Beets — The Music Library Manager and MusicBrainz Tagger

Introduction

Beets is a command-line music library manager that handles the tedious work of organizing, tagging, and cataloging music collections. It uses the MusicBrainz database for accurate metadata matching and provides a plugin architecture for tasks like fetching lyrics, generating playlists, and transcoding.

What Beets Does

• Automatically identifies and tags music files using MusicBrainz acoustic fingerprinting
• Organizes files into a consistent directory structure based on metadata templates
• Maintains a SQLite database of your music collection for fast querying
• Supports batch operations across thousands of albums with smart duplicate detection
• Fetches album art, lyrics, and genre information from multiple online sources

Architecture Overview

Beets is built as a Python application with a core import pipeline that matches audio files against the MusicBrainz database using a combination of tag-based and acoustic fingerprint matching. The library database is SQLite with a query language supporting regex, numeric ranges, and boolean logic. Plugins hook into well-defined extension points (import stages, commands, template functions) without modifying core code.

Self-Hosting & Configuration

• Install via pip or your system package manager (available in most Linux distros)
• Configure in ~/.config/beets/config.yaml with directory paths and plugin list
• Set path templates like $albumartist/$album%aunique{}/$track $title for file organization
• Enable plugins by listing them in config: plugins: fetchart lyrics lastgenre
• Supports MusicBrainz rate limiting and custom server URLs for local MB instances

Key Features

• Acoustic fingerprinting via Chromaprint identifies tracks without relying on filenames
• Flexible query language supports regex, date ranges, and field comparisons
• Path templates with functions allow complex naming rules without scripting
• Web plugin provides a JSON API and simple web interface for library browsing
• ReplayGain plugin calculates loudness normalization values for consistent playback

Comparison with Similar Tools

• MusicBrainz Picard — GUI-based tagger; Beets is CLI-first with better automation for large libraries
• Mp3tag — Windows GUI editor; Beets is cross-platform and scriptable
• Lidarr — focused on automated downloading; Beets excels at organizing existing collections
• Navidrome/Jellyfin — media servers; Beets handles the library management layer beneath them

FAQ

Q: Does Beets modify my original files? A: By default it writes corrected tags and can move/copy files. Use copy: yes to preserve originals.

Q: How accurate is the auto-tagging? A: Very accurate for well-known releases. The interactive importer lets you confirm or override matches.

Q: Can Beets handle 100,000+ tracks? A: Yes, the SQLite backend handles large libraries efficiently. Import speed is mainly network-bound.

Q: Does it support FLAC, MP3, and other formats? A: Yes, via Mutagen it supports MP3, FLAC, OGG, AAC, WMA, AIFF, and more.

Sources

• https://github.com/beetbox/beets
• https://beets.readthedocs.io/