Mocking out objects and methods#

Mocking is the process of replacing objects used in your code with ones that make testing easier, but only while the tests are running.

This may mean replacing resources or dependencies, such as database connections or file paths, with ones that are isolated for testing. It may also mean replacing chunks of complex functionality that aren’t the subject of the test with mock objects that allow you to check that the mocked out functionality is being used as expected.

What to mock with#

Python has a standard mock implementation in the form of unittest.mock which is also available as a rolling backport so that the latest features and bugfixes can be used in any version of Python.

For convenience, testfixtures provides a facade over both of these in the form of testfixtures.mock. The contents are identical and preference is given to the rolling backport if it is present. The facade also contains any bugfixes that are critical to the operation of functionality provided by testfixtures.

Testfixtures also provides specialised mocks for dealing with dates and times and subprocesses.

How to mock#

Testfixtures provides Replace, Replacer and the replace() decorator to mock out objects. These work in a similar way to unittest.mock.patch(), and have been around longer. They still provide a little more flexibility than patch(), so use whichever feels best in your codebase.

Methods of replacement#

When using the tools provided by Testfixtures, there are three different methods of mocking out functionality that can be used to replace functions, classes or even individual methods on a class. Consider the following module:

We want to mock out the y method of the X class, with, for example, the following function:

def mock_y(self):
     return 'mock y'

The context manager#

For replacement of a single thing, it’s easiest to use the Replace context manager:

from testfixtures import Replace

def test_function():
    with Replace('testfixtures.tests.sample1.X.y', mock_y):
        print(X().y())

For the duration of the with block, the replacement is used:

>>> test_function()
mock y

For multiple replacements, the Replacer context manager can be used instead:

from testfixtures.mock import Mock
from testfixtures import Replacer

def test_function():
    with Replacer() as replace:
        mock_y = replace('testfixtures.tests.sample1.X.y', Mock())
        mock_y.return_value = 'mock y'
        print(X().y())

For the duration of the with block, the replacement is used:

>>> test_function()
mock y

The decorator#

If you want to replace different things in different test functions, you may find the decorator suits your needs better:

from testfixtures import replace

@replace('testfixtures.tests.sample1.X.y', mock_y)
def test_function():
    print(X().y())

When using the decorator, the replacement is used for the duration of the decorated callable’s execution:

>>> test_function()
mock y

If you need to manipulate or inspect the object that’s used as a replacement, you can add an extra parameter to your function. The decorator will see this and pass the replacement in it’s place:

from testfixtures.mock import Mock, call
from testfixtures import compare, replace

@replace('testfixtures.tests.sample1.X.y', Mock())
def test_function(mocked_y):
    mocked_y.return_value = 'mock y'
    print(X().y())
    compare(mocked_y.mock_calls, expected=[call()])

The above still results in the same output:

>>> test_function()
mock y

Note

This method is not compatible with pytest’s fixture discovery stuff. Instead, put a fixture such as the following in your conftest.py:

from testfixtures import Replace
import pytest

@pytest.fixture()
def mocked_y():
    m = Mock()
    with Replace('testfixtures.tests.sample1.X.y', m):
        yield m

Manual usage#

If you want to replace something for the duration of a doctest or you want to replace something for every test in a TestCase, then you can use the Replacer manually.

The instantiation and replacement are done in the set-up step of the TestCase or equivalent:

>>> from testfixtures import Replacer
>>> replacer = Replacer()
>>> replacer.replace('testfixtures.tests.sample1.X.y', mock_y)

The replacement then stays in place until removed:

>>> X().y()
'mock y'

Then, in the tear-down step of the TestCase or equivalent, the replacement is removed:

>>> replacer.restore()
>>> X().y()
'original y'

The restore() method can also be added as an addCleanup() if that is easier or more compact in your test suite.

Replacing more than one thing#

Both the Replacer and the replace() decorator can be used to replace more than one thing at a time. For the former, this is fairly obvious:

def test_function():
    with Replacer() as replace:
        y = replace('testfixtures.tests.sample1.X.y', Mock())
        y.return_value = 'mock y'
        aMethod = replace('testfixtures.tests.sample1.X.aMethod', Mock())
        aMethod.return_value = 'mock method'
        x = X()
        print(x.y(), x.aMethod())

For the decorator, it’s less obvious but still pretty easy:

from testfixtures import replace

@replace('testfixtures.tests.sample1.X.y', Mock())
@replace('testfixtures.tests.sample1.X.aMethod', Mock())
def test_function(aMethod, y):
    print(aMethod, y)
    aMethod().return_value = 'mock method'
    y().return_value = 'mock y'
    x = X()
    print(aMethod, y)
    print(x.y(), x.aMethod())

You’ll notice that you can still get access to the replacements, even though there are several of them.

Replacing things that may not be there#

The following code shows a situation where hpy may or may not be present depending on whether the guppy package is installed or not.

To test the behaviour of the code that uses hpy in both of these cases, regardless of whether or not the guppy package is actually installed, we need to be able to mock out both hpy and the guppy global. This is done by doing non-strict replacement, as shown in the following TestCase:

from testfixtures.tests.sample2 import dump
from testfixtures import replace
from testfixtures.mock import Mock, call

class Tests(unittest.TestCase):

    @replace('testfixtures.tests.sample2.guppy', True)
    @replace('testfixtures.tests.sample2.hpy', Mock(), strict=False)
    def test_method(self, hpy):

        dump('somepath')

        compare([
                 call(),
                 call().heap(),
                 call().heap().stat.dump('somepath')
               ], hpy.mock_calls)

    @replace('testfixtures.tests.sample2.guppy', False)
    @replace('testfixtures.tests.sample2.hpy', Mock(), strict=False)
    def test_method_no_heapy(self,hpy):

        dump('somepath')

        compare(hpy.mock_calls,[])

Non-strict replacement using the strict keyword parameter is supported both when calling a Replacer or using the replace() method.

Replacing items in dictionaries and lists#

Replace, Replacer and the replace() decorator can be used to replace items in dictionaries and lists.

For example, suppose you have a data structure like the following:

You can mock out the value associated with key and the second element in the complex_key list as follows:

from pprint import pprint
from testfixtures import Replacer
from testfixtures.tests.sample1 import some_dict

def test_function():
    with Replacer() as replace:
        replace('testfixtures.tests.sample1.some_dict.key', 'foo')
        replace('testfixtures.tests.sample1.some_dict.complex_key.1', 42)
        pprint(some_dict)

While the replacement is in effect, the new items are in place:

>>> test_function()
{'complex_key': [1, 42, 3], 'key': 'foo'}

When it is no longer in effect, the originals are returned:

>>> pprint(some_dict)
{'complex_key': [1, 2, 3], 'key': 'value'}

Removing attributes and dictionary items#

Replace, Replacer and the replace() decorator can be used to remove attributes from objects and remove items from dictionaries.

For example, suppose you have a data structure like the following:

If you want to remove the key for the duration of a test, you can do so as follows:

from testfixtures import Replace, not_there
from testfixtures.tests.sample1 import some_dict

def test_function():
    with Replace('testfixtures.tests.sample1.some_dict.key', not_there):
        pprint(some_dict)

While the replacement is in effect, key is gone:

>>> test_function()
{'complex_key': [1, 2, 3]}

When it is no longer in effect, key is returned:

>>> pprint(some_dict)
{'complex_key': [1, 2, 3], 'key': 'value'}

If you want the whole some_dict dictionary to be removed for the duration of a test, you would do so as follows:

from testfixtures import Replace, not_there
from testfixtures.tests import sample1

def test_function():
    with Replace('testfixtures.tests.sample1.some_dict', not_there):
        print(hasattr(sample1, 'some_dict'))

While the replacement is in effect, key is gone:

>>> test_function()
False

When it is no longer in effect, key is returned:

>>> pprint(sample1.some_dict)
{'complex_key': [1, 2, 3], 'key': 'value'}

Gotchas#

  • Make sure you replace the object where it’s used and not where it’s defined. For example, with the following code from the testfixtures.tests.sample1 package:

    from time import time
    
    
    def str_time():
        return str(time())
    

    You might be tempted to mock things as follows:

    >>> replace = Replacer()
    >>> replace('time.time', Mock())
    <...>
    

    But this won’t work:

    >>> from testfixtures.tests.sample1 import str_time
    >>> type(float(str_time()))
    <... 'float'>
    

    You need to replace time() where it’s used, not where it’s defined:

    >>> replace('testfixtures.tests.sample1.time', Mock())
    <...>
    >>> str_time()
    "<...Mock...>"
    

    A corollary of this is that you need to replace all occurrences of an original to safely be able to test. This can be tricky when an original is imported into many modules that may be used by a particular test.

  • You can’t replace whole top level modules, and nor should you want to! The reason being that everything up to the last dot in the replacement target specifies where the replacement will take place, and the part after the last dot is used as the name of the thing to be replaced:

    >>> Replacer().replace('sys', Mock())
    Traceback (most recent call last):
     ...
    ValueError: target must contain at least one dot!