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Starfyre – A WASM Based SSR Python Front End Web Framework

Hacker News

Starfyre – A WASM Based SSR Python Front End Web Framework

Hey HN community, I'm excited to share Starfyre, a cutting-edge library that enables you to create front-end applications by leveraging the power of Python. It's perfect for those who love Python and want to extend its capabilities to frontend development. Key Features: * Reactive Frontend Development: Starfyre allows you to build reactive frontends using only Python. This means you can create highly interactive and real-time applications with ease. * Effortless Interactive Application Creation: With Starfyre, the process of creating interactive applications becomes straightforward. You define your frontend with observables and reusable components, using a JSX like syntax in Python called Pyxides. * Built with Pyscript and WASM: This innovative approach ensures that your applications run natively in the browser, providing a seamless user experience. * Minimal Effort, Maximum Impact: Starfyre is designed for minimalistic yet effective development. You can create complex, real-time applications without the usual hassle. It is fairly early in development but here is a sample codebase - https://github.com/sparckles/create-starfyre-app Do let me know what you folks think of it. Any feedback is highly appreciated

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
90%90% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: user, using, code · Missing: mac, agents, macos
80%80% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: excited, ide, io · Missing: https docs, just released, exist
69%69% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoStrong fit for a featured deal · Missing: plus, platform, intuitive
66%66% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
32%32% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
11%11% 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.

Incorrect prediction on native model

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