Additional packages

Hypothesis has a zero dependency policy for the core library. For things which need a dependency to work, these are farmed off into additional packages on pypi. These end up putting any additional things you need to import (if there are any) under the hypothesis.extra namespace.

Generally these will be for providing new sources of data for Hypothesis, or for better integrating it into an existing testing framework.


As might be expected, this provides a strategy which generates instances of datetime. It depends on pytz.

hypothesis-datetime lives in the hypothesis.extra.datetime package:

>>> from hypothesis.extra.datetime import datetimes
>>> datetimes().example()
datetime.datetime(1705, 1, 20, 0, 32, 0, 973139, tzinfo=<DstTzInfo 'Israel...
>>> datetimes().example()
datetime.datetime(7274, 6, 9, 23, 0, 31, 75498, tzinfo=<DstTzInfo 'America...

As you can see, it produces years from quite a wide range. If you want to narrow it down you can ask for a more specific range of years:

>>> datetimes(min_year=2001, max_year=2010).example()
datetime.datetime(2010, 7, 7, 0, 15, 0, 614034, tzinfo=<DstTzInfo 'Pacif...
>>> datetimes(min_year=2001, max_year=2010).example()
datetime.datetime(2006, 9, 26, 22, 0, 0, 220365, tzinfo=<DstTzInfo 'Asia...

You can also specify timezones:

>>> import pytz
>>> pytz.all_timezones[:3]
['Africa/Abidjan', 'Africa/Accra', 'Africa/Addis_Ababa']
>>> datetimes(timezones=pytz.all_timezones[:3]).example()
datetime.datetime(6257, 8, 21, 13, 6, 24, 8751, tzinfo=<DstTzInfo 'Africa/Accra' GMT0:00:00 STD>)
>>> datetimes(timezones=pytz.all_timezones[:3]).example()
datetime.datetime(7851, 2, 3, 0, 0, 0, 767400, tzinfo=<DstTzInfo 'Africa/Accra' GMT0:00:00 STD>)
>>> datetimes(timezones=pytz.all_timezones[:3]).example()
datetime.datetime(8262, 6, 22, 16, 0, 0, 154235, tzinfo=<DstTzInfo 'Africa/Abidjan' GMT0:00:00 STD>)

If the set of timezones is empty you will get a naive datetime:

>>> datetimes(timezones=[]).example()
datetime.datetime(918, 11, 26, 2, 0, 35, 916439)

You can also explicitly get a mix of naive and non-naive datetimes if you want:

>>> datetimes(allow_naive=True).example()
datetime.datetime(2433, 3, 20, 0, 0, 44, 460383, tzinfo=<DstTzInfo 'Asia/Hovd' HOVT+7:00:00 STD>)
>>> datetimes(allow_naive=True).example()
datetime.datetime(7003, 1, 22, 0, 0, 52, 401259)


Fake-factory is another Python library for data generation. hypothesis-fakefactory is a package which lets you use fake-factory generators to parametrize tests.

It currently only supports the 0.4.2 release of fake-factory, due to some issues with the 0.5.0 release. These are known to be fixed in master but there hasn’t been a release containing the fixes yet.

hypothesis.extra.fakefactory defines a function fake_factory which returns a strategy for producing text data from any FakeFactory provider.

So for example the following will parametrize a test by an email address:

>>> fake_factory('email').example()

>>> fake_factory('name').example()
'Zbyněk Černý CSc.'

You can explicitly specify the locale (otherwise it uses any of the available locales), either as a single locale or as several:

>>> fake_factory('name', locale='en_GB').example()
'Antione Gerlach'
>>> fake_factory('name', locales=['en_GB', 'cs_CZ']).example()
'Miloš Šťastný'
>>> fake_factory('name', locales=['en_GB', 'cs_CZ']).example()
'Harm Sanford'

If you want to your own FakeFactory providers you can do that too, passing them in as a providers argument:

>>> from faker.providers import BaseProvider
>>> class KittenProvider(BaseProvider):
...     def meows(self):
...             return 'meow %d' % (self.random_number(digits=10),)
>>> fake_factory('meows', providers=[KittenProvider]).example()
'meow 9139348419'

Generally you probably shouldn’t do this unless you’re reusing a provider you already have - Hypothesis’s facilities for strategy generation are much more powerful and easier to use. Consider using something like BasicStrategy instead if you want to write a strategy from scratch. This is only here to provide easy reuse of things you already have.


hypothesis-pytest is the world’s most basic pytest plugin. Install it to get slightly better integrated example reporting when using @given and running under pytest. That’s basically all it does.


hypothesis-django adds support for testing your Django models with Hypothesis.

It’s large enough that it is documented elsewhere.