ENH: non-nano Timestamp.timestamp, to_period (#46990)

* ENH: Timestamp.timestamp non-nano * ENH: Timestamp.to_period non-nano * normalize prelims

Author: jbrockmendel

pandas/_libs/tslibs/dtypes.pxd

@@ -6,6 +6,7 @@ from pandas._libs.tslibs.np_datetime cimport NPY_DATETIMEUNIT
 cdef str npy_unit_to_abbrev(NPY_DATETIMEUNIT unit)
 cdef NPY_DATETIMEUNIT freq_group_code_to_npy_unit(int freq) nogil
 cdef int64_t periods_per_day(NPY_DATETIMEUNIT reso=*) except? -1
+cdef int64_t periods_per_second(NPY_DATETIMEUNIT reso) except? -1
 
 cdef dict attrname_to_abbrevs
 

pandas/_libs/tslibs/dtypes.pyx

@@ -348,6 +348,19 @@ cdef int64_t periods_per_day(NPY_DATETIMEUNIT reso=NPY_DATETIMEUNIT.NPY_FR_ns) e
  return day_units
 
 
+cdef int64_t periods_per_second(NPY_DATETIMEUNIT reso) except? -1:
+ if reso == NPY_DATETIMEUNIT.NPY_FR_ns:
+ return 1_000_000_000
+ elif reso == NPY_DATETIMEUNIT.NPY_FR_us:
+ return 1_000_000
+ elif reso == NPY_DATETIMEUNIT.NPY_FR_ms:
+ return 1_000
+ elif reso == NPY_DATETIMEUNIT.NPY_FR_s:
+ return 1
+ else:
+ raise NotImplementedError(reso)
+
+
 cdef dict _reso_str_map = {
  Resolution.RESO_NS.value: "nanosecond",
  Resolution.RESO_US.value: "microsecond",

pandas/_libs/tslibs/timestamps.pyx

@@ -52,7 +52,11 @@ from pandas._libs.tslibs.conversion cimport (
  convert_datetime_to_tsobject,
  convert_to_tsobject,
 )
-from pandas._libs.tslibs.dtypes cimport npy_unit_to_abbrev
+from pandas._libs.tslibs.dtypes cimport (
+ npy_unit_to_abbrev,
+ periods_per_day,
+ periods_per_second,
+)
 from pandas._libs.tslibs.util cimport (
  is_array,
  is_datetime64_object,
@@ -811,11 +815,12 @@ cdef class _Timestamp(ABCTimestamp):
  cdef:
  local_val = self._maybe_convert_value_to_local()
  int64_t normalized
+ int64_t ppd = periods_per_day(self._reso)
 
  if self._reso != NPY_FR_ns:
  raise NotImplementedError(self._reso)
 
- normalized = normalize_i8_stamp(local_val)
+ normalized = normalize_i8_stamp(local_val, ppd)
  return Timestamp(normalized).tz_localize(self.tzinfo)
 
  # -----------------------------------------------------------------
@@ -834,8 +839,8 @@ cdef class _Timestamp(ABCTimestamp):
 
  if len(state) == 3:
  # pre-non-nano pickle
+ # TODO: no tests get here 2022-05-10
  reso = NPY_FR_ns
- assert False # checking for coverage
  else:
  reso = state[4]
  self._reso = reso
@@ -982,10 +987,10 @@ cdef class _Timestamp(ABCTimestamp):
  """
  # GH 17329
  # Note: Naive timestamps will not match datetime.stdlib
- if self._reso != NPY_FR_ns:
- raise NotImplementedError(self._reso)
 
- return round(self.value / 1e9, 6)
+ denom = periods_per_second(self._reso)
+
+ return round(self.value / denom, 6)
 
  cpdef datetime to_pydatetime(_Timestamp self, bint warn=True):
  """
@@ -1080,9 +1085,6 @@ cdef class _Timestamp(ABCTimestamp):
  """
  from pandas import Period
 
- if self._reso != NPY_FR_ns:
- raise NotImplementedError(self._reso)
-
  if self.tz is not None:
  # GH#21333
  warnings.warn(
@@ -2252,16 +2254,18 @@ Timestamp.resolution = Timedelta(nanoseconds=1) # GH#21336, GH#21365
 
 
 @cython.cdivision(False)
-cdef inline int64_t normalize_i8_stamp(int64_t local_val) nogil:
+cdef inline int64_t normalize_i8_stamp(int64_t local_val, int64_t ppd) nogil:
  """
  Round the localized nanosecond timestamp down to the previous midnight.
 
  Parameters
  ----------
  local_val : int64_t
+ ppd : int64_t
+ Periods per day in the Timestamp's resolution.
 
  Returns
  -------
  int64_t
  """
- return local_val - (local_val % ccalendar.DAY_NANOS)
+ return local_val - (local_val % ppd)

pandas/tests/scalar/timestamp/test_timestamp.py

@@ -840,3 +840,11 @@ def test_to_datetime64(self, dt64, ts):
  res = ts.to_datetime64()
  assert res == dt64
  assert res.dtype == dt64.dtype
+
+ def test_timestamp(self, dt64, ts):
+ alt = Timestamp(dt64)
+ assert ts.timestamp() == alt.timestamp()
+
+ def test_to_period(self, dt64, ts):
+ alt = Timestamp(dt64)
+ assert ts.to_period("D") == alt.to_period("D")