JSX-Htmx that doesn't conflict with react

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Hey folks, I've been tinkering with a TypeScript/JSX library that might interest some of you: jsx-htmx. HTMX has been gaining traction lately for its simplicity and performance benefits in handling dynamic HTML content. However, as someone who values type safety and enjoys working with TypeScript, I found the existing options for integrating HTMX with TSX files to conflict with what I wanted to achieve. So, I decided to roll up my sleeves and create jsx-htmx. With just a single line (`/* @jsxImportSource jsx-htmx */`) added to your TSX file, you can seamlessly blend HTMX into your TypeScript projects while maintaining type safety. I've also included types to ensure your components align with the HTMX API, providing an extra layer of confidence in your codebase. ```tsx const Badge: SimpleCustomComponent = (props) => { return <div class="component">{props.children}</div>; }; ``` I've been using jsx-htmx in a couple of production sites, and so far, the performance has been solid, with render times consistently in the low milliseconds range. I'm eager to hear your thoughts and suggestions on how to improve jsx-htmx. Are there any specific features you'd like to see added? Any ideas for enhancing type safety or optimizing performance? Looking forward to your feedback! Cheers, M

Visit product View on Hacker NewsApr 12, 2024

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

90%90% 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 HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

88%88% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

44%44% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

36%36% 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

13%13% 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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