这篇文章主要讲解了基于线程池提升request模块效率的方法，内容清晰明了，对此有兴趣的小伙伴可以学习一下，相信大家阅读完之后会有帮助。
普通方法：爬取梨视频
import re
import time
import random
import requests
from lxml import etree
start_time = time.time()
url = "https://www.pearvideo.com/category_3"
headers = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/79.0.3945.88 Safari/537.36"
}
ex = 'srcUrl="(.*?)",vdoUrl=srcUrl'
def request_video(url):
"""
向视频链接发送请求
"""
return requests.get(url=url, headers=headers).content
def save_video(content):
"""
将视频的二进制数据保存到本地
"""
video_name = str(random.randint(100, 999)) + ".mp4"
with open(video_name, 'wb') as f:
f.write(content)
# 获取首页源码
page_text = requests.get(url=url, headers=headers).text
tree = etree.HTML(page_text)
li_list = tree.xpath('//ul[@class="listvideo-list clearfix"]/li')
video_url_list = list()
for li in li_list:
detail_url = "https://www.pearvideo.com/" + li.xpath('./div/a/@href')[0]
# 获取该视频页面的源码
detail_page_text = requests.get(url=detail_url, headers=headers).text
# 正则匹配视频的URL
video_url = re.findall(ex, detail_page_text, re.S)[0]
video_url_list.append(video_url)
content = request_video(video_url)
save_video(content)
print("执行耗时: ", time.time() - start_time)执行耗时: 147.22410440444946
使用线程池：爬取梨视频
# 使用线程池爬去梨视频的
import re
import time
import random
import requests
from lxml import etree
from multiprocessing.dummy import Pool
start_time = time.time()
url = "https://www.pearvideo.com/category_3"
headers = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/79.0.3945.88 Safari/537.36"
}
ex = 'srcUrl="(.*?)",vdoUrl=srcUrl'
def request_video(url):
"""
向视频链接发送请求
"""
return requests.get(url=url, headers=headers).content
def save_video(content):
"""
将视频的二进制数据保存到本地
"""
video_name = str(random.randint(100, 999)) + ".mp4"
with open(video_name, 'wb') as f:
f.write(content)
# 获取首页源码
page_text = requests.get(url=url, headers=headers).text
tree = etree.HTML(page_text)
li_list = tree.xpath('//ul[@class="listvideo-list clearfix"]/li')
video_url_list = list()
for li in li_list:
detail_url = "https://www.pearvideo.com/" + li.xpath('./div/a/@href')[0]
# 获取该视频页面的源码
detail_page_text = requests.get(url=detail_url, headers=headers).text
# 正则匹配视频的URL
video_url = re.findall(ex, detail_page_text, re.S)[0]
video_url_list.append(video_url)
pool = Pool(4)
#使用线程池将视频的二进制数据下载下来
content_list = pool.map(request_video, video_url_list)
# 使用线程池将视频的二进制数据保存到本地
pool.map(save_video, content_list)
print("执行耗时: ", time.time() - start_time)看完上述内容，是不是对基于线程池提升request模块效率的方法有进一步的了解，如果还想学习更多内容，欢迎关注亿速云行业资讯频道。
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