Peeroxide – Full wire-compatible Rust implementation of Hyperswarm

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Just shipped peeroxide, a complete, production-ready Rust port of the Hyperswarm P2P networking stack. It’s fully wire-compatible with the existing Node.js implementation, so Rust peers can join the live public HyperDHT and seamlessly discover/connect with Node.js peers. Key features: Full HyperDHT (Kademlia + hole-punching + blind relays) Noise handshakes + SecretStream encryption Pure-Rust libudx with BBR congestion control (no C dependencies) Topic-based peer discovery 497 tests + golden fixtures + live cross-language interop validation All three crates are now live on crates.io at v1.0.1: peeroxide peeroxide-dht libudx GitHub: https://github.com/Rightbracket/peeroxide This was a solo project, but I used Claude (Anthropic) + OpenCode/oh-my-openagent very heavily. I needed this for a different project and hope other people find it useful too.

Visit product View on Hacker NewsApr 26, 2026

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, claude, code · Missing: mac, agents, macos

52%52% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersIH features products with proven revenue · Strong signals: compatible · Missing: supports, reddit linkedin, podcasting

46%46% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: exist, existing, ide · Missing: https docs, excited, just released

40%40% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

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