The challenges of managing ever-growing codebases are hardly new. As far back as 1995, Niklaus Wirth, (creator of programming language Pascal) already emphasized the importance of keeping software lean in his essay A Plea for Lean Software. Fast forward to today: many programmers still face the reality that, despite their best coding intentions, as projects grow in size and complexity, so do their codebases. Even when a project scales to millions of lines of code, developers still expect their IDE to be fast, accurate, and efficient. And with increasingly large and interconnected (dare I say, spaghetti?) code, you probably rely on your IDE even more to help you navigate the chaos (ahem I mean complexity).

Python is one of the most successful programming languages out there, with it recently overtaking Javascript as the most popular language on GitHub, according to the latest GitHub Octoverse report. The report emphasises the popularity of the language in the growing fields of AI, data science and scientific computing - fields where speedy experimentation and iteration are critical, and where developers are coming from a broad range of STEM backgrounds, not necessarily computer science. But as the Python community expands and projects grow from experiments to production systems, that same flexibility can become a liability.

That’s why today we’re going to talk about typed Python - what it is, why it’s become important for Python developers today, and how to get started using it to write higher quality, more reliable code.

Today we are announcing an alpha version of Pyrefly, an open source Python typechecker and IDE extension crafted in Rust. Pyrefly is a static type checker that analyzes Python code to ensure type consistency and help you catch errors throughout your codebase before your code runs. It also supports IDE integration and CLI usage to give you flexibility in how you incorporate it into your workflow.