Backport PR pandas-dev#62283: BUG: fix pyarrow string regex replacement

Author: Alvaro-Kothe

doc/source/whatsnew/v2.3.3.rst

@@ -22,6 +22,7 @@ become the default string dtype in pandas 3.0. See
 
 Bug fixes
 ^^^^^^^^^
+- Fix bug in :meth:`Series.str.replace` using named capture groups (e.g., ``\g<name>``) with the Arrow-backed dtype would raise an error (:issue:`57636`)
 - Fix regression in ``~Series.str.contains``, ``~Series.str.match`` and ``~Series.str.fullmatch``
   with a compiled regex and custom flags (:issue:`62240`)
 

pandas/core/arrays/_arrow_string_mixins.py

@@ -168,10 +168,20 @@ def _str_replace(
         flags: int = 0,
         regex: bool = True,
     ) -> Self:
-        if isinstance(pat, re.Pattern) or callable(repl) or not case or flags:
+        if (
+            isinstance(pat, re.Pattern)
+            or callable(repl)
+            or not case
+            or flags
+            or (
+                isinstance(repl, str)
+                and (r"\g<" in repl or re.search(r"\\\d", repl) is not None)
+            )
+        ):
             raise NotImplementedError(
                 "replace is not supported with a re.Pattern, callable repl, "
-                "case=False, or flags!=0"
+                "case=False, flags!=0, or when the replacement string contains "
+                "named group references (\\g<...>, \\d+)"
             )
 
         func = pc.replace_substring_regex if regex else pc.replace_substring

pandas/core/arrays/string_arrow.py

@@ -419,7 +419,17 @@ def _str_replace(
         flags: int = 0,
         regex: bool = True,
     ):
-        if isinstance(pat, re.Pattern) or callable(repl) or not case or flags:
+        if (
+            isinstance(pat, re.Pattern)
+            or callable(repl)
+            or not case
+            or flags
+            or (  # substitution contains a named group pattern
+                # https://docs.python.org/3/library/re.html
+                isinstance(repl, str)
+                and (r"\g<" in repl or re.search(r"\\\d", repl) is not None)
+            )
+        ):
             return super()._str_replace(pat, repl, n, case, flags, regex)
 
         return ArrowStringArrayMixin._str_replace(

pandas/tests/strings/test_find_replace.py

@@ -594,6 +594,68 @@ def test_replace_callable_raises(any_string_dtype, repl):
         values.str.replace("a", repl, regex=True)
 
 
+@pytest.mark.parametrize(
+    "repl, expected_list",
+    [
+        (
+            r"\g<three> \g<two> \g<one>",
+            ["Three Two One", "Baz Bar Foo"],
+        ),
+        (
+            r"\g<3> \g<2> \g<1>",
+            ["Three Two One", "Baz Bar Foo"],
+        ),
+        (
+            r"\g<2>0",
+            ["Two0", "Bar0"],
+        ),
+        (
+            r"\g<2>0 \1",
+            ["Two0 One", "Bar0 Foo"],
+        ),
+    ],
+    ids=[
+        "named_groups_full_swap",
+        "numbered_groups_full_swap",
+        "single_group_with_literal",
+        "mixed_group_reference_with_literal",
+    ],
+)
+@pytest.mark.parametrize("use_compile", [True, False])
+def test_replace_named_groups_regex_swap(
+    any_string_dtype, use_compile, repl, expected_list
+):
+    # GH#57636
+    ser = Series(["One Two Three", "Foo Bar Baz"], dtype=any_string_dtype)
+    pattern = r"(?P<one>\w+) (?P<two>\w+) (?P<three>\w+)"
+    if use_compile:
+        pattern = re.compile(pattern)
+    result = ser.str.replace(pattern, repl, regex=True)
+    expected = Series(expected_list, dtype=any_string_dtype)
+    tm.assert_series_equal(result, expected)
+
+
+@pytest.mark.parametrize(
+    "repl",
+    [
+        r"\g<20>",
+        r"\20",
+    ],
+)
+@pytest.mark.parametrize("use_compile", [True, False])
+def test_replace_named_groups_regex_swap_expected_fail(
+    any_string_dtype, repl, use_compile
+):
+    # GH#57636
+    pattern = r"(?P<one>\w+) (?P<two>\w+) (?P<three>\w+)"
+    if use_compile:
+        pattern = re.compile(pattern)
+    ser = Series(["One Two Three", "Foo Bar Baz"], dtype=any_string_dtype)
+
+    with pytest.raises(re.error, match="invalid group reference"):
+        ser.str.replace(pattern, repl, regex=True)
+
+
 def test_replace_callable_named_groups(any_string_dtype):
     # test regex named groups
     ser = Series(["Foo Bar Baz", np.nan], dtype=any_string_dtype)