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This book is neither a textbook on Python programming, nor a tutorial for a specific tool, nor a textbook on quantum chemistry theory. It represents a combining experience from both academic research and industrial practice. The content of this book is designed to help you better understand advanced Python programming technologies and how to apply these techniques to practical quantum chemistry programs.
• This book is not intended as a tutorial on quantum chemistry theories. When presenting applications in quantum chemistry, we will briefly describe the background and formalism of quantum chemistry theory, but detailed derivations will be omitted. For a deeper understanding of the theory, it is recommended to consult more specialized quantum chemistry textbooks, such as Modern Quantum Chemistry by Szabo, Molecular Electronic-Structure Theory by Helgaker, and Methods of Molecular Quantum Mechanics by McWeeny.
• This book does not teach Python programming syntax. Before diving into this book, it is recommended that readers acquire some basic knowledge of Python programming. For the basics of Python coding, readers can refer to the Python documentation or other Python programming textbooks, such as Fluent Python by Ramalho and Think Python by Downey [6]. Additionally, this book involves some knowledge of C/C++, networking, and operating systems. Although not prerequisites, some knowledges in these areas will enhance the understanding of the content presented in this book.
• This book does not intend to present detailed instructions on how to install or use specific software packages. Instead, we discuss the principles, designs, and trade-offs of various Python packages.
• Although many of the techniques and insights in this book are derived from the Python quantum chemistry package PySCF, this book is not intended to serve as a programming reference or a user guide for PySCF.
• The examples discussed in this book may not represent the latest or most efficient algorithms and implementations. Our focus is not on the theoretical models, methodologies, or optimal algorithms. Instead, we aim to demonstrate how a technology or a Python feature can be applied in quantum chemistry. Some technologies may appear different from traditional implementations of quantum chemistry programs. We hope this approach will inspire you to use these technologies in your own projects.
When selecting content for this book, we considered the ifluence of many new technologies on modern software, such as heterogeneous computation, cloud computing. We have intentionally included discussions on new technologies to enrich the content. If you are interested in these areas, you will find relevant application examples in the book. We strongly encourage the use of AI tools to explore technologies. Some very basic knowledge can be delegated to ChatGPT or other AI tools, which is an effective method for quickly learning new technologies. Although this book is not specifically about how to use AI tools, in some chapters, we demonstrate the AI prompts directly. These examples can serve as a reference for using AI coding tools. The content of this book is written in depth, and we have intentionally omitted many fundamental topics. We strive to avoid presenting knowledge and techniques that can be easily acquired through the use of search engines or AI tools.