AwesomeDataviz

High-performance & GPU plotting libraries for Python

Plotting millions of points and real-time data. 5 tools, ranked by GitHub stars and updated .

Libraries for data too large or too fast for standard plotting. VisPy, glumpy and fastplotlib render with the GPU, PyQtGraph is built for real-time plots in Qt applications, and Datashader rasterizes billions of points into accurate images.

By GitHub stars, the most popular Python GPU plotting libraries here are PyQtGraph (4.4K stars), VisPy (3.6K stars), and Datashader (3.6K stars). 4 of 5 had commits in the last 90 days.
1 PyQtGraph

Interactive and realtime 2D/3D/Image plotting and science/engineering widgets.

 4.4K 352 MIT
2 VisPy

High-performance scientific visualization based on OpenGL.

 3.6K 63 BSD-3-Clause
3 Datashader

Renders very large datasets into accurate images by rasterizing them.

 3.6K 74 BSD-3-Clause
4 fastplotlib

GPU-accelerated plotting library built on WGPU and pygfx for fast interactive visualization.

 1.5K 40 Apache-2.0
5 glumpy Inactive

OpenGL scientific visualizations library.

 1.3K 0 BSD-3-Clause

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Frequently asked questions

What is the most popular Python GPU plotting library?

By GitHub stars, PyQtGraph is the most popular, with 4.4K stars, followed by VisPy (3.6K) and Datashader (3.6K).

Which Python GPU plotting libraries are actively maintained?

4 of the 5 tools listed had commits in the last 12 months, including PyQtGraph, VisPy, Datashader, and fastplotlib. Each tool page shows monthly commit activity.

Are these Python GPU plotting libraries free and open source?

5 of the 5 tools listed use an OSI-approved open-source license. The most common license here is BSD-3-Clause.

Missing a tool? Add it with a one-line pull request to the README.