TEST: account for changed exception raised by PipelineDF in sklearn>=1.1

test/test/sklearndf/pipeline/test_pipeline_df.py

@@ -13,6 +13,7 @@
 import numpy as np
 import numpy.typing as npt
 import pandas as pd
+import pytest
 from numpy.testing import (
     assert_array_equal,
     assert_no_warnings,
@@ -23,6 +24,7 @@
 from sklearn.base import BaseEstimator, TransformerMixin, is_classifier, is_regressor
 from sklearn.feature_selection import f_classif
 
+from sklearndf import __sklearn_1_1__, __sklearn_version__
 from sklearndf.classification import SVCDF, LogisticRegressionDF
 from sklearndf.pipeline import PipelineDF
 from sklearndf.regression import DummyRegressorDF, LassoDF, LinearRegressionDF
@@ -220,14 +222,25 @@ def test_pipeline_df__init() -> None:
     assert_raises(TypeError, PipelineDF)
     # Check that we can't instantiate pipelines with objects without fit
     # method
-    assert_raises_regex(
-        TypeError,
-        "Last step of Pipeline should implement fit "
-        "or be the string 'passthrough'"
-        ".*NoFit.*",
-        PipelineDF,
-        [("clf", NoFit())],
-    )
+    if __sklearn_version__ < __sklearn_1_1__:
+        with pytest.raises(
+            TypeError,
+            match=(
+                "Last step of Pipeline should implement fit "
+                "or be the string 'passthrough'"
+                ".*NoFit.*"
+            ),
+        ):
+            PipelineDF([("clf", NoFit())])
+    else:
+        with pytest.raises(
+            ValueError,
+            match=(
+                'expected final step "clf" to contain a EstimatorDF, '
+                "but found an instance of NoFit"
+            ),
+        ):
+            PipelineDF([("clf", NoFit())])
 
     # Smoke test with only an estimator
     clf = NoTransformerDF()