys
 
-app = Flask('project4')
+app = Flask("project4")
 
-@app.route('/')
-def RootPage():
-    return render_template('root.html')
 
-@app.route('/anaylzeData', methods=['POST'])
-def anaylzeData():
+@app.route("/")
+def root_page():
+    """Root page route"""
+    return render_template("root.html")
+
+
+@app.route("/analyze_data", methods=["POST"])
+def anaylze_data():
+    """Analyze data by sending it to the ml client"""
     return
 
+
 if __name__ == "__main__":
-    PORT = os.getenv('PORT', 5000) 
-    app.run(debug=True,port=PORT)
+    PORT = os.getenv("PORT", 5000)
+    app.run(debug=True, port=PORT)

web-app/requirements.txt

@@ -0,0 +1,2 @@
+flask
+pymongo