Track Nearest Neighbors Classifier

The purpose of this script is to implement a basic K Nearest Neighbors Classifier using an audio summary generated from Echonest. We can then classify new tracks using their audio summary and it's nearest neighbors.

Install Dependencies

pip install -r requirements.txt

Setup

Relies on the track data generated from Spotify and Echonest in the format created using this script.

Add Environment Variables for Spotify/Echonest API's

This is used for the new track being classified.

export SPOTIPY_CLIENT_ID='your-spotify-client-id'
export SPOTIPY_CLIENT_SECRET='your-spotify-client-secret'
export SPOTIPY_REDIRECT_URI='http://localhost'
export ECHO_NEST_API_KEY='your-echonest-api-key'

Run the script

• python main.py <spotify-uri> <n-training-data> <n_neighbors>
  • spotify-uri (required): the Spotify URI of the track to classify
  • n-training-data (optional): the total number of tracks to use as training data
  • n_neighbors (optional): the number of neighbors to classify with
• Spotify Authentication will open in your default browser (first time only)
• Grant Access
• Copy the URL to the terminal when prompted (contains the Spotify code)
• The track will be classified using existing track data from this script)