Python Mock Cookbook

The python mock library is one of the awesome things about working in Python. No matter what code you're unit testing, it's possible to mock out various pieces with very little test code. That being said, it's sometimes difficult to figure out the exact syntax for your situation. I attribute this to the nature of how you apply the mocks. Sometimes it feel like you're shooting in the dark.

The official documentation is comprehensive, but I find it somewhat hard to locate what you're looking for. I recommend their examples doc.

This post is a write-up of my own personal usage.

Big Upfront Caveat

The biggest mistake people make is mocking something out in the wrong place. You always need to mock the thing where it's imported TO, not where it's imported FROM. Translation: if you're importing from foo import bar into a package bat.baz, you need to mock it as @mock.patch(''). This can be confusing if you think you should be mocking it where it's defined, not where it's used.


For all these sections, assume we're in a package called myapp. The code you're testing is in a module at and the definition of the objects that you're mocking is imported there from myapp.lib.

Want to see the full code? I have an repository on git with these examples called python-mocking.


The easiest things to mock out are constants.

@mock.patch('', 7)
def test_constant(self):


For functions, you will commonly need to specify a return value, check if they were called, and with what values.

def test_function(self, mock_get_first_name):
    mock_get_first_name.return_value = 'Bat'


Mocking a method on a class is just like mocking a function, you just reference it through the class name.

def test_method(self, mock_get_make):
    mock_get_make.return_value = 'Ford'


These are just special methods on a class with the @property decorator. Now we're starting to get tricky.

@mock.patch('', new_callable=mock.PropertyMock)
def test_property(self, mock_wheels):
    mock_wheels.return_value = 2

Entire classes

What if you want to swap out an entire class implementation? No problem! The key is that the return_value should be a new instance of the class.

def test_class(self, mock_car):

    class NewCar(object):

        def get_make(self):
            return 'Audi'

        def wheels(self):
            return 6

    mock_car.return_value = NewCar()

Class Methods

What about a @classmethod on a class? It's the same as a method.

def test_classmethod(self, mock_for_make):
    new_car = Car()
    new_car.make = 'Chevy'
    mock_for_make.return_value = new_car

Static Methods

Static methods are the same as class methods.

def test_classmethod(self, mock_get_roll_call):
    mock_get_roll_call.return_value = [Car('Ford'), ]

Decorators & Context Managers

Decorators are a tough one. They are defined at import time, and are thus diffucult to re-define as a mock. Your best bet is to create a function for the body of the decorator, and mock that.

Context managers are more do-able, but tricky.

def test_context_manager(self, mock_open_car):

    def enter_car(car):

    mock_open_car.return_value.__enter__ = enter_car


Bonus - Mocking All Tests in a Suite

San you have a certain mock that you want to apply to all tests in a TestCase class. You have two options. You can apply the patch in the setUp and un-apply the patch in tearDown, or you can over-ride run.

def run(self, result=None):
    with mock.patch('') as foo: = foo
        super(MyTestCase, self).run(result)

Alternatively, you can mock out something in setUp:

def setUp(self):
    patcher = mock.patch('')
    self.mock_foo = patcher.start()
    super(NWApiTestCase, self).setUp()

I'm currently working at NerdWallet, a startup in San Francisco trying to bring clarity to all of life's financial decisions. We're hiring like crazy. Hit me up on Twitter, I would love to talk.

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