diff --git a/Doc/library/development.rst b/Doc/library/development.rst
index c822e08..79c5dd9 100644
--- a/Doc/library/development.rst
+++ b/Doc/library/development.rst
@@ -19,5 +19,11 @@
    pydoc.rst
    doctest.rst
    unittest.rst
+   unittest.mock.rst
+   unittest.mock-patch.rst
+   unittest.mock-magicmethods.rst
+   unittest.mock-helpers.rst
+   unittest.mock-getting-started.rst
+   unittest.mock-examples.rst
    2to3.rst
    test.rst
diff --git a/Doc/library/unittest.mock-examples.rst b/Doc/library/unittest.mock-examples.rst
new file mode 100644
index 0000000..4b6616c
--- /dev/null
+++ b/Doc/library/unittest.mock-examples.rst
@@ -0,0 +1,887 @@
+.. _further-examples:
+
+:mod:`unittest.mock` --- further examples
+=========================================
+
+.. module:: unittest.mock
+   :synopsis: Mock object library.
+.. moduleauthor:: Michael Foord <michael@python.org>
+.. currentmodule:: unittest.mock
+
+.. versionadded:: 3.3
+
+
+Here are some more examples for some slightly more advanced scenarios than in
+the :ref:`getting started <getting-started>` guide.
+
+
+Mocking chained calls
+---------------------
+
+Mocking chained calls is actually straightforward with mock once you
+understand the :attr:`~Mock.return_value` attribute. When a mock is called for
+the first time, or you fetch its `return_value` before it has been called, a
+new `Mock` is created.
+
+This means that you can see how the object returned from a call to a mocked
+object has been used by interrogating the `return_value` mock:
+
+    >>> mock = Mock()
+    >>> mock().foo(a=2, b=3)
+    <Mock name='mock().foo()' id='...'>
+    >>> mock.return_value.foo.assert_called_with(a=2, b=3)
+
+From here it is a simple step to configure and then make assertions about
+chained calls. Of course another alternative is writing your code in a more
+testable way in the first place...
+
+So, suppose we have some code that looks a little bit like this:
+
+    >>> class Something(object):
+    ...     def __init__(self):
+    ...         self.backend = BackendProvider()
+    ...     def method(self):
+    ...         response = self.backend.get_endpoint('foobar').create_call('spam', 'eggs').start_call()
+    ...         # more code
+
+Assuming that `BackendProvider` is already well tested, how do we test
+`method()`? Specifically, we want to test that the code section `# more
+code` uses the response object in the correct way.
+
+As this chain of calls is made from an instance attribute we can monkey patch
+the `backend` attribute on a `Something` instance. In this particular case
+we are only interested in the return value from the final call to
+`start_call` so we don't have much configuration to do. Let's assume the
+object it returns is 'file-like', so we'll ensure that our response object
+uses the builtin `file` as its `spec`.
+
+To do this we create a mock instance as our mock backend and create a mock
+response object for it. To set the response as the return value for that final
+`start_call` we could do this:
+
+    `mock_backend.get_endpoint.return_value.create_call.return_value.start_call.return_value = mock_response`.
+
+We can do that in a slightly nicer way using the :meth:`~Mock.configure_mock`
+method to directly set the return value for us:
+
+    >>> something = Something()
+    >>> mock_response = Mock(spec=file)
+    >>> mock_backend = Mock()
+    >>> config = {'get_endpoint.return_value.create_call.return_value.start_call.return_value': mock_response}
+    >>> mock_backend.configure_mock(**config)
+
+With these we monkey patch the "mock backend" in place and can make the real
+call:
+
+    >>> something.backend = mock_backend
+    >>> something.method()
+
+Using :attr:`~Mock.mock_calls` we can check the chained call with a single
+assert. A chained call is several calls in one line of code, so there will be
+several entries in `mock_calls`. We can use :meth:`call.call_list` to create
+this list of calls for us:
+
+    >>> chained = call.get_endpoint('foobar').create_call('spam', 'eggs').start_call()
+    >>> call_list = chained.call_list()
+    >>> assert mock_backend.mock_calls == call_list
+
+
+Partial mocking
+---------------
+
+In some tests I wanted to mock out a call to `datetime.date.today()
+<http://docs.python.org/library/datetime.html#datetime.date.today>`_ to return
+a known date, but I didn't want to prevent the code under test from
+creating new date objects. Unfortunately `datetime.date` is written in C, and
+so I couldn't just monkey-patch out the static `date.today` method.
+
+I found a simple way of doing this that involved effectively wrapping the date
+class with a mock, but passing through calls to the constructor to the real
+class (and returning real instances).
+
+The :func:`patch decorator <patch>` is used here to
+mock out the `date` class in the module under test. The :attr:`side_effect`
+attribute on the mock date class is then set to a lambda function that returns
+a real date. When the mock date class is called a real date will be
+constructed and returned by `side_effect`.
+
+    >>> from datetime import date
+    >>> with patch('mymodule.date') as mock_date:
+    ...     mock_date.today.return_value = date(2010, 10, 8)
+    ...     mock_date.side_effect = lambda *args, **kw: date(*args, **kw)
+    ...
+    ...     assert mymodule.date.today() == date(2010, 10, 8)
+    ...     assert mymodule.date(2009, 6, 8) == date(2009, 6, 8)
+    ...
+
+Note that we don't patch `datetime.date` globally, we patch `date` in the
+module that *uses* it. See :ref:`where to patch <where-to-patch>`.
+
+When `date.today()` is called a known date is returned, but calls to the
+`date(...)` constructor still return normal dates. Without this you can find
+yourself having to calculate an expected result using exactly the same
+algorithm as the code under test, which is a classic testing anti-pattern.
+
+Calls to the date constructor are recorded in the `mock_date` attributes
+(`call_count` and friends) which may also be useful for your tests.
+
+An alternative way of dealing with mocking dates, or other builtin classes,
+is discussed in `this blog entry
+<http://williamjohnbert.com/2011/07/how-to-unit-testing-in-django-with-mocking-and-patching/>`_.
+
+
+Mocking a Generator Method
+--------------------------
+
+A Python generator is a function or method that uses the `yield statement
+<http://docs.python.org/reference/simple_stmts.html#the-yield-statement>`_ to
+return a series of values when iterated over [#]_.
+
+A generator method / function is called to return the generator object. It is
+the generator object that is then iterated over. The protocol method for
+iteration is `__iter__
+<http://docs.python.org/library/stdtypes.html#container.__iter__>`_, so we can
+mock this using a `MagicMock`.
+
+Here's an example class with an "iter" method implemented as a generator:
+
+    >>> class Foo(object):
+    ...     def iter(self):
+    ...         for i in [1, 2, 3]:
+    ...             yield i
+    ...
+    >>> foo = Foo()
+    >>> list(foo.iter())
+    [1, 2, 3]
+
+
+How would we mock this class, and in particular its "iter" method?
+
+To configure the values returned from the iteration (implicit in the call to
+`list`), we need to configure the object returned by the call to `foo.iter()`.
+
+    >>> mock_foo = MagicMock()
+    >>> mock_foo.iter.return_value = iter([1, 2, 3])
+    >>> list(mock_foo.iter())
+    [1, 2, 3]
+
+.. [#] There are also generator expressions and more `advanced uses
+    <http://www.dabeaz.com/coroutines/index.html>`_ of generators, but we aren't
+    concerned about them here. A very good introduction to generators and how
+    powerful they are is: `Generator Tricks for Systems Programmers
+    <http://www.dabeaz.com/generators/>`_.
+
+
+Applying the same patch to every test method
+--------------------------------------------
+
+If you want several patches in place for multiple test methods the obvious way
+is to apply the patch decorators to every method. This can feel like unnecessary
+repetition. For Python 2.6 or more recent you can use `patch` (in all its
+various forms) as a class decorator. This applies the patches to all test
+methods on the class. A test method is identified by methods whose names start
+with `test`:
+
+    >>> @patch('mymodule.SomeClass')
+    ... class MyTest(TestCase):
+    ...
+    ...     def test_one(self, MockSomeClass):
+    ...         self.assertTrue(mymodule.SomeClass is MockSomeClass)
+    ...
+    ...     def test_two(self, MockSomeClass):
+    ...         self.assertTrue(mymodule.SomeClass is MockSomeClass)
+    ...
+    ...     def not_a_test(self):
+    ...         return 'something'
+    ...
+    >>> MyTest('test_one').test_one()
+    >>> MyTest('test_two').test_two()
+    >>> MyTest('test_two').not_a_test()
+    'something'
+
+An alternative way of managing patches is to use the :ref:`start-and-stop`.
+These allow you to move the patching into your `setUp` and `tearDown` methods.
+
+    >>> class MyTest(TestCase):
+    ...     def setUp(self):
+    ...         self.patcher = patch('mymodule.foo')
+    ...         self.mock_foo = self.patcher.start()
+    ...
+    ...     def test_foo(self):
+    ...         self.assertTrue(mymodule.foo is self.mock_foo)
+    ...
+    ...     def tearDown(self):
+    ...         self.patcher.stop()
+    ...
+    >>> MyTest('test_foo').run()
+
+If you use this technique you must ensure that the patching is "undone" by
+calling `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('mymodule.foo')
+    ...         self.addCleanup(patcher.stop)
+    ...         self.mock_foo = patcher.start()
+    ...
+    ...     def test_foo(self):
+    ...         self.assertTrue(mymodule.foo is self.mock_foo)
+    ...
+    >>> MyTest('test_foo').run()
+
+
+Mocking Unbound Methods
+-----------------------
+
+Whilst writing tests today I needed to patch an *unbound method* (patching the
+method on the class rather than on the instance). I needed self to be passed
+in as the first argument because I want to make asserts about which objects
+were calling this particular method. The issue is that you can't patch with a
+mock for this, because if you replace an unbound method with a mock it doesn't
+become a bound method when fetched from the instance, and so it doesn't get
+self passed in. The workaround is to patch the unbound method with a real
+function instead. The :func:`patch` decorator makes it so simple to
+patch out methods with a mock that having to create a real function becomes a
+nuisance.
+
+If you pass `autospec=True` to patch then it does the patching with a
+*real* function object. This function object has the same signature as the one
+it is replacing, but delegates to a mock under the hood. You still get your
+mock auto-created in exactly the same way as before. What it means though, is
+that if you use it to patch out an unbound method on a class the mocked
+function will be turned into a bound method if it is fetched from an instance.
+It will have `self` passed in as the first argument, which is exactly what I
+wanted:
+
+    >>> class Foo(object):
+    ...   def foo(self):
+    ...     pass
+    ...
+    >>> with patch.object(Foo, 'foo', autospec=True) as mock_foo:
+    ...   mock_foo.return_value = 'foo'
+    ...   foo = Foo()
+    ...   foo.foo()
+    ...
+    'foo'
+    >>> mock_foo.assert_called_once_with(foo)
+
+If we don't use `autospec=True` then the unbound method is patched out
+with a Mock instance instead, and isn't called with `self`.
+
+
+Checking multiple calls with mock
+---------------------------------
+
+mock has a nice API for making assertions about how your mock objects are used.
+
+    >>> mock = Mock()
+    >>> mock.foo_bar.return_value = None
+    >>> mock.foo_bar('baz', spam='eggs')
+    >>> mock.foo_bar.assert_called_with('baz', spam='eggs')
+
+If your mock is only being called once you can use the
+:meth:`assert_called_once_with` method that also asserts that the
+:attr:`call_count` is one.
+
+    >>> mock.foo_bar.assert_called_once_with('baz', spam='eggs')
+    >>> mock.foo_bar()
+    >>> mock.foo_bar.assert_called_once_with('baz', spam='eggs')
+    Traceback (most recent call last):
+        ...
+    AssertionError: Expected to be called once. Called 2 times.
+
+Both `assert_called_with` and `assert_called_once_with` make assertions about
+the *most recent* call. If your mock is going to be called several times, and
+you want to make assertions about *all* those calls you can use
+:attr:`~Mock.call_args_list`:
+
+    >>> mock = Mock(return_value=None)
+    >>> mock(1, 2, 3)
+    >>> mock(4, 5, 6)
+    >>> mock()
+    >>> mock.call_args_list
+    [call(1, 2, 3), call(4, 5, 6), call()]
+
+The :data:`call` helper makes it easy to make assertions about these calls. You
+can build up a list of expected calls and compare it to `call_args_list`. This
+looks remarkably similar to the repr of the `call_args_list`:
+
+    >>> expected = [call(1, 2, 3), call(4, 5, 6), call()]
+    >>> mock.call_args_list == expected
+    True
+
+
+Coping with mutable arguments
+-----------------------------
+
+Another situation is rare, but can bite you, is when your mock is called with
+mutable arguments. `call_args` and `call_args_list` store *references* to the
+arguments. If the arguments are mutated by the code under test then you can no
+longer make assertions about what the values were when the mock was called.
+
+Here's some example code that shows the problem. Imagine the following functions
+defined in 'mymodule'::
+
+    def frob(val):
+        pass
+
+    def grob(val):
+        "First frob and then clear val"
+        frob(val)
+        val.clear()
+
+When we try to test that `grob` calls `frob` with the correct argument look
+what happens:
+
+    >>> with patch('mymodule.frob') as mock_frob:
+    ...     val = set([6])
+    ...     mymodule.grob(val)
+    ...
+    >>> val
+    set([])
+    >>> mock_frob.assert_called_with(set([6]))
+    Traceback (most recent call last):
+        ...
+    AssertionError: Expected: ((set([6]),), {})
+    Called with: ((set([]),), {})
+
+One possibility would be for mock to copy the arguments you pass in. This
+could then cause problems if you do assertions that rely on object identity
+for equality.
+
+Here's one solution that uses the :attr:`side_effect`
+functionality. If you provide a `side_effect` function for a mock then
+`side_effect` will be called with the same args as the mock. This gives us an
+opportunity to copy the arguments and store them for later assertions. In this
+example I'm using *another* mock to store the arguments so that I can use the
+mock methods for doing the assertion. Again a helper function sets this up for
+me.
+
+    >>> from copy import deepcopy
+    >>> from unittest.mock import Mock, patch, DEFAULT
+    >>> def copy_call_args(mock):
+    ...     new_mock = Mock()
+    ...     def side_effect(*args, **kwargs):
+    ...         args = deepcopy(args)
+    ...         kwargs = deepcopy(kwargs)
+    ...         new_mock(*args, **kwargs)
+    ...         return DEFAULT
+    ...     mock.side_effect = side_effect
+    ...     return new_mock
+    ...
+    >>> with patch('mymodule.frob') as mock_frob:
+    ...     new_mock = copy_call_args(mock_frob)
+    ...     val = set([6])
+    ...     mymodule.grob(val)
+    ...
+    >>> new_mock.assert_called_with(set([6]))
+    >>> new_mock.call_args
+    call(set([6]))
+
+`copy_call_args` is called with the mock that will be called. It returns a new
+mock that we do the assertion on. The `side_effect` function makes a copy of
+the args and calls our `new_mock` with the copy.
+
+.. note::
+
+    If your mock is only going to be used once there is an easier way of
+    checking arguments at the point they are called. You can simply do the
+    checking inside a `side_effect` function.
+
+        >>> def side_effect(arg):
+        ...     assert arg == set([6])
+        ...
+        >>> mock = Mock(side_effect=side_effect)
+        >>> mock(set([6]))
+        >>> mock(set())
+        Traceback (most recent call last):
+            ...
+        AssertionError
+
+An alternative approach is to create a subclass of `Mock` or `MagicMock` that
+copies (using :func:`copy.deepcopy`) the arguments.
+Here's an example implementation:
+
+    >>> from copy import deepcopy
+    >>> class CopyingMock(MagicMock):
+    ...     def __call__(self, *args, **kwargs):
+    ...         args = deepcopy(args)
+    ...         kwargs = deepcopy(kwargs)
+    ...         return super(CopyingMock, self).__call__(*args, **kwargs)
+    ...
+    >>> c = CopyingMock(return_value=None)
+    >>> arg = set()
+    >>> c(arg)
+    >>> arg.add(1)
+    >>> c.assert_called_with(set())
+    >>> c.assert_called_with(arg)
+    Traceback (most recent call last):
+        ...
+    AssertionError: Expected call: mock(set([1]))
+    Actual call: mock(set([]))
+    >>> c.foo
+    <CopyingMock name='mock.foo' id='...'>
+
+When you subclass `Mock` or `MagicMock` all dynamically created attributes,
+and the `return_value` will use your subclass automatically. That means all
+children of a `CopyingMock` will also have the type `CopyingMock`.
+
+
+Multiple calls with different effects
+-------------------------------------
+
+Handling code that needs to behave differently on subsequent calls during the
+test can be tricky. For example you may have a function that needs to raise
+an exception the first time it is called but returns a response on the second
+call (testing retry behaviour).
+
+One approach is to use a :attr:`side_effect` function that replaces itself. The
+first time it is called the `side_effect` sets a new `side_effect` that will
+be used for the second call. It then raises an exception:
+
+    >>> def side_effect(*args):
+    ...   def second_call(*args):
+    ...     return 'response'
+    ...   mock.side_effect = second_call
+    ...   raise Exception('boom')
+    ...
+    >>> mock = Mock(side_effect=side_effect)
+    >>> mock('first')
+    Traceback (most recent call last):
+        ...
+    Exception: boom
+    >>> mock('second')
+    'response'
+    >>> mock.assert_called_with('second')
+
+Another perfectly valid way would be to pop return values from a list. If the
+return value is an exception, raise it instead of returning it:
+
+    >>> returns = [Exception('boom'), 'response']
+    >>> def side_effect(*args):
+    ...   result = returns.pop(0)
+    ...   if isinstance(result, Exception):
+    ...     raise result
+    ...   return result
+    ...
+    >>> mock = Mock(side_effect=side_effect)
+    >>> mock('first')
+    Traceback (most recent call last):
+        ...
+    Exception: boom
+    >>> mock('second')
+    'response'
+    >>> mock.assert_called_with('second')
+
+Which approach you prefer is a matter of taste. The first approach is actually
+a line shorter but maybe the second approach is more readable.
+
+
+Nesting Patches
+---------------
+
+Using patch as a context manager is nice, but if you do multiple patches you
+can end up with nested with statements indenting further and further to the
+right:
+
+    >>> class MyTest(TestCase):
+    ...
+    ...     def test_foo(self):
+    ...         with patch('mymodule.Foo') as mock_foo:
+    ...             with patch('mymodule.Bar') as mock_bar:
+    ...                 with patch('mymodule.Spam') as mock_spam:
+    ...                     assert mymodule.Foo is mock_foo
+    ...                     assert mymodule.Bar is mock_bar
+    ...                     assert mymodule.Spam is mock_spam
+    ...
+    >>> original = mymodule.Foo
+    >>> MyTest('test_foo').test_foo()
+    >>> assert mymodule.Foo is original
+
+With unittest `cleanup` functions and the :ref:`start-and-stop` we can
+achieve the same effect without the nested indentation. A simple helper
+method, `create_patch`, puts the patch in place and returns the created mock
+for us:
+
+    >>> class MyTest(TestCase):
+    ...
+    ...     def create_patch(self, name):
+    ...         patcher = patch(name)
+    ...         thing = patcher.start()
+    ...         self.addCleanup(patcher.stop)
+    ...         return thing
+    ...
+    ...     def test_foo(self):
+    ...         mock_foo = self.create_patch('mymodule.Foo')
+    ...         mock_bar = self.create_patch('mymodule.Bar')
+    ...         mock_spam = self.create_patch('mymodule.Spam')
+    ...
+    ...         assert mymodule.Foo is mock_foo
+    ...         assert mymodule.Bar is mock_bar
+    ...         assert mymodule.Spam is mock_spam
+    ...
+    >>> original = mymodule.Foo
+    >>> MyTest('test_foo').run()
+    >>> assert mymodule.Foo is original
+
+
+Mocking a dictionary with MagicMock
+-----------------------------------
+
+You may want to mock a dictionary, or other container object, recording all
+access to it whilst having it still behave like a dictionary.
+
+We can do this with :class:`MagicMock`, which will behave like a dictionary,
+and using :data:`~Mock.side_effect` to delegate dictionary access to a real
+underlying dictionary that is under our control.
+
+When the `__getitem__` and `__setitem__` methods of our `MagicMock` are called
+(normal dictionary access) then `side_effect` is called with the key (and in
+the case of `__setitem__` the value too). We can also control what is returned.
+
+After the `MagicMock` has been used we can use attributes like
+:data:`~Mock.call_args_list` to assert about how the dictionary was used:
+
+    >>> my_dict = {'a': 1, 'b': 2, 'c': 3}
+    >>> def getitem(name):
+    ...      return my_dict[name]
+    ...
+    >>> def setitem(name, val):
+    ...     my_dict[name] = val
+    ...
+    >>> mock = MagicMock()
+    >>> mock.__getitem__.side_effect = getitem
+    >>> mock.__setitem__.side_effect = setitem
+
+.. note::
+
+    An alternative to using `MagicMock` is to use `Mock` and *only* provide
+    the magic methods you specifically want:
+
+        >>> mock = Mock()
+        >>> mock.__setitem__ = Mock(side_effect=getitem)
+        >>> mock.__getitem__ = Mock(side_effect=setitem)
+
+    A *third* option is to use `MagicMock` but passing in `dict` as the `spec`
+    (or `spec_set`) argument so that the `MagicMock` created only has
+    dictionary magic methods available:
+
+        >>> mock = MagicMock(spec_set=dict)
+        >>> mock.__getitem__.side_effect = getitem
+        >>> mock.__setitem__.side_effect = setitem
+
+With these side effect functions in place, the `mock` will behave like a normal
+dictionary but recording the access. It even raises a `KeyError` if you try
+to access a key that doesn't exist.
+
+    >>> mock['a']
+    1
+    >>> mock['c']
+    3
+    >>> mock['d']
+    Traceback (most recent call last):
+        ...
+    KeyError: 'd'
+    >>> mock['b'] = 'fish'
+    >>> mock['d'] = 'eggs'
+    >>> mock['b']
+    'fish'
+    >>> mock['d']
+    'eggs'
+
+After it has been used you can make assertions about the access using the normal
+mock methods and attributes:
+
+    >>> mock.__getitem__.call_args_list
+    [call('a'), call('c'), call('d'), call('b'), call('d')]
+    >>> mock.__setitem__.call_args_list
+    [call('b', 'fish'), call('d', 'eggs')]
+    >>> my_dict
+    {'a': 1, 'c': 3, 'b': 'fish', 'd': 'eggs'}
+
+
+Mock subclasses and their attributes
+------------------------------------
+
+There are various reasons why you might want to subclass `Mock`. One reason
+might be to add helper methods. Here's a silly example:
+
+    >>> class MyMock(MagicMock):
+    ...     def has_been_called(self):
+    ...         return self.called
+    ...
+    >>> mymock = MyMock(return_value=None)
+    >>> mymock
+    <MyMock id='...'>
+    >>> mymock.has_been_called()
+    False
+    >>> mymock()
+    >>> mymock.has_been_called()
+    True
+
+The standard behaviour for `Mock` instances is that attributes and the return
+value mocks are of the same type as the mock they are accessed on. This ensures
+that `Mock` attributes are `Mocks` and `MagicMock` attributes are `MagicMocks`
+[#]_. So if you're subclassing to add helper methods then they'll also be
+available on the attributes and return value mock of instances of your
+subclass.
+
+    >>> mymock.foo
+    <MyMock name='mock.foo' id='...'>
+    >>> mymock.foo.has_been_called()
+    False
+    >>> mymock.foo()
+    <MyMock name='mock.foo()' id='...'>
+    >>> mymock.foo.has_been_called()
+    True
+
+Sometimes this is inconvenient. For example, `one user
+<https://code.google.com/p/mock/issues/detail?id=105>`_ is subclassing mock to
+created a `Twisted adaptor
+<http://twistedmatrix.com/documents/11.0.0/api/twisted.python.components.html>`_.
+Having this applied to attributes too actually causes errors.
+
+`Mock` (in all its flavours) uses a method called `_get_child_mock` to create
+these "sub-mocks" for attributes and return values. You can prevent your
+subclass being used for attributes by overriding this method. The signature is
+that it takes arbitrary keyword arguments (`**kwargs`) which are then passed
+onto the mock constructor:
+
+    >>> class Subclass(MagicMock):
+    ...     def _get_child_mock(self, **kwargs):
+    ...         return MagicMock(**kwargs)
+    ...
+    >>> mymock = Subclass()
+    >>> mymock.foo
+    <MagicMock name='mock.foo' id='...'>
+    >>> assert isinstance(mymock, Subclass)
+    >>> assert not isinstance(mymock.foo, Subclass)
+    >>> assert not isinstance(mymock(), Subclass)
+
+.. [#] An exception to this rule are the non-callable mocks. Attributes use the
+    callable variant because otherwise non-callable mocks couldn't have callable
+    methods.
+
+
+Mocking imports with patch.dict
+-------------------------------
+
+One situation where mocking can be hard is where you have a local import inside
+a function. These are harder to mock because they aren't using an object from
+the module namespace that we can patch out.
+
+Generally local imports are to be avoided. They are sometimes done to prevent
+circular dependencies, for which there is *usually* a much better way to solve
+the problem (refactor the code) or to prevent "up front costs" by delaying the
+import. This can also be solved in better ways than an unconditional local
+import (store the module as a class or module attribute and only do the import
+on first use).
+
+That aside there is a way to use `mock` to affect the results of an import.
+Importing fetches an *object* from the `sys.modules` dictionary. Note that it
+fetches an *object*, which need not be a module. Importing a module for the
+first time results in a module object being put in `sys.modules`, so usually
+when you import something you get a module back. This need not be the case
+however.
+
+This means you can use :func:`patch.dict` to *temporarily* put a mock in place
+in `sys.modules`. Any imports whilst this patch is active will fetch the mock.
+When the patch is complete (the decorated function exits, the with statement
+body is complete or `patcher.stop()` is called) then whatever was there
+previously will be restored safely.
+
+Here's an example that mocks out the 'fooble' module.
+
+    >>> mock = Mock()
+    >>> with patch.dict('sys.modules', {'fooble': mock}):
+    ...    import fooble
+    ...    fooble.blob()
+    ...
+    <Mock name='mock.blob()' id='...'>
+    >>> assert 'fooble' not in sys.modules
+    >>> mock.blob.assert_called_once_with()
+
+As you can see the `import fooble` succeeds, but on exit there is no 'fooble'
+left in `sys.modules`.
+
+This also works for the `from module import name` form:
+
+    >>> mock = Mock()
+    >>> with patch.dict('sys.modules', {'fooble': mock}):
+    ...    from fooble import blob
+    ...    blob.blip()
+    ...
+    <Mock name='mock.blob.blip()' id='...'>
+    >>> mock.blob.blip.assert_called_once_with()
+
+With slightly more work you can also mock package imports:
+
+    >>> mock = Mock()
+    >>> modules = {'package': mock, 'package.module': mock.module}
+    >>> with patch.dict('sys.modules', modules):
+    ...    from package.module import fooble
+    ...    fooble()
+    ...
+    <Mock name='mock.module.fooble()' id='...'>
+    >>> mock.module.fooble.assert_called_once_with()
+
+
+Tracking order of calls and less verbose call assertions
+--------------------------------------------------------
+
+The :class:`Mock` class allows you to track the *order* of method calls on
+your mock objects through the :attr:`~Mock.method_calls` attribute. This
+doesn't allow you to track the order of calls between separate mock objects,
+however we can use :attr:`~Mock.mock_calls` to achieve the same effect.
+
+Because mocks track calls to child mocks in `mock_calls`, and accessing an
+arbitrary attribute of a mock creates a child mock, we can create our separate
+mocks from a parent one. Calls to those child mock will then all be recorded,
+in order, in the `mock_calls` of the parent:
+
+    >>> manager = Mock()
+    >>> mock_foo = manager.foo
+    >>> mock_bar = manager.bar
+
+    >>> mock_foo.something()
+    <Mock name='mock.foo.something()' id='...'>
+    >>> mock_bar.other.thing()
+    <Mock name='mock.bar.other.thing()' id='...'>
+
+    >>> manager.mock_calls
+    [call.foo.something(), call.bar.other.thing()]
+
+We can then assert about the calls, including the order, by comparing with
+the `mock_calls` attribute on the manager mock:
+
+    >>> expected_calls = [call.foo.something(), call.bar.other.thing()]
+    >>> manager.mock_calls == expected_calls
+    True
+
+If `patch` is creating, and putting in place, your mocks then you can attach
+them to a manager mock using the :meth:`~Mock.attach_mock` method. After
+attaching calls will be recorded in `mock_calls` of the manager.
+
+    >>> manager = MagicMock()
+    >>> with patch('mymodule.Class1') as MockClass1:
+    ...     with patch('mymodule.Class2') as MockClass2:
+    ...         manager.attach_mock(MockClass1, 'MockClass1')
+    ...         manager.attach_mock(MockClass2, 'MockClass2')
+    ...         MockClass1().foo()
+    ...         MockClass2().bar()
+    ...
+    <MagicMock name='mock.MockClass1().foo()' id='...'>
+    <MagicMock name='mock.MockClass2().bar()' id='...'>
+    >>> manager.mock_calls
+    [call.MockClass1(),
+     call.MockClass1().foo(),
+     call.MockClass2(),
+     call.MockClass2().bar()]
+
+If many calls have been made, but you're only interested in a particular
+sequence of them then an alternative is to use the
+:meth:`~Mock.assert_has_calls` method. This takes a list of calls (constructed
+with the :data:`call` object). If that sequence of calls are in
+:attr:`~Mock.mock_calls` then the assert succeeds.
+
+    >>> m = MagicMock()
+    >>> m().foo().bar().baz()
+    <MagicMock name='mock().foo().bar().baz()' id='...'>
+    >>> m.one().two().three()
+    <MagicMock name='mock.one().two().three()' id='...'>
+    >>> calls = call.one().two().three().call_list()
+    >>> m.assert_has_calls(calls)
+
+Even though the chained call `m.one().two().three()` aren't the only calls that
+have been made to the mock, the assert still succeeds.
+
+Sometimes a mock may have several calls made to it, and you are only interested
+in asserting about *some* of those calls. You may not even care about the
+order. In this case you can pass `any_order=True` to `assert_has_calls`:
+
+    >>> m = MagicMock()
+    >>> m(1), m.two(2, 3), m.seven(7), m.fifty('50')
+    (...)
+    >>> calls = [call.fifty('50'), call(1), call.seven(7)]
+    >>> m.assert_has_calls(calls, any_order=True)
+
+
+More complex argument matching
+------------------------------
+
+Using the same basic concept as :data:`ANY` we can implement matchers to do more
+complex assertions on objects used as arguments to mocks.
+
+Suppose we expect some object to be passed to a mock that by default
+compares equal based on object identity (which is the Python default for user
+defined classes). To use :meth:`~Mock.assert_called_with` we would need to pass
+in the exact same object. If we are only interested in some of the attributes
+of this object then we can create a matcher that will check these attributes
+for us.
+
+You can see in this example how a 'standard' call to `assert_called_with` isn't
+sufficient:
+
+    >>> class Foo(object):
+    ...     def __init__(self, a, b):
+    ...         self.a, self.b = a, b
+    ...
+    >>> mock = Mock(return_value=None)
+    >>> mock(Foo(1, 2))
+    >>> mock.assert_called_with(Foo(1, 2))
+    Traceback (most recent call last):
+        ...
+    AssertionError: Expected: call(<__main__.Foo object at 0x...>)
+    Actual call: call(<__main__.Foo object at 0x...>)
+
+A comparison function for our `Foo` class might look something like this:
+
+    >>> def compare(self, other):
+    ...     if not type(self) == type(other):
+    ...         return False
+    ...     if self.a != other.a:
+    ...         return False
+    ...     if self.b != other.b:
+    ...         return False
+    ...     return True
+    ...
+
+And a matcher object that can use comparison functions like this for its
+equality operation would look something like this:
+
+    >>> class Matcher(object):
+    ...     def __init__(self, compare, some_obj):
+    ...         self.compare = compare
+    ...         self.some_obj = some_obj
+    ...     def __eq__(self, other):
+    ...         return self.compare(self.some_obj, other)
+    ...
+
+Putting all this together:
+
+    >>> match_foo = Matcher(compare, Foo(1, 2))
+    >>> mock.assert_called_with(match_foo)
+
+The `Matcher` is instantiated with our compare function and the `Foo` object
+we want to compare against. In `assert_called_with` the `Matcher` equality
+method will be called, which compares the object the mock was called with
+against the one we created our matcher with. If they match then
+`assert_called_with` passes, and if they don't an `AssertionError` is raised:
+
+    >>> match_wrong = Matcher(compare, Foo(3, 4))
+    >>> mock.assert_called_with(match_wrong)
+    Traceback (most recent call last):
+        ...
+    AssertionError: Expected: ((<Matcher object at 0x...>,), {})
+    Called with: ((<Foo object at 0x...>,), {})
+
+With a bit of tweaking you could have the comparison function raise the
+`AssertionError` directly and provide a more useful failure message.
+
+As of version 1.5, the Python testing library `PyHamcrest
+<http://pypi.python.org/pypi/PyHamcrest>`_ provides similar functionality,
+that may be useful here, in the form of its equality matcher
+(`hamcrest.library.integration.match_equality
+<http://packages.python.org/PyHamcrest/integration.html#hamcrest.library.integration.match_equality>`_).
diff --git a/Doc/library/unittest.mock-getting-started.rst b/Doc/library/unittest.mock-getting-started.rst
new file mode 100644
index 0000000..850a894
--- /dev/null
+++ b/Doc/library/unittest.mock-getting-started.rst
@@ -0,0 +1,419 @@
+:mod:`unittest.mock` --- getting started
+========================================
+
+.. module:: unittest.mock
+   :synopsis: Mock object library.
+.. moduleauthor:: Michael Foord <michael@python.org>
+.. currentmodule:: unittest.mock
+
+.. versionadded:: 3.3
+
+
+.. _getting-started:
+
+Using Mock
+----------
+
+Mock Patching Methods
+~~~~~~~~~~~~~~~~~~~~~
+
+Common uses for :class:`Mock` objects include:
+
+* Patching methods
+* Recording method calls on objects
+
+You might want to replace a method on an object to check that
+it is called with the correct arguments by another part of the system:
+
+    >>> real = SomeClass()
+    >>> real.method = MagicMock(name='method')
+    >>> real.method(3, 4, 5, key='value')
+    <MagicMock name='method()' id='...'>
+
+Once our mock has been used (`real.method` in this example) it has methods
+and attributes that allow you to make assertions about how it has been used.
+
+.. note::
+
+    In most of these examples the :class:`Mock` and :class:`MagicMock` classes
+    are interchangeable. As the `MagicMock` is the more capable class it makes
+    a sensible one to use by default.
+
+Once the mock has been called its :attr:`~Mock.called` attribute is set to
+`True`. More importantly we can use the :meth:`~Mock.assert_called_with` or
+:meth`~Mock.assert_called_once_with` method to check that it was called with
+the correct arguments.
+
+This example tests that calling `ProductionClass().method` results in a call to
+the `something` method:
+
+    >>> class ProductionClass(object):
+    ...     def method(self):
+    ...         self.something(1, 2, 3)
+    ...     def something(self, a, b, c):
+    ...         pass
+    ...
+    >>> real = ProductionClass()
+    >>> real.something = MagicMock()
+    >>> real.method()
+    >>> real.something.assert_called_once_with(1, 2, 3)
+
+
+
+Mock for Method Calls on an Object
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+In the last example we patched a method directly on an object to check that it
+was called correctly. Another common use case is to pass an object into a
+method (or some part of the system under test) and then check that it is used
+in the correct way.
+
+The simple `ProductionClass` below has a `closer` method. If it is called with
+an object then it calls `close` on it.
+
+    >>> class ProductionClass(object):
+    ...     def closer(self, something):
+    ...         something.close()
+    ...
+
+So to test it we need to pass in an object with a `close` method and check
+that it was called correctly.
+
+    >>> real = ProductionClass()
+    >>> mock = Mock()
+    >>> real.closer(mock)
+    >>> mock.close.assert_called_with()
+
+We don't have to do any work to provide the 'close' method on our mock.
+Accessing close creates it. So, if 'close' hasn't already been called then
+accessing it in the test will create it, but :meth:`~Mock.assert_called_with`
+will raise a failure exception.
+
+
+Mocking Classes
+~~~~~~~~~~~~~~~
+
+A common use case is to mock out classes instantiated by your code under test.
+When you patch a class, then that class is replaced with a mock. Instances
+are created by *calling the class*. This means you access the "mock instance"
+by looking at the return value of the mocked class.
+
+In the example below we have a function `some_function` that instantiates `Foo`
+and calls a method on it. The call to `patch` replaces the class `Foo` with a
+mock. The `Foo` instance is the result of calling the mock, so it is configured
+by modify the mock :attr:`~Mock.return_value`.
+
+    >>> def some_function():
+    ...     instance = module.Foo()
+    ...     return instance.method()
+    ...
+    >>> with patch('module.Foo') as mock:
+    ...     instance = mock.return_value
+    ...     instance.method.return_value = 'the result'
+    ...     result = some_function()
+    ...     assert result == 'the result'
+
+
+Naming your mocks
+~~~~~~~~~~~~~~~~~
+
+It can be useful to give your mocks a name. The name is shown in the repr of
+the mock and can be helpful when the mock appears in test failure messages. The
+name is also propagated to attributes or methods of the mock:
+
+    >>> mock = MagicMock(name='foo')
+    >>> mock
+    <MagicMock name='foo' id='...'>
+    >>> mock.method
+    <MagicMock name='foo.method' id='...'>
+
+
+Tracking all Calls
+~~~~~~~~~~~~~~~~~~
+
+Often you want to track more than a single call to a method. The
+:attr:`~Mock.mock_calls` attribute records all calls
+to child attributes of the mock - and also to their children.
+
+    >>> mock = MagicMock()
+    >>> mock.method()
+    <MagicMock name='mock.method()' id='...'>
+    >>> mock.attribute.method(10, x=53)
+    <MagicMock name='mock.attribute.method()' id='...'>
+    >>> mock.mock_calls
+    [call.method(), call.attribute.method(10, x=53)]
+
+If you make an assertion about `mock_calls` and any unexpected methods
+have been called, then the assertion will fail. This is useful because as well
+as asserting that the calls you expected have been made, you are also checking
+that they were made in the right order and with no additional calls:
+
+You use the :data:`call` object to construct lists for comparing with
+`mock_calls`:
+
+    >>> expected = [call.method(), call.attribute.method(10, x=53)]
+    >>> mock.mock_calls == expected
+    True
+
+
+Setting Return Values and Attributes
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+Setting the return values on a mock object is trivially easy:
+
+    >>> mock = Mock()
+    >>> mock.return_value = 3
+    >>> mock()
+    3
+
+Of course you can do the same for methods on the mock:
+
+    >>> mock = Mock()
+    >>> mock.method.return_value = 3
+    >>> mock.method()
+    3
+
+The return value can also be set in the constructor:
+
+    >>> mock = Mock(return_value=3)
+    >>> mock()
+    3
+
+If you need an attribute setting on your mock, just do it:
+
+    >>> mock = Mock()
+    >>> mock.x = 3
+    >>> mock.x
+    3
+
+Sometimes you want to mock up a more complex situation, like for example
+`mock.connection.cursor().execute("SELECT 1")`. If we wanted this call to
+return a list, then we have to configure the result of the nested call.
+
+We can use :data:`call` to construct the set of calls in a "chained call" like
+this for easy assertion afterwards:
+
+    >>> mock = Mock()
+    >>> cursor = mock.connection.cursor.return_value
+    >>> cursor.execute.return_value = ['foo']
+    >>> mock.connection.cursor().execute("SELECT 1")
+    ['foo']
+    >>> expected = call.connection.cursor().execute("SELECT 1").call_list()
+    >>> mock.mock_calls
+    [call.connection.cursor(), call.connection.cursor().execute('SELECT 1')]
+    >>> mock.mock_calls == expected
+    True
+
+It is the call to `.call_list()` that turns our call object into a list of
+calls representing the chained calls.
+
+
+Raising exceptions with mocks
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+A useful attribute is :attr:`~Mock.side_effect`. If you set this to an
+exception class or instance then the exception will be raised when the mock
+is called.
+
+    >>> mock = Mock(side_effect=Exception('Boom!'))
+    >>> mock()
+    Traceback (most recent call last):
+      ...
+    Exception: Boom!
+
+
+Side effect functions and iterables
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+`side_effect` can also be set to a function or an iterable. The use case for
+`side_effect` as an iterable is where your mock is going to be called several
+times, and you want each call to return a different value. When you set
+`side_effect` to an iterable every call to the mock returns the next value
+from the iterable:
+
+    >>> mock = MagicMock(side_effect=[4, 5, 6])
+    >>> mock()
+    4
+    >>> mock()
+    5
+    >>> mock()
+    6
+
+
+For more advanced use cases, like dynamically varying the return values
+depending on what the mock is called with, `side_effect` can be a function.
+The function will be called with the same arguments as the mock. Whatever the
+function returns is what the call returns:
+
+    >>> vals = {(1, 2): 1, (2, 3): 2}
+    >>> def side_effect(*args):
+    ...     return vals[args]
+    ...
+    >>> mock = MagicMock(side_effect=side_effect)
+    >>> mock(1, 2)
+    1
+    >>> mock(2, 3)
+    2
+
+
+Creating a Mock from an Existing Object
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+One problem with over use of mocking is that it couples your tests to the
+implementation of your mocks rather than your real code. Suppose you have a
+class that implements `some_method`. In a test for another class, you
+provide a mock of this object that *also* provides `some_method`. If later
+you refactor the first class, so that it no longer has `some_method` - then
+your tests will continue to pass even though your code is now broken!
+
+`Mock` allows you to provide an object as a specification for the mock,
+using the `spec` keyword argument. Accessing methods / attributes on the
+mock that don't exist on your specification object will immediately raise an
+attribute error. If you change the implementation of your specification, then
+tests that use that class will start failing immediately without you having to
+instantiate the class in those tests.
+
+    >>> mock = Mock(spec=SomeClass)
+    >>> mock.old_method()
+    Traceback (most recent call last):
+       ...
+    AttributeError: object has no attribute 'old_method'
+
+If you want a stronger form of specification that prevents the setting
+of arbitrary attributes as well as the getting of them then you can use
+`spec_set` instead of `spec`.
+
+
+
+Patch Decorators
+----------------
+
+.. note::
+
+   With `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>`.
+
+
+A common need in tests is to patch a class attribute or a module attribute,
+for example patching a builtin or patching a class in a module to test that it
+is instantiated. Modules and classes are effectively global, so patching on
+them has to be undone after the test or the patch will persist into other
+tests and cause hard to diagnose problems.
+
+mock provides three convenient decorators for this: `patch`, `patch.object` and
+`patch.dict`. `patch` takes a single string, of the form
+`package.module.Class.attribute` to specify the attribute you are patching. It
+also optionally takes a value that you want the attribute (or class or
+whatever) to be replaced with. 'patch.object' takes an object and the name of
+the attribute you would like patched, plus optionally the value to patch it
+with.
+
+`patch.object`:
+
+    >>> original = SomeClass.attribute
+    >>> @patch.object(SomeClass, 'attribute', sentinel.attribute)
+    ... def test():
+    ...     assert SomeClass.attribute == sentinel.attribute
+    ...
+    >>> test()
+    >>> assert SomeClass.attribute == original
+
+    >>> @patch('package.module.attribute', sentinel.attribute)
+    ... def test():
+    ...     from package.module import attribute
+    ...     assert attribute is sentinel.attribute
+    ...
+    >>> test()
+
+If you are patching a module (including `__builtin__`) then use `patch`
+instead of `patch.object`:
+
+    >>> mock = MagicMock(return_value = sentinel.file_handle)
+    >>> with patch('__builtin__.open', mock):
+    ...     handle = open('filename', 'r')
+    ...
+    >>> mock.assert_called_with('filename', 'r')
+    >>> assert handle == sentinel.file_handle, "incorrect file handle returned"
+
+The module name can be 'dotted', in the form `package.module` if needed:
+
+    >>> @patch('package.module.ClassName.attribute', sentinel.attribute)
+    ... def test():
+    ...     from package.module import ClassName
+    ...     assert ClassName.attribute == sentinel.attribute
+    ...
+    >>> test()
+
+A nice pattern is to actually decorate test methods themselves:
+
+    >>> class MyTest(unittest2.TestCase):
+    ...     @patch.object(SomeClass, 'attribute', sentinel.attribute)
+    ...     def test_something(self):
+    ...         self.assertEqual(SomeClass.attribute, sentinel.attribute)
+    ...
+    >>> original = SomeClass.attribute
+    >>> MyTest('test_something').test_something()
+    >>> assert SomeClass.attribute == original
+
+If you want to patch with a Mock, you can use `patch` with only one argument
+(or `patch.object` with two arguments). The mock will be created for you and
+passed into the test function / method:
+
+    >>> class MyTest(unittest2.TestCase):
+    ...     @patch.object(SomeClass, 'static_method')
+    ...     def test_something(self, mock_method):
+    ...         SomeClass.static_method()
+    ...         mock_method.assert_called_with()
+    ...
+    >>> MyTest('test_something').test_something()
+
+You can stack up multiple patch decorators using this pattern:
+
+    >>> class MyTest(unittest2.TestCase):
+    ...     @patch('package.module.ClassName1')
+    ...     @patch('package.module.ClassName2')
+    ...     def test_something(self, MockClass2, MockClass1):
+    ...         self.assertTrue(package.module.ClassName1 is MockClass1)
+    ...         self.assertTrue(package.module.ClassName2 is MockClass2)
+    ...
+    >>> MyTest('test_something').test_something()
+
+When you nest patch decorators the mocks are passed in to the decorated
+function in the same order they applied (the normal *python* order that
+decorators are applied). This means from the bottom up, so in the example
+above the mock for `test_module.ClassName2` is passed in first.
+
+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
+
+`patch`, `patch.object` and `patch.dict` can all be used as context managers.
+
+Where you use `patch` to create a mock for you, you can get a reference to the
+mock using the "as" form of the with statement:
+
+    >>> class ProductionClass(object):
+    ...     def method(self):
+    ...         pass
+    ...
+    >>> with patch.object(ProductionClass, 'method') as mock_method:
+    ...     mock_method.return_value = None
+    ...     real = ProductionClass()
+    ...     real.method(1, 2, 3)
+    ...
+    >>> mock_method.assert_called_with(1, 2, 3)
+
+
+As an alternative `patch`, `patch.object` and `patch.dict` can be used as
+class decorators. When used in this way it is the same as applying the
+decorator indvidually to every method whose name starts with "test".
+
+For some more advanced examples, see the :ref:`further-examples` page.
diff --git a/Doc/library/unittest.mock-helpers.rst b/Doc/library/unittest.mock-helpers.rst
new file mode 100644
index 0000000..6c68a48
--- /dev/null
+++ b/Doc/library/unittest.mock-helpers.rst
@@ -0,0 +1,537 @@
+:mod:`unittest.mock` --- helpers
+================================
+
+.. module:: unittest.mock
+   :synopsis: Mock object library.
+.. moduleauthor:: Michael Foord <michael@python.org>
+.. currentmodule:: unittest.mock
+
+.. versionadded:: 3.3
+
+
+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.
diff --git a/Doc/library/unittest.mock-magicmethods.rst b/Doc/library/unittest.mock-magicmethods.rst
new file mode 100644
index 0000000..f5209ab
--- /dev/null
+++ b/Doc/library/unittest.mock-magicmethods.rst
@@ -0,0 +1,226 @@
+:mod:`unittest.mock` --- MagicMock and magic method support
+===========================================================
+
+.. module:: unittest.mock
+   :synopsis: Mock object library.
+.. moduleauthor:: Michael Foord <michael@python.org>
+.. currentmodule:: unittest.mock
+
+.. versionadded:: 3.3
+
+
+.. _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.
diff --git a/Doc/library/unittest.mock-patch.rst b/Doc/library/unittest.mock-patch.rst
new file mode 100644
index 0000000..e3e3525
--- /dev/null
+++ b/Doc/library/unittest.mock-patch.rst
@@ -0,0 +1,538 @@
+:mod:`unittest.mock` --- the patchers
+=====================================
+
+.. module:: unittest.mock
+   :synopsis: Mock object library.
+.. moduleauthor:: Michael Foord <michael@python.org>
+.. currentmodule:: unittest.mock
+
+.. versionadded:: 3.3
+
+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`
+    (specified in the form `'package.module.ClassName'`) is patched
+    with a `new` object. When the function/with statement exits the patch is
+    undone.
+
+    The `target` is imported and the specified attribute patched with the new
+    object, so it must be importable from the environment you are calling the
+    decorator from. The target is imported when the decorated function is
+    executed, not at decoration time.
+
+    If `new` is omitted, then a new `MagicMock` is created and passed in as an
+    extra argument to the decorated function.
+
+    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.
+
+
+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.
+
+In fact `start` and `stop` are just aliases for the context manager
+`__enter__` and `__exit__` methods.
+
+
+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>`_.
diff --git a/Doc/library/unittest.mock.rst b/Doc/library/unittest.mock.rst
new file mode 100644
index 0000000..71b7386
--- /dev/null
+++ b/Doc/library/unittest.mock.rst
@@ -0,0 +1,900 @@
+: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 and ignoring `return_value`). 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)]
+
+
+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
+
+
+.. _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>`.