About the talk

Python's flexible and intuitive syntax enables developers to quickly build applications. But on the other hand, it may be slow during runtime. There have been different attempts into making Python faster. In recent years, Python 3.11 was released and popularized as the "faster Python" and Mojo programming language was recently announced, advertised as having "usability of Python with the performance of C". Going back further, we see languages such as Cython, Just In Time (JIT) compilers and bindings.

In this talk, we'll go over the different approaches to increasing the speed of a Python application. We'll briefly explain how they work, compare the performance through a simple use case, and look at the limitations, tooling, trade-offs, and ease of use.

Outline

• Introduction and setup (3min)
• Baseline - Python 3.9 (3min)
• Alternatives (20min):
• Python 3.11
• Cython & Mypyc
• Pypy3
• PyO3
• Mojo
• Recap and takeaways (4min)