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Using Mock¶Mock Patching Methods¶Common uses for
You might want to replace a method on an object to check that it is called with the correct arguments by another part of the system: >>> real = SomeClass() >>> real.method = MagicMock(name='method') >>> real.method(3, 4, 5, key='value') <MagicMock name='method()' id='...'> Once our mock has been used ( Note In most of these examples the Once the mock has been called its This example tests that calling
>>> class ProductionClass: ... def method(self): ... self.something(1, 2, 3) ... def something(self, a, b, c): ... pass ... >>> real = ProductionClass() >>> real.something = MagicMock() >>> real.method() >>> real.something.assert_called_once_with(1, 2, 3) Mock for Method Calls on an Object¶In the last example we patched a method directly on an object to check that it was called correctly. Another common use case is to pass an object into a method (or some part of the system under test) and then check that it is used in the correct way. The simple >>> class ProductionClass: ... def closer(self, something): ... something.close() ... So to test it we need to pass in an object with a >>> real = ProductionClass() >>> mock = Mock() >>> real.closer(mock) >>> mock.close.assert_called_with() We don’t have to do any work to provide the ‘close’ method on our mock. Accessing close creates
it. So, if ‘close’ hasn’t already been called then accessing it in the test will create it, but Mocking Classes¶A common use case is to mock out classes instantiated by your code under test. When you patch a class, then that class is replaced with a mock. Instances are created by calling the class. This means you access the “mock instance” by looking at the return value of the mocked class. In the example below we have a function
>>> def some_function(): ... instance = module.Foo() ... return instance.method() ... >>> with patch('module.Foo') as mock: ... instance = mock.return_value ... instance.method.return_value = 'the result' ... result = some_function() ... assert result == 'the result' Naming your mocks¶It can be useful to give your mocks a name. The name is shown in the repr of the mock and can be helpful when the mock appears in test failure messages. The name is also propagated to attributes or methods of the mock: >>> mock = MagicMock(name='foo') >>> mock <MagicMock name='foo' id='...'> >>> mock.method <MagicMock name='foo.method' id='...'> Tracking all Calls¶Often you want to track more than a single call to a method. The
>>> mock = MagicMock() >>> mock.method() <MagicMock name='mock.method()' id='...'> >>> mock.attribute.method(10, x=53) <MagicMock name='mock.attribute.method()' id='...'> >>> mock.mock_calls [call.method(), call.attribute.method(10, x=53)] If you make an assertion about You use the >>> expected = [call.method(), call.attribute.method(10, x=53)] >>> mock.mock_calls == expected True However, parameters to calls that return mocks are not recorded, which means it is not possible to track nested calls where the parameters used to create ancestors are important: >>> m = Mock() >>> m.factory(important=True).deliver() <Mock name='mock.factory().deliver()' id='...'> >>> m.mock_calls[-1] == call.factory(important=False).deliver() True Setting Return Values and Attributes¶Setting the return values on a mock object is trivially easy: >>> mock = Mock() >>> mock.return_value = 3 >>> mock() 3 Of course you can do the same for methods on the mock: >>> mock = Mock() >>> mock.method.return_value = 3 >>> mock.method() 3 The return value can also be set in the constructor: >>> mock = Mock(return_value=3) >>> mock() 3 If you need an attribute setting on your mock, just do it: >>> mock = Mock() >>> mock.x = 3 >>> mock.x 3 Sometimes you want to mock up a more complex situation, like for example We can use >>> mock = Mock() >>> cursor = mock.connection.cursor.return_value >>> cursor.execute.return_value = ['foo'] >>> mock.connection.cursor().execute("SELECT 1") ['foo'] >>> expected = call.connection.cursor().execute("SELECT 1").call_list() >>> mock.mock_calls [call.connection.cursor(), call.connection.cursor().execute('SELECT 1')] >>> mock.mock_calls == expected True It is the call to Raising exceptions with mocks¶A useful attribute is
>>> mock = Mock(side_effect=Exception('Boom!')) >>> mock() Traceback (most recent call last): ... Exception: Boom! Side effect functions and iterables¶
>>> mock = MagicMock(side_effect=[4, 5, 6]) >>> mock() 4 >>> mock() 5 >>> mock() 6 For more advanced use cases, like dynamically varying the return values depending on what the mock is called with, >>> vals = {(1, 2): 1, (2, 3): 2} >>> def side_effect(*args): ... return vals[args] ... >>> mock = MagicMock(side_effect=side_effect) >>> mock(1, 2) 1 >>> mock(2, 3) 2 Mocking asynchronous iterators¶Since Python 3.8, >>> mock = MagicMock() # AsyncMock also works here >>> mock.__aiter__.return_value = [1, 2, 3] >>> async def main(): ... return [i async for i in mock] ... >>> asyncio.run(main()) [1, 2, 3] Mocking asynchronous context manager¶Since Python 3.8, >>> class AsyncContextManager: ... async def __aenter__(self): ... return self ... async def __aexit__(self, exc_type, exc, tb): ... pass ... >>> mock_instance = MagicMock(AsyncContextManager()) # AsyncMock also works here >>> async def main(): ... async with mock_instance as result: ... pass ... >>> asyncio.run(main()) >>> mock_instance.__aenter__.assert_awaited_once() >>> mock_instance.__aexit__.assert_awaited_once() Creating a Mock from an Existing Object¶One problem with over use of mocking is that it couples your tests to the implementation of your mocks rather than your real code. Suppose you have a class that implements
>>> mock = Mock(spec=SomeClass) >>> mock.old_method() Traceback (most recent call last): ... AttributeError: object has no attribute 'old_method' Using a specification also enables a smarter matching of calls made to the mock, regardless of whether some parameters were passed as positional or named arguments: >>> def f(a, b, c): pass ... >>> mock = Mock(spec=f) >>> mock(1, 2, 3) <Mock name='mock()' id='140161580456576'> >>> mock.assert_called_with(a=1, b=2, c=3) If you want this smarter matching to also work with method calls on the mock, you can use auto-speccing. If you want a stronger form of specification that prevents the setting of arbitrary attributes as well as the getting of them then you can use spec_set instead of spec. Patch Decorators¶Note With A common need in tests is to patch a class attribute or a module attribute, for example patching a builtin or patching a class in a module to test that it is instantiated. Modules and classes are effectively global, so patching on them has to be undone after the test or the patch will persist into other tests and cause hard to diagnose problems. mock
provides three convenient decorators for this:
>>> original = SomeClass.attribute >>> @patch.object(SomeClass, 'attribute', sentinel.attribute) ... def test(): ... assert SomeClass.attribute == sentinel.attribute ... >>> test() >>> assert SomeClass.attribute == original >>> @patch('package.module.attribute', sentinel.attribute) ... def test(): ... from package.module import attribute ... assert attribute is sentinel.attribute ... >>> test() If you are patching a module (including
>>> mock = MagicMock(return_value=sentinel.file_handle) >>> with patch('builtins.open', mock): ... handle = open('filename', 'r') ... >>> mock.assert_called_with('filename', 'r') >>> assert handle == sentinel.file_handle, "incorrect file handle returned" The module name can be ‘dotted’, in the form >>> @patch('package.module.ClassName.attribute', sentinel.attribute) ... def test(): ... from package.module import ClassName ... assert ClassName.attribute == sentinel.attribute ... >>> test() A nice pattern is to actually decorate test methods themselves: >>> class MyTest(unittest.TestCase): ... @patch.object(SomeClass, 'attribute', sentinel.attribute) ... def test_something(self): ... self.assertEqual(SomeClass.attribute, sentinel.attribute) ... >>> original = SomeClass.attribute >>> MyTest('test_something').test_something() >>> assert SomeClass.attribute == original If you want to patch with a Mock, you can use >>> class MyTest(unittest.TestCase): ... @patch.object(SomeClass, 'static_method') ... def test_something(self, mock_method): ... SomeClass.static_method() ... mock_method.assert_called_with() ... >>> MyTest('test_something').test_something() You can stack up multiple patch decorators using this pattern: >>> class MyTest(unittest.TestCase): ... @patch('package.module.ClassName1') ... @patch('package.module.ClassName2') ... def test_something(self, MockClass2, MockClass1): ... self.assertIs(package.module.ClassName1, MockClass1) ... self.assertIs(package.module.ClassName2, MockClass2) ... >>> MyTest('test_something').test_something() When you nest patch decorators the mocks are passed in to the decorated function in the same order they applied (the normal
Python order that decorators are applied). This means from the bottom up, so in the example above the mock for There is also >>> foo = {'key': 'value'} >>> original = foo.copy() >>> with patch.dict(foo, {'newkey': 'newvalue'}, clear=True): ... assert foo == {'newkey': 'newvalue'} ... >>> assert foo == original
Where you use >>> class ProductionClass: ... def method(self): ... pass ... >>> with patch.object(ProductionClass, 'method') as mock_method: ... mock_method.return_value = None ... real = ProductionClass() ... real.method(1, 2, 3) ... >>> mock_method.assert_called_with(1, 2, 3) As an alternative Further Examples¶Here are some more examples for some slightly more advanced scenarios. Mocking chained calls¶Mocking chained calls is actually straightforward with mock once you understand the This means that you can see how the object returned from a call to a mocked object has been used by interrogating the >>> mock = Mock() >>> mock().foo(a=2, b=3) <Mock name='mock().foo()' id='...'> >>> mock.return_value.foo.assert_called_with(a=2, b=3) From here it is a simple step to configure and then make assertions about chained calls. Of course another alternative is writing your code in a more testable way in the first place… So, suppose we have some code that looks a little bit like this: >>> class Something: ... def __init__(self): ... self.backend = BackendProvider() ... def method(self): ... response = self.backend.get_endpoint('foobar').create_call('spam', 'eggs').start_call() ... # more code Assuming that As this chain of calls is made from an instance attribute we can monkey patch the To do this we create a mock instance as our mock backend and create a mock response object for it. To set the response as the return value for that final mock_backend.get_endpoint.return_value.create_call.return_value.start_call.return_value = mock_response We can do that in a slightly nicer way using the >>> something = Something() >>> mock_response = Mock(spec=open) >>> mock_backend = Mock() >>> config = {'get_endpoint.return_value.create_call.return_value.start_call.return_value': mock_response} >>> mock_backend.configure_mock(**config) With these we monkey patch the “mock backend” in place and can make the real call: >>> something.backend = mock_backend >>> something.method() Using
>>> chained = call.get_endpoint('foobar').create_call('spam', 'eggs').start_call() >>> call_list = chained.call_list() >>> assert mock_backend.mock_calls == call_list Partial mocking¶In some tests I wanted to mock out a call to I found a simple way of doing this that involved effectively wrapping the date class with a mock, but passing through calls to the constructor to the real class (and returning real instances). The
>>> from datetime import date >>> with patch('mymodule.date') as mock_date: ... mock_date.today.return_value = date(2010, 10, 8) ... mock_date.side_effect = lambda *args, **kw: date(*args, **kw) ... ... assert mymodule.date.today() == date(2010, 10, 8) ... assert mymodule.date(2009, 6, 8) == date(2009, 6, 8) Note that we don’t patch
When Calls to the date constructor are recorded in the An alternative way of dealing with mocking dates, or other builtin classes, is discussed in this blog entry. Mocking a Generator Method¶A Python generator is a function or method that uses the A generator method / function is called to return the generator object. It is the generator object that is then iterated over. The protocol method for iteration is Here’s an example class with an “iter” method implemented as a generator: >>> class Foo: ... def iter(self): ... for i in [1, 2, 3]: ... yield i ... >>> foo = Foo() >>> list(foo.iter()) [1, 2, 3] How would we mock this class, and in particular its “iter” method? To configure the values returned from the iteration (implicit in the call to
>>> mock_foo = MagicMock() >>> mock_foo.iter.return_value = iter([1, 2, 3]) >>> list(mock_foo.iter()) [1, 2, 3]1 There are also generator expressions and more advanced uses of generators, but we aren’t concerned about them here. A very good introduction to generators and how powerful they are is: Generator Tricks for Systems Programmers. Applying the same patch to every test method¶If you want several patches in place for multiple test methods the obvious way is to apply the patch decorators to every method. This can feel like unnecessary repetition. For Python 2.6 or more recent you can use >>> @patch('mymodule.SomeClass') ... class MyTest(unittest.TestCase): ... ... def test_one(self, MockSomeClass): ... self.assertIs(mymodule.SomeClass, MockSomeClass) ... ... def test_two(self, MockSomeClass): ... self.assertIs(mymodule.SomeClass, MockSomeClass) ... ... def not_a_test(self): ... return 'something' ... >>> MyTest('test_one').test_one() >>> MyTest('test_two').test_two() >>> MyTest('test_two').not_a_test() 'something' An alternative way of managing patches is to use the patch methods: start and stop. These allow you to move the patching into your >>> class MyTest(unittest.TestCase): ... def setUp(self): ... self.patcher = patch('mymodule.foo') ... self.mock_foo = self.patcher.start() ... ... def test_foo(self): ... self.assertIs(mymodule.foo, self.mock_foo) ... ... def tearDown(self): ... self.patcher.stop() ... >>> MyTest('test_foo').run() If you use this technique you must ensure that the patching is “undone” by calling >>> class MyTest(unittest.TestCase): ... def setUp(self): ... patcher = patch('mymodule.foo') ... self.addCleanup(patcher.stop) ... self.mock_foo = patcher.start() ... ... def test_foo(self): ... self.assertIs(mymodule.foo, self.mock_foo) ... >>> MyTest('test_foo').run() Mocking Unbound Methods¶Whilst writing tests today I needed to patch an unbound method (patching the method on the class rather than on the instance). I needed self to be passed in as the first argument because I want to make asserts about which objects were calling this particular method. The issue is that you can’t patch with a mock for
this, because if you replace an unbound method with a mock it doesn’t become a bound method when fetched from the instance, and so it doesn’t get self passed in. The workaround is to patch the unbound method with a real function instead. The If you pass >>> class Foo: ... def foo(self): ... pass ... >>> with patch.object(Foo, 'foo', autospec=True) as mock_foo: ... mock_foo.return_value = 'foo' ... foo = Foo() ... foo.foo() ... 'foo' >>> mock_foo.assert_called_once_with(foo) If we don’t use Checking multiple calls with mock¶mock has a nice API for making assertions about how your mock objects are used. >>> mock = Mock() >>> mock.foo_bar.return_value = None >>> mock.foo_bar('baz', spam='eggs') >>> mock.foo_bar.assert_called_with('baz', spam='eggs') If your mock is only being called once you can use the >>> mock.foo_bar.assert_called_once_with('baz', spam='eggs') >>> mock.foo_bar() >>> mock.foo_bar.assert_called_once_with('baz', spam='eggs') Traceback (most recent call last): ... AssertionError: Expected to be called once. Called 2 times. Both >>> mock = Mock(return_value=None) >>> mock(1, 2, 3) >>> mock(4, 5, 6) >>> mock() >>> mock.call_args_list [call(1, 2, 3), call(4, 5, 6), call()] The >>> expected = [call(1, 2, 3), call(4, 5, 6), call()] >>> mock.call_args_list == expected True Coping with mutable arguments¶Another situation is rare, but can bite you, is when your mock is called with mutable arguments. Here’s some example code that shows the problem. Imagine the following functions defined in ‘mymodule’: def frob(val): pass def grob(val): "First frob and then clear val" frob(val) val.clear() When we try to test that >>> with patch('mymodule.frob') as mock_frob: ... val = {6} ... mymodule.grob(val) ... >>> val set() >>> mock_frob.assert_called_with({6}) Traceback (most recent call last): ... AssertionError: Expected: (({6},), {}) Called with: ((set(),), {}) One possibility would be for mock to copy the arguments you pass in. This could then cause problems if you do assertions that rely on object identity for equality. Here’s one solution that uses the >>> from copy import deepcopy >>> from unittest.mock import Mock, patch, DEFAULT >>> def copy_call_args(mock): ... new_mock = Mock() ... def side_effect(*args, **kwargs): ... args = deepcopy(args) ... kwargs = deepcopy(kwargs) ... new_mock(*args, **kwargs) ... return DEFAULT ... mock.side_effect = side_effect ... return new_mock ... >>> with patch('mymodule.frob') as mock_frob: ... new_mock = copy_call_args(mock_frob) ... val = {6} ... mymodule.grob(val) ... >>> new_mock.assert_called_with({6}) >>> new_mock.call_args call({6})
Note If your mock is only going to be used once there is an easier way of checking arguments at the point they are called. You can simply do the checking inside a >>> def side_effect(arg): ... assert arg == {6} ... >>> mock = Mock(side_effect=side_effect) >>> mock({6}) >>> mock(set()) Traceback (most recent call last): ... AssertionError An alternative approach is to create a subclass of
>>> from copy import deepcopy >>> class CopyingMock(MagicMock): ... def __call__(self, /, *args, **kwargs): ... args = deepcopy(args) ... kwargs = deepcopy(kwargs) ... return super().__call__(*args, **kwargs) ... >>> c = CopyingMock(return_value=None) >>> arg = set() >>> c(arg) >>> arg.add(1) >>> c.assert_called_with(set()) >>> c.assert_called_with(arg) Traceback (most recent call last): ... AssertionError: Expected call: mock({1}) Actual call: mock(set()) >>> c.foo <CopyingMock name='mock.foo' id='...'> When you subclass Nesting Patches¶Using patch as a context manager is nice, but if you do multiple patches you can end up with nested with statements indenting further and further to the right: >>> class MyTest(unittest.TestCase): ... ... def test_foo(self): ... with patch('mymodule.Foo') as mock_foo: ... with patch('mymodule.Bar') as mock_bar: ... with patch('mymodule.Spam') as mock_spam: ... assert mymodule.Foo is mock_foo ... assert mymodule.Bar is mock_bar ... assert mymodule.Spam is mock_spam ... >>> original = mymodule.Foo >>> MyTest('test_foo').test_foo() >>> assert mymodule.Foo is original With unittest >>> class MyTest(unittest.TestCase): ... ... def create_patch(self, name): ... patcher = patch(name) ... thing = patcher.start() ... self.addCleanup(patcher.stop) ... return thing ... ... def test_foo(self): ... mock_foo = self.create_patch('mymodule.Foo') ... mock_bar = self.create_patch('mymodule.Bar') ... mock_spam = self.create_patch('mymodule.Spam') ... ... assert mymodule.Foo is mock_foo ... assert mymodule.Bar is mock_bar ... assert mymodule.Spam is mock_spam ... >>> original = mymodule.Foo >>> MyTest('test_foo').run() >>> assert mymodule.Foo is original Mocking a dictionary with MagicMock¶You may want to mock a dictionary, or other container object, recording all access to it whilst having it still behave like a dictionary. We can do this with
When the After the >>> my_dict = {'a': 1, 'b': 2, 'c': 3} >>> def getitem(name): ... return my_dict[name] ... >>> def setitem(name, val): ... my_dict[name] = val ... >>> mock = MagicMock() >>> mock.__getitem__.side_effect = getitem >>> mock.__setitem__.side_effect = setitem Note An alternative
to using >>> mock = Mock() >>> mock.__getitem__ = Mock(side_effect=getitem) >>> mock.__setitem__ = Mock(side_effect=setitem) A third option is to use >>> mock = MagicMock(spec_set=dict) >>> mock.__getitem__.side_effect = getitem >>> mock.__setitem__.side_effect = setitem With these side effect functions in place, the >>> mock['a'] 1 >>> mock['c'] 3 >>> mock['d'] Traceback (most recent call last): ... KeyError: 'd' >>> mock['b'] = 'fish' >>> mock['d'] = 'eggs' >>> mock['b'] 'fish' >>> mock['d'] 'eggs' After it has been used you can make assertions about the access using the normal mock methods and attributes: >>> mock.__getitem__.call_args_list [call('a'), call('c'), call('d'), call('b'), call('d')] >>> mock.__setitem__.call_args_list [call('b', 'fish'), call('d', 'eggs')] >>> my_dict {'a': 1, 'b': 'fish', 'c': 3, 'd': 'eggs'} Mock subclasses and their attributes¶There are various reasons why you might want to subclass >>> class MyMock(MagicMock): ... def has_been_called(self): ... return self.called ... >>> mymock = MyMock(return_value=None) >>> mymock <MyMock id='...'> >>> mymock.has_been_called() False >>> mymock() >>> mymock.has_been_called() True The standard behaviour for
>>> mymock.foo <MyMock name='mock.foo' id='...'> >>> mymock.foo.has_been_called() False >>> mymock.foo() <MyMock name='mock.foo()' id='...'> >>> mymock.foo.has_been_called() True Sometimes this is inconvenient. For example, one user is subclassing mock to created a Twisted adaptor. Having this applied to attributes too actually causes errors.
>>> class Subclass(MagicMock): ... def _get_child_mock(self, /, **kwargs): ... return MagicMock(**kwargs) ... >>> mymock = Subclass() >>> mymock.foo <MagicMock name='mock.foo' id='...'> >>> assert isinstance(mymock, Subclass) >>> assert not isinstance(mymock.foo, Subclass) >>> assert not isinstance(mymock(), Subclass)2 An exception to this rule are the non-callable mocks. Attributes use the callable variant because otherwise non-callable mocks couldn’t have callable methods. Mocking imports with patch.dict¶One situation where mocking can be hard is where you have a local import inside a function. These are harder to mock because they aren’t using an object from the module namespace that we can patch out. Generally local imports are to be avoided. They are sometimes done to prevent circular dependencies, for which there is usually a much better way to solve the problem (refactor the code) or to prevent “up front costs” by delaying the import. This can also be solved in better ways than an unconditional local import (store the module as a class or module attribute and only do the import on first use). That aside there is a way to use This means you can use
Here’s an example that mocks out the ‘fooble’ module. >>> import sys >>> mock = Mock() >>> with patch.dict('sys.modules', {'fooble': mock}): ... import fooble ... fooble.blob() ... <Mock name='mock.blob()' id='...'> >>> assert 'fooble' not in sys.modules >>> mock.blob.assert_called_once_with() As you can see the This also works for the >>> mock = Mock() >>> with patch.dict('sys.modules', {'fooble': mock}): ... from fooble import blob ... blob.blip() ... <Mock name='mock.blob.blip()' id='...'> >>> mock.blob.blip.assert_called_once_with() With slightly more work you can also mock package imports: >>> mock = Mock() >>> modules = {'package': mock, 'package.module': mock.module} >>> with patch.dict('sys.modules', modules): ... from package.module import fooble ... fooble() ... <Mock name='mock.module.fooble()' id='...'> >>> mock.module.fooble.assert_called_once_with() Tracking order of calls and less verbose call assertions¶The Because mocks track calls to child mocks in >>> manager = Mock() >>> mock_foo = manager.foo >>> mock_bar = manager.bar >>> mock_foo.something() <Mock name='mock.foo.something()' id='...'> >>> mock_bar.other.thing() <Mock name='mock.bar.other.thing()' id='...'> >>> manager.mock_calls [call.foo.something(), call.bar.other.thing()] We can then assert about the calls, including the order, by comparing with the >>> expected_calls = [call.foo.something(), call.bar.other.thing()] >>> manager.mock_calls == expected_calls True If >>> manager = MagicMock() >>> with patch('mymodule.Class1') as MockClass1: ... with patch('mymodule.Class2') as MockClass2: ... manager.attach_mock(MockClass1, 'MockClass1') ... manager.attach_mock(MockClass2, 'MockClass2') ... MockClass1().foo() ... MockClass2().bar() <MagicMock name='mock.MockClass1().foo()' id='...'> <MagicMock name='mock.MockClass2().bar()' id='...'> >>> manager.mock_calls [call.MockClass1(), call.MockClass1().foo(), call.MockClass2(), call.MockClass2().bar()] If many calls have been made, but you’re only interested in a particular sequence of them then an alternative is to use
the >>> m = MagicMock() >>> m().foo().bar().baz() <MagicMock name='mock().foo().bar().baz()' id='...'> >>> m.one().two().three() <MagicMock name='mock.one().two().three()' id='...'> >>> calls = call.one().two().three().call_list() >>> m.assert_has_calls(calls) Even though the chained call Sometimes a mock may have several calls made to it, and you are only interested in asserting about some of those calls. You may not even care about the
order. In this case you can pass >>> m = MagicMock() >>> m(1), m.two(2, 3), m.seven(7), m.fifty('50') (...) >>> calls = [call.fifty('50'), call(1), call.seven(7)] >>> m.assert_has_calls(calls, any_order=True) More complex argument matching¶Using the same basic concept as Suppose we expect some object to be passed to a mock that by default compares equal based on object identity (which is the Python default for user defined classes). To use You can see in this example how a ‘standard’ call to >>> class Foo: ... def __init__(self, a, b): ... self.a, self.b = a, b ... >>> mock = Mock(return_value=None) >>> mock(Foo(1, 2)) >>> mock.assert_called_with(Foo(1, 2)) Traceback (most recent call last): ... AssertionError: Expected: call(<__main__.Foo object at 0x...>) Actual call: call(<__main__.Foo object at 0x...>) A comparison function for our >>> def compare(self, other): ... if not type(self) == type(other): ... return False ... if self.a != other.a: ... return False ... if self.b != other.b: ... return False ... return True ... And a matcher object that can use comparison functions like this for its equality operation would look something like this: >>> class Matcher: ... def __init__(self, compare, some_obj): ... self.compare = compare ... self.some_obj = some_obj ... def __eq__(self, other): ... return self.compare(self.some_obj, other) ... Putting all this together: >>> match_foo = Matcher(compare, Foo(1, 2)) >>> mock.assert_called_with(match_foo) The >>> match_wrong = Matcher(compare, Foo(3, 4)) >>> mock.assert_called_with(match_wrong) Traceback (most recent call last): ... AssertionError: Expected: ((<Matcher object at 0x...>,), {}) Called with: ((<Foo object at 0x...>,), {}) With a bit of tweaking you could have the comparison function raise the As of version 1.5, the Python testing library PyHamcrest provides similar functionality, that may be useful here, in the form of its equality matcher (hamcrest.library.integration.match_equality). |