Скачать или смотреть Handling Dependency Issues in pytest: Skipped Parameterized Tests Explained

Discover why your `pytest` parameterized tests might be getting skipped and learn how to fix them effectively with dependency markers.
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This video is based on the question https://stackoverflow.com/q/65705465/ asked by the user 'Tal' ( https://stackoverflow.com/u/1177650/ ) and on the answer https://stackoverflow.com/a/65706006/ provided by the user 'MrBean Bremen' ( https://stackoverflow.com/u/12480730/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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Understanding pytest Dependency Issues: Why Are Parameterized Tests Being Skipped?

When working with testing frameworks like pytest, it's not uncommon to encounter unexpected behavior, particularly when using parameterized tests along with dependencies. If you've found that your dependent tests are being skipped, even after the independent tests succeed, you're not alone! This guide dives deep into this problem and uncovers a simple solution.

The Setup: A Common Test Case

Let's first take a look at a typical scenario. Imagine you have two tests, test_a and test_b, where test_b is dependent on test_a. You're using pytest-dependency to manage this relationship. Here’s a sample of what your test setup might look like:

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What Happens When You Run This?

When executing the test suite with the command pytest --log-cli-level=INFO, you notice that while test_a passes for all parameters, test_b is skipped for each parameterized value:

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This leads to the question: Why does this happen?

Why Are Dependencies Failing?

The core issue lies in the naming convention used in parameterized tests. When you use pytest with parameterization, the test names include the parameters — for instance, test_a[val1] instead of just test_a.

As a result, when you declare the dependency in test_b with depends=["test_a"], pytest-dependency cannot find a test named test_a, since the actual names are different (like test_a[val1]). This is why you're seeing your dependent tests being skipped, even when the independent ones succeed.

The Solution: Using Named Dependencies

The solution to this problem is quite simple! You can explicitly assign a name to your dependency marker that pytest-dependency can recognize. Modify test_a to provide a name parameter:

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Now, When You Run Your Tests:

Executing the test suite with the changes made should yield results where both test_a and test_b pass as expected if all test_a tests succeed. No more skipped tests!

Takeaway

Using dependencies in pytest can multiply your test coverage and make your testing framework powerful, but it can lead to issues if not handled correctly. By understanding how pytest names your parameterized tests and managing your dependencies effectively, you can create a robust test suite without surprises.

Happy testing, and may your pytest adventures be free of skipped tests!