Hypothesis is an advanced testing library for Python. It lets you write tests which are parametrized by a source of examples, and then generates simple and comprehensible examples that make your tests fail. This lets you find more bugs in your code with less work.

e.g.

@given(st.lists(
  st.floats(allow_nan=False, allow_infinity=False), min_size=1))
def test_mean(xs):
    assert min(xs) <= mean(xs) <= max(xs)

Falsifying example: test_mean(
  xs=[1.7976321109618856e+308, 6.102390043022755e+303]
)

Hypothesis is extremely practical and advances the state of the art of unit testing by some way. It's easy to use, stable, and powerful. If you're not using Hypothesis to test your project then you're missing out.

If you'd like to help support Hypothesis development, there are three main ways:

1. Hire my services to help you out, either with custom development or training.
2. Support me on salt to try to help me build up a salary for pure work on Hypothesis.
3. Or if you just want to say thanks, you can buy me books from this wishlist.

To learn more about how to use Hypothesis, extensive documentation and examples of usage are available at readthedocs.

If you want to talk to people about using Hypothesis, we have both an IRC channel and a mailing list.

If you want to receive occasional updates about Hypothesis, including useful tips and tricks, there's a TinyLetter mailing list to sign up for them.

If you want to contribute to Hypothesis, instructions are here.

If you want to hear from people who are already using Hypothesis, some of them have written about it.

If you want to create a downstream package of Hypothesis, please read these guidelines for packagers