Efficiently Pass Return Values from Coroutines to Callbacks Without Blocking in Python asyncio

Explore how to utilize Python's `asyncio` to pass return values from coroutines to callback functions without blocking the execution of your program. --- This video is based on the question https://stackoverflow.com/q/68350868/ asked by the user 'finefoot' ( https://stackoverflow.com/u/1621041/ ) and on the answer https://stackoverflow.com/a/68351658/ provided by the user 'PIG208' ( https://stackoverflow.com/u/11612399/ ) 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: Pass return value from coroutine to callback function without using await 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. --- Efficiently Pass Return Values from Coroutines to Callbacks Without Blocking in Python asyncio When working with asynchronous programming in Python, specifically using the asyncio library, you may encounter scenarios where you want a coroutine to return a value to a callback function without blocking the execution of the main program. Many developers often resort to using the await keyword, but doing so can halt other tasks until the awaited function completes. This guide will explore a clean and efficient way to achieve this using Python's asyncio module. Understanding the Problem Let's consider a small example. Imagine you have a coroutine function named f(). This function takes some time to execute, perhaps because it involves a delay (such as asyncio.sleep). The target is to use its return value in a callback function without waiting for f() to finish, allowing other tasks to continue running in the meantime. A Simple Example Here's a rough idea of what we want to accomplish if f() takes 4 seconds to complete: While waiting for f() to return its value, your main function can continue executing other tasks. Once f() completes and returns its value, that value should be printed out. A conventional way to handle this might prompt you to use print(await f()), but this approach blocks execution, which is contrary to our intention. Instead, we want to establish a non-blocking mechanism. Implementing a Non-blocking Callback with asyncio To pass the return value from a coroutine to a callback function without using await, we can create a helper function that takes both the coroutine and the callback as arguments. Here’s how to implement this solution step-by-step: Step 1: Define the Coroutine First, let’s define our coroutine f() which simulates a delay before returning a value. [[See Video to Reveal this Text or Code Snippet]] Step 2: Create a Task Scheduler Function Next, we will create a function that takes our coroutine and a callback function as parameters. This is where we will invoke our coroutine and pass its result to the callback. [[See Video to Reveal this Text or Code Snippet]] Step 3: Schedule the Coroutine Without Blocking We can now schedule our coroutine to run in the background without blocking other operations in the main() function. Here’s how to do it: [[See Video to Reveal this Text or Code Snippet]] Explanation of the Code f() Coroutine: This coroutine simulates a task with a delay of 4 seconds and returns a string. call() Function: This takes the coroutine f and the callback function cb. It executes f() and passes the result to cb, which is print in our case. main() Function: We use asyncio.create_task() to run call(f, print). This allows main() to continue executing the loop while f() is running in the background. Expected Output If we run the above code, after approximately 4 seconds, the output would look like this: [[See Video to Reveal this Text or Code Snippet]] Conclusion Using asyncio.create_task() combined with a simple callback mechanism allows you to handle coroutines and their results effectively without blocking the execution of your program. This method leverages the strengths of Python's asynchronous capabilities, providing a seamless user experience while maintaining responsiveness. Now you can implement similar patterns in your applications where efficient task management is desired! With this knowledge, you're one step closer to mastering async programming in Python!