Cython

I first presented Cython in 2020. Five years and several major releases later, I wanted to see whether that old advice still held up. This talk looked at what changed in Cython, whether it got faster, and whether it became any easier to use. I worked through a few demo problems and compared the results with modern Python and its performance libraries. Abstract Python is often praised for its speed of development but criticized for its execution speed. However, this has changed significantly in recent years due to major improvements in both Python itself and its most popular libraries. Libraries such as TensorFlow, OpenCV, NumPy, and Pandas all use a tool called Cython. Cython is an extension of Python that allows functions to be compiled into C or C++, mitigating Python’s performance limitations. ...

Back when I first got hired at SHARCNET, I used a lot of Python. I mean a lot. This meant I quickly became the lightning rod for all Python-related questions and commentary. During a fun Friday chat, a colleague remarked that Python was, on average, 40x slower than C++. I defended my current language of choice, saying it was better than that, surely. To make a long story short, I was wrong. It really is about 40x slower depending on the problem. Determined to prove myself capable, and my language of choice a bit more defensible, I decided to look into ways to make Python faster. ...