Mnt

.github/workflows/build-test.yml

@@ -22,7 +22,8 @@ jobs:
           ci-sklearn14,
           ci-sklearn15,
           ci-sklearn16,
-          ci-sklearn17
+          ci-sklearn17,
+          ci-sklearn-nightly
         ]
 
     # Timeout: https://stackoverflow.com/a/59076067/4521646

pyproject.toml

@@ -194,17 +194,23 @@ python = "~=3.12.0"
 quantile-forest = "~=1.3.11"
 
 [tool.pixi.feature.sklearn16.dependencies]
-scikit-learn = "*"
+scikit-learn = "~=1.6.0"
 fairlearn = "~=0.11.0"
 pandas = "~=2.2.0"
 numpy = "~=2.1.0"
 scipy = "~=1.14.0"
-# add when catboost supports 3.13
-# https://github.com/catboost/catboost/issues/2748
-# catboost = ">=1.0"
-# add quantile-forest when it's released
-# https://github.com/zillow/quantile-forest/issues/103
-# quantile-forest = "~=1.4.0"
+catboost = ">=1.0"
+quantile-forest = "~=1.4.0"
+python = "~=3.13.0"
+
+[tool.pixi.feature.sklearn17.dependencies]
+scikit-learn = "~=1.7.0"
+fairlearn = "~=0.12.0"
+pandas = "~=2.3.0"
+numpy = "~=2.3.0"
+scipy = "~=1.16.0"
+catboost = ">=1.0"
+quantile-forest = "~=1.4.0"
 python = "~=3.13.0"
 
 
@@ -216,13 +222,13 @@ python = "~=3.13.0"
 # ]
 
 
-[tool.pixi.feature.sklearn17.pypi-options]
+[tool.pixi.feature.sklearn-nightly.pypi-options]
 # This is for the nightly channel to test the dev version of scikit-learn.
 extra-index-urls = ["https://pypi.anaconda.org/scientific-python-nightly-wheels/simple"]
 
-[tool.pixi.feature.sklearn17.pypi-dependencies]
+[tool.pixi.feature.sklearn-nightly.pypi-dependencies]
 # The version value here needs to be exact, hence == instead of ~=
-scikit-learn = "==1.7.dev0"
+scikit-learn = "==1.8.dev0"
 fairlearn = "*"
 pandas = "*"
 numpy = "*"
@@ -235,7 +241,7 @@ lint = { cmd = "pre-commit install && pre-commit run -v --all-files --show-diff-
 tests = { cmd = "pytest -vsl --cov=skops --cov-report=xml --cov-report=term-missing -m \"not inference\" skops" }
 
 [tool.pixi.environments]
-default = ["docs", "tests", "lint", "rich", "dev", "sklearn17"]
+default = ["docs", "tests", "lint", "rich", "dev", "sklearn-nightly"]
 lint = ["lint"]
 docs = ["docs"]
 ci-sklearn12 = ["rich", "tests", "lint", "sklearn12"]
@@ -244,3 +250,4 @@ ci-sklearn14 = ["rich", "tests", "lint", "sklearn14"]
 ci-sklearn15 = ["rich", "tests", "lint", "sklearn15"]
 ci-sklearn16 = ["rich", "tests", "lint", "sklearn16"]
 ci-sklearn17 = ["rich", "tests", "lint", "sklearn17"]
+ci-sklearn-nightly = ["rich", "tests", "lint", "sklearn-nightly"]

skops/card/_model_card.py

@@ -333,7 +333,7 @@ class Card:
     >>> from sklearn.linear_model import LogisticRegression
     >>> from skops.card import Card
     >>> X, y = load_iris(return_X_y=True)
-    >>> model = LogisticRegression(solver="liblinear", random_state=0).fit(X, y)
+    >>> model = LogisticRegression(solver="saga", random_state=0).fit(X, y)
     >>> model_card = Card(model)
     >>> y_pred = model.predict(X)
     >>> model_card.add_metrics(**{
@@ -364,7 +364,7 @@ class Card:
     >>> # add new subsection to an existing section by using "/"
     >>> model_card.add(**{"Model description/Model name": "This model is called Bob"})
     Card(
-      model=LogisticRegression(random_state=0, solver='liblinear'),
+      model=LogisticRegression(random_state=0, solver='saga'),
       ...
     )
     >>> # save the card to a README.md file
@@ -1022,7 +1022,7 @@ def add_permutation_importances(
             ax,
             x=permutation_importances.importances[sorted_importances_idx].T,
             tick_labels=columns[sorted_importances_idx],
-            vert=False,
+            vert="horizontal",
         )
         ax.set_title(plot_name)
         ax.set_xlabel("Decrease in Score")

skops/card/tests/test_card.py

@@ -1068,7 +1068,7 @@ def expected_lines(self):
         Card(
           model=MyRegressor(param_1=10),
           Model description/Training Procedure/Hyperparameters=TableSection(3x2),
-          Model description/Training Procedure/Model Plot=<style>#sk-co...v></div></div>,
+          Model description/Training Procedure/Model Plot=__anything__,
           Model Card Authors=Jane Doe,
           Figures/ROC=PlotSection(ROC.png),
           Figures/Confusion matrix=PlotSection(confusion_matrix.jpg),
@@ -1077,14 +1077,16 @@ def expected_lines(self):
         )
         """  # noqa: E501
         expected = textwrap.dedent(card_repr).strip()
+        expected = re.escape(expected)
+        expected = expected.replace("__anything__", ".*")
         lines = expected.split("\n")
         return lines
 
     @pytest.mark.parametrize("meth", [repr, str])
     def test_card_repr(self, card: Card, meth, expected_lines):
         result = meth(card)
         expected = "\n".join(expected_lines)
-        assert reprs_equal(expected, result)
+        assert re.match(expected, result)
 
     @pytest.mark.parametrize("meth", [repr, str])
     def test_card_repr_empty_card(self, meth):
@@ -1112,7 +1114,7 @@ def test_very_long_lines_are_shortened(self, card: Card, meth, expected_lines):
         expected = "\n".join(expected_lines)
 
         result = meth(card)
-        assert reprs_equal(expected, result)
+        assert re.match(expected, result)
 
     @pytest.mark.parametrize("meth", [repr, str])
     def test_without_model_attribute(self, card: Card, meth, expected_lines):
@@ -1123,7 +1125,7 @@ def test_without_model_attribute(self, card: Card, meth, expected_lines):
         expected = "\n".join(expected_lines)
 
         result = meth(card)
-        assert reprs_equal(expected, result)
+        assert re.match(expected, result)
 
 
 class TestCardModelAttributeIsPath:

skops/io/tests/_utils.py

@@ -96,8 +96,8 @@ def _assert_vals_equal(val1, val2, path=""):
     elif isinstance(val1, (np.ndarray, np.generic)):
         if len(val1.dtype) == 0:
             # for arrays with at least 2 dimensions, check that contiguity is
-            # preserved
-            if val1.squeeze().ndim > 1:
+            # preserved, but only if the array is not a view
+            if val1.squeeze().ndim > 1 and val1.flags["OWNDATA"]:
                 assert (
                     val1.flags["C_CONTIGUOUS"] is val2.flags["C_CONTIGUOUS"]
                 ), f"Path: {path}.flags"

skops/io/tests/test_persist.py

@@ -897,7 +897,7 @@ def test_disk_and_memory_are_identical(tmp_path):
                 ("scale", MinMaxScaler()),
             ])),
         ])),
-        ("clf", LogisticRegression(random_state=0, solver="liblinear")),
+        ("clf", LogisticRegression(random_state=0, solver="saga")),
     ]).fit([[0, 1], [2, 3], [4, 5]], [0, 1, 2])
     # fmt: on
 

skops/io/tests/test_visualize.py

@@ -56,7 +56,7 @@ def unsafe_function(x):
                     ("scale", MinMaxScaler()),
                 ])),
             ])),
-            ("clf", LogisticRegression(random_state=0, solver="liblinear")),
+            ("clf", LogisticRegression(random_state=0, solver="saga")),
         ]).fit([[0, 1], [2, 3], [4, 5]], [0, 1, 2])
         # fmt: on
         return pipeline