학술논문

A PyMOL Snippet Library for Jupyter to Boost Researcher Productivity
Document Type
Periodical
Source
Computing in Science & Engineering Comput. Sci. Eng. Computing in Science & Engineering. 23(2):47-53 Apr, 2021
Subject
Computing and Processing
Bioengineering
Communication, Networking and Broadcast Technologies
Libraries
Python
Proteins
Graphical user interfaces
Biological information theory
Task analysis
Software development management
Language
ISSN
1521-9615
1558-366X
Abstract
Snippets—code templates one line or longer—boost researcher productivity because they are faster to insert than writing the code from scratch and because they reduce debugging time. Several extensions support the use of snippets in Jupyter. We developed a Python version of the pymolsnips library and customized it for the use in the jupyterlab-snippets-multimenus extension for JupyterLab. The extension provides access to the snippets by pull-down menus. Each snippet performs one task. Each task often requires many lines of code. This library’s availability in Jupyter enables PyMOL users to run PyMOL efficiently inside Jupyter while storing the code and the associated molecular graphics images next to each other in one notebook document. This proximity of code and images supports reproducible research in structural biology, and the use of one computer file facilitates collaborations.