alt Hacker NewsI’m not convinced GPU acceleration is a meaningful advantage for most charting use cases. Most dashboards don’t render enough data for it to matter. Once a chart is dense enough for rendering to become the bottleneck, it normally is already be too crowded to be meaningful. Zooming can justify supporting larger datasets, but sampling/viewport culling and level of detail often avoid drawing unnecessary points...
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I constantly have to work around the slowness of matplotlib when creating animated sequences for my scientific work (even with the Agg back end)
It depends on how much data you are planning on showing, but as you can see from the benchmarks its also more performant than other python charting libs for small data.
We also built this library for extreme customization with CSS/Tailwind support so rendering large amounts of data is an important but not the only advantage.
Ok, we won't convince you and we can move on.
Feel free to not use it, then.
You don't have to justify your decision to people here, literally just move on with your life and forget about it.
There are some niche charting applications which are offloaded to FPGAs and even ASICs.
I think meaningful is in the eye of the beholder. The library is designed such that the trace buffers are directly used as inputs to the WebGL2 drawing contexts to avoid unnecessary copying throughout the stack, which does make a difference when rendering on mobile and embedded devices with limited CPU but often having GPU resources available.