Add entity-level HDFStore output format alongside h5py#568
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Add entity-level HDFStore output format alongside h5py#568
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The stacked_dataset_builder now produces a Pandas HDFStore file (.hdfstore.h5) in addition to the existing h5py file. The HDFStore contains one table per entity (person, household, tax_unit, spm_unit, family, marital_unit) plus an embedded _variable_metadata manifest recording each variable's entity and uprating parameter path. The upload pipeline uploads HDFStore files to dedicated subdirectories (states_hdfstore/, districts_hdfstore/, cities_hdfstore/). A comparison test (test_format_comparison.py) validates that both formats contain identical data for all variables. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Replaces the two-file-input test with a self-contained roundtrip script that takes only an h5py file path, generates an HDFStore using inlined splitting logic, then compares both formats. Handles entity-level h5py files and yearly/ETERNITY/monthly period keys. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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Fixes #567
Related to PolicyEngine/policyengine-us#7700
Summary
stacked_dataset_builder.pynow produces a Pandas HDFStore file (.hdfstore.h5) alongside the existing h5py file, with one table per entity and an embedded uprating manifeststates_hdfstore/,districts_hdfstore/,cities_hdfstore/)Test plan
stacked_dataset_builderon a single CD/state and confirm both.h5and.hdfstore.h5files are createdpytest test_format_comparison.py --h5py-path STATE.h5 --hdfstore-path STATE.hdfstore.h5and confirm all variables match_variable_metadatamanifest with correct entity and uprating columns🤖 Generated with Claude Code