python/mock-1.0.0/docs/examples.txt

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1 .. _further-examples:
2
3 ==================
4 Further Examples
5 ==================
6
7 .. currentmodule:: mock
8
9 .. testsetup::
10
11 from datetime import date
12
13 BackendProvider = Mock()
14 sys.modules['mymodule'] = mymodule = Mock(name='mymodule')
15
16 def grob(val):
17 "First frob and then clear val"
18 mymodule.frob(val)
19 val.clear()
20
21 mymodule.frob = lambda val: val
22 mymodule.grob = grob
23 mymodule.date = date
24
25 class TestCase(unittest2.TestCase):
26 def run(self):
27 result = unittest2.TestResult()
28 out = unittest2.TestCase.run(self, result)
29 assert result.wasSuccessful()
30
31 from mock import inPy3k
32
33
34
35 For comprehensive examples, see the unit tests included in the full source
36 distribution.
37
38 Here are some more examples for some slightly more advanced scenarios than in
39 the :ref:`getting started <getting-started>` guide.
40
41
42 Mocking chained calls
43 =====================
44
45 Mocking chained calls is actually straightforward with mock once you
46 understand the :attr:`~Mock.return_value` attribute. When a mock is called for
47 the first time, or you fetch its `return_value` before it has been called, a
48 new `Mock` is created.
49
50 This means that you can see how the object returned from a call to a mocked
51 object has been used by interrogating the `return_value` mock:
52
53 .. doctest::
54
55 >>> mock = Mock()
56 >>> mock().foo(a=2, b=3)
57 <Mock name='mock().foo()' id='...'>
58 >>> mock.return_value.foo.assert_called_with(a=2, b=3)
59
60 From here it is a simple step to configure and then make assertions about
61 chained calls. Of course another alternative is writing your code in a more
62 testable way in the first place...
63
64 So, suppose we have some code that looks a little bit like this:
65
66 .. doctest::
67
68 >>> class Something(object):
69 ... def __init__(self):
70 ... self.backend = BackendProvider()
71 ... def method(self):
72 ... response = self.backend.get_endpoint('foobar').create_call('spam', 'eggs').start_call()
73 ... # more code
74
75 Assuming that `BackendProvider` is already well tested, how do we test
76 `method()`? Specifically, we want to test that the code section `# more
77 code` uses the response object in the correct way.
78
79 As this chain of calls is made from an instance attribute we can monkey patch
80 the `backend` attribute on a `Something` instance. In this particular case
81 we are only interested in the return value from the final call to
82 `start_call` so we don't have much configuration to do. Let's assume the
83 object it returns is 'file-like', so we'll ensure that our response object
84 uses the builtin `file` as its `spec`.
85
86 To do this we create a mock instance as our mock backend and create a mock
87 response object for it. To set the response as the return value for that final
88 `start_call` we could do this:
89
90 `mock_backend.get_endpoint.return_value.create_call.return_value.start_call.return_value = mock_response`.
91
92 We can do that in a slightly nicer way using the :meth:`~Mock.configure_mock`
93 method to directly set the return value for us:
94
95 .. doctest::
96
97 >>> something = Something()
98 >>> mock_response = Mock(spec=file)
99 >>> mock_backend = Mock()
100 >>> config = {'get_endpoint.return_value.create_call.return_value.start_call.return_value': mock_response}
101 >>> mock_backend.configure_mock(**config)
102
103 With these we monkey patch the "mock backend" in place and can make the real
104 call:
105
106 .. doctest::
107
108 >>> something.backend = mock_backend
109 >>> something.method()
110
111 Using :attr:`~Mock.mock_calls` we can check the chained call with a single
112 assert. A chained call is several calls in one line of code, so there will be
113 several entries in `mock_calls`. We can use :meth:`call.call_list` to create
114 this list of calls for us:
115
116 .. doctest::
117
118 >>> chained = call.get_endpoint('foobar').create_call('spam', 'eggs').start_call()
119 >>> call_list = chained.call_list()
120 >>> assert mock_backend.mock_calls == call_list
121
122
123 Partial mocking
124 ===============
125
126 In some tests I wanted to mock out a call to `datetime.date.today()
127 <http://docs.python.org/library/datetime.html#datetime.date.today>`_ to return
128 a known date, but I didn't want to prevent the code under test from
129 creating new date objects. Unfortunately `datetime.date` is written in C, and
130 so I couldn't just monkey-patch out the static `date.today` method.
131
132 I found a simple way of doing this that involved effectively wrapping the date
133 class with a mock, but passing through calls to the constructor to the real
134 class (and returning real instances).
135
136 The :func:`patch decorator <patch>` is used here to
137 mock out the `date` class in the module under test. The :attr:`side_effect`
138 attribute on the mock date class is then set to a lambda function that returns
139 a real date. When the mock date class is called a real date will be
140 constructed and returned by `side_effect`.
141
142 .. doctest::
143
144 >>> from datetime import date
145 >>> with patch('mymodule.date') as mock_date:
146 ... mock_date.today.return_value = date(2010, 10, 8)
147 ... mock_date.side_effect = lambda *args, **kw: date(*args, **kw)
148 ...
149 ... assert mymodule.date.today() == date(2010, 10, 8)
150 ... assert mymodule.date(2009, 6, 8) == date(2009, 6, 8)
151 ...
152
153 Note that we don't patch `datetime.date` globally, we patch `date` in the
154 module that *uses* it. See :ref:`where to patch <where-to-patch>`.
155
156 When `date.today()` is called a known date is returned, but calls to the
157 `date(...)` constructor still return normal dates. Without this you can find
158 yourself having to calculate an expected result using exactly the same
159 algorithm as the code under test, which is a classic testing anti-pattern.
160
161 Calls to the date constructor are recorded in the `mock_date` attributes
162 (`call_count` and friends) which may also be useful for your tests.
163
164 An alternative way of dealing with mocking dates, or other builtin classes,
165 is discussed in `this blog entry
166 <http://williamjohnbert.com/2011/07/how-to-unit-testing-in-django-with-mocking-and-patching/>`_.
167
168
169 Mocking a Generator Method
170 ==========================
171
172 A Python generator is a function or method that uses the `yield statement
173 <http://docs.python.org/reference/simple_stmts.html#the-yield-statement>`_ to
174 return a series of values when iterated over [#]_.
175
176 A generator method / function is called to return the generator object. It is
177 the generator object that is then iterated over. The protocol method for
178 iteration is `__iter__
179 <http://docs.python.org/library/stdtypes.html#container.__iter__>`_, so we can
180 mock this using a `MagicMock`.
181
182 Here's an example class with an "iter" method implemented as a generator:
183
184 .. doctest::
185
186 >>> class Foo(object):
187 ... def iter(self):
188 ... for i in [1, 2, 3]:
189 ... yield i
190 ...
191 >>> foo = Foo()
192 >>> list(foo.iter())
193 [1, 2, 3]
194
195
196 How would we mock this class, and in particular its "iter" method?
197
198 To configure the values returned from the iteration (implicit in the call to
199 `list`), we need to configure the object returned by the call to `foo.iter()`.
200
201 .. doctest::
202
203 >>> mock_foo = MagicMock()
204 >>> mock_foo.iter.return_value = iter([1, 2, 3])
205 >>> list(mock_foo.iter())
206 [1, 2, 3]
207
208 .. [#] There are also generator expressions and more `advanced uses
209 <http://www.dabeaz.com/coroutines/index.html>`_ of generators, but we aren't
210 concerned about them here. A very good introduction to generators and how
211 powerful they are is: `Generator Tricks for Systems Programmers
212 <http://www.dabeaz.com/generators/>`_.
213
214
215 Applying the same patch to every test method
216 ============================================
217
218 If you want several patches in place for multiple test methods the obvious way
219 is to apply the patch decorators to every method. This can feel like unnecessary
220 repetition. For Python 2.6 or more recent you can use `patch` (in all its
221 various forms) as a class decorator. This applies the patches to all test
222 methods on the class. A test method is identified by methods whose names start
223 with `test`:
224
225 .. doctest::
226
227 >>> @patch('mymodule.SomeClass')
228 ... class MyTest(TestCase):
229 ...
230 ... def test_one(self, MockSomeClass):
231 ... self.assertTrue(mymodule.SomeClass is MockSomeClass)
232 ...
233 ... def test_two(self, MockSomeClass):
234 ... self.assertTrue(mymodule.SomeClass is MockSomeClass)
235 ...
236 ... def not_a_test(self):
237 ... return 'something'
238 ...
239 >>> MyTest('test_one').test_one()
240 >>> MyTest('test_two').test_two()
241 >>> MyTest('test_two').not_a_test()
242 'something'
243
244 An alternative way of managing patches is to use the :ref:`start-and-stop`.
245 These allow you to move the patching into your `setUp` and `tearDown` methods.
246
247 .. doctest::
248
249 >>> class MyTest(TestCase):
250 ... def setUp(self):
251 ... self.patcher = patch('mymodule.foo')
252 ... self.mock_foo = self.patcher.start()
253 ...
254 ... def test_foo(self):
255 ... self.assertTrue(mymodule.foo is self.mock_foo)
256 ...
257 ... def tearDown(self):
258 ... self.patcher.stop()
259 ...
260 >>> MyTest('test_foo').run()
261
262 If you use this technique you must ensure that the patching is "undone" by
263 calling `stop`. This can be fiddlier than you might think, because if an
264 exception is raised in the setUp then tearDown is not called. `unittest2
265 <http://pypi.python.org/pypi/unittest2>`_ cleanup functions make this simpler:
266
267
268 .. doctest::
269
270 >>> class MyTest(TestCase):
271 ... def setUp(self):
272 ... patcher = patch('mymodule.foo')
273 ... self.addCleanup(patcher.stop)
274 ... self.mock_foo = patcher.start()
275 ...
276 ... def test_foo(self):
277 ... self.assertTrue(mymodule.foo is self.mock_foo)
278 ...
279 >>> MyTest('test_foo').run()
280
281
282 Mocking Unbound Methods
283 =======================
284
285 Whilst writing tests today I needed to patch an *unbound method* (patching the
286 method on the class rather than on the instance). I needed self to be passed
287 in as the first argument because I want to make asserts about which objects
288 were calling this particular method. The issue is that you can't patch with a
289 mock for this, because if you replace an unbound method with a mock it doesn't
290 become a bound method when fetched from the instance, and so it doesn't get
291 self passed in. The workaround is to patch the unbound method with a real
292 function instead. The :func:`patch` decorator makes it so simple to
293 patch out methods with a mock that having to create a real function becomes a
294 nuisance.
295
296 If you pass `autospec=True` to patch then it does the patching with a
297 *real* function object. This function object has the same signature as the one
298 it is replacing, but delegates to a mock under the hood. You still get your
299 mock auto-created in exactly the same way as before. What it means though, is
300 that if you use it to patch out an unbound method on a class the mocked
301 function will be turned into a bound method if it is fetched from an instance.
302 It will have `self` passed in as the first argument, which is exactly what I
303 wanted:
304
305 .. doctest::
306
307 >>> class Foo(object):
308 ... def foo(self):
309 ... pass
310 ...
311 >>> with patch.object(Foo, 'foo', autospec=True) as mock_foo:
312 ... mock_foo.return_value = 'foo'
313 ... foo = Foo()
314 ... foo.foo()
315 ...
316 'foo'
317 >>> mock_foo.assert_called_once_with(foo)
318
319 If we don't use `autospec=True` then the unbound method is patched out
320 with a Mock instance instead, and isn't called with `self`.
321
322
323 Checking multiple calls with mock
324 =================================
325
326 mock has a nice API for making assertions about how your mock objects are used.
327
328 .. doctest::
329
330 >>> mock = Mock()
331 >>> mock.foo_bar.return_value = None
332 >>> mock.foo_bar('baz', spam='eggs')
333 >>> mock.foo_bar.assert_called_with('baz', spam='eggs')
334
335 If your mock is only being called once you can use the
336 :meth:`assert_called_once_with` method that also asserts that the
337 :attr:`call_count` is one.
338
339 .. doctest::
340
341 >>> mock.foo_bar.assert_called_once_with('baz', spam='eggs')
342 >>> mock.foo_bar()
343 >>> mock.foo_bar.assert_called_once_with('baz', spam='eggs')
344 Traceback (most recent call last):
345 ...
346 AssertionError: Expected to be called once. Called 2 times.
347
348 Both `assert_called_with` and `assert_called_once_with` make assertions about
349 the *most recent* call. If your mock is going to be called several times, and
350 you want to make assertions about *all* those calls you can use
351 :attr:`~Mock.call_args_list`:
352
353 .. doctest::
354
355 >>> mock = Mock(return_value=None)
356 >>> mock(1, 2, 3)
357 >>> mock(4, 5, 6)
358 >>> mock()
359 >>> mock.call_args_list
360 [call(1, 2, 3), call(4, 5, 6), call()]
361
362 The :data:`call` helper makes it easy to make assertions about these calls. You
363 can build up a list of expected calls and compare it to `call_args_list`. This
364 looks remarkably similar to the repr of the `call_args_list`:
365
366 .. doctest::
367
368 >>> expected = [call(1, 2, 3), call(4, 5, 6), call()]
369 >>> mock.call_args_list == expected
370 True
371
372
373 Coping with mutable arguments
374 =============================
375
376 Another situation is rare, but can bite you, is when your mock is called with
377 mutable arguments. `call_args` and `call_args_list` store *references* to the
378 arguments. If the arguments are mutated by the code under test then you can no
379 longer make assertions about what the values were when the mock was called.
380
381 Here's some example code that shows the problem. Imagine the following functions
382 defined in 'mymodule'::
383
384 def frob(val):
385 pass
386
387 def grob(val):
388 "First frob and then clear val"
389 frob(val)
390 val.clear()
391
392 When we try to test that `grob` calls `frob` with the correct argument look
393 what happens:
394
395 .. doctest::
396
397 >>> with patch('mymodule.frob') as mock_frob:
398 ... val = set([6])
399 ... mymodule.grob(val)
400 ...
401 >>> val
402 set([])
403 >>> mock_frob.assert_called_with(set([6]))
404 Traceback (most recent call last):
405 ...
406 AssertionError: Expected: ((set([6]),), {})
407 Called with: ((set([]),), {})
408
409 One possibility would be for mock to copy the arguments you pass in. This
410 could then cause problems if you do assertions that rely on object identity
411 for equality.
412
413 Here's one solution that uses the :attr:`side_effect`
414 functionality. If you provide a `side_effect` function for a mock then
415 `side_effect` will be called with the same args as the mock. This gives us an
416 opportunity to copy the arguments and store them for later assertions. In this
417 example I'm using *another* mock to store the arguments so that I can use the
418 mock methods for doing the assertion. Again a helper function sets this up for
419 me.
420
421 .. doctest::
422
423 >>> from copy import deepcopy
424 >>> from mock import Mock, patch, DEFAULT
425 >>> def copy_call_args(mock):
426 ... new_mock = Mock()
427 ... def side_effect(*args, **kwargs):
428 ... args = deepcopy(args)
429 ... kwargs = deepcopy(kwargs)
430 ... new_mock(*args, **kwargs)
431 ... return DEFAULT
432 ... mock.side_effect = side_effect
433 ... return new_mock
434 ...
435 >>> with patch('mymodule.frob') as mock_frob:
436 ... new_mock = copy_call_args(mock_frob)
437 ... val = set([6])
438 ... mymodule.grob(val)
439 ...
440 >>> new_mock.assert_called_with(set([6]))
441 >>> new_mock.call_args
442 call(set([6]))
443
444 `copy_call_args` is called with the mock that will be called. It returns a new
445 mock that we do the assertion on. The `side_effect` function makes a copy of
446 the args and calls our `new_mock` with the copy.
447
448 .. note::
449
450 If your mock is only going to be used once there is an easier way of
451 checking arguments at the point they are called. You can simply do the
452 checking inside a `side_effect` function.
453
454 .. doctest::
455
456 >>> def side_effect(arg):
457 ... assert arg == set([6])
458 ...
459 >>> mock = Mock(side_effect=side_effect)
460 >>> mock(set([6]))
461 >>> mock(set())
462 Traceback (most recent call last):
463 ...
464 AssertionError
465
466 An alternative approach is to create a subclass of `Mock` or `MagicMock` that
467 copies (using `copy.deepcopy
468 <http://docs.python.org/library/copy.html#copy.deepcopy>`_) the arguments.
469 Here's an example implementation:
470
471 .. doctest::
472
473 >>> from copy import deepcopy
474 >>> class CopyingMock(MagicMock):
475 ... def __call__(self, *args, **kwargs):
476 ... args = deepcopy(args)
477 ... kwargs = deepcopy(kwargs)
478 ... return super(CopyingMock, self).__call__(*args, **kwargs)
479 ...
480 >>> c = CopyingMock(return_value=None)
481 >>> arg = set()
482 >>> c(arg)
483 >>> arg.add(1)
484 >>> c.assert_called_with(set())
485 >>> c.assert_called_with(arg)
486 Traceback (most recent call last):
487 ...
488 AssertionError: Expected call: mock(set([1]))
489 Actual call: mock(set([]))
490 >>> c.foo
491 <CopyingMock name='mock.foo' id='...'>
492
493 When you subclass `Mock` or `MagicMock` all dynamically created attributes,
494 and the `return_value` will use your subclass automatically. That means all
495 children of a `CopyingMock` will also have the type `CopyingMock`.
496
497
498 Raising exceptions on attribute access
499 ======================================
500
501 You can use :class:`PropertyMock` to mimic the behaviour of properties. This
502 includes raising exceptions when an attribute is accessed.
503
504 Here's an example raising a `ValueError` when the 'foo' attribute is accessed:
505
506 .. doctest::
507
508 >>> m = MagicMock()
509 >>> p = PropertyMock(side_effect=ValueError)
510 >>> type(m).foo = p
511 >>> m.foo
512 Traceback (most recent call last):
513 ....
514 ValueError
515
516 Because every mock object has its own type, a new subclass of whichever mock
517 class you're using, all mock objects are isolated from each other. You can
518 safely attach properties (or other descriptors or whatever you want in fact)
519 to `type(mock)` without affecting other mock objects.
520
521
522 Multiple calls with different effects
523 =====================================
524
525 .. note::
526
527 In mock 1.0 the handling of iterable `side_effect` was changed. Any
528 exceptions in the iterable will be raised instead of returned.
529
530 Handling code that needs to behave differently on subsequent calls during the
531 test can be tricky. For example you may have a function that needs to raise
532 an exception the first time it is called but returns a response on the second
533 call (testing retry behaviour).
534
535 One approach is to use a :attr:`side_effect` function that replaces itself. The
536 first time it is called the `side_effect` sets a new `side_effect` that will
537 be used for the second call. It then raises an exception:
538
539 .. doctest::
540
541 >>> def side_effect(*args):
542 ... def second_call(*args):
543 ... return 'response'
544 ... mock.side_effect = second_call
545 ... raise Exception('boom')
546 ...
547 >>> mock = Mock(side_effect=side_effect)
548 >>> mock('first')
549 Traceback (most recent call last):
550 ...
551 Exception: boom
552 >>> mock('second')
553 'response'
554 >>> mock.assert_called_with('second')
555
556 Another perfectly valid way would be to pop return values from a list. If the
557 return value is an exception, raise it instead of returning it:
558
559 .. doctest::
560
561 >>> returns = [Exception('boom'), 'response']
562 >>> def side_effect(*args):
563 ... result = returns.pop(0)
564 ... if isinstance(result, Exception):
565 ... raise result
566 ... return result
567 ...
568 >>> mock = Mock(side_effect=side_effect)
569 >>> mock('first')
570 Traceback (most recent call last):
571 ...
572 Exception: boom
573 >>> mock('second')
574 'response'
575 >>> mock.assert_called_with('second')
576
577 Which approach you prefer is a matter of taste. The first approach is actually
578 a line shorter but maybe the second approach is more readable.
579
580
581 Nesting Patches
582 ===============
583
584 Using patch as a context manager is nice, but if you do multiple patches you
585 can end up with nested with statements indenting further and further to the
586 right:
587
588 .. doctest::
589
590 >>> class MyTest(TestCase):
591 ...
592 ... def test_foo(self):
593 ... with patch('mymodule.Foo') as mock_foo:
594 ... with patch('mymodule.Bar') as mock_bar:
595 ... with patch('mymodule.Spam') as mock_spam:
596 ... assert mymodule.Foo is mock_foo
597 ... assert mymodule.Bar is mock_bar
598 ... assert mymodule.Spam is mock_spam
599 ...
600 >>> original = mymodule.Foo
601 >>> MyTest('test_foo').test_foo()
602 >>> assert mymodule.Foo is original
603
604 With unittest2_ `cleanup` functions and the :ref:`start-and-stop` we can
605 achieve the same effect without the nested indentation. A simple helper
606 method, `create_patch`, puts the patch in place and returns the created mock
607 for us:
608
609 .. doctest::
610
611 >>> class MyTest(TestCase):
612 ...
613 ... def create_patch(self, name):
614 ... patcher = patch(name)
615 ... thing = patcher.start()
616 ... self.addCleanup(patcher.stop)
617 ... return thing
618 ...
619 ... def test_foo(self):
620 ... mock_foo = self.create_patch('mymodule.Foo')
621 ... mock_bar = self.create_patch('mymodule.Bar')
622 ... mock_spam = self.create_patch('mymodule.Spam')
623 ...
624 ... assert mymodule.Foo is mock_foo
625 ... assert mymodule.Bar is mock_bar
626 ... assert mymodule.Spam is mock_spam
627 ...
628 >>> original = mymodule.Foo
629 >>> MyTest('test_foo').run()
630 >>> assert mymodule.Foo is original
631
632
633 Mocking a dictionary with MagicMock
634 ===================================
635
636 You may want to mock a dictionary, or other container object, recording all
637 access to it whilst having it still behave like a dictionary.
638
639 We can do this with :class:`MagicMock`, which will behave like a dictionary,
640 and using :data:`~Mock.side_effect` to delegate dictionary access to a real
641 underlying dictionary that is under our control.
642
643 When the `__getitem__` and `__setitem__` methods of our `MagicMock` are called
644 (normal dictionary access) then `side_effect` is called with the key (and in
645 the case of `__setitem__` the value too). We can also control what is returned.
646
647 After the `MagicMock` has been used we can use attributes like
648 :data:`~Mock.call_args_list` to assert about how the dictionary was used:
649
650 .. doctest::
651
652 >>> my_dict = {'a': 1, 'b': 2, 'c': 3}
653 >>> def getitem(name):
654 ... return my_dict[name]
655 ...
656 >>> def setitem(name, val):
657 ... my_dict[name] = val
658 ...
659 >>> mock = MagicMock()
660 >>> mock.__getitem__.side_effect = getitem
661 >>> mock.__setitem__.side_effect = setitem
662
663 .. note::
664
665 An alternative to using `MagicMock` is to use `Mock` and *only* provide
666 the magic methods you specifically want:
667
668 .. doctest::
669
670 >>> mock = Mock()
671 >>> mock.__setitem__ = Mock(side_effect=getitem)
672 >>> mock.__getitem__ = Mock(side_effect=setitem)
673
674 A *third* option is to use `MagicMock` but passing in `dict` as the `spec`
675 (or `spec_set`) argument so that the `MagicMock` created only has
676 dictionary magic methods available:
677
678 .. doctest::
679
680 >>> mock = MagicMock(spec_set=dict)
681 >>> mock.__getitem__.side_effect = getitem
682 >>> mock.__setitem__.side_effect = setitem
683
684 With these side effect functions in place, the `mock` will behave like a normal
685 dictionary but recording the access. It even raises a `KeyError` if you try
686 to access a key that doesn't exist.
687
688 .. doctest::
689
690 >>> mock['a']
691 1
692 >>> mock['c']
693 3
694 >>> mock['d']
695 Traceback (most recent call last):
696 ...
697 KeyError: 'd'
698 >>> mock['b'] = 'fish'
699 >>> mock['d'] = 'eggs'
700 >>> mock['b']
701 'fish'
702 >>> mock['d']
703 'eggs'
704
705 After it has been used you can make assertions about the access using the normal
706 mock methods and attributes:
707
708 .. doctest::
709
710 >>> mock.__getitem__.call_args_list
711 [call('a'), call('c'), call('d'), call('b'), call('d')]
712 >>> mock.__setitem__.call_args_list
713 [call('b', 'fish'), call('d', 'eggs')]
714 >>> my_dict
715 {'a': 1, 'c': 3, 'b': 'fish', 'd': 'eggs'}
716
717
718 Mock subclasses and their attributes
719 ====================================
720
721 There are various reasons why you might want to subclass `Mock`. One reason
722 might be to add helper methods. Here's a silly example:
723
724 .. doctest::
725
726 >>> class MyMock(MagicMock):
727 ... def has_been_called(self):
728 ... return self.called
729 ...
730 >>> mymock = MyMock(return_value=None)
731 >>> mymock
732 <MyMock id='...'>
733 >>> mymock.has_been_called()
734 False
735 >>> mymock()
736 >>> mymock.has_been_called()
737 True
738
739 The standard behaviour for `Mock` instances is that attributes and the return
740 value mocks are of the same type as the mock they are accessed on. This ensures
741 that `Mock` attributes are `Mocks` and `MagicMock` attributes are `MagicMocks`
742 [#]_. So if you're subclassing to add helper methods then they'll also be
743 available on the attributes and return value mock of instances of your
744 subclass.
745
746 .. doctest::
747
748 >>> mymock.foo
749 <MyMock name='mock.foo' id='...'>
750 >>> mymock.foo.has_been_called()
751 False
752 >>> mymock.foo()
753 <MyMock name='mock.foo()' id='...'>
754 >>> mymock.foo.has_been_called()
755 True
756
757 Sometimes this is inconvenient. For example, `one user
758 <https://code.google.com/p/mock/issues/detail?id=105>`_ is subclassing mock to
759 created a `Twisted adaptor
760 <http://twistedmatrix.com/documents/11.0.0/api/twisted.python.components.html>`_.
761 Having this applied to attributes too actually causes errors.
762
763 `Mock` (in all its flavours) uses a method called `_get_child_mock` to create
764 these "sub-mocks" for attributes and return values. You can prevent your
765 subclass being used for attributes by overriding this method. The signature is
766 that it takes arbitrary keyword arguments (`**kwargs`) which are then passed
767 onto the mock constructor:
768
769 .. doctest::
770
771 >>> class Subclass(MagicMock):
772 ... def _get_child_mock(self, **kwargs):
773 ... return MagicMock(**kwargs)
774 ...
775 >>> mymock = Subclass()
776 >>> mymock.foo
777 <MagicMock name='mock.foo' id='...'>
778 >>> assert isinstance(mymock, Subclass)
779 >>> assert not isinstance(mymock.foo, Subclass)
780 >>> assert not isinstance(mymock(), Subclass)
781
782 .. [#] An exception to this rule are the non-callable mocks. Attributes use the
783 callable variant because otherwise non-callable mocks couldn't have callable
784 methods.
785
786
787 Mocking imports with patch.dict
788 ===============================
789
790 One situation where mocking can be hard is where you have a local import inside
791 a function. These are harder to mock because they aren't using an object from
792 the module namespace that we can patch out.
793
794 Generally local imports are to be avoided. They are sometimes done to prevent
795 circular dependencies, for which there is *usually* a much better way to solve
796 the problem (refactor the code) or to prevent "up front costs" by delaying the
797 import. This can also be solved in better ways than an unconditional local
798 import (store the module as a class or module attribute and only do the import
799 on first use).
800
801 That aside there is a way to use `mock` to affect the results of an import.
802 Importing fetches an *object* from the `sys.modules` dictionary. Note that it
803 fetches an *object*, which need not be a module. Importing a module for the
804 first time results in a module object being put in `sys.modules`, so usually
805 when you import something you get a module back. This need not be the case
806 however.
807
808 This means you can use :func:`patch.dict` to *temporarily* put a mock in place
809 in `sys.modules`. Any imports whilst this patch is active will fetch the mock.
810 When the patch is complete (the decorated function exits, the with statement
811 body is complete or `patcher.stop()` is called) then whatever was there
812 previously will be restored safely.
813
814 Here's an example that mocks out the 'fooble' module.
815
816 .. doctest::
817
818 >>> mock = Mock()
819 >>> with patch.dict('sys.modules', {'fooble': mock}):
820 ... import fooble
821 ... fooble.blob()
822 ...
823 <Mock name='mock.blob()' id='...'>
824 >>> assert 'fooble' not in sys.modules
825 >>> mock.blob.assert_called_once_with()
826
827 As you can see the `import fooble` succeeds, but on exit there is no 'fooble'
828 left in `sys.modules`.
829
830 This also works for the `from module import name` form:
831
832 .. doctest::
833
834 >>> mock = Mock()
835 >>> with patch.dict('sys.modules', {'fooble': mock}):
836 ... from fooble import blob
837 ... blob.blip()
838 ...
839 <Mock name='mock.blob.blip()' id='...'>
840 >>> mock.blob.blip.assert_called_once_with()
841
842 With slightly more work you can also mock package imports:
843
844 .. doctest::
845
846 >>> mock = Mock()
847 >>> modules = {'package': mock, 'package.module': mock.module}
848 >>> with patch.dict('sys.modules', modules):
849 ... from package.module import fooble
850 ... fooble()
851 ...
852 <Mock name='mock.module.fooble()' id='...'>
853 >>> mock.module.fooble.assert_called_once_with()
854
855
856 Tracking order of calls and less verbose call assertions
857 ========================================================
858
859 The :class:`Mock` class allows you to track the *order* of method calls on
860 your mock objects through the :attr:`~Mock.method_calls` attribute. This
861 doesn't allow you to track the order of calls between separate mock objects,
862 however we can use :attr:`~Mock.mock_calls` to achieve the same effect.
863
864 Because mocks track calls to child mocks in `mock_calls`, and accessing an
865 arbitrary attribute of a mock creates a child mock, we can create our separate
866 mocks from a parent one. Calls to those child mock will then all be recorded,
867 in order, in the `mock_calls` of the parent:
868
869 .. doctest::
870
871 >>> manager = Mock()
872 >>> mock_foo = manager.foo
873 >>> mock_bar = manager.bar
874
875 >>> mock_foo.something()
876 <Mock name='mock.foo.something()' id='...'>
877 >>> mock_bar.other.thing()
878 <Mock name='mock.bar.other.thing()' id='...'>
879
880 >>> manager.mock_calls
881 [call.foo.something(), call.bar.other.thing()]
882
883 We can then assert about the calls, including the order, by comparing with
884 the `mock_calls` attribute on the manager mock:
885
886 .. doctest::
887
888 >>> expected_calls = [call.foo.something(), call.bar.other.thing()]
889 >>> manager.mock_calls == expected_calls
890 True
891
892 If `patch` is creating, and putting in place, your mocks then you can attach
893 them to a manager mock using the :meth:`~Mock.attach_mock` method. After
894 attaching calls will be recorded in `mock_calls` of the manager.
895
896 .. doctest::
897
898 >>> manager = MagicMock()
899 >>> with patch('mymodule.Class1') as MockClass1:
900 ... with patch('mymodule.Class2') as MockClass2:
901 ... manager.attach_mock(MockClass1, 'MockClass1')
902 ... manager.attach_mock(MockClass2, 'MockClass2')
903 ... MockClass1().foo()
904 ... MockClass2().bar()
905 ...
906 <MagicMock name='mock.MockClass1().foo()' id='...'>
907 <MagicMock name='mock.MockClass2().bar()' id='...'>
908 >>> manager.mock_calls
909 [call.MockClass1(),
910 call.MockClass1().foo(),
911 call.MockClass2(),
912 call.MockClass2().bar()]
913
914 If many calls have been made, but you're only interested in a particular
915 sequence of them then an alternative is to use the
916 :meth:`~Mock.assert_has_calls` method. This takes a list of calls (constructed
917 with the :data:`call` object). If that sequence of calls are in
918 :attr:`~Mock.mock_calls` then the assert succeeds.
919
920 .. doctest::
921
922 >>> m = MagicMock()
923 >>> m().foo().bar().baz()
924 <MagicMock name='mock().foo().bar().baz()' id='...'>
925 >>> m.one().two().three()
926 <MagicMock name='mock.one().two().three()' id='...'>
927 >>> calls = call.one().two().three().call_list()
928 >>> m.assert_has_calls(calls)
929
930 Even though the chained call `m.one().two().three()` aren't the only calls that
931 have been made to the mock, the assert still succeeds.
932
933 Sometimes a mock may have several calls made to it, and you are only interested
934 in asserting about *some* of those calls. You may not even care about the
935 order. In this case you can pass `any_order=True` to `assert_has_calls`:
936
937 .. doctest::
938
939 >>> m = MagicMock()
940 >>> m(1), m.two(2, 3), m.seven(7), m.fifty('50')
941 (...)
942 >>> calls = [call.fifty('50'), call(1), call.seven(7)]
943 >>> m.assert_has_calls(calls, any_order=True)
944
945
946 More complex argument matching
947 ==============================
948
949 Using the same basic concept as `ANY` we can implement matchers to do more
950 complex assertions on objects used as arguments to mocks.
951
952 Suppose we expect some object to be passed to a mock that by default
953 compares equal based on object identity (which is the Python default for user
954 defined classes). To use :meth:`~Mock.assert_called_with` we would need to pass
955 in the exact same object. If we are only interested in some of the attributes
956 of this object then we can create a matcher that will check these attributes
957 for us.
958
959 You can see in this example how a 'standard' call to `assert_called_with` isn't
960 sufficient:
961
962 .. doctest::
963
964 >>> class Foo(object):
965 ... def __init__(self, a, b):
966 ... self.a, self.b = a, b
967 ...
968 >>> mock = Mock(return_value=None)
969 >>> mock(Foo(1, 2))
970 >>> mock.assert_called_with(Foo(1, 2))
971 Traceback (most recent call last):
972 ...
973 AssertionError: Expected: call(<__main__.Foo object at 0x...>)
974 Actual call: call(<__main__.Foo object at 0x...>)
975
976 A comparison function for our `Foo` class might look something like this:
977
978 .. doctest::
979
980 >>> def compare(self, other):
981 ... if not type(self) == type(other):
982 ... return False
983 ... if self.a != other.a:
984 ... return False
985 ... if self.b != other.b:
986 ... return False
987 ... return True
988 ...
989
990 And a matcher object that can use comparison functions like this for its
991 equality operation would look something like this:
992
993 .. doctest::
994
995 >>> class Matcher(object):
996 ... def __init__(self, compare, some_obj):
997 ... self.compare = compare
998 ... self.some_obj = some_obj
999 ... def __eq__(self, other):
1000 ... return self.compare(self.some_obj, other)
1001 ...
1002
1003 Putting all this together:
1004
1005 .. doctest::
1006
1007 >>> match_foo = Matcher(compare, Foo(1, 2))
1008 >>> mock.assert_called_with(match_foo)
1009
1010 The `Matcher` is instantiated with our compare function and the `Foo` object
1011 we want to compare against. In `assert_called_with` the `Matcher` equality
1012 method will be called, which compares the object the mock was called with
1013 against the one we created our matcher with. If they match then
1014 `assert_called_with` passes, and if they don't an `AssertionError` is raised:
1015
1016 .. doctest::
1017
1018 >>> match_wrong = Matcher(compare, Foo(3, 4))
1019 >>> mock.assert_called_with(match_wrong)
1020 Traceback (most recent call last):
1021 ...
1022 AssertionError: Expected: ((<Matcher object at 0x...>,), {})
1023 Called with: ((<Foo object at 0x...>,), {})
1024
1025 With a bit of tweaking you could have the comparison function raise the
1026 `AssertionError` directly and provide a more useful failure message.
1027
1028 As of version 1.5, the Python testing library `PyHamcrest
1029 <http://pypi.python.org/pypi/PyHamcrest>`_ provides similar functionality,
1030 that may be useful here, in the form of its equality matcher
1031 (`hamcrest.library.integration.match_equality
1032 <http://packages.python.org/PyHamcrest/integration.html#hamcrest.library.integration.match_equality>`_).
1033
1034
1035 Less verbose configuration of mock objects
1036 ==========================================
1037
1038 This recipe, for easier configuration of mock objects, is now part of `Mock`.
1039 See the :meth:`~Mock.configure_mock` method.
1040
1041
1042 Matching any argument in assertions
1043 ===================================
1044
1045 This example is now built in to mock. See :data:`ANY`.
1046
1047
1048 Mocking Properties
1049 ==================
1050
1051 This example is now built in to mock. See :class:`PropertyMock`.
1052
1053
1054 Mocking open
1055 ============
1056
1057 This example is now built in to mock. See :func:`mock_open`.
1058
1059
1060 Mocks without some attributes
1061 =============================
1062
1063 This example is now built in to mock. See :ref:`deleting-attributes`.

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