Swizz: One-Liner Figures, LaTeX Tables, and Flexible Layouts for Scientific Papers

Lars C.P.M. Quaedvlieg, Andrea Miele, Caglar Gulcehre

Keywords: Python Library, Visualization, LaTeX Tables, Machine Learning, Plotting, Scientific Workflows, Open Source

TL;DR: Swizz is a lightweight Python library for one-liner creation of publication-ready figures, LaTeX tables, and layouts. It features extensive docs with live previews and a gallery, streamlining ML paper visualization and reducing formatting overhead.

Abstract: Producing publication-quality visualizations and tables for machine learning papers is often tedious, time-consuming, and prone to inconsistencies. We introduce Swizz, a lightweight Python library designed specifically for researchers to effortlessly generate elegant figures, LaTeX-ready tables, and customizable figure layouts with minimal code. Swizz enables one-liner creation of consistent, conference-ready visualizations, including advanced plots and multilevel tables, and provides intuitive, composable layouts to simplify complex figure arrangements. Its automated styling and built-in visual gallery facilitate rapid experimentation, allowing researchers to focus more on research and less on formatting. Swizz is publicly available, easy to integrate into existing workflows, and themed for major machine learning publication venues. Swizz is open source (MIT) and is available on GitHub and PyPI.

Submission Number: 15