ENH: Add test for to_datetime with scalar out of bounds value

Author: kosiew

pandas/tests/tools/test_to_datetime.py

@@ -1,6 +1,7 @@
 """test to_datetime"""
 
 import calendar
+import locale
 from collections import deque
 from datetime import (
     date,
@@ -9,12 +10,12 @@
     timezone,
 )
 from decimal import Decimal
-import locale
 import zoneinfo
 
-from dateutil.parser import parse
 import numpy as np
+import pandas as pd
 import pytest
+from dateutil.parser import parse
 
 from pandas._libs import tslib
 from pandas._libs.tslibs import (
@@ -29,8 +30,6 @@
 import pandas.util._test_decorators as td
 
 from pandas.core.dtypes.common import is_datetime64_ns_dtype
-
-import pandas as pd
 from pandas import (
     DataFrame,
     DatetimeIndex,
@@ -3689,3 +3688,22 @@ def test_to_datetime_wrapped_datetime64_ps():
         ["1970-01-01 00:00:01.901901901"], dtype="datetime64[ns]", freq=None
     )
     tm.assert_index_equal(result, expected)
+    
+
+def test_to_datetime_scalar_out_of_bounds():
+    """Ensure pd.to_datetime raises an error for out-of-bounds scalar values."""
+    uint64_max = np.iinfo("uint64").max
+
+    # Expect an OverflowError when passing uint64_max as a scalar
+    with pytest.raises(OutOfBoundsDatetime):
+        pd.to_datetime(uint64_max, unit="ns")
+
+    # Expect the same behavior when passing it as a list
+    with pytest.raises(OutOfBoundsDatetime):
+        pd.to_datetime([uint64_max], unit="ns")
+
+    # Test a valid value (should not raise an error)
+    valid_timestamp = 1_700_000_000_000_000_000  # A reasonable nanosecond timestamp
+    result = pd.to_datetime(valid_timestamp, unit="ns")
+    assert isinstance(result, pd.Timestamp)
+