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Python Unit Test Patch Function - Avoid passing mocked function to test function

I am trying to mock a python function similar to below. I am not doing anything with the mocked function except for the fact that it is used to return the mocked data in the called function. Is it possible for me to avoid passing in the variable (sum, in this case) to the test function?
# test_calculator.py
from unittest import TestCase
from unittest.mock import patch
class TestCalculator(TestCase):
#patch('calculator.Calculator.sum', return_value=9)
def test_sum(self, sum):
self.assertEqual(sum(2,3), 9)

unittest.mock.patch can also be used as a context manager, if simply avoiding sum in the parameters is desired
class TestCalculator(TestCase):
def test_sum(self):
with patch('calculator.Calculator.sum', return_value=9) as sum:
self.assertEqual(sum(2, 3), 9)

Python: calling stop on mock patch class decorator

The Mock documentation describes a simple and elegant way of applying patches to all of the tests method inside a TestCase:
#patch('foo.bar')
#patch('foo.baz')
#patch('foo.quux')
#patch('foo.narf')
class FooTest(TestCase):
def test_foo(self, bar, baz, quux, narf):
""" foo """
self.assertTrue(False)
However, one issue I've encountered with this method is that if I'd like to call stop() on one of the patches inside one of the test methods, there doesn't appear to be anyway of getting a reference to the patcher object -- the only thing that is passed into the method is the mock objects, in this case bar, baz, quux, narf.
The only way I've found to solve this problem is to move to the pattern described in the Mock docs where the patchers are instantiated and started inside the setUp method of the TestCase and stopped inside the tearDown method. This fits my purpose, but adds a lot of extra boilerplate and isn't as elegant as the class decorator approach.
Is there another way to solve this problem?

1
Say you want to temporarily restore foo.narf in a method. foo.narf is, in the context of the decorated function, a MagicMock object. This object has a _mock_wraps attribute which will be invoked when the mock is called! So at the top of your module, _narf = foo.narf, and in your test case, foo.narf._mock_wraps = _narf.
The catch is that this will only pass through to the real function, not actually swap it back, which means that some test cases will fail (e.g. if they rely on the function object actually being "itself"). And if your mock has other attributes, that could interfere (I haven't tested much) because the passthrough call to _mock_wraps() comes at the bottom of a method that first considers the other properties of the mock.
2
The patch() decorator involves each patcher (separate copies per method) being added to a list called patchings which is a field of the method itself. I.e. you can access this list as self.test_foo.patchings, and go through to find the one you want.
However, start() and stop() are not actually called when you use patch() as a decorator, and the behavior gets tricky once you start reaching in and changing it. So I wrote this context manager.
class unpatch:
def __init__(self, name, method):
compare = patch(name)
self.patcher = next((
p for p in method.patchings
if p.target == compare.getter()
and p.attribute == compare.attribute
), None)
if self.patcher is None:
raise ValueError(name)
def __enter__(self):
self.patcher.__exit__()
def __exit__(self, *exc_info):
self.patcher.__enter__()
Inside your test case, you use it like this:
with unpatch('foo.narf', self.test_foo):
foo.narf()
Disclaimer: this is hacks.

#Patch decorator is not compatible with pytest fixture

I have encountered something mysterious, when using patch decorator from mock package integrated with pytest fixture.
I have two modules:
-----test folder
-------func.py
-------test_test.py
in func.py:
def a():
return 1
def b():
return a()
in test_test.py:
import pytest
from func import a,b
from mock import patch,Mock
#pytest.fixture(scope="module")
def brands():
return 1
mock_b=Mock()
#patch('test_test.b',mock_b)
def test_compute_scores(brands):
a()
It seems that patch decorate is not compatible with pytest fixture. Does anyone have a insight on that? Thanks

When using pytest fixture with mock.patch, test parameter order is crucial.
If you place a fixture parameter before a mocked one:
from unittest import mock
#mock.patch('my.module.my.class')
def test_my_code(my_fixture, mocked_class):
then the mock object will be in my_fixture and mocked_class will be search as a fixture:
fixture 'mocked_class' not found
But, if you reverse the order, placing the fixture parameter at the end:
from unittest import mock
#mock.patch('my.module.my.class')
def test_my_code(mocked_class, my_fixture):
then all will be fine.

As of Python3.3, the mock module has been pulled into the unittest library. There is also a backport (for previous versions of Python) available as the standalone library mock.
Combining these 2 libraries within the same test-suite yields the above-mentioned error:
E fixture 'fixture_name' not found
Within your test-suite's virtual environment, run pip uninstall mock, and make sure you aren't using the backported library alongside the core unittest library. When you re-run your tests after uninstalling, you would see ImportErrors if this were the case.
Replace all instances of this import with from unittest.mock import <stuff>.

Hopefully this answer on an old question will help someone.
First off, the question doesn't include the error, so we don't really know what's up. But I'll try to provide something that helped me.
If you want a test decorated with a patched object, then in order for it to work with pytest you could just do this:
#mock.patch('mocked.module')
def test_me(*args):
mocked_module = args[0]
Or for multiple patches:
#mock.patch('mocked.module1')
#mock.patch('mocked.module')
def test_me(*args):
mocked_module1, mocked_module2 = args
pytest is looking for the names of the fixtures to look up in the test function/method. Providing the *args argument gives us a good workaround the lookup phase. So, to include a fixture with patches, you could do this:
# from question
#pytest.fixture(scope="module")
def brands():
return 1
#mock.patch('mocked.module1')
def test_me(brands, *args):
mocked_module1 = args[0]
This worked for me running python 3.6 and pytest 3.0.6.

If you have multiple patches to be applied, order they are injected is important:
# from question
#pytest.fixture(scope="module")
def brands():
return 1
# notice the order
#patch('my.module.my.class1')
#patch('my.module.my.class2')
def test_list_instance_elb_tg(mocked_class2, mocked_class1, brands):
pass

This doesn't address your question directly, but there is the pytest-mock plugin which allows you to write this instead:
def test_compute_scores(brands, mock):
mock_b = mock.patch('test_test.b')
a()

a) For me the solution was to use a with block inside the test function instead of using a #patch decoration before the test function:
class TestFoo:
def test_baa(self, my_fixture):
with patch(
'module.Class.function_to_patch',
MagicMock(return_value='mocked_result')
) as mocked_function_to_patch:
result= my_fixture.baa('mocked_input')
assert result == 'mocked_result'
mocked_function_to_patch.assert_has_calls([
call('mocked_input')
])
This solution does work inside classes (that are used to structure/group my test methods). Using the with block, you don't need to worry about the order of the arguments. I find it more explicit then the injection mechanism but the code becomes ugly if you patch more then one variable. If you need to patch many dependencies, that might be a signal that your tested function does too many things and that you should refactor it, e.g. by extracting some of the functionality to extra functions.
b) If you are outside classes and do want a patched object to be injected as extra argument in a test method... please note that #patch does not support to define the mock as second argument of the decoration:
#patch('path.to.foo', MagicMock(return_value='foo_value'))
def test_baa(self, my_fixture, mocked_foo):
does not work.
=> Make sure to pass the path as only argument to the decoration. Then define the return value inside the test function:
#patch('path.to.foo')
def test_baa(self, my_fixture, mocked_foo):
mocked_foo.return_value = 'foo_value'
(Unfortunately, this does not seem to work inside classes.)
First let inject the fixture(s), then let inject the variables of the #patch decorations (e.g. 'mocked_foo').
The name of the injected fixture 'my_fixture' needs to be correct. It needs to match the name of the decorated fixture function (or the explicit name used in the fixture decoration).
The name of the injected patch variable 'mocked_foo' does not follow a distinct naming pattern. You can choose it as you like, independent from the corresponding path of the #patch decoration.
If you inject several patched variables, note that the order is reversed: the mocked instance belonging to the last #patch decoration is injected first:
#patch('path.to.foo')
#patch('path.to.qux')
def test_baa(self, my_fixture, mocked_qux, mocked_foo):
mocked_foo.return_value = 'foo_value'

I had the same problem and solution for me was to use mock library in 1.0.1 version (before I was using unittest.mock in 2.6.0 version). Now it works like a charm :)

Is there a way to use Python unit test assertions outside of a TestCase?

I need to create a fake helper class to be used in unit tests (injected into tested classes). Is there some way to use TestCase assertions in such class?
I would like to use the assertions for some common checks performed by the Fake class. Something like:
class FakeFoo(object):
def do_foo(self, a, b):
assertNotNull(a)
...

You can create a instance of unittest.TestCase() and call the methods on that.
import unittest
tc = unittest.TestCase()
tc.assertIsNotNone(a)
On older Python versions (Python 2.7 and earlier, 3.0, 3.1) you need to you pass in the name of an existing method on the class TestCase class (normally it's passed the name of a test method on a subclass). __init__ will do in this case:
tc = unittest.TestCase('__init__')
tc.assertIsNotNone(a)
However, you are probably looking for a good Mock library instead. mock would be a good choice.
Another option is to use pytest, which augments assert statements to provide the same or more context as unittest.TestCase() assertion methods; you'd simply write assert a is not None.

You can use Pytest or Nosetest. Though I'don't know if they have 'assertNotNull' function. I know they can use 'assert' simply for assertion. Or you can use something like assertpy or ptest, if you like, you can search for them on github.

python - Accessing objects mocked with patch

I've been using the mock library to do some of my testing. It's been great so far, but there are some things that I haven't completely understand yet.
mock provides a nice way of patching an entire method using patch, and I could access the patched object in a method like so:
#patch('package.module')
def test_foo(self, patched_obj):
# ... call patched_obj here
self.assertTrue(patched_obj.called)
My question is, how do I access a patched object, if I use the patch decorator on an entire class?
For example:
#patch('package.module')
class TestPackage(unittest.TestCase):
def test_foo(self):
# how to access the patched object?

In this case, test_foo will have an extra argument, the same way as when you decorate the method. If your method is also patched, it those args will be added as well:
#patch.object(os, 'listdir')
class TestPackage(unittest.TestCase):
#patch.object(sys, 'exit')
def test_foo(self, sys_exit, os_listdir):
os_listdir.return_value = ['file1', 'file2']
# ... Test logic
sys_exit.assert_called_with(1)
The arguments order is determined by the order of the decorators calls. The method decorator is called first, so it appends the first argument. The class decorator is outer, so it will add a second argument. The same applies when you attach several patch decorators to the same test method or class (i.e. the outer decorator goes last).