How and why to run modified Python code using the ast module

The text delves into the intricacies of using Python's Abstract Syntax Tree (AST) module for parsing, understanding, and manipulating Python code, highlighting its potential in tackling complex tasks and its relevance with the advent of AI. The author explains how the AST can be used to backport modern Python type hint syntax to older versions, showcasing this through the eval-type-backport library. Several code snippets illustrate the process of transforming ASTs, such as replacing the | operator with safe_or to maintain compatibility across Python versions. The article also emphasizes the value of metaprogramming skills in enhancing one's career, noting the author's own experiences with companies like Grist and Pydantic. Furthermore, it argues that as AI increasingly automates routine code, advanced skills like metaprogramming will become more crucial, especially for AI agents that can execute Python code to improve their functionalities. This exploration of AST and its applications is part of a broader series on Python metaprogramming, aimed at deepening the reader’s understanding and capabilities in Python, with future posts promising insights into import hooks, tracing, and more.