In this talk, we will explore the world of Just-In-Time (JIT) compilation within the CPython interpreter. As Python continues to grow in popularity, performance enhancements are crucial to meet the demands of modern applications. The new CPython JIT implementation represents a tool for pushing Python's performance forward in a scalable, maintainable way.

I will start by exploring the mechanics of JIT compilation, explaining how it differs from traditional interpretation. Next, I will provide an overview of the current state of the CPython JIT in Python 3.14, highlighting its latest advancements and performance improvements. I will also briefly touch on my personal contributions to this project. By sharing these insights, I aim to inspire others to engage with open-source projects and contribute to the ongoing innovation within the Python ecosystem.

Finally, we will discuss practical applications of the CPython JIT and how you can enable it in your applications. Attendees will gain a clear understanding of how the JIT dynamically translates Python code into machine code at runtime using the CPython 3.14 implementation as reference and will learn how to use the JIT on their own Python applications.