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Learn how to effectively mock nested properties using PropertyMock in Python's unittest library. This guide simplifies the process for effortless unit testing.
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How to Mock Nested Properties with PropertyMock in Python

When it comes to unit testing in Python, mocking external dependencies is essential for isolating the code under test. One common scenario involves mocking properties of objects, particularly when dealing with nested properties. In this post, we'll discuss how to properly mock a property of a property, focusing on a specific example using the mlflow library.

The Problem

You may often find yourself needing to mock complex object structures. For instance, let's say you want to mock the following expression in your tests:

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You might easily mock a single layer like this:

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However, you encounter an error when trying to extend this to a nested property:

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This is a common hiccup that many developers face when dealing with mocked objects, but the solution is straightforward once you know the correct approach.

The Solution

To effectively mock nested properties, you need to create a mock instance for each layer down the hierarchy and set the appropriate return values. Here's a step-by-step breakdown of how to do this:

Step 1: Create the Base Mock

You start by creating a base mock that represents the get_run method from the mlflow library:

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Step 2: Mock the Data Property

Next, you need to mock the data property of your base mock. Here's where you'll set the return_value to another MagicMock:

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Step 3: Mock the Nested Metrics Property

Now that you have the data property mocked, you can dive deeper and mock the nested metrics property:

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Complete Example

Putting it all together, your complete code would look like this:

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Explanation of the Code

Base Mock: The first line creates a MagicMock that is set to only allow attributes that exist on the original get_run method.

Data Property Mock: We create a PropertyMock for the data property that returns another MagicMock. This mocks the object that would normally come back from the data property.

Metrics Property Mock: Finally, we mock the metrics property on the object returned by data. The side_effect allows us to specify what should be returned upon successive calls.

Conclusion

With this approach, you can effectively mock nested properties in Python's unittest framework using PropertyMock. This method can help you write cleaner, more focused tests without relying on the actual implementation of external dependencies.

By understanding how to set up your mocks in layers, you can handle almost any scenario involving complex properties in your unit tests. Happy testing!