A JavaScript library for data visualization in both SVG and Canvas

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Here's a project I've been working on for a little while now. Ripl is a JS library that provides a unified API for rendering shapes on both canvas and SVG interchangeably. Over the years I've used D3 extensively to create data visualisations so I figured I'd have a go at making my own version with a slightly more modern API and stricter TypeScript support. I am aware there are already libraries that can draw to multiple contexts interchangeably, but I've added a few little niceties to Ripl that (as far as I know) some other libraries don't have such as CSS-like query selectors, DOM-like event bubbling, and keyframe animation support. The project is far from done and not published to NPM yet, but there are a few demos and source that you can look at in the repo. I'm happy with how it has come along and the things I've learnt along the way, especially the math. My dream would be to one day work on this full-time and build out a full data-viz library.

Visit product View on Hacker NewsApr 12, 2024

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

85%85% 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 · Missing: supports, reddit linkedin, podcasting

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

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

64%64% 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: way · Missing: mobile apps, ios, personal

48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

26%26% 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

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

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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