On Thu, Jan 8, 2015 at 7:04 AM, Skip Montanaro <s...@pobox.com> wrote:
> I'm real naive about this stuff, but I have always wondered why
> matplotlib didn't just use datetime objects, or at least use
> timezone-aware datetime objects as an "interchange" format to get the
> timezone stuff right.
>
Time zone handling is a pain in the %}€*
And the definitions keep changing.
So you need a complex DB and library that needs frequent updating.
This is why neither the standard library nor numpy support time zone
handling out of the box.
But the datetime object does support a hook to add timezone info.
The numpy datetime64 may implementation _may_ provide a similar hook in
the future.
There is the pytz package, which MPL could choose to depend on.
But even that is a bit ugly--e.g. from the pytz docs:
"""Unfortunately using the tzinfo argument of the standard datetime
constructors ‘’does not work’’ with pytz for many timezones."""
So my suggestion is that MPL punts, and stick with leaving time zone
handling up to the user, I.e only use datetimes that are timezone "naive".
What this means is that MPL would always a assume all datetimes interacting
with each other are in the same time zone (including same DST status).
Anyway, I'm being a bit lazy here, so I may be wrong, but I think the issue
at hand is that MPL currently uses a float array to store and manipulate
datetimes, and the thought is that it may be better to use numpy datetime64
arrays -- that would give us more consistent precision, and less code to
convert to/from various datetime formats.
I'm a bit on the fence about whether it's time to do it, as datetime64 does
have issues with the locale timezone, but as any implementation would want
to work with not-just-the-latest numpy anyway, it may make sense to start
now.
-Chris
--
Christopher Barker, Ph.D.
Oceanographer
Emergency Response Division
NOAA/NOS/OR&R (206) 526-6959 voice
7600 Sand Point Way NE (206) 526-6329 fax
Seattle, WA 98115 (206) 526-6317 main reception
chris.bar...@noaa.gov
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