Python多线程实战:如何通过多线程让Python爬虫速度提升10倍?

2026-05-21 20:473阅读0评论SEO教程
  • 内容介绍
  • 文章标签
  • 相关推荐

本文共计285个文字,预计阅读时间需要2分钟。

Python多线程实战:如何通过多线程让Python爬虫速度提升10倍?

Python 创建多线程的方法及单线程、多线程爬取博客园速度对比tmp/blog_spider.pyimport requestsurls=[https://www.c.com/]

python创建多线程的方法

单线程、多线程爬取博客园速度对比

tmp/blog_spider.py

import requests

urls = [
f"www.c.com/#p{page}"
for page in range(1, 50+1)
]

def craw(url):
r = requests.get(url)
print(url, len(r.text))


craw(urls[0])

01.multi_thread_craw.py

Python多线程实战:如何通过多线程让Python爬虫速度提升10倍?

import blog_spider
import threading, time


def single_thread():
print("single_thread begin")
for url in blog_spider.urls:
blog_spider.craw(url)
print("single_thread end")


def multi_thread():
print("single_thread begin")
threads = []
for url in blog_spider.urls:
threads.append(
threading.Thread(target=blog_spider.craw, args=(url, ))
)


for thread in threads:
thread.start()

for thread in threads:
thread.join()

print("single_thread end")



if __name__ == '__main__':
start = time.time()
single_thread()
end = time.time()
print("single_thread cost: ", end - start, "seconds")

start = time.time()
multi_thread()
end = time.time()
print("multi_thread cost: ", end - start, "seconds")

爬取速度对比
可以看到,速度足足提高了8倍,当然和电脑的性能也有关系
单线程

多线程


本文共计285个文字,预计阅读时间需要2分钟。

Python多线程实战:如何通过多线程让Python爬虫速度提升10倍?

Python 创建多线程的方法及单线程、多线程爬取博客园速度对比tmp/blog_spider.pyimport requestsurls=[https://www.c.com/]

python创建多线程的方法

单线程、多线程爬取博客园速度对比

tmp/blog_spider.py

import requests

urls = [
f"www.c.com/#p{page}"
for page in range(1, 50+1)
]

def craw(url):
r = requests.get(url)
print(url, len(r.text))


craw(urls[0])

01.multi_thread_craw.py

Python多线程实战:如何通过多线程让Python爬虫速度提升10倍?

import blog_spider
import threading, time


def single_thread():
print("single_thread begin")
for url in blog_spider.urls:
blog_spider.craw(url)
print("single_thread end")


def multi_thread():
print("single_thread begin")
threads = []
for url in blog_spider.urls:
threads.append(
threading.Thread(target=blog_spider.craw, args=(url, ))
)


for thread in threads:
thread.start()

for thread in threads:
thread.join()

print("single_thread end")



if __name__ == '__main__':
start = time.time()
single_thread()
end = time.time()
print("single_thread cost: ", end - start, "seconds")

start = time.time()
multi_thread()
end = time.time()
print("multi_thread cost: ", end - start, "seconds")

爬取速度对比
可以看到,速度足足提高了8倍,当然和电脑的性能也有关系
单线程

多线程