Welcome to MusicGenreDB, an archive dedicated to preserving and extending the original work of Glenn McDonald, the former Data Alchemist at Spotify, known for his project Every Noise at Once. This repository aims to maintain and potentially expand on the intricate genre classifications that McDonald created, ensuring the longevity and accessibility of this valuable data.
MusicGenreDB is an extensive collection of 6,291 genre-shaped distinctions as categorized by Spotify. Each song in this repository is associated with a unique ID that links it to detailed metadata. This project serves as an archive and aims to possibly introduce new features in the future to enhance the original concept.
The repository contains two main components:
- songs/: A folder with 6,291 audio files. Each file is named with a number corresponding to its ID.
- songs_data.json: A JSON file containing metadata for each song. The structure of the JSON file is as follows:
[
{
"id": "SONG ID",
"genre": "SONG GENRE",
"url": "SONG URL",
"title": "ARTIST - SONG NAME",
"color": "CHOSEN COLOR"
}
]
-
Clone the repository:
git clone https://github.com/yourusername/MusicGenreDB.git cd MusicGenreDB
-
Explore the data: You can browse the
songs/
folder to access the audio files directly or use thesongs_data.json
file to retrieve detailed information about each song. -
Listen to the samples: Each song entry in
songs_data.json
includes a URL to a Spotify MP3 preview.
We welcome contributions to MusicGenreDB! If you have ideas for new features, improvements, or just want to fix a bug, feel free to submit a pull request or open an issue.
All credit for the data itself goes to Glenn McDonald and the artists and bands who created the music. This project is a tribute to their work and aims to preserve and expand upon it.
- Email: [email protected]
- LinkedIn: glenn mcdonald
- Twitter: glenn_mcdonald
- Threads: glennmcdonald
- Bluesky: glenn_mcdonald
- Mastodon: @[email protected]
- Instagram: glennmcdonald
- Spotify: glenn mcdonald
- Facebook: glenn mcdonald
This project is licensed under the MIT License.