rmv f from _create_arrow_py_udf

python/pyspark/sql/connect/udf.py

@@ -78,7 +78,7 @@ def _create_py_udf(
         and not isinstance(return_type, ArrayType)
     )
     if is_arrow_enabled and is_output_atomic_type and is_func_with_args:
-        return _create_arrow_py_udf(f, regular_udf)
+        return _create_arrow_py_udf(regular_udf)
     else:
         return regular_udf
 

python/pyspark/sql/udf.py

@@ -141,19 +141,20 @@ def _create_py_udf(
         and not isinstance(return_type, ArrayType)
     )
     if is_arrow_enabled and is_output_atomic_type and is_func_with_args:
-        return _create_arrow_py_udf(f, regular_udf)
+        return _create_arrow_py_udf(regular_udf)
     else:
         return regular_udf
 
 
-def _create_arrow_py_udf(f, regular_udf):  # type: ignore
+def _create_arrow_py_udf(regular_udf):  # type: ignore
     """Create an Arrow-optimized Python UDF out of a regular Python UDF."""
     require_minimum_pandas_version()
     require_minimum_pyarrow_version()
 
     import pandas as pd
     from pyspark.sql.pandas.functions import _create_pandas_udf
 
+    f = regular_udf.func
     return_type = regular_udf.returnType
 
     # "result_func" ensures the result of a Python UDF to be consistent with/without Arrow