Understanding the “RuntimeWarning: coroutine ‘to_thread’ was never awaited” Error in Python

Resolving the Coroutine Await Warning in Loops

Encountering a “RuntimeWarning: coroutine ‘to_thread’ was never awaited” error during a loop iteration is a common scenario in Python. Let’s delve into why this error occurs and explore effective ways to resolve it.

What You’ll Learn

In this comprehensive guide, you will understand the reasons behind Python throwing a RuntimeWarning related to unawaited coroutines within loops. You will also master techniques to handle such situations with finesse.

Introduction to the Problem and Solution

When dealing with asynchronous code in Python, especially when involving async IO operations or task offloading using asyncio‘s to_thread function, correctly awaiting coroutines is crucial. Neglecting this can trigger warnings like the one mentioned above. This warning serves as an indicator that your program may not be running at its optimal efficiency, potentially leading to unresponsive behavior or missed critical tasks.

To address this issue effectively, we will explore the significance of properly awaiting coroutines inside loops to prevent such warnings from arising. Furthermore, we will unravel the workings of asyncio’s event loop and dive into how async/await syntax plays a pivotal role in managing asynchronous executions seamlessly. Through practical examples and lucid explanations, you will learn to adapt your loop structures for enhanced performance and accuracy.


import asyncio

async def example_task():
    # Simulate some task
    await asyncio.sleep(1)
    print("Task completed")

async def main():
    for _ in range(2):
        await asyncio.to_thread(example_task)


# Copyright PHD


The provided solution showcases the correct handling of operations that require offloading from an asynchronous context (using asyncio.to_thread) within a loop. Here’s a breakdown:

  • We define an asynchronous function named example_task() that mimics performing work by sleeping for 1 second before displaying “Task completed.”
  • In our primary coroutine main(), we iterate over a simple range twice (simulating the original scenario) and crucially�we await each invocation made through asyncio.to_thread() within the loop.
  • By awaiting each operation initiated via to_thread, we ensure that every task completes before progressing further. This approach eliminates the runtime warning since each coroutine created by calling example_task() is now correctly awaited following recommended async IO practices in Python.
    Why do I need to use “await” with coroutines?

    Using “await” allows your program to wait for an asynchronous operation (coroutine) to finish before proceeding further, ensuring proper execution flow when handling concurrent tasks.

    What is asyncio.to_thread used for?

    asyncio.to_thread facilitates offloading blocking operations from the async thread pool onto a separate thread pool, preventing CPU-bound tasks from obstructing other async operations.

    Can I use regular functions with “await”?

    No, only functions defined with “async def” or those returning a coroutine object can be awaited.

    Is it necessary always use “await” inside loops?

    Yes, if you’re invoking another coroutine within an async function inside loops; every call must be awaited unless explicitly handled differently (e.g., gathering).

    How does awaiting affect performance?

    Properly awaiting tasks enables your program to utilize concurrency effectively, resulting in improved overall performance, especially for I/O-bound applications.

    What happens if I forget to await a coroutine?

    Forgetting �await� leaves the coroutine unexecuted, potentially causing logic errors and triggering runtime warnings about unawaited coroutines.


    By now, you should have gained a solid understanding of the importance of correctly awaiting coroutines�especially when they are invoked inside loops. With hands-on examples on fixing RuntimeWarning due to overlooked awaits and detailed insights into async programming workings in Python revealed throughout this guide, you are now equipped with knowledge essential for implementing best practices ensuring smooth and efficient application execution going forward.

    Leave a Comment