June 16, 2026
Walk? More like a full sprint
Making ast.walk 220x Faster
Python got roasted as devs cheered a Rust rescue and argued if the speedup was worth it
TLDR: A developer made Python’s code-tree scanner massively faster after discovering the built-in approach was the bottleneck, then rewrote the hottest part in Rust. Commenters were equal parts amused and ruthless, joking that Rust was inevitable and dunking on Python for being slow in surprisingly ordinary code.
A programmer set out to fix a painfully slow code-checking tool and ended up turning a sleepy Python tree-walk into something 220 times faster. The practical problem was simple: their app was generating huge amounts of Python code, and when the code was wrong, the checker only found one mistake at a time. That meant more waiting, more reruns, and more frustration. So they built a custom linter—basically a code spellchecker—and then discovered the real villain was the built-in way Python walks through code structures.
But the article’s real fireworks came from the crowd. The most on-the-nose joke landed immediately: “let me guess, the improved version is written in Rust?” And yes, that was the twist, which made the comments feel like a sitcom where everyone already knows the ending. Another commenter gave rare applause for the author first trying to squeeze more speed out of plain Python before calling in Rust, while others turned it into a bigger debate about whether Python is secretly terrible at its own “nice, clean code” philosophy. One brutal hot take summed up the mood: Python punishes you for modularizing your code.
Then came the practical peanut gallery: could this trick speed up tools like LibCST or Bandit too? Could the whole thing have been done with Semgrep rules instead? So while the article is about speed, the comments are really about something juicier: when does polishing Python stop making sense, and when do you just hand the job to Rust and move on?
Key Points
- •The article describes building a custom linter for Reflex-generated Python code because existing linters did not support Reflex-specific rules.
- •`ast.walk` was identified as a major performance bottleneck when processing large volumes of generated code.
- •The author attributes much of the overhead in Python AST traversal to generator-based helpers such as `ast.walk`, `iter_child_nodes`, and `iter_fields`.
- •A series of Python-level changes—including list accumulation, inlining helper logic, and avoiding unused tuple data—produced cumulative speed improvements reported at roughly 5%, 25%, 50%, and 55%.
- •After Python-level optimizations plateaued, the traversal logic was rewritten in Rust with PyO3 bindings, which the article presents as the basis for the much larger speedup in the title.