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A beginner's guide to writing effective `pytest` or `unittest` tests for your Python code, specifically targeting unit testing with a focus on function calls and schedule time validation.
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This video is based on the question https://stackoverflow.com/q/67014124/ asked by the user 'Aishwarya Prabhu' ( https://stackoverflow.com/u/15587746/ ) and on the answer https://stackoverflow.com/a/67391472/ provided by the user 'Amogh Katwe' ( https://stackoverflow.com/u/10609859/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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How to Write Effective pytest or unittest for Your Python Code

Unit testing is an essential practice in software development that helps ensure your code behaves as expected. If you're new to unit testing, you may find it challenging to know where to start, especially when dealing with function calls and specific behaviors. In this guide, we'll explore how to write unit tests using pytest or unittest, focusing on validating a particular function in your Python code.

Understanding the Problem

Let’s consider the example code provided. You have a function called screenshot() that performs several operations, including taking a screenshot and sending it via email. However, you may want to confirm a couple of things through unit testing:

Whether the screenshot() function is actually called.

If the scheduled time to take the screenshot is correct.

Here's the original function for reference:

[[See Video to Reveal this Text or Code Snippet]]

The challenge lies in testing a function that has dependencies and external calls. Let's break down the solution.

Setting Up Your Testing Environment

Before diving into the test code, you need to ensure that your development environment is set up with pytest or unittest. You also might want to use pytest-mock or unittest.mock for mocking dependencies.

Install pytest: If you haven’t already installed pytest, you can easily do so using pip:

[[See Video to Reveal this Text or Code Snippet]]

Organize Your Tests: Create a new file, such as test_schedule.py, in the same directory as your schedule.py file.

Writing Unit Tests

Now, let's delve into writing a proper test for the screenshot() function.

Example Test Code

Here is how you can create a test using pytest with the help of mocking:

[[See Video to Reveal this Text or Code Snippet]]

Breaking Down the Test Code

mocker.patch: This is where the magic happens. It replaces the actual function calls you might not want to execute during testing with mock functions to avoid side effects.

The first mocker.patch mocks the environment setup.

The second mocker.patch mocks the email_it() function.

Calling your function: After setting up the mocks, you simply call the screenshot() function to test whether it behaves as expected in the context of your tests.

Executing Your Tests

To run your test, simply navigate to your project directory and execute:

[[See Video to Reveal this Text or Code Snippet]]

You should see the test results in your terminal, indicating whether your tests passed or failed.

Conclusion

Learning to write unit tests is a valuable skill that enhances your coding practices. With tools like pytest and unittest, you can assure that your functions run as intended. Remember to mock external dependencies to create isolated and reliable tests.

Testing may seem daunting at first, but with practice, it becomes an essential part of your development workflow, promoting more robust and maintainable code.

If you have any questions or need further clarification on unit testing, feel free to drop a comment!