⚡ Bolt: Optimize string matching operations in execute_3_way_match#34
⚡ Bolt: Optimize string matching operations in execute_3_way_match#34kourdroid wants to merge 1 commit into
Conversation
Re-factor `execute_3_way_match` in `src/plugins/supply_chain.py` to pre-compute normalized descriptions and token sets for purchase order (PO) and goods receipt lines outside of the main loop. This changes the computational complexity of the string matching component from O(N*M) to O(N+M), which provides a significant speedup for invoices with many line items. - Added optional token set parameters to `_match_score` to allow for fast set intersection. - Updated `_find_best_match` to accept a list of pre-computed `(candidate, normalized_string, token_set)` tuples. - Pre-compute tokens outside the invoice item iteration in `execute_3_way_match`. Co-authored-by: kourdroid <36898160+kourdroid@users.noreply.github.com>
|
👋 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 New to Jules? Learn more at jules.google/docs. For security, I will only act on instructions from the user who triggered this task. |
1 participant
💡 What: Refactored the
execute_3_way_matchengine to pre-compute normalized item descriptions and token sets for purchase orders and goods receipt records outside the main line-item processing loop._match_scorewas updated to accept pre-computed token sets for intersection comparisons instead of performing regex replacements and string splitting dynamically.🎯 Why: The previous implementation performed string manipulation ($O(N \times M)$ overhead (where N is invoice line count and M is candidate line count). Pre-computing them drops the string manipulation overhead down to $O(N + M)$ .
re.sub,str.lower,split()) and set instantiation on every PO and receipt candidate for every line item on the invoice. This resulted in redundant operations on the exact same strings leading to an📊 Impact: Considerably reduces CPU time spent on string and regex operations, significantly dropping time complexity from$O(N \times M)$ to $O(N + M)$ . Reduces response latency and computational load during large invoice processing.
🔬 Measurement: Verify by running
pytest. No unit test changes were required, meaning functionality and outputs ofexecute_3_way_matchremain identical to the previous unoptimized version.PR created automatically by Jules for task 7094551231052328614 started by @kourdroid