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Improve Your Tests With the Python Mock Object Library (Summary)

You’ve learned so much about mocking objects using unittest.mock!

Now, you’re able to:

  • Use Mock to imitate objects in your tests
  • Check usage data to understand how you use your objects
  • Customize your mock objects’ return values and side effects
  • patch() objects throughout your codebase
  • See and avoid problems with using Python mock objects

You have built a foundation of understanding that will help you build better tests. You can use mocks to gain insights into your code that you would not have been able to get otherwise.

Here’s one last disclaimer: Beware of overusing mock objects! It’s easy to take advantage of the power of Python mock objects and mock so much that you actually decrease the value of your tests.

If you’re interested in learning more about unittest.mock, then check out its excellent documentation.

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Comments & Discussion

Chris James on May 17, 2020

I learned about ‘autospec’ I’m going to use that in my code, it will be a big time saver.

mock.side_effect takes as list of return_values and exceptions, you can only do one callable side_effect at a time.

Unix has a utility called ‘cal’ and New Year’s Day 3030 is a Friday!

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