Python Tutorial: Write a simple unit test using pytest

Want to learn more? Take the full course at https://learn.datacamp.com/courses/unit-testing-for-data-science-in-python at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work. --- In the last exercise, you went through a function's life cycle. At every step, you tested it by calling row_to_list() on different arguments and checked if the return values are correct. This was repetitive, tedious and time consuming. In this lesson, we will learn to write unit tests and improve this process. There are many Python libraries for writing unit tests such as pytest, unittest, nosetests, and doctest. We will use pytest for this course, because pytest has all essential features, is easiest to use, and is the most popular testing library in Python. To start unit testing with pytest, we will first create a file called test_row_to_list.py. When pytest sees a filename starting with "test_", it understands that this is not an usual Python file, but a special one containing unit tests. We must make sure to follow this naming convention. Files holding unit tests are also called test modules, and we just created our first test module. In the test module, we first import pytest. Then we import the function under test. A unit test is written as a Python function, whose name starts with a "test_", just like the test module. This way, pytest can tell that it is a unit test and not an ordinary function. The unit test usually corresponds to exactly one entry in the argument and return value table for row_to_list(). The unit test checks whether row_to_list() has the expected return value when called on this particular argument. This particular argument is a clean row, so we call the unit test test_for_clean_row(). The actual check is done via an assert statement, and every test must contain one. The assert statement has a required first argument, which can be any boolean expression. If the expression is True, the assert statem