Скачать или смотреть How to Use assert_called in Python Unit Tests with Any Arguments

Learn how to skip argument checks in Python unit tests using `assert_called` with the `mock` module, enabling your tests to be more flexible.
---
This video is based on the question https://stackoverflow.com/q/70749923/ asked by the user 'Prats' ( https://stackoverflow.com/u/17207537/ ) and on the answer https://stackoverflow.com/a/71121149/ provided by the user 'Prats' ( https://stackoverflow.com/u/17207537/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: assert_called with any argument

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Ensuring Function Calls in Unit Testing with Any Arguments

Unit testing is an essential part of software development that ensures your code behaves as expected. In Python, using the unittest.mock module makes it easy to create mock objects for testing purposes. However, there are scenarios where you might want to verify if a function was called, regardless of the arguments it received. This guide will guide you through addressing this common problem in unit testing.

The Problem: Validating Function Calls Regardless of Arguments

Imagine you have a function called wait_until_complete that takes two arguments: a string uid and an integer time. In your unit test, you want to confirm that this function gets called, but you don't care about the specific values of the arguments. Instead, you want your assertion to pass no matter what arguments are provided. The challenge arises when you run your test, and you encounter an error like this:

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

This indicates that the actual arguments used during the function call do not match the expected ones, leading to the failure of your test case.

The Solution: Using call_count for Flexibility

To solve this issue, you can use the call_count attribute of mock objects to check how many times a function has been called, rather than checking the specifics of the arguments. Here’s how you can implement this solution in your unit test:

Step 1: Set Up Your Mock Object

Ensure you have your mock object ready for the function you intend to test. For instance, using unittest.mock:

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

Step 2: Use call_count for Assertion

Instead of using assert_called, which requires checking arguments, you can simply assert the call_count like this:

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

This line of code effectively checks if your function was called exactly once, and it disregards any details about the arguments passed.

Why This Approach Is Beneficial

Flexibility: Your tests become more adaptable by not needing to worry about every detail of the arguments provided to the function.

Simplicity: It simplifies your test logic and helps focus on the behavior rather than the exact input values.

Less Fragile Tests: By not tying your tests to specific parameters, your tests will be less prone to breakage due to changes in the function's signature.

Conclusion

By leveraging the call_count property of Python's mock objects, you can easily validate whether a function was called without the hassle of matching arguments. This method not only enhances the reliability of your unit tests but also promotes cleaner code and better practices in your testing strategy.

Feel free to implement this tactic in your own tests and watch as your development process becomes smoother and more efficient!