This post will demonstrate a basic setup of the PyTest library to run unit tests on your Python code.

Let's create the hello-pytest directory and install Pillow.

# Make the `hello-pytest` directory
$ mkdir hello-pytest
$ cd hello-pytest

# Init the virtual environment
$ pipenv --three
$ pipenv install --dev pytest

# Create a folder to place files
$ mkdir src tests
# Create the required files
$ touch src/math.py src/__init__.py tests/test_math.py tests/__init__.py
copy

At this stage, we are ready to add our math functions.

Our example will be very contrived, but we will create an add, subtract and multiply function to demonstrate how to import functions and unit test them.

Inside of src/math.py, add the following code:

def add(x: int, y: int) -> int:
    """add two numbers together

    Args:
                    x (int): first number to add
                    y (int): second number to add

    Returns:
                    int: sum of x and y
    """
    return x + y


def subtract(x: int, y: int) -> int:
    """subtract one number from another

    Args:
                    x (int): first number to subtract
                    y (int): second number to subtract

    Returns:
                    int: resut of x subtract y
    """
    return x - y


def multiply(x: int, y: int) -> int:
    """multiply two numbers together

    Args:
                    x (int): first number in the multiplication
                    y (int): second number in the multiplication

    Returns:
                    int: product of x and y
    """
    return x * y
copy

The above code contains three functiosn that each do as you would expect from a math helper.

With these in mind, let's add code to the test file for our math module.

Inside of tests/test_math.py, add the following code:

from src.math import add, subtract, multiply


def test_add():
    assert add(3, 2) == 5


def test_subtract():
    assert subtract(3, 2) == 1


def test_multiply():
    assert multiply(3, 2) == 6
copy

Each test does as your would expect and asserts on simple math. The assert function will pass if the result is true and fail if not.

We can run our tests now by running pipenv run pytest from the command line.

If done correctly, you should now see the following:

============================================= test session starts =============================================
platform darwin -- Python 3.9.6, pytest-6.2.4, py-1.10.0, pluggy-0.13.1
rootdir: /Users/dennisokeeffe/code/blog-projects/hello-pytest
collected 3 items

tests/test_math.py ...                                                                                  [100%]

============================================== 3 passed in 0.02s ==============================================
copy

To ensure our tests are working as expected and failing when they should, you can update a function to fail and test that it does fail.

If I update my add function in src/math.py to return x + y + 1 instead of x + y, I can test that the function fails and provides information about the failure.

============================================= test session starts =============================================
platform darwin -- Python 3.9.6, pytest-6.2.4, py-1.10.0, pluggy-0.13.1
rootdir: /Users/dennisokeeffe/code/blog-projects/hello-pytest
collected 3 items

tests/test_math.py F..                                                                                  [100%]

================================================== FAILURES ===================================================
__________________________________________________ test_add ___________________________________________________

    def test_add():
>       assert add(3, 2) == 5
E       assert 6 == 5
E        +  where 6 = add(3, 2)

tests/test_math.py:5: AssertionError
=========================================== short test summary info ===========================================
FAILED tests/test_math.py::test_add - assert 6 == 5
========================================= 1 failed, 2 passed in 0.08s =========================================
copy

Changing it back will pass the tests again and we successfully written our first test with PyTest.

Today's post demonstrated how to use PyTest to write unit tests for our math module.

Although contrived, the example was helpful in learning how to write unit tests for our code.

If you would like to read into more examples of testing, Pluralsight have a delightful repo that you can read through and see how they make their tests.

I will be writing on more complex usages of PyTest over the coming weeks.

Photo credit: rstone_design