Great, Rust and Tailwind CSS two of my favorite things in one.
NickyHeC•Jul 28, 2026
been stuck on matplotlib for centuries, academia loves such a change
apetuskey•Jul 28, 2026
Thanks! Yes we are working on a Matplotlib compatible Api its very early but we hope to polish it up soon.
airstrike•Jul 28, 2026
> XY is an extremely fast, interactive, customizable Python charting library for the web
apetuskey•Jul 28, 2026
I have adjusted the title
kasts•Jul 28, 2026
I’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...
apetuskey•Jul 28, 2026
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.
formerly_proven•Jul 28, 2026
There are some niche charting applications which are offloaded to FPGAs and even ASICs.
Evidlo•Jul 28, 2026
I constantly have to work around the slowness of matplotlib when creating animated sequences for my scientific work (even with the Agg back end)
apetuskey•Jul 28, 2026
How many points are you working with usually?
moralestapia•Jul 28, 2026
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.
cozzyd•Jul 28, 2026
no support for native GUI?
apetuskey•Jul 28, 2026
What do you mean by this?
cozzyd•Jul 28, 2026
like, not in a browser?
ranger_danger•Jul 28, 2026
> written in Rust
> XY is an extremely fast, interactive, customizable Python charting library
which is it?
apetuskey•Jul 28, 2026
Its a Python library with some rust in it, to speed up some of the calculations
xg15•Jul 28, 2026
Python libraries can have compiled artifacts that were written in any language. This is such a library.
pcpliu•Jul 28, 2026
I misread it as ‘Chatting’ library and I was so confused on the GitHub page.
Love rust as the impl.
adhami•Jul 28, 2026
it's possible to render data out-of-core with XY, allowing it to render the entirety of OpenStreetMaps (that's 10,742,674,832 nodes!) with sub-second pan/zooms. it's a bit difficult to host online but you can try it out locally: https://github.com/reflex-dev/xy/tree/main/examples/osm
kl01•Jul 28, 2026
absolutely fantastic.
kl01•Jul 28, 2026
super cool!
HoneySpoons•Jul 28, 2026
This is awesome, can easily see this becoming a standard library. Can't wait for the 3D and volume visualizations.
ahns•Jul 28, 2026
Interesting; how do the examples compare to datashader?
Edit: for my use cases, I use napari (~1e7-8 points) if I need true interactivity; otherwise, datashader/holoviz, or even just fast-histogram's 2D histograms work.
For extremely large point clouds, these caveats[0] still apply. It irks me when people make dense scatterplots without any indication of just how dense some portions are.
Still, if it can indeed handle 1e10 points, that's pretty impressive.
how does this stack up to evilcharts? my main use case is mapping out data onto frontend, and there are a lot of great libraries out there
apetuskey•Jul 28, 2026
its a python charting library
hantusk•Jul 28, 2026
Check out mosaic from uwdata which works on top of Observable plot
Or plotly-resampler which works on top of plotly and uses the rust package tsdownsample to aggregate on the 4pixels per pixel shown level (to make antialias work)
the grammar of graphics approach really is a great abstraction, and I'd love to see xy work in that direction
raychis•Jul 28, 2026
Interesting approach to large scale visualisation. Moving reduction into Rust and sending screen bounded data to WebGL seems much more sensible than pushing millions of raw points into the browser. How does it perform with real time updates? I am assuming it is much more performant? Any plans for a prod deployment?
apetuskey•Jul 28, 2026
Yes, it’s significantly faster than existing Python charting libraries for real-time updates.
Instead of serializing and sending the full dataset as JSON, it sends compact typed binary buffers and only the screen-relevant data reducing payload size and browser-side work.
15 Comments
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.
You don't have to justify your decision to people here, literally just move on with your life and forget about it.
> XY is an extremely fast, interactive, customizable Python charting library
which is it?
Love rust as the impl.
Edit: for my use cases, I use napari (~1e7-8 points) if I need true interactivity; otherwise, datashader/holoviz, or even just fast-histogram's 2D histograms work.
For extremely large point clouds, these caveats[0] still apply. It irks me when people make dense scatterplots without any indication of just how dense some portions are.
Still, if it can indeed handle 1e10 points, that's pretty impressive.
[0]: https://datashader.org/user_guide/Plotting_Pitfalls.html
Or plotly-resampler which works on top of plotly and uses the rust package tsdownsample to aggregate on the 4pixels per pixel shown level (to make antialias work)
the grammar of graphics approach really is a great abstraction, and I'd love to see xy work in that direction
Instead of serializing and sending the full dataset as JSON, it sends compact typed binary buffers and only the screen-relevant data reducing payload size and browser-side work.
More detail here https://github.com/reflex-dev/xy#how-it-works