Inspiration

Inspired by Spotify trends and our shared love for music, we decided to do this project because it would encourage others to broaden their music tastes.

What it does

Waverider takes information about your playlists from Spotify and recommends music to you based on your taste, as well as encouraging you to explore new genres of music with use of a similarity algorithm. It also gives you your music information components in the form of a graph.

How we built it

Using React Native with Typescript for front-end, Spotify API for user authentication and playlist information, and a machine learning algorithm.

Challenges we ran into

User authentication was the biggest problem we ran into because of the difficulty of setting up a token system. In the future, we hope to use passport.js to mitigate this issue. On the front-end, it was a bit slow to get used to React. Another problem we ran into was using Git, as a few of our team members had difficulty cloning and creating branches as well as pushing to the repository. Finally, time was one of our biggest enemies in succeeding because of how short of a time we had to make a rather large project.

Accomplishments that we're proud of

Our UI came out to be just what we wanted, and reflected our mockup decently well. The algorithm also worked excellently.

What we learned

On front-end, we learned so much about front-end work and UI and how to use React Native's tools to successfully create a multi-platform application. We learned much from our mistakes with regards to user authentication and database functions and adapted as we implemented these technologies.

What's next for WaveRider

A subscription-based plan for DJs and party planners to view their area's most popular songs, and an in-app authentication system with Firebase's database to use alongside Spotify's authentication.

Share this project:

Updates