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pytheory/tests
kennethreitz b68cec889f feat(audio): render_scores() — parallel batch rendering across cores
A single render_score is already fast, so the multicore win is in batch
work: exporting an album, rendering many clips, serving several requests.
render_scores(scores, workers=) renders each Score independently on its
own thread; NumPy releases the GIL during the heavy math, so it scales
~2x on a typical machine with zero change to how any Score sounds.

(Within-a-single-render parallelism was measured and rejected: renders are
already ~0.2s and the process-pool spawn + buffer serialization overhead
made it slower, on audio-critical, non-deterministic code.)

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-17 03:13:24 -04:00
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