Biomolecular Crystallographic Computing with Jupyter

—The ease of use of Jupyter notebooks has helped biologists enter scientific computing, especially in protein crystallography, where a collaborative community develops extensive libraries, user-friendly GUIs, and Python APIs. The APIs allow users to use the libraries in Jupyter. To further advance this use of Jupyter, we developed a collection of code fragments that use the vast Computational Crystallography Toolbox ( cctbx ) library for novel analyses. We made versions of this library for use in JupyterLab and Colab. We also made versions of the snippet library for the text editors VS Code, Vim, and Emacs that support editing live code cells in Jupyter notebooks via the GhostText web browser extension. Readers of this paper may be inspired to adapt this latter capability to their domains of science.