Inspiration

We wanted to expose people up to different genres of music based on existing music tastes. We also wanted this process to be fast and efficient so that way more people can discover new music faster.

What it does

The app analyzes your Spotify playlists and the music you saved in those playlists by energy, mood, pace, etc. and generates classical music that correlates to your tastes. The app suggests 10 suggested classical tracks, giving 30 seconds of each track for the users sampling. Apart from the playback feature, the app also gives snippets of information about the suggested song and allows one to save it to a new Playlist on their own Spotify if they so choose.

How we built it

We utilized python, flask, css, html, aws, amazon-web-services

Challenges we ran into

aws was a challenge

Accomplishments that we're proud of

the complete Spotify authentication homepage being able to save the songs into your actual Spotify

What we learned

What's next for Spotifind

Conducting the same analyzation process and execution for different genres

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