in the case of unit testing a wrapper library, testing the wrapper without depending/exercising the upstream library is a goal; In a known case, all calls to the upstream library can be mocked and that's what I've done, but I've been frustrated by changes to the wrapper that introduce more calls to the upstream library being missed by the mock tools;
How can I best fail any test that tries to use a given namespace?
My idea currently is to change all the unittest methods to have a monkey patch like
#unittest.mock.patch('wrapper_namespace.upsteam_namespace')
and reply the upstream library with a mock that can be asserted untouched; I'm hoping for an option that works globally, so that I
don't have to add a monkeypatch to every test method, though this level of granularity is acceptable; but also don't have to perform the assertion that the mock was never used in the test methods (or make a decorator to do all that either)
prohibits access to the upstream library from any part of the software
(e.g, Wrapper calls B calls Upstream, B's call to upstream might not be caught)
You don't have to patch every test method. You can easily patch over the class if you're using unittest, or just assign the module to whatever you want to patch over it with. Here's a workable example:
A fake lib in some_lib.py:
def some_lib_func():
raise ValueError("I've been called.")
def some_other_lib_func():
raise ValueError("I've been called.")
class SomeClass:
def __init__(self):
raise ValueError("I've been constructed.")
wrapper.py:
import some_lib
def wrapper1():
some_lib.some_lib_func()
def wrapper2():
some_lib.some_other_lib_func()
def wrapper3():
x = some_lib.SomeClass()
test.py:
from unittest.mock import patch, MagicMock
import unittest
import wrapper
# Alternative:
# wrapper.some_lib = MagicMock()
# Can patch an entire class
#patch('wrapper.some_lib', MagicMock())
class TestWrapper(unittest.TestCase):
def test_wrapper1(self):
wrapper.wrapper1()
def test_wrapper2(self):
wrapper.wrapper2()
def test_wrapper3(self):
wrapper.wrapper3()
if __name__ == "__main__":
unittest.main()
We would explode if the functions/classes in some_lib were called, but they aren't:
Matthews-MacBook-Pro:stackoverflow matt$ python test.py
...
----------------------------------------------------------------------
Ran 3 tests in 0.001s
OK
Feel free to comment out the patch and comment in wrapper.some_lib = MagicMock(). You'll get the same result in this toy example, but there is a major difference between the two approaches:
When using #patch('wrapper.some_lib', MagicMock()) the patch is only live for that Test Case class.
When using wrapper.some_lib = MagicMock(), however, that patch will stay live for the entire length of your python program, unless you save off the original module and patch it back manually at some point. Everything that is using the wrapper module will get the mocked version.
So you could so something like:
original_lib = wrapper.some_lib
wrapper.some_lib = MagicMock()
...
# call some test suite, every call to the wrapper module will be mocked out
...
wrapper.some_lib = original_lib
...
# call some other test suite that actually needs the real thing
...
HTH.
EDIT: Misread your question slightly, but you can inspect MagicMock objects to see if they've been called, and if so, fail the test. Or just patch over with something that fails when called (instead of MagicMock). I can provide code to do this if requested (just leave a comment), but hopefully the above can get you started. I think the crux of the question was really about the global patching. Cheers!
Related
I am trying to implement unittests for my python program. The problem is, that my program is using several imported classes, which I would like to replace by a mocked object/class to verify single functions/methods.
I do not get any errors with my mocked class. But it appears that the mock itself didn't replace the object I wanted to replace.
This is basically my structure:
First the class I want to mock. Might look like that:
class ToMock():
def getSomething(self):
return "something"
The class I want to test looks like this:
from x.y import ToMock
class ClassToTest():
def __init__(self):
self.obj = ToMock()
def returnStuff():
return self.obj.getSomething()
As you can imagine, I want to test the returnStuff method. Therfore I want to mock .getSomething, or better said the whole ToMock object.
The unittest should therefore test the ClassToTest with the mocked ToMock class. I tried several mock.patch variants, but I couldn't get it to run/test properly.
import unittest
from unittest import mock
from a.b import ClassToTest
class TestObject(unittest.TestCase):
def setUp(self):
with mock.patch('x.y.ToMock') as mock_obj:
mock_obj.return_value.getSomething().return_value="mocked return value"
self.test_class = ClassToTest()
result = self.test_class.returnStuff() # This should return now 'mocked return value', I guess?
mock_obj.return_value.getSomething.assert_called_once_with("")
The problem I face is, that the self.test_class.returnStuff() is not "calling" the mocked object, but imports the real class etc. and therefore I am running into timeouts, or similar stuff.
I am sure, that I provide the wrong path for the object which should be mocked. Perhaps someone can hint me into the right direction.
Thanks
-GreNait
The issue is that you are not patching in the correct place. You are patching where the object is defined as opposed to where it is looked up.
a.py
-> Defines ToMock
b.py
-> from a import ToMock
-> some_function/class instantiates ToMock
In your code shown you are patching a.ToMock however you should be patching b.ToMock. That is why it is not running your mock object when testing. You can read more about where to patch here.
I am testing a class that needs a mock in the constructor, so I usually do this:
class TestActionManager(unittest.TestCase):
#patch('actionlib.SimpleActionClient', return_value=create_autospec(actionlib.SimpleActionClient))
def setUp(self, mock1):
self.action_manager = ActionManager()
Then in this class I add all the tests. So the first one is working fine
def test_1(self):
self.action_manager.f()
self.action_manager.f.assert_called_once()
But if I add another test and run both
def test_2(self):
self.action_manager.f()
self.action_manager.f.assert_called_once()
It says f has been called twice. I was expecting setUp to create a new ActionManager (and hence create a new mock) before starting every test, but it is clearly not happening, since the mock is somehow shared. Also I tried to do
def tearDown(self):
del self.action_manager
But it does not fix the problem.
I have read something related in
Python Testing - Reset all mocks?
where the solution is to use a different library (something that I would like to avoid)
and in Any way to reset a mocked method to its original state? - Python Mock - mock 1.0b1 where it is using different classes to do it.
Is there any possibility to reset the mock in the same class before or after every test?
BTW, this is a unittest question, not a pytest question.
Anyways,
I believe what you're looking for is reset_mock
Here's, in general, how it works:
def test_1(self):
f = MagicMock() # or whatever you're mocking
f()
f.assert_called_once()
f.reset_mock()
f()
f.assert_called_once()
The result will be PASSED
If you want to automate, then you store the mocked thing inside setUp, and in tearDown you call the mocked thing's .reset_mock() method.
def setUp(self, mock1):
self.mock1 = mock1
# ... do other things ...
def tearDown(self):
self.mock1.reset_mock()
My current script calls an external script to perform some task. I want to check the code up to that point in a unittest, but not actually run the external script. Is there some way I can tell the script to effectively skip the following block IF the code is being run as part of a unit test?
The unittest package has extensive support for "mocking" functions and methods. Encapsulate the call to an external program in a simple function that your unit tests can override ("mock out") without modifying the structure of your program. Example:
Here is part of your program, in the module realcode.py
def internal_function_calling_exec(arg1):
"""The real thing"""
print("I am executing an external program")
def bigger_function_being_tested(arg1, arg2):
"""
A complex function with one or more calls to `internal_function_calling_exec`
"""
print("I will now call `internal_function_calling_exec()`")
internal_function_calling_exec(42)
Your unit test can then look like this:
import unittest
from unittest.mock import patch
import realcode
class MyTest(unittest.TestCase):
#patch("realcode.internal_function_calling_exec")
def test_something(self, mocked_func):
realcode.bigger_function_being_tested(1, 2)
mocked_func.assert_called_with(42)
This will never call the original internal_function_calling_exec(). Instead, this will trigger a call to the mock object; your test can then query the object to confirm that it was called properly.
There are ways to mock class methods etc., so you could mock subprocess.call instead, for example. But I think the above is the better pattern.
One possible approach is to set an environment variable in the unit test, and check for that environment variable in the script being tested.
For example, in unittest.py:
os.environ["testing"] = "1"
And in script-to-be-tested.py:
testing = os.environ["testing"]
... do stuff based on the testing variable
Since script-to-be-tested.py will be called from unittest.py, it should inherit the environment variables.
Possibly not the cleanest solution, but it should work.
I'm using the datashape Python package and registering a new type with the #datashape.discover.register decorator. I'd like to test that when I call datashape.discover on an object of the type I'm registering, it calls the function being decorated. I'd also like to do this with good unit testing principles, meaning not actually executing the function being decorated, as it would have side effects I don't want in the test. However, this isn't working.
Here's some sample code to demonstrate the problem:
myfile.py:
#datashape.discover.register(SomeType)
def discover_some_type(data)
...some stuff i don't want done in a unit test...
test_myfile.py:
class TestDiscoverSomeType(unittest.TestCase):
#patch('myfile.discover_some_type')
def test_discover_some_type(self, mock_discover_some_type):
file_to_discover = SomeType()
datashape.discover(file_to_discover)
mock_discover_some_type.assert_called_with(file_to_discover)
The issue seems to be that the function I want mocked is mocked in the body of the test, however, it was not mocked when it was decorated (i.e. when it was imported). The discover.register function essentially internally registers the function being decorated to look it up when discover() is called with an argument of the given type. Unfortunately, it seems to internally register the real function every time, and not the patched version I want, so it will always call the real function.
Any thoughts on how to be able to patch the function being decorated and assert that it is called when datashape.discover is called?
Here's a solution I've found that's only a little hacky:
sometype.py:
def discover_some_type(data):
...some stuff i don't want done in a unit test...
discovery_channel.py:
import sometype
#datashape.discover.register(SomeType)
def discover_some_type(data):
return sometype.discover_some_type(data)
test_sometype.py:
class TestDiscoverSomeType(unittest.TestCase):
#patch('sometype.discover_some_type')
def test_discover_some_type(self, mock_discover_some_type):
import discovery_channel
file_to_discover = SomeType()
datashape.discover(file_to_discover)
mock_discover_some_type.assert_called_with(file_to_discover)
The key is that you have to patch out whatever will actually do stuff before you import the module that has the decorated function that will register the patched function to datashape. This unfortunately means that you can't have your decorated function and the function doing the discovery in the same module (so things that should logically go together are now apart). And you have the somewhat hacky import-in-a-function in your unit test (to trigger the discover.register). But at least it works.
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 :)