726 lines
23 KiB
Cython
726 lines
23 KiB
Cython
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"""
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timezone conversion
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"""
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cimport cython
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from cpython.datetime cimport (
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PyDelta_Check,
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datetime,
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datetime_new,
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import_datetime,
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timedelta,
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tzinfo,
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)
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from cython cimport Py_ssize_t
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import_datetime()
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import numpy as np
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import pytz
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cimport numpy as cnp
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from numpy cimport (
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int64_t,
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intp_t,
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ndarray,
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uint8_t,
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)
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cnp.import_array()
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from pandas._libs.tslibs.dtypes cimport (
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periods_per_day,
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periods_per_second,
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)
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from pandas._libs.tslibs.nattype cimport NPY_NAT
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from pandas._libs.tslibs.np_datetime cimport (
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NPY_DATETIMEUNIT,
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npy_datetimestruct,
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pandas_datetime_to_datetimestruct,
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)
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from pandas._libs.tslibs.timezones cimport (
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get_dst_info,
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is_fixed_offset,
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is_tzlocal,
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is_utc,
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is_zoneinfo,
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utc_pytz,
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)
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cdef const int64_t[::1] _deltas_placeholder = np.array([], dtype=np.int64)
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@cython.freelist(16)
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@cython.final
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cdef class Localizer:
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# cdef:
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# tzinfo tz
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# NPY_DATETIMEUNIT _reso
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# bint use_utc, use_fixed, use_tzlocal, use_dst, use_pytz
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# ndarray trans
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# Py_ssize_t ntrans
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# const int64_t[::1] deltas
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# int64_t delta
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# int64_t* tdata
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@cython.initializedcheck(False)
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@cython.boundscheck(False)
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def __cinit__(self, tzinfo tz, NPY_DATETIMEUNIT reso):
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self.tz = tz
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self._reso = reso
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self.use_utc = self.use_tzlocal = self.use_fixed = False
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self.use_dst = self.use_pytz = False
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self.ntrans = -1 # placeholder
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self.delta = -1 # placeholder
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self.deltas = _deltas_placeholder
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self.tdata = NULL
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if is_utc(tz) or tz is None:
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self.use_utc = True
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elif is_tzlocal(tz) or is_zoneinfo(tz):
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self.use_tzlocal = True
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else:
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trans, deltas, typ = get_dst_info(tz)
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if reso != NPY_DATETIMEUNIT.NPY_FR_ns:
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# NB: using floordiv here is implicitly assuming we will
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# never see trans or deltas that are not an integer number
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# of seconds.
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# TODO: avoid these np.array calls
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if reso == NPY_DATETIMEUNIT.NPY_FR_us:
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trans = np.array(trans) // 1_000
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deltas = np.array(deltas) // 1_000
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elif reso == NPY_DATETIMEUNIT.NPY_FR_ms:
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trans = np.array(trans) // 1_000_000
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deltas = np.array(deltas) // 1_000_000
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elif reso == NPY_DATETIMEUNIT.NPY_FR_s:
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trans = np.array(trans) // 1_000_000_000
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deltas = np.array(deltas) // 1_000_000_000
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else:
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raise NotImplementedError(reso)
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self.trans = trans
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self.ntrans = self.trans.shape[0]
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self.deltas = deltas
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if typ != "pytz" and typ != "dateutil":
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# static/fixed; in this case we know that len(delta) == 1
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self.use_fixed = True
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self.delta = deltas[0]
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else:
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self.use_dst = True
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if typ == "pytz":
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self.use_pytz = True
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self.tdata = <int64_t*>cnp.PyArray_DATA(trans)
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@cython.boundscheck(False)
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cdef inline int64_t utc_val_to_local_val(
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self, int64_t utc_val, Py_ssize_t* pos, bint* fold=NULL
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) except? -1:
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if self.use_utc:
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return utc_val
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elif self.use_tzlocal:
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return utc_val + _tz_localize_using_tzinfo_api(
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utc_val, self.tz, to_utc=False, reso=self._reso, fold=fold
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)
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elif self.use_fixed:
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return utc_val + self.delta
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else:
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pos[0] = bisect_right_i8(self.tdata, utc_val, self.ntrans) - 1
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if fold is not NULL:
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fold[0] = _infer_dateutil_fold(
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utc_val, self.trans, self.deltas, pos[0]
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)
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return utc_val + self.deltas[pos[0]]
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cdef int64_t tz_localize_to_utc_single(
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int64_t val,
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tzinfo tz,
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object ambiguous=None,
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object nonexistent=None,
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NPY_DATETIMEUNIT reso=NPY_DATETIMEUNIT.NPY_FR_ns,
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) except? -1:
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"""See tz_localize_to_utc.__doc__"""
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cdef:
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int64_t delta
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int64_t[::1] deltas
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if val == NPY_NAT:
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return val
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elif is_utc(tz) or tz is None:
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# TODO: test with non-nano
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return val
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elif is_tzlocal(tz) or is_zoneinfo(tz):
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return val - _tz_localize_using_tzinfo_api(val, tz, to_utc=True, reso=reso)
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elif is_fixed_offset(tz):
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_, deltas, _ = get_dst_info(tz)
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delta = deltas[0]
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# TODO: de-duplicate with Localizer.__init__
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if reso != NPY_DATETIMEUNIT.NPY_FR_ns:
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if reso == NPY_DATETIMEUNIT.NPY_FR_us:
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delta = delta // 1000
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elif reso == NPY_DATETIMEUNIT.NPY_FR_ms:
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delta = delta // 1_000_000
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elif reso == NPY_DATETIMEUNIT.NPY_FR_s:
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delta = delta // 1_000_000_000
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return val - delta
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else:
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return tz_localize_to_utc(
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np.array([val], dtype="i8"),
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tz,
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ambiguous=ambiguous,
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nonexistent=nonexistent,
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reso=reso,
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)[0]
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@cython.boundscheck(False)
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@cython.wraparound(False)
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def tz_localize_to_utc(
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ndarray[int64_t] vals,
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tzinfo tz,
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object ambiguous=None,
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object nonexistent=None,
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NPY_DATETIMEUNIT reso=NPY_DATETIMEUNIT.NPY_FR_ns,
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):
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"""
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Localize tzinfo-naive i8 to given time zone (using pytz). If
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there are ambiguities in the values, raise AmbiguousTimeError.
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Parameters
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----------
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vals : ndarray[int64_t]
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tz : tzinfo or None
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ambiguous : str, bool, or arraylike
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When clocks moved backward due to DST, ambiguous times may arise.
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For example in Central European Time (UTC+01), when going from 03:00
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DST to 02:00 non-DST, 02:30:00 local time occurs both at 00:30:00 UTC
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and at 01:30:00 UTC. In such a situation, the `ambiguous` parameter
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dictates how ambiguous times should be handled.
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- 'infer' will attempt to infer fall dst-transition hours based on
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order
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- bool-ndarray where True signifies a DST time, False signifies a
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non-DST time (note that this flag is only applicable for ambiguous
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times, but the array must have the same length as vals)
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- bool if True, treat all vals as DST. If False, treat them as non-DST
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- 'NaT' will return NaT where there are ambiguous times
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nonexistent : {None, "NaT", "shift_forward", "shift_backward", "raise", \
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timedelta-like}
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How to handle non-existent times when converting wall times to UTC
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reso : NPY_DATETIMEUNIT, default NPY_FR_ns
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Returns
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-------
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localized : ndarray[int64_t]
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"""
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cdef:
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ndarray[uint8_t, cast=True] ambiguous_array
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Py_ssize_t i, idx, pos, n = vals.shape[0]
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Py_ssize_t delta_idx_offset, delta_idx, pos_left, pos_right
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int64_t v, left, right, val, new_local, remaining_mins
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int64_t first_delta, delta
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int64_t shift_delta = 0
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ndarray[int64_t] result_a, result_b, dst_hours
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int64_t[::1] result
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npy_datetimestruct dts
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bint infer_dst = False, is_dst = False, fill = False
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bint shift_forward = False, shift_backward = False
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bint fill_nonexist = False
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str stamp
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Localizer info = Localizer(tz, reso=reso)
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int64_t pph = periods_per_day(reso) // 24
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# Vectorized version of DstTzInfo.localize
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if info.use_utc:
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return vals.copy()
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result = cnp.PyArray_EMPTY(vals.ndim, vals.shape, cnp.NPY_INT64, 0)
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if info.use_tzlocal:
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for i in range(n):
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v = vals[i]
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if v == NPY_NAT:
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result[i] = NPY_NAT
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else:
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result[i] = v - _tz_localize_using_tzinfo_api(
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v, tz, to_utc=True, reso=reso
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)
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return result.base # to return underlying ndarray
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elif info.use_fixed:
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delta = info.delta
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for i in range(n):
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v = vals[i]
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if v == NPY_NAT:
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result[i] = NPY_NAT
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else:
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result[i] = v - delta
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return result.base # to return underlying ndarray
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# silence false-positive compiler warning
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ambiguous_array = np.empty(0, dtype=bool)
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if isinstance(ambiguous, str):
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if ambiguous == 'infer':
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infer_dst = True
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elif ambiguous == 'NaT':
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fill = True
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elif isinstance(ambiguous, bool):
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is_dst = True
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if ambiguous:
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ambiguous_array = np.ones(len(vals), dtype=bool)
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else:
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ambiguous_array = np.zeros(len(vals), dtype=bool)
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elif hasattr(ambiguous, '__iter__'):
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is_dst = True
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if len(ambiguous) != len(vals):
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raise ValueError("Length of ambiguous bool-array must be "
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"the same size as vals")
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ambiguous_array = np.asarray(ambiguous, dtype=bool)
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if nonexistent == 'NaT':
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fill_nonexist = True
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elif nonexistent == 'shift_forward':
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shift_forward = True
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elif nonexistent == 'shift_backward':
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shift_backward = True
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elif PyDelta_Check(nonexistent):
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from .timedeltas import delta_to_nanoseconds
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shift_delta = delta_to_nanoseconds(nonexistent, reso=reso)
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elif nonexistent not in ('raise', None):
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msg = ("nonexistent must be one of {'NaT', 'raise', 'shift_forward', "
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"shift_backwards} or a timedelta object")
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raise ValueError(msg)
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# Determine whether each date lies left of the DST transition (store in
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# result_a) or right of the DST transition (store in result_b)
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result_a, result_b =_get_utc_bounds(
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vals, info.tdata, info.ntrans, info.deltas, reso=reso
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)
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# silence false-positive compiler warning
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dst_hours = np.empty(0, dtype=np.int64)
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if infer_dst:
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dst_hours = _get_dst_hours(vals, result_a, result_b, reso=reso)
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# Pre-compute delta_idx_offset that will be used if we go down non-existent
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# paths.
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# Shift the delta_idx by if the UTC offset of
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# the target tz is greater than 0 and we're moving forward
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# or vice versa
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first_delta = info.deltas[0]
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if (shift_forward or shift_delta > 0) and first_delta > 0:
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delta_idx_offset = 1
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elif (shift_backward or shift_delta < 0) and first_delta < 0:
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delta_idx_offset = 1
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else:
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delta_idx_offset = 0
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for i in range(n):
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val = vals[i]
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left = result_a[i]
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right = result_b[i]
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if val == NPY_NAT:
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# TODO: test with non-nano
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result[i] = val
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elif left != NPY_NAT and right != NPY_NAT:
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if left == right:
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# TODO: test with non-nano
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result[i] = left
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else:
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if infer_dst and dst_hours[i] != NPY_NAT:
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# TODO: test with non-nano
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result[i] = dst_hours[i]
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elif is_dst:
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if ambiguous_array[i]:
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result[i] = left
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else:
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result[i] = right
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elif fill:
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# TODO: test with non-nano; parametrize test_dt_round_tz_ambiguous
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result[i] = NPY_NAT
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else:
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stamp = _render_tstamp(val, reso=reso)
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raise pytz.AmbiguousTimeError(
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f"Cannot infer dst time from {stamp}, try using the "
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"'ambiguous' argument"
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)
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elif left != NPY_NAT:
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result[i] = left
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elif right != NPY_NAT:
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# TODO: test with non-nano
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|
|
result[i] = right
|
||
|
|
else:
|
||
|
|
# Handle nonexistent times
|
||
|
|
if shift_forward or shift_backward or shift_delta != 0:
|
||
|
|
# Shift the nonexistent time to the closest existing time
|
||
|
|
remaining_mins = val % pph
|
||
|
|
if shift_delta != 0:
|
||
|
|
# Validate that we don't relocalize on another nonexistent
|
||
|
|
# time
|
||
|
|
if -1 < shift_delta + remaining_mins < pph:
|
||
|
|
raise ValueError(
|
||
|
|
"The provided timedelta will relocalize on a "
|
||
|
|
f"nonexistent time: {nonexistent}"
|
||
|
|
)
|
||
|
|
new_local = val + shift_delta
|
||
|
|
elif shift_forward:
|
||
|
|
new_local = val + (pph - remaining_mins)
|
||
|
|
else:
|
||
|
|
# Subtract 1 since the beginning hour is _inclusive_ of
|
||
|
|
# nonexistent times
|
||
|
|
new_local = val - remaining_mins - 1
|
||
|
|
|
||
|
|
delta_idx = bisect_right_i8(info.tdata, new_local, info.ntrans)
|
||
|
|
|
||
|
|
delta_idx = delta_idx - delta_idx_offset
|
||
|
|
result[i] = new_local - info.deltas[delta_idx]
|
||
|
|
elif fill_nonexist:
|
||
|
|
result[i] = NPY_NAT
|
||
|
|
else:
|
||
|
|
stamp = _render_tstamp(val, reso=reso)
|
||
|
|
raise pytz.NonExistentTimeError(stamp)
|
||
|
|
|
||
|
|
return result.base # .base to get underlying ndarray
|
||
|
|
|
||
|
|
|
||
|
|
cdef inline Py_ssize_t bisect_right_i8(int64_t *data,
|
||
|
|
int64_t val, Py_ssize_t n):
|
||
|
|
# Caller is responsible for checking n > 0
|
||
|
|
# This looks very similar to local_search_right in the ndarray.searchsorted
|
||
|
|
# implementation.
|
||
|
|
cdef:
|
||
|
|
Py_ssize_t pivot, left = 0, right = n
|
||
|
|
|
||
|
|
# edge cases
|
||
|
|
if val > data[n - 1]:
|
||
|
|
return n
|
||
|
|
|
||
|
|
# Caller is responsible for ensuring 'val >= data[0]'. This is
|
||
|
|
# ensured by the fact that 'data' comes from get_dst_info where data[0]
|
||
|
|
# is *always* NPY_NAT+1. If that ever changes, we will need to restore
|
||
|
|
# the following disabled check.
|
||
|
|
# if val < data[0]:
|
||
|
|
# return 0
|
||
|
|
|
||
|
|
while left < right:
|
||
|
|
pivot = left + (right - left) // 2
|
||
|
|
|
||
|
|
if data[pivot] <= val:
|
||
|
|
left = pivot + 1
|
||
|
|
else:
|
||
|
|
right = pivot
|
||
|
|
|
||
|
|
return left
|
||
|
|
|
||
|
|
|
||
|
|
cdef inline str _render_tstamp(int64_t val, NPY_DATETIMEUNIT reso):
|
||
|
|
""" Helper function to render exception messages"""
|
||
|
|
from pandas._libs.tslibs.timestamps import Timestamp
|
||
|
|
ts = Timestamp._from_value_and_reso(val, reso, None)
|
||
|
|
return str(ts)
|
||
|
|
|
||
|
|
|
||
|
|
cdef _get_utc_bounds(
|
||
|
|
ndarray vals,
|
||
|
|
int64_t* tdata,
|
||
|
|
Py_ssize_t ntrans,
|
||
|
|
const int64_t[::1] deltas,
|
||
|
|
NPY_DATETIMEUNIT reso,
|
||
|
|
):
|
||
|
|
# Determine whether each date lies left of the DST transition (store in
|
||
|
|
# result_a) or right of the DST transition (store in result_b)
|
||
|
|
|
||
|
|
cdef:
|
||
|
|
ndarray result_a, result_b
|
||
|
|
Py_ssize_t i, n = vals.size
|
||
|
|
int64_t val, v_left, v_right
|
||
|
|
Py_ssize_t isl, isr, pos_left, pos_right
|
||
|
|
int64_t ppd = periods_per_day(reso)
|
||
|
|
|
||
|
|
result_a = cnp.PyArray_EMPTY(vals.ndim, vals.shape, cnp.NPY_INT64, 0)
|
||
|
|
result_b = cnp.PyArray_EMPTY(vals.ndim, vals.shape, cnp.NPY_INT64, 0)
|
||
|
|
|
||
|
|
for i in range(n):
|
||
|
|
# This loops resembles the "Find the two best possibilities" block
|
||
|
|
# in pytz's DstTZInfo.localize method.
|
||
|
|
result_a[i] = NPY_NAT
|
||
|
|
result_b[i] = NPY_NAT
|
||
|
|
|
||
|
|
val = vals[i]
|
||
|
|
if val == NPY_NAT:
|
||
|
|
continue
|
||
|
|
|
||
|
|
# TODO: be careful of overflow in val-ppd
|
||
|
|
isl = bisect_right_i8(tdata, val - ppd, ntrans) - 1
|
||
|
|
if isl < 0:
|
||
|
|
isl = 0
|
||
|
|
|
||
|
|
v_left = val - deltas[isl]
|
||
|
|
pos_left = bisect_right_i8(tdata, v_left, ntrans) - 1
|
||
|
|
# timestamp falls to the left side of the DST transition
|
||
|
|
if v_left + deltas[pos_left] == val:
|
||
|
|
result_a[i] = v_left
|
||
|
|
|
||
|
|
# TODO: be careful of overflow in val+ppd
|
||
|
|
isr = bisect_right_i8(tdata, val + ppd, ntrans) - 1
|
||
|
|
if isr < 0:
|
||
|
|
isr = 0
|
||
|
|
|
||
|
|
v_right = val - deltas[isr]
|
||
|
|
pos_right = bisect_right_i8(tdata, v_right, ntrans) - 1
|
||
|
|
# timestamp falls to the right side of the DST transition
|
||
|
|
if v_right + deltas[pos_right] == val:
|
||
|
|
result_b[i] = v_right
|
||
|
|
|
||
|
|
return result_a, result_b
|
||
|
|
|
||
|
|
|
||
|
|
@cython.boundscheck(False)
|
||
|
|
cdef ndarray[int64_t] _get_dst_hours(
|
||
|
|
# vals, reso only needed here to potential render an exception message
|
||
|
|
const int64_t[:] vals,
|
||
|
|
ndarray[int64_t] result_a,
|
||
|
|
ndarray[int64_t] result_b,
|
||
|
|
NPY_DATETIMEUNIT reso,
|
||
|
|
):
|
||
|
|
cdef:
|
||
|
|
Py_ssize_t i, n = vals.shape[0]
|
||
|
|
ndarray[uint8_t, cast=True] mismatch
|
||
|
|
ndarray[int64_t] delta, dst_hours
|
||
|
|
ndarray[intp_t] switch_idxs, trans_idx, grp, a_idx, b_idx, one_diff
|
||
|
|
list trans_grp
|
||
|
|
intp_t switch_idx
|
||
|
|
int64_t left, right
|
||
|
|
|
||
|
|
dst_hours = cnp.PyArray_EMPTY(result_a.ndim, result_a.shape, cnp.NPY_INT64, 0)
|
||
|
|
dst_hours[:] = NPY_NAT
|
||
|
|
|
||
|
|
mismatch = cnp.PyArray_ZEROS(result_a.ndim, result_a.shape, cnp.NPY_BOOL, 0)
|
||
|
|
|
||
|
|
for i in range(n):
|
||
|
|
left = result_a[i]
|
||
|
|
right = result_b[i]
|
||
|
|
|
||
|
|
# Get the ambiguous hours (given the above, these are the hours
|
||
|
|
# where result_a != result_b and neither of them are NAT)
|
||
|
|
if left != right and left != NPY_NAT and right != NPY_NAT:
|
||
|
|
mismatch[i] = 1
|
||
|
|
|
||
|
|
trans_idx = mismatch.nonzero()[0]
|
||
|
|
|
||
|
|
if trans_idx.size == 1:
|
||
|
|
# see test_tz_localize_to_utc_ambiguous_infer
|
||
|
|
stamp = _render_tstamp(vals[trans_idx[0]], reso=reso)
|
||
|
|
raise pytz.AmbiguousTimeError(
|
||
|
|
f"Cannot infer dst time from {stamp} as there "
|
||
|
|
"are no repeated times"
|
||
|
|
)
|
||
|
|
|
||
|
|
# Split the array into contiguous chunks (where the difference between
|
||
|
|
# indices is 1). These are effectively dst transitions in different
|
||
|
|
# years which is useful for checking that there is not an ambiguous
|
||
|
|
# transition in an individual year.
|
||
|
|
if trans_idx.size > 0:
|
||
|
|
one_diff = np.where(np.diff(trans_idx) != 1)[0] + 1
|
||
|
|
trans_grp = np.array_split(trans_idx, one_diff)
|
||
|
|
|
||
|
|
# Iterate through each day, if there are no hours where the
|
||
|
|
# delta is negative (indicates a repeat of hour) the switch
|
||
|
|
# cannot be inferred
|
||
|
|
for grp in trans_grp:
|
||
|
|
|
||
|
|
delta = np.diff(result_a[grp])
|
||
|
|
if grp.size == 1 or np.all(delta > 0):
|
||
|
|
# see test_tz_localize_to_utc_ambiguous_infer
|
||
|
|
stamp = _render_tstamp(vals[grp[0]], reso=reso)
|
||
|
|
raise pytz.AmbiguousTimeError(stamp)
|
||
|
|
|
||
|
|
# Find the index for the switch and pull from a for dst and b
|
||
|
|
# for standard
|
||
|
|
switch_idxs = (delta <= 0).nonzero()[0]
|
||
|
|
if switch_idxs.size > 1:
|
||
|
|
# see test_tz_localize_to_utc_ambiguous_infer
|
||
|
|
raise pytz.AmbiguousTimeError(
|
||
|
|
f"There are {switch_idxs.size} dst switches when "
|
||
|
|
"there should only be 1."
|
||
|
|
)
|
||
|
|
|
||
|
|
switch_idx = switch_idxs[0] + 1
|
||
|
|
# Pull the only index and adjust
|
||
|
|
a_idx = grp[:switch_idx]
|
||
|
|
b_idx = grp[switch_idx:]
|
||
|
|
dst_hours[grp] = np.hstack((result_a[a_idx], result_b[b_idx]))
|
||
|
|
|
||
|
|
return dst_hours
|
||
|
|
|
||
|
|
|
||
|
|
# ----------------------------------------------------------------------
|
||
|
|
# Timezone Conversion
|
||
|
|
|
||
|
|
cpdef int64_t tz_convert_from_utc_single(
|
||
|
|
int64_t utc_val, tzinfo tz, NPY_DATETIMEUNIT reso=NPY_DATETIMEUNIT.NPY_FR_ns
|
||
|
|
) except? -1:
|
||
|
|
"""
|
||
|
|
Convert the val (in i8) from UTC to tz
|
||
|
|
|
||
|
|
This is a single value version of tz_convert_from_utc.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
utc_val : int64
|
||
|
|
tz : tzinfo
|
||
|
|
reso : NPY_DATETIMEUNIT, default NPY_FR_ns
|
||
|
|
|
||
|
|
Returns
|
||
|
|
-------
|
||
|
|
converted: int64
|
||
|
|
"""
|
||
|
|
cdef:
|
||
|
|
Localizer info = Localizer(tz, reso=reso)
|
||
|
|
Py_ssize_t pos
|
||
|
|
|
||
|
|
# Note: caller is responsible for ensuring utc_val != NPY_NAT
|
||
|
|
return info.utc_val_to_local_val(utc_val, &pos)
|
||
|
|
|
||
|
|
|
||
|
|
# OSError may be thrown by tzlocal on windows at or close to 1970-01-01
|
||
|
|
# see https://github.com/pandas-dev/pandas/pull/37591#issuecomment-720628241
|
||
|
|
cdef int64_t _tz_localize_using_tzinfo_api(
|
||
|
|
int64_t val,
|
||
|
|
tzinfo tz,
|
||
|
|
bint to_utc=True,
|
||
|
|
NPY_DATETIMEUNIT reso=NPY_DATETIMEUNIT.NPY_FR_ns,
|
||
|
|
bint* fold=NULL,
|
||
|
|
) except? -1:
|
||
|
|
"""
|
||
|
|
Convert the i8 representation of a datetime from a general-case timezone to
|
||
|
|
UTC, or vice-versa using the datetime/tzinfo API.
|
||
|
|
|
||
|
|
Private, not intended for use outside of tslibs.tzconversion.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
val : int64_t
|
||
|
|
tz : tzinfo
|
||
|
|
to_utc : bint
|
||
|
|
True if converting _to_ UTC, False if going the other direction.
|
||
|
|
reso : NPY_DATETIMEUNIT
|
||
|
|
fold : bint*, default NULL
|
||
|
|
pointer to fold: whether datetime ends up in a fold or not
|
||
|
|
after adjustment.
|
||
|
|
Only passed with to_utc=False.
|
||
|
|
|
||
|
|
Returns
|
||
|
|
-------
|
||
|
|
delta : int64_t
|
||
|
|
Value to add when converting from utc, subtract when converting to utc.
|
||
|
|
|
||
|
|
Notes
|
||
|
|
-----
|
||
|
|
Sets fold by pointer
|
||
|
|
"""
|
||
|
|
cdef:
|
||
|
|
npy_datetimestruct dts
|
||
|
|
datetime dt
|
||
|
|
int64_t delta
|
||
|
|
timedelta td
|
||
|
|
int64_t pps = periods_per_second(reso)
|
||
|
|
|
||
|
|
pandas_datetime_to_datetimestruct(val, reso, &dts)
|
||
|
|
|
||
|
|
# datetime_new is cython-optimized constructor
|
||
|
|
if not to_utc:
|
||
|
|
# tz.utcoffset only makes sense if datetime
|
||
|
|
# is _wall time_, so if val is a UTC timestamp convert to wall time
|
||
|
|
dt = _astimezone(dts, tz)
|
||
|
|
|
||
|
|
if fold is not NULL:
|
||
|
|
# NB: fold is only passed with to_utc=False
|
||
|
|
fold[0] = dt.fold
|
||
|
|
else:
|
||
|
|
dt = datetime_new(dts.year, dts.month, dts.day, dts.hour,
|
||
|
|
dts.min, dts.sec, dts.us, None)
|
||
|
|
|
||
|
|
td = tz.utcoffset(dt)
|
||
|
|
delta = int(td.total_seconds() * pps)
|
||
|
|
return delta
|
||
|
|
|
||
|
|
|
||
|
|
cdef datetime _astimezone(npy_datetimestruct dts, tzinfo tz):
|
||
|
|
"""
|
||
|
|
Optimized equivalent to:
|
||
|
|
|
||
|
|
dt = datetime(dts.year, dts.month, dts.day, dts.hour,
|
||
|
|
dts.min, dts.sec, dts.us, utc_pytz)
|
||
|
|
dt = dt.astimezone(tz)
|
||
|
|
|
||
|
|
Derived from the datetime.astimezone implementation at
|
||
|
|
https://github.com/python/cpython/blob/main/Modules/_datetimemodule.c#L6187
|
||
|
|
|
||
|
|
NB: we are assuming tz is not None.
|
||
|
|
"""
|
||
|
|
cdef:
|
||
|
|
datetime result
|
||
|
|
|
||
|
|
result = datetime_new(dts.year, dts.month, dts.day, dts.hour,
|
||
|
|
dts.min, dts.sec, dts.us, tz)
|
||
|
|
return tz.fromutc(result)
|
||
|
|
|
||
|
|
|
||
|
|
# NB: relies on dateutil internals, subject to change.
|
||
|
|
@cython.boundscheck(False)
|
||
|
|
@cython.wraparound(False)
|
||
|
|
cdef bint _infer_dateutil_fold(
|
||
|
|
int64_t value,
|
||
|
|
const int64_t[::1] trans,
|
||
|
|
const int64_t[::1] deltas,
|
||
|
|
Py_ssize_t pos,
|
||
|
|
):
|
||
|
|
"""
|
||
|
|
Infer _TSObject fold property from value by assuming 0 and then setting
|
||
|
|
to 1 if necessary.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
value : int64_t
|
||
|
|
trans : ndarray[int64_t]
|
||
|
|
ndarray of offset transition points in nanoseconds since epoch.
|
||
|
|
deltas : int64_t[:]
|
||
|
|
array of offsets corresponding to transition points in trans.
|
||
|
|
pos : Py_ssize_t
|
||
|
|
Position of the last transition point before taking fold into account.
|
||
|
|
|
||
|
|
Returns
|
||
|
|
-------
|
||
|
|
bint
|
||
|
|
Due to daylight saving time, one wall clock time can occur twice
|
||
|
|
when shifting from summer to winter time; fold describes whether the
|
||
|
|
datetime-like corresponds to the first (0) or the second time (1)
|
||
|
|
the wall clock hits the ambiguous time
|
||
|
|
|
||
|
|
References
|
||
|
|
----------
|
||
|
|
.. [1] "PEP 495 - Local Time Disambiguation"
|
||
|
|
https://www.python.org/dev/peps/pep-0495/#the-fold-attribute
|
||
|
|
"""
|
||
|
|
cdef:
|
||
|
|
bint fold = 0
|
||
|
|
int64_t fold_delta
|
||
|
|
|
||
|
|
if pos > 0:
|
||
|
|
fold_delta = deltas[pos - 1] - deltas[pos]
|
||
|
|
if value - fold_delta < trans[pos]:
|
||
|
|
fold = 1
|
||
|
|
|
||
|
|
return fold
|