Python is pretty much the most popular programming language out there right now. It runs everything from basic web apps to crazy advanced AI systems. But despite all the love it gets, it has one really obvious flaw… it is notoriously slow.
For a long time, the holy grail for the Python community has been figuring out how to make the language run faster without losing what makes it so easy to write in the first place. The magic bullet everyone talks about is a JIT compiler. But before we get into the latest drama about Python’s attempt to build one, let’s break down what a JIT actually is.
What is a JIT Compiler?
Imagine you have a book written in English, and you need to present its contents to a Spanish-speaking audience. You generally have two ways to handle this.
First, you have the compiled approach. You hire a translator to sit down and translate the entire book into Spanish before the presentation. It takes a lot of time up front, but when you step on stage, you can just read the Spanish version smoothly and rapidly. Languages like C++ and Rust work this way.
Second, you have the interpreted approach. You step on stage with the English book and a live interpreter. You read a sentence in English, the interpreter thinks for a second, and then translates it into Spanish out loud. It requires zero prep time, but the actual presentation takes much longer because you are constantly pausing to translate. Python currently works this way.
JIT, which stands for Just-In-Time, is a clever hybrid of the two.
Imagine you are using that live interpreter, but they are incredibly smart. They notice that you keep reading the exact same introductory paragraph at the start of every chapter. Instead of translating that paragraph from scratch in their head every single time, the interpreter writes down the Spanish translation on a cheat sheet. The next time you read that English paragraph, the interpreter just reads instantly from the cheat sheet.
In the software world, a JIT compiler watches your program as it runs, identifies the code that gets repeated over and over, and quietly translates those parts into hyper-fast, machine-ready instructions on the fly.
Why JIT?
The beauty of a JIT compiler is how it gives you the best of both worlds.
Programmers love interpreted languages because they are flexible, easy to work with, and let you test your code instantly without waiting for a massive translation process, but users hate slow apps. JIT bridges this gap. It allows developers to write code quickly and comfortably, while the engine works behind the scenes to give the software a massive speed boost right when the user needs it most.
Implications for Python
For Python, a native JIT compiler would be an absolute game changer.
Because Python is intrinsically slow, developers who need high performance, like data scientists crunching millions of rows of data or game developers rendering graphics, often have to write the heavy lifting parts of their code in more complex languages like C or C++. Python is frequently just used as a friendly wrapper around that complex code.
If Python had a built-in JIT compiler, developers wouldn’t have to learn a second language just to make their programs run fast. Pure Python code could run lightning-fast right out of the box. It would democratize high performance and make it accessible to anyone who knows basic Python.
A Bump in the Road
This brings us to the latest news, which honestly is a bit of a heartbreak for speed enthusiasts.
Back in early 2024, an experimental JIT compiler was added to the main version of Python for its 3.13 release. It was a huge moment that had the community buzzing with excitement. However, as detailed in a recent update from LWN.net, the project has hit a wall.
The Python Steering Council, the governing body that ensures Python remains stable and secure, requested a formal proposal outlining exactly how this massive new feature would be maintained long-term. A JIT is incredibly complex, and the council rightfully demanded guarantees around backwards compatibility, security reviews, and cross-platform support before making it a permanent fixture.
Ultimately, the developers behind the JIT proposal realized that meeting the council’s high bar required more personal time and energy than they could realistically commit to right now. They have withdrawn their proposal, and the experimental JIT code will be removed from Python’s main branch.
While the authors still believe in the technical direction of the project, the dream of a native Python JIT is officially on pause. For now, Python developers will have to stick to their traditional tricks to squeeze out extra speed. But the groundwork has definitely been laid, and the community hasn’t given up on the need for speed just yet.
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