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diff --git a/Doc/library/unittest.mock.rst b/Doc/library/unittest.mock.rst new file mode 100644 index 0000000..bed698a --- /dev/null +++ b/Doc/library/unittest.mock.rst @@ -0,0 +1,2225 @@ +:mod:`unittest.mock` --- mock object library +============================================ + +.. module:: unittest.mock + :synopsis: Mock object library. +.. moduleauthor:: Michael Foord <michael@python.org> +.. currentmodule:: unittest.mock + +.. versionadded:: 3.3 + +:mod:`unittest.mock` is a library for testing in Python. It allows you to +replace parts of your system under test with mock objects and make assertions +about how they have been used. + +`unittest.mock` provides a core :class:`Mock` class removing the need to +create a host of stubs throughout your test suite. After performing an +action, you can make assertions about which methods / attributes were used +and arguments they were called with. You can also specify return values and +set needed attributes in the normal way. + +Additionally, mock provides a :func:`patch` decorator that handles patching +module and class level attributes within the scope of a test, along with +:const:`sentinel` for creating unique objects. See the `quick guide`_ for +some examples of how to use :class:`Mock`, :class:`MagicMock` and +:func:`patch`. + +Mock is very easy to use and is designed for use with :mod:`unittest`. Mock +is based on the 'action -> assertion' pattern instead of `'record -> replay'` +used by many mocking frameworks. + +There is a backport of `unittest.mock` for earlier versions of Python, +available as `mock on PyPI <http://pypi.python.org/pypi/mock>`_. + +**Source code:** :source:`Lib/unittest/mock.py` + + +Quick Guide +----------- + +:class:`Mock` and :class:`MagicMock` objects create all attributes and +methods as you access them and store details of how they have been used. You +can configure them, to specify return values or limit what attributes are +available, and then make assertions about how they have been used: + + >>> from unittest.mock import MagicMock + >>> thing = ProductionClass() + >>> thing.method = MagicMock(return_value=3) + >>> thing.method(3, 4, 5, key='value') + 3 + >>> thing.method.assert_called_with(3, 4, 5, key='value') + +:attr:`side_effect` allows you to perform side effects, including raising an +exception when a mock is called: + + >>> mock = Mock(side_effect=KeyError('foo')) + >>> mock() + Traceback (most recent call last): + ... + KeyError: 'foo' + + >>> values = {'a': 1, 'b': 2, 'c': 3} + >>> def side_effect(arg): + ... return values[arg] + ... + >>> mock.side_effect = side_effect + >>> mock('a'), mock('b'), mock('c') + (1, 2, 3) + >>> mock.side_effect = [5, 4, 3, 2, 1] + >>> mock(), mock(), mock() + (5, 4, 3) + +Mock has many other ways you can configure it and control its behaviour. For +example the `spec` argument configures the mock to take its specification +from another object. Attempting to access attributes or methods on the mock +that don't exist on the spec will fail with an `AttributeError`. + +The :func:`patch` decorator / context manager makes it easy to mock classes or +objects in a module under test. The object you specify will be replaced with a +mock (or other object) during the test and restored when the test ends: + + >>> from unittest.mock import patch + >>> @patch('module.ClassName2') + ... @patch('module.ClassName1') + ... def test(MockClass1, MockClass2): + ... module.ClassName1() + ... module.ClassName2() + ... assert MockClass1 is module.ClassName1 + ... assert MockClass2 is module.ClassName2 + ... assert MockClass1.called + ... assert MockClass2.called + ... + >>> test() + +.. note:: + + 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 `module.ClassName1` is passed in first. + + With `patch` it matters that you patch objects in the namespace where they + are looked up. This is normally straightforward, but for a quick guide + read :ref:`where to patch <where-to-patch>`. + +As well as a decorator `patch` can be used as a context manager in a with +statement: + + >>> with patch.object(ProductionClass, 'method', return_value=None) as mock_method: + ... thing = ProductionClass() + ... thing.method(1, 2, 3) + ... + >>> mock_method.assert_called_once_with(1, 2, 3) + + +There is also :func:`patch.dict` for setting values in a dictionary just +during a scope and restoring the dictionary to its original state when the test +ends: + + >>> foo = {'key': 'value'} + >>> original = foo.copy() + >>> with patch.dict(foo, {'newkey': 'newvalue'}, clear=True): + ... assert foo == {'newkey': 'newvalue'} + ... + >>> assert foo == original + +Mock supports the mocking of Python :ref:`magic methods <magic-methods>`. The +easiest way of using magic methods is with the :class:`MagicMock` class. It +allows you to do things like: + + >>> mock = MagicMock() + >>> mock.__str__.return_value = 'foobarbaz' + >>> str(mock) + 'foobarbaz' + >>> mock.__str__.assert_called_with() + +Mock allows you to assign functions (or other Mock instances) to magic methods +and they will be called appropriately. The `MagicMock` class is just a Mock +variant that has all of the magic methods pre-created for you (well, all the +useful ones anyway). + +The following is an example of using magic methods with the ordinary Mock +class: + + >>> mock = Mock() + >>> mock.__str__ = Mock(return_value='wheeeeee') + >>> str(mock) + 'wheeeeee' + +For ensuring that the mock objects in your tests have the same api as the +objects they are replacing, you can use :ref:`auto-speccing <auto-speccing>`. +Auto-speccing can be done through the `autospec` argument to patch, or the +:func:`create_autospec` function. Auto-speccing creates mock objects that +have the same attributes and methods as the objects they are replacing, and +any functions and methods (including constructors) have the same call +signature as the real object. + +This ensures that your mocks will fail in the same way as your production +code if they are used incorrectly: + + >>> from unittest.mock import create_autospec + >>> def function(a, b, c): + ... pass + ... + >>> mock_function = create_autospec(function, return_value='fishy') + >>> mock_function(1, 2, 3) + 'fishy' + >>> mock_function.assert_called_once_with(1, 2, 3) + >>> mock_function('wrong arguments') + Traceback (most recent call last): + ... + TypeError: <lambda>() takes exactly 3 arguments (1 given) + +`create_autospec` can also be used on classes, where it copies the signature of +the `__init__` method, and on callable objects where it copies the signature of +the `__call__` method. + + + +The Mock Class +-------------- + + +`Mock` is a flexible mock object intended to replace the use of stubs and +test doubles throughout your code. Mocks are callable and create attributes as +new mocks when you access them [#]_. Accessing the same attribute will always +return the same mock. Mocks record how you use them, allowing you to make +assertions about what your code has done to them. + +:class:`MagicMock` is a subclass of `Mock` with all the magic methods +pre-created and ready to use. There are also non-callable variants, useful +when you are mocking out objects that aren't callable: +:class:`NonCallableMock` and :class:`NonCallableMagicMock` + +The :func:`patch` decorators makes it easy to temporarily replace classes +in a particular module with a `Mock` object. By default `patch` will create +a `MagicMock` for you. You can specify an alternative class of `Mock` using +the `new_callable` argument to `patch`. + + +.. class:: Mock(spec=None, side_effect=None, return_value=DEFAULT, wraps=None, name=None, spec_set=None, **kwargs) + + Create a new `Mock` object. `Mock` takes several optional arguments + that specify the behaviour of the Mock object: + + * `spec`: This can be either a list of strings or an existing object (a + class or instance) that acts as the specification for the mock object. If + you pass in an object then a list of strings is formed by calling dir on + the object (excluding unsupported magic attributes and methods). + Accessing any attribute not in this list will raise an `AttributeError`. + + If `spec` is an object (rather than a list of strings) then + :attr:`__class__` returns the class of the spec object. This allows mocks + to pass `isinstance` tests. + + * `spec_set`: A stricter variant of `spec`. If used, attempting to *set* + or get an attribute on the mock that isn't on the object passed as + `spec_set` will raise an `AttributeError`. + + * `side_effect`: A function to be called whenever the Mock is called. See + the :attr:`~Mock.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 :data:`DEFAULT`, the return + value of this function is used as the return value. + + Alternatively `side_effect` can be an exception class or instance. In + this case the exception will be raised when the mock is called. + + If `side_effect` is an iterable then each call to the mock will return + the next value from the iterable. + + A `side_effect` can be cleared by setting it to `None`. + + * `return_value`: The value returned when the mock is called. By default + this is a new Mock (created on first access). See the + :attr:`return_value` attribute. + + * `wraps`: Item for the mock object to wrap. If `wraps` is not None then + calling the Mock will pass the call through to the wrapped object + (returning the real result). Attribute access on the mock will return a + Mock object that wraps the corresponding attribute of the wrapped + object (so attempting to access an attribute that doesn't exist will + raise an `AttributeError`). + + If the mock has an explicit `return_value` set then calls are not passed + to the wrapped object and the `return_value` is returned instead. + + * `name`: If the mock has a name then it will be used in the repr of the + mock. This can be useful for debugging. The name is propagated to child + mocks. + + Mocks can also be called with arbitrary keyword arguments. These will be + used to set attributes on the mock after it is created. See the + :meth:`configure_mock` method for details. + + + .. method:: assert_called_with(*args, **kwargs) + + This method is a convenient way of asserting that calls are made in a + particular way: + + >>> mock = Mock() + >>> mock.method(1, 2, 3, test='wow') + <Mock name='mock.method()' id='...'> + >>> mock.method.assert_called_with(1, 2, 3, test='wow') + + + .. method:: assert_called_once_with(*args, **kwargs) + + Assert that the mock was called exactly once and with the specified + arguments. + + >>> mock = Mock(return_value=None) + >>> mock('foo', bar='baz') + >>> mock.assert_called_once_with('foo', bar='baz') + >>> mock('foo', bar='baz') + >>> mock.assert_called_once_with('foo', bar='baz') + Traceback (most recent call last): + ... + AssertionError: Expected to be called once. Called 2 times. + + + .. method:: assert_any_call(*args, **kwargs) + + assert the mock has been called with the specified arguments. + + The assert passes if the mock has *ever* been called, unlike + :meth:`assert_called_with` and :meth:`assert_called_once_with` that + only pass if the call is the most recent one. + + >>> mock = Mock(return_value=None) + >>> mock(1, 2, arg='thing') + >>> mock('some', 'thing', 'else') + >>> mock.assert_any_call(1, 2, arg='thing') + + + .. method:: assert_has_calls(calls, any_order=False) + + assert the mock has been called with the specified calls. + The `mock_calls` list is checked for the calls. + + If `any_order` is False (the default) then the calls must be + sequential. There can be extra calls before or after the + specified calls. + + If `any_order` is True then the calls can be in any order, but + they must all appear in :attr:`mock_calls`. + + >>> mock = Mock(return_value=None) + >>> mock(1) + >>> mock(2) + >>> mock(3) + >>> mock(4) + >>> calls = [call(2), call(3)] + >>> mock.assert_has_calls(calls) + >>> calls = [call(4), call(2), call(3)] + >>> mock.assert_has_calls(calls, any_order=True) + + + .. method:: reset_mock() + + The reset_mock method resets all the call attributes on a mock object: + + >>> mock = Mock(return_value=None) + >>> mock('hello') + >>> mock.called + True + >>> mock.reset_mock() + >>> mock.called + False + + This can be useful where you want to make a series of assertions that + reuse the same object. Note that `reset_mock` *doesn't* clear the + return value, :attr:`side_effect` or any child attributes you have + set using normal assignment. Child mocks and the return value mock + (if any) are reset as well. + + + .. method:: mock_add_spec(spec, spec_set=False) + + Add a spec to a mock. `spec` can either be an object or a + list of strings. Only attributes on the `spec` can be fetched as + attributes from the mock. + + If `spec_set` is `True` then only attributes on the spec can be set. + + + .. method:: attach_mock(mock, attribute) + + Attach a mock as an attribute of this one, replacing its name and + parent. Calls to the attached mock will be recorded in the + :attr:`method_calls` and :attr:`mock_calls` attributes of this one. + + + .. method:: configure_mock(**kwargs) + + Set attributes on the mock through keyword arguments. + + Attributes plus return values and side effects can be set on child + mocks using standard dot notation and unpacking a dictionary in the + method call: + + >>> mock = Mock() + >>> attrs = {'method.return_value': 3, 'other.side_effect': KeyError} + >>> mock.configure_mock(**attrs) + >>> mock.method() + 3 + >>> mock.other() + Traceback (most recent call last): + ... + KeyError + + The same thing can be achieved in the constructor call to mocks: + + >>> attrs = {'method.return_value': 3, 'other.side_effect': KeyError} + >>> mock = Mock(some_attribute='eggs', **attrs) + >>> mock.some_attribute + 'eggs' + >>> mock.method() + 3 + >>> mock.other() + Traceback (most recent call last): + ... + KeyError + + `configure_mock` exists to make it easier to do configuration + after the mock has been created. + + + .. method:: __dir__() + + `Mock` objects limit the results of `dir(some_mock)` to useful results. + For mocks with a `spec` this includes all the permitted attributes + for the mock. + + See :data:`FILTER_DIR` for what this filtering does, and how to + switch it off. + + + .. method:: _get_child_mock(**kw) + + Create the child mocks for attributes and return value. + By default child mocks will be the same type as the parent. + Subclasses of Mock may want to override this to customize the way + child mocks are made. + + For non-callable mocks the callable variant will be used (rather than + any custom subclass). + + + .. attribute:: called + + A boolean representing whether or not the mock object has been called: + + >>> mock = Mock(return_value=None) + >>> mock.called + False + >>> mock() + >>> mock.called + True + + .. attribute:: call_count + + An integer telling you how many times the mock object has been called: + + >>> mock = Mock(return_value=None) + >>> mock.call_count + 0 + >>> mock() + >>> mock() + >>> mock.call_count + 2 + + + .. attribute:: return_value + + Set this to configure the value returned by calling the mock: + + >>> mock = Mock() + >>> mock.return_value = 'fish' + >>> mock() + 'fish' + + The default return value is a mock object and you can configure it in + the normal way: + + >>> mock = Mock() + >>> mock.return_value.attribute = sentinel.Attribute + >>> mock.return_value() + <Mock name='mock()()' id='...'> + >>> mock.return_value.assert_called_with() + + `return_value` can also be set in the constructor: + + >>> mock = Mock(return_value=3) + >>> mock.return_value + 3 + >>> mock() + 3 + + + .. attribute:: side_effect + + This can either be a function to be called when the mock is called, + or an exception (class or instance) to be raised. + + If you pass in a function it will be called with same arguments as the + mock and unless the function returns the :data:`DEFAULT` singleton the + call to the mock will then return whatever the function returns. If the + function returns :data:`DEFAULT` then the mock will return its normal + value (from the :attr:`return_value`. + + An example of a mock that raises an exception (to test exception + handling of an API): + + >>> mock = Mock() + >>> mock.side_effect = Exception('Boom!') + >>> mock() + Traceback (most recent call last): + ... + Exception: Boom! + + Using `side_effect` to return a sequence of values: + + >>> mock = Mock() + >>> mock.side_effect = [3, 2, 1] + >>> mock(), mock(), mock() + (3, 2, 1) + + The `side_effect` function is called with the same arguments as the + mock (so it is wise for it to take arbitrary args and keyword + arguments) and whatever it returns is used as the return value for + the call. The exception is if `side_effect` returns :data:`DEFAULT`, + in which case the normal :attr:`return_value` is used. + + >>> mock = Mock(return_value=3) + >>> def side_effect(*args, **kwargs): + ... return DEFAULT + ... + >>> mock.side_effect = side_effect + >>> mock() + 3 + + `side_effect` can be set in the constructor. Here's an example that + adds one to the value the mock is called with and returns it: + + >>> side_effect = lambda value: value + 1 + >>> mock = Mock(side_effect=side_effect) + >>> mock(3) + 4 + >>> mock(-8) + -7 + + Setting `side_effect` to `None` clears it: + + >>> m = Mock(side_effect=KeyError, return_value=3) + >>> m() + Traceback (most recent call last): + ... + KeyError + >>> m.side_effect = None + >>> m() + 3 + + + .. attribute:: call_args + + This is either `None` (if the mock hasn't been called), or the + arguments that the mock was last called with. This will be in the + form of a tuple: the first member is any ordered arguments the mock + was called with (or an empty tuple) and the second member is any + keyword arguments (or an empty dictionary). + + >>> mock = Mock(return_value=None) + >>> print mock.call_args + None + >>> mock() + >>> mock.call_args + call() + >>> mock.call_args == () + True + >>> mock(3, 4) + >>> mock.call_args + call(3, 4) + >>> mock.call_args == ((3, 4),) + True + >>> mock(3, 4, 5, key='fish', next='w00t!') + >>> mock.call_args + call(3, 4, 5, key='fish', next='w00t!') + + `call_args`, along with members of the lists :attr:`call_args_list`, + :attr:`method_calls` and :attr:`mock_calls` are :data:`call` objects. + These are tuples, so they can be unpacked to get at the individual + arguments and make more complex assertions. See + :ref:`calls as tuples <calls-as-tuples>`. + + + .. attribute:: call_args_list + + This is a list of all the calls made to the mock object in sequence + (so the length of the list is the number of times it has been + called). Before any calls have been made it is an empty list. The + :data:`call` object can be used for conveniently constructing lists of + calls to compare with `call_args_list`. + + >>> mock = Mock(return_value=None) + >>> mock() + >>> mock(3, 4) + >>> mock(key='fish', next='w00t!') + >>> mock.call_args_list + [call(), call(3, 4), call(key='fish', next='w00t!')] + >>> expected = [(), ((3, 4),), ({'key': 'fish', 'next': 'w00t!'},)] + >>> mock.call_args_list == expected + True + + Members of `call_args_list` are :data:`call` objects. These can be + unpacked as tuples to get at the individual arguments. See + :ref:`calls as tuples <calls-as-tuples>`. + + + .. attribute:: method_calls + + As well as tracking calls to themselves, mocks also track calls to + methods and attributes, and *their* methods and attributes: + + >>> mock = Mock() + >>> mock.method() + <Mock name='mock.method()' id='...'> + >>> mock.property.method.attribute() + <Mock name='mock.property.method.attribute()' id='...'> + >>> mock.method_calls + [call.method(), call.property.method.attribute()] + + Members of `method_calls` are :data:`call` objects. These can be + unpacked as tuples to get at the individual arguments. See + :ref:`calls as tuples <calls-as-tuples>`. + + + .. attribute:: mock_calls + + `mock_calls` records *all* calls to the mock object, its methods, magic + methods *and* return value mocks. + + >>> mock = MagicMock() + >>> result = mock(1, 2, 3) + >>> mock.first(a=3) + <MagicMock name='mock.first()' id='...'> + >>> mock.second() + <MagicMock name='mock.second()' id='...'> + >>> int(mock) + 1 + >>> result(1) + <MagicMock name='mock()()' id='...'> + >>> expected = [call(1, 2, 3), call.first(a=3), call.second(), + ... call.__int__(), call()(1)] + >>> mock.mock_calls == expected + True + + Members of `mock_calls` are :data:`call` objects. These can be + unpacked as tuples to get at the individual arguments. See + :ref:`calls as tuples <calls-as-tuples>`. + + + .. attribute:: __class__ + + Normally the `__class__` attribute of an object will return its type. + For a mock object with a `spec` `__class__` returns the spec class + instead. This allows mock objects to pass `isinstance` tests for the + object they are replacing / masquerading as: + + >>> mock = Mock(spec=3) + >>> isinstance(mock, int) + True + + `__class__` is assignable to, this allows a mock to pass an + `isinstance` check without forcing you to use a spec: + + >>> mock = Mock() + >>> mock.__class__ = dict + >>> isinstance(mock, dict) + True + +.. class:: NonCallableMock(spec=None, wraps=None, name=None, spec_set=None, **kwargs) + + A non-callable version of `Mock`. The constructor parameters have the same + meaning of `Mock`, with the exception of `return_value` and `side_effect` + which have no meaning on a non-callable mock. + +Mock objects that use a class or an instance as a `spec` or `spec_set` are able +to pass `isintance` tests: + + >>> mock = Mock(spec=SomeClass) + >>> isinstance(mock, SomeClass) + True + >>> mock = Mock(spec_set=SomeClass()) + >>> isinstance(mock, SomeClass) + True + +The `Mock` classes have support for mocking magic methods. See :ref:`magic +methods <magic-methods>` for the full details. + +The mock classes and the :func:`patch` decorators all take arbitrary keyword +arguments for configuration. For the `patch` decorators the keywords are +passed to the constructor of the mock being created. The keyword arguments +are for configuring attributes of the mock: + + >>> m = MagicMock(attribute=3, other='fish') + >>> m.attribute + 3 + >>> m.other + 'fish' + +The return value and side effect of child mocks can be set in the same way, +using dotted notation. As you can't use dotted names directly in a call you +have to create a dictionary and unpack it using `**`: + + >>> attrs = {'method.return_value': 3, 'other.side_effect': KeyError} + >>> mock = Mock(some_attribute='eggs', **attrs) + >>> mock.some_attribute + 'eggs' + >>> mock.method() + 3 + >>> mock.other() + Traceback (most recent call last): + ... + KeyError + + +.. class:: PropertyMock(*args, **kwargs) + + A mock intended to be used as a property, or other descriptor, on a class. + `PropertyMock` provides `__get__` and `__set__` methods so you can specify + a return value when it is fetched. + + Fetching a `PropertyMock` instance from an object calls the mock, with + no args. Setting it calls the mock with the value being set. + + >>> class Foo(object): + ... @property + ... def foo(self): + ... return 'something' + ... @foo.setter + ... def foo(self, value): + ... pass + ... + >>> with patch('__main__.Foo.foo', new_callable=PropertyMock) as mock_foo: + ... mock_foo.return_value = 'mockity-mock' + ... this_foo = Foo() + ... print this_foo.foo + ... this_foo.foo = 6 + ... + mockity-mock + >>> mock_foo.mock_calls + [call(), call(6)] + +Because of the way mock attributes are stored you can't directly attach a +`PropertyMock` to a mock object. Instead you can attach it to the mock type +object:: + + >>> m = MagicMock() + >>> p = PropertyMock(return_value=3) + >>> type(m).foo = p + >>> m.foo + 3 + >>> p.assert_called_once_with() + + +Calling +~~~~~~~ + +Mock objects are callable. The call will return the value set as the +:attr:`~Mock.return_value` attribute. The default return value is a new Mock +object; it is created the first time the return value is accessed (either +explicitly or by calling the Mock) - but it is stored and the same one +returned each time. + +Calls made to the object will be recorded in the attributes +like :attr:`~Mock.call_args` and :attr:`~Mock.call_args_list`. + +If :attr:`~Mock.side_effect` is set then it will be called after the call has +been recorded, so if `side_effect` raises an exception the call is still +recorded. + +The simplest way to make a mock raise an exception when called is to make +:attr:`~Mock.side_effect` an exception class or instance: + + >>> m = MagicMock(side_effect=IndexError) + >>> m(1, 2, 3) + Traceback (most recent call last): + ... + IndexError + >>> m.mock_calls + [call(1, 2, 3)] + >>> m.side_effect = KeyError('Bang!') + >>> m('two', 'three', 'four') + Traceback (most recent call last): + ... + KeyError: 'Bang!' + >>> m.mock_calls + [call(1, 2, 3), call('two', 'three', 'four')] + +If `side_effect` is a function then whatever that function returns is what +calls to the mock return. The `side_effect` function is called with the +same arguments as the mock. This allows you to vary the return value of the +call dynamically, based on the input: + + >>> def side_effect(value): + ... return value + 1 + ... + >>> m = MagicMock(side_effect=side_effect) + >>> m(1) + 2 + >>> m(2) + 3 + >>> m.mock_calls + [call(1), call(2)] + +If you want the mock to still return the default return value (a new mock), or +any set return value, then there are two ways of doing this. Either return +`mock.return_value` from inside `side_effect`, or return :data:`DEFAULT`: + + >>> m = MagicMock() + >>> def side_effect(*args, **kwargs): + ... return m.return_value + ... + >>> m.side_effect = side_effect + >>> m.return_value = 3 + >>> m() + 3 + >>> def side_effect(*args, **kwargs): + ... return DEFAULT + ... + >>> m.side_effect = side_effect + >>> m() + 3 + +To remove a `side_effect`, and return to the default behaviour, set the +`side_effect` to `None`: + + >>> m = MagicMock(return_value=6) + >>> def side_effect(*args, **kwargs): + ... return 3 + ... + >>> m.side_effect = side_effect + >>> m() + 3 + >>> m.side_effect = None + >>> m() + 6 + +The `side_effect` can also be any iterable object. Repeated calls to the mock +will return values from the iterable (until the iterable is exhausted and +a `StopIteration` is raised): + + >>> m = MagicMock(side_effect=[1, 2, 3]) + >>> m() + 1 + >>> m() + 2 + >>> m() + 3 + >>> m() + Traceback (most recent call last): + ... + StopIteration + +If any members of the iterable are exceptions they will be raised instead of +returned:: + + >>> iterable = (33, ValueError, 66) + >>> m = MagicMock(side_effect=iterable) + >>> m() + 33 + >>> m() + Traceback (most recent call last): + ... + ValueError + >>> m() + 66 + + +.. _deleting-attributes: + +Deleting Attributes +~~~~~~~~~~~~~~~~~~~ + +Mock objects create attributes on demand. This allows them to pretend to be +objects of any type. + +You may want a mock object to return `False` to a `hasattr` call, or raise an +`AttributeError` when an attribute is fetched. You can do this by providing +an object as a `spec` for a mock, but that isn't always convenient. + +You "block" attributes by deleting them. Once deleted, accessing an attribute +will raise an `AttributeError`. + + >>> mock = MagicMock() + >>> hasattr(mock, 'm') + True + >>> del mock.m + >>> hasattr(mock, 'm') + False + >>> del mock.f + >>> mock.f + Traceback (most recent call last): + ... + AttributeError: f + + +Attaching Mocks as Attributes +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ + +When you attach a mock as an attribute of another mock (or as the return +value) it becomes a "child" of that mock. Calls to the child are recorded in +the :attr:`~Mock.method_calls` and :attr:`~Mock.mock_calls` attributes of the +parent. This is useful for configuring child mocks and then attaching them to +the parent, or for attaching mocks to a parent that records all calls to the +children and allows you to make assertions about the order of calls between +mocks: + + >>> parent = MagicMock() + >>> child1 = MagicMock(return_value=None) + >>> child2 = MagicMock(return_value=None) + >>> parent.child1 = child1 + >>> parent.child2 = child2 + >>> child1(1) + >>> child2(2) + >>> parent.mock_calls + [call.child1(1), call.child2(2)] + +The exception to this is if the mock has a name. This allows you to prevent +the "parenting" if for some reason you don't want it to happen. + + >>> mock = MagicMock() + >>> not_a_child = MagicMock(name='not-a-child') + >>> mock.attribute = not_a_child + >>> mock.attribute() + <MagicMock name='not-a-child()' id='...'> + >>> mock.mock_calls + [] + +Mocks created for you by :func:`patch` are automatically given names. To +attach mocks that have names to a parent you use the :meth:`~Mock.attach_mock` +method: + + >>> thing1 = object() + >>> thing2 = object() + >>> parent = MagicMock() + >>> with patch('__main__.thing1', return_value=None) as child1: + ... with patch('__main__.thing2', return_value=None) as child2: + ... parent.attach_mock(child1, 'child1') + ... parent.attach_mock(child2, 'child2') + ... child1('one') + ... child2('two') + ... + >>> parent.mock_calls + [call.child1('one'), call.child2('two')] + + +.. [#] The only exceptions are magic methods and attributes (those that have + leading and trailing double underscores). Mock doesn't create these but + instead of raises an ``AttributeError``. This is because the interpreter + will often implicitly request these methods, and gets *very* confused to + get a new Mock object when it expects a magic method. If you need magic + method support see :ref:`magic methods <magic-methods>`. + + +The patchers +============ + +The patch decorators are used for patching objects only within the scope of +the function they decorate. They automatically handle the unpatching for you, +even if exceptions are raised. All of these functions can also be used in with +statements or as class decorators. + + +patch +----- + +.. note:: + + `patch` is straightforward to use. The key is to do the patching in the + right namespace. See the section `where to patch`_. + +.. function:: patch(target, new=DEFAULT, spec=None, create=False, spec_set=None, autospec=None, new_callable=None, **kwargs) + + `patch` acts as a function decorator, class decorator or a context + manager. Inside the body of the function or with statement, the `target` + is patched with a `new` object. When the function/with statement exits + the patch is undone. + + If `new` is omitted, then the target is replaced with a + :class:`MagicMock`. If `patch` is used as a decorator and `new` is + omitted, the created mock is passed in as an extra argument to the + decorated function. If `patch` is used as a context manager the created + mock is returned by the context manager. + + `target` should be a string in the form `'package.module.ClassName'`. The + `target` is imported and the specified object replaced with the `new` + object, so the `target` must be importable from the environment you are + calling `patch` from. The target is imported when the decorated function + is executed, not at decoration time. + + The `spec` and `spec_set` keyword arguments are passed to the `MagicMock` + if patch is creating one for you. + + In addition you can pass `spec=True` or `spec_set=True`, which causes + patch to pass in the object being mocked as the spec/spec_set object. + + `new_callable` allows you to specify a different class, or callable object, + that will be called to create the `new` object. By default `MagicMock` is + used. + + A more powerful form of `spec` is `autospec`. If you set `autospec=True` + then the mock with be created with a spec from the object being replaced. + All attributes of the mock will also have the spec of the corresponding + attribute of the object being replaced. Methods and functions being mocked + will have their arguments checked and will raise a `TypeError` if they are + called with the wrong signature. For mocks + replacing a class, their return value (the 'instance') will have the same + spec as the class. See the :func:`create_autospec` function and + :ref:`auto-speccing`. + + Instead of `autospec=True` you can pass `autospec=some_object` to use an + arbitrary object as the spec instead of the one being replaced. + + By default `patch` will fail to replace attributes that don't exist. If + you pass in `create=True`, and the attribute doesn't exist, patch will + create the attribute for you when the patched function is called, and + delete it again afterwards. This is useful for writing tests against + attributes that your production code creates at runtime. It is off by by + default because it can be dangerous. With it switched on you can write + passing tests against APIs that don't actually exist! + + Patch can be used as a `TestCase` class decorator. It works by + decorating each test method in the class. This reduces the boilerplate + code when your test methods share a common patchings set. `patch` finds + tests by looking for method names that start with `patch.TEST_PREFIX`. + By default this is `test`, which matches the way `unittest` finds tests. + You can specify an alternative prefix by setting `patch.TEST_PREFIX`. + + Patch can be used as a context manager, with the with statement. Here the + patching applies to the indented block after the with statement. If you + use "as" then the patched object will be bound to the name after the + "as"; very useful if `patch` is creating a mock object for you. + + `patch` takes arbitrary keyword arguments. These will be passed to + the `Mock` (or `new_callable`) on construction. + + `patch.dict(...)`, `patch.multiple(...)` and `patch.object(...)` are + available for alternate use-cases. + +`patch` as function decorator, creating the mock for you and passing it into +the decorated function: + + >>> @patch('__main__.SomeClass') + ... def function(normal_argument, mock_class): + ... print(mock_class is SomeClass) + ... + >>> function(None) + True + +Patching a class replaces the class with a `MagicMock` *instance*. If the +class is instantiated in the code under test then it will be the +:attr:`~Mock.return_value` of the mock that will be used. + +If the class is instantiated multiple times you could use +:attr:`~Mock.side_effect` to return a new mock each time. Alternatively you +can set the `return_value` to be anything you want. + +To configure return values on methods of *instances* on the patched class +you must do this on the `return_value`. For example: + + >>> class Class(object): + ... def method(self): + ... pass + ... + >>> with patch('__main__.Class') as MockClass: + ... instance = MockClass.return_value + ... instance.method.return_value = 'foo' + ... assert Class() is instance + ... assert Class().method() == 'foo' + ... + +If you use `spec` or `spec_set` and `patch` is replacing a *class*, then the +return value of the created mock will have the same spec. + + >>> Original = Class + >>> patcher = patch('__main__.Class', spec=True) + >>> MockClass = patcher.start() + >>> instance = MockClass() + >>> assert isinstance(instance, Original) + >>> patcher.stop() + +The `new_callable` argument is useful where you want to use an alternative +class to the default :class:`MagicMock` for the created mock. For example, if +you wanted a :class:`NonCallableMock` to be used: + + >>> thing = object() + >>> with patch('__main__.thing', new_callable=NonCallableMock) as mock_thing: + ... assert thing is mock_thing + ... thing() + ... + Traceback (most recent call last): + ... + TypeError: 'NonCallableMock' object is not callable + +Another use case might be to replace an object with a `StringIO` instance: + + >>> from StringIO import StringIO + >>> def foo(): + ... print 'Something' + ... + >>> @patch('sys.stdout', new_callable=StringIO) + ... def test(mock_stdout): + ... foo() + ... assert mock_stdout.getvalue() == 'Something\n' + ... + >>> test() + +When `patch` is creating a mock for you, it is common that the first thing +you need to do is to configure the mock. Some of that configuration can be done +in the call to patch. Any arbitrary keywords you pass into the call will be +used to set attributes on the created mock: + + >>> patcher = patch('__main__.thing', first='one', second='two') + >>> mock_thing = patcher.start() + >>> mock_thing.first + 'one' + >>> mock_thing.second + 'two' + +As well as attributes on the created mock attributes, like the +:attr:`~Mock.return_value` and :attr:`~Mock.side_effect`, of child mocks can +also be configured. These aren't syntactically valid to pass in directly as +keyword arguments, but a dictionary with these as keys can still be expanded +into a `patch` call using `**`: + + >>> config = {'method.return_value': 3, 'other.side_effect': KeyError} + >>> patcher = patch('__main__.thing', **config) + >>> mock_thing = patcher.start() + >>> mock_thing.method() + 3 + >>> mock_thing.other() + Traceback (most recent call last): + ... + KeyError + + +patch.object +------------ + +.. function:: patch.object(target, attribute, new=DEFAULT, spec=None, create=False, spec_set=None, autospec=None, new_callable=None, **kwargs) + + patch the named member (`attribute`) on an object (`target`) with a mock + object. + + `patch.object` can be used as a decorator, class decorator or a context + manager. Arguments `new`, `spec`, `create`, `spec_set`, `autospec` and + `new_callable` have the same meaning as for `patch`. Like `patch`, + `patch.object` takes arbitrary keyword arguments for configuring the mock + object it creates. + + When used as a class decorator `patch.object` honours `patch.TEST_PREFIX` + for choosing which methods to wrap. + +You can either call `patch.object` with three arguments or two arguments. The +three argument form takes the object to be patched, the attribute name and the +object to replace the attribute with. + +When calling with the two argument form you omit the replacement object, and a +mock is created for you and passed in as an extra argument to the decorated +function: + + >>> @patch.object(SomeClass, 'class_method') + ... def test(mock_method): + ... SomeClass.class_method(3) + ... mock_method.assert_called_with(3) + ... + >>> test() + +`spec`, `create` and the other arguments to `patch.object` have the same +meaning as they do for `patch`. + + +patch.dict +---------- + +.. function:: patch.dict(in_dict, values=(), clear=False, **kwargs) + + Patch a dictionary, or dictionary like object, and restore the dictionary + to its original state after the test. + + `in_dict` can be a dictionary or a mapping like container. If it is a + mapping then it must at least support getting, setting and deleting items + plus iterating over keys. + + `in_dict` can also be a string specifying the name of the dictionary, which + will then be fetched by importing it. + + `values` can be a dictionary of values to set in the dictionary. `values` + can also be an iterable of `(key, value)` pairs. + + If `clear` is True then the dictionary will be cleared before the new + values are set. + + `patch.dict` can also be called with arbitrary keyword arguments to set + values in the dictionary. + + `patch.dict` can be used as a context manager, decorator or class + decorator. When used as a class decorator `patch.dict` honours + `patch.TEST_PREFIX` for choosing which methods to wrap. + +`patch.dict` can be used to add members to a dictionary, or simply let a test +change a dictionary, and ensure the dictionary is restored when the test +ends. + + >>> foo = {} + >>> with patch.dict(foo, {'newkey': 'newvalue'}): + ... assert foo == {'newkey': 'newvalue'} + ... + >>> assert foo == {} + + >>> import os + >>> with patch.dict('os.environ', {'newkey': 'newvalue'}): + ... print os.environ['newkey'] + ... + newvalue + >>> assert 'newkey' not in os.environ + +Keywords can be used in the `patch.dict` call to set values in the dictionary: + + >>> mymodule = MagicMock() + >>> mymodule.function.return_value = 'fish' + >>> with patch.dict('sys.modules', mymodule=mymodule): + ... import mymodule + ... mymodule.function('some', 'args') + ... + 'fish' + +`patch.dict` can be used with dictionary like objects that aren't actually +dictionaries. At the very minimum they must support item getting, setting, +deleting and either iteration or membership test. This corresponds to the +magic methods `__getitem__`, `__setitem__`, `__delitem__` and either +`__iter__` or `__contains__`. + + >>> class Container(object): + ... def __init__(self): + ... self.values = {} + ... def __getitem__(self, name): + ... return self.values[name] + ... def __setitem__(self, name, value): + ... self.values[name] = value + ... def __delitem__(self, name): + ... del self.values[name] + ... def __iter__(self): + ... return iter(self.values) + ... + >>> thing = Container() + >>> thing['one'] = 1 + >>> with patch.dict(thing, one=2, two=3): + ... assert thing['one'] == 2 + ... assert thing['two'] == 3 + ... + >>> assert thing['one'] == 1 + >>> assert list(thing) == ['one'] + + +patch.multiple +-------------- + +.. function:: patch.multiple(target, spec=None, create=False, spec_set=None, autospec=None, new_callable=None, **kwargs) + + Perform multiple patches in a single call. It takes the object to be + patched (either as an object or a string to fetch the object by importing) + and keyword arguments for the patches:: + + with patch.multiple(settings, FIRST_PATCH='one', SECOND_PATCH='two'): + ... + + Use :data:`DEFAULT` as the value if you want `patch.multiple` to create + mocks for you. In this case the created mocks are passed into a decorated + function by keyword, and a dictionary is returned when `patch.multiple` is + used as a context manager. + + `patch.multiple` can be used as a decorator, class decorator or a context + manager. The arguments `spec`, `spec_set`, `create`, `autospec` and + `new_callable` have the same meaning as for `patch`. These arguments will + be applied to *all* patches done by `patch.multiple`. + + When used as a class decorator `patch.multiple` honours `patch.TEST_PREFIX` + for choosing which methods to wrap. + +If you want `patch.multiple` to create mocks for you, then you can use +:data:`DEFAULT` as the value. If you use `patch.multiple` as a decorator +then the created mocks are passed into the decorated function by keyword. + + >>> thing = object() + >>> other = object() + + >>> @patch.multiple('__main__', thing=DEFAULT, other=DEFAULT) + ... def test_function(thing, other): + ... assert isinstance(thing, MagicMock) + ... assert isinstance(other, MagicMock) + ... + >>> test_function() + +`patch.multiple` can be nested with other `patch` decorators, but put arguments +passed by keyword *after* any of the standard arguments created by `patch`: + + >>> @patch('sys.exit') + ... @patch.multiple('__main__', thing=DEFAULT, other=DEFAULT) + ... def test_function(mock_exit, other, thing): + ... assert 'other' in repr(other) + ... assert 'thing' in repr(thing) + ... assert 'exit' in repr(mock_exit) + ... + >>> test_function() + +If `patch.multiple` is used as a context manager, the value returned by the +context manger is a dictionary where created mocks are keyed by name: + + >>> with patch.multiple('__main__', thing=DEFAULT, other=DEFAULT) as values: + ... assert 'other' in repr(values['other']) + ... assert 'thing' in repr(values['thing']) + ... assert values['thing'] is thing + ... assert values['other'] is other + ... + + +.. _start-and-stop: + +patch methods: start and stop +----------------------------- + +All the patchers have `start` and `stop` methods. These make it simpler to do +patching in `setUp` methods or where you want to do multiple patches without +nesting decorators or with statements. + +To use them call `patch`, `patch.object` or `patch.dict` as normal and keep a +reference to the returned `patcher` object. You can then call `start` to put +the patch in place and `stop` to undo it. + +If you are using `patch` to create a mock for you then it will be returned by +the call to `patcher.start`. + + >>> patcher = patch('package.module.ClassName') + >>> from package import module + >>> original = module.ClassName + >>> new_mock = patcher.start() + >>> assert module.ClassName is not original + >>> assert module.ClassName is new_mock + >>> patcher.stop() + >>> assert module.ClassName is original + >>> assert module.ClassName is not new_mock + + +A typical use case for this might be for doing multiple patches in the `setUp` +method of a `TestCase`: + + >>> class MyTest(TestCase): + ... def setUp(self): + ... self.patcher1 = patch('package.module.Class1') + ... self.patcher2 = patch('package.module.Class2') + ... self.MockClass1 = self.patcher1.start() + ... self.MockClass2 = self.patcher2.start() + ... + ... def tearDown(self): + ... self.patcher1.stop() + ... self.patcher2.stop() + ... + ... def test_something(self): + ... assert package.module.Class1 is self.MockClass1 + ... assert package.module.Class2 is self.MockClass2 + ... + >>> MyTest('test_something').run() + +.. caution:: + + If you use this technique you must ensure that the patching is "undone" by + calling `stop`. This can be fiddlier than you might think, because if an + exception is raised in the ``setUp`` then ``tearDown`` is not called. + :meth:`unittest.TestCase.addCleanup` makes this easier: + + >>> class MyTest(TestCase): + ... def setUp(self): + ... patcher = patch('package.module.Class') + ... self.MockClass = patcher.start() + ... self.addCleanup(patcher.stop) + ... + ... def test_something(self): + ... assert package.module.Class is self.MockClass + ... + + As an added bonus you no longer need to keep a reference to the `patcher` + object. + +It is also possible to stop all patches which have been started by using +`patch.stopall`. + +.. function:: patch.stopall + + Stop all active patches. Only stops patches started with `start`. + + +TEST_PREFIX +----------- + +All of the patchers can be used as class decorators. When used in this way +they wrap every test method on the class. The patchers recognise methods that +start with `test` as being test methods. This is the same way that the +:class:`unittest.TestLoader` finds test methods by default. + +It is possible that you want to use a different prefix for your tests. You can +inform the patchers of the different prefix by setting `patch.TEST_PREFIX`: + + >>> patch.TEST_PREFIX = 'foo' + >>> value = 3 + >>> + >>> @patch('__main__.value', 'not three') + ... class Thing(object): + ... def foo_one(self): + ... print value + ... def foo_two(self): + ... print value + ... + >>> + >>> Thing().foo_one() + not three + >>> Thing().foo_two() + not three + >>> value + 3 + + +Nesting Patch Decorators +------------------------ + +If you want to perform multiple patches then you can simply stack up the +decorators. + +You can stack up multiple patch decorators using this pattern: + + >>> @patch.object(SomeClass, 'class_method') + ... @patch.object(SomeClass, 'static_method') + ... def test(mock1, mock2): + ... assert SomeClass.static_method is mock1 + ... assert SomeClass.class_method is mock2 + ... SomeClass.static_method('foo') + ... SomeClass.class_method('bar') + ... return mock1, mock2 + ... + >>> mock1, mock2 = test() + >>> mock1.assert_called_once_with('foo') + >>> mock2.assert_called_once_with('bar') + + +Note that the decorators are applied from the bottom upwards. This is the +standard way that Python applies decorators. The order of the created mocks +passed into your test function matches this order. + + +.. _where-to-patch: + +Where to patch +-------------- + +`patch` works by (temporarily) changing the object that a *name* points to with +another one. There can be many names pointing to any individual object, so +for patching to work you must ensure that you patch the name used by the system +under test. + +The basic principle is that you patch where an object is *looked up*, which +is not necessarily the same place as where it is defined. A couple of +examples will help to clarify this. + +Imagine we have a project that we want to test with the following structure:: + + a.py + -> Defines SomeClass + + b.py + -> from a import SomeClass + -> some_function instantiates SomeClass + +Now we want to test `some_function` but we want to mock out `SomeClass` using +`patch`. The problem is that when we import module b, which we will have to +do then it imports `SomeClass` from module a. If we use `patch` to mock out +`a.SomeClass` then it will have no effect on our test; module b already has a +reference to the *real* `SomeClass` and it looks like our patching had no +effect. + +The key is to patch out `SomeClass` where it is used (or where it is looked up +). In this case `some_function` will actually look up `SomeClass` in module b, +where we have imported it. The patching should look like:: + + @patch('b.SomeClass') + +However, consider the alternative scenario where instead of `from a import +SomeClass` module b does `import a` and `some_function` uses `a.SomeClass`. Both +of these import forms are common. In this case the class we want to patch is +being looked up on the a module and so we have to patch `a.SomeClass` instead:: + + @patch('a.SomeClass') + + +Patching Descriptors and Proxy Objects +-------------------------------------- + +Both patch_ and patch.object_ correctly patch and restore descriptors: class +methods, static methods and properties. You should patch these on the *class* +rather than an instance. They also work with *some* objects +that proxy attribute access, like the `django setttings object +<http://www.voidspace.org.uk/python/weblog/arch_d7_2010_12_04.shtml#e1198>`_. + + +MagicMock and magic method support +================================== + +.. _magic-methods: + +Mocking Magic Methods +--------------------- + +:class:`Mock` supports mocking the Python protocol methods, also known as +"magic methods". This allows mock objects to replace containers or other +objects that implement Python protocols. + +Because magic methods are looked up differently from normal methods [#]_, this +support has been specially implemented. This means that only specific magic +methods are supported. The supported list includes *almost* all of them. If +there are any missing that you need please let us know. + +You mock magic methods by setting the method you are interested in to a function +or a mock instance. If you are using a function then it *must* take ``self`` as +the first argument [#]_. + + >>> def __str__(self): + ... return 'fooble' + ... + >>> mock = Mock() + >>> mock.__str__ = __str__ + >>> str(mock) + 'fooble' + + >>> mock = Mock() + >>> mock.__str__ = Mock() + >>> mock.__str__.return_value = 'fooble' + >>> str(mock) + 'fooble' + + >>> mock = Mock() + >>> mock.__iter__ = Mock(return_value=iter([])) + >>> list(mock) + [] + +One use case for this is for mocking objects used as context managers in a +`with` statement: + + >>> mock = Mock() + >>> mock.__enter__ = Mock(return_value='foo') + >>> mock.__exit__ = Mock(return_value=False) + >>> with mock as m: + ... assert m == 'foo' + ... + >>> mock.__enter__.assert_called_with() + >>> mock.__exit__.assert_called_with(None, None, None) + +Calls to magic methods do not appear in :attr:`~Mock.method_calls`, but they +are recorded in :attr:`~Mock.mock_calls`. + +.. note:: + + If you use the `spec` keyword argument to create a mock then attempting to + set a magic method that isn't in the spec will raise an `AttributeError`. + +The full list of supported magic methods is: + +* ``__hash__``, ``__sizeof__``, ``__repr__`` and ``__str__`` +* ``__dir__``, ``__format__`` and ``__subclasses__`` +* ``__floor__``, ``__trunc__`` and ``__ceil__`` +* Comparisons: ``__cmp__``, ``__lt__``, ``__gt__``, ``__le__``, ``__ge__``, + ``__eq__`` and ``__ne__`` +* Container methods: ``__getitem__``, ``__setitem__``, ``__delitem__``, + ``__contains__``, ``__len__``, ``__iter__``, ``__getslice__``, + ``__setslice__``, ``__reversed__`` and ``__missing__`` +* Context manager: ``__enter__`` and ``__exit__`` +* Unary numeric methods: ``__neg__``, ``__pos__`` and ``__invert__`` +* The numeric methods (including right hand and in-place variants): + ``__add__``, ``__sub__``, ``__mul__``, ``__div__``, + ``__floordiv__``, ``__mod__``, ``__divmod__``, ``__lshift__``, + ``__rshift__``, ``__and__``, ``__xor__``, ``__or__``, and ``__pow__`` +* Numeric conversion methods: ``__complex__``, ``__int__``, ``__float__``, + ``__index__`` and ``__coerce__`` +* Descriptor methods: ``__get__``, ``__set__`` and ``__delete__`` +* Pickling: ``__reduce__``, ``__reduce_ex__``, ``__getinitargs__``, + ``__getnewargs__``, ``__getstate__`` and ``__setstate__`` + + +The following methods exist but are *not* supported as they are either in use +by mock, can't be set dynamically, or can cause problems: + +* ``__getattr__``, ``__setattr__``, ``__init__`` and ``__new__`` +* ``__prepare__``, ``__instancecheck__``, ``__subclasscheck__``, ``__del__`` + + + +Magic Mock +---------- + +There are two `MagicMock` variants: `MagicMock` and `NonCallableMagicMock`. + + +.. class:: MagicMock(*args, **kw) + + ``MagicMock`` is a subclass of :class:`Mock` with default implementations + of most of the magic methods. You can use ``MagicMock`` without having to + configure the magic methods yourself. + + The constructor parameters have the same meaning as for :class:`Mock`. + + If you use the `spec` or `spec_set` arguments then *only* magic methods + that exist in the spec will be created. + + +.. class:: NonCallableMagicMock(*args, **kw) + + A non-callable version of `MagicMock`. + + The constructor parameters have the same meaning as for + :class:`MagicMock`, with the exception of `return_value` and + `side_effect` which have no meaning on a non-callable mock. + +The magic methods are setup with `MagicMock` objects, so you can configure them +and use them in the usual way: + + >>> mock = MagicMock() + >>> mock[3] = 'fish' + >>> mock.__setitem__.assert_called_with(3, 'fish') + >>> mock.__getitem__.return_value = 'result' + >>> mock[2] + 'result' + +By default many of the protocol methods are required to return objects of a +specific type. These methods are preconfigured with a default return value, so +that they can be used without you having to do anything if you aren't interested +in the return value. You can still *set* the return value manually if you want +to change the default. + +Methods and their defaults: + +* ``__lt__``: NotImplemented +* ``__gt__``: NotImplemented +* ``__le__``: NotImplemented +* ``__ge__``: NotImplemented +* ``__int__`` : 1 +* ``__contains__`` : False +* ``__len__`` : 1 +* ``__iter__`` : iter([]) +* ``__exit__`` : False +* ``__complex__`` : 1j +* ``__float__`` : 1.0 +* ``__bool__`` : True +* ``__index__`` : 1 +* ``__hash__`` : default hash for the mock +* ``__str__`` : default str for the mock +* ``__sizeof__``: default sizeof for the mock + +For example: + + >>> mock = MagicMock() + >>> int(mock) + 1 + >>> len(mock) + 0 + >>> list(mock) + [] + >>> object() in mock + False + +The two equality method, `__eq__` and `__ne__`, are special. +They do the default equality comparison on identity, using a side +effect, unless you change their return value to return something else: + + >>> MagicMock() == 3 + False + >>> MagicMock() != 3 + True + >>> mock = MagicMock() + >>> mock.__eq__.return_value = True + >>> mock == 3 + True + +The return value of `MagicMock.__iter__` can be any iterable object and isn't +required to be an iterator: + + >>> mock = MagicMock() + >>> mock.__iter__.return_value = ['a', 'b', 'c'] + >>> list(mock) + ['a', 'b', 'c'] + >>> list(mock) + ['a', 'b', 'c'] + +If the return value *is* an iterator, then iterating over it once will consume +it and subsequent iterations will result in an empty list: + + >>> mock.__iter__.return_value = iter(['a', 'b', 'c']) + >>> list(mock) + ['a', 'b', 'c'] + >>> list(mock) + [] + +``MagicMock`` has all of the supported magic methods configured except for some +of the obscure and obsolete ones. You can still set these up if you want. + +Magic methods that are supported but not setup by default in ``MagicMock`` are: + +* ``__subclasses__`` +* ``__dir__`` +* ``__format__`` +* ``__get__``, ``__set__`` and ``__delete__`` +* ``__reversed__`` and ``__missing__`` +* ``__reduce__``, ``__reduce_ex__``, ``__getinitargs__``, ``__getnewargs__``, + ``__getstate__`` and ``__setstate__`` +* ``__getformat__`` and ``__setformat__`` + + + +.. [#] Magic methods *should* be looked up on the class rather than the + instance. Different versions of Python are inconsistent about applying this + rule. The supported protocol methods should work with all supported versions + of Python. +.. [#] The function is basically hooked up to the class, but each ``Mock`` + instance is kept isolated from the others. + + +Helpers +======= + +sentinel +-------- + +.. data:: sentinel + + The ``sentinel`` object provides a convenient way of providing unique + objects for your tests. + + Attributes are created on demand when you access them by name. Accessing + the same attribute will always return the same object. The objects + returned have a sensible repr so that test failure messages are readable. + +Sometimes when testing you need to test that a specific object is passed as an +argument to another method, or returned. It can be common to create named +sentinel objects to test this. `sentinel` provides a convenient way of +creating and testing the identity of objects like this. + +In this example we monkey patch `method` to return `sentinel.some_object`: + + >>> real = ProductionClass() + >>> real.method = Mock(name="method") + >>> real.method.return_value = sentinel.some_object + >>> result = real.method() + >>> assert result is sentinel.some_object + >>> sentinel.some_object + sentinel.some_object + + +DEFAULT +------- + + +.. data:: DEFAULT + + The `DEFAULT` object is a pre-created sentinel (actually + `sentinel.DEFAULT`). It can be used by :attr:`~Mock.side_effect` + functions to indicate that the normal return value should be used. + + + +call +---- + +.. function:: call(*args, **kwargs) + + `call` is a helper object for making simpler assertions, for comparing with + :attr:`~Mock.call_args`, :attr:`~Mock.call_args_list`, + :attr:`~Mock.mock_calls` and :attr:`~Mock.method_calls`. `call` can also be + used with :meth:`~Mock.assert_has_calls`. + + >>> m = MagicMock(return_value=None) + >>> m(1, 2, a='foo', b='bar') + >>> m() + >>> m.call_args_list == [call(1, 2, a='foo', b='bar'), call()] + True + +.. method:: call.call_list() + + For a call object that represents multiple calls, `call_list` + returns a list of all the intermediate calls as well as the + final call. + +`call_list` is particularly useful for making assertions on "chained calls". A +chained call is multiple calls on a single line of code. This results in +multiple entries in :attr:`~Mock.mock_calls` on a mock. Manually constructing +the sequence of calls can be tedious. + +:meth:`~call.call_list` can construct the sequence of calls from the same +chained call: + + >>> m = MagicMock() + >>> m(1).method(arg='foo').other('bar')(2.0) + <MagicMock name='mock().method().other()()' id='...'> + >>> kall = call(1).method(arg='foo').other('bar')(2.0) + >>> kall.call_list() + [call(1), + call().method(arg='foo'), + call().method().other('bar'), + call().method().other()(2.0)] + >>> m.mock_calls == kall.call_list() + True + +.. _calls-as-tuples: + +A `call` object is either a tuple of (positional args, keyword args) or +(name, positional args, keyword args) depending on how it was constructed. When +you construct them yourself this isn't particularly interesting, but the `call` +objects that are in the :attr:`Mock.call_args`, :attr:`Mock.call_args_list` and +:attr:`Mock.mock_calls` attributes can be introspected to get at the individual +arguments they contain. + +The `call` objects in :attr:`Mock.call_args` and :attr:`Mock.call_args_list` +are two-tuples of (positional args, keyword args) whereas the `call` objects +in :attr:`Mock.mock_calls`, along with ones you construct yourself, are +three-tuples of (name, positional args, keyword args). + +You can use their "tupleness" to pull out the individual arguments for more +complex introspection and assertions. The positional arguments are a tuple +(an empty tuple if there are no positional arguments) and the keyword +arguments are a dictionary: + + >>> m = MagicMock(return_value=None) + >>> m(1, 2, 3, arg='one', arg2='two') + >>> kall = m.call_args + >>> args, kwargs = kall + >>> args + (1, 2, 3) + >>> kwargs + {'arg2': 'two', 'arg': 'one'} + >>> args is kall[0] + True + >>> kwargs is kall[1] + True + + >>> m = MagicMock() + >>> m.foo(4, 5, 6, arg='two', arg2='three') + <MagicMock name='mock.foo()' id='...'> + >>> kall = m.mock_calls[0] + >>> name, args, kwargs = kall + >>> name + 'foo' + >>> args + (4, 5, 6) + >>> kwargs + {'arg2': 'three', 'arg': 'two'} + >>> name is m.mock_calls[0][0] + True + + +create_autospec +--------------- + +.. function:: create_autospec(spec, spec_set=False, instance=False, **kwargs) + + Create a mock object using another object as a spec. Attributes on the + mock will use the corresponding attribute on the `spec` object as their + spec. + + Functions or methods being mocked will have their arguments checked to + ensure that they are called with the correct signature. + + If `spec_set` is `True` then attempting to set attributes that don't exist + on the spec object will raise an `AttributeError`. + + If a class is used as a spec then the return value of the mock (the + instance of the class) will have the same spec. You can use a class as the + spec for an instance object by passing `instance=True`. The returned mock + will only be callable if instances of the mock are callable. + + `create_autospec` also takes arbitrary keyword arguments that are passed to + the constructor of the created mock. + +See :ref:`auto-speccing` for examples of how to use auto-speccing with +`create_autospec` and the `autospec` argument to :func:`patch`. + + +ANY +--- + +.. data:: ANY + +Sometimes you may need to make assertions about *some* of the arguments in a +call to mock, but either not care about some of the arguments or want to pull +them individually out of :attr:`~Mock.call_args` and make more complex +assertions on them. + +To ignore certain arguments you can pass in objects that compare equal to +*everything*. Calls to :meth:`~Mock.assert_called_with` and +:meth:`~Mock.assert_called_once_with` will then succeed no matter what was +passed in. + + >>> mock = Mock(return_value=None) + >>> mock('foo', bar=object()) + >>> mock.assert_called_once_with('foo', bar=ANY) + +`ANY` can also be used in comparisons with call lists like +:attr:`~Mock.mock_calls`: + + >>> m = MagicMock(return_value=None) + >>> m(1) + >>> m(1, 2) + >>> m(object()) + >>> m.mock_calls == [call(1), call(1, 2), ANY] + True + + + +FILTER_DIR +---------- + +.. data:: FILTER_DIR + +`FILTER_DIR` is a module level variable that controls the way mock objects +respond to `dir` (only for Python 2.6 or more recent). The default is `True`, +which uses the filtering described below, to only show useful members. If you +dislike this filtering, or need to switch it off for diagnostic purposes, then +set `mock.FILTER_DIR = False`. + +With filtering on, `dir(some_mock)` shows only useful attributes and will +include any dynamically created attributes that wouldn't normally be shown. +If the mock was created with a `spec` (or `autospec` of course) then all the +attributes from the original are shown, even if they haven't been accessed +yet: + + >>> dir(Mock()) + ['assert_any_call', + 'assert_called_once_with', + 'assert_called_with', + 'assert_has_calls', + 'attach_mock', + ... + >>> from urllib import request + >>> dir(Mock(spec=request)) + ['AbstractBasicAuthHandler', + 'AbstractDigestAuthHandler', + 'AbstractHTTPHandler', + 'BaseHandler', + ... + +Many of the not-very-useful (private to `Mock` rather than the thing being +mocked) underscore and double underscore prefixed attributes have been +filtered from the result of calling `dir` on a `Mock`. If you dislike this +behaviour you can switch it off by setting the module level switch +`FILTER_DIR`: + + >>> from unittest import mock + >>> mock.FILTER_DIR = False + >>> dir(mock.Mock()) + ['_NonCallableMock__get_return_value', + '_NonCallableMock__get_side_effect', + '_NonCallableMock__return_value_doc', + '_NonCallableMock__set_return_value', + '_NonCallableMock__set_side_effect', + '__call__', + '__class__', + ... + +Alternatively you can just use `vars(my_mock)` (instance members) and +`dir(type(my_mock))` (type members) to bypass the filtering irrespective of +`mock.FILTER_DIR`. + + +mock_open +--------- + +.. function:: mock_open(mock=None, read_data=None) + + A helper function to create a mock to replace the use of `open`. It works + for `open` called directly or used as a context manager. + + The `mock` argument is the mock object to configure. If `None` (the + default) then a `MagicMock` will be created for you, with the API limited + to methods or attributes available on standard file handles. + + `read_data` is a string for the `read` method of the file handle to return. + This is an empty string by default. + +Using `open` as a context manager is a great way to ensure your file handles +are closed properly and is becoming common:: + + with open('/some/path', 'w') as f: + f.write('something') + +The issue is that even if you mock out the call to `open` it is the +*returned object* that is used as a context manager (and has `__enter__` and +`__exit__` called). + +Mocking context managers with a :class:`MagicMock` is common enough and fiddly +enough that a helper function is useful. + + >>> m = mock_open() + >>> with patch('__main__.open', m, create=True): + ... with open('foo', 'w') as h: + ... h.write('some stuff') + ... + >>> m.mock_calls + [call('foo', 'w'), + call().__enter__(), + call().write('some stuff'), + call().__exit__(None, None, None)] + >>> m.assert_called_once_with('foo', 'w') + >>> handle = m() + >>> handle.write.assert_called_once_with('some stuff') + +And for reading files: + + >>> with patch('__main__.open', mock_open(read_data='bibble'), create=True) as m: + ... with open('foo') as h: + ... result = h.read() + ... + >>> m.assert_called_once_with('foo') + >>> assert result == 'bibble' + + +.. _auto-speccing: + +Autospeccing +------------ + +Autospeccing is based on the existing `spec` feature of mock. It limits the +api of mocks to the api of an original object (the spec), but it is recursive +(implemented lazily) so that attributes of mocks only have the same api as +the attributes of the spec. In addition mocked functions / methods have the +same call signature as the original so they raise a `TypeError` if they are +called incorrectly. + +Before I explain how auto-speccing works, here's why it is needed. + +`Mock` is a very powerful and flexible object, but it suffers from two flaws +when used to mock out objects from a system under test. One of these flaws is +specific to the `Mock` api and the other is a more general problem with using +mock objects. + +First the problem specific to `Mock`. `Mock` has two assert methods that are +extremely handy: :meth:`~Mock.assert_called_with` and +:meth:`~Mock.assert_called_once_with`. + + >>> mock = Mock(name='Thing', return_value=None) + >>> mock(1, 2, 3) + >>> mock.assert_called_once_with(1, 2, 3) + >>> mock(1, 2, 3) + >>> mock.assert_called_once_with(1, 2, 3) + Traceback (most recent call last): + ... + AssertionError: Expected to be called once. Called 2 times. + +Because mocks auto-create attributes on demand, and allow you to call them +with arbitrary arguments, if you misspell one of these assert methods then +your assertion is gone: + +.. code-block:: pycon + + >>> mock = Mock(name='Thing', return_value=None) + >>> mock(1, 2, 3) + >>> mock.assret_called_once_with(4, 5, 6) + +Your tests can pass silently and incorrectly because of the typo. + +The second issue is more general to mocking. If you refactor some of your +code, rename members and so on, any tests for code that is still using the +*old api* but uses mocks instead of the real objects will still pass. This +means your tests can all pass even though your code is broken. + +Note that this is another reason why you need integration tests as well as +unit tests. Testing everything in isolation is all fine and dandy, but if you +don't test how your units are "wired together" there is still lots of room +for bugs that tests might have caught. + +`mock` already provides a feature to help with this, called speccing. If you +use a class or instance as the `spec` for a mock then you can only access +attributes on the mock that exist on the real class: + + >>> from urllib import request + >>> mock = Mock(spec=request.Request) + >>> mock.assret_called_with + Traceback (most recent call last): + ... + AttributeError: Mock object has no attribute 'assret_called_with' + +The spec only applies to the mock itself, so we still have the same issue +with any methods on the mock: + +.. code-block:: pycon + + >>> mock.has_data() + <mock.Mock object at 0x...> + >>> mock.has_data.assret_called_with() + +Auto-speccing solves this problem. You can either pass `autospec=True` to +`patch` / `patch.object` or use the `create_autospec` function to create a +mock with a spec. If you use the `autospec=True` argument to `patch` then the +object that is being replaced will be used as the spec object. Because the +speccing is done "lazily" (the spec is created as attributes on the mock are +accessed) you can use it with very complex or deeply nested objects (like +modules that import modules that import modules) without a big performance +hit. + +Here's an example of it in use: + + >>> from urllib import request + >>> patcher = patch('__main__.request', autospec=True) + >>> mock_request = patcher.start() + >>> request is mock_request + True + >>> mock_request.Request + <MagicMock name='request.Request' spec='Request' id='...'> + +You can see that `request.Request` has a spec. `request.Request` takes two +arguments in the constructor (one of which is `self`). Here's what happens if +we try to call it incorrectly: + + >>> req = request.Request() + Traceback (most recent call last): + ... + TypeError: <lambda>() takes at least 2 arguments (1 given) + +The spec also applies to instantiated classes (i.e. the return value of +specced mocks): + + >>> req = request.Request('foo') + >>> req + <NonCallableMagicMock name='request.Request()' spec='Request' id='...'> + +`Request` objects are not callable, so the return value of instantiating our +mocked out `request.Request` is a non-callable mock. With the spec in place +any typos in our asserts will raise the correct error: + + >>> req.add_header('spam', 'eggs') + <MagicMock name='request.Request().add_header()' id='...'> + >>> req.add_header.assret_called_with + Traceback (most recent call last): + ... + AttributeError: Mock object has no attribute 'assret_called_with' + >>> req.add_header.assert_called_with('spam', 'eggs') + +In many cases you will just be able to add `autospec=True` to your existing +`patch` calls and then be protected against bugs due to typos and api +changes. + +As well as using `autospec` through `patch` there is a +:func:`create_autospec` for creating autospecced mocks directly: + + >>> from urllib import request + >>> mock_request = create_autospec(request) + >>> mock_request.Request('foo', 'bar') + <NonCallableMagicMock name='mock.Request()' spec='Request' id='...'> + +This isn't without caveats and limitations however, which is why it is not +the default behaviour. In order to know what attributes are available on the +spec object, autospec has to introspect (access attributes) the spec. As you +traverse attributes on the mock a corresponding traversal of the original +object is happening under the hood. If any of your specced objects have +properties or descriptors that can trigger code execution then you may not be +able to use autospec. On the other hand it is much better to design your +objects so that introspection is safe [#]_. + +A more serious problem is that it is common for instance attributes to be +created in the `__init__` method and not to exist on the class at all. +`autospec` can't know about any dynamically created attributes and restricts +the api to visible attributes. + + >>> class Something(object): + ... def __init__(self): + ... self.a = 33 + ... + >>> with patch('__main__.Something', autospec=True): + ... thing = Something() + ... thing.a + ... + Traceback (most recent call last): + ... + AttributeError: Mock object has no attribute 'a' + +There are a few different ways of resolving this problem. The easiest, but +not necessarily the least annoying, way is to simply set the required +attributes on the mock after creation. Just because `autospec` doesn't allow +you to fetch attributes that don't exist on the spec it doesn't prevent you +setting them: + + >>> with patch('__main__.Something', autospec=True): + ... thing = Something() + ... thing.a = 33 + ... + +There is a more aggressive version of both `spec` and `autospec` that *does* +prevent you setting non-existent attributes. This is useful if you want to +ensure your code only *sets* valid attributes too, but obviously it prevents +this particular scenario: + + >>> with patch('__main__.Something', autospec=True, spec_set=True): + ... thing = Something() + ... thing.a = 33 + ... + Traceback (most recent call last): + ... + AttributeError: Mock object has no attribute 'a' + +Probably the best way of solving the problem is to add class attributes as +default values for instance members initialised in `__init__`. Note that if +you are only setting default attributes in `__init__` then providing them via +class attributes (shared between instances of course) is faster too. e.g. + +.. code-block:: python + + class Something(object): + a = 33 + +This brings up another issue. It is relatively common to provide a default +value of `None` for members that will later be an object of a different type. +`None` would be useless as a spec because it wouldn't let you access *any* +attributes or methods on it. As `None` is *never* going to be useful as a +spec, and probably indicates a member that will normally of some other type, +`autospec` doesn't use a spec for members that are set to `None`. These will +just be ordinary mocks (well - `MagicMocks`): + + >>> class Something(object): + ... member = None + ... + >>> mock = create_autospec(Something) + >>> mock.member.foo.bar.baz() + <MagicMock name='mock.member.foo.bar.baz()' id='...'> + +If modifying your production classes to add defaults isn't to your liking +then there are more options. One of these is simply to use an instance as the +spec rather than the class. The other is to create a subclass of the +production class and add the defaults to the subclass without affecting the +production class. Both of these require you to use an alternative object as +the spec. Thankfully `patch` supports this - you can simply pass the +alternative object as the `autospec` argument: + + >>> class Something(object): + ... def __init__(self): + ... self.a = 33 + ... + >>> class SomethingForTest(Something): + ... a = 33 + ... + >>> p = patch('__main__.Something', autospec=SomethingForTest) + >>> mock = p.start() + >>> mock.a + <NonCallableMagicMock name='Something.a' spec='int' id='...'> + + +.. [#] This only applies to classes or already instantiated objects. Calling + a mocked class to create a mock instance *does not* create a real instance. + It is only attribute lookups - along with calls to `dir` - that are done. + |