numbduck 0.0.1

No project description provided

NumbDuck

Adapting DuckDB database API to the Numba JIT context.

Leverages bindings toolkit in the NumbOx project.

Inspired by the NumbSQL project.

Examples

Runnable narrative-style examples comparing numbduck against the closest stock DuckDB Python+Arrow approaches live in examples/. Each script is self-contained, generates its own data, and prints the measured numbers.

Highlights:

• Throughput (haversine.py): JIT chunk callback is ~400× faster than a per-row Python scalar UDF (10K rows) and ~100× faster than a PyArrow expression UDF at 1M rows. The win comes from no Python crossings per chunk and LLVM-fused math with no intermediate arrays.

• Latency + GIL-free (online_scoring.py): ~2.2× lower per-event latency vs pure-Python conn.execute, and monotonic parallel scaling to ~2.4× on 8 threads while the Python loop plateaus under GIL contention.

• Branchy logic (fraud_score.py): Arrow's pc.if_else chain beats the Python scalar UDF by ~60× (Arrow is the right stock-DuckDB tool here). The JIT chunk callback then beats Arrow by ~16× at 10K and ~1750× at 1M rows — the gap grows because each Arrow UDF chunk crosses the Python boundary and allocates intermediates, while the JIT computes in registers.