This is the repository for the online module Bots as Digital Infrapuncture, commissioned by the Utrecht University
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#!/usr/bin/env python
'''
$Id: tzfile.py,v 1.8 2004/06/03 00:15:24 zenzen Exp $
'''
from datetime import datetime
from struct import unpack, calcsize
from pytz.tzinfo import StaticTzInfo, DstTzInfo, memorized_ttinfo
from pytz.tzinfo import memorized_datetime, memorized_timedelta
def _byte_string(s):
"""Cast a string or byte string to an ASCII byte string."""
return s.encode('ASCII')
_NULL = _byte_string('\0')
def _std_string(s):
"""Cast a string or byte string to an ASCII string."""
return str(s.decode('ASCII'))
def build_tzinfo(zone, fp):
head_fmt = '>4s c 15x 6l'
head_size = calcsize(head_fmt)
(magic, format, ttisgmtcnt, ttisstdcnt, leapcnt, timecnt,
typecnt, charcnt) = unpack(head_fmt, fp.read(head_size))
# Make sure it is a tzfile(5) file
assert magic == _byte_string('TZif'), 'Got magic %s' % repr(magic)
# Read out the transition times, localtime indices and ttinfo structures.
data_fmt = '>%(timecnt)dl %(timecnt)dB %(ttinfo)s %(charcnt)ds' % dict(
timecnt=timecnt, ttinfo='lBB' * typecnt, charcnt=charcnt)
data_size = calcsize(data_fmt)
data = unpack(data_fmt, fp.read(data_size))
# make sure we unpacked the right number of values
assert len(data) == 2 * timecnt + 3 * typecnt + 1
transitions = [memorized_datetime(trans)
for trans in data[:timecnt]]
lindexes = list(data[timecnt:2 * timecnt])
ttinfo_raw = data[2 * timecnt:-1]
tznames_raw = data[-1]
del data
# Process ttinfo into separate structs
ttinfo = []
tznames = {}
i = 0
while i < len(ttinfo_raw):
# have we looked up this timezone name yet?
tzname_offset = ttinfo_raw[i + 2]
if tzname_offset not in tznames:
nul = tznames_raw.find(_NULL, tzname_offset)
if nul < 0:
nul = len(tznames_raw)
tznames[tzname_offset] = _std_string(
tznames_raw[tzname_offset:nul])
ttinfo.append((ttinfo_raw[i],
bool(ttinfo_raw[i + 1]),
tznames[tzname_offset]))
i += 3
# Now build the timezone object
if len(ttinfo) == 1 or len(transitions) == 0:
ttinfo[0][0], ttinfo[0][2]
cls = type(zone, (StaticTzInfo,), dict(
zone=zone,
_utcoffset=memorized_timedelta(ttinfo[0][0]),
_tzname=ttinfo[0][2]))
else:
# Early dates use the first standard time ttinfo
i = 0
while ttinfo[i][1]:
i += 1
if ttinfo[i] == ttinfo[lindexes[0]]:
transitions[0] = datetime.min
else:
transitions.insert(0, datetime.min)
lindexes.insert(0, i)
# calculate transition info
transition_info = []
for i in range(len(transitions)):
inf = ttinfo[lindexes[i]]
utcoffset = inf[0]
if not inf[1]:
dst = 0
else:
for j in range(i - 1, -1, -1):
prev_inf = ttinfo[lindexes[j]]
if not prev_inf[1]:
break
dst = inf[0] - prev_inf[0] # dst offset
# Bad dst? Look further. DST > 24 hours happens when
# a timzone has moved across the international dateline.
if dst <= 0 or dst > 3600 * 3:
for j in range(i + 1, len(transitions)):
stdinf = ttinfo[lindexes[j]]
if not stdinf[1]:
dst = inf[0] - stdinf[0]
if dst > 0:
break # Found a useful std time.
tzname = inf[2]
# Round utcoffset and dst to the nearest minute or the
# datetime library will complain. Conversions to these timezones
# might be up to plus or minus 30 seconds out, but it is
# the best we can do.
utcoffset = int((utcoffset + 30) // 60) * 60
dst = int((dst + 30) // 60) * 60
transition_info.append(memorized_ttinfo(utcoffset, dst, tzname))
cls = type(zone, (DstTzInfo,), dict(
zone=zone,
_utc_transition_times=transitions,
_transition_info=transition_info))
return cls()
if __name__ == '__main__':
import os.path
from pprint import pprint
base = os.path.join(os.path.dirname(__file__), 'zoneinfo')
tz = build_tzinfo('Australia/Melbourne',
open(os.path.join(base, 'Australia', 'Melbourne'), 'rb'))
tz = build_tzinfo('US/Eastern',
open(os.path.join(base, 'US', 'Eastern'), 'rb'))
pprint(tz._utc_transition_times)