Skip to content

⚡ Bolt: [performance improvement] Avoid eager list materialization in AST traversal - #133

Open
tachyon-beep wants to merge 1 commit into
mainfrom
bolt-perf-ast-eager-lists-14090105435108711551
Open

⚡ Bolt: [performance improvement] Avoid eager list materialization in AST traversal#133
tachyon-beep wants to merge 1 commit into
mainfrom
bolt-perf-ast-eager-lists-14090105435108711551

Conversation

@tachyon-beep

Copy link
Copy Markdown
Collaborator

💡 What: Updated _assignment_callee and _collect_return_paths to take Iterable[ast.AST] instead of list[ast.AST]. Avoided eagerly wrapping generators like ast.iter_child_nodes() and standard lists like func_node.body in list(...).
🎯 Why: Creating intermediate lists during deep recursive AST walks wastes memory and time by forcing Python to allocate and populate list objects that are only used sequentially.
📊 Impact: Reduced memory pressure and allocations across recursive function body traversal.
🔬 Measurement: Verified that tests pass properly and no functionality breaks. Added a performance learning to .jules/bolt.md.


PR created automatically by Jules for task 14090105435108711551 started by @tachyon-beep

Updated `_assignment_callee` and `_collect_return_paths` in `src/wardline/scanner/taint/variable_level.py` to accept `Iterable[ast.AST]` instead of `list[ast.AST]`. Updated their callers to pass `ast.iter_child_nodes(node)` generators and `func_node.body` direct lists directly instead of wrapping them in `list(...)`. This avoids eagerly materializing intermediate lists, reducing memory allocation overhead.

Co-authored-by: tachyon-beep <544926+tachyon-beep@users.noreply.github.com>
Copilot AI review requested due to automatic review settings August 3, 2026 16:37
@google-labs-jules

Copy link
Copy Markdown
Contributor

👋 Jules, reporting for duty! I'm here to lend a hand with this pull request.

When you start a review, I'll add a 👀 emoji to each comment to let you know I've read it. I'll focus on feedback directed at me and will do my best to stay out of conversations between you and other bots or reviewers to keep the noise down.

I'll push a commit with your requested changes shortly after. Please note there might be a delay between these steps, but rest assured I'm on the job!

For more direct control, you can switch me to Reactive Mode. When this mode is on, I will only act on comments where you specifically mention me with @jules. You can find this option in the Pull Request section of your global Jules UI settings. You can always switch back!

New to Jules? Learn more at jules.google/docs.


For security, I will only act on instructions from the user who triggered this task.

@chatgpt-codex-connector

Copy link
Copy Markdown

You have reached your Codex usage limits for code reviews. You can see your limits in the Codex usage dashboard.
To continue using code reviews, add credits to your account and enable them for code reviews in your settings.

Copilot AI left a comment

Copy link
Copy Markdown

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Pull request overview

This PR optimizes AST traversal in the taint scanner by avoiding unnecessary eager list materialization during recursive walks, reducing intermediate allocations and memory pressure in hot-path analysis.

Changes:

  • Updated _assignment_callee and _collect_return_paths to accept Iterable[ast.AST] instead of list[ast.AST].
  • Removed list(...) wrapping around func_node.body and ast.iter_child_nodes(...), passing iterables directly.
  • Added a short performance note to .jules/bolt.md capturing the learning and action.

Reviewed changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated no comments.

File Description
src/wardline/scanner/taint/variable_level.py Switches traversal helpers to Iterable and removes eager list() materialization in recursive AST walking.
.jules/bolt.md Documents the performance learning and recommended pattern for AST traversal.

💡 Add Copilot custom instructions for smarter, more guided reviews. Learn how to get started.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment

Labels

None yet

Projects

None yet

Development

Successfully merging this pull request may close these issues.

2 participants