Torrent Search Tool

torrent_search.py is a Python script that allows you to search for torrents on The Pirate Bay (using the apibay.org API) with keywords defined in a text file. The results are saved in an SQLite database and also exported to a CSV file for further analysis and reference.

Features

• Torrent search by keyword: Input keywords in a text file, and the script will search for related torrents.
• SQLite database: Search results are stored in an SQLite database for later queries.
• CSV export: The search results are also exported to a CSV file with well-formatted column names.
• Torrent details retrieval: The script fetches additional details for each torrent, such as age, size, included files, and magnet links.
• Support for multiple categories: The tool classifies torrents into different categories, such as movies, applications, games, music, and more.

Requirements

• Python 3.6 or higher
• Additional packages:
  • requests
  • beautifulsoup4
  • pytz
  • sqlite3 (included in Python’s standard library)
  • csv
  • argparse
  • logging
  • subprocess

You can install the additional dependencies by running:

pip3 install requests beautifulsoup4 pytz

Usage Instructions

1. Prepare a keyword file: Create a text file where each line contains a keyword to search for on The Pirate Bay. Example:

   movie
   software
   music

2. Run the script: To run the script, use the following command in the terminal:

   python3 torrent_search.py keywords.txt

   Where keywords.txt is the text file with the keywords. The script will search for the keywords, store the results in the torrents.db database, and export the results to a CSV file.

3. Script options: The script supports the following options:

   python3 torrent_search.py -h

   Options:

   • -h, --help: Displays the help message.
   • file: Text file with keywords for the search.

4. File structure:

   • SQLite database (torrents.db): Stores the details of the torrents, including:

     • id: Unique torrent ID.
     • name: Torrent name.
     • info_hash: Torrent hash.
     • leechers: Number of leechers.
     • seeders: Number of seeders.
     • num_files: Number of files included in the torrent.
     • size: Torrent size.
     • username: Username of the uploader.
     • added: Addition date (Unix timestamp).
     • added_utc: Addition date in UTC format.
     • status: Torrent status (e.g., vip, trusted).
     • category: Category code.
     • category_name: Category name (e.g., Movies, Software).
     • imdb: IMDb ID, if available.
     • torrent_age: Torrent age.
     • details: List of files included in the torrent.
     • magnet_link: Magnet link.

   • CSV: Exports the search results to a CSV file in the format:

     id|name|info_hash|leechers|seeders|num_files|size|username|added|added_utc|status|category|category_name|imdb|torrent_age|details|magnet_link
     

Usage Examples

1. Search for torrents using keywords from a file:

   python3 torrent_search.py keywords.txt

   Output:

   The folder Torrents already exists
   Processing keyword 'pistol'...
   [...]
   100 results saved in the torrents.db database
   Results have been exported to a CSV file called 2024-09-27_Results.csv

2. Query the SQLite database:

   sqlite3 torrents.db
   sqlite> SELECT * FROM torrents LIMIT 3;

   Example output:

   74591101|DungeonSex - Kink - Sophia Locke - Deep Connection, Sophia and Tommy Pistol 720p|8F600F390F079F16E0B4E49E133CA28854710CA3|3|12|1|2781502161|Yurievij|1707652679|2024-02-11 11:57:59|vip|505|HD - Movies||7 months||magnet:?xt=urn:btih:8f600f390f079f16e0b4e49e133ca28854710ca3&dn=DungeonSex+-+Deep+Connection+-+Sophia+Locke+and+Tommy+Pistol,+Feb+9,+2024_720p.mp4&tr=udp://tracker.openbittorrent.com:80&tr=udp://tracker.opentrackr.org:1337/announce

Log

The script generates a detailed log of the operations performed, useful for debugging or reviewing program behavior. It uses DEBUG level by default, meaning it includes detailed debugging messages.

Contributions

Contributions are welcome. If you have suggestions, bugs to report, or improvements to make, feel free to open an issue or submit a pull request.

License

This project is licensed under the GNU Affero General Public License v3.0 (AGPL-3.0). See the LICENSE file for more details.