Zifeng Li's code for Computational Physics(计算物理), you can find some classic topics, including OdeSolver， Numerical Integral， Interpolation，PDE Equation from Ode Here, Some interesting problems like Ising Model, Kuramoto Model, DLA Model, ... are also up for grabs.
You can Learn Basic Coding Skills and use dynamic Programming Language(Python) to solve practial problems, you will learn how to using powerful tools including numpy, scipy and useful visualization tool including matplotlib, seaborn. If you prefer, you can build fundamental tools like fft, odesolver for yourself.
This code base privide some coding results from homeworks. Let's use ode (ordinary derivative equation, 常微分方程) as an example : usually you will be told Eular methods, backward Eular method. But do you know why these methods can work and what do they do?
The reason is that these methods are different approaching of Taylor Series (泰勒级数), but how to get these formulars? And how to use these formulars to get powerful codes?
You are strongly recommended learning and rebuilding this code base, when you are learning Computational Physica(计算物理) Just follow the classes, and rebuild what the teacher told you, and compair what you do with this codebase