Clamshell- an experimental Python based shell

Hacker News

About a month ago I started a suprisingly-not-that tricky project to build an experimental python repl that I could use instead of bash as a daily shell in windows, mac or linux. It"s more hack-for-exploration than a production ready shell, but here it is! Hope somebody finds it anywhere near as interesting to check out as I found making it. Disclaimer: I know about xonsh and love it (if you haven't heard of it, google it). This project is more pure python and less python and bash interacting - see the readme for more details.

Visit product View on Hacker NewsJan 28, 2023

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

73%73% 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: mac, google · Missing: agents, macos, agent

60%60% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

31%31% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

23%23% 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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