⚡ Bolt: Replace asdict() with direct access in storage layer#26
⚡ Bolt: Replace asdict() with direct access in storage layer#26
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Identify and address a performance bottleneck in the storage layer where `dataclasses.asdict()` was used for every database insertion and retrieval result. - Replaced `asdict()` with direct attribute access in `ObserverStore.record_event`, `WikiBrain.store_record`, `SessionStore.upsert_session`, and `SessionStore.record_episode`. - Introduced `BrainRecord.to_dict()` for optimized serialization in `WikiBrain.cognitive_recall` and `WikiBrain.review_playbook`. Performance impact (measured via benchmark): - `BrainEvent` recording serialization: ~20x speedup (1.08s -> 0.05s for 100k records). - `BrainRecord` search result serialization: ~8x speedup (1.26s -> 0.15s for 100k records). Co-authored-by: jhweb <12529192+jhweb@users.noreply.github.com>
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💡 What:
Optimized the serialization of dataclasses in the persistence layer by replacing the built-in
dataclasses.asdict()with direct attribute access and manual dictionary construction.🎯 Why:
asdict()is a known bottleneck in Python's standard library for performance-critical paths because it performs recursive traversal and deep copying, even for simple data structures. In a memory-intensive application like BRAINDRAIN that frequently records events and queries records, this adds unnecessary overhead.📊 Impact:
🔬 Measurement:
Verified with two benchmark scripts (
bench_asdict.pyandbench_wiki_brain.py) comparingasdict()vs direct access over 100,000 iterations.asdict(): ~1.26sdirect/manual: ~0.05s - 0.15sAll existing tests in
tests/pass with these changes.PR created automatically by Jules for task 9600068806259228845 started by @jhweb