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Oct 29, 2017
Merged

Follow-up to #17805 #18023

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43 changes: 16 additions & 27 deletions pandas/_libs/period.pyx
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Original file line number Diff line number Diff line change
Expand Up @@ -17,12 +17,9 @@ from pandas.compat import PY2

cimport cython

from datetime cimport (
is_leapyear,
pandas_datetimestruct,
pandas_datetimestruct_to_datetime,
pandas_datetime_to_datetimestruct,
PANDAS_FR_ns)
from tslibs.np_datetime cimport (pandas_datetimestruct,
dtstruct_to_dt64, dt64_to_dtstruct)
from datetime cimport is_leapyear


cimport util
Expand Down Expand Up @@ -137,7 +134,7 @@ def dt64arr_to_periodarr(ndarray[int64_t] dtarr, int freq, tz=None):
if dtarr[i] == NPY_NAT:
out[i] = NPY_NAT
continue
pandas_datetime_to_datetimestruct(dtarr[i], PANDAS_FR_ns, &dts)
dt64_to_dtstruct(dtarr[i], &dts)
out[i] = get_period_ordinal(dts.year, dts.month, dts.day,
dts.hour, dts.min, dts.sec,
dts.us, dts.ps, freq)
Expand Down Expand Up @@ -268,7 +265,7 @@ cpdef int64_t period_ordinal_to_dt64(int64_t ordinal, int freq) nogil:
dts.us = int((subsecond_fraction) * 1e6)
dts.ps = int(((subsecond_fraction) * 1e6 - dts.us) * 1e6)

return pandas_datetimestruct_to_datetime(PANDAS_FR_ns, &dts)
return dtstruct_to_dt64(&dts)


def period_format(int64_t value, int freq, object fmt=None):
Expand Down Expand Up @@ -499,7 +496,7 @@ cpdef resolution(ndarray[int64_t] stamps, tz=None):
for i in range(n):
if stamps[i] == NPY_NAT:
continue
pandas_datetime_to_datetimestruct(stamps[i], PANDAS_FR_ns, &dts)
dt64_to_dtstruct(stamps[i], &dts)
curr_reso = _reso_stamp(&dts)
if curr_reso < reso:
reso = curr_reso
Expand Down Expand Up @@ -530,21 +527,19 @@ cdef _reso_local(ndarray[int64_t] stamps, object tz):
for i in range(n):
if stamps[i] == NPY_NAT:
continue
pandas_datetime_to_datetimestruct(stamps[i], PANDAS_FR_ns, &dts)
dt64_to_dtstruct(stamps[i], &dts)
curr_reso = _reso_stamp(&dts)
if curr_reso < reso:
reso = curr_reso
elif is_tzlocal(tz):
for i in range(n):
if stamps[i] == NPY_NAT:
continue
pandas_datetime_to_datetimestruct(stamps[i], PANDAS_FR_ns,
&dts)
dt64_to_dtstruct(stamps[i], &dts)
dt = datetime(dts.year, dts.month, dts.day, dts.hour,
dts.min, dts.sec, dts.us, tz)
delta = int(get_utcoffset(tz, dt).total_seconds()) * 1000000000
pandas_datetime_to_datetimestruct(stamps[i] + delta,
PANDAS_FR_ns, &dts)
dt64_to_dtstruct(stamps[i] + delta, &dts)
curr_reso = _reso_stamp(&dts)
if curr_reso < reso:
reso = curr_reso
Expand All @@ -562,17 +557,15 @@ cdef _reso_local(ndarray[int64_t] stamps, object tz):
for i in range(n):
if stamps[i] == NPY_NAT:
continue
pandas_datetime_to_datetimestruct(stamps[i] + deltas[0],
PANDAS_FR_ns, &dts)
dt64_to_dtstruct(stamps[i] + deltas[0], &dts)
curr_reso = _reso_stamp(&dts)
if curr_reso < reso:
reso = curr_reso
else:
for i in range(n):
if stamps[i] == NPY_NAT:
continue
pandas_datetime_to_datetimestruct(stamps[i] + deltas[pos[i]],
PANDAS_FR_ns, &dts)
dt64_to_dtstruct(stamps[i] + deltas[pos[i]], &dts)
curr_reso = _reso_stamp(&dts)
if curr_reso < reso:
reso = curr_reso
Expand All @@ -595,7 +588,7 @@ cdef ndarray[int64_t] localize_dt64arr_to_period(ndarray[int64_t] stamps,
if stamps[i] == NPY_NAT:
result[i] = NPY_NAT
continue
pandas_datetime_to_datetimestruct(stamps[i], PANDAS_FR_ns, &dts)
dt64_to_dtstruct(stamps[i], &dts)
result[i] = get_period_ordinal(dts.year, dts.month, dts.day,
dts.hour, dts.min, dts.sec,
dts.us, dts.ps, freq)
Expand All @@ -605,13 +598,11 @@ cdef ndarray[int64_t] localize_dt64arr_to_period(ndarray[int64_t] stamps,
if stamps[i] == NPY_NAT:
result[i] = NPY_NAT
continue
pandas_datetime_to_datetimestruct(stamps[i], PANDAS_FR_ns,
&dts)
dt64_to_dtstruct(stamps[i], &dts)
dt = datetime(dts.year, dts.month, dts.day, dts.hour,
dts.min, dts.sec, dts.us, tz)
delta = int(get_utcoffset(tz, dt).total_seconds()) * 1000000000
pandas_datetime_to_datetimestruct(stamps[i] + delta,
PANDAS_FR_ns, &dts)
dt64_to_dtstruct(stamps[i] + delta, &dts)
result[i] = get_period_ordinal(dts.year, dts.month, dts.day,
dts.hour, dts.min, dts.sec,
dts.us, dts.ps, freq)
Expand All @@ -630,8 +621,7 @@ cdef ndarray[int64_t] localize_dt64arr_to_period(ndarray[int64_t] stamps,
if stamps[i] == NPY_NAT:
result[i] = NPY_NAT
continue
pandas_datetime_to_datetimestruct(stamps[i] + deltas[0],
PANDAS_FR_ns, &dts)
dt64_to_dtstruct(stamps[i] + deltas[0], &dts)
result[i] = get_period_ordinal(dts.year, dts.month, dts.day,
dts.hour, dts.min, dts.sec,
dts.us, dts.ps, freq)
Expand All @@ -640,8 +630,7 @@ cdef ndarray[int64_t] localize_dt64arr_to_period(ndarray[int64_t] stamps,
if stamps[i] == NPY_NAT:
result[i] = NPY_NAT
continue
pandas_datetime_to_datetimestruct(stamps[i] + deltas[pos[i]],
PANDAS_FR_ns, &dts)
dt64_to_dtstruct(stamps[i] + deltas[pos[i]], &dts)
result[i] = get_period_ordinal(dts.year, dts.month, dts.day,
dts.hour, dts.min, dts.sec,
dts.us, dts.ps, freq)
Expand Down
42 changes: 18 additions & 24 deletions pandas/_libs/tslib.pyx
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -33,7 +33,6 @@ cimport util
from cpython.datetime cimport PyDelta_Check, PyTZInfo_Check
# this is our datetime.pxd
from datetime cimport (
pandas_datetimestruct,
pandas_datetime_to_datetimestruct,
pandas_datetimestruct_to_datetime,
days_per_month_table,
Expand All @@ -50,14 +49,15 @@ from datetime cimport (
PANDAS_FR_ns,
PyDateTime_Check, PyDate_Check,
PyDateTime_IMPORT,
timedelta, datetime
)
timedelta, datetime)

# stdlib datetime imports
from datetime import timedelta, datetime
from datetime import time as datetime_time

from tslibs.np_datetime cimport check_dts_bounds
from tslibs.np_datetime cimport (check_dts_bounds,
pandas_datetimestruct,
dt64_to_dtstruct, dtstruct_to_dt64)
from tslibs.np_datetime import OutOfBoundsDatetime

from khash cimport (
Expand Down Expand Up @@ -149,17 +149,15 @@ def ints_to_pydatetime(ndarray[int64_t] arr, tz=None, freq=None, box=False):
if value == NPY_NAT:
result[i] = NaT
else:
pandas_datetime_to_datetimestruct(
value, PANDAS_FR_ns, &dts)
dt64_to_dtstruct(value, &dts)
result[i] = func_create(value, dts, tz, freq)
elif is_tzlocal(tz) or is_fixed_offset(tz):
for i in range(n):
value = arr[i]
if value == NPY_NAT:
result[i] = NaT
else:
pandas_datetime_to_datetimestruct(
value, PANDAS_FR_ns, &dts)
dt64_to_dtstruct(value, &dts)
dt = create_datetime_from_ts(value, dts, tz, freq)
dt = dt + tz.utcoffset(dt)
if box:
Expand All @@ -185,8 +183,7 @@ def ints_to_pydatetime(ndarray[int64_t] arr, tz=None, freq=None, box=False):
# represented in single object.
new_tz = tz

pandas_datetime_to_datetimestruct(
value + deltas[pos], PANDAS_FR_ns, &dts)
dt64_to_dtstruct(value + deltas[pos], &dts)
result[i] = func_create(value, dts, new_tz, freq)
else:
for i in range(n):
Expand All @@ -195,7 +192,7 @@ def ints_to_pydatetime(ndarray[int64_t] arr, tz=None, freq=None, box=False):
if value == NPY_NAT:
result[i] = NaT
else:
pandas_datetime_to_datetimestruct(value, PANDAS_FR_ns, &dts)
dt64_to_dtstruct(value, &dts)
result[i] = func_create(value, dts, None, freq)

return result
Expand Down Expand Up @@ -698,7 +695,7 @@ class Timestamp(_Timestamp):
value += value - value_tz

# setup components
pandas_datetime_to_datetimestruct(value, PANDAS_FR_ns, &dts)
dt64_to_dtstruct(value, &dts)
dts.ps = self.nanosecond * 1000

# replace
Expand Down Expand Up @@ -1811,7 +1808,7 @@ def _test_parse_iso8601(object ts):
obj = _TSObject()

_string_to_dts(ts, &obj.dts, &out_local, &out_tzoffset)
obj.value = pandas_datetimestruct_to_datetime(PANDAS_FR_ns, &obj.dts)
obj.value = dtstruct_to_dt64(&obj.dts)
check_dts_bounds(&obj.dts)
if out_local == 1:
obj.tzinfo = pytz.FixedOffset(out_tzoffset)
Expand Down Expand Up @@ -1984,7 +1981,7 @@ def format_array_from_datetime(ndarray[int64_t] values, object tz=None,
result[i] = na_rep
elif basic_format:

pandas_datetime_to_datetimestruct(val, PANDAS_FR_ns, &dts)
dt64_to_dtstruct(val, &dts)
res = '%d-%.2d-%.2d %.2d:%.2d:%.2d' % (dts.year,
dts.month,
dts.day,
Expand Down Expand Up @@ -3792,7 +3789,7 @@ cdef inline int64_t _normalized_stamp(pandas_datetimestruct *dts) nogil:
dts.sec = 0
dts.us = 0
dts.ps = 0
return pandas_datetimestruct_to_datetime(PANDAS_FR_ns, dts)
return dtstruct_to_dt64(dts)


def dates_normalized(ndarray[int64_t] stamps, tz=None):
Expand Down Expand Up @@ -3910,13 +3907,12 @@ def shift_months(int64_t[:] dtindex, int months, object day=None):
out[i] = NPY_NAT
continue

pandas_datetime_to_datetimestruct(dtindex[i],
PANDAS_FR_ns, &dts)
dt64_to_dtstruct(dtindex[i], &dts)
dts.year = _year_add_months(dts, months)
dts.month = _month_add_months(dts, months)

dts.day = min(dts.day, days_in_month(dts))
out[i] = pandas_datetimestruct_to_datetime(PANDAS_FR_ns, &dts)
out[i] = dtstruct_to_dt64(&dts)
elif day == 'start':
roll_check = False
if months <= 0:
Expand All @@ -3928,8 +3924,7 @@ def shift_months(int64_t[:] dtindex, int months, object day=None):
out[i] = NPY_NAT
continue

pandas_datetime_to_datetimestruct(dtindex[i],
PANDAS_FR_ns, &dts)
dt64_to_dtstruct(dtindex[i], &dts)
months_to_roll = months

# offset semantics - if on the anchor point and going backwards
Expand All @@ -3941,7 +3936,7 @@ def shift_months(int64_t[:] dtindex, int months, object day=None):
dts.month = _month_add_months(dts, months_to_roll)
dts.day = 1

out[i] = pandas_datetimestruct_to_datetime(PANDAS_FR_ns, &dts)
out[i] = dtstruct_to_dt64(&dts)
elif day == 'end':
roll_check = False
if months > 0:
Expand All @@ -3953,8 +3948,7 @@ def shift_months(int64_t[:] dtindex, int months, object day=None):
out[i] = NPY_NAT
continue

pandas_datetime_to_datetimestruct(dtindex[i],
PANDAS_FR_ns, &dts)
dt64_to_dtstruct(dtindex[i], &dts)
months_to_roll = months

# similar semantics - when adding shift forward by one
Expand All @@ -3966,7 +3960,7 @@ def shift_months(int64_t[:] dtindex, int months, object day=None):
dts.month = _month_add_months(dts, months_to_roll)

dts.day = days_in_month(dts)
out[i] = pandas_datetimestruct_to_datetime(PANDAS_FR_ns, &dts)
out[i] = dtstruct_to_dt64(&dts)
else:
raise ValueError("day must be None, 'start' or 'end'")

Expand Down
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