Three Pytest Tips

I happened to use pytest a lot in the last few months, so I decided to write down a couple tips which could be useful to those who are already a bit familiar with the framework. For those who are not, pytest documentation is a good place where to start.

Parametrized dictionary

Use case

Run the same test with different input parameters and expected values

Benefit

First of all, define a dictionary where the key is the name of your test case and the value is a tuple with inputs parameters and expected values.

params = {
    'empty_line': ('', {}),
    'get_ok': ('GET 200', {'request': 'GET', 'status': '200'}),
    'get_not_found': ('GET 404', {'request': 'GET', 'status': '404'}),
}

Then decorate your test as the following:

@pytest.mark.parametrize('line,expected', list(params.values()), ids=list(params.keys()))
def test_decode(self, line, expected):
    assert decode(line) == expected

The first parameter of the decorator is a string containing the names of the parameters you want to parametrize your test on separated by a comma (in this case line and expected). You can then use those names as arguments for your test function.

The second parameter of the decorator is the list of values to be assigned to the parameters; in our case is always going to be the list of values of the dictionary.

Finally, the third parameter is the list of test names that will be used for each generated test case; in our case this corresponds with the keys of the dictionary.

This is the output when you run pytest -v with the above code:

pytest -v tests/dict_test.py
========================================== test session starts ==============================================
platform linux  Python 3.6.3, pytest-3.3.1, py-1.5.2, pluggy-0.6.0 /home/antonio/virtualenv_run/bin/python3.6
cachedir: .cache
rootdir: /home/antonio, inifile:
collected 3 items

tests/dict_test.py::test_decode[empty_line] PASSED                                                     [ 33%]
tests/dict_test.py::test_decode[get_ok] PASSED                                                         [ 66%]
tests/dict_test.py::test_decode[get_not_found] FAILED                                                  [100%]

================================================ FAILURES ===================================================
_________________________________________ test_decode[get_not_found] ________________________________________
line = 'GET 404', expected = {'request': 'GET', 'status': '404'}

...

For more information on pytest parametrization, have a look at the documentation here.

Note: dict.values() and dict.keys() should have the same order starting from Python 3.6. Before that it was implementation dependent, but it worked for me since Python2.6. I never tried with PyPy, though.

Context manager/mock yield

Use case

Execute some setup and teardown logic for a fixture (not a test)

Benefit

Pytest provides a feature to execute some setup and teardown logic when defining a fixture, like in the example below:

def session():
    # setup
    client = client.open("myapp.com/api", 872)
	# provide the fixture value
    yield session
    # teardown
    session.close()

This feature is incredibly useful when combined with context managers, since they are going to automatically execute the teardown code when they get out of scope; e.g. opening of a file:

def text():
    with open("text.txt") as f:
        yield f

This feature makes possible to create pytest fixtures where we can mock something out only until the fixture stays in scope, avoiding a pretty common source of test pollution:

def consumer():
    with mock.patch('logging.getLogger'):
        yield Consumer('my_stream')

If you want to know more about this feature, the documentation has a nice writeup here

Composing fixtures

Use case

Define a fixture based on another fixture and intercat with both of them in the test

Benefit

Pytest fixtures can be combined at any level, making very easy to build chains of mocked components. This is easier showed than said, so let’s just have a look at an example:

@pytest.fixture
def stream():
    return mock.Mock(spec=Stream)

@pytest.fixture
def output():
    return open('test.txt', 'w')

@pytest.fixture
def tailer(self, stream, output):
    with mock.patch('logging.getLogger', autospec=True):
        yield Tailer(stream, output, mock.sentinel.lines)

@mock.patch('consumer.read_lines')
def test_tailer(mock_read, tailer, stream):
    stream.fetch.return_value = "test\n"
    tailer.run()
    mock_read.assert_called_once_with(stream, mock.sentinel.lines)
    with open('test.txt', 'r') as f:
        assert f.read() == "test"

As you can see, the stream fixture is used as parameter to create a the tailer fixture. Then, both of them are used in the test case to make the desired assertions.

This one is probably useful only for integration tests or tests covering lots of moving parts, but it makes reading these complex tests much easier, since it makes much more explicit the relation between all the components involed in the test.


I kept this list short in the hope that people could at least remember one of the tips; but I might write more tips in another post in case I find something particularly useful. Stay tuned!

Antonio Uccio Verardi

Antonio Uccio Verardi

from yelp import software_engineer

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