expand test for demonstration purposes

pandas/tests/tslibs/test_array_to_datetime.py

@@ -272,15 +272,21 @@ def test_to_datetime_barely_out_of_bounds():
  tslib.array_to_datetime(arr)
 
 
-def test_to_datetime_barely_inside_bounds():
+@pytest.mark.parametrize(
+ "timestamp",
+ [
+ # Close enough to bounds that scaling micros to nanos overflows
+ # but adding nanos would result in an in-bounds datetime.
+ "1677-09-21T00:12:43.145224193",
+ "1677-09-21T00:12:43.145224999",
+ # this always worked
+ "1677-09-21T00:12:43.145225000",
+ ],
+)
+def test_to_datetime_barely_inside_bounds(timestamp):
  # see gh-57150
- #
- # Close enough to bounds that scaling micros to nanos overflows
- # but adding nanos would result in an in-bounds datetime.
- arr = np.array(["1677-09-21T00:12:43.145224193"], dtype=object)
- result, _ = tslib.array_to_datetime(arr)
- expected = ["1677-09-21T00:12:43.145224193"]
- tm.assert_numpy_array_equal(result, np.array(expected, dtype="M8[ns]"))
+ result, _ = tslib.array_to_datetime(np.array([timestamp], dtype=object))
+ tm.assert_numpy_array_equal(result, np.array([timestamp], dtype="M8[ns]"))
 
 
 class SubDatetime(datetime):