⚡ Bolt: [performance improvement] Optimizing SQLite insertions by replacing execute with executemany in _record_user_decision#234
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…cing execute with executemany in _record_user_decision Eliminates an N+1 performance bottleneck during batch file processing by grouping user feedback into a single `executemany` database insertion. Avoids executing repeated SQL parsing and reduces Python-to-C API crossover overhead, speeding up processing for large file groups. Co-authored-by: thebearwithabite <216692431+thebearwithabite@users.noreply.github.com>
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2 participants
💡 What
Replaced a loop of repeated
conn.execute()queries with a singleconn.executemany()operation inside_record_user_decisionininteractive_batch_processor.py. Also hoisted invariant calculations (e.g.,datetime.now().isoformat(),json.dumps) out of the iteration loop.🎯 Why
Executing sequential
INSERTstatements within a Pythonforloop over large arrays introduces significant N+1 performance overhead. Consolidating into a single batchedexecutemany()operation drastically reduces latency and minimizes roundtrips across the database boundary.📊 Impact
Eliminates O(N) repetitive SQL parses and significantly decreases batch processing time and CPU load when evaluating decisions on heavily populated file previews arrays.
🔬 Measurement
Tests via unit testing execution and a mock script execution verifying identical output properties (i.e., table entries persist successfully per
session_id).PR created automatically by Jules for task 12303098320918172003 started by @thebearwithabite