MusiqParti

You bring the music. We bring the party

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💡 Inspiration

Ever wanted a platform to find playlists with music similar to yours? Wouldn't it be cool to easily connect and talk with other Spotify users with similar tastes? MusiqParti offers a digital platform for you to do just that!

🔎 What it does

Login with your Spotify account and choose your favourite playlist. This playlist will analyze to match you and other similar users. Once matched with users, you can view their profile along with all their playlists!

🔧 How we built it

Frontend: Next.js + React + Chakra UI

Backend/Cloud: Node.js/Express + MongoDB

External APIs: SpotifyAPI

Design and UI: Figma

🛑 Challenges we ran into

  • The SpotifyAPI had a low request limit, which heavily interfered with our original plan of using the internal API to implement the matching algorithm for users based on playlists
  • The SpotifyAPI didn't have a request call for analyzing an entire playlist, the only makeshift way to do so is to analyze all the songs in the track one at a time and return the average of the result
  • Trying to get SpotifyAPI authentication to work with the frontend was a challenge. Especially considering how the auth URL was inconsistent throughout the development
  • It was most of the team's first time developing a client using Next.js + Chakra, despite it all, the team learned a lot during the experience and built a slick frontend.
  • Because an external API was used, the .env files would change often, sometimes causing unneeded confusion and downtime.
  • Due to everyone's busy schedule, it was hard to meet up on a regular basis.

✅ Accomplishments that we're proud of

  • Building a full-featured frontend despite being the team's first time using new tools (Next.js + Chakra)
  • Integrating SpotifyAPI with the frontend and database

📖 What we learned

  • How to integrate the SpotifyAPI into a full-stack application
  • How to use Next.js + Chakra to build a slick UI
  • How to integrate a database with existing data (Spotify playlist/user data)

💭 What's next for MusiqParti

  • Better matching algorithms! Due to the lack of time, the current matching algorithm is not too practical. By using data analytics with machine learning models, the algorithm can be improved.
  • User trending page to see popular users within MusiqParti
  • Follow users and connect with people within the platform!
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