451 lines
14 KiB
Cython
451 lines
14 KiB
Cython
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from datetime import (
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timedelta,
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timezone,
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)
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from pandas.compat._optional import import_optional_dependency
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try:
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# py39+
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import zoneinfo
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from zoneinfo import ZoneInfo
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except ImportError:
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zoneinfo = None
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ZoneInfo = None
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from cpython.datetime cimport (
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datetime,
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timedelta,
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tzinfo,
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)
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# dateutil compat
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from dateutil.tz import (
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gettz as dateutil_gettz,
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tzfile as _dateutil_tzfile,
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tzlocal as _dateutil_tzlocal,
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tzutc as _dateutil_tzutc,
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)
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import pytz
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from pytz.tzinfo import BaseTzInfo as _pytz_BaseTzInfo
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UTC = pytz.utc
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import numpy as np
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cimport numpy as cnp
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from numpy cimport int64_t
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cnp.import_array()
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# ----------------------------------------------------------------------
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from pandas._libs.tslibs.util cimport (
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get_nat,
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is_integer_object,
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)
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cdef int64_t NPY_NAT = get_nat()
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cdef tzinfo utc_stdlib = timezone.utc
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cdef tzinfo utc_pytz = UTC
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cdef tzinfo utc_dateutil_str = dateutil_gettz("UTC") # NB: *not* the same as tzutc()
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cdef tzinfo utc_zoneinfo = None
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# ----------------------------------------------------------------------
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cdef inline bint is_utc_zoneinfo(tzinfo tz):
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# Workaround for cases with missing tzdata
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# https://github.com/pandas-dev/pandas/pull/46425#discussion_r830633025
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if tz is None or zoneinfo is None:
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return False
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global utc_zoneinfo
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if utc_zoneinfo is None:
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try:
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utc_zoneinfo = ZoneInfo("UTC")
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except zoneinfo.ZoneInfoNotFoundError:
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return False
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# Warn if tzdata is too old, even if there is a system tzdata to alert
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# users about the mismatch between local/system tzdata
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import_optional_dependency("tzdata", errors="warn", min_version="2022.1")
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return tz is utc_zoneinfo
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cpdef inline bint is_utc(tzinfo tz):
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return (
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tz is utc_pytz
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or tz is utc_stdlib
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or isinstance(tz, _dateutil_tzutc)
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or tz is utc_dateutil_str
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or is_utc_zoneinfo(tz)
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)
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cdef inline bint is_zoneinfo(tzinfo tz):
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if ZoneInfo is None:
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return False
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return isinstance(tz, ZoneInfo)
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cdef inline bint is_tzlocal(tzinfo tz):
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return isinstance(tz, _dateutil_tzlocal)
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cdef inline bint treat_tz_as_pytz(tzinfo tz):
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return (hasattr(tz, '_utc_transition_times') and
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hasattr(tz, '_transition_info'))
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cdef inline bint treat_tz_as_dateutil(tzinfo tz):
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return hasattr(tz, '_trans_list') and hasattr(tz, '_trans_idx')
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# Returns str or tzinfo object
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cpdef inline object get_timezone(tzinfo tz):
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"""
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We need to do several things here:
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1) Distinguish between pytz and dateutil timezones
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2) Not be over-specific (e.g. US/Eastern with/without DST is same *zone*
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but a different tz object)
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3) Provide something to serialize when we're storing a datetime object
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in pytables.
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We return a string prefaced with dateutil if it's a dateutil tz, else just
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the tz name. It needs to be a string so that we can serialize it with
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UJSON/pytables. maybe_get_tz (below) is the inverse of this process.
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"""
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if tz is None:
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raise TypeError("tz argument cannot be None")
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if is_utc(tz):
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return tz
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else:
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if treat_tz_as_dateutil(tz):
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if '.tar.gz' in tz._filename:
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raise ValueError(
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'Bad tz filename. Dateutil on python 3 on windows has a '
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'bug which causes tzfile._filename to be the same for all '
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'timezone files. Please construct dateutil timezones '
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'implicitly by passing a string like "dateutil/Europe'
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'/London" when you construct your pandas objects instead '
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'of passing a timezone object. See '
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'https://github.com/pandas-dev/pandas/pull/7362')
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return 'dateutil/' + tz._filename
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else:
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# tz is a pytz timezone or unknown.
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try:
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zone = tz.zone
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if zone is None:
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return tz
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return zone
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except AttributeError:
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return tz
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cpdef inline tzinfo maybe_get_tz(object tz):
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"""
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(Maybe) Construct a timezone object from a string. If tz is a string, use
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it to construct a timezone object. Otherwise, just return tz.
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"""
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if isinstance(tz, str):
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if tz == 'tzlocal()':
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tz = _dateutil_tzlocal()
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elif tz.startswith('dateutil/'):
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zone = tz[9:]
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tz = dateutil_gettz(zone)
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# On Python 3 on Windows, the filename is not always set correctly.
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if isinstance(tz, _dateutil_tzfile) and '.tar.gz' in tz._filename:
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tz._filename = zone
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elif tz[0] in {'-', '+'}:
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hours = int(tz[0:3])
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minutes = int(tz[0] + tz[4:6])
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tz = timezone(timedelta(hours=hours, minutes=minutes))
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elif tz[0:4] in {'UTC-', 'UTC+'}:
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hours = int(tz[3:6])
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minutes = int(tz[3] + tz[7:9])
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tz = timezone(timedelta(hours=hours, minutes=minutes))
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else:
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tz = pytz.timezone(tz)
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elif is_integer_object(tz):
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tz = pytz.FixedOffset(tz / 60)
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elif isinstance(tz, tzinfo):
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pass
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elif tz is None:
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pass
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else:
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raise TypeError(type(tz))
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return tz
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def _p_tz_cache_key(tz: tzinfo):
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"""
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Python interface for cache function to facilitate testing.
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"""
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return tz_cache_key(tz)
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# Timezone data caches, key is the pytz string or dateutil file name.
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dst_cache = {}
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cdef inline object tz_cache_key(tzinfo tz):
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"""
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Return the key in the cache for the timezone info object or None
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if unknown.
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The key is currently the tz string for pytz timezones, the filename for
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dateutil timezones.
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Notes
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-----
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This cannot just be the hash of a timezone object. Unfortunately, the
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hashes of two dateutil tz objects which represent the same timezone are
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not equal (even though the tz objects will compare equal and represent
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the same tz file). Also, pytz objects are not always hashable so we use
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str(tz) instead.
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"""
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if isinstance(tz, _pytz_BaseTzInfo):
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return tz.zone
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elif isinstance(tz, _dateutil_tzfile):
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if '.tar.gz' in tz._filename:
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raise ValueError('Bad tz filename. Dateutil on python 3 on '
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'windows has a bug which causes tzfile._filename '
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'to be the same for all timezone files. Please '
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'construct dateutil timezones implicitly by '
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'passing a string like "dateutil/Europe/London" '
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'when you construct your pandas objects instead '
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'of passing a timezone object. See '
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'https://github.com/pandas-dev/pandas/pull/7362')
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return 'dateutil' + tz._filename
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else:
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return None
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# ----------------------------------------------------------------------
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# UTC Offsets
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cdef timedelta get_utcoffset(tzinfo tz, datetime obj):
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try:
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return tz._utcoffset
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except AttributeError:
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return tz.utcoffset(obj)
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cpdef inline bint is_fixed_offset(tzinfo tz):
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if treat_tz_as_dateutil(tz):
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if len(tz._trans_idx) == 0 and len(tz._trans_list) == 0:
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return 1
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else:
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return 0
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elif treat_tz_as_pytz(tz):
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if (len(tz._transition_info) == 0
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and len(tz._utc_transition_times) == 0):
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return 1
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else:
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return 0
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elif is_zoneinfo(tz):
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return 0
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# This also implicitly accepts datetime.timezone objects which are
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# considered fixed
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return 1
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cdef object _get_utc_trans_times_from_dateutil_tz(tzinfo tz):
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"""
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Transition times in dateutil timezones are stored in local non-dst
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time. This code converts them to UTC. It's the reverse of the code
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in dateutil.tz.tzfile.__init__.
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"""
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new_trans = list(tz._trans_list)
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last_std_offset = 0
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for i, (trans, tti) in enumerate(zip(tz._trans_list, tz._trans_idx)):
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if not tti.isdst:
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last_std_offset = tti.offset
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new_trans[i] = trans - last_std_offset
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return new_trans
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cdef int64_t[::1] unbox_utcoffsets(object transinfo):
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cdef:
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Py_ssize_t i, sz
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int64_t[::1] arr
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sz = len(transinfo)
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arr = np.empty(sz, dtype='i8')
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for i in range(sz):
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arr[i] = int(transinfo[i][0].total_seconds()) * 1_000_000_000
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return arr
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# ----------------------------------------------------------------------
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# Daylight Savings
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cdef object get_dst_info(tzinfo tz):
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"""
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Returns
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-------
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ndarray[int64_t]
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Nanosecond UTC times of DST transitions.
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ndarray[int64_t]
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Nanosecond UTC offsets corresponding to DST transitions.
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str
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Describing the type of tzinfo object.
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"""
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cache_key = tz_cache_key(tz)
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if cache_key is None:
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# e.g. pytz.FixedOffset, matplotlib.dates._UTC,
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# psycopg2.tz.FixedOffsetTimezone
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num = int(get_utcoffset(tz, None).total_seconds()) * 1_000_000_000
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# If we have e.g. ZoneInfo here, the get_utcoffset call will return None,
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# so the total_seconds() call will raise AttributeError.
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return (np.array([NPY_NAT + 1], dtype=np.int64),
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np.array([num], dtype=np.int64),
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"unknown")
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if cache_key not in dst_cache:
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if treat_tz_as_pytz(tz):
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trans = np.array(tz._utc_transition_times, dtype='M8[ns]')
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trans = trans.view('i8')
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if tz._utc_transition_times[0].year == 1:
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trans[0] = NPY_NAT + 1
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deltas = unbox_utcoffsets(tz._transition_info)
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typ = 'pytz'
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elif treat_tz_as_dateutil(tz):
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if len(tz._trans_list):
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# get utc trans times
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trans_list = _get_utc_trans_times_from_dateutil_tz(tz)
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trans = np.hstack([
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np.array([0], dtype='M8[s]'), # place holder for 1st item
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np.array(trans_list, dtype='M8[s]')]).astype(
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'M8[ns]') # all trans listed
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trans = trans.view('i8')
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trans[0] = NPY_NAT + 1
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# deltas
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deltas = np.array([v.offset for v in (
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tz._ttinfo_before,) + tz._trans_idx], dtype='i8')
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deltas *= 1_000_000_000
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typ = 'dateutil'
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elif is_fixed_offset(tz):
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trans = np.array([NPY_NAT + 1], dtype=np.int64)
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deltas = np.array([tz._ttinfo_std.offset],
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dtype='i8') * 1_000_000_000
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typ = 'fixed'
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else:
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# 2018-07-12 this is not reached in the tests, and this case
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# is not handled in any of the functions that call
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# get_dst_info. If this case _were_ hit the calling
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# functions would then hit an IndexError because they assume
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# `deltas` is non-empty.
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# (under the just-deleted code that returned empty arrays)
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raise AssertionError("dateutil tzinfo is not a FixedOffset "
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"and has an empty `_trans_list`.", tz)
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else:
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# static tzinfo, we can get here with pytz.StaticTZInfo
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# which are not caught by treat_tz_as_pytz
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trans = np.array([NPY_NAT + 1], dtype=np.int64)
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num = int(get_utcoffset(tz, None).total_seconds()) * 1_000_000_000
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deltas = np.array([num], dtype=np.int64)
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typ = "static"
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dst_cache[cache_key] = (trans, deltas, typ)
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return dst_cache[cache_key]
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def infer_tzinfo(datetime start, datetime end):
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if start is not None and end is not None:
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tz = start.tzinfo
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if not tz_compare(tz, end.tzinfo):
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raise AssertionError(f'Inputs must both have the same timezone, '
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f'{tz} != {end.tzinfo}')
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elif start is not None:
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tz = start.tzinfo
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elif end is not None:
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tz = end.tzinfo
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else:
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tz = None
|
||
|
|
return tz
|
||
|
|
|
||
|
|
|
||
|
|
cpdef bint tz_compare(tzinfo start, tzinfo end):
|
||
|
|
"""
|
||
|
|
Compare string representations of timezones
|
||
|
|
|
||
|
|
The same timezone can be represented as different instances of
|
||
|
|
timezones. For example
|
||
|
|
`<DstTzInfo 'Europe/Paris' LMT+0:09:00 STD>` and
|
||
|
|
`<DstTzInfo 'Europe/Paris' CET+1:00:00 STD>` are essentially same
|
||
|
|
timezones but aren't evaluated such, but the string representation
|
||
|
|
for both of these is `'Europe/Paris'`.
|
||
|
|
|
||
|
|
This exists only to add a notion of equality to pytz-style zones
|
||
|
|
that is compatible with the notion of equality expected of tzinfo
|
||
|
|
subclasses.
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
start : tzinfo
|
||
|
|
end : tzinfo
|
||
|
|
|
||
|
|
Returns:
|
||
|
|
-------
|
||
|
|
bool
|
||
|
|
"""
|
||
|
|
# GH 18523
|
||
|
|
if is_utc(start):
|
||
|
|
# GH#38851 consider pytz/dateutil/stdlib UTCs as equivalent
|
||
|
|
return is_utc(end)
|
||
|
|
elif is_utc(end):
|
||
|
|
# Ensure we don't treat tzlocal as equal to UTC when running in UTC
|
||
|
|
return False
|
||
|
|
elif start is None or end is None:
|
||
|
|
return start is None and end is None
|
||
|
|
return get_timezone(start) == get_timezone(end)
|
||
|
|
|
||
|
|
|
||
|
|
def tz_standardize(tz: tzinfo) -> tzinfo:
|
||
|
|
"""
|
||
|
|
If the passed tz is a pytz timezone object, "normalize" it to the a
|
||
|
|
consistent version
|
||
|
|
|
||
|
|
Parameters
|
||
|
|
----------
|
||
|
|
tz : tzinfo
|
||
|
|
|
||
|
|
Returns
|
||
|
|
-------
|
||
|
|
tzinfo
|
||
|
|
|
||
|
|
Examples
|
||
|
|
--------
|
||
|
|
>>> from datetime import datetime
|
||
|
|
>>> from pytz import timezone
|
||
|
|
>>> tz = timezone('US/Pacific').normalize(
|
||
|
|
... datetime(2014, 1, 1, tzinfo=pytz.utc)
|
||
|
|
... ).tzinfo
|
||
|
|
>>> tz
|
||
|
|
<DstTzInfo 'US/Pacific' PST-1 day, 16:00:00 STD>
|
||
|
|
>>> tz_standardize(tz)
|
||
|
|
<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>
|
||
|
|
|
||
|
|
>>> tz = timezone('US/Pacific')
|
||
|
|
>>> tz
|
||
|
|
<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>
|
||
|
|
>>> tz_standardize(tz)
|
||
|
|
<DstTzInfo 'US/Pacific' LMT-1 day, 16:07:00 STD>
|
||
|
|
"""
|
||
|
|
if treat_tz_as_pytz(tz):
|
||
|
|
return pytz.timezone(str(tz))
|
||
|
|
return tz
|