With an extensive and high-quality ecosystem of libraries, scientific Python has emerged as the leading platform for data analysis. This ecosystem is sustained by independent volunteers with separate mailing lists, websites, roadmaps, documentation, engineering and packaging solutions, and governance structures. Unfortunately, this also means that there is a lack of coordination that results in duplicated effort, disorganized documentation, breakage upon new releases, unintended performance regressions, and user confusion. Moreover, we have no venue for developing a formal, shared vision of the future.
Our objective is to prepare scientific Python for the next decade of data science. To this end, we will:
- Improve common engineering infrastructure,
- Better coordinate core projects,
- Write a community vetted strategic plan, and
- Help the community develop grant proposals.
The developers of these projects are technically able; but they have little time to coordinate efforts within their own projects, let alone focus on strategies for bringing the entire ecosystem together. This project will provide support where it is deeply needed.
Read the full grant.
Since the grant was written pre-COVID-19, we are currently rethinking our original approach, recruiting the advisory council, and shaping the initial stage of the grant. Watch this space for more, early in 2021!
This work is funded in part by the Gordon and Betty Moore Foundation through grant GBMF8599 to the University of California, Berkeley.