⚡ Bolt: O(N) Precomputation in 3-Way Match#32
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Refactored `execute_3_way_match` in `src/plugins/supply_chain.py` to precompute normalized descriptions and tokens for candidates outside the inner loop. What: Created `_prepare_candidates` function and updated matching functions to accept precomputed tokens instead of raw strings. Why: Previously, `_normalize_description` and string tokenization were repeatedly executed inside a nested loop comparing `invoice_items` against `po_lines` and `receipt_lines`. This resulted in O(N*M) string and regex operations, slowing down execution for large item lists. Impact: Reduces time complexity of string/regex operations from O(N*M) to O(N+M), significantly improving matching speed. In tests, it reduced execution time from ~0.98s to ~0.17s (~82% speedup). Measurement: Tested logic and performance with isolated benchmark. Tests confirmed correct execution and expected speedup. Co-authored-by: kourdroid <36898160+kourdroid@users.noreply.github.com>
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💡 What: Added
_prepare_candidatesto precompute normalized descriptions and tokens. Updated_match_scoreand_find_best_matchto accept precomputed values instead of calculating them for every comparison. Updatedexecute_3_way_matchto use the precomputed candidates.🎯 Why:
_normalize_descriptionand tokenization operations were inside the inner loop of a nested loop checking every invoice item against every PO line and receipt line. This caused O(NM) expensive string operations which caused a bottleneck for larger lists.📊 Impact: Reduces time complexity of the repetitive string operations from O(NM) to O(N+M), drastically improving performance (measured ~82% speedup).
🔬 Measurement: Verified functionality using
pytesttest suite, verified speedup using benchmark script, and verified code usingflake8.PR created automatically by Jules for task 6760937199755700660 started by @kourdroid