Tenaryo

Tenaryo / TinyBitTorrent

Public

A High-Performance BitTorrent Client in C++23

12
3
89% credibility
Found May 20, 2026 at 13 stars -- GitGems finds repos before they trend. Get early access to the next one.
Sign Up Free
AI Analysis
C++
AI Summary

TinyBitTorrent is a command-line tool that lets you download files using the BitTorrent protocol. You give it a torrent file or magnet link, and it connects to other users currently sharing that file, downloads pieces from multiple sources in parallel, verifies each piece matches the original, and saves the complete file to your computer. The program handles all the complexity of finding peers, negotiating downloads, and ensuring data integrity so you just get your file.

How It Works

1
🔍 You find a file you want

You discover a file online that someone is sharing, and you get either a magnet link or a small torrent file to download it.

2
⚙️ You set up the program

You download the program and build it on your computer following simple instructions, or run it in a container for a zero-config experience.

3
🎯 You start your download

You run one simple command telling the program what file you want and where to save it.

4
The program finds people sharing your file
📁
Using a torrent file

The program reads your .torrent file to learn about the file and its tracker

🧲
Using a magnet link

The program parses the magnet link and asks peers for the file information

5
🤝 The program connects to peers

It shakes hands with the people sharing your file and asks permission to download pieces from them.

6
📥 Your file downloads piece by piece

The program downloads small chunks from multiple people at once, verifying each piece is correct before saving it.

✅ Your file is complete

Once all pieces are downloaded and verified, your file is ready to use exactly as the original was intended.

Sign up to see the full architecture

5 more

Sign Up Free

Star Growth

See how this repo grew from 13 to 12 stars Sign Up Free
Repurpose This Repo

Repurpose is a Pro feature

Generate ready-to-use prompts for X threads, LinkedIn posts, blog posts, YouTube scripts, and more -- with full repo context baked in.

Unlock Repurpose
AI-Generated Review

What is TinyBitTorrent?

TinyBitTorrent is a high-performance BitTorrent client written in C++23. It implements the full BitTorrent protocol from scratch -- tracker communication, peer wire protocol, magnet link support with the ut_metadata extension, and SHA-1 verified downloads. The client uses modern C++ techniques like std::jthread for concurrent piece downloads across multiple peers, pipelined block requests to saturate network links, and zero-copy incremental writes that place data directly at file offsets. It ships as a CLI tool with 11 commands covering everything from parsing .torrent files and querying trackers to downloading entire files via magnet links.

Why is it gaining traction?

The project demonstrates what a clean protocol implementation looks like when built with modern C++. No external dependencies beyond the standard library and POSIX sockets -- you get a working BitTorrent client in 2,550 lines. Performance is a deliberate focus: pipeline depth of 5 keeps multiple requests in-flight per piece, while multi-peer parallelism gives 2-5x speedup over single-peer downloads. The CLI makes it practical for scripting and automation, and the codebase ships with 83 tests and a Docker image for zero-config builds.

Who should use this?

Backend developers building torrent-related tooling who need C++ performance rather than Python or Go. Systems programmers exploring how BitTorrent works in practice -- the code reads cleanly and avoids abstraction overhead. Teams evaluating BitTorrent for private swarm deployments where a lightweight, auditable client matters more than a full-featured client like libtorrent. Not suitable for Windows environments or teams lacking C++23 compiler access.

Verdict

A well-structured, fast BitTorrent client that demonstrates clean protocol implementation. The 12 stars and lack of community feedback mean this is unproven in production environments, though the 83 tests and MIT license offer reasonable starting confidence. The 0.8999999761581421% credibility score reflects a niche project with minimal adoption. Use it for learning, prototyping, or private tooling -- not for critical infrastructure until the codebase builds a track record.

Sign up to read the full AI review Sign Up Free

Similar repos coming soon.