Скачать или смотреть Understanding pytest-async Synchronization Issues: Why Rate Limiter May Not Work as Expected

Learn how to effectively handle synchronization with `pytest-async` when using Rate Limiters in Python's asyncio framework. Understand common pitfalls and how to solve them.
---
This video is based on the question https://stackoverflow.com/q/77206247/ asked by the user 'Dory Zidon' ( https://stackoverflow.com/u/1059549/ ) and on the answer https://stackoverflow.com/a/77216267/ provided by the user 'danzel' ( https://stackoverflow.com/u/4325768/ ) 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: pytest-async synronization objects not working, tests finish, but async loop not waited on. It worked on unittest IsolatedAsyncioTestCase

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.
---
Understanding pytest-async Synchronization Issues

When working with asynchronous testing in Python, particularly using pytest-async, developers often encounter problems where synchronization objects, like rate limiters, do not behave as intended. This can lead to tests that finish far too quickly, failing to respect the defined limits.

The Problem

In your situation, you've outlined that although the code works perfectly with unittest, the async loop does not wait when you switch to pytest-async. This leads to unexpected behavior where requests are executed without the appropriate delay, essentially bypassing the rate limits you intended to enforce.

Analyzing the Code

Let's break down the crucial parts of your code to identify the root cause of the problem.

Rate Limiter Classes

You have defined two rate limater classes:

RateLimiterA: Uses a semaphore to manage concurrency.

RateLimiterB: Uses an asynchronous limiter to control request rates.

Here’s a quick overview of how they are supposed to work:

acquire: Acquires a limit before proceeding with an action.

release: Releases the limit after the action is complete.

The Issue in Usage

In your execute_async function, you instantiate a new rate limiter for each invocation:

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

This means each request operates on a fresh instance of the limiter, which does not remember the previous state. Therefore, the requests execute immediately without waiting, leading to potential test failures.

Working Code Example

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

A Solution: Single Instance Usage

To resolve this issue, you must ensure that you're using a single instance of the rate limiter across all requests. By doing so, the limiter will keep track of the requests being made, and the synchronization will work as expected.

Proposed Change

Define the Rate Limiter at the Class Level: Instead of creating a new limiter in the execute_async method, you can define it as a class-level attribute.

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

Use the Same Instance in Async Calls:

Modify execute_async to use this instance:

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

Testing with Pytest

When testing the RateLimiter, ensure that your tests also refer to the same instance as your application code. This way, your tests will also respect the limits you set during execution.

Example Test Code

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

Conclusion

By refactoring the code to use a single instance of the rate limiter, you can solve the synchronization issue and ensure smooth operation of your tests in pytest-async. Always be careful about how instances are created and utilized in asynchronous scenarios to avoid this common pitfall.

With this approach, you can enjoy the powerful features of asynchronous programming without running into frustrating synchronization problems.