完整代码

import asyncio
import httpx
from concurrent.futures import ThreadPoolExecutor, Future
import time
import contextvars

# 测试时将测试网址替换
urls = [
    "http://www.bxxxx.com",
    "http://www.aaaa.com",
    "http://www.bbbb.com",
    "http://www.cccc.com",
    "http://www.sdddd.com",
    "http://www.jdddd.com",
    "http://www.zeeee.com",
    "http://www.tffff.com",
    "http://www.cgggg.com",
    "http://www.zhhhhh.com.cn",
    "http://www.google.com",
    "https://www.yiiiii.com/",
]


async def check_one_ip(url):
    headers = {
        "user-ageng": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 \
            (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36 Edg/116.0.1938.69"
    }
    TIMEOUT = 3
    result = ()
    try:
        async with httpx.AsyncClient() as client:
            response = await client.get(url, headers=headers,timeout=TIMEOUT)
            print(f"response from {url} is : {response.status_code}")
            if 200 <= response.status_code < 300:
                print(f"length of response body is {len(response.text)}")
            result = (url, response.status_code)
    except  Exception as e:
        print(f"{url} met timeout error")
        return (url, 999)
    return result 

def task_callback(context):
    # print response.status_code 
    url, code = context.result()
    print(f"It is callback,  got status_code: {code} of {url}")

async def main():
    tasks=[]
    for url in urls:
        task = asyncio.create_task(check_one_ip(url))
        task.add_done_callback(task_callback)
        tasks.append(task)
    await asyncio.gather(*tasks) 
        

if __name__=="__main__":
    t1 = time.time()
    asyncio.run(main())
    t2 = time.time()
    print(f"total time: {t2-t1:.3f}s")    

运行结果如下，可以看到，总耗时： 3.161s，相比同步编程方式，耗时减少了1半。 随着发送请求量的增加，可以看到更加明显的效果。

response from url is : 302
It is callback,  got status_code: 302 of url
response from url is : 302
It is callback,  got status_code: 302 of url
response from url is : 200
length of response body is 23508
It is callback,  got status_code: 200 of url
response from url is : 302
response from url is : 301
It is callback,  got status_code: 302 of url
It is callback,  got status_code: 301 of url
response from url is : 301
response from url is : 301
response from url is : 301
response from url is : 200
length of response body is 396837
It is callback,  got status_code: 301 of url
It is callback,  got status_code: 301 of url
It is callback,  got status_code: 301 of url
It is callback,  got status_code: 200 of url
response from url is : 404
It is callback,  got status_code: 404 of url
response from url is : 200
length of response body is 1151330
It is callback,  got status_code: 200 of url
url met timeout error
It is callback,  got status_code: 999 of url
total time: 3.161s

五、异步编程注意事项

1）协程不应该执行耗时长的任务

异步event loop执行期间，虽然各个协程是在工作，但主线程是被阻塞的。本例中，异步耗时的总时长与访问google.com超时时长相同，那么意味着，如果协程中如果有1个是耗时很长的任务，那么主线程还将被阻塞，异步解决不了这个问题，这时耗时协程应该拿出来，用子线程、或者子进程来执行。

2） 协程应该汇集后并发执行

遇到一些开发者咨询，为什么采用了异步编程，但性能没有明显提升呢？ 创建多个协程任务后，必须按第3步，用gather()方法来汇集创建的协程任务，然后用asyncio.run()方法并发运行。 另外官方文档要求 event loop要在主线程main() 方法中运行。

3）慎用底层编程接口

另外由于官方文档并未清晰说明 event loop、future对象等低层编程接口，除非你很了解异步低层的实现机制，否则不建议使用低层接口，
使用ayncio.run() 来启动evnetloop， 使用 task 对象，而非future 对象。