The Scientific Python project aims to better coordinate the ecosystem and grow the community. This session focuses on our efforts to better coordinate project development, and to improve shared infrastructure. In this session together we will discuss project goals and recent technical work. The Scientific Python project’s vision is to help pave the way towards a unified, expanded scientific Python community. It focuses its efforts along two primary axes: (i) to create a joint community around all scientific projects and (ii) to support maintainers by building cross-cutting technical infrastructure and tools. In this session we mostly focus on the second aspect. The project has already launched a process whereby projects can, voluntarily, adopt reference guidelines; these are known as SPECs or Scientific Python Ecosystem Coordination documents. SPECs are similar to projects specific guidelines like PEPs, NEPs, SLEPs, and SKIPs, to name a few. The distinction being that SPECs have a broader scope, targeted at all (or most) projects from the scientific Python ecosystem. The project also provides and maintains tools to help maintainers. This includes a theme for the project websites (used on, e.g., numpy.org and scipy.org), a self-hosted privacy-friendly web analytics platform, a community discussions forum, a technical blog, and project development statistics. We present these tools, discuss various upcoming SPECs, and highlight the project’s future potential.
The Scientific Python project aims to better coordinate the ecosystem and grow the community. This session focuses on our efforts to better coordinate project development, and to improve shared infrastructure. In this session together we will discuss project goals and recent technical work. The Scientific Python project’s vision is to help pave the way towards a unified, expanded scientific Python community. It focuses its efforts along two primary axes: (i) to create a joint community around all scientific projects and (ii) to support maintainers by building cross-cutting technical infrastructure and tools. In this session we mostly focus on the second aspect. The project has already launched a process whereby projects can, voluntarily, adopt reference guidelines; these are known as SPECs or Scientific Python Ecosystem Coordination documents. SPECs are similar to projects specific guidelines like PEPs, NEPs, SLEPs, and SKIPs, to name a few. The distinction being that SPECs have a broader scope, targeted at all (or most) projects from the scientific Python ecosystem. The project also provides and maintains tools to help maintainers. This includes a theme for the project websites (currently used on, e.g., numpy.org and scipy.org), a self-hosted privacy-friendly web analytics platform, a community discussions forum, a technical blog, and project development statistics. We present all these tools, discuss various upcoming SPECs, and highlight the project’s future potential. The Scientific Python project is already supported by eight core projects: IPython, Matplotlib, NetworkX, NumPy, pandas, scikit-image, scikit-learn, and SciPy. The organization has spent the last several months working on the infrastructure, and is now ready to engage more widely to help grow and support the community.
Speakers: Jarrod Millman