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I have gone through the page https://docs.python.org/3/library/unittest.mock-examples.html and i see that they have listed an example on how to mock generators
I have a code where i call a generator to give me a set of values that i save as a dictionary. I want to mock the calls to this generator in my unit test.
I have written the following code and it does not work.
Where am i going wrong?
In [7]: items = [(1,'a'),(2,'a'),(3,'a')] In [18]: def f(): print "here" for i in [1,2,3]: yield i,'a' In [8]: def call_f(): ...: my_dict = dict(f()) ...: print my_dict[1] ...: In [9]: call_f() "here" a In [10]: import mock In [18]: def test_call_f(): with mock.patch('__main__.f') as mock_f: mock_f.iter.return_value = items call_f() ....: In [19]: test_call_f() --------------------------------------------------------------------------- KeyError Traceback (most recent call last) <ipython-input-19-33ca65a4f3eb> in <module>() ----> 1 test_call_f() <ipython-input-18-92ff5f1363c8> in test_call_f() 2 with mock.patch('__main__.f') as mock_f: 3 mock_f.iter.return_value = items ----> 4 call_f() <ipython-input-8-a5cff08ebf69> in call_f() 1 def call_f(): 2 my_dict = dict(f()) ----> 3 print my_dict[1] KeyError: 1 
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patch() unittest. mock provides a powerful mechanism for mocking objects, called patch() , which looks up an object in a given module and replaces that object with a Mock . Usually, you use patch() as a decorator or a context manager to provide a scope in which you will mock the target object.
Mock vs. So what is the difference between them? MagicMock is a subclass of Mock . It contains all magic methods pre-created and ready to use (e.g. __str__ , __len__ , etc.). Therefore, you should use MagicMock when you need magic methods, and Mock if you don't need them.
side_effect: A function to be called whenever the Mock is called. See the side_effect attribute. Useful for raising exceptions or dynamically changing return values. The function is called with the same arguments as the mock, and unless it returns DEFAULT , the return value of this function is used as the return value.
Mock is a type, and patch is a context. So you are going to pass or receive Mock instances as parameters, and apply patch contexts to blocks of code. (Lowercase 'mock' is just the name of the package.) Tests and test classes are often decorated with calls to patch.
Change this line:
mock_f.iter.return_value = items To this:
mock_f.return_value = iter(items) Wims answer:
mock_f.return_value = iter(items) works as long as your mock gets called only once. In unit testing, we may often want to call a function or method multiple times with different arguments. That will fail in this case, because on the first call the iterator will be exhausted such that on the second call it will immediately raise a StopIteration exception. With Alexandre Paes' answer I was getting an AttributeError: 'function' object has no attribute '__iter__' when my mock was coming from unittest.mock.patch.
As an alternative, we can create a “fake” iterator and assign that as a side_effect:
@unittest.mock.patch("mymod.my_generator", autospec=True): def test_my_func(mm): from mymod import my_func def fake(): yield from [items] mm.side_effect = fake my_func() # which calls mymod.my_generator my_func() # subsequent calls work without unwanted memory from first call If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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