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.
The Scientific Python project aims to better coordinate the ecosystem and prepare scientific Python for the next decade of data science. We provide resources, planning, and coordination for the community.
Our roadmap indicates the type of large, fundamental changes to individual projects and the ecosystem more generally that are likely to take months or years to realize. Given the distributed decision-making processes of the ecosystem, progress on the roadmap is dependent on support and agreement from the community.
Improved common infrastructure & process#
- Reusable libraries with commonly used functionality
- Shared build system for binary packaging
- Integrated websites and expanded documentation
- Shared benchmarking
- Developer Operations (DevOps)
Better coordination of the ecosystem#
- Community best operating and development practices manual
- Coordinated release schedule
- Regular cross-project communication
- Joint governance structures
Shared development vision#
- Videos archive of project challenges, strategies, and visions
- Community vetted strategic plan