Oracle of Music
Find the shortest chain of collaborations linking any two music artists, like the Oracle of Bacon (Six Degrees of Kevin Bacon), but for music.
Live at oracleofmusic.app: currently covers the top 5,000 Spotify artists and everyone they've collaborated with.
Built with: Python · Flask · SQLAlchemy · PostgreSQL · Docker · Gunicorn · Nginx · vanilla JS/HTML/CSS · MusicBrainz · Spotify Web API
How it works
flowchart LR
A[MusicBrainz dump] --> B[(PostgreSQL)]
B --> C[Adjacency list]
C --> D[BFS]
D --> E[Spotify Web API]
E --> F[HTML/CSS Path]
- Self-hosted data: a PostgreSQL database built from the full MusicBrainz data dump, running in Docker.
- Clean collaborations only: tracks are filtered to official albums, singles and EPs, excluding bootlegs and unofficial releases.
- Fast search: collaborations are worked out once and cached in the database, then searched in memory with breadth-first search, so each Path is the shortest one possible.
- Lazy Spotify data: artist pictures, album art and Spotify links load after the Path is shown, one request per item.
- Typeahead search: accent-insensitive artist suggestions that also match alternative names.
- Accessible Path display: keyboard-focusable, respects reduced-motion settings, and switches to a vertical layout on narrow screens.
Running locally
Prerequisites
- Python 3.13+
- Docker
- About 40 GB of free disk space for the database
- A Spotify developer app (client ID and secret)
1. Build the database
Follow deploy_database/instructions.txt to start PostgreSQL in Docker and load the MusicBrainz data dump into it.
2. Configure the app
Create a .env file in the repo root:
| Variable | Description |
|---|
DATABASE_URL | SQLAlchemy URL for the MusicBrainz database, e.g. postgresql+psycopg://postgres:<password>@localhost:5432/musicbrainz |
SPOTIFY_CLIENT_ID | Spotify app client ID |
SPOTIFY_CLIENT_SECRET | Spotify app client secret |
ARTIST_NAMES_FILE_PATH | Text file with one artist name per line, most important first |
ARTISTS_TO_LOAD | How many names to read from that file. The app finds Paths between these artists and everyone they've collaborated with. The live site uses the top 5,000 Spotify artists. |
3. Install and run
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
cd app
gunicorn app:app # or: flask --app app run
The first start builds the collaboration graph and caches it in the database. Later starts reuse the cache.
Tests
The tests don't need a database or Spotify credentials:
pytest
Acknowledgements
License
MIT
