Puck (Visual Editor for React) now supports viewport switching

Hacker News

We've been working hard to add viewport previewing to Puck, our MIT visual editor for React, over the last few months. In order to get device-like viewport previewing with CSS media queries etc, you need to render your content within an iframe. Drag-and-drop is a core part of Puck's experience, but is famously difficult to pair with iframes. We didn't want to compromise Puck's experience, so we released two new packages to support this effort: 1) @measured/dnd, a fork the underlying dnd library (@hello-pangea/dnd, a maintained fork of react-beautiful-dnd) to support both iframes and CSS transforms 2) @measured/auto-frame-component, an iframe package that syncs the styles between the host and same-origin iframe. The result is a seamless drag-and-drop experience across iframes with true viewport previewing that we're very excited about! Thank you to our wonderful contributors and the HN community for such great support!

Visit product View on Hacker NewsApr 18, 2024

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

83%83% 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 · Strong signals: supports · Missing: reddit linkedin, podcasting, created

68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

59%59% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

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

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

40%40% 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

18%18% 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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