pyLoad
Open source download manager with a web interface for managing bulk file downloads from file-hosting sites, direct links, and torrents. Runs headlessly on a server and handles queuing, scheduling, and extraction automatically
Quick Start
docker run -d -p 8000:8000 -v /path/to/downloads:/downloads -v /path/to/config:/config pyload/pyload:latest Overview
pyLoad is a download manager that runs as a headless server process and exposes a web interface for managing the queue. You add download links through the browser, and pyLoad handles the rest: queuing, downloading, retrying failed transfers, and extracting archives once a download completes. The process runs continuously on a server or NAS without requiring a desktop session to stay open.
The plugin architecture covers the mechanics of downloading from file-hosting services that use CAPTCHAs, wait timers, or account authentication. Each supported host has a plugin that handles the site-specific logic, so you paste a link and pyLoad figures out how to retrieve the file rather than requiring you to interact with the site manually. The plugin library covers several hundred hosts, with community plugins extending support further.
Automatic extraction handles the most tedious part of bulk file-hosting downloads. Files downloaded from hosting sites are typically distributed as multi-part RAR archives. pyLoad can unpack them automatically after the full set completes, which removes the step of manually opening a terminal or file manager to run the extraction.
Scheduling lets you set download windows so transfers happen overnight or during off-peak hours. For households where bandwidth is shared across streaming, video calls, and work, this keeps large downloads from interfering with other activity.
pyLoad does not include a BitTorrent client. It handles HTTP-based downloads and file-hosting links. Teams that want torrent support alongside direct downloads typically pair pyLoad with a separate torrent client like qBittorrent rather than looking for a single tool that does both.
Use Cases
Specific ways to use pyLoad for your workflow.
Deployment Strategy
Recommended ways to host pyLoad in your own environment.