What Is pytest?

(& why you should be using it)

About Me

My name is Matt Gilbert and I have been in the Software Testing field for close to 10 years now. I have my B.S. in Software Development from Western Governors University. I’ve had the opportunity to take on many different roles in varying industries like Insurance, Startups, SaaS, and Healthcare, as well as contract work. Across these different industries, I also gained experience with several different testing techniques. These include API testing, Integration, Performance, Accessibility, UI, Usability, Mobile, and Contract, as well as Test Automation Framework development in Java, C#, Typescript, and Python. You can find me on LinkedIn. Let’s connect!

What Is Pytest?

Pytest is a popular testing framework for Python. It allows you to write tests using Python code to ensure that it is correct and working as expected. Pytest makes it easy to write and run tests, as well as customize and extend your testing process using the framework.

One of the key features of Pytest is its ability to automatically discover and run tests. This means that you can simply create a file with test functions, and Pytest will find and run those tests for you. For example, you might create a file called test_my_module.py with the following contents:

def test_my_function():

    assert my_function() == 5

Pytest will discover this test function and run it when you run the pytest command. You can also specify which tests to run by using the -k flag, which allows you to specify a pattern that the test name must match. For example, you could run only tests that have "my_function" in their name by using the following command:

pytest -k my_function

Another useful feature of Pytest is its ability to parametrize tests. This means that you can write a single test function and provide it with different arguments to test different scenarios. For example, you might want to test your my_function with different input values to ensure that it works correctly for all inputs. With Pytest, you can do this by using the @pytest.mark.parametrize decorator, like this:

@pytest.mark.parametrize("input, expected", [
    (2, 4),
    (3, 9),
    (4, 16),
])
def test_my_function(input, expected):
    assert my_function(input) == expected

In this example, the test_my_function test will be run three times, once for each pair of input and expected values provided in the parametrize decorator. This allows you to test your code with a variety of inputs, without having to write separate test functions for each scenario.

Pytest also has a rich ecosystem of plugins and extensions that you can use to customize and enhance the testing process. For example, you can use the pytest-cov plugin to measure the code coverage of your tests, or the pytest-xdist plugin to run your tests in parallel across multiple CPUs or machines.

Can You Show Me The Actual Code That Runs A Test?

In Pytest, you can use the built-in assert keyword to make assertions about the expected behavior of your code. For example, you might write a test like this:

def test_my_function():

     result = my_function()

     assert result == 5, f”Expected 5 but got {result}”

In this test, the assert statement checks whether the result of calling my_function is equal to 5. If it is not, the test will fail and Pytest will print the error message provided in the assert statement. This makes it easy to write tests that check the expected behavior of your code and provides helpful error messages when the code does not behave as expected.

How To Use Fixtures

Another useful feature of Pytest is its support for fixtures. Fixtures are pieces of code that are used to set up the environment for a test. For example, you might have a fixture that sets up a database connection or one that creates a temporary directory for the test to use. In Pytest, you can define fixtures using the @pytest.fixture decorator, like this:

@pytest.fixture 

def my_fixture():
     # Set up code goes here

     yield

     # Tear down code goes here

The code in the yield statement is the actual fixture code that will be run when the fixture is used in a test. The code before and after the yield statement is used for setup and tear down, respectively. This allows you to easily and consistently set up the environment for your tests, and clean up after the tests are finished.

In addition to the built-in fixtures provided by Pytest, you can also create your own custom fixtures to use in your tests. This allows you to tailor the fixture to your specific needs, and make it reusable across multiple tests.

Pytest is a feature-rich testing framework that provides many useful tools and features for writing and running tests in Python. Whether you are new to testing or an experienced developer, Pytest is a powerful and flexible tool that can help you ensure the quality of your Python code.

Outro

Thanks for reading! If you have any questions about this article or any of my past articles, feel free to reach out on my LinkedIn. I’d love to hear your thoughts!

Keep on the lookout for my next article!