TST: arithmetic test parametrization/cleanup (#38673)

Author: jbrockmendel

pandas/core/arrays/datetimes.py

@@ -2077,15 +2077,15 @@ def objects_to_datetime64ns(
             require_iso8601=require_iso8601,
         )
         result = result.reshape(data.shape, order=order)
-    except ValueError as e:
+    except ValueError as err:
         try:
             values, tz_parsed = conversion.datetime_to_datetime64(data.ravel("K"))
             # If tzaware, these values represent unix timestamps, so we
             #  return them as i8 to distinguish from wall times
             values = values.reshape(data.shape, order=order)
             return values.view("i8"), tz_parsed
         except (ValueError, TypeError):
-            raise e
+            raise err
 
     if tz_parsed is not None:
         # We can take a shortcut since the datetime64 numpy array

pandas/core/dtypes/cast.py

@@ -231,6 +231,7 @@ def maybe_downcast_to_dtype(result, dtype: Union[str, np.dtype]):
             # convert to datetime and change timezone
             i8values = result.astype("i8", copy=False)
             cls = dtype.construct_array_type()
+            # equiv: DatetimeArray(i8values).tz_localize("UTC").tz_convert(dtype.tz)
             result = cls._simple_new(i8values, dtype=dtype)
         else:
             result = result.astype(dtype)

pandas/tests/arithmetic/test_period.py

@@ -41,7 +41,9 @@ def test_compare_zerodim(self, box_with_array):
         expected = tm.box_expected(expected, xbox)
         tm.assert_equal(result, expected)
 
-    @pytest.mark.parametrize("scalar", ["foo", Timestamp.now(), Timedelta(days=4)])
+    @pytest.mark.parametrize(
+        "scalar", ["foo", Timestamp.now(), Timedelta(days=4), 9, 9.5]
+    )
     def test_compare_invalid_scalar(self, box_with_array, scalar):
         # comparison with scalar that cannot be interpreted as a Period
         pi = pd.period_range("2000", periods=4)

pandas/tests/arithmetic/test_timedelta64.py

@@ -16,6 +16,7 @@
     Timedelta,
     TimedeltaIndex,
     Timestamp,
+    offsets,
     timedelta_range,
 )
 import pandas._testing as tm
@@ -70,7 +71,12 @@ def test_compare_timedelta64_zerodim(self, box_with_array):
 
     @pytest.mark.parametrize(
         "td_scalar",
-        [timedelta(days=1), Timedelta(days=1), Timedelta(days=1).to_timedelta64()],
+        [
+            timedelta(days=1),
+            Timedelta(days=1),
+            Timedelta(days=1).to_timedelta64(),
+            offsets.Hour(24),
+        ],
     )
     def test_compare_timedeltalike_scalar(self, box_with_array, td_scalar):
         # regression test for GH#5963
@@ -84,7 +90,18 @@ def test_compare_timedeltalike_scalar(self, box_with_array, td_scalar):
         expected = tm.box_expected(expected, xbox)
         tm.assert_equal(actual, expected)
 
-    @pytest.mark.parametrize("invalid", [345600000000000, "a"])
+    @pytest.mark.parametrize(
+        "invalid",
+        [
+            345600000000000,
+            "a",
+            Timestamp.now(),
+            Timestamp.now("UTC"),
+            Timestamp.now().to_datetime64(),
+            Timestamp.now().to_pydatetime(),
+            Timestamp.now().date(),
+        ],
+    )
     def test_td64_comparisons_invalid(self, box_with_array, invalid):
         # GH#13624 for str
         box = box_with_array
@@ -261,7 +278,6 @@ def test_ufunc_coercions(self):
             tm.assert_index_equal(result, exp)
             assert result.freq == "H"
 
-        idx = TimedeltaIndex(["2H", "4H", "6H", "8H", "10H"], freq="2H", name="x")
         for result in [-idx, np.negative(idx)]:
             assert isinstance(result, TimedeltaIndex)
             exp = TimedeltaIndex(
@@ -413,10 +429,6 @@ def test_dti_tdi_numeric_ops(self):
         tdi = TimedeltaIndex(["1 days", pd.NaT, "2 days"], name="foo")
         dti = pd.date_range("20130101", periods=3, name="bar")
 
-        # TODO(wesm): unused?
-        # td = Timedelta('1 days')
-        # dt = Timestamp('20130101')
-
         result = tdi - tdi
         expected = TimedeltaIndex(["0 days", pd.NaT, "0 days"], name="foo")
         tm.assert_index_equal(result, expected)
@@ -543,7 +555,6 @@ def test_tda_add_sub_index(self):
         expected = tdi - tdi
         tm.assert_index_equal(result, expected)
 
-    @pytest.mark.xfail(reason="GH38630", strict=False)
     def test_tda_add_dt64_object_array(self, box_with_array, tz_naive_fixture):
         # Result should be cast back to DatetimeArray
         box = box_with_array
@@ -555,10 +566,7 @@ def test_tda_add_dt64_object_array(self, box_with_array, tz_naive_fixture):
         obj = tm.box_expected(tdi, box)
         other = tm.box_expected(dti, box)
 
-        warn = None
-        if box is not pd.DataFrame or tz_naive_fixture is None:
-            warn = PerformanceWarning
-        with tm.assert_produces_warning(warn):
+        with tm.assert_produces_warning(PerformanceWarning):
             result = obj + other.astype(object)
         tm.assert_equal(result, other)
 

pandas/tests/extension/base/setitem.py

@@ -40,7 +40,7 @@ def test_setitem_sequence_mismatched_length_raises(self, data, as_array):
             ser[slice(3)] = value
         self.assert_series_equal(ser, original)
 
-    def test_setitem_empty_indxer(self, data, box_in_series):
+    def test_setitem_empty_indexer(self, data, box_in_series):
         if box_in_series:
             data = pd.Series(data)
         original = data.copy()

pandas/tests/series/test_arithmetic.py

@@ -267,7 +267,7 @@ def test_sub_datetimelike_align(self):
 
     def test_alignment_doesnt_change_tz(self):
         # GH#33671
-        dti = pd.date_range("2016-01-01", periods=10, tz="CET")
+        dti = date_range("2016-01-01", periods=10, tz="CET")
         dti_utc = dti.tz_convert("UTC")
         ser = Series(10, index=dti)
         ser_utc = Series(10, index=dti_utc)
@@ -399,7 +399,7 @@ def test_ser_flex_cmp_return_dtypes_empty(self, opname):
     )
     def test_ser_cmp_result_names(self, names, op):
         # datetime64 dtype
-        dti = pd.date_range("1949-06-07 03:00:00", freq="H", periods=5, name=names[0])
+        dti = date_range("1949-06-07 03:00:00", freq="H", periods=5, name=names[0])
         ser = Series(dti).rename(names[1])
         result = op(ser, dti)
         assert result.name == names[2]
@@ -624,9 +624,13 @@ def test_ne(self):
             ),
         ],
     )
-    def test_comp_ops_df_compat(self, left, right):
+    def test_comp_ops_df_compat(self, left, right, frame_or_series):
         # GH 1134
-        msg = "Can only compare identically-labeled Series objects"
+        msg = f"Can only compare identically-labeled {frame_or_series.__name__} objects"
+        if frame_or_series is not Series:
+            left = left.to_frame()
+            right = right.to_frame()
+
         with pytest.raises(ValueError, match=msg):
             left == right
         with pytest.raises(ValueError, match=msg):
@@ -642,22 +646,6 @@ def test_comp_ops_df_compat(self, left, right):
         with pytest.raises(ValueError, match=msg):
             right < left
 
-        msg = "Can only compare identically-labeled DataFrame objects"
-        with pytest.raises(ValueError, match=msg):
-            left.to_frame() == right.to_frame()
-        with pytest.raises(ValueError, match=msg):
-            right.to_frame() == left.to_frame()
-
-        with pytest.raises(ValueError, match=msg):
-            left.to_frame() != right.to_frame()
-        with pytest.raises(ValueError, match=msg):
-            right.to_frame() != left.to_frame()
-
-        with pytest.raises(ValueError, match=msg):
-            left.to_frame() < right.to_frame()
-        with pytest.raises(ValueError, match=msg):
-            right.to_frame() < left.to_frame()
-
     def test_compare_series_interval_keyword(self):
         # GH#25338
         s = Series(["IntervalA", "IntervalB", "IntervalC"])
@@ -724,7 +712,7 @@ def test_series_add_aware_naive_raises(self):
     def test_datetime_understood(self):
         # Ensures it doesn't fail to create the right series
         # reported in issue#16726
-        series = Series(pd.date_range("2012-01-01", periods=3))
+        series = Series(date_range("2012-01-01", periods=3))
         offset = pd.offsets.DateOffset(days=6)
         result = series - offset
         expected = Series(pd.to_datetime(["2011-12-26", "2011-12-27", "2011-12-28"]))
@@ -746,58 +734,46 @@ def test_align_date_objects_with_datetimeindex(self):
         tm.assert_series_equal(result2, expected)
 
 
-@pytest.mark.parametrize(
-    "names",
-    [
-        ("foo", None, None),
-        ("Egon", "Venkman", None),
-        ("NCC1701D", "NCC1701D", "NCC1701D"),
-    ],
-)
-@pytest.mark.parametrize("box", [list, tuple, np.array, pd.Index, pd.Series, pd.array])
-@pytest.mark.parametrize("flex", [True, False])
-def test_series_ops_name_retention(flex, box, names, all_binary_operators, request):
-    # GH#33930 consistent name retention
-    op = all_binary_operators
-
-    if op is ops.rfloordiv and box in [list, tuple] and not flex:
-        mark = pytest.mark.xfail(
-            reason="op fails because of inconsistent ndarray-wrapping GH#28759"
-        )
-        request.node.add_marker(mark)
-
-    left = Series(range(10), name=names[0])
-    right = Series(range(10), name=names[1])
-
-    name = op.__name__.strip("_")
-    is_logical = name in ["and", "rand", "xor", "rxor", "or", "ror"]
-    is_rlogical = is_logical and name.startswith("r")
-
-    right = box(right)
-    if flex:
-        if is_logical:
-            # Series doesn't have these as flex methods
+class TestNamePreservation:
+    @pytest.mark.parametrize("box", [list, tuple, np.array, Index, Series, pd.array])
+    @pytest.mark.parametrize("flex", [True, False])
+    def test_series_ops_name_retention(self, flex, box, names, all_binary_operators):
+        # GH#33930 consistent name renteiton
+        op = all_binary_operators
+
+        if op is ops.rfloordiv and box in [list, tuple]:
+            pytest.xfail("op fails because of inconsistent ndarray-wrapping GH#28759")
+
+        left = Series(range(10), name=names[0])
+        right = Series(range(10), name=names[1])
+
+        name = op.__name__.strip("_")
+        is_logical = name in ["and", "rand", "xor", "rxor", "or", "ror"]
+        is_rlogical = is_logical and name.startswith("r")
+
+        right = box(right)
+        if flex:
+            if is_logical:
+                # Series doesn't have these as flex methods
+                return
+            result = getattr(left, name)(right)
+        else:
+            # GH#37374 logical ops behaving as set ops deprecated
+            warn = FutureWarning if is_rlogical and box is Index else None
+            with tm.assert_produces_warning(warn, check_stacklevel=False):
+                result = op(left, right)
+
+        if box is Index and is_rlogical:
+            # Index treats these as set operators, so does not defer
+            assert isinstance(result, Index)
             return
-        result = getattr(left, name)(right)
-    else:
-        # GH#37374 logical ops behaving as set ops deprecated
-        warn = FutureWarning if is_rlogical and box is Index else None
-        with tm.assert_produces_warning(warn, check_stacklevel=False):
-            result = op(left, right)
-
-    if box is pd.Index and is_rlogical:
-        # Index treats these as set operators, so does not defer
-        assert isinstance(result, pd.Index)
-        return
-
-    assert isinstance(result, Series)
-    if box in [pd.Index, pd.Series]:
-        assert result.name == names[2]
-    else:
-        assert result.name == names[0]
 
+        assert isinstance(result, Series)
+        if box in [Index, Series]:
+            assert result.name == names[2]
+        else:
+            assert result.name == names[0]
 
-class TestNamePreservation:
     def test_binop_maybe_preserve_name(self, datetime_series):
         # names match, preserve
         result = datetime_series * datetime_series