The document discusses different approaches to mock testing in Python including using the Mocker, PostMonkey, and Mock libraries. It provides examples of replacing dependencies with mocks using Mocker, configuring return values on mocks, and patching modules under test using Mock. The goal of mock testing is to isolate units from external dependencies like databases and networks for reliable isolated testing.

1. Mock Testing mit Python
PyBonn Meetup – März 2013
Timo Stollenwerk

2. Testing Pyramide

3. Ein Test ist kein Unit Test wenn
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Datenbankverbindung
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Netzwerkverbindung
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Dateisystemzugriff
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Externer Service

4. Mocks in Python
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Mock
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Mocker
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pMock
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pyMock
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mox
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...

5. PostMonkey
>>> from postmonkey import PostMonkey
>>> pm = PostMonkey('your_api_key')
>>> pm.ping()
u"Everything's Chimpy!"

6. Mocker
>>> mocker = Mocker()
>>> postmonkey = mocker.replace("postmonkey")
>>> pm = postmonkey.PostMonkey(ANY)
>>> pm.ping()
>>> mocker.result(u"Everything's Chimpy!")
>>> mocker.replay()

7. Mocker: PostMonkey
>>> from postmonkey import PostMonkey
>>> pm = PostMonkey('your_api_key')
>>> pm.ping()
u"Everything's Chimpy!"
>>> pm
<mocker.Mock object at 0x9d7624c>

8. Mock
>>> @patch('postmonkey.PostMonkey')
>>> def test_mailchimp_ping_method(mock_class):
>>> mock_class().ping = MagicMock(
>>> return_value=u"Everything's Chimpy!")
>>> from postmonkey import PostMonkey
>>> pm = PostMonkey('123')
>>> assert pm.ping() == u"Everything's Chimpy!"
>>> test_mailchimp_ping_method()

9. Mock Testing mit Python
PyBonn Meetup – März 2013
Timo Stollenwerk
github.com/tisto/mock-testing-in-python