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.
replyOk, we won't convince you and we can move on.
replyI constantly have to work around the slowness of matplotlib when creating animated sequences for my scientific work (even with the Agg back end)
replyHow many points are you working with usually?
replyIt 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.
replyWe 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.
Feel free to not use it, then!
replyYou don't have to justify your decision to people here, literally just move on with your life and forget about it.
I’m not trying to justify whether I'd personally use it, I was simply raising the question because the tradeoffs are interesting, and the replies, including Evidlo’s, have already taught me something.
replyI tried the library before commenting, it’s a cool project. The performance improvements at larger scales I've found are real. I was mainly just trying to have a conversation to learn where we all learn!
“Just move on” seems like a curious response on a discussion forum, though :)
There are some niche charting applications which are offloaded to FPGAs and even ASICs.
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