forked from mirrors/gecko-dev
479 lines
14 KiB
Text
479 lines
14 KiB
Text
===========================
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Getting Started with Mock
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===========================
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.. _getting-started:
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.. index:: Getting Started
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.. testsetup::
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class SomeClass(object):
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static_method = None
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class_method = None
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attribute = None
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sys.modules['package'] = package = Mock(name='package')
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sys.modules['package.module'] = module = package.module
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sys.modules['module'] = package.module
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Using Mock
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==========
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Mock Patching Methods
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---------------------
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Common uses for :class:`Mock` objects include:
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* Patching methods
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* Recording method calls on objects
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You might want to replace a method on an object to check that
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it is called with the correct arguments by another part of the system:
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.. doctest::
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>>> real = SomeClass()
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>>> real.method = MagicMock(name='method')
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>>> real.method(3, 4, 5, key='value')
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<MagicMock name='method()' id='...'>
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Once our mock has been used (`real.method` in this example) it has methods
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and attributes that allow you to make assertions about how it has been used.
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.. note::
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In most of these examples the :class:`Mock` and :class:`MagicMock` classes
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are interchangeable. As the `MagicMock` is the more capable class it makes
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a sensible one to use by default.
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Once the mock has been called its :attr:`~Mock.called` attribute is set to
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`True`. More importantly we can use the :meth:`~Mock.assert_called_with` or
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:meth:`~Mock.assert_called_once_with` method to check that it was called with
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the correct arguments.
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This example tests that calling `ProductionClass().method` results in a call to
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the `something` method:
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.. doctest::
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>>> from mock import MagicMock
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>>> class ProductionClass(object):
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... def method(self):
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... self.something(1, 2, 3)
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... def something(self, a, b, c):
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... pass
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...
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>>> real = ProductionClass()
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>>> real.something = MagicMock()
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>>> real.method()
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>>> real.something.assert_called_once_with(1, 2, 3)
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Mock for Method Calls on an Object
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----------------------------------
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In the last example we patched a method directly on an object to check that it
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was called correctly. Another common use case is to pass an object into a
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method (or some part of the system under test) and then check that it is used
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in the correct way.
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The simple `ProductionClass` below has a `closer` method. If it is called with
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an object then it calls `close` on it.
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.. doctest::
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>>> class ProductionClass(object):
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... def closer(self, something):
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... something.close()
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...
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So to test it we need to pass in an object with a `close` method and check
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that it was called correctly.
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.. doctest::
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>>> real = ProductionClass()
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>>> mock = Mock()
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>>> real.closer(mock)
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>>> mock.close.assert_called_with()
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We don't have to do any work to provide the 'close' method on our mock.
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Accessing close creates it. So, if 'close' hasn't already been called then
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accessing it in the test will create it, but :meth:`~Mock.assert_called_with`
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will raise a failure exception.
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Mocking Classes
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---------------
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A common use case is to mock out classes instantiated by your code under test.
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When you patch a class, then that class is replaced with a mock. Instances
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are created by *calling the class*. This means you access the "mock instance"
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by looking at the return value of the mocked class.
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In the example below we have a function `some_function` that instantiates `Foo`
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and calls a method on it. The call to `patch` replaces the class `Foo` with a
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mock. The `Foo` instance is the result of calling the mock, so it is configured
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by modifying the mock :attr:`~Mock.return_value`.
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.. doctest::
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>>> def some_function():
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... instance = module.Foo()
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... return instance.method()
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...
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>>> with patch('module.Foo') as mock:
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... instance = mock.return_value
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... instance.method.return_value = 'the result'
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... result = some_function()
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... assert result == 'the result'
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Naming your mocks
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-----------------
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It can be useful to give your mocks a name. The name is shown in the repr of
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the mock and can be helpful when the mock appears in test failure messages. The
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name is also propagated to attributes or methods of the mock:
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.. doctest::
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>>> mock = MagicMock(name='foo')
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>>> mock
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<MagicMock name='foo' id='...'>
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>>> mock.method
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<MagicMock name='foo.method' id='...'>
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Tracking all Calls
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------------------
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Often you want to track more than a single call to a method. The
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:attr:`~Mock.mock_calls` attribute records all calls
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to child attributes of the mock - and also to their children.
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.. doctest::
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>>> mock = MagicMock()
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>>> mock.method()
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<MagicMock name='mock.method()' id='...'>
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>>> mock.attribute.method(10, x=53)
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<MagicMock name='mock.attribute.method()' id='...'>
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>>> mock.mock_calls
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[call.method(), call.attribute.method(10, x=53)]
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If you make an assertion about `mock_calls` and any unexpected methods
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have been called, then the assertion will fail. This is useful because as well
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as asserting that the calls you expected have been made, you are also checking
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that they were made in the right order and with no additional calls:
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You use the :data:`call` object to construct lists for comparing with
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`mock_calls`:
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.. doctest::
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>>> expected = [call.method(), call.attribute.method(10, x=53)]
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>>> mock.mock_calls == expected
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True
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Setting Return Values and Attributes
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------------------------------------
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Setting the return values on a mock object is trivially easy:
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.. doctest::
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>>> mock = Mock()
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>>> mock.return_value = 3
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>>> mock()
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3
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Of course you can do the same for methods on the mock:
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.. doctest::
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>>> mock = Mock()
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>>> mock.method.return_value = 3
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>>> mock.method()
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3
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The return value can also be set in the constructor:
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.. doctest::
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>>> mock = Mock(return_value=3)
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>>> mock()
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3
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If you need an attribute setting on your mock, just do it:
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.. doctest::
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>>> mock = Mock()
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>>> mock.x = 3
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>>> mock.x
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3
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Sometimes you want to mock up a more complex situation, like for example
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`mock.connection.cursor().execute("SELECT 1")`. If we wanted this call to
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return a list, then we have to configure the result of the nested call.
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We can use :data:`call` to construct the set of calls in a "chained call" like
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this for easy assertion afterwards:
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.. doctest::
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>>> mock = Mock()
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>>> cursor = mock.connection.cursor.return_value
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>>> cursor.execute.return_value = ['foo']
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>>> mock.connection.cursor().execute("SELECT 1")
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['foo']
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>>> expected = call.connection.cursor().execute("SELECT 1").call_list()
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>>> mock.mock_calls
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[call.connection.cursor(), call.connection.cursor().execute('SELECT 1')]
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>>> mock.mock_calls == expected
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True
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It is the call to `.call_list()` that turns our call object into a list of
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calls representing the chained calls.
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Raising exceptions with mocks
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-----------------------------
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A useful attribute is :attr:`~Mock.side_effect`. If you set this to an
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exception class or instance then the exception will be raised when the mock
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is called.
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.. doctest::
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>>> mock = Mock(side_effect=Exception('Boom!'))
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>>> mock()
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Traceback (most recent call last):
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...
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Exception: Boom!
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Side effect functions and iterables
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-----------------------------------
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`side_effect` can also be set to a function or an iterable. The use case for
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`side_effect` as an iterable is where your mock is going to be called several
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times, and you want each call to return a different value. When you set
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`side_effect` to an iterable every call to the mock returns the next value
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from the iterable:
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.. doctest::
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>>> mock = MagicMock(side_effect=[4, 5, 6])
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>>> mock()
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4
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>>> mock()
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5
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>>> mock()
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6
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For more advanced use cases, like dynamically varying the return values
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depending on what the mock is called with, `side_effect` can be a function.
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The function will be called with the same arguments as the mock. Whatever the
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function returns is what the call returns:
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.. doctest::
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>>> vals = {(1, 2): 1, (2, 3): 2}
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>>> def side_effect(*args):
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... return vals[args]
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...
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>>> mock = MagicMock(side_effect=side_effect)
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>>> mock(1, 2)
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1
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>>> mock(2, 3)
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2
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Creating a Mock from an Existing Object
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---------------------------------------
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One problem with over use of mocking is that it couples your tests to the
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implementation of your mocks rather than your real code. Suppose you have a
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class that implements `some_method`. In a test for another class, you
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provide a mock of this object that *also* provides `some_method`. If later
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you refactor the first class, so that it no longer has `some_method` - then
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your tests will continue to pass even though your code is now broken!
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`Mock` allows you to provide an object as a specification for the mock,
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using the `spec` keyword argument. Accessing methods / attributes on the
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mock that don't exist on your specification object will immediately raise an
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attribute error. If you change the implementation of your specification, then
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tests that use that class will start failing immediately without you having to
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instantiate the class in those tests.
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.. doctest::
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>>> mock = Mock(spec=SomeClass)
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>>> mock.old_method()
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Traceback (most recent call last):
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...
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AttributeError: object has no attribute 'old_method'
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If you want a stronger form of specification that prevents the setting
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of arbitrary attributes as well as the getting of them then you can use
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`spec_set` instead of `spec`.
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Patch Decorators
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================
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.. note::
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With `patch` it matters that you patch objects in the namespace where they
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are looked up. This is normally straightforward, but for a quick guide
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read :ref:`where to patch <where-to-patch>`.
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A common need in tests is to patch a class attribute or a module attribute,
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for example patching a builtin or patching a class in a module to test that it
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is instantiated. Modules and classes are effectively global, so patching on
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them has to be undone after the test or the patch will persist into other
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tests and cause hard to diagnose problems.
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mock provides three convenient decorators for this: `patch`, `patch.object` and
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`patch.dict`. `patch` takes a single string, of the form
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`package.module.Class.attribute` to specify the attribute you are patching. It
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also optionally takes a value that you want the attribute (or class or
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whatever) to be replaced with. 'patch.object' takes an object and the name of
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the attribute you would like patched, plus optionally the value to patch it
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with.
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`patch.object`:
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.. doctest::
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>>> original = SomeClass.attribute
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>>> @patch.object(SomeClass, 'attribute', sentinel.attribute)
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... def test():
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... assert SomeClass.attribute == sentinel.attribute
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...
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>>> test()
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>>> assert SomeClass.attribute == original
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>>> @patch('package.module.attribute', sentinel.attribute)
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... def test():
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... from package.module import attribute
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... assert attribute is sentinel.attribute
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...
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>>> test()
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If you are patching a module (including `__builtin__`) then use `patch`
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instead of `patch.object`:
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.. doctest::
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>>> mock = MagicMock(return_value = sentinel.file_handle)
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>>> with patch('__builtin__.open', mock):
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... handle = open('filename', 'r')
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...
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>>> mock.assert_called_with('filename', 'r')
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>>> assert handle == sentinel.file_handle, "incorrect file handle returned"
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The module name can be 'dotted', in the form `package.module` if needed:
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.. doctest::
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>>> @patch('package.module.ClassName.attribute', sentinel.attribute)
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... def test():
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... from package.module import ClassName
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... assert ClassName.attribute == sentinel.attribute
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...
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>>> test()
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A nice pattern is to actually decorate test methods themselves:
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.. doctest::
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>>> class MyTest(unittest2.TestCase):
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... @patch.object(SomeClass, 'attribute', sentinel.attribute)
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... def test_something(self):
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... self.assertEqual(SomeClass.attribute, sentinel.attribute)
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...
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>>> original = SomeClass.attribute
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>>> MyTest('test_something').test_something()
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>>> assert SomeClass.attribute == original
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If you want to patch with a Mock, you can use `patch` with only one argument
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(or `patch.object` with two arguments). The mock will be created for you and
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passed into the test function / method:
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.. doctest::
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>>> class MyTest(unittest2.TestCase):
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... @patch.object(SomeClass, 'static_method')
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... def test_something(self, mock_method):
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... SomeClass.static_method()
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... mock_method.assert_called_with()
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...
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>>> MyTest('test_something').test_something()
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You can stack up multiple patch decorators using this pattern:
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.. doctest::
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>>> class MyTest(unittest2.TestCase):
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... @patch('package.module.ClassName1')
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... @patch('package.module.ClassName2')
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... def test_something(self, MockClass2, MockClass1):
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... self.assertTrue(package.module.ClassName1 is MockClass1)
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... self.assertTrue(package.module.ClassName2 is MockClass2)
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...
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>>> MyTest('test_something').test_something()
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When you nest patch decorators the mocks are passed in to the decorated
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function in the same order they applied (the normal *python* order that
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decorators are applied). This means from the bottom up, so in the example
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above the mock for `test_module.ClassName2` is passed in first.
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There is also :func:`patch.dict` for setting values in a dictionary just
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during a scope and restoring the dictionary to its original state when the test
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ends:
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.. doctest::
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>>> foo = {'key': 'value'}
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>>> original = foo.copy()
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>>> with patch.dict(foo, {'newkey': 'newvalue'}, clear=True):
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... assert foo == {'newkey': 'newvalue'}
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...
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>>> assert foo == original
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`patch`, `patch.object` and `patch.dict` can all be used as context managers.
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Where you use `patch` to create a mock for you, you can get a reference to the
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mock using the "as" form of the with statement:
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.. doctest::
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>>> class ProductionClass(object):
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... def method(self):
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... pass
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...
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>>> with patch.object(ProductionClass, 'method') as mock_method:
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... mock_method.return_value = None
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... real = ProductionClass()
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... real.method(1, 2, 3)
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...
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>>> mock_method.assert_called_with(1, 2, 3)
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As an alternative `patch`, `patch.object` and `patch.dict` can be used as
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class decorators. When used in this way it is the same as applying the
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decorator indvidually to every method whose name starts with "test".
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For some more advanced examples, see the :ref:`further-examples` page.
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