Harden data pipeline against corrupted dataset uploads#570
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Harden data pipeline against corrupted dataset uploads#570
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Checks employment_income, population counts, poverty rate, and income tax against wide bounds after each data build. Would have caught the enhanced CPS overwrite bug (PR #569) where employment_income_before_lsr was dropped, zeroing out all income and inflating poverty to 40%. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Five layers of defense against the bug class from PR #569 where a lossy sparse rebuild overwrote the enhanced CPS, dropping employment_income_before_lsr and zeroing all income: 1. Pre-upload validation gate (upload_completed_datasets.py): - File size check (enhanced CPS must be >100MB, was 14MB when bad) - H5 structure check (critical variables must exist with data) - Aggregate stats check (employment income >5T, household count 100-200M) 2. Post-generation assertions (enhanced_cps.py, small_enhanced_cps.py): - Weight validation (no NaN, no negatives, reasonable sum) - Critical variable existence checks before save - Output file size verification after write 3. CI workflow safety (reusable_test.yaml): - Upload gated on success() so test failures block upload - Pre-upload H5 validation step checks structure before upload - employment_income_before_lsr explicitly checked 4. Makefile hardening: - Sparse file swap validates existence and size before/after - New validate-data target for standalone validation 5. Comprehensive test coverage: - Sparse dataset sanity tests (employment income, household count, poverty) - Direct employment income checks in enhanced and sparse test files - File size regression test (catches the 590MB→14MB shrink) - Small ECPS employment income and household count checks Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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The variable was named optimised_weights_dense but the actual variable from reweight() is optimised_weights. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Summary
Hardens the data pipeline with 5 layers of defense to prevent corrupted datasets from being uploaded to HuggingFace — the bug class from PR #569 where
employment_income_before_lsrwas dropped, zeroing all income and inflating poverty to 40%.Defense layers
upload_completed_datasets.py): File size, H5 structure, and aggregate stats checks run before ANY uploadenhanced_cps.py,small_enhanced_cps.py): Weight validation, critical variable checks, output file size verificationreusable_test.yaml): Upload gated onsuccess(), pre-upload H5 validation stepHow each layer would have caught PR #569's bug
employment_income_before_lsrwas emptycreate_sparse_ecps()output missing critical variablesemployment_income_before_lsrtest_ecps_employment_income_positivecatches $0 employment incomeTest plan
🤖 Generated with Claude Code