Copper – A Go framework for your projects

Hacker News

Hey HN! I've been working with Go for the last 5+ years at large-ish companies building products that many of you may use regularly. A ton of people say that Go's standard library is really powerful and usually enough to get by without external dependencies. I think that's true for companies that have the resources to build and maintain packages to reduce code duplication. For everyone else, we're left to finding the right set of packages to build our projects. So, I built Copper - a toolkit that helps you get your project off the ground with minimal dependencies. It covers everything from routing, html, storage to tooling and more. Check it out, star it, and feel free to ask questions! P.S. I also have a video demo building an HN clone in the docs [1] https://gocopper.dev/

Visit product View on Hacker NewsJul 2, 2022

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Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

77%77% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

55%55% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

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

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

39%39% predicted probability of success on AppSumo, 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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