Getting Started

This project targets Python 3.10+ and assumes you have a Torznab/Jackett instance as well as Transmission available somewhere on your network. Follow the steps below to prep the repo for use or further hacking.

Prerequisites

  • Python 3.10 or newer
  • Access to a Torznab/Jackett feed with a valid API key
  • Transmission installed locally or reachable over the network (RPC or transmission-remote)

Create an isolated environment

python3 -m venv .venv
source .venv/bin/activate

Install dependencies

pip install --upgrade pip
pip install -r requirements.txt

Set up configuration

Start from the sample file, then see Configuration for every available option.

cp config.example.json config.json

Bootstrap Jackett + FlareSolverr

Need a Jackett + FlareSolverr pair without the clickfest? Use the bundled helper:

python scripts/setup_indexing_stack.py

It will:

  • detect existing instances before touching anything,
  • optionally write a Docker Compose stack under ~/.local/share/torrent_finder/stack and spin up linuxserver/jackett + ghcr.io/flaresolverr,
  • link Jackett to FlareSolverr and point you to the local Jackett UI so you can finish configuration manually (add indexers, copy the API key),
  • update config.json whenever torznab.url/torznab.apikey are still on placeholder values after you paste the key.

Pass --help to the script for more knobs (custom tracker list, ports, or skipping Docker entirely when you manage the services yourself).

!!! note Jackett does not offer a supported API for retrieving the Torznab key or bulk-importing indexers without user interaction. After running the bootstrap script, visit the printed Jackett URL (typically http://127.0.0.1:9117), add at least one indexer (none are auto-installed), and copy the API key into your config.json.

Verify the installation

Run the unit tests to confirm the environment is wired correctly.

pytest

From here you are ready to explore Usage or build out your own automation on top of the API.