Efficiently Cache Async Requests in Pytest Test Functions

Discover how to efficiently manage and `cache async requests` in Pytest, enhancing your testing strategy while minimizing duplicative API calls.
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Caching Async Requests in Pytest Test Functions

Testing is an integral part of the development process, especially when working with asynchronous requests in Python. However, duplicating requests can lead to inefficiencies, not to mention slow tests that don't accurately reflect the performance of your application. In this post, we will dive into how to implement an effective caching mechanism for async requests in your Pytest test functions.

The Issue at Hand

When running a series of tests, it's not uncommon to send multiple requests to the same endpoint with identical request bodies. This redundancy can lead to unnecessary delays, particularly when each request must wait for a response before the next in line can be processed. With this in mind, the goal is to cache these requests so that we do not send duplicate requests during the testing process.

Consider the original test function, which sends a POST request using the httpx.AsyncClient:

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

In this function, each test that runs could potentially make the same request multiple times, leading to inefficient testing.

The Solution: Manual Caching

Step-by-Step Implementation

Define a Cache Dictionary

The first step is to declare a global cache dictionary that will store the responses based on the request URL.

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

Create a Request Handler Function

Next, we will define a function that sends the request. This function will check if the response for a specific URL is already in the cache. If not, it will make the request and store the response in the cache for future use.

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

Modify the Test Function to Use the Cached Request Handler

Finally, we'll modify the original test function to utilize this new send_request function rather than making the direct POST request each time.

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

Conclusion

Caching async requests in Pytest is a powerful strategy for enhancing the performance of your tests. Instead of relying on existing libraries that may not suit every situation, implementing a manual caching system allows you to efficiently reuse responses for identical requests, thus streamlining your testing process.

By following the outlined approach, you can significantly reduce the time spent waiting for responses, allowing for faster and more efficient test execution.

Feel free to implement and adjust the caching mechanism to better suit your testing needs. Happy testing!