Mayu Live, a reactive web framework written in Ruby

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Hi everyone, I have been working on this for some time now and thought I should post it here. I have enjoyed working with React in the past, and I love Ruby, so I thought I'd implement something like React in Ruby, and this is the result. Components are written in Haml and transformed into Ruby. Everything runs on the server, and there's no need to write any JavaScript. It's pretty fast, and latency is usually low enough nowadays when you can deploy apps anywhere in the world. It might not be suitable for all types of web apps, but it might be perfect for some. One of the main benefits of using something like this is that you don't have to implement an API to update state on the server; you can talk directly to a database from within a callback handler. I thought that if the project got some attention, maybe I would get motivated to keep working on it.

Visit product View on Hacker NewsMay 15, 2023

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

89%89% 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.

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

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

nativeThis product was originally launched on this platform.

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

65%65% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

49%49% 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

41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

16%16% 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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