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The property-based testing library for Python

Project description

Hypothesis

Hypothesis is the property-based testing library for Python. With Hypothesis, you write tests which should pass for all inputs in whatever range you describe, and let Hypothesis randomly choose which of those inputs to check - including edge cases you might not have thought about. For example:

from hypothesis import given, strategies as st


@given(st.lists(st.integers()))
def test_matches_builtin(ls):
    assert sorted(ls) == my_sort(ls)

This randomized testing can catch bugs and edge cases that you didn't think of and wouldn't have found. In addition, when Hypothesis does find a bug, it doesn't just report any failing example — it reports the simplest possible one. This makes property-based tests a powerful tool for debugging, as well as testing.

For instance,

def my_sort(ls):
    return sorted(set(ls))

fails with the simplest possible failing example:

Falsifying example: test_matches_builtin(ls=[0, 0])

Installation

To install Hypothesis:

pip install hypothesis

There are also optional extras available.

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BLAKE2b-256 e875d97f346b73acd3935a60c444f9643c22578f720227a488b23823ee46156a

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SHA256 859d74d2ad2025dd39f362c57dd115d6f643240f5b1fc5334db8bfecd740a297
MD5 8295d177895d08f9858fef496a9a2b09
BLAKE2b-256 9a8b9be617a0abe009b6653920e251fe65c186b2056c49f3b380eecc7ad3075b

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SHA256 da683d7aa3bc95164c06138895322e8b90e61e6198097d6497e62644ebbec90d
MD5 39b8604c465e3c63a054460f915bb807
BLAKE2b-256 676ece331a3e02797dba2888f56de85a8223e4568ad415f8e9b0cf65b1c1a5dd

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