stabldev/torrra

AI Summary: This GitHub issue proposes to update the documentation configuration file (`conf.py`) to dynamically retrieve the project's version. Instead of hardcoding the version string, it suggests importing `__version__` directly from the `torrra` module and assigning it to the `release` variable, ensuring the documentation always reflects the current package version.

AI Summary: Users are encountering 'nothing found for' errors with torrra when using Prowlarr, despite Prowlarr still searching, suggesting slow indexers are causing issues. This problem persists in version 2.0.1, even with `--no-cache`, and is suspected to be due to a 10-second timeout. The user proposes adding a configurable timeout setting.

AI Summary: The `torrra` application (v1.3.4) on Arch Linux x86_64 is failing with a `StylesheetError` when run from its binary version. The user suspects this is caused by a recent change (#159) that transitioned to `.tcss` stylesheets, while the binary might still be attempting to load `.css` files as referenced in `torrra.spec`. This issue prevents the application from starting correctly.

AI Summary: The task is to debug a Dockerized version of the `torrra` application. The issue is that downloaded torrents are not being saved to the specified `download_path` in the `config.toml` file, instead ending up in a Docker overlay directory. The solution likely involves correctly mapping the host's download directory to the container's filesystem using Docker volume mounts, ensuring the container has the necessary permissions to write to the mounted directory.

AI Summary: Implement support for downloading and handling .torrent files in the `torrra` CLI torrent client. This involves prioritizing magnet link retrieval, but if unavailable, downloading the .torrent file, and then feeding it to the libtorrent library for seeding and downloading. The existing magnet link handling should remain unchanged.

AI Summary: Implement a configuration option to enable/disable a transparent background in the torrra TUI. This involves adding a new setting to the `config.toml` file, parsing this setting in the Python code, and dynamically updating the TUI's CSS to apply or remove the transparency effect.

AI Summary: Implement a configuration option to specify the torrent indexer (e.g., Jackett) within the `config.toml` file, eliminating the need to provide it as a command-line argument each time the application is launched. This involves modifying the configuration parsing and application logic to read and utilize the indexer setting from the config file.

AI Summary: Modify the `torrra` Python application to allow users to specify API keys within the configuration file (`config.toml`) instead of only accepting them via the command line. This involves adding functionality to read and utilize API keys from the config file, potentially adding new configuration options, and ensuring secure handling of sensitive information.

AI Summary: The task is to modify the `torrra` Python torrent downloader to correctly handle magnet URIs returned by Prowlarr. Currently, Prowlarr returns redirect links instead of valid magnet URIs, causing download failures. The solution involves parsing the redirect link to extract the actual magnet URI and using that for the download.

AI Summary: Implement a `--no-cache` command-line argument for the `torrra` Python torrent downloader. This argument should disable the caching mechanism (currently using `diskcache`) for the current session, forcing the program to fetch fresh data from the provider each time. The implementation should involve modifying the `search` methods to respect a `use_cache` argument, controlled by the presence of the `--no-cache` flag.

AI Summary: Improve the error handling in the `torrra` Python CLI tool to provide a more informative message when Jackett is not installed or configured correctly. This involves checking for the existence of the Jackett configuration file before attempting to access it and displaying a user-friendly error message if it's missing or inaccessible.

AI Summary: Add command-line flags (`--jackett-url` and `--jackett-api-key`) to the `torrra` CLI tool to allow users to specify the Jackett server URL and API key directly, instead of relying solely on the configuration file. This will enable users with cloud-hosted Jackett instances to use the tool without modifying the configuration file.

AI Summary: Implement Prowlarr support as a new torrent indexer option in the torrra CLI tool. This involves adding a new command-line flag or option to select Prowlarr, integrating with the Prowlarr API to fetch search results, and handling any authentication or configuration requirements specific to Prowlarr.