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Stirfry, a small Ruby web framework mixing it up

Hacker News

Stirfry, a small Ruby web framework mixing it up

Stirfry is a ruby webframe work with JSX-like templating, easy routing, and minimal magic! It is made for mixing everything all together with htmx so there is almost no line between frontend or backend! Is this good design? No. Is it a good idea? Also no. Does it support Rack-based middleware? Yes! Should you use it? Almost definitely not. Is it fun? To me it is! Shout out to https://github.com/patbenatar/rbexy that I used as a starting point to write a RBX parser. Shout out to https://github.com/sinatra/sinatra for being my fave and basically the template for this project. Shout out to Rack as well because it's still a great/fun interface after all of these years!

Visit productView on Hacker NewsSep 7, 2026
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Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos
62%62% 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 · Missing: supports, reddit linkedin, podcasting
49%49% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: interface · Missing: plus, platform, intuitive
48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide · Missing: https docs, excited, just released
42%42% 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
37%37% 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
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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