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UID:pretalx-scipy-2026-MEKP9F@pretalx.com
DTSTART;TZID=CST:20260716T112500
DTEND;TZID=CST:20260716T115500
DESCRIPTION:After 3 years\, Pixi is widely adopted in the scientific Python
  ecosystem. At SciPy 2026\, we want to show why.\n\nScientific Python has 
 specific challenges that Pixi can solve well\; a lot of our beloved packag
 es contain C\, C++\, Rust\, CUDA or even Fortran code. With Pixi\, a singl
 e tool can install the compilers\, different Python versions and other bui
 ld tools in one go\, thanks to piggy backing on the years of development t
 hat the Conda ecosystem has seen.\n\nThanks to Pixi’s task system and na
 tive multi-platform capabilities\, the contributor experience is also enha
 nced. Daunting tasks like running CMake\, installing the correct Rust vers
 ion or C++ compilers are all hidden away behind a magical: `pixi run fooba
 r`.\n\nAre you interested to see how you could improve your own workflow a
 nd learn from what these big open-source projects are doing? Then you shou
 ld join this talk! You'll be amazed by what is possible these days.
DTSTAMP:20260715T022642Z
LOCATION:Memorial Hall
SUMMARY:Scipy\, Numpy\, Xarray and Python all have a pixi.toml. Why? - Rube
 n Arts
URL:https://pretalx.com/scipy-2026/talk/MEKP9F/
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