BUG (string dtype): fix inplace mutation with copy=False in ensure_string_array (pandas-dev#59756)

* BUG (string dtype): fix inplace mutation with copy=False in ensure_string_array

* update

Author: jorisvandenbossche

pandas/_libs/lib.pyx

@@ -736,7 +736,9 @@ cpdef ndarray[object] ensure_string_array(
     convert_na_value : bool, default True
         If False, existing na values will be used unchanged in the new array.
     copy : bool, default True
-        Whether to ensure that a new array is returned.
+        Whether to ensure that a new array is returned. When True, a new array
+        is always returned. When False, a new array is only returned when needed
+        to avoid mutating the input array.
     skipna : bool, default True
         Whether or not to coerce nulls to their stringified form
         (e.g. if False, NaN becomes 'nan').
@@ -765,10 +767,17 @@ cpdef ndarray[object] ensure_string_array(
 
     result = np.asarray(arr, dtype="object")
 
-    if copy and (result is arr or np.shares_memory(arr, result)):
-        # GH#54654
-        result = result.copy()
-    elif not copy and result is arr:
+    if result is arr or np.may_share_memory(arr, result):
+        # if np.asarray(..) did not make a copy of the input arr, we still need
+        #  to do that to avoid mutating the input array
+        # GH#54654: share_memory check is needed for rare cases where np.asarray
+        #  returns a new object without making a copy of the actual data
+        if copy:
+            result = result.copy()
+        else:
+            already_copied = False
+    elif not copy and not result.flags.writeable:
+        # Weird edge case where result is a view
         already_copied = False
 
     if issubclass(arr.dtype.type, np.str_):

pandas/tests/copy_view/test_astype.py

@@ -135,7 +135,8 @@ def test_astype_string_and_object_update_original(
     tm.assert_frame_equal(df2, df_orig)
 
 
-def test_astype_string_copy_on_pickle_roundrip():
+def test_astype_str_copy_on_pickle_roundrip():
+    # TODO(infer_string) this test can be removed after 3.0 (once str is the default)
     # https://github.com/pandas-dev/pandas/issues/54654
     # ensure_string_array may alter array inplace
     base = Series(np.array([(1, 2), None, 1], dtype="object"))
@@ -144,6 +145,25 @@ def test_astype_string_copy_on_pickle_roundrip():
     tm.assert_series_equal(base, base_copy)
 
 
+def test_astype_string_copy_on_pickle_roundrip(any_string_dtype):
+    # https://github.com/pandas-dev/pandas/issues/54654
+    # ensure_string_array may alter array inplace
+    base = Series(np.array([(1, 2), None, 1], dtype="object"))
+    base_copy = pickle.loads(pickle.dumps(base))
+    base_copy.astype(any_string_dtype)
+    tm.assert_series_equal(base, base_copy)
+
+
+def test_astype_string_read_only_on_pickle_roundrip(any_string_dtype):
+    # https://github.com/pandas-dev/pandas/issues/54654
+    # ensure_string_array may alter read-only array inplace
+    base = Series(np.array([(1, 2), None, 1], dtype="object"))
+    base_copy = pickle.loads(pickle.dumps(base))
+    base_copy._values.flags.writeable = False
+    base_copy.astype(any_string_dtype)
+    tm.assert_series_equal(base, base_copy)
+
+
 def test_astype_dict_dtypes(using_copy_on_write):
     df = DataFrame(
         {"a": [1, 2, 3], "b": [4, 5, 6], "c": Series([1.5, 1.5, 1.5], dtype="float64")}

pandas/tests/libs/test_lib.py

@@ -1,3 +1,5 @@
+import pickle
+
 import numpy as np
 import pytest
 
@@ -283,3 +285,15 @@ def test_no_default_pickle():
     # GH#40397
     obj = tm.round_trip_pickle(lib.no_default)
     assert obj is lib.no_default
+
+
+def test_ensure_string_array_copy():
+    # ensure the original array is not modified in case of copy=False with
+    # pickle-roundtripped object dtype array
+    # https://github.com/pandas-dev/pandas/issues/54654
+    arr = np.array(["a", None], dtype=object)
+    arr = pickle.loads(pickle.dumps(arr))
+    result = lib.ensure_string_array(arr, copy=False)
+    assert not np.shares_memory(arr, result)
+    assert arr[1] is None
+    assert result[1] is np.nan