fix: find_ending_with too slow

[AloneFire]

find_ending_with Find all qualified names ending with the given suffix using DFS on the trie.
This avoids a full scan of the _entries dict and instead walks the trie structure once, checking each stored qualified name.

[gemini-code-assist]

Summary of Changes

Hello @AloneFire, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request addresses a performance bottleneck in the find_ending_with method within the graph_updater.py module. By replacing a linear scan of all entries with a more efficient Depth-First Search (DFS) traversal of the underlying trie structure, the method can now locate qualified names ending with a specific suffix much faster, significantly improving the overall efficiency of name lookups.

Highlights

• Performance Improvement: The find_ending_with method in codebase_rag/graph_updater.py has been refactored to significantly improve its performance.
• Algorithm Change: The method now utilizes a Depth-First Search (DFS) traversal on the trie structure instead of a full scan of the _entries dictionary, making suffix-based lookups much more efficient.

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[gemini-code-assist]

Code Review

This pull request aims to optimize the find_ending_with method by replacing a full scan of the _entries dictionary with a DFS traversal on the trie. While the change is functionally correct, the new implementation duplicates logic that already exists in the find_with_prefix_and_suffix method. My review includes a suggestion to refactor the new method to reuse the existing one, which will improve code maintainability by removing redundancy.

[vitali87]

Thanks for the PR! The refactor to reuse find_with_prefix_and_suffix is a nice cleanup.

However, I think the performance reasoning in the description is slightly off. Tries are optimized for prefix lookups, so searching for a suffix still requires visiting every node in the tree. There's no pruning possible when the prefix is empty.

Actually, the new implementation is likely slower in practice. The DFS traverses every trie node (intermediate modules plus leaves) rather than just the qualified names in _entries. On top of that, recursive Python function calls have significantly more overhead than iterating a flat dictionary, which uses CPython's optimized C implementation.

[vitali87]

One more question: what would deprecating _entries actually give us? Is there a concrete memory or maintainability benefit you're aiming for?

[AloneFire]

One more question: what would deprecating _entries actually give us? Is there a concrete memory or maintainability benefit you're aiming for?

You're right, I didn't think through the implementation carefully. However, DFS did show significant speed improvements on my project. I've pushed a new commit that optimizes this using a different approach—trading space for time through indexing.

[vitali87]

1. Trailing Whitespace

Line 83 has trailing whitespace. Please install pre-commit hooks:

pre-commit install

This runs automatically on every commit and catches formatting issues.

2. No Benchmark Data

I previously asked about performance reasoning. Please provide before/after benchmark results.

3. Insufficient Test Coverage

Add tests for:

• Multi-part suffix: find_ending_with("Logger.info")
• Suffix index cleanup after deletion
• Multiple entries with same suffix

4. Coding Standards

Review CONTRIBUTING.md for project coding standards.

---

Please address all of these and re-request review. Thanks!