如何确定每秒使用aiohttp的请求数？

Question

我正在尝试使用aiohttp创建一个网站流量模拟器。以下代码示例异步发出10k个请求。我想知道他们中有多少人同时发生，所以我可以说这是10k用户同时请求网站的模型。

如何确定并发网络请求的数量，或者如何确定aiohttp每秒请求多少个请求？有没有办法实时调试/分析并发请求的数量？

有没有更好的方法来使用任何其他编程语言来建模网络流量模拟器？

import asyncio 
import aiohttp 

async def fetch(session, url): 
    with aiohttp.Timeout(10, loop=session.loop): 
     async with session.get(url) as response: 
      return await response.text() 

async def run(r): 
    url = "http://localhost:3000/" 
    tasks = [] 

    # Create client session that will ensure we dont open new connection 
    # per each request. 
    async with aiohttp.ClientSession() as session: 
     for i in range(r): 
      html = await fetch(session, url) 
      print(html) 


# make 10k requests per second ?? (not confident this is true) 
number = 10000 
loop = asyncio.get_event_loop() 
loop.run_until_complete(run(number)) 

Answer 1

嗨首先有原代码中的错误：

async with aiohttp.ClientSession() as session: 
    for i in range(r): 
     # This line (the await part) makes your code wait for a response 
     # This means you done 1 concurent request 
     html = await fetch(session, url) 

如果你解决，你会得到你想要的错误 - 所有的请求都将在同一时间启动。

你要锤击服务 - 除非使用信号量/队列。

无论如何，如果这就是你想要你可以使用这个东西：

import asyncio 
import aiohttp 
import tqdm 


async def fetch(session, url): 
    with aiohttp.Timeout(10, loop=session.loop): 
     async with session.get(url) as response: 
      return await response.text() 


async def run(r): 
    url = "http://localhost:3000/" 
    tasks = [] 
    # The default connection is only 20 - you want to stress... 
    conn = aiohttp.TCPConnector(limit=1000) 
    tasks, responses = [], [] 
    async with aiohttp.ClientSession(connector=conn) as session: 
     tasks = [asyncio.ensure_future(fetch(session, url)) for _ in range(r)] 
     #This will show you some progress bar on the responses 
     for f in tqdm.tqdm(asyncio.as_completed(tasks), total=len(tasks)): 
      responses.append(await f) 
    return responses 

number = 10000 
loop = asyncio.get_event_loop() 
loop.run_until_complete(run(number)) 

感谢asyncio aiohttp progress bar with tqdm为tqdm :)

我还建议您阅读https://pawelmhm.github.io/asyncio/python/aiohttp/2016/04/22/asyncio-aiohttp.html以更好地理解如何协同程序的工作。