Taichi Blogs

Imagine you'd like to write a new particle-based fluid algorithm. You started simple, didn't spend much time before finding a reference C++/CUDA work online (or derived the work from your labmate, unfortunately). cmake .. && make, you typed. Oops, cmake threw out an error due to a random incompatible third party library. Installed and rebuilt, now it passed. Then you ran it, which immediately segfaulted (without any stacktrace, of course). Then you started gazing at the code, placed the necessary asset files at the right place, fixed a few dangling pointers and reran. It... actually worked, until you plugged in your revised algorithm. Now another big fight with the GPU or CPU code. More often than not, you get lost in the language details.

Ever since the Python programming language was born, its core philosophy has always been to maximize the readability and simplicity of code. In fact, the reach for readability and simplicity is so deep within Python's root, that if you type import this in a Python console, it will recite a little poem: