Backport PR #57314 on branch 2.2.x (BUG: Fix near-minimum timestamp h…

…andling) (#57573) Backport PR #57314: BUG: Fix near-minimum timestamp handling Co-authored-by: Robert Schmidtke <robert-schmidtke@users.noreply.github.com>

doc/source/whatsnew/v2.2.1.rst

@@ -21,6 +21,7 @@ Fixed regressions
 ~~~~~~~~~~~~~~~~~
 - Fixed memory leak in :func:`read_csv` (:issue:`57039`)
 - Fixed performance regression in :meth:`Series.combine_first` (:issue:`55845`)
+- Fixed regression causing overflow for near-minimum timestamps (:issue:`57150`)
 - Fixed regression in :func:`concat` changing long-standing behavior that always sorted the non-concatenation axis when the axis was a :class:`DatetimeIndex` (:issue:`57006`)
 - Fixed regression in :func:`merge_ordered` raising ``TypeError`` for ``fill_method="ffill"`` and ``how="left"`` (:issue:`57010`)
 - Fixed regression in :func:`pandas.testing.assert_series_equal` defaulting to ``check_exact=True`` when checking the :class:`Index` (:issue:`57067`)

pandas/_libs/src/vendored/numpy/datetime/np_datetime.c

@@ -482,10 +482,20 @@ npy_datetime npy_datetimestruct_to_datetime(NPY_DATETIMEUNIT base,
 
  if (base == NPY_FR_ns) {
  int64_t nanoseconds;
- PD_CHECK_OVERFLOW(
- scaleMicrosecondsToNanoseconds(microseconds, &nanoseconds));
- PD_CHECK_OVERFLOW(
- checked_int64_add(nanoseconds, dts->ps / 1000, &nanoseconds));
+
+ // Minimum valid timestamp in nanoseconds (1677-09-21 00:12:43.145224193).
+ const int64_t min_nanoseconds = NPY_MIN_INT64 + 1;
+ if (microseconds == min_nanoseconds / 1000 - 1) {
+ // For values within one microsecond of min_nanoseconds, use it as base
+ // and offset it with nanosecond delta to avoid overflow during scaling.
+ PD_CHECK_OVERFLOW(checked_int64_add(
+ min_nanoseconds, (dts->ps - _NS_MIN_DTS.ps) / 1000, &nanoseconds));
+ } else {
+ PD_CHECK_OVERFLOW(
+ scaleMicrosecondsToNanoseconds(microseconds, &nanoseconds));
+ PD_CHECK_OVERFLOW(
+ checked_int64_add(nanoseconds, dts->ps / 1000, &nanoseconds));
+ }
 
  return nanoseconds;
  }

pandas/tests/tslibs/test_array_to_datetime.py

@@ -296,6 +296,23 @@ def test_to_datetime_barely_out_of_bounds():
  tslib.array_to_datetime(arr)
 
 
+@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
+ 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):
  pass