By Siddharta Govindaraj

Develop fine quality and maintainable Python purposes utilizing the foundations of test-driven development

About This Book

  • Write powerful and simply maintainable code utilizing the foundations of attempt pushed development
  • Get ideas to real-world difficulties confronted via Python developers
  • Go from a unit trying out newbie to a grasp via a sequence of step by step tutorials which are effortless to follow

Who This ebook Is For

This booklet is meant for Python builders who are looking to use the foundations of test-driven improvement (TDD) to create effective and strong functions. with a view to get the easiest out of this publication, you will have improvement adventure with Python.

What you are going to Learn

  • Implement the test-driven improvement method in Python applications
  • Fully leverage Python's strong integrated unittest and doctest modules
  • Effectively upload gains to latest code bases that don't have any tests
  • Safely unravel issues of the code and layout, with no breaking any functionality
  • Utilize Python's strong mock and patch performance to check advanced interactions
  • Integrate unit checking out into the final software program supply process
  • Use doctest to check code with examples
  • Enhance TDD with the nose2 try runner

In Detail

This publication starts off with a glance on the test-driven improvement method, and the way it truly is varied from the conventional method of writing code. the entire recommendations are offered within the context of a true software that's built in a step by step demeanour over the process the publication. whereas exploring the typical forms of pungent code, we are going to return into our instance undertaking and freshen up the smells that we find.

Additionally, we'll use mocking to enforce the components of our instance undertaking that rely on different platforms. in the direction of the top of the booklet, we will have a look at the most typical styles and anti-patterns linked to test-driven improvement, together with integration of attempt effects into the advance process.

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Extra info for Test- Driven Python Development

Sample text

Since all three prices are increasing, the is_increasing_trend method should return True. To make this test pass, we need to first add support for storing price history. In the initializer, let us replace the price attribute with a price_history list. price_history = [] [ 30 ] Chapter 2 After making this change, all the tests will now fail, including the ones that were passing before. Only after we complete a few steps will we be able to have the tests pass again. When tests are passing, we can constantly run the tests to make sure we aren't breaking any functionality with our changes.

It checks that its parameter is None. If the parameter is not None, it raises an AssertionError and fails the test. Otherwise, execution continues to the next line. Since that is the last line of the method, the test completes and is marked as a pass. 6. The last segment checks if the module was executed directly from the command line. main() function. This function will scan the current file for all tests and execute them. The reason we need to wrap this function call inside the conditional is because this part does not get executed if the module is imported into another file.

Remember to put the @classmethod decorator on the setupClass method. exchange. [ 36 ] Chapter 2 Otherwise, the tests are simply a matter of constructing a rule and checking the matches method. A (very) quick primer on decorators Decorators are functions that take a function as an input and return another function as an output. Python has a shorthand syntax by which we can say @decorator above a function or method and it will apply the decorator to that function. For more details, check the python documentation or a tutorial.

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