🔗 Ruff, MyPy, pytest, and then what?

Structural quality in AI-written Python code is often overlooked. The article reveals how tools like Ruff, mypy, and pytest don’t catch issues like code duplication, which can frustrate agents during development. Agents sometimes mirror code across multiple functions and modules without realizing it, leading to confusion and inefficiency. By running structural analyses on a repository and leveraging tools like pyscn, the author shows the impact of code complexity and duplication over time. A few strategic changes can mitigate these issues for better collaboration between human developers and AI. Clear rules for function imports and tracking average complexity are essential for maintaining a clean codebase. Understanding and addressing these pitfalls can enhance the overall structure and readability of Python projects, benefiting both human and AI developers alike.