KelpsGet – Modern download manager built in Rust

Hacker News

Hi HN! I'm the creator of KelpsGet, a download manager I built in Rust. Started as a learning project to understand Rust better, but it evolved into something I think others might find useful. Key features: - GUI interface (built with egui) - Multiple protocols: HTTP/HTTPS, FTP, SFTP, torrents - Parallel downloads with resume capability - Cross-platform (Linux, macOS, Windows) The interesting technical challenges were: - Handling different protocols in a unified interface - Building a responsive GUI in Rust - Managing concurrent downloads efficiently Try it: `cargo install kelpsget` or download binaries from releases. Would love feedback from the community, especially on the Rust implementation and any missing features you'd find useful!

Visit product View on Hacker NewsMay 23, 2025

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Indie HackersFits the IH revenue-focused audience · Strong signals: started, para, efficiently · Missing: supports, reddit linkedin, podcasting

73%73% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

AppSumoStrong fit for a featured deal · Strong signals: platform, interface, efficient · Missing: plus, intuitive, reviews

58%58% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: mac, macos · Missing: agents, agent, cursor

49%49% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

45%45% 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 · Strong signals: para · Missing: mobile apps, ios, personal

33%33% 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

18%18% 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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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