Effective Computation in Physics with Python

This book is an O'Reilly practical guide for researchers in computational physics. The Chinese edition was brought out by Posts & Telecom Press under its Asynchronous Books imprint, translated by Sun Boxiang. Built around a four-part structure, it bridges the gap between being able to write physics formulas and being able to write maintainable research code. Part I, Getting Started (Chapters 1–6), opens with the command line, Python programming basics, and basic containers, then moves through flow control and logic, functions, and classes and objects, giving physics readers with no programming background a foundation in the language. Part II, Getting Your Hands Dirty (Chapters 7–13), turns to real research scenarios: analysis and visualization, regular expressions, thinking in NumPy arrays, storing data in plain files and HDF5, data structures commonly used in physics such as hash tables and k-d trees, threading, multiprocessing, and MPI parallelization, and software deployment tools including pip, Conda, virtual machines, and Docker. Part III, Getting It Right (Chapters 14–18), shifts to engineering craft: build processes such as make, local and remote version control, debugging, and testing. Part IV, Getting It Out There (Chapters 19–23), covers generating code documentation, publishing research results, collaboration, licenses and copyright, and further reflections on computational physics. The book runs to 23 chapters plus a glossary, threads examples from physics projects throughout, and emphasizes replacing repetitive manual computation and data wrangling with automation.