Does Python asyncio use threads?

Python's asyncio module is a popular way to write concurrent and asynchronous code in Python. But it can be confusing to understand how asyncio relates to threads and concurrency concepts.

At its core, asyncio provides infrastructure to write single-threaded concurrent code. It allows you to execute code out of order without using multiple OS threads. This is done through the use of coroutines and an event loop.

import asyncio

async def my_coro():
    print("Hello from a coroutine!")

asyncio.run(my_coro())

So asyncio code runs in a single thread, but allows concurrency by suspending and resuming coroutines to execute them out of order. This avoids overhead from thread context switching.

However, asyncio can utilize threads in some cases:

Blocking IO operations - Performing synchronous, blocking IO in an asyncio coroutine will block the event loop thread. To avoid this, asyncio runs blocking code in a thread pool to avoid blocking.

CPU-bound tasks - Since asyncio uses a single thread, CPU-bound work can block the event loop. For this, you can use asyncio.to_thread to run CPU intensive work in a thread pool.

So while asyncio itself provides single-threaded concurrency, it integrates with threads to avoid issues around blocking operations.

The key takeaways are:

asyncio allows concurrency in Python without threads via coroutines and an event loop

Coroutines run on a single thread, avoiding overhead from thread switching

Blocking IO and CPU intensive work can be offloaded to thread pools to avoid blocking the event loop

By understanding this relationship, you can leverage asyncio for high performance concurrency while avoiding threading issues like deadlocks and race conditions. The event loop model fits many IO bound workloads like web servers very well.

Does Python asyncio use threads?

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