As students, we often find ourselves connecting our Spotify playlists to speakers, be it during pre's or for a regular friday chill sesh.. However, deciding who gets to connect their music to the speaker is often a struggle that can only end in others regretting the person in charge of the playlist. This incited us to create an app that makes music listening that much more enjoyable and effortless.

What it does

This IOS app connects with the users' Spotify accounts, allowing them to manage which of their playlists they wish to share. When the users are connected, the 'master' user will create a group, allowing others to join it by inputing a specific group name. Once the group is created, the app will automatically scan the 'shared' Spotify playlists of each user to generate songs that aim to please as many people as possible.

After a group is created, it will be stored in each user's existing groups, allowing them to reconnect to that group the next day or the next month if they wish.

How we built it

Node.js was used for the backend along with the Sequelize ORM to create the server and to connect to a SQLite database server.

For the front-end, Xcode was used with Swift to provide the user interface of the app that connects to the server. It implements Spotify's API in order to get user data (including username to login, and playlists).

Challenges we ran into

Using Spotify's API was a bigger challenge that we expected, in particular to extract the specific data we needed. We initially intended to do an Android app, but then decided it would be better to focus on a single product to deliver the best end product we could.

Accomplishments that we're proud of

The app compiles! On a more serious note, getting all the Spotify user data to coordinate with the server and the app as we wanted was satisfying.

What we learned

This was our first experience using XCode, so we definitely learnt a lot about it. At the same time, we played around with apps connecting to network servers and figuring out how to save user data to a network server we created. Another major aspect we benefited from was interacting with APIs to create this app

What's next for Multiplier

We have the following ambitions for Multiplier:

  • develop an even more efficient algorithm that uses AI to generate similar artist or songs to the ones in a group's users' playlists (using Spotify or Last FM's API for example)
  • extend it to other patforms such as Android
  • add an option for the user to save group playlists if he wishes, or save particular songs he discovered
  • add an option to modify your shared Playlists once you're logged in
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