JDS Journal of Data Science 1683-8602 1680-743X 1680-743X School of Statistics, Renmin University of China JDS998 10.6339/21-JDS998 Computing in Data Science Reproducible Science with LATEX BarHaimhaim.bar@uconn.edu1∗ WangHaiYing1 Department of Statistics, University of Connecticut, Storrs, CT, USA Corresponding author. Email: haim.bar@uconn.edu. 20212812021 191111125 Supplementary Material

Detailed examples and documentation are available in a GitHub repository at https://github.com/Ossifragus/runcode. The runcode LATEX package is available via CTAN, and the talk2stat Python package for the server-mode is available at https://pypi.org/project/talk2stat/.

 82020 112020 2021 The Author(s). Published by the School of Statistics and the Center for Applied Statistics, Renmin University of China.2021 Open access article under the CC BY license.

This paper proposes a procedure to execute external source codes from a LATEX document and include the calculation outputs in the resulting Portable Document Format (pdf) file automatically. It integrates programming tools into the LATEX writing tool to facilitate the production of reproducible research. In our proposed approach to a LATEX-based scientific notebook the user can easily invoke any programming language or a command-line program when compiling the LATEX document, while using their favorite LATEX editor in the writing process. The required LATEX setup, a new Python package, and the defined preamble are discussed in detail, and working examples using R, Julia, and MatLab to reproduce existing research are provided to illustrate the proposed procedure. We also demonstrate how to include system setting information in a paper by invoking shell scripts when compiling the document.

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