scikit-learn · ogrisel · Feb 6, 2024 · Feb 2, 2024 · Feb 2, 2024 · Feb 2, 2024
diff --git a/sklearn/neighbors/_binary_tree.pxi.tp b/sklearn/neighbors/_binary_tree.pxi.tp
@@ -1482,7 +1482,7 @@ cdef class BinaryTree{{name_suffix}}:
             raise ValueError("query data dimension must "
                              "match training data dimension")
         Xarr_np = X.reshape((-1, n_features))
-        cdef {{INPUT_DTYPE_t}}[:, ::1] Xarr = Xarr_np
+        cdef const {{INPUT_DTYPE_t}}[:, ::1] Xarr = Xarr_np
 
         log_density_arr = np.zeros(Xarr.shape[0], dtype={{INPUT_DTYPE}})
         cdef {{INPUT_DTYPE_t}}[::1] log_density = log_density_arr

diff --git a/sklearn/utils/tests/test_utils.py b/sklearn/utils/tests/test_utils.py
@@ -3,11 +3,13 @@
 import warnings
 from copy import copy
 from itertools import chain
+from unittest import SkipTest
 
 import numpy as np
 import pytest
 
 from sklearn import config_context
+from sklearn.externals._packaging.version import parse as parse_version
 from sklearn.utils import (
     _approximate_mode,
     _determine_key_type,
@@ -461,6 +463,12 @@ def test_safe_indexing_pandas_no_settingwithcopy_warning():
     # DataFrame -> ensure it doesn't raise a warning if modified
     pd = pytest.importorskip("pandas")
 
+    pd_version = parse_version(pd.__version__)
+    pd_base_version = parse_version(pd_version.base_version)
+
+    if pd_base_version >= parse_version("3"):
+        raise SkipTest("SettingWithCopyWarning has been removed in pandas 3.0.0.dev")
+
     X = pd.DataFrame({"a": [1, 2, 3], "b": [3, 4, 5]})
     subset = _safe_indexing(X, [0, 1], axis=0)
     if hasattr(pd.errors, "SettingWithCopyWarning"):

diff --git a/sklearn/utils/validation.py b/sklearn/utils/validation.py
@@ -1084,6 +1084,18 @@ def is_sparse(dtype):
                 % (n_features, array.shape, ensure_min_features, context)
             )
 
+    # With an input pandas dataframe or series, we know we can always make the
+    # resulting array writeable:
+    # - if copy=True, we have already made a copy so it is fine to make the
+    #   array writeable
+    # - if copy=False, the caller is telling us explicitly that we can do
+    #   in-place modifications
+    # See https://pandas.pydata.org/docs/dev/user_guide/copy_on_write.html#read-only-numpy-arrays
+    # for more details about pandas copy-on-write mechanism, that is enabled by
+    # default in pandas 3.0.0.dev.
+    if _is_pandas_df_or_series(array_orig) and hasattr(array, "flags"):
+        array.flags.writeable = True
+
     return array
 
 
@@ -2140,6 +2152,15 @@ def _check_method_params(X, params, indices=None):
     return method_params_validated
 
 
+def _is_pandas_df_or_series(X):
+    """Return True if the X is a pandas dataframe or series."""
+    try:
+        pd = sys.modules["pandas"]
+    except KeyError:
+        return False
+    return isinstance(X, (pd.DataFrame, pd.Series))
+
+
 def _is_pandas_df(X):
     """Return True if the X is a pandas dataframe."""
     try: