Coding for Chemists

Welcome to the companion site for the Coding for Chemists book!

Coding for Chemists is a book (forthcoming, summer 2025) by professors Christopher Johnson (Stony Brook University) and Benjamin Lear (The Pennsylvania State University) aimed at helping chemists learn to code in Python. The target audience for the book are people who have workflows common to chemical research and that they would like to streamline or to which they would like to add additional capabilities or data visualization. Thus, the book presents core Python concepts, data visualization, and data analysis topics as needed in the context of a student researcher’s evolving thesis research project. It begins with the automation of large-scale experimental design in well plates (Chapter 1) and rapidly progresses to automated fitting of complex models to data (Chapter 6). At the end of each chapter, the reader will both understand more of Python and have a new tool that could be immediately used in chemical research. A complete list of workflows and topics can be found in the Table of Contents.

The book assumes no prior knowledge of coding, but does assume a basic familiarity with experimental chemical research—perhaps equivalent to that of a 2nd year undergraduate chemistry laboratory class. Each chapter of the book introduces a common problem encountered in chemical research, presents a complete Python-based solution to this problem, and then provides exercises to practice the knowledge and skills presented in the chapter.

The book is written to be used either for independent study by individuals and groups of students or as the foundation of a course devoted to teaching students Python in a chemical context—at either the undergraduate or graduate level. On this website we present guidance for such stand-alone courses, as well as for how the book might be adapted for use across an entire undergraduate curriculum. In addition to this website, we will are hosting a discord community about the book.