利用Python发送 10 万个 http 请求

前言:

假如有一个文件,里面有 10 万个 url,需要对每个 url 发送 http 请求,并打印请求结果的状态码,如何编写代码尽可能快的完成这些任务呢?

Python 并发编程有很多方法,多线程的标准库 threadingconcurrency,协程 asyncio,当然还有 grequests 这种异步库,每一个都可以实现上述需求,下面一一用代码实现一下,本文的代码可以直接运行,给你以后的并发编程作为参考:

1.队列+多线程

定义一个大小为 400 的队列,然后开启 200 个线程,每个线程都是不断的从队列中获取 url 并访问。

主线程读取文件中的 url 放入队列中,然后等待队列中所有的元素都被接收和处理完毕。

代码如下:

from threading import Thread

import sys

from queue import Queue

import requests

concurrent = 200

def doWork():

while True:

url = q.get()

status, url = getStatus(url)

doSomethingWithResult(status, url)

q.task_done()

def getStatus(ourl):

try:

res = requests.get(ourl)

return res.status_code, ourl

except:

return "error", ourl

def doSomethingWithResult(status, url):

print(status, url)

q = Queue(concurrent * 2)

for i in range(concurrent):

t = Thread(target=doWork)

t.daemon = True

t.start()

try:

for url in open("urllist.txt"):

q.put(url.strip())

q.join()

except KeyboardInterrupt:

sys.exit(1)

运行结果如下:

有没有 get 到新技能?

2.线程池

如果使用线程池,推荐使用更高级的 concurrent.futures 库:

import concurrent.futures

import requests

out = []

CONNECTIONS = 100

TIMEOUT = 5

urls = []

with open("urllist.txt") as reader:

for url in reader:

urls.append(url.strip())

def load_url(url, timeout):

ans = requests.get(url, timeout=timeout)

return ans.status_code

with concurrent.futures.ThreadPoolExecutor(max_workers=CONNECTIONS) as executor:

future_to_url = (executor.submit(load_url, url, TIMEOUT) for url in urls)

for future in concurrent.futures.as_completed(future_to_url):

try:

data = future.result()

except Exception as exc:

data = str(type(exc))

finally:

out.append(data)

print(data)

3.协程 + aiohttp

协程也是并发非常常用的工具了,

import asyncio

from aiohttp import ClientSession, ClientConnectorError

async def fetch_html(url: str, session: ClientSession, **kwargs) -> tuple:

try:

resp = await session.request(method="GET", url=url, **kwargs)

except ClientConnectorError:

return (url, 404)

return (url, resp.status)

async def make_requests(urls: set, **kwargs) -> None:

async with ClientSession() as session:

tasks = []

for url in urls:

tasks.append(

fetch_html(url=url, session=session, **kwargs)

)

results = await asyncio.gather(*tasks)

for result in results:

print(f"{result[1]} - {str(result[0])}")

if __name__ == "__main__":

import sys

assert sys.version_info >= (3, 7), "Script requires Python 3.7+."

with open("urllist.txt") as infile:

urls = set(map(str.strip, infile))

asyncio.run(make_requests(urls=urls))

4.grequests[1]

这是个第三方库,目前有 3.8K 个星,就是 Requests + Gevent[2],让异步 http 请求变得更加简单。Gevent 的本质还是协程。

使用前:

pip install grequests

使用起来那是相当的简单:

import grequests

urls = []

with open("urllist.txt") as reader:

for url in reader:

urls.append(url.strip())

rs = (grequests.get(u) for u in urls)

for result in grequests.map(rs):

print(result.status_code, result.url)

注意 :grequests.map(rs) 是并发执行的。

运行结果如下:

也可以加入异常处理:

>>> def exception_handler(request, exception):

...    print("Request failed")

>>> reqs = [

...    grequests.get("http://httpbin.org/delay/1", timeout=0.001),

...    grequests.get("http://fakedomain/"),

...    grequests.get("http://httpbin.org/status/500")]

>>> grequests.map(reqs, exception_handler=exception_handler)

Request failed

Request failed

[None, None, <Response [500]>]

最后的话:

今天分享了并发 http 请求的几种实现方式,有人说异步(协程)性能比多线程好,其实要分场景看的,没有一种方法适用所有的场景,笔者就曾做过一个实验,也是请求 url,当并发数量超过 500 时,协程明显变慢。所以,不能说哪个一定比哪个好,需要划分情况。

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