BUG: catch overflow in timestamp + offset operations

xref statsmodels/statsmodels#3374

Author: jreback

doc/source/whatsnew/v0.20.0.txt

@@ -355,6 +355,7 @@ Bug Fixes
 - Bug in ``DataFrame.groupby().describe()`` when grouping on ``Index`` containing tuples (:issue:`14848`)
 - Bug in creating a ``MultiIndex`` with tuples and not passing a list of names; this will now raise ``ValueError`` (:issue:`15110`)
 
+- Bug in catching an overflow in ``Timestamp`` + ``Timedelta/Offset`` operations (:issue:``)
 
 
 

pandas/tseries/offsets.py

@@ -2710,6 +2710,9 @@ def __add__(self, other):
             return self.apply(other)
         except ApplyTypeError:
             return NotImplemented
+        except OverflowError:
+            raise OverflowError("the add operation between {} and {} "
+                                "will overflow".format(self, other))
 
     def __eq__(self, other):
         if isinstance(other, compat.string_types):
@@ -2748,14 +2751,20 @@ def nanos(self):
 
     def apply(self, other):
         # Timestamp can handle tz and nano sec, thus no need to use apply_wraps
-        if isinstance(other, (datetime, np.datetime64, date)):
+        if isinstance(other, Timestamp):
+            result = as_timestamp(other).__add__(self)
+            if result == NotImplemented:
+                raise OverflowError
+            return result
+        elif isinstance(other, (datetime, np.datetime64, date)):
             return as_timestamp(other) + self
+
         if isinstance(other, timedelta):
             return other + self.delta
         elif isinstance(other, type(self)):
             return type(self)(self.n + other.n)
-        else:
-            raise ApplyTypeError('Unhandled type: %s' % type(other).__name__)
+
+        raise ApplyTypeError('Unhandled type: %s' % type(other).__name__)
 
     _prefix = 'undefined'
 

pandas/tseries/tests/test_timedeltas.py

@@ -971,6 +971,11 @@ def test_overflow(self):
         s2 = s[0:1000]
         result = (s2 - s2.min()).sum()
 
+    def test_overflow_on_construction(self):
+        # xref https://github.com/statsmodels/statsmodels/issues/3374
+        value = pd.Timedelta('1day').value * 20169940
+        self.assertRaises(OverflowError, pd.Timedelta, value)
+
     def test_timedelta_ops_scalar(self):
         # GH 6808
         base = pd.to_datetime('20130101 09:01:12.123456')

pandas/tseries/tests/test_timeseries.py

@@ -3320,6 +3320,21 @@ def test_datetime64_with_DateOffset(self):
     #     expected = rng + timedelta(2)
     #     self.assertTrue(result.equals(expected))
 
+
+    def test_really_large_offset(self):
+        # xref https://github.com/statsmodels/statsmodels/issues/3374
+        # ends up multiplying really large numbers which overflow
+
+        t = Timestamp('2017-01-13 00:00:00', freq='D')
+        offset = 20169940 * pd.offsets.Day(1)
+        def f():
+            t + offset
+        self.assertRaises(OverflowError, f)
+
+        def f():
+            offset + t
+        self.assertRaises(OverflowError, f)
+
     def test_get_duplicates(self):
         idx = DatetimeIndex(['2000-01-01', '2000-01-02', '2000-01-02',
                              '2000-01-03', '2000-01-03', '2000-01-04'])

pandas/tslib.pyx

@@ -1220,7 +1220,10 @@ cdef class _Timestamp(datetime):
             return Timestamp((self.freq * other).apply(self), freq=self.freq)
 
         elif isinstance(other, timedelta) or hasattr(other, 'delta'):
-            nanos = _delta_to_nanoseconds(other)
+            try:
+                nanos = _delta_to_nanoseconds(other)
+            except OverflowError:
+                return NotImplemented
             result = Timestamp(self.value + nanos,
                                tz=self.tzinfo, freq=self.freq)
             if getattr(other, 'normalize', False):
@@ -3125,7 +3128,7 @@ class Timedelta(_Timedelta):
         if not (is_integer_object(other) or is_float_object(other)):
             return NotImplemented
 
-        return Timedelta(other *self.value, unit='ns')
+        return Timedelta(other * self.value, unit='ns')
 
     __rmul__ = __mul__