We

Web page animation libary for all frameworks

Hacker News

Web page animation libary for all frameworks

# Smooth page transitions for web apps - like native mobile apps Ever notice how native mobile apps have those buttery smooth transitions when navigating between screens? Instagram stories, WhatsApp chats, any modern mobile app really. Meanwhile, web pages still feel clunky with their instant page loads. I built *SSGOI* to bridge that gap - a library that brings native-like screen transitions to web applications. ## Technical challenges solved: *Universal browser support* - No reliance on cutting-edge APIs like Chrome's View Transition API. Had to build everything from scratch to ensure compatibility across all browsers. *SSR compatibility* - Works seamlessly with Next.js, Nuxt, and other server-side rendering frameworks without breaking hydration or causing layout shifts. *Drop-in integration* - Zero refactoring required. Add the library to existing projects without touching routing logic or application structure. ## Framework agnostic approach Built to work with React, Vue, Svelte, Angular, or vanilla JavaScript. The core engine handles the heavy lifting while framework-specific adapters provide the integration layer. ## Performance considerations - Hardware-accelerated CSS transforms - Efficient memory management during transitions - Minimal bundle size impact - Configurable transition duration and easing The goal was simple: make web navigation feel as polished as native apps without sacrificing performance or developer experience. * https://github.com/meursyphus/ssgoi\ * Open to feedback and contributions. Would appreciate any stars if you find this useful for your projects.

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
85%85% 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: apps, using, apis · Missing: mac, agents, macos
83%83% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: mobile apps, apps · Missing: ios, personal, entrepreneurs
54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, ide · Missing: https docs, excited, just released
51%51% 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 · Strong signals: efficient · Missing: plus, platform, intuitive
50%50% 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
22%22% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
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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