Lidarr

Lidarr is a self‑hosted music collection manager that automates the discovery, download, and organization of audio releases from Usenet and BitTorrent sources. From a developer’s standpoint it functions as a full‑stack application with an extensible API surface, making it ideal for integration into media pipelines or custom tooling. The core workflow revolves around monitoring RSS feeds, matching releases to an internal catalog of artists and albums, and orchestrating downloads through popular indexers or download clients. Once a file lands in the configured folder, Lidarr performs metadata enrichment, renaming according to user‑defined patterns, and optionally triggers notifications or library updates in media servers such as Kodi or Plex.

Lidarr is built on .NET Core / .NET 6+, written primarily in C#. The application exposes a RESTful API that follows standard HTTP conventions, enabling programmatic control over artists, releases, and queue management. Data persistence relies on SQLite for lightweight deployments and PostgreSQL or MySQL for larger installations, with Entity Framework Core handling schema migrations. Background tasks are scheduled via a built‑in job runner that polls RSS feeds, interacts with indexers (NZB or torrent), and processes the download queue. The UI is a SPA served from the same binary, leveraging Razor Pages for server‑side rendering and JavaScript for dynamic interactions. Containerization is first‑class: official Docker images are available on Docker Hub, and the project includes a docker-compose.yml template that wires Lidarr with SABnzbd or NZBGet, databases, and optional reverse‑proxy layers.

• API: Full CRUD operations for artists, albums, tracks, and download clients. Webhooks can be configured to fire on events such as track_added, download_complete, or artist_imported.
• Download Integration: Native support for SABnzbd, NZBGet, and torrent clients (e.g., qBittorrent), exposing hooks to push NZBs or magnet links directly into the queue.
• Metadata Management: Pulls cover art, release dates, and track listings from services like MusicBrainz, Discogs, and the Lidarr Metadata Server.
• Renaming & Sorting: Uses templated patterns ({artist} - {album} [{year}] / {tracknumber} - {title}.{ext}) that can be overridden per library.
• Upgrade Engine: Periodically scans the existing collection for higher‑quality releases and triggers re‑downloads automatically.
• Extensibility: Supports custom plugins written in C# or via the plugin API, allowing developers to hook into events, modify release selection logic, or expose new endpoints.

Lidarr’s lightweight footprint (≈200 MB binary) makes it suitable for Raspberry Pi, NAS devices, or cloud VMs. The Docker image can run in a docker-compose stack alongside a database, download client, and reverse‑proxy (Traefik or Nginx). For high‑availability scenarios, multiple Lidarr instances can share a common database and file storage, with load balancing handled externally. The application exposes health endpoints (/health, /ready) that integrate seamlessly with Kubernetes liveness/readiness probes, enabling container orchestration without additional tooling.

Developers can embed Lidarr into existing media ecosystems by:

• Consuming the REST API to trigger artist imports or monitor queue status.
• Subscribing to webhooks for real‑time updates and integrating with CI/CD pipelines or home automation scripts.
• Writing plugins that modify release selection algorithms, add custom metadata sources, or expose new UI components.
• Leveraging the command‑line interface (lidarr --help) for scripting bulk operations or automated backups.

The project offers comprehensive documentation on the official wiki, covering API usage, plugin development, and deployment scenarios. Issue triage is handled through GitHub, with a dedicated Discord community for rapid support. The codebase follows standard .NET conventions, making it approachable for developers familiar with C# and Entity Framework. Continuous integration on Azure Pipelines ensures that every pull request is built, tested, and linted before merging, which translates into a stable release cycle.

1. Automated Music Library for Home Media Servers – A developer can deploy Lidarr behind Traefik, connect it to a NAS where music files are stored, and configure webhooks to trigger Plex library scans whenever new tracks arrive.
2. Enterprise Podcast Distribution – By exposing Lidarr’s API, a company can ingest podcast releases from multiple feeds, standardize naming conventions, and push them to an internal CDN.
3. Custom Media Bot – Integrate Lidarr with a Discord bot: users request tracks, the bot queries Lidarr’s API, and upon download completion posts a message with links to the media.
4. Research Data Collection – Use Lidarr’s metadata enrichment to harvest large datasets of music releases for analytics or recommendation engine training.

• Performance: C#/.NET delivers low‑latency API responses and efficient background processing, suitable for high‑volume download queues.
• Flexibility: The plugin architecture and open REST API allow deep customization without modifying core code.
• Licensing: Completely free and open‑source under the MIT license, with no subscription costs.
• Community & Support: Active contributors and a responsive Discord channel reduce friction for new developers.
• **Cross‑