# Beets — The Music Library Manager and MusicBrainz Tagger

> A command-line tool for organizing, tagging, and managing music collections using the MusicBrainz database, with a flexible plugin system for transcoding, lyrics, and more.

## Install

Save as a script file and run:

# Beets — The Music Library Manager and MusicBrainz Tagger

## Quick Use
```bash
pip install beets
beet import ~/Music/inbox/
beet ls artist:Beatles
beet stats
```

## 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/

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Source: https://tokrepo.com/en/workflows/asset-8cbb3a3e
Author: Script Depot