Testing

If you want to skip a test when a condition is not met, use pytest skipif. For example, in the code above, I use skipif to skip a test if the python version is less than 3.9.

My previous tips on testing in Python.
Favorite

Have you ever wanted to use the result of one test for another test? That is when pytest_steps comes in handy. 

In the code above, I use the result of sum_test as the input of average_2_nums. The argument steps_data allows me to share the data between 2 tests. 

Link to pytest_steps.

My previous tips on testing.
Favorite

When using pytest parametrize, it can be difficult to understand the role of each test case. You can add the ids parameter to pytest parametrize to assign names to test cases.

In the code above, the first test case is shown as neg-neg instead of [-1–2]. This makes it easier for others to understand the roles of your test cases.

My previous tips on testing in Python.
Favorite

If you want to test the combinations of two sets of parameters, writing all possible combinations can be time-consuming and is difficult to read. 

You can save your time by using pytest.mark.parametrize twice instead. From the output of pytest, we can see that all possible combinations of the given functions and inputs are tested.

My previous tips on testing.
Favorite

Sometimes, it is important to know if your test set contains the same categories in the train set. If you want to check the category mismatch between the train and test set, use Deepchecks’s CategoryMismatchTrainTest.

In the example above, the result shows that there are 2 new categories in the test set. They are ‘d’ and ‘e’.

Link to Deepchecks.

My previous tips on testing.
Favorite

If you want to test some properties or assumptions, it can be cumbersome to write a wide range of scenarios.

To automatically run your tests against a wide range of scenarios and find edge cases in your code that you would otherwise have missed, use hypothesis.

In the code above, I test if the addition of two floats is commutative. The test fails when either x or y is NaN. Now I can rewrite my code to make it more robust against these edge cases.

Learn more about hypothesis here.

Link to my previous tips about testing.
Favorite