I'm getting confused by using Mock in my python unittests. I've made this simplified version of my problem:
I have this dummy class and methods:
# app/project.py
class MyClass(object):
def method_a(self):
print(FetcherA)
results = FetcherA()
Which is using this class:
# app/fetch.py
class FetcherA(object):
pass
And then this test:
# app/tests/test.py
from mock import patch
from django.test import TestCase
from ..project import MyClass
class MyTestCase(TestCase):
#patch('app.fetch.FetcherA')
def test_method_a(self, test_class):
MyClass().method_a()
test_class.assert_called_once_with()
I would expect that running this test would pass and that print statement, for debugging, would output something like <MagicMock name=...>. Instead it prints out <class 'app.fetch.FetcherA'> and I get:
AssertionError: Expected to be called once. Called 0 times.
Why isn't FetcherA being patched?
OK, fourth time through I think I understood the 'Where to patch' section of the Mock docs.
So, instead of:
#patch('app.fetch.FetcherA')
I should use:
#patch('app.project.FetcherA')
Because we're testing the code in app.project.MyClass where FetcherA has been imported already. So at that point FetcherA is availably globally(?) within app.project.
Related
I have a class ProductionClass with a method method_to_test which I want to test. Class ProductionClass has dependency to api, which I want to mock in the test.
from my_module.apis import api
class ProductionClass:
def method_to_test:
data = api.method_to_mock()
api.method_to_check_call(data)
The test code is as follows:
For api I have a mock class MockApi that I use by refering to it in the #patch decorator.
from unittest.mock import patch, MagicMock
class MockApi:
def method_to_mock():
return some_mock_data
def method_to_check_call(data):
pass
class TestClass:
#patch('my_module.apis.api', MagicMock(return_value=MockApi()))
def test_check_called_with(self):
from module_of_class_production_class.ProductionClass import method_to_test
mock_api = MockApi()
method_to_test()
some_data = { ... }
mock.method_to_check_call.assert_called_with(some_data)
The problem is that it does not work because mock_api is not the same instance of MockApi that is provided in the #patch decorator. Is there a better way to test that?
I have not tested this, but I think that your patch object will get passed as first argument to test_check_called_with like so:
#patch('my_module.apis.api', MagicMock(return_value=MockApi()))
def test_check_called_with(self, your_magic_mock):
# Rest of code
You can also use the with construct like so:
def test_check_called_with(self):
my_api = MockApi()
with patch('my_module.apis.api', MagicMock(return_value=my_api)) as my_mock_api:
# Your code here
You can checkout the official python documentation here for more details: https://docs.python.org/3/library/unittest.mock.html#quick-guide
So I've this code that mocks two times, the first time by mocking imports with:
sys.modules['random'] = MagicMock()
The second time happens inside the unittest of a function that used that import, for example a function that used random
The tests. py is:
import sys
import unittest
from unittest import mock
from unittest.mock import MagicMock
import foo
sys.modules['random'] = MagicMock()
class test_foo(unittest.TestCase):
def test_method(self):
with mock.patch('random.choice', return_value = 2):
object = foo.FooClass(3)
self.assertEqual(2, object.method(), 'Should be 2')
def test_staticmethod(self):
with mock.patch('random.choice', return_value = 2):
object = foo.FooClass(3)
self.assertEqual(2, object.method(), 'should be 2')
The original file Foo.py is:
import random
class FooClass:
def __init__(self,arg):
self.arg = arg
def method(self):
print(random.choice)
return random.choice([1,2,3])
#staticmethod
def staticmethod():
print(random.choice)
random.choice([1,2,3])
The two mocks contrarrest each other, and the mocking of random doesn't happen.
When it prints random it actually prints:
<<bound method Random.choice of <random.Random object at 0x7fe688028018>>
I want that to print a MagicMock.
Can someone help me understand what's happening? Why are they contrarresting each other?
You don't need to update the module source with sys.modules['random'] = MagicMock() without this line it works fine <MagicMock name='choice' id='...'>. patch already does all the work for the isolated temporary updating the method. See more explanation in the docs - Where to patch
I'm encountering a problem with unit testing in Python. Specifically, when I try to mock a function my code imports, variables assigned to the output of that function get assigned to a MagicMock object instead of the mock-function's return_value. I've been digging through the docs for python's unittest library, but am not having any luck.
The following is the code I want to test:
from production_class import function_A, function_B, function_M
class MyClass:
def do_something(self):
variable = functionB()
if variable:
do_other_stuff()
else:
do_something_else
this is what I've tried:
#mock.patch(path.to.MyClass.functionB)
#mock.patch(<other dependencies in MyClass>)
def test_do_something(self, functionB_mock):
functionB_mock.return_value = None # or False, or 'foo' or whatever.
myClass = MyClass()
myClass.do_something()
self.assertTrue(else_block_was_executed)
The issue I have is that when the test gets to variable = functionB in MyClass, the variable doesn't get set to my return value; it gets set to a MagicMock object (and so the if-statement always evaluates to True). How do I mock an imported function such that when executed, variables actually get set to the return value and not the MagicMock object itself?
We'd have to see what import path you're actually using with path.to.MyClass.functionB. When mocking objects, you don't necessarily use the path directly to where the object is located, but the one that the intepreter sees when recursively importing modules.
For example, if your test imports MyClass from myclass.py, and that file imports functionB from production_class.py, the mock path would be myclass.functionB, instead of production_class.functionB.
Then there's the issue that you need additional mocks of MyClass.do_other_stuff and MyClass.do_something_else in to check whether MyClass called the correct downstream method, based on the return value of functionB.
Here's a working example that tests both possible return values of functionB, and whether they call the correct downstream method:
myclass.py
from production_class import functionA, functionB, functionM
class MyClass:
def do_something(self):
variable = functionB()
if variable:
self.do_other_stuff()
else:
self.do_something_else()
def do_other_stuff(self):
pass
def do_something_else(self):
pass
production_class.py
import random
def functionA():
pass
def functionB():
return random.choice([True, False])
def functionM():
pass
test_myclass.py
import unittest
from unittest.mock import patch
from myclass import MyClass
class MyTest(unittest.TestCase):
#patch('myclass.functionB')
#patch('myclass.MyClass.do_something_else')
def test_do_something_calls_do_something_else(self, do_something_else_mock, functionB_mock):
functionB_mock.return_value = False
instance = MyClass()
instance.do_something()
do_something_else_mock.assert_called()
#patch('myclass.functionB')
#patch('myclass.MyClass.do_other_stuff')
def test_do_something_calls_do_other_stuff(self, do_other_stuff_mock, functionB_mock):
functionB_mock.return_value = True
instance = MyClass()
instance.do_something()
do_other_stuff_mock.assert_called()
if __name__ == '__main__':
unittest.main()
calling python test_myclass.py results in:
..
----------------------------------------------------------------------
Ran 2 tests in 0.002s
OK
What I wound up doing was changing the import statements in MyClass to import the object instead of the individual methods. I was then able to mock the object without any trouble.
More explicitly I changed MyClass to look like this:
import production_class as production_class
class MyClass:
def do_something(self):
variable = production_class.functionB()
if variable:
do_other_stuff()
else:
do_something_else
and changed my test to
#mock.patch(path.to.MyClass.production_class)
def test_do_something(self, prod_class_mock):
prod_class_mock.functionB.return_value = None
myClass = MyClass()
myClass.do_something()
self.assertTrue(else_block_was_executed)
I'm trying to unit test a class which is derived from a base_class in an external module. In my dev/test environment I have not access to this external module, which means I have to somehow mock this base_class.
My test-code resides in a different file from the code I'm trying to test.
The problem can be summarized as follows:
my_class.py
import external_module
class MyClass(external_module.ExternalClass):
def test_method(self):
return "successful"
test_my_class.py
import sys
import unittest
from unittest.mock import MagicMock
sys.modules['external_module'] = MagicMock()
from my_class import MyClass
class TestMyClass(unittest.TestCase):
def test_first(self):
my_class = MyClass()
result = my_class.test_method()
self.assertEqual(result, "successful")
if __name__ == '__main__':
unittest.main()
Results
When running test_my_class.py the result are the following.
AssertionError: <MagicMock name='mock.ExternalClass.test_method()' id='140272215184664'> != 'successful'
Clearly since the external_module is mocked, even MyClass becomes an instance of a mock-object.
Similar posts
The problem is similar to as described in Python mock: mocking base class for inheritance, but has the difference that the base_class is from an external module.
Even How to mock a base class with python mock library show som similarities to my problem, though the solutions can not be directly applied.
Tries and failures
To get the import
import external_module
to work in my_class.py
sys.modules['external_module'] = MagicMock()
need to be set in test_my_class.py.
Though, this leads to that external_module.* becomes a Mock-instance.
You could create a helper module mocked_external_module, which can be imported from your tests and also contains a class base_class. Then you do the following in your test code:
import mocked_external_module
sys.modules['external_module'] = mocked_external_module
Plus, every method of your base_class that you need to mock you can create as a Mock or MagicMock.
Im trying to patch multiple methods in a class. Here is my simplified set up
Hook.py is defined as
class Hook():
def get_key(self):
return "Key"
def get_value(self):
return "Value"
HookTransfer.py defined as
from Hook import Hook
class HookTransfer():
def execute(self):
self.hook = Hook()
key = self.hook.get_key()
value = self.hook.get_value()
print(key)
print(value)
I want to mock the methods get_key and get_value in the Hook class. The following works i.e. prints New_Key and New_Value
from HookTransfer import HookTransfer
import unittest
from unittest import mock
class TestMock(unittest.TestCase):
#mock.patch('HookTransfer.Hook.get_key', return_value="New_Key")
#mock.patch('HookTransfer.Hook.get_value', return_value="New_Value")
def test_execute1(self, mock_get_key, mock_get_value):
HookTransfer().execute()
if __name__ == '__main__':
unittest.main()
However this does not. It prints <MagicMock name='Hook().get_key()' id='4317706896'> and <MagicMock name='Hook().get_value()' id='4317826128'>
from HookTransfer import HookTransfer
import unittest
from unittest import mock
class TestMock(unittest.TestCase):
#mock.patch('HookTransfer.Hook', spec=True)
def test_execute2(self, mock_hook):
mock_hook.get_key = mock.Mock(return_value="New_Key")
mock_hook.get_value = mock.Mock(return_value="New_Value")
HookTransfer().execute()
if __name__ == '__main__':
unittest.main()
Intuitively it seems like the second one should work too but it doesnt. Could you help explain why it does not. I suspect it has something to do with "where to patch" but Im unable to get clarity.
You can patch multiple methods of a module or a class using patch.multiple(). Something like this should work for your case:
import unittest
from unittest.mock import MagicMock, patch
class TestMock(unittest.TestCase):
#patch.multiple('HookTransfer.Hook',
get_key=MagicMock(return_value='New_Key'),
get_value=MagicMock(return_value='New_Value'))
def test_execute1(self, **mocks):
HookTransfer().execute()
When patch.multiple() is used as a decorator, the mocks are passed into the decorated function by keyword, and a dictionary is returned when it's used as a context manager.
What you need to is:
mock the class Hook,
from HookTransfer import HookTransfer
from Hook import Hook
import unittest
try:
import mock
except ImportError:
from unittest import mock
class TestMock(unittest.TestCase):
#mock.patch.object(Hook, 'get_key', return_value="New_Key")
#mock.patch.object(Hook, 'get_value', return_value="New_Value")
def test_execute1(self, mock_get_value, mock_get_key):
HookTransfer().execute()
if __name__ == "__main__":
unittest.main()
After some testing I was able to find the issue.
In the second test case, the patch decorator creates a new instance of a Mock class and passes it via mock_hook argument to test_execute2 function. Lets refer to this as mock1. mock1 replaces the Hook class in HookTransfer.py. When self.hook = Hook() is run, it translates to calling __init__ of mock1. By design this returns yet another Mock instance - lets refer to this as mock2. So self.hook points to mock2. But mock_hook.get_key = mock.Mock(return_value="New_Key"), mocks the methods in mock1.
In order to mock correctly, mock2 needs to be patched. This can be done in 2 ways
By mocking the return_value of mock1 (which returns mock2) mock_hook.return_value.get_key = mock.Mock(return_value="New_Key")
Mocking the return value of constructor of mock1 (which returns mock2) mock_hook().get_key = mock.Mock(return_value="New_Key")
Under the wraps both options really do the same thing.