Show HN: XY – A Fast, composable, GPU-accelerated interactive plotting library
github.com83 points by apetuskey 5 hours ago
83 points by apetuskey 5 hours ago
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?
Yes its is more performant than existing Python charting libs for updates https://github.com/reflex-dev/xy#how-it-works
The details can be found here but essentially instead of sending everything as JSON it sends a more compact payload of typed binary buffers reducing the size of the data sent
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
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...
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.
There are some niche charting applications which are offloaded to FPGAs and even ASICs.
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.
[0]: https://datashader.org/user_guide/Plotting_Pitfalls.html
This is awesome, can easily see this becoming a standard library. Can't wait for the 3D and volume visualizations.
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
been stuck on matplotlib for centuries, academia loves such a change
Thanks! Yes we are working on a Matplotlib compatible Api its very early but we hope to polish it up soon.
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
I misread it as ‘Chatting’ library and I was so confused on the GitHub page.
Love rust as the impl.
> XY is an extremely fast, interactive, customizable Python charting library for the web
Great, Rust and Tailwind CSS two of my favorite things in one.
absolutely fantastic.
> written in Rust
> XY is an extremely fast, interactive, customizable Python charting library
which is it?
Python libraries can have compiled artifacts that were written in any language. This is such a library.
Its a Python library with some rust in it, to speed up some of the calculations
no support for native GUI?
super cool!