9fe989b5021aedb829ea09277de09e58beb00ae3
Architecture: DuckDB for persistence + full in-memory materialization for reads. All reads served from Python dicts (sub-microsecond). DuckDB only hit on writes. Performance evolution (get_asset benchmark): V0 (raw DuckDB): 876µs per call V1 (LRU cache): 2.3µs per call (380x) V2 (in-memory): 0.2µs per call (4380x) All reads now sub-microsecond: get_asset: 0.2µs (was 876µs) query(blockian): 6.6µs (was 2.2ms) query(sector): 6.6µs (was 3.2ms) exchange lookup: 12.5µs (was 1.5ms) full scan: 5.9µs (was 1.8ms) behavior: 0.4µs Write path: sync_from_profiles batch-inserts all data, then materializes into Python dicts. Resync: 76ms (was 210ms, 2.8x faster). Data integrity: DuckDB WAL provides crash recovery. In-memory dicts are reconstructed from DB on every sync/close-reopen cycle. Zero data loss.
Description
Sentiment analysis engine with ONNX FinBERT + LoRA adapters
Languages
Python
99.9%
Dockerfile
0.1%