Fix equivalent() for NumPy scalar NaN comparison #10838
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Fixes pydata#10833 where NaN attributes were incorrectly dropped after NetCDF roundtrip when using combine_attrs="drop_conflicts". The issue: np.float64(np.nan) == np.float64(np.nan) returns np.bool_(False) instead of Python bool, causing the code to return False before reaching the NaN equivalence check. The fix: Check for NaN equivalence before doing the equality comparison, avoiding the np.bool_ type trap entirely. Co-authored-by: Claude <[email protected]>
The test requires NetCDF backend libraries (netCDF4, h5netcdf, or scipy) which are not available in the bare-minimum test environment. Co-authored-by: Claude <[email protected]>
dcherian
approved these changes
Oct 10, 2025
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Fixes #10833
Problem
equivalent()returnedFalsefor NumPy scalar NaN comparisons likenp.float64(np.nan), causing NaN attributes to be incorrectly dropped when usingcombine_attrs="drop_conflicts"after NetCDF roundtrip.Root Cause
np.float64(np.nan) == np.float64(np.nan)returnsnp.bool_(False)(not Pythonbool). The old code converted this to Python bool and returnedFalseimmediately, preventing the NaN equivalence check from running.Fix
Check for NaN equivalence before the equality comparison, avoiding the
np.bool_type issue entirely.Changes
xarray/core/utils.py: Moved NaN check before equality comparisonxarray/tests/test_utils.py: Added tests for Python float & NumPy scalar NaNxarray/tests/test_concat.py: Added integration test for NetCDF roundtrip scenario🤖 Generated with Claude Code