MAINT: Remove tm.assertNotIsInstance (#16061)

Author: gfyoung

pandas/tests/indexes/common.py

@@ -1,5 +1,7 @@
 # -*- coding: utf-8 -*-
 
+import pytest
+
 from pandas import compat
 from pandas.compat import PY3
 
@@ -793,41 +795,41 @@ def test_numpy_ufuncs(self):
                 if isinstance(idx, DatetimeIndexOpsMixin):
                     # raise TypeError or ValueError (PeriodIndex)
                     # PeriodIndex behavior should be changed in future version
-                    with tm.assertRaises(Exception):
+                    with pytest.raises(Exception):
                         with np.errstate(all='ignore'):
                             func(idx)
                 elif isinstance(idx, (Float64Index, Int64Index, UInt64Index)):
                     # coerces to float (e.g. np.sin)
                     with np.errstate(all='ignore'):
                         result = func(idx)
                         exp = Index(func(idx.values), name=idx.name)
-                    self.assert_index_equal(result, exp)
-                    self.assertIsInstance(result, pd.Float64Index)
+
+                    tm.assert_index_equal(result, exp)
+                    assert isinstance(result, pd.Float64Index)
                 else:
                     # raise AttributeError or TypeError
                     if len(idx) == 0:
                         continue
                     else:
-                        with tm.assertRaises(Exception):
+                        with pytest.raises(Exception):
                             with np.errstate(all='ignore'):
                                 func(idx)
 
             for func in [np.isfinite, np.isinf, np.isnan, np.signbit]:
                 if isinstance(idx, DatetimeIndexOpsMixin):
                     # raise TypeError or ValueError (PeriodIndex)
-                    with tm.assertRaises(Exception):
+                    with pytest.raises(Exception):
                         func(idx)
                 elif isinstance(idx, (Float64Index, Int64Index, UInt64Index)):
-                    # results in bool array
+                    # Results in bool array
                     result = func(idx)
-                    exp = func(idx.values)
-                    self.assertIsInstance(result, np.ndarray)
-                    tm.assertNotIsInstance(result, Index)
+                    assert isinstance(result, np.ndarray)
+                    assert not isinstance(result, Index)
                 else:
                     if len(idx) == 0:
                         continue
                     else:
-                        with tm.assertRaises(Exception):
+                        with pytest.raises(Exception):
                             func(idx)
 
     def test_hasnans_isnans(self):

pandas/tests/indexes/datetimes/test_indexing.py

@@ -1,5 +1,6 @@
-import numpy as np
+import pytest
 
+import numpy as np
 import pandas as pd
 import pandas.util.testing as tm
 import pandas.compat as compat
@@ -54,9 +55,9 @@ def test_insert(self):
         expected = Index([datetime(2000, 1, 4), 'inserted',
                           datetime(2000, 1, 1),
                           datetime(2000, 1, 2)], name='idx')
-        self.assertNotIsInstance(result, DatetimeIndex)
+        assert not isinstance(result, DatetimeIndex)
         tm.assert_index_equal(result, expected)
-        self.assertEqual(result.name, expected.name)
+        assert result.name == expected.name
 
         idx = date_range('1/1/2000', periods=3, freq='M', name='idx')
 
@@ -85,33 +86,32 @@ def test_insert(self):
         for n, d, expected in cases:
             result = idx.insert(n, d)
             tm.assert_index_equal(result, expected)
-            self.assertEqual(result.name, expected.name)
-            self.assertEqual(result.freq, expected.freq)
+            assert result.name == expected.name
+            assert result.freq == expected.freq
 
         # reset freq to None
         result = idx.insert(3, datetime(2000, 1, 2))
         expected = DatetimeIndex(['2000-01-31', '2000-02-29', '2000-03-31',
                                   '2000-01-02'], name='idx', freq=None)
         tm.assert_index_equal(result, expected)
-        self.assertEqual(result.name, expected.name)
-        self.assertTrue(result.freq is None)
+        assert result.name == expected.name
+        assert result.freq is None
 
         # GH 7299
         tm._skip_if_no_pytz()
         import pytz
 
         idx = date_range('1/1/2000', periods=3, freq='D', tz='Asia/Tokyo',
                          name='idx')
-        with tm.assertRaises(ValueError):
-            result = idx.insert(3, pd.Timestamp('2000-01-04'))
-        with tm.assertRaises(ValueError):
-            result = idx.insert(3, datetime(2000, 1, 4))
-        with tm.assertRaises(ValueError):
-            result = idx.insert(3, pd.Timestamp('2000-01-04', tz='US/Eastern'))
-        with tm.assertRaises(ValueError):
-            result = idx.insert(3,
-                                datetime(2000, 1, 4,
-                                         tzinfo=pytz.timezone('US/Eastern')))
+        with pytest.raises(ValueError):
+            idx.insert(3, pd.Timestamp('2000-01-04'))
+        with pytest.raises(ValueError):
+            idx.insert(3, datetime(2000, 1, 4))
+        with pytest.raises(ValueError):
+            idx.insert(3, pd.Timestamp('2000-01-04', tz='US/Eastern'))
+        with pytest.raises(ValueError):
+            idx.insert(3, datetime(2000, 1, 4,
+                                   tzinfo=pytz.timezone('US/Eastern')))
 
         for tz in ['US/Pacific', 'Asia/Singapore']:
             idx = date_range('1/1/2000 09:00', periods=6, freq='H', tz=tz,
@@ -124,9 +124,9 @@ def test_insert(self):
 
                 result = idx.insert(6, d)
                 tm.assert_index_equal(result, expected)
-                self.assertEqual(result.name, expected.name)
-                self.assertEqual(result.freq, expected.freq)
-                self.assertEqual(result.tz, expected.tz)
+                assert result.name == expected.name
+                assert result.freq == expected.freq
+                assert result.tz == expected.tz
 
             expected = DatetimeIndex(['2000-01-01 09:00', '2000-01-01 10:00',
                                       '2000-01-01 11:00',
@@ -139,9 +139,9 @@ def test_insert(self):
                       pytz.timezone(tz).localize(datetime(2000, 1, 1, 10))]:
                 result = idx.insert(6, d)
                 tm.assert_index_equal(result, expected)
-                self.assertEqual(result.name, expected.name)
-                self.assertTrue(result.freq is None)
-                self.assertEqual(result.tz, expected.tz)
+                assert result.name == expected.name
+                assert result.tz == expected.tz
+                assert result.freq is None
 
     def test_delete(self):
         idx = date_range(start='2000-01-01', periods=5, freq='M', name='idx')

pandas/tests/indexes/test_base.py

@@ -283,27 +283,27 @@ def test_constructor_dtypes(self):
         for idx in [Index(np.array([1, 2, 3], dtype=int)),
                     Index(np.array([1, 2, 3], dtype=int), dtype=int),
                     Index([1, 2, 3], dtype=int)]:
-            self.assertIsInstance(idx, Int64Index)
+            assert isinstance(idx, Int64Index)
 
-        # these should coerce
+        # These should coerce
         for idx in [Index(np.array([1., 2., 3.], dtype=float), dtype=int),
                     Index([1., 2., 3.], dtype=int)]:
-            self.assertIsInstance(idx, Int64Index)
+            assert isinstance(idx, Int64Index)
 
         for idx in [Index(np.array([1., 2., 3.], dtype=float)),
                     Index(np.array([1, 2, 3], dtype=int), dtype=float),
                     Index(np.array([1., 2., 3.], dtype=float), dtype=float),
                     Index([1, 2, 3], dtype=float),
                     Index([1., 2., 3.], dtype=float)]:
-            self.assertIsInstance(idx, Float64Index)
+            assert isinstance(idx, Float64Index)
 
         for idx in [Index(np.array([True, False, True], dtype=bool)),
                     Index([True, False, True]),
                     Index(np.array([True, False, True], dtype=bool),
                           dtype=bool),
                     Index([True, False, True], dtype=bool)]:
-            self.assertIsInstance(idx, Index)
-            self.assertEqual(idx.dtype, object)
+            assert isinstance(idx, Index)
+            assert idx.dtype == object
 
         for idx in [Index(np.array([1, 2, 3], dtype=int), dtype='category'),
                     Index([1, 2, 3], dtype='category'),
@@ -312,32 +312,32 @@ def test_constructor_dtypes(self):
                           dtype='category'),
                     Index([datetime(2011, 1, 1), datetime(2011, 1, 2)],
                           dtype='category')]:
-            self.assertIsInstance(idx, CategoricalIndex)
+            assert isinstance(idx, CategoricalIndex)
 
         for idx in [Index(np.array([np_datetime64_compat('2011-01-01'),
                                     np_datetime64_compat('2011-01-02')])),
                     Index([datetime(2011, 1, 1), datetime(2011, 1, 2)])]:
-            self.assertIsInstance(idx, DatetimeIndex)
+            assert isinstance(idx, DatetimeIndex)
 
         for idx in [Index(np.array([np_datetime64_compat('2011-01-01'),
                                     np_datetime64_compat('2011-01-02')]),
                           dtype=object),
                     Index([datetime(2011, 1, 1),
                            datetime(2011, 1, 2)], dtype=object)]:
-            self.assertNotIsInstance(idx, DatetimeIndex)
-            self.assertIsInstance(idx, Index)
-            self.assertEqual(idx.dtype, object)
+            assert not isinstance(idx, DatetimeIndex)
+            assert isinstance(idx, Index)
+            assert idx.dtype == object
 
         for idx in [Index(np.array([np.timedelta64(1, 'D'), np.timedelta64(
                 1, 'D')])), Index([timedelta(1), timedelta(1)])]:
-            self.assertIsInstance(idx, TimedeltaIndex)
+            assert isinstance(idx, TimedeltaIndex)
 
         for idx in [Index(np.array([np.timedelta64(1, 'D'),
                                     np.timedelta64(1, 'D')]), dtype=object),
                     Index([timedelta(1), timedelta(1)], dtype=object)]:
-            self.assertNotIsInstance(idx, TimedeltaIndex)
-            self.assertIsInstance(idx, Index)
-            self.assertEqual(idx.dtype, object)
+            assert not isinstance(idx, TimedeltaIndex)
+            assert isinstance(idx, Index)
+            assert idx.dtype == object
 
     def test_constructor_dtypes_datetime(self):
 

pandas/tests/indexes/test_category.py

@@ -1,5 +1,7 @@
 # -*- coding: utf-8 -*-
 
+import pytest
+
 import pandas.util.testing as tm
 from pandas.core.indexes.api import Index, CategoricalIndex
 from .common import Base
@@ -37,62 +39,66 @@ def test_construction(self):
 
         result = Index(ci)
         tm.assert_index_equal(result, ci, exact=True)
-        self.assertFalse(result.ordered)
+        assert not result.ordered
 
         result = Index(ci.values)
         tm.assert_index_equal(result, ci, exact=True)
-        self.assertFalse(result.ordered)
+        assert not result.ordered
 
         # empty
         result = CategoricalIndex(categories=categories)
-        self.assert_index_equal(result.categories, Index(categories))
+        tm.assert_index_equal(result.categories, Index(categories))
         tm.assert_numpy_array_equal(result.codes, np.array([], dtype='int8'))
-        self.assertFalse(result.ordered)
+        assert not result.ordered
 
         # passing categories
         result = CategoricalIndex(list('aabbca'), categories=categories)
-        self.assert_index_equal(result.categories, Index(categories))
+        tm.assert_index_equal(result.categories, Index(categories))
         tm.assert_numpy_array_equal(result.codes,
-                                    np.array([0, 0, 1, 1, 2, 0], dtype='int8'))
+                                    np.array([0, 0, 1,
+                                              1, 2, 0], dtype='int8'))
 
         c = pd.Categorical(list('aabbca'))
         result = CategoricalIndex(c)
-        self.assert_index_equal(result.categories, Index(list('abc')))
+        tm.assert_index_equal(result.categories, Index(list('abc')))
         tm.assert_numpy_array_equal(result.codes,
-                                    np.array([0, 0, 1, 1, 2, 0], dtype='int8'))
-        self.assertFalse(result.ordered)
+                                    np.array([0, 0, 1,
+                                              1, 2, 0], dtype='int8'))
+        assert not result.ordered
 
         result = CategoricalIndex(c, categories=categories)
-        self.assert_index_equal(result.categories, Index(categories))
+        tm.assert_index_equal(result.categories, Index(categories))
         tm.assert_numpy_array_equal(result.codes,
-                                    np.array([0, 0, 1, 1, 2, 0], dtype='int8'))
-        self.assertFalse(result.ordered)
+                                    np.array([0, 0, 1,
+                                              1, 2, 0], dtype='int8'))
+        assert not result.ordered
 
         ci = CategoricalIndex(c, categories=list('abcd'))
         result = CategoricalIndex(ci)
-        self.assert_index_equal(result.categories, Index(categories))
+        tm.assert_index_equal(result.categories, Index(categories))
         tm.assert_numpy_array_equal(result.codes,
-                                    np.array([0, 0, 1, 1, 2, 0], dtype='int8'))
-        self.assertFalse(result.ordered)
+                                    np.array([0, 0, 1,
+                                              1, 2, 0], dtype='int8'))
+        assert not result.ordered
 
         result = CategoricalIndex(ci, categories=list('ab'))
-        self.assert_index_equal(result.categories, Index(list('ab')))
+        tm.assert_index_equal(result.categories, Index(list('ab')))
         tm.assert_numpy_array_equal(result.codes,
-                                    np.array([0, 0, 1, 1, -1, 0],
-                                             dtype='int8'))
-        self.assertFalse(result.ordered)
+                                    np.array([0, 0, 1,
+                                              1, -1, 0], dtype='int8'))
+        assert not result.ordered
 
         result = CategoricalIndex(ci, categories=list('ab'), ordered=True)
-        self.assert_index_equal(result.categories, Index(list('ab')))
+        tm.assert_index_equal(result.categories, Index(list('ab')))
         tm.assert_numpy_array_equal(result.codes,
-                                    np.array([0, 0, 1, 1, -1, 0],
-                                             dtype='int8'))
-        self.assertTrue(result.ordered)
+                                    np.array([0, 0, 1,
+                                              1, -1, 0], dtype='int8'))
+        assert result.ordered
 
         # turn me to an Index
         result = Index(np.array(ci))
-        self.assertIsInstance(result, Index)
-        self.assertNotIsInstance(result, CategoricalIndex)
+        assert isinstance(result, Index)
+        assert not isinstance(result, CategoricalIndex)
 
     def test_construction_with_dtype(self):
 
@@ -325,9 +331,9 @@ def test_delete(self):
         expected = CategoricalIndex(list('aabbc'), categories=categories)
         tm.assert_index_equal(result, expected, exact=True)
 
-        with tm.assertRaises((IndexError, ValueError)):
-            # either depeidnig on numpy version
-            result = ci.delete(10)
+        with pytest.raises((IndexError, ValueError)):
+            # Either depending on NumPy version
+            ci.delete(10)
 
     def test_astype(self):
 
@@ -336,12 +342,12 @@ def test_astype(self):
         tm.assert_index_equal(result, ci, exact=True)
 
         result = ci.astype(object)
-        self.assert_index_equal(result, Index(np.array(ci)))
+        tm.assert_index_equal(result, Index(np.array(ci)))
 
         # this IS equal, but not the same class
-        self.assertTrue(result.equals(ci))
-        self.assertIsInstance(result, Index)
-        self.assertNotIsInstance(result, CategoricalIndex)
+        assert result.equals(ci)
+        assert isinstance(result, Index)
+        assert not isinstance(result, CategoricalIndex)
 
         # interval
         ii = IntervalIndex.from_arrays(left=[-0.001, 2.0],

pandas/tests/indexes/test_multi.py

@@ -539,17 +539,17 @@ def test_astype(self):
     def test_constructor_single_level(self):
         single_level = MultiIndex(levels=[['foo', 'bar', 'baz', 'qux']],
                                   labels=[[0, 1, 2, 3]], names=['first'])
-        tm.assertIsInstance(single_level, Index)
-        self.assertNotIsInstance(single_level, MultiIndex)
-        self.assertEqual(single_level.name, 'first')
+        assert isinstance(single_level, Index)
+        assert not isinstance(single_level, MultiIndex)
+        assert single_level.name == 'first'
 
         single_level = MultiIndex(levels=[['foo', 'bar', 'baz', 'qux']],
                                   labels=[[0, 1, 2, 3]])
-        self.assertIsNone(single_level.name)
+        assert single_level.name is None
 
     def test_constructor_no_levels(self):
-        assertRaisesRegexp(ValueError, "non-zero number of levels/labels",
-                           MultiIndex, levels=[], labels=[])
+        tm.assertRaisesRegexp(ValueError, "non-zero number of levels/labels",
+                              MultiIndex, levels=[], labels=[])
         both_re = re.compile('Must pass both levels and labels')
         with tm.assertRaisesRegexp(TypeError, both_re):
             MultiIndex(levels=[])