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Learn to assert multiple calls on a function in Python using `pytest` and how to manage mutable parameters effectively during testing. Improve your API testing with practical strategies!
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How to Effectively Use pytest for Asserting Multiple Calls with Dictionary Parameters

When writing tests for your Python code, especially when dealing with API calls, you might encounter scenarios that require your mock functions to be called multiple times with different parameters. One such situation arises when you're trying to fetch paginated data from an API and are faced with the challenge of asserting that the correct parameters are used across these calls. In this guide, we'll walk through a common problem related to asserting multiple calls on a function with dictionary parameters and how to resolve it using pytest.

The Problem

Let's consider a scenario where you have a function, fetch_all(), designed to accumulate data from a paginated API. Here's a simplified version of the code:

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

While testing this function, you might decide to mock the fetch function to assert if it was called multiple times with different offset values. However, due to the mutable nature of dictionaries in Python, all calls can end up referencing the same dictionary object. As a result, you may observe unexpected behavior in your test outputs:

Expected vs Actual Results

Expected Calls:

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

Actual Calls:

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

In this case, every call to the fetch function ends up using the most recent value of params, leading to confusing test results.

The Solution

To resolve this issue, you can create a stub method that stores a copy of the parameters each time the method is called. This approach allows you to maintain the integrity of the parameters used in each invocation of the fetch function. Below is a modified version of the previous code that successfully resolves the issue:

Modified Test Function

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

Breakdown of the Solution

Store a Copy of Parameters: Inside the my_fetch function, we append a tuple of the URL and a copy of the params dictionary to call_parameters. This ensures that each test reflects the state of params at the time of the corresponding call.

Mock Behavior: We use mocker.patch to replace the fetch method with our custom my_fetch, which simulates the desired behavior of the API call.

Benefits of this Approach

Clear Assertions: By using copies of the parameters, you can clearly assert the expected calls made to the fetch function without interference from changes made to the params dictionary in subsequent iterations.

Reliable Testing: This method keeps your tests consistent and prevents unexpected results caused by mutable data types.

Conclusion

When testing functions that involve mutable parameters such as dictionaries, it's crucial to ensure that each call to a mocked function references its own copy of the arguments. By employing the approach outlined in this article, you can effectively use pytest to assert multiple calls with different parameters in a clear and organized manner. Keep these principles in mind, and you'll be able to write more reliable tests for your Python applications!