TST: move fixtures to Base_pytest(object) class

Author: winklerand

pandas/tests/test_resample.py

@@ -2697,31 +2697,52 @@ def test_evenly_divisible_with_no_extra_bins(self):
 def assert_series_or_frame_equal(result, expected):
     if isinstance(result, Series):
         return assert_series_equal(result, expected)
-    else:
+    if isinstance(result, DataFrame):
         return assert_frame_equal(result, expected)
 
 
-class TestPeriodIndexIdiomaticPytest:
+class Base_pytest(object):
+    """
+    base class for resampling testing providing fixtures for each index type
+    - index: default index defined by _index_factory in each subclass
+    - pandas_obj: default Series and DataFrame objects
+    """
 
-    @pytest.fixture(scope='class')
-    def index(self):
-        return period_range(datetime(2005, 1, 1),
-                            datetime(2005, 1, 10), freq='D')
+    _index_fixture_start = datetime(2005, 1, 1)
+    _index_fixture_end = datetime(2005, 1, 10)
+    _index_fixture_freq = 'D'
 
-    @pytest.fixture(scope='class')
-    def series(self, index):
-        return Series(np.arange(len(index)), index=index, name='pi')
+    def create_index(self, *args, **kwargs):
+        """ return the _index_factory created using the args, kwargs """
+        factory = self._index_factory()
+        return factory(*args, **kwargs)
 
     @pytest.fixture(scope='class')
-    def frame(self, index):
-        return DataFrame({'value': np.arange(len(index))}, index=index)
+    def index(self):
+        return self.create_index(self._index_fixture_start,
+                                 self._index_fixture_end,
+                                 freq=self._index_fixture_freq)
 
     @pytest.fixture(params=[Series, DataFrame], scope='class')
     def pandas_obj(self, request, index):
         if request.param == Series:
-            return self.series(index)
+            return Series(np.arange(len(index)), index=index,
+                          name=self._series_fixture_name)
         if request.param == DataFrame:
-            return self.frame(index)
+            return DataFrame({'value': np.arange(len(index))}, index=index)
+
+
+class TestDatetimeIndex_pytest(Base_pytest):
+    _index_factory = lambda x: date_range
+    _series_fixture_name = 'dti'
+
+    # stub, put parametrized tests here
+    pass
+
+
+class TestPeriodIndex_pytest(Base_pytest):
+    _index_factory = lambda x: period_range
+    _series_fixture_name = 'pi'
 
     @pytest.mark.parametrize('freq', ['2D'])
     @pytest.mark.parametrize('kind', ['period', None])
@@ -2810,18 +2831,19 @@ def test_resample_5minute(self, freq, kind):
         result = ts.resample(freq, kind=kind).mean()
         assert_series_equal(result, expected)
 
+    @pytest.mark.parametrize('pandas_obj', [DataFrame], indirect=True)
     @pytest.mark.parametrize('kind', ['period', None, 'timestamp'])
     @pytest.mark.parametrize('agg_arg', ['mean', {'value': 'mean'}, ['mean']])
-    def test_loffset_returns_datetimeindex(self, frame, kind, agg_arg):
+    def test_loffset_returns_datetimeindex(self, pandas_obj, kind, agg_arg):
         # make sure passing loffset returns DatetimeIndex in all cases
         # basic method taken from Base.test_resample_loffset_arg_type()
         # df = self.create_series().to_frame('value')
-        df = frame
+        df = pandas_obj
         expected_means = [df.values[i:i + 2].mean()
                           for i in range(0, len(df.values), 2)]
-        expected_index = period_range(df.index[0], periods=len(df.index) / 2,
-                                      freq='2D')
-
+        expected_index = self.create_index(df.index[0],
+                                           periods=len(df.index) / 2,
+                                           freq='2D')
         # loffset coreces PeriodIndex to DateTimeIndex
         expected_index = expected_index.to_timestamp()
         expected_index += timedelta(hours=2)