SciPy 2023

"Notebooks can be a powerful tool for the purposes for which they were designed—learning, experimenting, and sharing results. However, users face many challenges when trying to achieve true reproducbility with notebooks alone, including lack of dependency management, pitfalls of non-linear interactive execution, and requiring bespoke tooling to open and execute. Furthermore, there is a growing need to go beyond reprodubility of individual results—siloed into an opaque format possessing limited interoperability with the rest of the Python ecosystem—toward reusuability of research methods, that can be shared, built upon, and deployed by users across the world.

Therefore, we invite the community to share their tools and workflows to go beyond reproducibility and towards true reusable science, built on the shoulders of giants. Furthermore, we hope to explore how we can encourage users and the community to move beyond the notebooks monoculture and toward a holistic, open, modular and interoperable approaches to conducting research and developing scientific code."