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The following commit(s) were added to refs/heads/master by this push:
     new 73de7ccc8314 [SPARK-52419][PYTHON][TESTS] Make Python Connect tests 
work with NumPy 2.3.0
73de7ccc8314 is described below

commit 73de7ccc8314a00e300561e421a5ecbec0f1b0f5
Author: Hyukjin Kwon <[email protected]>
AuthorDate: Sun Jun 8 21:48:22 2025 -0700

    [SPARK-52419][PYTHON][TESTS] Make Python Connect tests work with NumPy 2.3.0
    
    ### What changes were proposed in this pull request?
    
    This PR proposes to skip a type definition test with NumPy 2.3 for now.
    
    ### Why are the changes needed?
    
    To fix the build for Python Connect client 
(https://github.com/apache/spark/actions/runs/15521622757/job/43695591595). It 
fails after NumPy got upgraded to 2.3.0.
    
    ### Does this PR introduce _any_ user-facing change?
    
    No, test-only.
    
    ### How was this patch tested?
    
    Manually.
    
    ### Was this patch authored or co-authored using generative AI tooling?
    
    No.
    
    Closes #51120 from HyukjinKwon/SPARK-52419.
    
    Authored-by: Hyukjin Kwon <[email protected]>
    Signed-off-by: Hyukjin Kwon <[email protected]>
---
 python/pyspark/pandas/tests/test_typedef.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/python/pyspark/pandas/tests/test_typedef.py 
b/python/pyspark/pandas/tests/test_typedef.py
index cac9aaf193a0..329af01a3944 100644
--- a/python/pyspark/pandas/tests/test_typedef.py
+++ b/python/pyspark/pandas/tests/test_typedef.py
@@ -313,7 +313,6 @@ class TypeHintTestsMixin:
     def test_as_spark_type_pandas_on_spark_dtype(self):
         type_mapper = {
             # binary
-            np.character: (np.character, BinaryType()),
             np.bytes_: (np.bytes_, BinaryType()),
             bytes: (np.bytes_, BinaryType()),
             # integer
@@ -347,6 +346,9 @@ class TypeHintTestsMixin:
                 LongType(),
             ),
         }
+        if LooseVersion(np.__version__) < LooseVersion("2.3"):
+            # binary
+            type_mapper.update({np.character: (np.character, BinaryType())})
 
         for numpy_or_python_type, (dtype, spark_type) in type_mapper.items():
             self.assertEqual(as_spark_type(numpy_or_python_type), spark_type)


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