What is the fastest way to send 100,000 HTTP requests in Python?

When handling a large number of HTTP requests, Python offers various methods to achieve efficient and fast request processing. For sending 100,000 HTTP requests, asynchronous programming or multi-threading/multi-processing methods are typically considered to optimize performance. The following are several possible implementation approaches:

1. Using aiohttp for Asynchronous HTTP Requests

Asynchronous programming provides a non-blocking way to send HTTP requests, which can significantly improve the processing speed for large volumes of requests. aiohttp is a Python library that supports asynchronous requests. The following is an example of sending multiple requests using aiohttp:

python
import aiohttp
import asyncio

async def fetch(session, url):
    async with session.get(url) as response:
        return await response.text()

async def fetch_all(urls):
    async with aiohttp.ClientSession() as session:
        tasks = []
        for url in urls:
            task = asyncio.create_task(fetch(session, url))
            tasks.append(task)
        responses = await asyncio.gather(*tasks)
        return responses

urls = ["http://example.com"] * 100000
loop = asyncio.get_event_loop()
results = loop.run_until_complete(fetch_all(urls))

2. Using requests Library with Thread Pool

Although requests is a synchronous library, by combining it with a thread pool, we can send multiple requests in parallel. Python's concurrent.futures module provides implementations of thread pools and process pools, suitable for concurrent execution of multiple tasks. The following is an example of sending requests using a thread pool:

python
import requests
from concurrent.futures import ThreadPoolExecutor

def fetch(url):
    response = requests.get(url)
    return response.text

def fetch_all(urls):
    with ThreadPoolExecutor(max_workers=20) as executor:
        responses = list(executor.map(fetch, urls))
    return responses

urls = ["http://example.com"] * 100000
results = fetch_all(urls)

3. Using grequests Library

grequests is a library that leverages the functionality provided by the gevent library, combined with the interface of the requests library, to achieve efficient concurrent HTTP requests. The following is an example of using grequests:

python
import grequests

def exception_handler(request, exception):
    print("Request failed")

urls = ["http://example.com"] * 100000
reqs = (grequests.get(u) for u in urls)
responses = grequests.map(reqs, exception_handler=exception_handler)

Summary

For sending a large number of HTTP requests, asynchronous methods typically provide the best performance, especially in I/O-intensive tasks. aiohttp is a powerful library that supports asynchronous HTTP requests and can easily scale to tens of thousands of requests. Additionally, combining thread pools or grequests can achieve efficient concurrent requests, but may not be as efficient as pure asynchronous methods. When selecting a specific implementation, it is also important to consider the actual application scenario and environmental constraints.