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unit testing in python

Unit Testing in Python: A Beginner’s Guide to Using unittest

by Martha Simmonds

Unit testing is pivotal in software development and testing, as it verifies the proper functioning of individual code components or “units.” It is an essential practice that facilitates the development of reliable and high-quality software.

Python’s built-in unittest module offers a comprehensive framework to create and execute unit tests, making it an invaluable tool for Python developers.

In this beginner’s guide, we aim to provide you with a thorough understanding of the fundamentals of unit testing in Python using the unittest module. We will walk you through the process of writing and running your Automation tests, equipping you with the knowledge necessary to enhance code quality, detect bugs at an early stage, and ensure that your software performs as expected.

Upon completing this guide, you will have established a strong foundation in unit testing, allowing you to apply these practices to your Python projects confidently. By incorporating unit testing into your software development process, you will be better positioned to create robust, maintainable, and well-functioning applications that meet the needs of your users.

What is Unit Testing?

Unit testing is the process of testing individual components of your code to ensure they work correctly. A “unit” typically refers to the smallest testable part of an application, such as a function or method. Unit tests verify that each unit behaves as expected, given a specific set of inputs, and produces the expected output.

Why is Unit Testing Important?

Unit testing offers numerous benefits to developers and their projects:

  • Code quality: Unit tests help maintain high code quality by ensuring that individual components work as intended.
  • Early bug detection: Unit tests catch bugs early in the development process, making them easier and less costly to fix.
  • Refactoring support: Unit tests serve as a safety net when refactoring code, allowing you to make changes with confidence that existing functionality will not be broken.
  • Simplified debugging: When a unit test fails, it’s easier to identify and fix the issue since the test is focused on a specific component.
  • Documentation: Unit tests can serve as documentation for your code, demonstrating how each unit is intended to work.

Overview of unittest

Unittest, also known as PyUnit, is Python’s built-in module for creating and running unit tests. It is based on the popular xUnit architecture, which is used by testing frameworks in many programming languages. unittest provides a rich set of features for creating test cases, organizing tests, and generating test reports.

Key Components of Unittest

Unittest consists of several key components:

  • TestCase: A TestCase is a subclass of unittest.TestCase contains the test methods to be executed. Each test method should test a specific aspect of your code.
  • Test methods: Test methods are functions within a TestCase that perform the actual testing. They should start with the word ‘test’ to be discovered and executed by unittest.
  • TestRunner: A TestRunner is responsible for discovering and executing tests and reporting the results. unittest includes several built-in test runners, such as the command-line runner and the graphical test runner.
  • Test fixtures: Test fixtures are methods that set up and tear down the testing environment, such as creating temporary files or initializing objects required by the tests.

Writing Your First Unit Test with unittest

Set Up Your Project

Before you start writing unit tests, create a project directory to keep your source code and tests organized. For this example, create a directory called “my_project” with the following structure:

In my_module.py, add the following sample function that we’ll test:

Creating a TestCase

In the tests directory, create a file called test_my_module.py. This file will contain our test case for the add function. Start by importing the necessary modules and creating a subclass of unittest.TestCase:

Writing Test Methods

Now, add test methods to the TestAddFunction class. Each test method should start with the word ‘test’ and focus on a specific aspect of the add function. For example, test the function with positive integers, negative integers, and floats:

In these tests, we use assertEqual and assertAlmostEqual to compare the actual output of the add function with the expected output. assertAlmostEqual is used when comparing floats to account for potential rounding errors.

Running Your Tests

To run your tests, navigate to your project’s root directory in the command line and execute the following command:

unittest will discover and run all tests in the tests directory and display the results:

This output indicates that all three tests have passed.

Using Test Fixtures

In some cases, you may need to set up and tear down a test environment, such as creating temporary files or initializing objects. unittest provides methods for setting up and cleaning up test fixtures:

  • setUp: This method is called before each test method in a TestCase, and is used to set up the test environment.
  • tearDown: This method is called after each test method in a TestCase, and is used to clean up any resources used during testing.
  • setUpClass: This class method is called before any test methods in a TestCase, and is used to set up resources shared by all test methods in the class.
  • tearDownClass: This class method is called after all test methods in a TestCase have been executed and is used to clean up any resources shared by all test methods in the class.

These methods can be overridden in your TestCase to implement the necessary setup and cleanup logic:

Advanced unittest Features

Unittest provides several advanced features that can improve your testing experience:

  • Skipping tests: You can skip tests by using the @unittest.skip decorator. This is useful when a test is temporarily broken or not yet implemented.
  • Conditional test execution: unittest allows you to run tests conditionally using decorators like @unittest.skipIf and @unittest.skipUnless.
  • Parameterized tests: Parameterized tests enable you to run the same test with different input values and expected results. You can achieve this using third-party libraries like parameterized or by creating custom test generators.

Best Practices for Unit Testing

To make your unit tests more effective, follow these best practices:

  • Write clear and concise test cases: Each test case should have a specific purpose and test a single aspect of your code. Keep test cases simple and avoid testing multiple things at once.
  • Write tests for edge cases: Test your code with edge cases and unexpected inputs to ensure it can handle different situations gracefully.
  • Keep tests independent: Test cases should not rely on the results of other tests. This makes it easier to identify the cause of a failed test and simplifies test maintenance.
  • Maintain a clear separation between test code and production code: Keep test code in a separate directory from your production code to maintain a clear distinction between the two.
  • Use descriptive test method names: Test method names should clearly describe the test’s purpose. This makes it easier to understand test results and identify failing tests.


In conclusion, this comprehensive beginner’s guide has provided a solid foundation in unit testing using Python’s unittest framework. We’ve discussed the importance of unit testing and its role in improving code quality, as well as explored the essential components of unittest, such as TestCase, TestRunner, and test fixtures.

Additionally, we’ve guided you through writing, running, and organizing your tests while shedding light on advanced features and best practices that can elevate your unit testing skills.

By incorporating unit testing into your Python projects, you not only ensure that your code is reliable and behaves as intended but also promote maintainability and ease of refactoring. This stays true for your local and cloud-based platforms (e.g., LambdaTest, AWS, or Selenium Grid).

LambdaTest is a cloud-based digital experience testing platform that allows developers and testers to perform real-time and automation testing across 3000+ environments and real mobile devices, making it a top choice among other cloud testing platforms.

LambdaTest also allows you to execute unit test scripts on an online cloud with features such as:

  • Allows unittest testing over more than 3000+ browsers and OS combinations.
  • Supports modern browsers such as Chrome, Mozilla, Safari, etc., for Selenium testing.
  • Allow integration with popular CI/CD tools like Jenkins, etc.

Moreover, writing clear, concise test cases and focusing on edge cases helps you catch bugs early in the development process, ultimately leading to a more robust and higher-quality software product.

Overall, investing time and effort in learning and applying unit testing with Python’s unittest framework will significantly benefit you and your projects in the long run, contributing to more efficient and effective software development.

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