On Wed, Sep 23, 2015 at 6:16 PM, Chris Angelico <[email protected]> wrote:
> A lot of the small numbers are going to be when different places > adopted standard time, and such. To get a better handle on what's > happening _now_, I added an option [1] to your stats function for a > starting year: > > >>> ZoneInfo.stats(start_year=1970) > Number of zones: 1790 = 46266 (gaps) + 46130 (folds) + 843 (zeros) > Min gap: 0:15:00 at 1985-12-31 18:30:13 in > right/Asia/Kathmandu > Max gap: 1 day, 0:00:00 at 2011-12-30 10:00:24 in > right/Pacific/Apia > Min fold: 0:30:00 at 2037-04-04 15:00:26 > in right/Australia/Lord_Howe > Max fold: 3:00:00 at 2012-02-21 17:00:24 > in right/Antarctica/Casey > >>> ZoneInfo.stats() > Number of zones: 1790 = 58914 (gaps) + 58777 (folds) + 1363 (zeros) > Min gap: 0:00:16 at 1935-01-01 03:40:52 in > posix/America/Paramaribo > Max gap: 1 day, 0:00:00 at 2011-12-30 10:00:24 in > right/Pacific/Apia > Min fold: 0:01:31 at 1932-01-01 03:58:29 in > posix/America/Barbados > Max fold: 10:00:00 at 1952-01-13 14:00:00 in > posix/Antarctica/DumontDUrville > It looks like you've got double counts because you included both "posix" and "right" tzfiles in the search. (I don't think the data that I actually read is different between the two sets.) > I'm not sure whether this actually helps anything or not, but hey, cool > stats :) > If we can make some simplified assumptions about transition locations and sizes, we can avoid a binary search over seconds to locate the transitions via POSIX localtime/mktime APIs. I am considering making the cut-off at 1970 and assume 1970 standard time for all times before that year. I think this is best we can do on Windows where (IIRC) mktime does not work for times before epoch. (What about localtime?) In any case, TZ data before 1970 is highly suspect so we will probably do our users a favor by assuming standard time and letting those with historical timeseries figure out the transitions by themselves.
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