10-20, 11:30–11:35 (Europe/Paris), Main track (Gym)
jupyterWith has made significant improvements this year towards maintainability and ease of use. This talk will discuss those improvements and how you can quickly start creating reproducible Jupyter notebooks.
JupyterLab is a popular web-based interactive development environment for notebooks, code, and data. However, it lacks the ability to lock dependencies and therefore lacks good reproducibility which jupyterWith overcomes by using Nix and Poetry. jupyterWith aims to be simple for researchers and developers and requires minimal understand of Nix and Jupyter to get started.
Beginner
Daniel studied Control Theory, Estimation Theory, and Signal Processing. He spent many years, as a Systems Engineer, analyzing, building, and testing gimbal stabilized platforms. Following that he spent a few years developing Signal Processing and Signal Communications libraries. Now he is passionate about creating clear, maintainable, and well tested code in reproducible systems. He cares about mentoring, teaching, and making complicated software accessible for the end user.