LocoListen

Inspiration

The main inspiration for this project is that we wanted to find a new way to connect people through music.

What it does

Users can upload songs, playlists, and albums that they want to share with others around them using Spotify. Users can also see what people are listening to around them based on what other people have uploaded.

How we built it

Using streamlit, we created the user interface including the map as well as the various buttons to upload and view music. We used gsheetsdb to use a google sheet as the way we stored songs, playlists, and their corresponding location.

Challenges we ran into

A problem that we ran into was storing the data in a meaningful and efficient way. In order to efficiently go through our data points, we didn't want to loop through every data point across the US that was in our database, so we created multiple(8) databases that corresponded with longitude and latitude ranges. Then we used a dictionary to get what database to query.

Accomplishments that we're proud of

One of the accomplishments that we're proud of is the interactive map that displays the songs being recommended to users, along with their corresponding locations. Another aspect we're proud of is properly accessing, storing, and keeping track of the location of user-entered music.

What we learned

Some of the things we learned were how to connect front-end streamlit framework and back-end databases using SQLite, effectively use numpy and pandas frameworks for map display, and gsheetsdb for database hosting.

What's next for LocoListen

Through Spotify's built-in location feature, which we don't have access to, Spotify themselves could allow users to do this in-app. They could also automatically upload things like the current song that is playing to the map. Using the music trends that Spotify collects, they could release an interactive map that shows the most popular songs, genres, etc. all based on location.