GrandPerspective-style treemaps for the web and disk usage visualizer

Hacker News

I like treemaps for visualizing hierarchical mass and density of resource usage. I've always particularly loved GrandPerspective's dense, colorful rendering, but haven't found a similar but generalized treemap that works in reactive web views across many data visualization contexts. So I built gp-treemap, a canvas-based web component that renders GP-style treemaps with millions of nodes: https://github.com/imbue-ai/gp-treemap/ If you want to give it a spin, try something like this command to visualize hierarchical disk usage: npx -p @imbue-ai/gp-treemap gpdu ~/Downloads Fun fact: I built gp-treemap as a test case for Imbue's Sculptor ( https://imbue.com/sculptor/ ) and Blueprint ( https://imbue.com/product/blueprint ) tools.

Visit product View on Hacker NewsApr 29, 2026

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

65%65% 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.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

49%49% 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: visualize, 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

46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

19%19% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

17%17% 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.

Correct prediction on native model

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