By Siddharta Govindaraj
Develop fine quality and maintainable Python functions utilizing the foundations of test-driven development
About This Book
- Write strong and simply maintainable code utilizing the rules of attempt pushed development
- Get options to real-world difficulties confronted via Python developers
- Go from a unit trying out newbie to a grasp via a chain of step by step tutorials which are effortless to follow
Who This publication Is For
This publication is meant for Python builders who are looking to use the foundations of test-driven improvement (TDD) to create effective and powerful functions. which will get the simplest out of this publication, you'll have improvement adventure with Python.
What you'll Learn
- Implement the test-driven improvement method in Python applications
- Fully leverage Python's strong integrated unittest and doctest modules
- Effectively upload positive factors to current 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 complicated interactions
- Integrate unit checking out into the general software program supply process
- Use doctest to check code with examples
- Enhance TDD with the nose2 try runner
In Detail
This ebook begins with a glance on the test-driven improvement strategy, and the way it truly is varied from the conventional means of writing code. the entire ideas are awarded within the context of a true program that's constructed in a step by step demeanour over the process the ebook. whereas exploring the typical different types of stinky code, we are going to return into our instance venture and freshen up the smells that we find.
Additionally, we are going to use mocking to enforce the elements of our instance undertaking that rely on different structures. in the direction of the tip of the e-book, we will look at the commonest styles and anti-patterns linked to test-driven improvement, together with integration of try effects into the improvement process.
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Additional resources for Test- Driven Python Development
Sample text
There is no right answer and it is a subjective decision that needs to be taken, weighing up the pros and cons of each specific situation. Refactoring the design In the previous section, we talked about the new requirement of having to check if a stock has an increasing trend. is_increasing_trend()) The test takes three timestamps and prices and performs an update for each one. 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.
38 ] Chapter 2 Try your hand at implementing this requirement. Do not make any changes to the existing interfaces for these methods, but feel free to make any changes to the implementation as you require. Here are some things to think about: • Does our existing design support this new feature? Do we need to make any changes to the current design? • What kind of tests would we write for this requirement? • After we get everything working, is there any clean up we can do to make the code more readable or maintainable?
The only way to test the caching functionality would be to verify if the calculated value is stored in the cache. If we later change the caching method (for example, moving from a file cache to memcache), then we will have to change the test as well. Brittle tests can be worse than no tests, as the maintenance overhead of having to fix ten or twenty tests with every change in the implementation can turn developers away from TDD, increase the amount of frustration, and lead to teams disabling or skipping testing.