Final Project

An exercise to put to practice software development teamwork, subsystem communication, containers, deployment, and CI/CD pipelines. See instructions for details.

Project Description

A customer feedback system that collects feedbacks and classifies into positive and negative groups. Display the positive and negative feedbacks separately. This project uses Flask as framework, evolves a machine learning subsystem that classifies feedbacks and MongoDb that helps with data processing.

Setting Up the Database

Prerequisites

• Ensure that MongoDB is installed and running on your local machine.
• Python and pymongo should be installed in your Python environment.

Steps to Set Up the Database

1. Run the db_setup.py Script: Navigate to the mongodb-database directory and run the db_setup.py script. This script will create two collections (users and feedback) in the customer_feedback_db database and insert some initial data into these collections.

   cd mongodb-database
   python db_setup.py
   

Link to images on Docker Hub

separate image for each subsystem

Run the Software

Make sure to run app.py as a python module to make sure the paths can be retrieved normally

   python -m flask-app.app