Вивчайте Running Concurrently with asyncio.gather()

Свайпніть щоб показати меню

asyncio.create_task() gives you fine-grained control over individual tasks. When you just want to run a group of coroutines concurrently and collect their results, asyncio.gather() is the cleaner tool.

Basic Usage

asyncio.gather() takes any number of coroutines or tasks, runs them concurrently, and returns a list of their results in the same order as the inputs – regardless of which one finished first.


              12345678910111213141516171819202122232425
            
import asyncio
import httpx
import nest_asyncio

nest_asyncio.apply()

# Fetching multiple posts concurrently
async def fetch_post(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:
        titles = await asyncio.gather(
            fetch_post(client, 1),
            fetch_post(client, 2),
            fetch_post(client, 3),
        )

    for index, title in enumerate(titles, start=1):
        print(f"Post {index}: {title}")

asyncio.run(main())

The results list preserves input order – titles[0] is always the result of fetch_post(client, 1), even if post 3 finished first.

Unpacking a List of Coroutines

When the number of tasks is dynamic, use the * unpacking operator:


              1234567891011121314151617181920212223
            
import asyncio
import httpx
import nest_asyncio

nest_asyncio.apply()

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

async def main():
    post_ids = [1, 2, 3, 4, 5]

    async with httpx.AsyncClient() as client:
        coroutines = [fetch_post(client, post_id) for post_id in post_ids]
        titles = await asyncio.gather(*coroutines)

    for title in titles:
        print(title)

asyncio.run(main())

Handling Exceptions with `return_exceptions`

By default, if one coroutine raises an exception, gather() immediately cancels the rest and re-raises it. Setting return_exceptions=True changes this behavior – exceptions are returned as results instead of being raised.


              12345678910111213141516171819202122232425262728293031
            
import asyncio
import httpx
import nest_asyncio

nest_asyncio.apply()

# Fetching posts – one with an invalid ID to trigger an error
async def fetch_post(client, post_id):
    url = f"https://jsonplaceholder.typicode.com/posts/{post_id}"
    response = await client.get(url)
    data = response.json()
    if not data:
        raise ValueError(f"No data for post {post_id}")
    return data["title"]

async def main():
    async with httpx.AsyncClient() as client:
        results = await asyncio.gather(
            fetch_post(client, 1),
            fetch_post(client, 99999),  # Returns empty – raises ValueError
            fetch_post(client, 3),
            return_exceptions=True,
        )

    for index, result in enumerate(results, start=1):
        if isinstance(result, Exception):
            print(f"Post {index} failed: {result}")
        else:
            print(f"Post {index}: {result}")

asyncio.run(main())

`gather()` vs `create_task()`

Все було зрозуміло?

Дякуємо за ваш відгук!

Секція 2. Розділ 2

Запитати АІ

Запитайте про що завгодно або спробуйте одне із запропонованих запитань, щоб почати наш чат

Секція 2. Розділ 2

Running Concurrently with asyncio.gather()

Basic Usage

Unpacking a List of Coroutines

Handling Exceptions with return_exceptions

gather() vs create_task()

Handling Exceptions with `return_exceptions`

`gather()` vs `create_task()`