Backport PR pandas-dev#35697: REGR: Don't ignore compiled patterns in replace (pandas-dev#35765)

Co-authored-by: Daniel Saxton <[email protected]>

Author: meeseeksmachine

doc/source/whatsnew/v1.1.1.rst

@@ -26,6 +26,7 @@ Fixed regressions
 - Fixed regression in :meth:`DataFrame.reset_index` would raise a ``ValueError`` on empty :class:`DataFrame` with a :class:`MultiIndex` with a ``datetime64`` dtype level (:issue:`35606`, :issue:`35657`)
 - Fixed regression where :meth:`DataFrame.merge_asof` would raise a ``UnboundLocalError`` when ``left_index`` , ``right_index`` and ``tolerance`` were set (:issue:`35558`)
 - Fixed regression in ``.groupby(..).rolling(..)`` where a custom ``BaseIndexer`` would be ignored (:issue:`35557`)
+- Fixed regression in :meth:`DataFrame.replace` and :meth:`Series.replace` where compiled regular expressions would be ignored during replacement (:issue:`35680`)
 - Fixed regression in :meth:`~pandas.core.groupby.DataFrameGroupBy.agg` where a list of functions would produce the wrong results if at least one of the functions did not aggregate. (:issue:`35490`)
 
 .. ---------------------------------------------------------------------------

pandas/core/internals/managers.py

@@ -2,7 +2,17 @@
 import itertools
 import operator
 import re
-from typing import DefaultDict, Dict, List, Optional, Sequence, Tuple, TypeVar, Union
+from typing import (
+    DefaultDict,
+    Dict,
+    List,
+    Optional,
+    Pattern,
+    Sequence,
+    Tuple,
+    TypeVar,
+    Union,
+)
 import warnings
 
 import numpy as np
@@ -1922,7 +1932,10 @@ def _merge_blocks(
 
 
 def _compare_or_regex_search(
-    a: ArrayLike, b: Scalar, regex: bool = False, mask: Optional[ArrayLike] = None
+    a: ArrayLike,
+    b: Union[Scalar, Pattern],
+    regex: bool = False,
+    mask: Optional[ArrayLike] = None,
 ) -> Union[ArrayLike, bool]:
     """
     Compare two array_like inputs of the same shape or two scalar values
@@ -1933,7 +1946,7 @@ def _compare_or_regex_search(
     Parameters
     ----------
     a : array_like
-    b : scalar
+    b : scalar or regex pattern
     regex : bool, default False
     mask : array_like or None (default)
 
@@ -1943,7 +1956,7 @@ def _compare_or_regex_search(
     """
 
     def _check_comparison_types(
-        result: Union[ArrayLike, bool], a: ArrayLike, b: Scalar,
+        result: Union[ArrayLike, bool], a: ArrayLike, b: Union[Scalar, Pattern],
     ):
         """
         Raises an error if the two arrays (a,b) cannot be compared.
@@ -1964,7 +1977,7 @@ def _check_comparison_types(
     else:
         op = np.vectorize(
             lambda x: bool(re.search(b, x))
-            if isinstance(x, str) and isinstance(b, str)
+            if isinstance(x, str) and isinstance(b, (str, Pattern))
             else False
         )
 

pandas/tests/frame/methods/test_replace.py

@@ -1573,3 +1573,11 @@ def test_replace_dict_category_type(self, input_category_df, expected_category_d
         result = input_df.replace({"a": "z", "obj1": "obj9", "cat1": "catX"})
 
         tm.assert_frame_equal(result, expected)
+
+    def test_replace_with_compiled_regex(self):
+        # https://github.com/pandas-dev/pandas/issues/35680
+        df = pd.DataFrame(["a", "b", "c"])
+        regex = re.compile("^a$")
+        result = df.replace({regex: "z"}, regex=True)
+        expected = pd.DataFrame(["z", "b", "c"])
+        tm.assert_frame_equal(result, expected)

pandas/tests/series/methods/test_replace.py

@@ -1,3 +1,5 @@
+import re
+
 import numpy as np
 import pytest
 
@@ -415,3 +417,11 @@ def test_replace_extension_other(self):
         # https://github.com/pandas-dev/pandas/issues/34530
         ser = pd.Series(pd.array([1, 2, 3], dtype="Int64"))
         ser.replace("", "")  # no exception
+
+    def test_replace_with_compiled_regex(self):
+        # https://github.com/pandas-dev/pandas/issues/35680
+        s = pd.Series(["a", "b", "c"])
+        regex = re.compile("^a$")
+        result = s.replace({regex: "z"}, regex=True)
+        expected = pd.Series(["z", "b", "c"])
+        tm.assert_series_equal(result, expected)