bunkr_dl

Download every file of a Bunkr album, or of every album found by a Bunkr search, from the command line.

Follows paginated albums (?page=N, 100 files per page).
Saves files under their original names.
Resumes partially downloaded files when run again against the same folder.
Works with any Bunkr mirror domain, since links are resolved relative to the URL you pass.

Requirements

Python 3 with:

requests
beautifulsoup4
lxml

Usage

bunkr_dl [-h] [-o DIR] url

Option	Meaning
`url`	Album URL (`https://<domain>/a/<id>`) or search URL (containing `?search=`)
`-o, --output DIR`	Base download folder (default: `/data/bunkr`)
`-h, --help`	Show help and exit

The default folder is set by DEFAULT_OUTPUT near the top of the script.

Examples:

bunkr_dl https://bunkr.cr/a/XXXXXXXX
bunkr_dl -o ~/Downloads https://bunkr.cr/a/XXXXXXXX
bunkr_dl 'https://bunkr.cr/?search=some%20name'

Quote search URLs so the shell leaves ? and & alone.

Where files go

Album: OUTPUT/<album title>/. If that folder already exists, a - 2, - 3, ... suffix is added.
Search: OUTPUT/<Search Terms>/<album title>/, one subfolder per album found.

How it works

Album page: collect the /f/<slug> file links, following ?page=N until a page adds nothing new.
File page: find the https://dl.<domain>/file/<id> download link.
POST the id to /api/_001_v2 on that host to get the storage path and original file name.
Ask https://glb-apisign.cdn.cr/sign for a token and download the signed CDN URL.

Bunkr changes domains and page layout often. When the script reports no media, check these steps against the live pages first.

License

This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License version 2 as published by the Free Software Foundation. See LICENSE for the full text.

Development Approach

This project is developed using AI-assisted tools. Code is generated with the help of AI based on human-provided specifications, design decisions, and iterative feedback.

All contributions are reviewed, tested, and curated by the maintainer before being included in the codebase. AI is used as a productivity and exploration tool, while human oversight remains central to all decisions.

The goal is to combine the flexibility of AI-assisted development with standard open-source practices such as transparency, review, and accountability.