Вивчайте Creating Tasks with asyncio.create_task()

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Awaiting a coroutine directly runs it – but sequentially. To run coroutines concurrently, you need to schedule them as tasks. That's what asyncio.create_task() is for.

Coroutines vs Tasks

When you await a coroutine directly, the current coroutine pauses and waits for it to finish before continuing. No concurrency happens.


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import asyncio
import nest_asyncio

nest_asyncio.apply()

async def fetch(source):
    print(f"Starting {source}")
    await asyncio.sleep(1)  # Simulating I/O delay
    print(f"Done {source}")

async def main():
    # Sequential
    await fetch("source_A")
    await fetch("source_B")

asyncio.run(main())

Wrapping a coroutine in asyncio.create_task() schedules it to run on the event loop immediately – without waiting for the current coroutine to finish.


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import asyncio
import nest_asyncio

nest_asyncio.apply()

async def fetch(source):
    print(f"Starting {source}")
    await asyncio.sleep(1)  # Simulating I/O delay
    print(f"Done {source}")

async def main():
    # Concurrent
    task_a = asyncio.create_task(fetch("source_A"))
    task_b = asyncio.create_task(fetch("source_B"))

    await task_a
    await task_b

asyncio.run(main())

Both tasks start almost simultaneously. Awaiting them at the end just waits for their completion.

Retrieving Return Values

Tasks capture the return value of the coroutine. You retrieve it by awaiting the task:


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import asyncio
import httpx
import nest_asyncio

nest_asyncio.apply()

# Fetching a single post title
async def fetch_title(client, post_id):
    url = f"https://jsonplaceholder.typicode.com/posts/{post_id}"
    response = await client.get(url)
    data = response.json()
    return data["title"]

async def main():
    async with httpx.AsyncClient() as client:
        task_1 = asyncio.create_task(fetch_title(client, 1))
        task_2 = asyncio.create_task(fetch_title(client, 2))

        title_1 = await task_1
        title_2 = await task_2

        print(f"Post 1: {title_1}")
        print(f"Post 2: {title_2}")

asyncio.run(main())

Task States

A task moves through three states after creation:

Pending: scheduled but not yet complete;
Done: finished successfully;
Cancelled: stopped before completing.

You can check a task's state with task.done() and task.cancelled().


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import asyncio
import nest_asyncio

nest_asyncio.apply()

async def work():
    await asyncio.sleep(1)
    return "result"

async def main():
    task = asyncio.create_task(work())
    print(task.done())  # False – still pending

    result = await task
    print(task.done())  # True – completed
    print(result)       # result

asyncio.run(main())

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