TST: Remove compat.PY2 and compat.PY3 flags from tests

pandas/tests/arithmetic/test_numeric.py

@@ -9,7 +9,7 @@
 import numpy as np
 import pytest
 
-from pandas.compat import PY3, Iterable
+from pandas.compat import Iterable
 
 import pandas as pd
 from pandas import Index, Series, Timedelta, TimedeltaIndex
@@ -438,17 +438,12 @@ def test_div_equiv_binop(self):
         tm.assert_series_equal(result, expected)
 
     def test_div_int(self, numeric_idx):
-        # truediv under PY3
         idx = numeric_idx
         result = idx / 1
-        expected = idx
-        if PY3:
-            expected = expected.astype('float64')
+        expected = idx.astype('float64')
         tm.assert_index_equal(result, expected)
 
         result = idx / 2
-        if PY3:
-            expected = expected.astype('float64')
         expected = Index(idx.values / 2)
         tm.assert_index_equal(result, expected)
 
@@ -1013,13 +1008,8 @@ def test_numeric_compat2(self):
         expected = pd.RangeIndex(-2, 8, 2)
         tm.assert_index_equal(result, expected, exact=True)
 
-        # truediv under PY3
         result = idx / 2
-
-        if PY3:
-            expected = pd.RangeIndex(0, 5, 1).astype('float64')
-        else:
-            expected = pd.RangeIndex(0, 5, 1)
+        expected = pd.RangeIndex(0, 5, 1).astype('float64')
         tm.assert_index_equal(result, expected, exact=True)
 
         result = idx / 4

pandas/tests/arrays/categorical/test_operators.py

@@ -4,8 +4,6 @@
 import numpy as np
 import pytest
 
-from pandas.compat import PY2
-
 import pandas as pd
 from pandas import Categorical, DataFrame, Series, date_range
 from pandas.tests.arrays.categorical.common import TestCategorical
@@ -19,7 +17,6 @@ def test_categories_none_comparisons(self):
                               'a', 'c', 'c', 'c'], ordered=True)
         tm.assert_categorical_equal(factor, self.factor)
 
-    @pytest.mark.skipif(PY2, reason="pytest.raises match regex fails")
     def test_comparisons(self):
 
         result = self.factor[self.factor == 'a']
@@ -190,7 +187,6 @@ def test_comparison_with_unknown_scalars(self):
         tm.assert_numpy_array_equal(cat != 4,
                                     np.array([True, True, True]))
 
-    @pytest.mark.skipif(PY2, reason="pytest.raises match regex fails")
     @pytest.mark.parametrize('data,reverse,base', [
         (list("abc"), list("cba"), list("bbb")),
         ([1, 2, 3], [3, 2, 1], [2, 2, 2])]

pandas/tests/arrays/categorical/test_repr.py

@@ -2,7 +2,7 @@
 
 import numpy as np
 
-from pandas.compat import PY3, u
+from pandas.compat import u
 
 from pandas import (
     Categorical, CategoricalIndex, Series, date_range, period_range,
@@ -60,26 +60,21 @@ def test_print_none_width(self):
             assert exp == repr(a)
 
     def test_unicode_print(self):
-        if PY3:
-            _rep = repr
-        else:
-            _rep = unicode  # noqa
-
         c = Categorical(['aaaaa', 'bb', 'cccc'] * 20)
         expected = u"""\
 [aaaaa, bb, cccc, aaaaa, bb, ..., bb, cccc, aaaaa, bb, cccc]
 Length: 60
 Categories (3, object): [aaaaa, bb, cccc]"""
 
-        assert _rep(c) == expected
+        assert repr(c) == expected
 
         c = Categorical([u'ああああ', u'いいいいい', u'ううううううう'] * 20)
         expected = u"""\
 [ああああ, いいいいい, ううううううう, ああああ, いいいいい, ..., いいいいい, ううううううう, ああああ, いいいいい, ううううううう]
 Length: 60
 Categories (3, object): [ああああ, いいいいい, ううううううう]"""  # noqa
 
-        assert _rep(c) == expected
+        assert repr(c) == expected
 
         # unicode option should not affect to Categorical, as it doesn't care
         # the repr width
@@ -90,7 +85,7 @@ def test_unicode_print(self):
 Length: 60
 Categories (3, object): [ああああ, いいいいい, ううううううう]"""  # noqa
 
-            assert _rep(c) == expected
+            assert repr(c) == expected
 
     def test_categorical_repr(self):
         c = Categorical([1, 2, 3])

pandas/tests/arrays/test_numpy.py

@@ -8,7 +8,6 @@
 import pandas.util._test_decorators as td
 
 import pandas as pd
-from pandas import compat
 from pandas.arrays import PandasArray
 from pandas.core.arrays.numpy_ import PandasDtype
 import pandas.util.testing as tm
@@ -42,8 +41,7 @@ def any_numpy_array(request):
     ('float', True),
     ('complex', True),
     ('str', False),
-    pytest.param('bytes', False,
-                 marks=pytest.mark.skipif(compat.PY2, reason="PY2")),
+    ('bytes', False),
     ('datetime64[ns]', False),
     ('object', False),
     ('void', False),
@@ -60,8 +58,7 @@ def test_is_numeric(dtype, expected):
     ('float', False),
     ('complex', False),
     ('str', False),
-    pytest.param('bytes', False,
-                 marks=pytest.mark.skipif(compat.PY2, reason="PY2")),
+    ('bytes', False),
     ('datetime64[ns]', False),
     ('object', False),
     ('void', False)

pandas/tests/computation/test_eval.py

@@ -7,7 +7,7 @@
 from numpy.random import rand, randint, randn
 import pytest
 
-from pandas.compat import PY3, reduce
+from pandas.compat import reduce
 from pandas.errors import PerformanceWarning
 import pandas.util._test_decorators as td
 
@@ -102,7 +102,7 @@ def _bool_and_frame(lhs, rhs):
 
 
 def _is_py3_complex_incompat(result, expected):
-    return (PY3 and isinstance(expected, (complex, np.complexfloating)) and
+    return (isinstance(expected, (complex, np.complexfloating)) and
             np.isnan(result))
 
 
@@ -1133,50 +1133,27 @@ def test_truediv(self):
         ex = 's / 1'
         d = {'s': s}  # noqa
 
-        if PY3:
-            res = self.eval(ex, truediv=False)
-            tm.assert_numpy_array_equal(res, np.array([1.0]))
+        res = self.eval(ex, truediv=False)
+        tm.assert_numpy_array_equal(res, np.array([1.0]))
 
-            res = self.eval(ex, truediv=True)
-            tm.assert_numpy_array_equal(res, np.array([1.0]))
+        res = self.eval(ex, truediv=True)
+        tm.assert_numpy_array_equal(res, np.array([1.0]))
 
-            res = self.eval('1 / 2', truediv=True)
-            expec = 0.5
-            assert res == expec
+        res = self.eval('1 / 2', truediv=True)
+        expec = 0.5
+        assert res == expec
 
-            res = self.eval('1 / 2', truediv=False)
-            expec = 0.5
-            assert res == expec
+        res = self.eval('1 / 2', truediv=False)
+        expec = 0.5
+        assert res == expec
 
-            res = self.eval('s / 2', truediv=False)
-            expec = 0.5
-            assert res == expec
+        res = self.eval('s / 2', truediv=False)
+        expec = 0.5
+        assert res == expec
 
-            res = self.eval('s / 2', truediv=True)
-            expec = 0.5
-            assert res == expec
-        else:
-            res = self.eval(ex, truediv=False)
-            tm.assert_numpy_array_equal(res, np.array([1]))
-
-            res = self.eval(ex, truediv=True)
-            tm.assert_numpy_array_equal(res, np.array([1.0]))
-
-            res = self.eval('1 / 2', truediv=True)
-            expec = 0.5
-            assert res == expec
-
-            res = self.eval('1 / 2', truediv=False)
-            expec = 0
-            assert res == expec
-
-            res = self.eval('s / 2', truediv=False)
-            expec = 0
-            assert res == expec
-
-            res = self.eval('s / 2', truediv=True)
-            expec = 0.5
-            assert res == expec
+        res = self.eval('s / 2', truediv=True)
+        expec = 0.5
+        assert res == expec
 
     def test_failing_subscript_with_name_error(self):
         df = DataFrame(np.random.randn(5, 3))  # noqa

pandas/tests/dtypes/test_inference.py

@@ -17,7 +17,7 @@
 import pytz
 
 from pandas._libs import iNaT, lib, missing as libmissing
-from pandas.compat import PY2, StringIO, lrange, u
+from pandas.compat import StringIO, lrange, u
 import pandas.util._test_decorators as td
 
 from pandas.core.dtypes import inference
@@ -30,7 +30,7 @@
 import pandas as pd
 from pandas import (
     Categorical, DataFrame, DateOffset, DatetimeIndex, Index, Interval, Period,
-    Series, Timedelta, TimedeltaIndex, Timestamp, compat, isna)
+    Series, Timedelta, TimedeltaIndex, Timestamp, isna)
 from pandas.util import testing as tm
 
 
@@ -286,18 +286,6 @@ def __hash__(self):
     # is_hashable()
     assert not inference.is_hashable(np.array([]))
 
-    # old-style classes in Python 2 don't appear hashable to
-    # collections.Hashable but also seem to support hash() by default
-    if PY2:
-
-        class OldStyleClass():
-            pass
-
-        c = OldStyleClass()
-        assert not isinstance(c, compat.Hashable)
-        assert inference.is_hashable(c)
-        hash(c)  # this will not raise
-
 
 @pytest.mark.parametrize(
     "ll", [re.compile('ad')])
@@ -330,7 +318,7 @@ def test_is_recompilable_fails(ll):
 class TestInference(object):
 
     def test_infer_dtype_bytes(self):
-        compare = 'string' if PY2 else 'bytes'
+        compare = 'bytes'
 
         # string array of bytes
         arr = np.array(list('abc'), dtype='S1')
@@ -658,7 +646,7 @@ def test_unicode(self):
 
         arr = [u'a', np.nan, u'c']
         result = lib.infer_dtype(arr, skipna=True)
-        expected = 'unicode' if PY2 else 'string'
+        expected = 'string'
         assert result == expected
 
     @pytest.mark.parametrize('dtype, missing, skipna, expected', [

pandas/tests/extension/decimal/test_decimal.py

@@ -6,7 +6,6 @@
 import pytest
 
 import pandas as pd
-from pandas import compat
 from pandas.tests.extension import base
 import pandas.util.testing as tm
 
@@ -114,15 +113,12 @@ def assert_frame_equal(self, left, right, *args, **kwargs):
 
 
 class TestDtype(BaseDecimal, base.BaseDtypeTests):
-    @pytest.mark.skipif(compat.PY2, reason="Context not hashable.")
     def test_hashable(self, dtype):
         pass
 
 
 class TestInterface(BaseDecimal, base.BaseInterfaceTests):
-
-    pytestmark = pytest.mark.skipif(compat.PY2,
-                                    reason="Unhashble dtype in Py2.")
+    pass
 
 
 class TestConstructors(BaseDecimal, base.BaseConstructorsTests):
@@ -134,8 +130,7 @@ def test_from_dtype(self, data):
 
 
 class TestReshaping(BaseDecimal, base.BaseReshapingTests):
-    pytestmark = pytest.mark.skipif(compat.PY2,
-                                    reason="Unhashble dtype in Py2.")
+    pass
 
 
 class TestGetitem(BaseDecimal, base.BaseGetitemTests):
@@ -193,22 +188,19 @@ def test_value_counts(self, all_data, dropna):
 
 
 class TestCasting(BaseDecimal, base.BaseCastingTests):
-    pytestmark = pytest.mark.skipif(compat.PY2,
-                                    reason="Unhashble dtype in Py2.")
+    pass
 
 
 class TestGroupby(BaseDecimal, base.BaseGroupbyTests):
-    pytestmark = pytest.mark.skipif(compat.PY2,
-                                    reason="Unhashble dtype in Py2.")
+    pass
 
 
 class TestSetitem(BaseDecimal, base.BaseSetitemTests):
     pass
 
 
 class TestPrinting(BaseDecimal, base.BasePrintingTests):
-    pytestmark = pytest.mark.skipif(compat.PY2,
-                                    reason="Unhashble dtype in Py2.")
+    pass
 
 
 # TODO(extension)
@@ -398,9 +390,6 @@ def _formatting_values(self):
             return np.array(self)
 
     ser = pd.Series(DecimalArray2([decimal.Decimal('1.0')]))
-    # different levels for 2 vs. 3
-    check_stacklevel = compat.PY3
 
-    with tm.assert_produces_warning(DeprecationWarning,
-                                    check_stacklevel=check_stacklevel):
+    with tm.assert_produces_warning(DeprecationWarning, check_stacklevel=True):
         repr(ser)

pandas/tests/extension/json/array.py

@@ -5,7 +5,7 @@
 
 Note:
 
-We currently store lists of UserDicts (Py3 only). Pandas has a few places
+We currently store lists of UserDicts. Pandas has a few places
 internally that specifically check for dicts, and does non-scalar things
 in that case. We *want* the dictionaries to be treated as scalars, so we
 hack around pandas by using UserDicts.

pandas/tests/extension/json/test_json.py

@@ -3,16 +3,14 @@
 
 import pytest
 
-from pandas.compat import PY2, PY36
+from pandas.compat import PY36
 
 import pandas as pd
 from pandas.tests.extension import base
 import pandas.util.testing as tm
 
 from .array import JSONArray, JSONDtype, make_data
 
-pytestmark = pytest.mark.skipif(PY2, reason="Py2 doesn't have a UserDict")
-
 
 @pytest.fixture
 def dtype():