Diversify recommends the latest tracks from any country around the world using the KNN algorithm. It displays personalized recommendations based on a user's music taste.
SpotifyRecommenderPreview.mp4
I wanted to find songs that I liked that were popular in other countries. So, I built a web app using Flask (backend) and React (frontend). The website is live at https://faizaanvidhani.github.io/spotify-recommender/. Since Heroku has ended its free tier, the backend has not been deployed. However, a demo of the web app using the local development server is shown above.
Instructions for setting up and running this web application:
- Clone the repository. Setup and activate a virtual environment in the server directory. Install dependencies.
- To create a virtual env:
python3 -m venv <name-of-virtual-environment> - To activate virtual env:
source <name-of-virtual-environment>/bin/activate - To install dependencies:
pip install -r requirements.txt
- Starting the web application
- To start the client: Navigate to the client directory. Execute
npm run start - To start the server: Navigate to the server directory. Execute
flask run. Alternatively, navigate to the client directory. Executenpm run start-server