
beets
A command-line music library manager that tags and organizes your audio files using MusicBrainz.
- Stars
- 15.9k
- Forks
- 2.2k
- Licence
- MIT
- Language
- Python
- Last update
- 4 days ago
- Type
- CLI
What it is
beets is a command-line tool for managing a music collection. It uses the MusicBrainz database to fill in and correct tags such as artist, album, and track names, and it can organize files into folders based on those tags. People use it to keep large, messy music libraries consistent without tagging each file by hand. The README provided here was empty, so this description relies on the repository description and topics.
- Tag a folder of music files by matching them against MusicBrainz records
- Organize a music library into a consistent folder and file naming structure
- Search and query your library from the command line
Great for
- People with large music collections that have inconsistent or missing tags
- Users comfortable working in a terminal
- Python users who want to customize their library workflow
- Anyone who wants MusicBrainz-based metadata applied automatically
Not ideal for
- People who want a graphical music player or streaming app, since the project is a command-line manager (reason: no GUI is described in the available material)
- Users who do not want to install Python tools and edit configuration files (reason: setup requires a command-line workflow)
How to get it
- 1
Install with a package manager
You'll need: Python 3
Clone the repository
git clone https://github.com/beetbox/beets.git - 2
Run it
- Install Python 3 on your system
- Install beets using the instructions in the project documentation at beets.io
- Run beets from the command line to import a music folder
- Review the tags and changes beets proposes before accepting them
- 3
Get the most out of it
- Read the documentation at http://beets.io/ for configuration options
- Explore available plugins listed in the project documentation
- Set up a configuration file to control how files are organized
Downloads
Strengths
- Uses the MusicBrainz database, a widely used open music metadata source
- Open source under the MIT license
- Actively maintained, with a recent release listed (v2.14.1) and a recent last push
Trade-offs
- The README provided was empty, so specific features and setup steps could not be verified here
- Command-line interface may be a barrier for non-technical users
- Requires Python and familiarity with configuration to get the most out of it
How it compares
| Project | Stars | Type | Level | Updated | Best for |
|---|---|---|---|---|---|
| beets (this) | 15.9k | CLI | intermediate | 4 days ago | People with large music collections that have inconsistent or missing tags |
| spotify-downloader | 26.6k | CLI | intermediate | 11 days ago | People comfortable running a command in a terminal who want local copies of Spotify playlists |
| AudioKit | 11.5k | Library | intermediate | 3 months ago | Swift developers adding synthesizers, effects, or audio analysis to an iOS or macOS app |
| pear-desktop | 34k | App | beginner | 4 days ago | People who want YouTube Music in a standalone desktop window |
| YesPlayMusic | 33.5k | App | beginner | 27 days ago | Existing NetEase Cloud Music users who want a different player interface |
| ultimatevocalremovergui | 26.9k | App | beginner | 30 days ago | Musicians who want karaoke or practice backing tracks from existing songs |
Stats synced from GitHub. The assessment above was drafted with AI from the project's README on 2026-10-29 and may miss recent changes — check the README before relying on a command. MIT licence: free to use, modify and distribute, including commercially, as long as you keep the copyright notice.