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Skip tests that use arff reading optimization for typecheck (#1185)
Those types changed in the switch to parquet, and we need to update the server parquet files and/or test expectations.
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tests/test_datasets/test_dataset.py

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@@ -143,6 +143,7 @@ def test_get_data_pandas(self):
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self.assertTrue(X[col_name].dtype.name == col_dtype[col_name])
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self.assertTrue(y.dtype.name == col_dtype["survived"])
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@pytest.mark.skip("https://github.com/openml/openml-python/issues/1157")
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def test_get_data_boolean_pandas(self):
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# test to check that we are converting properly True and False even
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# with some inconsistency when dumping the data on openml
@@ -170,6 +171,7 @@ def _check_expected_type(self, dtype, is_cat, col):
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self.assertEqual(dtype.name, expected_type)
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@pytest.mark.skip("https://github.com/openml/openml-python/issues/1157")
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def test_get_data_with_rowid(self):
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self.dataset.row_id_attribute = "condition"
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rval, _, categorical, _ = self.dataset.get_data(include_row_id=True)
@@ -196,6 +198,7 @@ def test_get_data_with_target_array(self):
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self.assertEqual(len(attribute_names), 38)
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self.assertNotIn("class", attribute_names)
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@pytest.mark.skip("https://github.com/openml/openml-python/issues/1157")
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def test_get_data_with_target_pandas(self):
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X, y, categorical, attribute_names = self.dataset.get_data(target="class")
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self.assertIsInstance(X, pd.DataFrame)
@@ -220,6 +223,7 @@ def test_get_data_rowid_and_ignore_and_target(self):
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self.assertListEqual(categorical, cats)
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self.assertEqual(y.shape, (898,))
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@pytest.mark.skip("https://github.com/openml/openml-python/issues/1157")
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def test_get_data_with_ignore_attributes(self):
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self.dataset.ignore_attribute = ["condition"]
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rval, _, categorical, _ = self.dataset.get_data(include_ignore_attribute=True)

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