From aafaa2e7df392234f53d18422b21b8a2f7e2c13f Mon Sep 17 00:00:00 2001
From: "Axel.Cffrd.Dnty" <150222552+AxelNoun@users.noreply.github.com>
Date: Sun, 19 Jul 2026 19:04:10 +0200
Subject: [PATCH 1/8] Guard CoW read-only .to_numpy()/.values mutations (#3362)

Under pandas 3.0 Copy-on-Write, .to_numpy()/.values return read-only
arrays for single-dtype selections; in-place mutation raises
ValueError. Use copy=True at the five affected sites. Pin unchanged.
---
 deeplabcut/pose_estimation_3d/plotting3D.py     | 17 ++++++++++++++---
 deeplabcut/pose_estimation_3d/triangulation.py  |  9 +++++++--
 deeplabcut/pose_estimation_pytorch/data/ctd.py  |  7 +++++--
 deeplabcut/post_processing/filtering.py         |  6 ++++--
 deeplabcut/refine_training_dataset/tracklets.py |  5 +++--
 5 files changed, 33 insertions(+), 11 deletions(-)

diff --git a/deeplabcut/pose_estimation_3d/plotting3D.py b/deeplabcut/pose_estimation_3d/plotting3D.py
index d39967a86..0b11f17be 100644
--- a/deeplabcut/pose_estimation_3d/plotting3D.py
+++ b/deeplabcut/pose_estimation_3d/plotting3D.py
@@ -215,15 +215,26 @@ def create_labeled_video_3d(
             bodyparts2plot = list(np.unique([val for sublist in bodyparts2connect for val in sublist]))
 
             # Format data
+            # copy=True: under pandas 3 CoW, to_numpy() may be read-only.
             mask2d = df_cam1.columns.get_level_values("bodyparts").isin(bodyparts2plot)
-            xy1 = df_cam1.iloc[: len(df_3d)].loc[:, mask2d].to_numpy().reshape((len(df_3d), -1, 3))
+            xy1 = (
+                df_cam1.iloc[: len(df_3d)]
+                .loc[:, mask2d]
+                .to_numpy(copy=True)
+                .reshape((len(df_3d), -1, 3))
+            )
             visible1 = xy1[..., 2] >= pcutoff
             xy1[~visible1] = np.nan
-            xy2 = df_cam2.iloc[: len(df_3d)].loc[:, mask2d].to_numpy().reshape((len(df_3d), -1, 3))
+            xy2 = (
+                df_cam2.iloc[: len(df_3d)]
+                .loc[:, mask2d]
+                .to_numpy(copy=True)
+                .reshape((len(df_3d), -1, 3))
+            )
             visible2 = xy2[..., 2] >= pcutoff
             xy2[~visible2] = np.nan
             mask = df_3d.columns.get_level_values("bodyparts").isin(bodyparts2plot)
-            xyz = df_3d.loc[:, mask].to_numpy().reshape((len(df_3d), -1, 3))
+            xyz = df_3d.loc[:, mask].to_numpy(copy=True).reshape((len(df_3d), -1, 3))
             xyz[~(visible1 & visible2)] = np.nan
 
             bpts = df_3d.columns.get_level_values("bodyparts")[mask][::3]
diff --git a/deeplabcut/pose_estimation_3d/triangulation.py b/deeplabcut/pose_estimation_3d/triangulation.py
index c213bfd31..b57d79a21 100644
--- a/deeplabcut/pose_estimation_3d/triangulation.py
+++ b/deeplabcut/pose_estimation_3d/triangulation.py
@@ -326,8 +326,13 @@ def triangulate(
             num_frames = dataFrame_camera1_undistort.shape[0]
             ### Assign nan to [X,Y] of low likelihood predictions ###
             # Convert the data to a np array to easily mask out the low likelihood predictions
-            data_cam1_tmp = dataFrame_camera1_undistort.to_numpy().reshape((num_frames, -1, 3))
-            data_cam2_tmp = dataFrame_camera2_undistort.to_numpy().reshape((num_frames, -1, 3))
+            # copy=True: under pandas 3 CoW, to_numpy() may be read-only.
+            data_cam1_tmp = dataFrame_camera1_undistort.to_numpy(copy=True).reshape(
+                (num_frames, -1, 3)
+            )
+            data_cam2_tmp = dataFrame_camera2_undistort.to_numpy(copy=True).reshape(
+                (num_frames, -1, 3)
+            )
             # Assign [X,Y] = nan to low likelihood predictions
             data_cam1_tmp[data_cam1_tmp[..., 2] < pcutoff, :2] = np.nan
             data_cam2_tmp[data_cam2_tmp[..., 2] < pcutoff, :2] = np.nan
diff --git a/deeplabcut/pose_estimation_pytorch/data/ctd.py b/deeplabcut/pose_estimation_pytorch/data/ctd.py
index b192f5126..8f6dfb39c 100644
--- a/deeplabcut/pose_estimation_pytorch/data/ctd.py
+++ b/deeplabcut/pose_estimation_pytorch/data/ctd.py
@@ -238,8 +238,11 @@ def load_conditions_h5(
         """
 
         def _parse_row(df_row) -> np.ndarray:
-            # Row to numpy and reshape
-            pose = df_row.to_numpy().reshape((num_conditions, num_bodyparts, 3))
+            # Row to numpy and reshape. copy=True: under pandas 3 CoW,
+            # to_numpy() may return a read-only view.
+            pose = df_row.to_numpy(copy=True).reshape(
+                (num_conditions, num_bodyparts, 3)
+            )
 
             # Remove missing data
             missing_keypoints = np.any(np.isnan(pose) | (pose < 0), axis=2)
diff --git a/deeplabcut/post_processing/filtering.py b/deeplabcut/post_processing/filtering.py
index e37591772..323409204 100644
--- a/deeplabcut/post_processing/filtering.py
+++ b/deeplabcut/post_processing/filtering.py
@@ -245,8 +245,10 @@ def filterpredictions(
         elif filtertype == "spline":
             data = df.copy()
             mask_data = data.columns.get_level_values("coords").isin(("x", "y"))
-            xy = data.loc[:, mask_data].values
-            prob = data.loc[:, ~mask_data].values
+            # copy=True: under pandas 3 CoW, homogeneous float selections
+            # via .values/.to_numpy() are read-only views.
+            xy = data.loc[:, mask_data].to_numpy(copy=True)
+            prob = data.loc[:, ~mask_data].to_numpy(copy=True)
             missing = np.isnan(xy)
             xy_filled = columnwise_spline_interp(xy, windowlength)
             filled = ~np.isnan(xy_filled)
diff --git a/deeplabcut/refine_training_dataset/tracklets.py b/deeplabcut/refine_training_dataset/tracklets.py
index 4e07e02d0..50b49a976 100644
--- a/deeplabcut/refine_training_dataset/tracklets.py
+++ b/deeplabcut/refine_training_dataset/tracklets.py
@@ -221,8 +221,9 @@ def load_tracklets_from_hdf(self, filename):
         self.filename = filename
         df = pd.read_hdf(filename)
 
-        # Fill existing gaps
-        data = df.to_numpy()
+        # Fill existing gaps. copy=True: under pandas 3 CoW, to_numpy() may
+        # return a read-only view that cannot be mutated in place.
+        data = df.to_numpy(copy=True)
         mask = ~df.columns.get_level_values(level="coords").str.contains("likelihood")
         xy = data[:, mask]
         prob = data[:, ~mask]

From 85291460806541469fdfcf4ce9dd3694e58ac417 Mon Sep 17 00:00:00 2001
From: Jaap de Ruyter van Steveninck
 <32810691+deruyter92@users.noreply.github.com>
Date: Wed, 22 Jul 2026 13:05:17 +0200
Subject: [PATCH 2/8] linting

---
 deeplabcut/pose_estimation_3d/plotting3D.py    | 14 ++------------
 deeplabcut/pose_estimation_3d/triangulation.py |  8 ++------
 deeplabcut/pose_estimation_pytorch/data/ctd.py |  4 +---
 3 files changed, 5 insertions(+), 21 deletions(-)

diff --git a/deeplabcut/pose_estimation_3d/plotting3D.py b/deeplabcut/pose_estimation_3d/plotting3D.py
index 0b11f17be..593e71203 100644
--- a/deeplabcut/pose_estimation_3d/plotting3D.py
+++ b/deeplabcut/pose_estimation_3d/plotting3D.py
@@ -217,20 +217,10 @@ def create_labeled_video_3d(
             # Format data
             # copy=True: under pandas 3 CoW, to_numpy() may be read-only.
             mask2d = df_cam1.columns.get_level_values("bodyparts").isin(bodyparts2plot)
-            xy1 = (
-                df_cam1.iloc[: len(df_3d)]
-                .loc[:, mask2d]
-                .to_numpy(copy=True)
-                .reshape((len(df_3d), -1, 3))
-            )
+            xy1 = df_cam1.iloc[: len(df_3d)].loc[:, mask2d].to_numpy(copy=True).reshape((len(df_3d), -1, 3))
             visible1 = xy1[..., 2] >= pcutoff
             xy1[~visible1] = np.nan
-            xy2 = (
-                df_cam2.iloc[: len(df_3d)]
-                .loc[:, mask2d]
-                .to_numpy(copy=True)
-                .reshape((len(df_3d), -1, 3))
-            )
+            xy2 = df_cam2.iloc[: len(df_3d)].loc[:, mask2d].to_numpy(copy=True).reshape((len(df_3d), -1, 3))
             visible2 = xy2[..., 2] >= pcutoff
             xy2[~visible2] = np.nan
             mask = df_3d.columns.get_level_values("bodyparts").isin(bodyparts2plot)
diff --git a/deeplabcut/pose_estimation_3d/triangulation.py b/deeplabcut/pose_estimation_3d/triangulation.py
index b57d79a21..3b945166c 100644
--- a/deeplabcut/pose_estimation_3d/triangulation.py
+++ b/deeplabcut/pose_estimation_3d/triangulation.py
@@ -327,12 +327,8 @@ def triangulate(
             ### Assign nan to [X,Y] of low likelihood predictions ###
             # Convert the data to a np array to easily mask out the low likelihood predictions
             # copy=True: under pandas 3 CoW, to_numpy() may be read-only.
-            data_cam1_tmp = dataFrame_camera1_undistort.to_numpy(copy=True).reshape(
-                (num_frames, -1, 3)
-            )
-            data_cam2_tmp = dataFrame_camera2_undistort.to_numpy(copy=True).reshape(
-                (num_frames, -1, 3)
-            )
+            data_cam1_tmp = dataFrame_camera1_undistort.to_numpy(copy=True).reshape((num_frames, -1, 3))
+            data_cam2_tmp = dataFrame_camera2_undistort.to_numpy(copy=True).reshape((num_frames, -1, 3))
             # Assign [X,Y] = nan to low likelihood predictions
             data_cam1_tmp[data_cam1_tmp[..., 2] < pcutoff, :2] = np.nan
             data_cam2_tmp[data_cam2_tmp[..., 2] < pcutoff, :2] = np.nan
diff --git a/deeplabcut/pose_estimation_pytorch/data/ctd.py b/deeplabcut/pose_estimation_pytorch/data/ctd.py
index 8f6dfb39c..d11abcab3 100644
--- a/deeplabcut/pose_estimation_pytorch/data/ctd.py
+++ b/deeplabcut/pose_estimation_pytorch/data/ctd.py
@@ -240,9 +240,7 @@ def load_conditions_h5(
         def _parse_row(df_row) -> np.ndarray:
             # Row to numpy and reshape. copy=True: under pandas 3 CoW,
             # to_numpy() may return a read-only view.
-            pose = df_row.to_numpy(copy=True).reshape(
-                (num_conditions, num_bodyparts, 3)
-            )
+            pose = df_row.to_numpy(copy=True).reshape((num_conditions, num_bodyparts, 3))
 
             # Remove missing data
             missing_keypoints = np.any(np.isnan(pose) | (pose < 0), axis=2)

From 18bc897c7ba688f949d8049361172c26d46ba7ba Mon Sep 17 00:00:00 2001
From: "Axel.Cffrd.Dnty" <150222552+AxelNoun@users.noreply.github.com>
Date: Sat, 25 Jul 2026 20:08:07 +0200
Subject: [PATCH 3/8] Guard remaining CoW read-only .to_numpy()/.values
 mutations

Follow-up to the pandas 3.0 CoW sweep (#3362). Three more sites extract a
NumPy array from a pandas object and mutate it in place; under pandas 3 CoW
these can be read-only views, raising "assignment destination is read-only".

- refine_training_dataset/tracklets.py: self.data backs self.xy/self.prob,
  which swap_tracklets and the refine GUI mutate in place (HDF load path;
  flagged in review).
- utils/make_labeled_video.py: coords is a view into xyp, masked in place in
  both the first-frame and per-frame branches.
- pose_estimation_tensorflow/.../pose_multianimal_imgaug.py: a single-row
  float Series is read-only; kpts is masked in place when
  mask_kpts_below_thresh is set.

Co-authored-by: Cursor <cursoragent@cursor.com>
---
 .../datasets/pose_multianimal_imgaug.py                     | 4 +++-
 deeplabcut/refine_training_dataset/tracklets.py             | 6 +++++-
 deeplabcut/utils/make_labeled_video.py                      | 4 +++-
 3 files changed, 11 insertions(+), 3 deletions(-)

diff --git a/deeplabcut/pose_estimation_tensorflow/datasets/pose_multianimal_imgaug.py b/deeplabcut/pose_estimation_tensorflow/datasets/pose_multianimal_imgaug.py
index 525ca297e..a2645754f 100644
--- a/deeplabcut/pose_estimation_tensorflow/datasets/pose_multianimal_imgaug.py
+++ b/deeplabcut/pose_estimation_tensorflow/datasets/pose_multianimal_imgaug.py
@@ -135,7 +135,9 @@ def _load_pseudo_data_from_h5(self, cfg, threshold=0.5, mask_kpts_below_thresh=F
             item = DataItem()
             data = df.loc[imagename]
             # 3 for likelihood
-            kpts = data.to_numpy().reshape(-1, 3)
+            # copy=True: `kpts` is masked in place below (mask_kpts_below_thresh);
+            # under pandas 3 CoW a single-row float Series returns a read-only view.
+            kpts = data.to_numpy(copy=True).reshape(-1, 3)
             item.num_joints = kpts.shape[0]
             joint_ids = np.arange(item.num_joints)[..., np.newaxis]
             frame_name = "frame_" + str(int(imagename.split("frame")[1])) + ".png"
diff --git a/deeplabcut/refine_training_dataset/tracklets.py b/deeplabcut/refine_training_dataset/tracklets.py
index 50b49a976..929726855 100644
--- a/deeplabcut/refine_training_dataset/tracklets.py
+++ b/deeplabcut/refine_training_dataset/tracklets.py
@@ -246,7 +246,11 @@ def load_tracklets_from_hdf(self, filename):
         self.bodyparts = idx.get_level_values("bodyparts")
         self.nframes = len(df)
         self.times = np.arange(self.nframes)
-        self.data = df.values.reshape((self.nframes, -1, 3)).swapaxes(0, 1)
+        # copy=True: `self.xy`/`self.prob` are views into `self.data` and are
+        # mutated in place (e.g. by `swap_tracklets`), so the backing array must
+        # stay writable. Under pandas 3 CoW, `.values` on a homogeneous float
+        # DataFrame returns a read-only view.
+        self.data = df.to_numpy(copy=True).reshape((self.nframes, -1, 3)).swapaxes(0, 1)
         self.xy = self.data[:, :, :2]
         self.prob = self.data[:, :, 2]
         individuals = idx.get_level_values("individuals")
diff --git a/deeplabcut/utils/make_labeled_video.py b/deeplabcut/utils/make_labeled_video.py
index b8bde8447..8f0d9cf79 100644
--- a/deeplabcut/utils/make_labeled_video.py
+++ b/deeplabcut/utils/make_labeled_video.py
@@ -1017,7 +1017,9 @@ def create_video_with_keypoints_only(
     ny = int(np.nanmax(df.xs("y", axis=1, level="coords")))
 
     n_frames = df.shape[0]
-    xyp = df.values.reshape((n_frames, -1, 3))
+    # copy=True: `coords` is a view into `xyp` and is masked in place below;
+    # under pandas 3 CoW `.values` would return a read-only view.
+    xyp = df.to_numpy(copy=True).reshape((n_frames, -1, 3))
 
     if color_by == "bodypart":
         map_ = bodyparts.map(dict(zip(bodypart_names, range(n_bodyparts), strict=False)))

From b9534165fab1f59d01cedc46bed1fba0c8ec0560 Mon Sep 17 00:00:00 2001
From: Jaap de Ruyter van Steveninck
 <32810691+deruyter92@users.noreply.github.com>
Date: Mon, 27 Jul 2026 15:55:15 +0200
Subject: [PATCH 4/8] fix pandas future mode tool: enable instead of "warn"

---
 deeplabcut/utils/pandas_future_mode.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/deeplabcut/utils/pandas_future_mode.py b/deeplabcut/utils/pandas_future_mode.py
index cfb9d952e..fb8adf40a 100644
--- a/deeplabcut/utils/pandas_future_mode.py
+++ b/deeplabcut/utils/pandas_future_mode.py
@@ -23,7 +23,7 @@ def configure_pandas_future_if_enabled() -> None:
         raise RuntimeError(f"pandas future mode requires pandas 2.3.x, got {pd.__version__}")
 
     pd.options.future.infer_string = True
-    pd.options.mode.copy_on_write = "warn"
+    pd.options.mode.copy_on_write = True
 
     print(
         f"pandas future mode enabled: pandas={pd.__version__}, "

From 7101f3c8568fb5ee633e95e38bd55b1432784378 Mon Sep 17 00:00:00 2001
From: Jaap de Ruyter van Steveninck
 <32810691+deruyter92@users.noreply.github.com>
Date: Mon, 27 Jul 2026 15:56:48 +0200
Subject: [PATCH 5/8] add tests for pd future mode tool

---
 tests/utils/test_pandas_cow.py | 106 +++++++++++++++++++++++++++++++++
 1 file changed, 106 insertions(+)
 create mode 100644 tests/utils/test_pandas_cow.py

diff --git a/tests/utils/test_pandas_cow.py b/tests/utils/test_pandas_cow.py
new file mode 100644
index 000000000..343199f50
--- /dev/null
+++ b/tests/utils/test_pandas_cow.py
@@ -0,0 +1,106 @@
+#
+# DeepLabCut Toolbox (deeplabcut.org)
+# (c) A. & M.W. Mathis Labs
+# https://github.com/DeepLabCut/DeepLabCut
+#
+# Please see AUTHORS for contributors.
+# https://github.com/DeepLabCut/DeepLabCut/blob/master/AUTHORS
+#
+# Licensed under GNU Lesser General Public License v3.0
+#
+
+"""Verify that ``configure_pandas_future_if_enabled`` (copy_on_write=True)
+surfaces mutation patterns that should be guarded by ``copy=True``.
+"""
+
+import numpy as np
+import pandas as pd
+import pytest
+
+from deeplabcut.utils.pandas_future_mode import (
+    configure_pandas_future_if_enabled,
+)
+
+# ---------------------------------------------------------------------------
+# Helpers
+# ---------------------------------------------------------------------------
+
+
+def _configure_cow_true(monkeypatch) -> None:
+    """Configure pandas CoW via the DLC future-mode machinery."""
+    monkeypatch.setenv("DLC_PANDAS_FUTURE", "1")
+    configure_pandas_future_if_enabled()
+
+
+def _make_dlc_df(n_frames: int = 5) -> pd.DataFrame:
+    """Build a small DLC-style MultiIndex DataFrame (scorer x bodypart x coord)."""
+    bodyparts = ["snout", "leftear", "rightear"]
+    coords = ["x", "y", "likelihood"]
+    arrays = {}
+    for bp in bodyparts:
+        for c in coords:
+            arrays[("scorer1", bp, c)] = np.random.randn(n_frames)
+    df = pd.DataFrame(arrays)
+    df.columns = pd.MultiIndex.from_tuples(
+        df.columns,
+        names=["scorer", "bodyparts", "coords"],
+    )
+    return df
+
+
+# ---------------------------------------------------------------------------
+# Sanity: the machinery actually engages.
+# ---------------------------------------------------------------------------
+
+
+def test_future_mode_sets_cow_true(monkeypatch):
+    """``configure_pandas_future_if_enabled()`` sets copy_on_write=True."""
+    _configure_cow_true(monkeypatch)
+    assert pd.options.mode.copy_on_write is True, f"Expected copy_on_write=True, got {pd.options.mode.copy_on_write!r}"
+    assert pd.options.future.infer_string is True
+
+
+# ---------------------------------------------------------------------------
+# The PR's patterns: extracting a numpy array, then mutating it in place.
+# Without copy=True each would blow up at runtime under pandas 3.
+# ---------------------------------------------------------------------------
+
+
+@pytest.mark.parametrize(
+    "label, extract",
+    [
+        pytest.param(
+            lambda df: df.to_numpy().reshape((len(df), -1, 3)),
+            id="to_numpy_reshape",
+        ),
+        pytest.param(
+            lambda df: df.values.reshape((len(df), -1, 3)),
+            id="values_reshape",
+        ),
+        pytest.param(
+            lambda df: df.loc[:, df.columns.get_level_values("coords").isin(("x", "y"))].to_numpy(),
+            id="column_subset",
+        ),
+        pytest.param(
+            lambda df: df.loc[df.index[0]].to_numpy().reshape(-1, 3),
+            id="single_row",
+        ),
+    ],
+)
+def test_future_mode_makes_numpy_arrays_read_only(extract, monkeypatch):
+    """``configure_pandas_future_if_enabled()`` with copy_on_write=True
+    returns read-only numpy arrays that cannot be mutated in place.
+
+    These are the patterns that this PR guards with ``copy=True``.
+    Without the guard, each would raise ``ValueError`` (read-only array)
+    under pandas 3.
+    """
+    _configure_cow_true(monkeypatch)
+    df = _make_dlc_df()
+
+    arr = extract(df)
+
+    assert not arr.flags.writeable, "array unexpectedly writeable — CoW may not be active"
+
+    with pytest.raises(ValueError, match="read-only"):
+        arr.flat[0] = 999.0

From 22ffb1b9306357dd8423cc9dc9f723edd5d44eff Mon Sep 17 00:00:00 2001
From: Jaap de Ruyter van Steveninck
 <32810691+deruyter92@users.noreply.github.com>
Date: Tue, 28 Jul 2026 09:36:17 +0200
Subject: [PATCH 6/8] fix test parametrization in test_pandas_cow

---
 tests/utils/test_pandas_cow.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/tests/utils/test_pandas_cow.py b/tests/utils/test_pandas_cow.py
index 343199f50..029bcfd11 100644
--- a/tests/utils/test_pandas_cow.py
+++ b/tests/utils/test_pandas_cow.py
@@ -67,7 +67,7 @@ def test_future_mode_sets_cow_true(monkeypatch):
 
 
 @pytest.mark.parametrize(
-    "label, extract",
+    "extract",
     [
         pytest.param(
             lambda df: df.to_numpy().reshape((len(df), -1, 3)),

From 7c997771a5326588363563306be2d9a9cdea5ed0 Mon Sep 17 00:00:00 2001
From: Jaap de Ruyter van Steveninck
 <32810691+deruyter92@users.noreply.github.com>
Date: Tue, 28 Jul 2026 09:43:29 +0200
Subject: [PATCH 7/8] Add copy=True to to_numpy in evaluate_multianimal
 peaks_gt

Guards against the in-place write on the next line producing a
read-only view when the intermediate frame becomes single-block.
---
 .../pose_estimation_tensorflow/core/evaluate_multianimal.py     | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/deeplabcut/pose_estimation_tensorflow/core/evaluate_multianimal.py b/deeplabcut/pose_estimation_tensorflow/core/evaluate_multianimal.py
index 5cd893f7e..0dc290cc0 100644
--- a/deeplabcut/pose_estimation_tensorflow/core/evaluate_multianimal.py
+++ b/deeplabcut/pose_estimation_tensorflow/core/evaluate_multianimal.py
@@ -328,7 +328,7 @@ def evaluate_multianimal_full(
                             )
 
                         temp["sample"] = 0
-                        peaks_gt = temp.loc[:, ["sample", "y", "x", "bodyparts"]].to_numpy()
+                        peaks_gt = temp.loc[:, ["sample", "y", "x", "bodyparts"]].to_numpy(copy=True)
                         peaks_gt[:, 1:3] = (peaks_gt[:, 1:3] - stride // 2) / stride
 
                         pred = predictma.predict_batched_peaks_and_costs(

From a3977ff926cc941d68be5176a07210e731ff849f Mon Sep 17 00:00:00 2001
From: Jaap de Ruyter van Steveninck
 <32810691+deruyter92@users.noreply.github.com>
Date: Tue, 28 Jul 2026 16:45:48 +0200
Subject: [PATCH 8/8] fix test_pandas_cow leaking global `infer_string` and
 `copy_on_write` options

---
 tests/utils/test_pandas_cow.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/tests/utils/test_pandas_cow.py b/tests/utils/test_pandas_cow.py
index 029bcfd11..84a5fee4d 100644
--- a/tests/utils/test_pandas_cow.py
+++ b/tests/utils/test_pandas_cow.py
@@ -28,6 +28,8 @@
 
 def _configure_cow_true(monkeypatch) -> None:
     """Configure pandas CoW via the DLC future-mode machinery."""
+    monkeypatch.setattr(pd.options.future, "infer_string", pd.options.future.infer_string)
+    monkeypatch.setattr(pd.options.mode, "copy_on_write", pd.options.mode.copy_on_write)
     monkeypatch.setenv("DLC_PANDAS_FUTURE", "1")
     configure_pandas_future_if_enabled()