perf: anonymize files in parallel with a process pool#23
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armand0e merged 2 commits intoJul 10, 2026
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Each file gets its own TraceAnonymizer, so files are fully independent and can be processed concurrently. Directory anonymization now fans out over a ProcessPoolExecutor sized to the machine's CPU count, falling back to the sequential path for small batches where process startup would cost more than it saves. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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Directory anonymization processed files strictly sequentially, but each file already gets its own
TraceAnonymizerinstance (replacement maps are per-trace by design), so files are fully independent.This fans the per-file work out over a
ProcessPoolExecutorsized toos.cpu_count()(falling back to 1 when unavailable — no hardware assumptions). Batches under 8 files keep the sequential path, since process startup would cost more than it saves. Report ordering, per-file scoping, and output are unchanged;executor.mappreserves the sorted file order.Testing
pytest tests/test_extract_anonymize_cli.py— 32 passed🤖 Generated with Claude Code