[SPARK-56816][PYTHON][TESTS] Patch pandas UDF input-type coercion golden in memory for Pandas 3#55793
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…emory for Pandas 3 In `_compare_or_generate_golden`, when running under Pandas >= 3.0, replace 'object' with 'str' in the Python Type column for rows whose Spark Type is `string`. Pandas 3 reports the dedicated `str` dtype for string columns where earlier versions reported `object`, so the same golden CSV works under both versions without regenerating. Generated-by: Claude Code (claude-opus-4-7)
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…den in memory for Pandas 3 ### What changes were proposed in this pull request? In `PandasUDFInputTypeTests._compare_or_generate_golden`, after loading the golden CSV, replace `'object'` with `'str'` in the `Python Type` column for rows whose `Spark Type` is `string`, but only when running under Pandas `>= 3.0`. The golden file on disk is unchanged. ### Why are the changes needed? The daily-scheduled `Build / Python-only (master, Python 3.12, Pandas 3)` workflow is failing `test_pandas_input_type_coercion_vanilla`: ``` line mismatch: expects ['string_values', 'string', "['abc', '', 'hello']", "['object', 'object', 'object']", ...] but got [..., "['str', 'str', 'str']", ...] line mismatch: expects ['string_null', 'string', "[None, 'test']", "['object', 'object']", ...] but got [..., "['str', 'str']", ...] ``` Pandas 3.0 changed the default representation of string columns from numpy `object` dtype to the dedicated `str` dtype, so the pandas UDF that records `str(series.dtype)` now reports `'str'` for string inputs and the recorded `Python Type` column no longer matches the golden. The values themselves are unchanged. See https://github.com/apache/spark/actions/runs/25611987987/job/75184547983 for the failing run. ### Does this PR introduce _any_ user-facing change? No. Test-only change. ### How was this patch tested? Ran the full test module under a Pandas 3 conda env (Python 3.13.12, Pandas 3.0.2, PyArrow 23.0.1, NumPy 2.4.3): ``` $ python/run-tests --testnames "pyspark.sql.tests.coercion.test_pandas_udf_input_type" Tests passed in 17 seconds ``` The Pandas `< 3.0` branch is a no-op, so existing behaviour is preserved. ### Was this patch authored or co-authored using generative AI tooling? Generated-by: Claude Code (claude-opus-4-7) Closes #55793 from zhengruifeng/pandas3-pandas-udf-input-type-coercion. Authored-by: Ruifeng Zheng <ruifengz@apache.org> Signed-off-by: Hyukjin Kwon <gurwls223@apache.org> (cherry picked from commit 5d21070) Signed-off-by: Hyukjin Kwon <gurwls223@apache.org>
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What changes were proposed in this pull request?
In
PandasUDFInputTypeTests._compare_or_generate_golden, after loading the golden CSV, replace'object'with'str'in thePython Typecolumn for rows whoseSpark Typeisstring, but only when running under Pandas>= 3.0. The golden file on disk is unchanged.Why are the changes needed?
The daily-scheduled
Build / Python-only (master, Python 3.12, Pandas 3)workflow is failingtest_pandas_input_type_coercion_vanilla:Pandas 3.0 changed the default representation of string columns from numpy
objectdtype to the dedicatedstrdtype, so the pandas UDF that recordsstr(series.dtype)now reports'str'for string inputs and the recordedPython Typecolumn no longer matches the golden. The values themselves are unchanged.See https://github.com/apache/spark/actions/runs/25611987987/job/75184547983 for the failing run.
Does this PR introduce any user-facing change?
No. Test-only change.
How was this patch tested?
Ran the full test module under a Pandas 3 conda env (Python 3.13.12, Pandas 3.0.2, PyArrow 23.0.1, NumPy 2.4.3):
The Pandas
< 3.0branch is a no-op, so existing behaviour is preserved.Was this patch authored or co-authored using generative AI tooling?
Generated-by: Claude Code (claude-opus-4-7)