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A web application that allows users to track and analyze their Spotify listening habits and statistics without Spotify Premium.
- View your top songs.
- View your top artists.
- See your listening history.
- Track your spotify recently listened in real time
- Import Spotify data export
- Import musicolet pro exports
- Automatically import files in the 'auto-import folder' with optional filtering
- Clone the repository:
git clone https://github.com/TzurSoffer/SpotifyStatsTracker
cd SpotifyStatsTracker- Install dependencies:
pip install -r requirements.txtUse this docker-compose file:
version: '3.8'
services:
spotify-tracker:
image: mepro3/spotify-tracker
ports:
- "5000:5000"
volumes:
- ./Database:/app/Database/Users
- ./secrets:/app/secrets
- ./autoImport:/app/autoImport #< files put in this folder will be imported automatically
environment:
- FLASK_APP=app.py
- PYTHONUNBUFFERED=1
- TZ=America/Los_Angeles #< don't forget to change this or you will get the wrong times for songs
# - IMPORT_KEYWORD=Weekly #< Uncomment to apply a filter to what files get auto-imported (only files containing this will be imported)
# - FLASK_DEBUG=1 #< To get more detailed logs from Flask (provide this when opening an issue)
restart: always
Then you can run docker compose up -d and the app should start on http://127.0.0.1:5000 or http://yourIp:5000
- Start the app:
python app.py- Open the app in your browser:
http://127.0.0.1:5000
or whatever your IP is
- Open the app in your browser:
http://127.0.0.1:5000
Note: The Docker container persists data in the Database/ directory on your host machine.
This project is licensed under the Soffer Non-Commercial Source-Available License 1.1 - see the LICENSE file for details.
For support, please open an issue on the GitHub repository or contact me.




