Smiskify

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One of our Smiski Results
One of our Smiski Results
One of our Smiski Results

Inspiration

What it does

The web application uses the Spotify API to analyze your top songs of the last 6 months to determine what personality-based Smiski matches your music taste! Intaking the song attributes of your top listens, we assign you a Smiski based on your most defining feature from your music. It is our unique approach to building a data visualizer from Spotify.

How we built it

We built a web application by integrating the Spotify API into a Flask web application framework that host and creates a custom server. This holds a RESTFUL API of our request and responses. OAuth 2.0 is utilized to proxy user log-ins from Spotify, allowing us to collect listening data from users. Used current session to retrieve an access token and write code to refresh that token from the Spotify API.

Challenges we faced

Spotify's API requires users to request for an extension on their application that allows users that aren't manually added to be able to access the application. Thus, we won't immediately be able to allow the program to be used by others until our extension request is approved.

What we learned

Flask was a brand new web application for team, and it was interesting to apply its functions to our program. In addition our project offered extensive practice with handling and parsing JSON files, which we prior did not have much experience with.

What's next for Smiskify

If Smiskify were to continue development, we would diversify the personality classification, factoring in additional filtering for top artists, genres, etc. Adding a feature to share data to friends and family would also be another goal with our web application. Lastly would probably or recruit a better designer/drawer for our Smiski personas (we do not claim to be good drawers T-T).