I read most of the 1st edition (busy), I'm sure it hasn't changed much to the 2nd. I would say it's rather good at an introductory level to the subject!

It definitely targets physics undergrads who have never programmed so if that's not you then you may feel friction during some chapters. If, like me, you are much more developed in programming than physics you might just want to do the exercises in the first few chapters to check your knowledge and move on to the good bits.

If you're looking for something more rigorous I would bet [Numerical Recipes](https://numerical.recipes/) is better (I haven't read it but I want to; see "busy").

> Exercises by chapter

Click on a chapter to download:

Chapter 2: Python programming for physicists

Chapter 3: Graphics and visualization

Chapter 4: Accuracy and speed

Chapter 5: Integrals and derivatives

Chapter 6: Solution of linear and nonlinear equations

Chapter 7: Fourier transforms

Chapter 8: Ordinary differential equations

Chapter 9: Partial differential equations

Chapter 10: Random processes and Monte Carlo methods

Chapter 11: Data science

Looks like not much. The book is about using Python to implement numerical methods, mainly about teaching the Python part, and that's all explained. You might be missing motivation if you don't know any physics, but even so, basic mechanics using differential equations seems to be enough to give context, at least for the earlier parts

Weber's Electrodynamics.

Just to give a bit of flavor, I was a math + physics major in the 80s. The physics curriculum had some oddly named courses such as "theoretical physics" that were not really physics courses but were meant to give you the math and computational background needed for the more advanced courses or for graduate work. The math was stuff that wasn't covered extensively enough in the math major courses, such as vector calculus.

Isn't it a pretty standard book/memoir template?

He could have invested in a Python syntax highlighter. I use minted, myself, but I'm sure there are many alternatives.

I hope that's sarcastic. Physics is the original computational science.

Should be modernized to Python or similar.

In 2026, I don't want to do numerical programming in C. That was fine 30 years ago, but today, I expect to have garbage collection or to be able to multiply a matrix as A×B.