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Comment by iknownothow | Hacker News Reader

I know some of the HN crowd are gonna wag their finger at me but the moment I have to deal with timestamps in Python, even for the most simplest of cases, I parachute in pandas. `pd.Timestamp` (and its friends like `pd.Timedelta`) in my opinion are the most powerful timestamp toolkit available anywhere.

To me it's very often easily worth the extra 50-150MB of install size that just works. I've used pandas for around 7 years now and it was inconsistent and buggy at the beginning. But these days, it's practically flawless. Also I'm aware that pd.Timestamp is built on top of many awesome libraries.

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Pendulum is quite good[0]. Relatively intuitive interface.

When I left Rails, this is one area I really missed.

Time.use_zone("Singapore") { (Time.zone.now - 3.days).beginning_of_week }

This readable line in datetime utils or even pendulum, is such a pain.

[0] https://github.com/sdispater/pendulum

How does the rails example work? It must be using a global/shared state?

Sorry I'm a bit confused by the question could you elaborate?

I've been using pendulum heavily in production for over a year now and it has made my life very much simpler. It's a great library.

Handling timestamps well was one of the motivations for building pandas in the first place (Wes McKinney started pandas while he was working at an investment management company).

I'm not a Pandas person - is it possible to install the Pandas timestamp functionality as a smaller library, or do you need to install the whole shebang?

I had investigated if this was possible to do but I couldn't find a way to do it myself. It's possible that pd.Timestamp might be intricately tied interally to vectorization optimizations using numpy or others. Therefore separating out just the timestamp stuff from pandas would be a lot of work.

Python is in many ways the anti-JavaScript when it comes to packaging. Where JavaScript will have a installable package that contains a single trivial function, Python packages will bundle hundreds of functions, all vaguely related to an area, with no easy way of just installing what you actually need.

My experience has been exactly the opposite, with two exceptions: pandas and numpy.

Generally every other library works in terms of standard python types where possible. Very few other places will you see things like a re-implementation of a time library.

with two exceptions

...and scipy and all the scikit libraries and whole bunch of others. 'Accidentally' pulling in hundreds of MBs of libraries you never use for a 100 line data processing script is par for the course in python land.

My experience is that Pendulum does a good job of handling date/time data as a drop-in replacement for the standard library classes.

> pd.Timestamp is built on top of many awesome libraries

... pytz for example ;-)

Yes, and? Doesn't mean it inherits all the usability flaws of pytz.

No, I think pandas actually abstracts away pytz's footguns, so that's a good thing.

As long as it hides the footguns, you are good to go. Pytz is not technically flawed.

Well, pytz actually is technically flawed at the moment because it cannot read TZif Version 2+ files, so it breaks for dates >2038 (and it would break if you tried to point it at system data generated with zic's "slim" mode), see this: https://github.com/stub42/pytz/issues/48

But you are right that pandas' use of pytz is benign and as far as I know doesn't suffer the same usability issues.

Django has similar functionality:

from django.utils import timezone

now = timezone.now()

later = timezone.now() + timezone.timedelta(minutes=1)

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