08/10, 14:30–15:05 (Europe/London), Tejita (Sala 1.9)
Idioma: English
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)
Intermediate (it is necessary to understand the related bases to go into detail)
Temática –Other
Murilo is a tech lead AI at Dataroots. He takes a pragmatic approach aiming to make AI both impactful and accessible. To that end, Murilo has an emphasis on MLOps when building ML systems. He's passionate about open-source, programming, and knowledge sharing.