PERF: fix slow repr for Series/DataFrame with third-party array-like objects#64638
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jbrockmendel wants to merge 1 commit intopandas-dev:mainfrom
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PERF: fix slow repr for Series/DataFrame with third-party array-like objects#64638jbrockmendel wants to merge 1 commit intopandas-dev:mainfrom
jbrockmendel wants to merge 1 commit intopandas-dev:mainfrom
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…objects Replace the duck-type is_sequence() check in pprint_thing() with an explicit isinstance allowlist. Previously, any object with __iter__ and __len__ (e.g. xarray DataArray) would be recursively iterated element-by-element via _pprint_seq, causing ~20,000 expensive repr calls for a single DataArray. Now only types that _pprint_seq was designed to handle are iterated; everything else uses str() directly. Closes pandas-dev#61809 Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Summary
is_sequence()check inpprint_thing()with an explicitisinstanceallowlist of types that_pprint_seqwas designed to handle.__iter__and__len__(e.g. xarrayDataArray) would be recursively iterated element-by-element, causing ~20,000 expensive repr calls for a single large DataArray stored in an object-dtype column.str(), using the object's own repr.Closes #61809
Test plan
test_printing.py,test_format.py,test_formats.py,test_repr.py,test_groupby.py,test_sorting.py,test_to_string.pyall pass🤖 Generated with Claude Code