Python Guide for Beginners: Unit Test in Python Example

Are you looking for the unit test in Python example? Both unit testing and Python are important tools for our software testing. In this blog, we will introduce both of them and discuss the unit testing framework in Python.

What is a unit test, and what is Python?

A unit refers to the smallest testable set of source code in an application. A group of source code is considered testable when it has clear inputs and outputs. Therefore, generally speaking, every method in the source code that includes explicit inputs and outputs is considered a testable unit. It's important to note that the term "output" here is not limited to the return value of a method or changes to input parameters, but includes any data changes that occur during the method's execution process.


The purpose of unit testing is to isolate all the source codes of an application into the smallest testable units, ensuring the correctness of each unit. Ideally, if each unit can be guaranteed to be correct, it contributes to the overall correctness of the application to a significant extent.

As for Python, we must be more familiar with it. Python is a versatile and easy-to-learn programming language known for its simplicity and readability. It provides a powerful and expressive syntax that allows developers to write code in fewer lines, making it efficient for both beginners and experienced programmers.

Unit test in Python example offers a variety of options and frameworks, each with its own unique features and advantages.


The standard framework module in Python, known as unittest, provides a robust and efficient way to develop and execute tests for your programs.

With unittest, you can easily define test cases by subclassing the unittest.TestCase class and writing individual test methods. This framework allows you to make assertions to verify expected behavior, such as asserting equality, checking for exceptions, and more.


For Python 2.7 and later versions, there is an alternative framework called unittest2. It offers additional features and compatibility with older Python versions, including Python 2.6. To use unittest2, simply replace import unittest with import unittest2 in your test scripts.

Extensions and Alternatives

Apart from unittest and unittest2, there are other frameworks and libraries available for unit testing in Python:

  • Nose2: A powerful alternative to the nose module, nose2 provides a wide range of plugins and features, making it highly customizable and flexible for testing.
  • Testify: Built on top of unittest, Testify is designed to offer a more expressive and user-friendly testing experience. It allows running unittest tests with minimal modifications.
  • PyTest: A comprehensive and widely used testing tool, PyTest offers a rich set of features, making it ideal for both beginners and experienced Python developers.
  • DocTest: A standard library module in Python, DocTest enables testing through interactive sessions and ensures that code examples provided in documentation remain up-to-date and functional.

Other Python Testing Frameworks

  • PluginCompat: Provides test execution and compatibility checks for plugins used with pytest.
  • Test-Junkie: A modern and flexible testing framework designed for Python applications.
  • Slash: A Python-based testing framework that focuses on simplicity and ease of use.
  • Lemoncheesecake: A feature-rich Python framework for functional testing. It offers advanced features like test case hierarchy, metadata, batch processing, and supports multiple report formats like JSON, XML, and HTML.


So, how do you do unit testing in Python? We provide a simple unit test in Python example (with unittest):


import unittest
# Function to test
def add_numbers(a, b):
    return a + b
# Test case
class TestAddNumbers(unittest.TestCase):
    def test_add_numbers(self):
        result = add_numbers(2, 3)
        self.assertEqual(result, 5)  # Check if the result is equal to 5
if __name__ == '__main__':


Here we define a function add_numbers that adds two numbers together. We create a test case class TestAddNumbers that inherits from unittest.TestCase. Inside this class, we define a test method test_add_numbers that calls the add_numbers function with arguments and asserts that the result is equal to the expected value using the self.assertEqual() method. Finally, we run the tests using unittest.main(). If all tests pass, you will see the output "OK"; otherwise, it will display the details of the failed test(s).

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