[huntergemmer]

That's a cool project! Just checked out the workbench. I should be upfront though: ChartGPU is currently focused on traditional 2D charts (line, bar, scatter, candlestick, etc.), not graph/network visualization with nodes and edges. That said, the WebGPU rendering patterns would translate well to force-directed graphs. The scatter renderer already handles thousands of instanced points - extending that to edges wouldn't be a huge leap architecturally.

Is graph visualization something you'd want as part of ChartGPU, or would a separate "GraphGPU" type library make more sense? Curious how you're thinking about it.

[agentcoops]

Really fantastic work! Can't wait to play around with your library. I did a lot of work on this at a past job long ago and the state of JS tooling was so inadequate at the time we ended up building an in-house Scala visualization library to pre-render charts...

More directly relevant, I haven't looked at the D3 internals for a decade, but I wonder if it might be tractable to use your library as a GPU rendering engine. I guess the big question for the future of your project is whether you want to focus on the performance side of certain primitives or expand the library to encompass all the various types of charts/customization that users might want. Probably that would just be a different project entirely/a nightmare, but if feasible even for a subset of D3 you would get infinitely customizable charts "for free." https://github.com/d3/d3-shape might be a place to look.

In my past life, the most tedious aspect of building such a tool was how different graph standards and expectations are across different communities (data science, finance, economics, natural sciences, etc). Don't get me started about finance's love for double y-axis charts... You're probably familiar with it, but https://www.amazon.com/Grammar-Graphics-Statistics-Computing... is fantastic if you continue on your own path chart-wise and you're looking for inspiration.

[huntergemmer]

Thanks - and great question about direction. My current thinking: Focus on performance-first primitives for the core library. The goal is "make fast charts easy" not "make every chart possible." There are already great libraries for infinite customization (D3, Observable Plot) - but they struggle at scale.

That said, the ECharts-style declarative API is intentionally designed to be "batteries included" for common cases. So it's a balance: the primitives are fast, but you get sensible defaults for the 80% use case without configuring everything. Double y-axis is a great example - that's on the roadmap because it's so common in finance and IoT dashboards. Same with annotations, reference lines, etc. Haven't read the Grammar of Graphics book but it's been on my list - I'll bump it up. And d3-shape is a great reference for the path generation patterns. Thanks for the pointers!

Question: What chart types or customization would be most valuable for your use cases?

[agentcoops]

Most of my use cases these days are for hobby projects, which I would bucket into the "data science"/"data journalism" category. I think this is the easiest audience to develop for, since people usually don't have any strict disciplinary norms apart from clean and sensible design. I mention double y-axes because in my own past library I stupidly assumed no sensible person would want such a chart -- only to have to rearchitect my rendering engine once I learned it was one of the most popular charts in finance.

That is, you're definitely developing the tool in a direction that I and I think most Hacker News readers will appreciate and it sounds like you're already thinking about some of the most common "extravagances" (annotations, reference lines, double y-axis etc). As OP mentioned, I think there's a big need for more performant client-side graph visualization libraries, but that's really a different project. Last I looked, you're still essentially stuck with graphviz prerendering for large enough graphs...

[huntergemmer]

Ha - the double y-axis story is exactly why I want to get it right. Better to build it in properly than bolt it on later.

"Data science/data journalism" is a great way to frame the target audience. Clean defaults, sensible design, fast enough that the tool disappears and you just see the data.

And yeah, graphviz keeps coming up in this thread - clearly a gap in the ecosystem. Might be a future project, but want to nail the 2D charting story first and foremost.

Thanks for the thoughtful feedback - this is exactly the kind of input that shapes the roadmap.

[graphviz]

Gratifying that it's still useful.

A lot of improvements are possible, based on 20 years of progress in interactive systems, and just overall computing performance.