Python datetimes made easy.
Supports Python 2.7+ and 3.2+.
>>> import pendulum >>> now_in_paris = pendulum.now('Europe/Paris') >>> now_in_paris '2016-07-04T00:49:58.502116+02:00' # Seamless timezone switching >>> now_in_paris.in_timezone('UTC') '2016-07-03T22:49:58.502116+00:00' >>> tomorrow = pendulum.now().add(days=1) >>> last_week = pendulum.now().subtract(weeks=1) >>> if pendulum.now().is_weekend(): ... print('Party!') 'Party!' >>> past = pendulum.now().subtract(minutes=2) >>> past.diff_for_humans() >>> '2 minutes ago' >>> delta = past - last_week >>> delta.hours 23 >>> delta.in_words(locale='en') '6 days 23 hours 58 minutes' # Proper handling of datetime normalization >>> pendulum.create(2013, 3, 31, 2, 30, 0, 0, 'Europe/Paris') '2013-03-31T03:30:00+02:00' # 2:30 does not exist (Skipped time) # Proper handling of dst transitions >>> just_before = pendulum.create(2013, 3, 31, 1, 59, 59, 999999, 'Europe/Paris') '2013-03-31T01:59:59.999999+01:00' >>> just_before.add(microseconds=1) '2013-03-31T03:00:00+02:00'
Native datetime instances are enough for basic cases but when you face more complex use-cases
they often show limitations and are not so intuitive to work with.
Pendulum provides a cleaner and more easy to use API while still relying on the standard library.
So it's still datetime but better.
Unlike other datetime libraries for Python, Pendulum is a drop-in replacement
for the standard datetime class (it inherits from it), so, basically, you can replace all your datetime
instances by Pendulum instances in you code (exceptions exist for libraries that check
the type of the objects by using the type function like sqlite3 or PyMySQL for instance).
It also removes the notion of naive datetimes: each Pendulum instance is timezone-aware
and by default in UTC for ease of use.
Pendulum also improves the standard timedelta class by providing more intuitive methods and properties.
Arrow is the most popular datetime library for Python right now, however its behavior
and API can be erratic and unpredictable. The get() method can receive pretty much anything
and it will try its best to return something while silently failing to handle some cases:
arrow.get('2016-1-17') # <Arrow [2016-01-01T00:00:00+00:00]> pendulum.parse('2016-1-17') # <Pendulum [2016-01-17T00:00:00+00:00]> # Parsing of a date with wrong day arrow.get('2015-06-31') # <Arrow [2015-06-01T00:00:00+00:00]> pendulum.parse('2016-06-31') # ValueError: day is out of range for month # fromtimestamp with timezone displays wrong offset arrow.Arrow.fromtimestamp(0, pytz.timezone('Europe/Paris')) # <Arrow [1970-01-01T01:00:00+00:09]> pendulum.from_timestamp(0, pytz.timezone('Europe/Paris')) # fromtimestamp() is also possible # <Pendulum [1970-01-01T01:00:00+01:00]> # Working with DST just_before = arrow.Arrow(2013, 3, 31, 1, 59, 59, 999999, 'Europe/Paris') just_after = just_before.replace(microseconds=1) '2013-03-31T02:00:00+02:00' # Should be 2013-03-31T03:00:00+02:00 (just_after.to('utc') - just_before.to('utc')).total_seconds() -3599.999999 # Should be 1e-06 just_before = pendulum.create(2013, 3, 31, 1, 59, 59, 999999, 'Europe/Paris') just_after = just_before.add(microseconds=1) '2013-03-31T03:00:00+02:00' (just_after.in_timezone('utc') - just_before.in_timezone('utc')).total_seconds() 1e-06
Those are a few examples showing that Arrow cannot always be trusted to have a consistent behavior with the data you are passing to it.
Contributions are welcome, especially with localization. Check the languages already supported, and if you want to add a new one, take the en file as a starting point and add tests accordingly.