API: Timestamp and Timedelta .value changing in 2.0

pandas/_libs/index.pyx

@@ -517,14 +517,16 @@ cdef class DatetimeEngine(Int64Engine):
  # NB: caller is responsible for ensuring tzawareness compat
  # before we get here
  if scalar is NaT:
- return NaT.value
+ return NaT._value
  elif isinstance(scalar, _Timestamp):
  if scalar._creso == self._creso:
- return scalar.value
+ return scalar._value
  else:
  # Note: caller is responsible for catching potential ValueError
  # from _as_creso
- return (<_Timestamp>scalar)._as_creso(self._creso, round_ok=False).value
+ return (
+ (<_Timestamp>scalar)._as_creso(self._creso, round_ok=False)._value
+ )
  raise TypeError(scalar)
 
  def __contains__(self, val: object) -> bool:
@@ -585,22 +587,24 @@ cdef class TimedeltaEngine(DatetimeEngine):
 
  cdef int64_t _unbox_scalar(self, scalar) except? -1:
  if scalar is NaT:
- return NaT.value
+ return NaT._value
  elif isinstance(scalar, _Timedelta):
  if scalar._creso == self._creso:
- return scalar.value
+ return scalar._value
  else:
  # Note: caller is responsible for catching potential ValueError
  # from _as_creso
- return (<_Timedelta>scalar)._as_creso(self._creso, round_ok=False).value
+ return (
+ (<_Timedelta>scalar)._as_creso(self._creso, round_ok=False)._value
+ )
  raise TypeError(scalar)
 
 
 cdef class PeriodEngine(Int64Engine):
 
  cdef int64_t _unbox_scalar(self, scalar) except? -1:
  if scalar is NaT:
- return scalar.value
+ return scalar._value
  if is_period_object(scalar):
  # NB: we assume that we have the correct freq here.
  return scalar.ordinal

pandas/_libs/src/ujson/python/objToJSON.c

@@ -1306,9 +1306,9 @@ char **NpyArr_encodeLabels(PyArrayObject *labels, PyObjectEncoder *enc,
  castfunc(dataptr, &nanosecVal, 1, NULL, NULL);
  } else if (PyDate_Check(item) || PyDelta_Check(item)) {
  is_datetimelike = 1;
- if (PyObject_HasAttrString(item, "value")) {
+ if (PyObject_HasAttrString(item, "_value")) {
  // see test_date_index_and_values for case with non-nano
- nanosecVal = get_long_attr(item, "value");
+ nanosecVal = get_long_attr(item, "_value");
  } else {
  if (PyDelta_Check(item)) {
  nanosecVal = total_seconds(item) *
@@ -1554,8 +1554,8 @@ void Object_beginTypeContext(JSOBJ _obj, JSONTypeContext *tc) {
  }
  return;
  } else if (PyDelta_Check(obj)) {
- if (PyObject_HasAttrString(obj, "value")) {
- value = get_long_attr(obj, "value");
+ if (PyObject_HasAttrString(obj, "_value")) {
+ value = get_long_attr(obj, "_value");
  } else {
  value = total_seconds(obj) * 1000000000LL; // nanoseconds per sec
  }

pandas/_libs/tslib.pyx

@@ -765,7 +765,7 @@ def array_to_datetime_with_tz(ndarray values, tzinfo tz):
  # datetime64, tznaive pydatetime, int, float
  ts = ts.tz_localize(tz)
  ts = ts.as_unit("ns")
- ival = ts.value
+ ival = ts._value
 
  # Analogous to: result[i] = ival
  (<int64_t*>cnp.PyArray_MultiIter_DATA(mi, 0))[0] = ival

pandas/_libs/tslibs/conversion.pyx

@@ -765,7 +765,7 @@ cdef int64_t parse_pydatetime(
  result = _ts.value
  else:
  if isinstance(val, _Timestamp):
- result = val.as_unit("ns").value
+ result = val.as_unit("ns")._value
  else:
  result = pydatetime_to_dt64(val, dts)
  check_dts_bounds(dts)

pandas/_libs/tslibs/nattype.pxd

@@ -8,7 +8,7 @@ cdef set c_nat_strings
 
 cdef class _NaT(datetime):
  cdef readonly:
- int64_t value
+ int64_t _value
 
 cdef _NaT c_NaT
 

pandas/_libs/tslibs/nattype.pyi

@@ -19,6 +19,7 @@ class _NatComparison:
 
 class NaTType:
  value: np.int64
+ _value: np.int64
  @property
  def asm8(self) -> np.datetime64: ...
  def to_datetime64(self) -> np.datetime64: ...

pandas/_libs/tslibs/nattype.pyx

@@ -357,7 +357,7 @@ class NaTType(_NaT):
  cdef _NaT base
 
  base = _NaT.__new__(cls, 1, 1, 1)
- base.value = NPY_NAT
+ base._value= NPY_NAT
 
  return base
 

pandas/_libs/tslibs/offsets.pyx

@@ -183,7 +183,7 @@ def apply_wraps(func):
  res = result.tz_localize(None)
  else:
  res = result
- value = res.as_unit("ns").value
+ value = res.as_unit("ns")._value
  result = Timestamp(value + nano)
 
  if tz is not None and result.tzinfo is None:
@@ -3469,7 +3469,7 @@ cdef class FY5253Quarter(FY5253Mixin):
  else:
  tdelta = Timedelta(0)
 
- # Note: we always have tdelta.value >= 0
+ # Note: we always have tdelta._value>= 0
  return start, num_qtrs, tdelta
 
  @apply_wraps
@@ -3481,7 +3481,7 @@ cdef class FY5253Quarter(FY5253Mixin):
  prev_year_end, num_qtrs, tdelta = self._rollback_to_year(other)
  res = prev_year_end
  n += num_qtrs
- if self.n <= 0 and tdelta.value > 0:
+ if self.n <= 0 and tdelta._value > 0:
  n += 1
 
  # Possible speedup by handling years first.

pandas/_libs/tslibs/strptime.pyx

@@ -113,14 +113,14 @@ cdef bint parse_today_now(str val, int64_t* iresult, bint utc):
  # microsecond resolution
  if val == "now":
  if utc:
- iresult[0] = Timestamp.utcnow().value * 1000
+ iresult[0] = Timestamp.utcnow()._value * 1000
  else:
  # GH#18705 make sure to_datetime("now") matches Timestamp("now")
  # Note using Timestamp.now() is faster than Timestamp("now")
- iresult[0] = Timestamp.now().value * 1000
+ iresult[0] = Timestamp.now()._value * 1000
  return True
  elif val == "today":
- iresult[0] = Timestamp.today().value * 1000
+ iresult[0] = Timestamp.today()._value * 1000
  return True
  return False
 
@@ -284,7 +284,7 @@ def array_strptime(
  utc,
  )
  if isinstance(val, _Timestamp):
- iresult[i] = val.tz_localize(None).as_unit("ns").value
+ iresult[i] = val.tz_localize(None).as_unit("ns")._value
  else:
  iresult[i] = pydatetime_to_dt64(val.replace(tzinfo=None), &dts)
  check_dts_bounds(&dts)

pandas/_libs/tslibs/timedeltas.pxd

@@ -14,7 +14,7 @@ cdef bint is_any_td_scalar(object obj)
 
 cdef class _Timedelta(timedelta):
  cdef readonly:
- int64_t value # nanoseconds
+ int64_t _value # nanoseconds
  bint _is_populated # are my components populated
  int64_t _d, _h, _m, _s, _ms, _us, _ns
  NPY_DATETIMEUNIT _creso

pandas/_libs/tslibs/timedeltas.pyi

@@ -89,6 +89,7 @@ class Timedelta(timedelta):
  max: ClassVar[Timedelta]
  resolution: ClassVar[Timedelta]
  value: int # np.int64
+ _value: int # np.int64
  # error: "__new__" must return a class instance (got "Union[Timestamp, NaTType]")
  def __new__( # type: ignore[misc]
  cls: type[_S],