Torrent RSS Rule Editor

Desktop application for building and managing qBittorrent RSS download rules with Autobrr export support and SubsPlease title integration.

The app now uses PySide6 as the default UI and keeps Tkinter available as a legacy fallback path, organized as a modular Python package under src.

What It Does

• Create and edit qBittorrent RSS rule payloads.
• Import title/rule data from JSON, CSV, TXT, clipboard text, and drag-and-drop.
• Export selected or full rule sets to JSON.
• Export to multi-target workflows (qBittorrent/Autobrr) from Qt.
• Sync rules to qBittorrent in online mode.
• Fetch and cache SubsPlease titles and AniList alias variations.
• Expand manual AniList refreshes to the selected season/year for broader cache pulls.
• Retain AniList alias cache by age, by size, or by dated archive rotation.
• Apply Title Variations to match pattern, title, and/or save path targets in the editor.
• Control season/year prefix behavior for imports and generated save paths from Settings.
• First launch opens a Setup Wizard when config.ini is missing, and Setup Wizard can be reopened from Settings menu.
• Validate and sanitize folder names using filesystem-aware rules.
• Manage backups and restores of qBittorrent rule state.
• Audit schedule and title variation caches in a tabbed, searchable tree/table viewer dialog.
• Responsive, lag-free UI with non-blocking background workers (QThread) for connection testing, rule syncing, and API cache refreshes.
• Sleek, compact top button bar with standard platform icons, flat Material-3-style vertical separator, status chips in the bottom statusbar, and descriptive tooltips across all controls.
• Use modern Qt setup/configuration dialogs including Setup Wizard, log viewer, bulk edit, and template manager.
• Fetch, parse, and queue torrent/magnet releases from SubsPlease using the Multi Batch Downloader dialog.

Quick Start

1. Create/activate your virtual environment. If using the default local setup:

python -m venv .venv
.\.venv\Scripts\Activate.ps1

Note: For mapped development environments (e.g., custom virtual environment paths mapped via PowerShell profile), activate them using your custom profile helpers. See AGENTS.local.md (if present) for local paths and agent command execution details.

2. Install dependencies.

pip install -r requirements.txt

3. Run the app.

python main.py

Run Tk fallback UI:

python main.py --ui=tk

You can also set environment variable TRRE_UI to qt or tk.

Runtime Files

• config.ini: application settings, connection profiles, and UI/tool preferences.
• cache.json: app cache storage.
• qbt_editor.log: runtime logs.
• .app_secret.key: local key for encrypted credential storage.

Current Module Layout

main.py
src/
    __init__.py
    constants.py
    config.py
    cache.py
    utils.py
    rss_rules.py
    backup.py
    api/
        __init__.py
        qbittorrent.py
        subsplease.py
        rss_fetcher.py
    services/
        __init__.py
        backup.py
        rules.py
        batch_downloader.py
        file_operations.py
        language_detection.py
    gui_qt/
        __init__.py
        main_window.py
        batch_downloader_dialog.py

Server/Target Support in Current Code

• qBittorrent: API client, rule sync, backup/restore integration.
• Autobrr: target option is present in settings/export flow paths where configured.

Testing

Run all tests:

python -m pytest -q

Run specific groups:

python -m pytest tests/test_qbittorrent_api.py -q
python -m pytest tests/test_qbittorrent_api_errors.py -q
python -m pytest tests/test_rss_rules.py -q
python -m pytest tests/test_integration.py -q
python -m pytest tests/test_modular_cleanup.py -q

Security and Policy Docs

• Security reporting and handling: see SECURITY.md.
• AI-assisted workflow expectations: see AI_USAGE.md.
• Agent-oriented repository rules: see AGENTS.md.

License

MIT. See LICENSE.

See AI_USAGE.md for the full policy.

Documentation

• README.md - Setup, usage, and feature overview
• AI_USAGE.md - AI-assisted coding policy and review standards
• AGENTS.md - AI agent operating and audit guidance
• TODO.md - Roadmap and pending improvements

Author

xAkai97

Developed with AI assistance from GitHub Copilot.