quickstart.rst

Quickstart

This is a lightning introduction to the most important features of Hypothesis; enough to get you started writing tests. The :doc:`tutorial <tutorial/index>` introduces these features (and more) in greater detail.

Install Hypothesis

pip install hypothesis

Write your first test

Create a new file called example.py, containing a simple test:

# contents of example.py
from hypothesis import given, strategies as st

@given(st.integers())
def test_integers(n):
    print(f"called with {n}")
    assert isinstance(n, int)

test_integers()

|@given| is the standard entrypoint to Hypothesis. It takes a strategy, which describes the type of inputs you want the decorated function to accept. When we call test_integers, Hypothesis will generate random integers (because we used the |st.integers| strategy) and pass them as n. Let's see that in action now by running python example.py:

called with 0
called with -18588
called with -672780074
called with 32616
...

We just called test_integers(), without passing a value for n, because Hypothesis generates random values of n for us.

Note

By default, Hypothesis generates 100 random inputs. You can control this with the |max_examples| setting.

Running in a test suite

A Hypothesis test is still a regular python function, which means pytest or unittest will pick it up and run it in all the normal ways.

# contents of example.py
from hypothesis import given, strategies as st

@given(st.integers(0, 200))
def test_integers(n):
    assert n < 50

This test will clearly fail, which can be confirmed by running pytest example.py:

$ pytest example.py

    ...

    @given(st.integers())
    def test_integers(n):
>       assert n < 50
E       assert 50 < 50
E       Failing test case: test_integers(
E           n=50,
E       )

Arguments to |@given|

You can pass multiple arguments to |@given|:

@given(st.integers(), st.text())
def test_integers(n, s):
    assert isinstance(n, int)
    assert isinstance(s, str)

Or use keyword arguments:

@given(n=st.integers(), s=st.text())
def test_integers(n, s):
    assert isinstance(n, int)
    assert isinstance(s, str)

Note

See |@given| for details about how |@given| handles different types of arguments.

Filtering inside a test

Sometimes, you need to remove invalid cases from your test. The best way to do this is with |.filter|:

@given(st.integers().filter(lambda n: n % 2 == 0))
def test_integers(n):
    assert n % 2 == 0

For more complicated conditions, you can use |assume|, which tells Hypothesis to discard any test case with a false-y argument:

@given(st.integers(), st.integers())
def test_integers(n1, n2):
    assume(n1 != n2)
    # n1 and n2 are guaranteed to be different here

Note

You can learn more about |.filter| and |assume| in the :doc:`/tutorial/adapting-strategies` tutorial page.

Dependent generation

You may want an input to depend on the value of another input. For instance, you might want to generate two integers n1 and n2 where n1 <= n2.

You can do this using the |st.composite| strategy. |st.composite| lets you define a new strategy which is itself built by drawing values from other strategies, using the automatically-passed draw function.

@st.composite
def ordered_pairs(draw):
    n1 = draw(st.integers())
    n2 = draw(st.integers(min_value=n1))
    return (n1, n2)

@given(ordered_pairs())
def test_pairs_are_ordered(pair):
    n1, n2 = pair
    assert n1 <= n2

In more complex cases, you might need to interleave generation and test code. In this case, use |st.data|.

@given(st.data(), st.text(min_size=1))
def test_string_characters_are_substrings(data, string):
    assert isinstance(string, str)
    index = data.draw(st.integers(0, len(string) - 1))
    assert string[index] in string

Combining Hypothesis with pytest

Hypothesis works with pytest features, like |pytest.mark.parametrize|:

import pytest

from hypothesis import given, strategies as st

@pytest.mark.parametrize("operation", [reversed, sorted])
@given(st.lists(st.integers()))
def test_list_operation_preserves_length(operation, lst):
    assert len(lst) == len(list(operation(lst)))

Hypothesis also works with pytest fixtures:

import pytest

@pytest.fixture(scope="session")
def shared_mapping():
    return {n: 0 for n in range(101)}

@given(st.integers(0, 100))
def test_shared_mapping_keys(shared_mapping, n):
    assert n in shared_mapping