perf: accelerate exact count-table parsing and preserve strict input boundaries - #149
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October 4, 2026 08:45
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Ordinary raw-count cells previously passed through regex and Decimal parsing. Parse unsigned ASCII integers of at most 64 characters directly as exact integers, preserving counts above 2**53. Longer inputs, signed values, decimals and scientific notation retain the existing Decimal path and limits; Unicode digits remain invalid and unselected sample columns remain validated.
The production diff against current main is the five-line count-parser fast path. Main already contains the equivalent FASTQ printable-ASCII optimization, and this branch retains main's implementation. Added 537 boundary cases cover byte-range characters, Unicode, lossless counts, conversion limits and unselected columns.
The reproducible benchmark and raw evidence in
docs/audits/2026-09-30-input-throughput.{md,json}record the original 30 September baseline/candidate pair. Five alternating Linux/CPython 3.12 runs measured count-table parsing at 0.468 → 0.176 seconds (2.66x throughput) for 10,000 guides × 32 samples, with identical complete parsed-output hashes. These are synthetic Python parsing measurements, including output hashing; they do not establish whole-assay speedups. The historical FASTQ measurement describes the optimization already integrated into main. These measurements were not rerun during reconciliation.Current integration validation incorporates main through
2fa3532549d5945991aba2d7645af66108206497, including the strict native gzip fix:make all shared test cli-test python-test: native build, both C test executables, CLI fixtures and native/Python FASTQ parity pass; 2,069 Python tests pass, with 7 optional-integration skips on Linux/CPython 3.12.git diff --check: clean.Draft until the updated branch's complete GitHub Actions matrix passes. Native matching and scientific policies are unchanged.