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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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SHA256 40584eed6a57c402d8ab32ea5c1779bae6f7390ff33d073c876e09dc8af31941
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SHA256 72b9305414c20802540ec0cd798478c9e06c8a248ce32d7df04722b64d7150ad
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SHA256 ea85fd8ca7be7acbba36c63de7a1450e8e267a29ed3a117a037e638be244c5b6
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MD5 269e7227f031b37d2441f1d17aa77cf8
BLAKE2b-256 923d9e19b368974bfedccdba6916b92fca8446f02018e0954a6e8b756d5450c1

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SHA256 79b4aa87fbb2e5121a24333906b7b481ddefc0af9d3ccd28463f5504b8d586f2
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