Metadata-Version: 2.4
Name: hypothesis
Version: 6.151.10
Summary: The property-based testing library for Python
Author-email: "David R. MacIver and Zac Hatfield-Dodds" <david@drmaciver.com>
License-Expression: MPL-2.0
Project-URL: homepage, https://hypothesis.works
Project-URL: source, https://github.com/HypothesisWorks/hypothesis
Project-URL: changelog, https://hypothesis.readthedocs.io/en/latest/changelog.html
Project-URL: documentation, https://hypothesis.readthedocs.io
Project-URL: issues, https://github.com/HypothesisWorks/hypothesis/issues
Keywords: python,testing,fuzzing,property-based-testing
Classifier: Development Status :: 5 - Production/Stable
Classifier: Framework :: Hypothesis
Classifier: Framework :: Pytest
Classifier: Intended Audience :: Developers
Classifier: Operating System :: Unix
Classifier: Operating System :: POSIX
Classifier: Operating System :: Microsoft :: Windows
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Programming Language :: Python :: 3.14
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Classifier: Topic :: Education :: Testing
Classifier: Topic :: Software Development :: Testing
Classifier: Typing :: Typed
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License-File: LICENSE.txt
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Dynamic: license-file

# Hypothesis

* [Website](https://hypothesis.works/)
* [Documentation](https://hypothesis.readthedocs.io/en/latest/)
* [Source code](https://github.com/hypothesisWorks/hypothesis/)
* [Contributing](https://github.com/HypothesisWorks/hypothesis/blob/master/CONTRIBUTING.rst)
* [Community](https://hypothesis.readthedocs.io/en/latest/community.html)

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:

```python
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,

```python
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](https://hypothesis.readthedocs.io/en/latest/extras.html).
