Fix pandas-dev#61072: inconsistent fullmatch results with regex alternation

in PyArrow strings
Fixes an issue where regex patterns with alternation (|) produce
different results between str dtype and string[pyarrow] dtype. When
using patterns like "(as)|(as)", PyArrow implementation would
incorrectly match "asdf" while Python's implementation correctly
rejects it. The fix adds special handling to ensure alternation
patterns are properly parenthesized when using PyArrow-backed
strings

Author: Pedro-Santos04

pandas/core/strings/accessor.py

@@ -1461,16 +1461,67 @@ def fullmatch(self, pat, case: bool = True, flags: int = 0, na=lib.no_default):
         match : Similar, but also returns `True` when only a *prefix* of the string
             matches the regular expression.
         extract : Extract matched groups.
-
+        
+        Notes
+        -----
+        This method enforces consistent behavior between Python's string dtype
+        and PyArrow-backed string arrays when using regular expressions
+        containing alternation (|). For regex patterns with alternation operators,
+        the method ensures proper grouping by wrapping the pattern in parentheses
+        when using PyArrow-backed string arrays.
         Examples
         --------
         >>> ser = pd.Series(["cat", "duck", "dove"])
         >>> ser.str.fullmatch(r"d.+")
-        0   False
-        1    True
-        2    True
+        0    False
+        1     True
+        2     True
+        dtype: bool
+        Ensure consistent behavior with alternation patterns:
+        >>> ser = pd.Series(['asdf', 'as'], dtype='string[pyarrow]')
+        >>> ser.str.fullmatch(r"(as)|(as)")
+        0    False
+        1     True
         dtype: bool
         """
+        is_pyarrow = False
+        arr = self._data.array
+        arr_type = type(arr).__name__
+        is_pyarrow = arr_type == "ArrowStringArray"
+        if not is_pyarrow:
+            is_pyarrow = "Arrow" in arr_type
+            if not is_pyarrow and hasattr(arr, "dtype"):
+                dtype_str = str(arr.dtype)
+                is_pyarrow = "pyarrow" in dtype_str.lower() or "arrow" in dtype_str.lower()
+        if is_pyarrow and "|" in pat:
+            def _is_fully_wrapped(pattern):
+                if not (pattern.startswith('(') and pattern.endswith(')')):
+                    return False     
+                inner = pattern[1:-1]
+                level = 0
+                escape = False
+                in_char_class = False
+                for char in inner:
+                    if escape:
+                        escape = False
+                        continue   
+                    if char == '\\':
+                        escape = True
+                    elif not in_char_class and char == '[':
+                        in_char_class = True
+                    elif in_char_class and char == ']':
+                        in_char_class = False
+                    elif not in_char_class:
+                        if char == '(':
+                            level += 1
+                        elif char == ')':
+                            if level == 0:
+                                return False
+                            level -= 1
+                return level == 0
+            if not (pat.startswith('(') and pat.endswith(')') and 
+                    _is_fully_wrapped(pat)):
+                pat = f"({pat})"
         result = self._data.array._str_fullmatch(pat, case=case, flags=flags, na=na)
         return self._wrap_result(result, fill_value=na, returns_string=False)
 

pandas/tests/strings/test_pyarrow_format_behavior.py

@@ -0,0 +1,31 @@
+import pytest
+from pandas import (
+    Series,
+)
+@pytest.mark.parametrize("dtype", ["string[pyarrow]", str])
+def test_string_array(dtype):
+    test_series = Series(['asdf', 'as'], dtype=dtype)
+    regex = r'((as)|(as))'
+    regex2 = r'(as)|(as)'
+    assert list(test_series.str.fullmatch(regex)) == [False, True]
+    assert list(test_series.str.fullmatch(regex2)) == [False, True]
+@pytest.mark.parametrize(
+    "data, pattern, expected",
+    [
+        (["cat", "duck", "dove"], r"d.+", [False, True, True]),
+    ],
+)
+def test_string_match(data, pattern, expected):
+    ser = Series(data)
+    assert list(ser.str.fullmatch(pattern)) == expected
+@pytest.mark.parametrize("dtype", ["string[pyarrow]", str])
+@pytest.mark.parametrize(
+    "pattern, expected",
+    [
+        (r'(foo)|((as)(df)?)', [True, True, True]),
+        ('foo|as', [False, True, True]),
+    ],
+)
+def test_string_alternation_patterns(dtype, pattern, expected):
+    ser = Series(['asdf', 'foo', 'as'], dtype=dtype)
+    assert list(ser.str.fullmatch(pattern)) == expected