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We want to test our functions in a way that is repeatable and automated. Ideally, we’d run a test program that runs all our unit tests and cleanly lets us know which ones failed and which ones succeeded. Fortunately, there are great tools available in Python that we can use to create effective unit tests!
Unit Test Advantages and Disadvantages
The advantage of unit tests is that they are isolated from the rest of your program, and thus, no dependencies are involved. They don’t require access to databases, APIs, or other external sources of information. However, passing unit tests isn’t always enough to prove that our program is working successfully. To show that all the parts of our program work with each other properly, communicating and transferring data between them correctly, we use integration tests. We’ll focus on unit tests; however, when you start building larger programs, you will want to use integration tests as well.
You can read about integration testing and how integration tests relate to unit tests here. That article contains other very useful links as well.
Unit Testing Tools
pip install -U pytest in your terminal. You can see more information on getting started here.
- Create a test file starting with
- Define unit test functions that start with
test_inside the test file
pytestinto your terminal in the directory of your test file and it will detect these tests for you!
test_ is the default – if you wish to change this, you can learn how to in this
In the test output, periods represent successful unit tests and F’s represent failed unit tests. Since all you see is what test functions failed, it’s wise to have only one
assert statement per test. Otherwise, you wouldn’t know exactly how many tests failed, and which tests failed.
Your tests won’t be stopped by failed
assert statements, but it will stop if you have syntax errors.
- TEST DRIVEN DEVELOPMENT: writing tests before you write the code that’s being tested. Your test would fail at first, and you’ll know you’ve finished implementing a task when this test passes.
- Tests can check for all the different scenarios and edge cases you can think of, before even starting to write your function. This way, when you do start implementing your function, you can run this test to get immediate feedback on whether it works or not in all the ways you can think of, as you tweak your function.
- When refactoring or adding to your code, tests help you rest assured that the rest of your code didn’t break while you were making those changes. Tests also helps ensure that your function behavior is repeatable, regardless of external parameters, such as hardware and time.