Pendulum

Python datetimes made easy.

Supports Python 2.7 and 3.4+.

.. code-block:: python

import pendulum

now_in_paris = pendulum.now('Europe/Paris')
now_in_paris
'2016-07-04T00:49:58.502116+02:00'

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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)

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.datetime(2013, 3, 31, 2, 30, tz='Europe/Paris')
'2013-03-31T03:30:00+02:00' # 2:30 does not exist (Skipped time)

Proper handling of dst transitions

just_before = pendulum.datetime(2013, 3, 31, 1, 59, 59, 999999, tz='Europe/Paris')
'2013-03-31T01:59:59.999999+01:00'
just_before.add(microseconds=1)
'2013-03-31T03:00:00+02:00'

Why Pendulum?

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 DateTime 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.

Why not Arrow?

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:

.. code-block:: python

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]>

arrow.get('20160413')
# <Arrow [1970-08-22T08:06:53+00:00]>

pendulum.parse('20160413')
# <Pendulum [2016-04-13T00:00:00+00:00]>

arrow.get('2016-W07-5')
# <Arrow [2016-01-01T00:00:00+00:00]>

pendulum.parse('2016-W07-5')
# <Pendulum [2016-02-19T00:00:00+00:00]>

# 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.datetime(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.

Limitations

Even though the DateTime class is a subclass of datetime there are some rare cases where
it can't replace the native class directly. Here is a list (non-exhaustive) of the reported cases with
a possible solution, if any:

  • sqlite3 will use the type() function to determine the type of the object by default. To work around it you can register a new adapter:

.. code-block:: python

from pendulum import DateTime
from sqlite3 import register_adapter

register_adapter(DateTime, lambda val: val.isoformat(' '))
  • mysqlclient (former MySQLdb) and PyMySQL will use the type() function to determine the type of the object by default. To work around it you can register a new adapter:

.. code-block:: python

import MySQLdb.converters
import pymysql.converters

from pendulum import DateTime

MySQLdb.converters.conversions[DateTime] = MySQLdb.converters.DateTime2literal
pymysql.converters.conversions[DateTime] = pymysql.converters.escape_datetime
  • django will use the isoformat() method to store datetimes in the database. However since pendulum is always timezone aware the offset information will always be returned by isoformat() raising an error, at least for MySQL databases. To work around it you can either create your own DateTimeField or use the previous workaround for MySQLdb:

.. code-block:: python

from django.db.models import DateTimeField as BaseDateTimeField
from pendulum import DateTime


class DateTimeField(BaseDateTimeField):

    def value_to_string(self, obj):
        val = self.value_from_object(obj)

        if isinstance(value, DateTime):
            return value.to_datetime_string()

        return '' if val is None else val.isoformat()

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