Create effortless page transitions with a new primitive in react-spring

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Today i wrapped up the last primitive i had in mind for react-spring ( https://github.com/drcmda/react-spring ): Parallax. Demo: https://codesandbox.io/embed/548lqnmk6l This makes the most daring and complex page transitions as easy as it gets. You basically define a page layout declaratively and the primitive takes care of scrolling. React-spring takes inspiration from React-motions api, but in a simplified form, at the same time can interpolate raw state (colors, svgs, arrays, etc) and animates very efficiently as it doesn't have to re-render components frame by frame. At this point it has four simple primitives to enable all sorts of UI oriented animations: Spring, Trail, Transition and Parallax.

Visit product View on Hacker NewsMar 22, 2018

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

76%76% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

67%67% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

58%58% 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 · Strong signals: efficient · Missing: plus, platform, intuitive

40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

33%33% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

15%15% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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