Stata-class statistics, GPU-accelerated by Apple Silicon. Native Swift — no Electron, no Python runtime, no compromises.
-
Wed, Aug 5, 2026 2
-
perf(data): 880x faster loads via DuckDB C-API bulk extraction
…
- root cause: duckdb-swift's element(forColumn:at:) linearly rescans every chunk on every element access — O(rows x chunks); a 10M-row CSV load took 276 s - DuckDBFastReader: pointer-based duckdb C calls via @_silgen_name (the C library is statically linked; only pointer-argument functions are declared, so no struct-ABI exposure), private in-memory instance, contiguous column_data/nullmask_data extraction - ZQDataStore.dataFrame(fromQuery:): LIMIT-0 schema probe through the supported API, SQL-side casts to DOUBLE/VARCHAR, memcpy per numeric column; dead per-element materializer removed - measured (M4-class): 10M-row parquet 0.20 s, csv 0.31 s, summarize ~0.27 s, robust reg ~0.24 s — CLAUDE.md §8 budgets met; table updated with measured numbers - 116 tests green (identical numerics through the new path) - version 1.0.1 Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
-
docs: README with badges, screenshots, and the v1.0 story
…
- hero: console session showing cluster-robust factor regression and the GPU-batched 10k bootstrap; screenshot grid (Charts by(), Metal 2M, data browser, manual) - shields badges: release, macOS 14+, Swift 6, arm64, Metal+MLX, 116 tests, R-validated 1e-10, notarized DMG - five-minute tour, feature matrix, numerical-validation section, architecture, build instructions, extensibility examples - METRIKA_AUTOPANE debug hook (headless pane selection for screenshots) Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
-