Use pytest conventions consistently (#6337)

* Do not derive from unittest.TestCase (not needed for pytest)

* assertRaises -> pytest.raises

* Simplify test_empty_dmatrix with test parametrization

* setUpClass -> setup_class, tearDownClass -> teardown_class

* Don't import unittest; import pytest

* Use plain assert

* Use parametrized tests in more places

* Fix test_gpu_with_sklearn.py

* Put back run_empty_dmatrix_reg / run_empty_dmatrix_cls

* Fix test_eta_decay_gpu_hist

* Add parametrized tests for monotone constraints

* Fix test names

* Remove test parametrization

* Revise test_slice to be not flaky

tests/python/test_with_modin.py

@@ -2,7 +2,6 @@
 import numpy as np
 import xgboost as xgb
 import testing as tm
-import unittest
 import pytest
 
 try:
@@ -18,7 +17,7 @@ dpath = 'demo/data/'
 rng = np.random.RandomState(1994)
 
 
-class TestModin(unittest.TestCase):
+class TestModin:
 
     def test_modin(self):
 
@@ -43,7 +42,8 @@ class TestModin(unittest.TestCase):
         # incorrect dtypes
         df = md.DataFrame([[1, 2., 'x'], [2, 3., 'y']],
                           columns=['a', 'b', 'c'])
-        self.assertRaises(ValueError, xgb.DMatrix, df)
+        with pytest.raises(ValueError):
+            xgb.DMatrix(df)
 
         # numeric columns
         df = md.DataFrame([[1, 2., True], [2, 3., False]])
@@ -113,13 +113,13 @@ class TestModin(unittest.TestCase):
     def test_modin_label(self):
         # label must be a single column
         df = md.DataFrame({'A': ['X', 'Y', 'Z'], 'B': [1, 2, 3]})
-        self.assertRaises(ValueError, xgb.data._transform_pandas_df, df,
-                          False, None, None, 'label', 'float')
+        with pytest.raises(ValueError):
+            xgb.data._transform_pandas_df(df, False, None, None, 'label', 'float')
 
         # label must be supported dtype
         df = md.DataFrame({'A': np.array(['a', 'b', 'c'], dtype=object)})
-        self.assertRaises(ValueError, xgb.data._transform_pandas_df, df,
-                          False, None, None, 'label', 'float')
+        with pytest.raises(ValueError):
+            xgb.data._transform_pandas_df(df, False, None, None, 'label', 'float')
 
         df = md.DataFrame({'A': np.array([1, 2, 3], dtype=int)})
         result, _, _ = xgb.data._transform_pandas_df(df, False, None, None,