2025-08-20 –, Room 2.41 (First floor)
There has been much progress in SciPy, scikit-learn and interesting efforts around Array API as well as some progress in dispatching similar to the NetworkX dispatching.
This session is to discuss d future plans and pain points for libraries to further adopt these patterns.
This session will be split in two parts. First we wish discuss Array API adoption into libraries, how to continue this work and what needs to be done.
There has been a lot of progress in adoption across several libraries and interesting efforts like https://github.com/mdhaber/marray.
What are patterns that work well or need improvement in the future?
In the second part, we want to discuss adoption of dispatching and backend selection across libraries. NetworkX has this for a long time and scikit-image has experimented with it in the past year.
We plan on showing the spatch design, but wish to focus discussion on what the missing pieces are for libraries to adopt spatch or similar patterns.
none
Expected audience expertise: Python:expert
Your relationship with the presented work/project:Maintainer of the presented library/project
I am a scikit-learn core maintainer and work at NVIDIA.
Before working on scikit-learn I helped build mybinder.org and worked on JupyterHub.
Many years ago I was a particle physicist at CERN in Geneva.
Sebastian has been a NumPy developer for about 10 years now. After a PhD in phsyics he worked at as a postdoc at the Berkeley Institute for Datascience on NumPy as grants byt the Alfred P. Sloan Foundation and the Gordon and Betty Moore Foundation. Since 2022 he has been a software engineer at NVIDIA where he continues to contribute to NumPy.