There are many ways to implement concurrency thousands of requests in python. The following are some commonly used methods:
threading
module to create and manage multiple threads to send requests concurrently. Each thread can be responsible for sending a request. You can use Thread Pool to manage and control the number of threads. import threading import requests def send_request(url): response = requests.get(url) print(response.text) urls = [...]# 存储要发送请求的URL列表 threads = [] for url in urls: thread = threading.Thread(target=send_request, args=(url,)) thread.start() threads.append(thread) for thread in threads: thread.join()
async<strong class="keylink">io</strong>
module and the <strong class="keylink">ai</strong>o<strong class="keylink">Http</strong>
library to achieve concurrency ask. A coroutine is a lightweight thread that can achieve concurrency in a single thread. By using the async
and await
keywords, you can create asynchronous functions to execute requests concurrently. import asyncio import aiohttp async def send_request(url): async with aiohttp.ClientSession() as session: async with session.get(url) as response: data = await response.text() print(data) urls = [...]# 存储要发送请求的URL列表 loop = asyncio.get_event_loop() tasks = [send_request(url) for url in urls] loop.run_until_complete(asyncio.wait(tasks)) loop.close()
grequests
or gevent
, to implement concurrent requests. These libraries can execute multiple requests concurrently in a single thread. Example using grequests
library:
import grequests urls = [...]# 存储要发送请求的URL列表 requests = [grequests.get(url) for url in urls] responses = grequests.map(requests) for response in responses: print(response.text)
Example using gevent
library:
import gevent import requests def send_request(url): response = requests.get(url) print(response.text) urls = [...]# 存储要发送请求的URL列表 greenlets = [gevent.spawn(send_request, url) for url in urls] gevent.joinall(greenlets)
No matter which method you choose, be careful to control the number of concurrent requests to avoid excessive resource consumption or server overloading.
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