Champaign Coffee Matcher is a Flask web application that recommends the best coffee for University of Illinois at Urbana-Champaign (UIUC) students.
The app scrapes data from coffee shop menus in Champaign (see coffee_data
) then stores the data into a database (see db.py
) and uses a matching algorithm to give personalized recommendations based on the user's preferences as described in algo-sketch.md.
Furthermore, users can rate the coffee and provide site feedback to help improve the recommendations.
- Flask
- Beautiful Soup (data webscraping)
- SQLite + SQLAlchemy
- Classic HTML/CSS/Javascript (frontend)
- Danny Kim (backend/algo implementation)
- Eyad Loutfi (frontend/algo implementation)
- Minhyung Lee (database/backend)
- Monica Para (frontend/web scraping)
https://mediaspace.illinois.edu/media/t/1_aipil0f2
To run the project locally on your machine, make a copy of the repo in your terminal as
git clone https://github.com/CS222-UIUC/course-project-champaign-coffee
Install any necessary Python libraries and flask run
to run the server locally as http://127.0.0.1:5000
/
- landing page/discover
- questionnaire for coffee selection/coffee_shops
- view all Champaign coffee shops with toggle-able details/browse_coffees
- browse all available items and view which shops offer them/ratings
- select coffee shop and give feedback out of 5/submit_rating
- coffee shop review submitted and stored in db/feedback
- allows users to provide feedback on the site in general/submit-feedback
- site feedback submitted