TST: Clean / make tests more performant

pandas/core/arrays/datetimes.py

@@ -90,6 +90,9 @@
     from pandas.core.arrays import PeriodArray
 
 
+_ITER_CHUNKSIZE = 10_000
+
+
 def tz_to_dtype(
     tz: tzinfo | None, unit: str = "ns"
 ) -> np.dtype[np.datetime64] | DatetimeTZDtype:
@@ -654,7 +657,7 @@ def __iter__(self) -> Iterator:
             # convert in chunks of 10k for efficiency
             data = self.asi8
             length = len(self)
-            chunksize = 10000
+            chunksize = _ITER_CHUNKSIZE
             chunks = (length // chunksize) + 1
 
             for i in range(chunks):

pandas/tests/indexes/datetimes/test_iter.py

@@ -7,6 +7,7 @@
     date_range,
     to_datetime,
 )
+from pandas.core.arrays import datetimes
 
 
 class TestDatetimeIndexIteration:
@@ -59,13 +60,17 @@ def test_iteration_preserves_tz3(self):
             assert result._repr_base == expected._repr_base
             assert result == expected
 
-    @pytest.mark.parametrize("periods", [0, 9999, 10000, 10001])
-    def test_iteration_over_chunksize(self, periods):
+    @pytest.mark.parametrize("offset", [-5, -1, 0, 1])
+    def test_iteration_over_chunksize(self, offset, monkeypatch):
         # GH#21012
-
-        index = date_range("2000-01-01 00:00:00", periods=periods, freq="min")
+        chunksize = 5
+        index = date_range(
+            "2000-01-01 00:00:00", periods=chunksize - offset, freq="min"
+        )
         num = 0
-        for stamp in index:
-            assert index[num] == stamp
-            num += 1
+        with monkeypatch.context() as m:
+            m.setattr(datetimes, "_ITER_CHUNKSIZE", chunksize)
+            for stamp in index:
+                assert index[num] == stamp
+                num += 1
         assert num == len(index)

pandas/tests/resample/test_datetime_index.py

@@ -1866,7 +1866,7 @@ def test_resample_equivalent_offsets(n1, freq1, n2, freq2, k, unit):
     # GH 24127
     n1_ = n1 * k
     n2_ = n2 * k
-    dti = date_range("19910905 13:00", "19911005 07:00", freq=freq1).as_unit(unit)
+    dti = date_range("1991-09-05", "1991-09-12", freq=freq1).as_unit(unit)
     ser = Series(range(len(dti)), index=dti)
 
     result1 = ser.resample(str(n1_) + freq1).mean()

pandas/tests/window/test_apply.py

@@ -301,8 +301,9 @@ def test_center_reindex_series(raw, series):
     tm.assert_series_equal(series_xp, series_rs)
 
 
-def test_center_reindex_frame(raw, frame):
+def test_center_reindex_frame(raw):
     # shifter index
+    frame = DataFrame(range(100), index=date_range("2020-01-01", freq="D", periods=100))
     s = [f"x{x:d}" for x in range(12)]
     minp = 10