Getting Started with Mock — Mock v0.7.0 documentation

Mock v0.7.0 documentation

# Getting Started with Mock

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# Getting Started with Mock

For comprehensive examples, see the unit tests included in the full source distribution.

## Using Mock

### Mock Patching Methods

`Mock` objects can be used for:

- Patching methods
- Recording method calls on objects

    >>> from mock import Mock
    >>> real = SomeClass()
    >>> real.method = Mock()
    >>> real.method(3, 4, 5, key='value')
    <mock.Mock object at 0x...>

Once the mock has been used it has methods and attributes that allow you to make assertions about how it has been used.

Mock objects are callable. If they are called then the `called` attribute is set to True.

This example tests that calling `method` results in a call to `something`:

    >>> from mock import Mock
    >>> class ProductionClass(object):
    ...     def method(self):
    ...         self.something()
    ...     def something(self):
    ...         pass
    ...
    >>> real = ProductionClass()
    >>> real.something = Mock()
    >>> real.method()
    >>> real.something.called
    True

If you want access to the actual arguments the mock was called with, for example to make assertions about the arguments themselves, then this information is available.

    >>> real = ProductionClass()
    >>> real.something = Mock()
    >>> real.method()
    >>> real.something.call_count
    1
    >>> args, kwargs = (), {}
    >>> assert real.something.call_args == (args, kwargs)
    >>> assert real.something.call_args_list == [(args, kwargs)]

Checking `call_args_list` tests how many times the mock was called, and the arguments for each call, in a single assertion.

From 0.7.0 you can omit empty args and keyword args, which makes comparisons less verbose:

    >>> real = ProductionClass()
    >>> real.something = Mock()
    >>> real.method()
    >>> assert real.something.call_args == ()
    >>> assert real.something.call_args_list == [()]

If the mock has only been called once then you can use `Mock.assert_called_once_with()`:

    >>> real = ProductionClass()
    >>> real.something = Mock()
    >>> real.method()
    >>> real.something.assert_called_once_with()

If you don’t care how many times an object has been called, but are just interested in the most recent call, then you can use `Mock.assert_called_with()`:

    >>> mock = Mock(return_value=None)
    >>> mock(1, 2, 3)
    >>> mock.assert_called_with(1, 2, 3)

### Mock for Method Calls on an Object

    >>> class ProductionClass(object):
    ...     def closer(self, something):
    ...         something.close()
    ...
    >>> 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 `Mock.assert_called_with()` will raise a failure exception.

As `close` is a mock object is has all the attributes from the previous example.

### 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 = Mock(name='foo')
    >>> mock
    <Mock name='foo' id='...'>
    >>> mock.method
    <Mock name='foo.method' id='...'>

### Limiting Available Methods

The disadvantage of the approach above is that all method access creates a new mock. This means that you can’t tell if any methods were called that shouldn’t have been. There are two ways round this. The first is by restricting the methods available on your mock.

    >>> mock = Mock(spec=['close'])
    >>> real.closer(mock)
    >>> mock.close.assert_called_with()
    >>> mock.foo
    Traceback (most recent call last):
      ...
    AttributeError: Mock object has no attribute 'foo'

If `closer` calls any methods on `mock` other than close, then an `AttributeError` will be raised.

When you use spec it is still possible to set arbitrary attributes on the mock object. For a stronger form that only allows you to set attributes that are in the spec you can use spec_set instead:

    >>> mock = Mock(spec=['close'])
    >>> mock.foo = 3
    >>> mock.foo
    3
    >>> mock = Mock(spec_set=['close'])
    >>> mock.foo = 3
    Traceback (most recent call last):
      ...
    AttributeError: Mock object has no attribute 'foo'

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

### Tracking all Method Calls

An alternative way to verify that only the expected methods have been accessed is to use the `method_calls` attribute of the mock. This records all calls to child attributes of the mock - and also to their children.

This is useful if you have a mock where you expect an attribute method to be called. You could access the attribute directly, but `method_calls` provides a convenient way of looking at all method calls:

    >>> mock = Mock()
    >>> mock.method()
    <mock.Mock object at 0x...>
    >>> mock.Property.method(10, x=53)
    <mock.Mock object at 0x...>
    >>> mock.method_calls
    [('method', (), {}), ('Property.method', (10,), {'x': 53})]

If you make an assertion about `method_calls` and any unexpected methods have been called, then the assertion will fail.

Again, from 0.7.0, empty arguments and keyword arguments can be omitted for less verbose comparisons:

    >>> mock = Mock()
    >>> mock.method1()
    <mock.Mock object at 0x...>
    >>> mock.method2()
    <mock.Mock object at 0x...>
    >>> assert mock.method_calls == [('method1',), ('method2',)]

### 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")`:

    >>> mock = Mock()
    >>> cursor = mock.connection.cursor.return_value
    >>> cursor.execute.return_value = None
    >>> mock.connection.cursor().execute("SELECT 1")
    >>> mock.method_calls
    [('connection.cursor', (), {})]
    >>> cursor.method_calls
    [('execute', ('SELECT 1',), {})]

### 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'

Again, 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.

### Raising exceptions with mocks

A useful attribute is side_effect. If you set this to an exception class or instance then the exception will be raised when the mock is called. If you set it to a callable then it will be called whenever the mock is called. This allows you to do things like return members of a sequence from repeated calls:

    >>> mock = Mock()
    >>> mock.side_effect = Exception('Boom!')
    >>> mock()
    Traceback (most recent call last):
      ...
    Exception: Boom!

    >>> results = [1, 2, 3]
    >>> def side_effect(*args, **kwargs):
    ...     return results.pop()
    ...
    >>> mock.side_effect = side_effect
    >>> mock(), mock(), mock()
    (3, 2, 1)

## Sentinel

`sentinel` is a useful object for providing unique objects in your tests:

    >>> from mock import sentinel
    >>> real = SomeClass()
    >>> real.method = Mock()
    >>> real.method.return_value = sentinel.return_value
    >>> real.method()
    <SentinelObject "return_value">

## 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 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 = Mock()
    >>> mock.return_value = sentinel.file_handle
    >>> @patch('__builtin__.open', mock)
    ... def test():
    ...     return open('filename', 'r')
    ...
    >>> handle = test()
    >>> 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()

If you don’t want to call the decorated test function yourself, you can add apply as a decorator on top, this calls it immediately.

A nice pattern is to actually decorate test methods themselves:

    >>> class MyTest(unittest.TestCase):
    ...     @patch.object(SomeClass, 'attribute', sentinel.attribute)
    ...     def test_something(self):
    ...         self.assertEqual(SomeClass.attribute, sentinel.attribute)
    ...
    >>> original = SomeClass.attribute
    >>> MyTest('test_something').test_something()
    >>> assert SomeClass.attribute == original

If you want to patch with a Mock, you can use 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(unittest.TestCase):
    ...     @patch.object(SomeClass, 'static_method')
    ...     def test_something(self, mock_method):
    ...         SomeClass.static_method()
    ...         mock_method.assert_called_with()
    ...
    >>> MyTest('test_something').test_something()

You can stack up multiple patch decorators using this pattern:

    >>> class MyTest(unittest.TestCase):
    ...     @patch('package.module.ClassName1')
    ...     @patch('package.module.ClassName2')
    ...     def test_something(self, MockClass2, MockClass1):
    ...         self.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 `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”.