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| .. currentmodule:: asyncio | ||
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| .. _asyncio-threading: | ||
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| asyncio and free-threaded Python | ||
| ================================ | ||
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| asyncio uses an event loop as a scheduler to enable highly efficient | ||
| I/O-bound concurrency by switching between tasks during non-blocking I/O | ||
| operations. It allows off-loading CPU-bound work to a thread or process | ||
| pool, but that is still limited by the :term:`global interpreter lock` | ||
| in CPython. | ||
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| However, in :ref:`free-threaded Python <freethreading-python-howto>`, | ||
| the GIL is disabled and Python can run true multi-threaded code. This | ||
| means that asyncio can now take advantage of multiple CPU cores without | ||
| the limitations imposed by the GIL. | ||
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| Since Python 3.14, asyncio has first-class support for free-threaded | ||
| Python, and the implementation of asyncio is safe to use in a | ||
| multi-threaded environment. | ||
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| Combining asyncio with threads is most useful when you want to scale | ||
| I/O-bound work across multiple CPU cores by running an event loop per | ||
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Member
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Maybe I don't know enough about asyncio: why would I/O-bound work need multiple cores in order to scale?
Contributor
Author
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. One core may handle multiple requests concurrently but not in parallel, with multiple cores you can handle them in parallel.
Member
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. I guess you mean the computation required by the requests once the IO is complete? One core with asyncio can make progress on the IO itself in parallel. Or am I misunderstanding. I don't mean to pick at this too much, but I think this particular point can be a source of confusion, and it would be stellar to concisely explain it here. |
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| thread, or when you need to run blocking or CPU bound code from an | ||
| asyncio application. | ||
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| .. seealso:: | ||
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| `Scaling asyncio on Free-Threaded Python | ||
| <https://labs.quansight.org/blog/scaling-asyncio-on-free-threaded-python>`__, | ||
| a blog post by Kumar Aditya which explains the internal changes | ||
| that make asyncio safe and efficient under free-threaded Python, | ||
| together with benchmarks of the resulting improvements. | ||
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| Thread safety considerations | ||
| ---------------------------- | ||
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| While asyncio is designed to be thread-safe in a free-threaded Python | ||
| environment, there are still some considerations to keep in mind when | ||
| using asyncio with threads: | ||
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| 1. **Event loop**: Each thread should have its own event loop which | ||
| should not be shared across threads. This ensures that the event loop | ||
| can manage its own tasks and callbacks without interference from | ||
| other threads. | ||
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| 2. **Task management**: Tasks and futures created in one thread should | ||
| not be awaited or manipulated from another thread. | ||
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| 3. **Thread-safe APIs**: When interacting with asyncio from multiple | ||
| threads, it's important to use thread-safe APIs provided by asyncio, | ||
| such as :func:`asyncio.run_coroutine_threadsafe` for submitting | ||
| coroutines to an event loop from another thread. If you need to | ||
| call a callback from a different thread, you can use | ||
| :meth:`loop.call_soon_threadsafe` to schedule it safely. | ||
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| 4. **Synchronization**: The synchronization primitives provided by | ||
| asyncio (like :class:`asyncio.Lock` and :class:`asyncio.Event`) | ||
| are not designed to be used across threads. If you need to | ||
| synchronize between threads, you should use the synchronization | ||
| primitives from the :mod:`threading` module instead. | ||
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| Using asyncio with threads | ||
| -------------------------- | ||
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| asyncio supports running one event loop per thread, which allows you to | ||
| take advantage of multiple CPU cores in a free-threaded Python | ||
| environment. Each thread can run its own event loop, and tasks can be | ||
| scheduled on those loops independently. | ||
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| Here's an example of how to use asyncio with threads:: | ||
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| import asyncio | ||
| import threading | ||
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| async def worker(name: str) -> None: | ||
| print(f"Worker {name} starting") | ||
| await asyncio.sleep(1) | ||
| print(f"Worker {name} done") | ||
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| def run_loop(name: str) -> None: | ||
| asyncio.run(worker(name)) | ||
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| threads = [ | ||
| threading.Thread(target=run_loop, args=(f"T{i}",)) | ||
| for i in range(4) | ||
| ] | ||
| for t in threads: | ||
| t.start() | ||
| for t in threads: | ||
| t.join() | ||
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| In this example, each thread creates its own event loop with | ||
| :func:`asyncio.run` and runs a coroutine on it. The threads execute | ||
| concurrently, and in a free-threaded build they can run on separate | ||
| CPU cores in parallel. | ||
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| Producer/consumer across threads | ||
| -------------------------------- | ||
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| When a regular (non-asyncio) thread needs to hand work to an asyncio | ||
| event loop running in another thread, use a thread-safe primitive such | ||
| as :class:`queue.Queue` rather than :class:`asyncio.Queue`, which is | ||
| only safe within a single event loop.:: | ||
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| import asyncio | ||
| import queue | ||
| import threading | ||
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| def producer(q: queue.Queue[int]) -> None: | ||
| for i in range(5): | ||
| print(f"Producing {i}") | ||
| q.put(i) | ||
| q.shutdown() | ||
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| async def consumer(q: queue.Queue[int]) -> None: | ||
| while True: | ||
| try: | ||
| item = q.get_nowait() | ||
| except queue.Empty: | ||
| await asyncio.sleep(0.1) | ||
| continue | ||
| except queue.ShutDown: | ||
| break | ||
| print(f"Consumed {item}") | ||
| await asyncio.sleep(item) | ||
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| q: queue.Queue[int] = queue.Queue() | ||
| consumer_thread = threading.Thread( | ||
| target=lambda: asyncio.run(consumer(q)) | ||
| ) | ||
| consumer_thread.start() | ||
| producer(q) | ||
| consumer_thread.join() | ||
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| The producer runs on the main thread while the consumer runs inside an | ||
| event loop on its own thread, yet they communicate safely through | ||
| ``queue.Queue``. When the queue is empty the consumer sleeps briefly | ||
| and tries again. When the producer is done it calls | ||
| :meth:`~queue.Queue.shutdown`, which causes subsequent | ||
| :meth:`~queue.Queue.get_nowait` calls to raise :exc:`queue.ShutDown` | ||
| so the consumer can exit cleanly. | ||
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