We wanted to expand the domain of what Spotify currently provides to its user, and we decided to use 'which songs are being heard by who at which place'.

What it does

As we know, the music of an area contributes to its general atmosphere and ambiance; the use case we have envisioned for our app is that it will provide public places (such as bars, cafes, restaurants etc.) the platform and the ability to do this.

The app shows a map with local users and their spotcasted playlists.

How We built it

We used the Spotify Web API to get user's Spotify data. Our app starts with logging-in the user with their Spotify credentials. We used the phone's location feature to allow them to SpotCast a playlist of their choice and this get's pushed to our backend.

The backend stores the user's SpotCast in an SQL table. This table is the basis for all SpotCasts on our map (which is loadable for each user in-sync).

Challenges I ran into

To integrate Spotify's API with Google Maps API in a clean and scalable manner.

Accomplishments that I'm proud of

We achieved our target for a Minimal Viable Product. Moreover, the idea we came up with was backed enthusiastically by every team member and everyone could see it's real world use-cases.

What I learned

We learned how to setup an AWS server for our Flask API. In addition, we learned how to integrate location based data into existing tools.

What's next for SpotCast

The app we built has a number of possible extensions, such as more interactive collaborative queues, localized trend analysis and a step towards creating a more open and social music-sharing platform.

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