07-12, 13:15–13:45 (America/Chicago), Amphitheater 204
The Scientific Python project aims to better coordinate the ecosystem and grow the community. Come hear about our recent progress and our plans for the coming year!
The Scientific Python project's vision is to help pave the way toward a vibrant, unified, and collaborative scientific Python community.
It focuses its efforts along two primary axes: (i) to create a joint community around scientific Python projects
and (ii) to support maintainers by building cross-cutting technical infrastructure and tools.
Last year we launched the project with new websites, a Hugo web theme, a social media campaign, and a collaborative coordination process similar to PEPs called SPECs.
This year, we are fortunate to have received funding from CZI for the continued development, maintenance, and support of web and documentation themes, as well as other community infrastructure, in collaboration with Quansight.
With the community and communication infrastructure having support for the next few years, we are able to focus more on technical topics and the SPECs.
As a first project, we are funded to work on improving sparse array (vs matrix) semantics in SciPy with the goal of removing sparse matrices and, eventually, also NumPy matrices from several ecosystem libraries. In line with our philosophy of continually working with the community and incorporating their feedback, we hosted the first of several Sparse Summits—virtual meetings to identify sparse array needs in ecosystem libraries.
This project spans multiple core projects, including numpy, scipy, scikit-image, networkx, scikit-learn, and many of the packages built on top of these libraries.
In addition to the sparse summit, we have hosted a domain stack summit, to discuss domain-specific umbrella projects that host several others, as well as the first annual developer summit.
This in-person workshop brought together over 30 community members for a week-long, collaborative sprint, and tackled topics including build & testing systems, continuous integration infrastructure, release management tools, and community management.
Finally, we will update the community on our progress on the decadal plan.
Our efforts thus far have already culminated in joint efforts to develop tools and shared infrastructure that will positively impact the whole ecosystem.
And, while there is still a long road ahead, we are excited to continue preparing the ecosystem for the next decade of scientific computing in Python.
Juanita Gomez is passionate programmer, mathematician and open source advocate; former developer of Spyder IDE at Quansight. She has a BS in Pure Mathematics from Pontificia Universidad Javeriana in Colombia and is currently pursuing a Ph.D position in Computer Science at UC Santa Cruz. She is a community manager for the Scientific Python project, a community effort to better coordinate and support scientific Python libraries.