如何使用多处理来循环浏览一个大的 URL 列表?

Str*_*ker 1 python multithreading multiprocessing python-multiprocessing

问题:检查超过 1000 个 url 的列表并获取 url 返回码 (status_code)。

我的脚本有效,但速度很慢。

我认为必须有一种更好的、pythonic(更漂亮)的方式来做到这一点,在那里我可以产生 10 或 20 个线程来检查 url 并收集响应。(IE:

200 -> www.yahoo.com
404 -> www.badurl.com
...
Run Code Online (Sandbox Code Playgroud)

输入文件:Url10.txt

www.example.com
www.yahoo.com
www.testsite.com
Run Code Online (Sandbox Code Playgroud)

....

import requests

with open("url10.txt") as f:
    urls = f.read().splitlines()

print(urls)
for url in urls:
    url =  'http://'+url   #Add http:// to each url (there has to be a better way to do this)
    try:
        resp = requests.get(url, timeout=1)
        print(len(resp.content), '->', resp.status_code, '->', resp.url)
    except Exception as e:
        print("Error", url)
Run Code Online (Sandbox Code Playgroud)

挑战: 通过多处理提高速度。


多处理

但它不工作。我收到以下错误:(注意:我不确定我是否正确实现了这一点)

AttributeError: Can't get attribute 'checkurl' on <module '__main__' (built-in)>
Run Code Online (Sandbox Code Playgroud)

——

import requests
from multiprocessing import Pool

with open("url10.txt") as f:
    urls = f.read().splitlines()
 
def checkurlconnection(url):
    
    for url in urls:
        url =  'http://'+url
        try:
            resp = requests.get(url, timeout=1)
            print(len(resp.content), '->', resp.status_code, '->', resp.url)
        except Exception as e:
            print("Error", url)
        
if __name__ == "__main__":
    p = Pool(processes=4)
    result = p.map(checkurlconnection, urls)
Run Code Online (Sandbox Code Playgroud)

zel*_*usp 6

在这种情况下,您的任务是 I/O 绑定而不是处理器绑定 - 网站回复所需的时间比您的 CPU 通过脚本循环一次(不包括 TCP 请求)花费的时间更长。这意味着您不会从并行执行此任务中获得任何加速(这就是这样multiprocessing做的)。你想要的是多线程。实现这一点的方法是使用很少记录的,也许名字很差的,multiprocessing.dummy

import requests
from multiprocessing.dummy import Pool as ThreadPool 

urls = ['https://www.python.org',
        'https://www.python.org/about/']

def get_status(url):
    r = requests.get(url)
    return r.status_code

if __name__ == "__main__":
    pool = ThreadPool(4)  # Make the Pool of workers
    results = pool.map(get_status, urls) #Open the urls in their own threads
    pool.close() #close the pool and wait for the work to finish 
    pool.join() 
Run Code Online (Sandbox Code Playgroud)

有关Python 中多处理与多线程的示例,请参见此处