通过解析时间来对比分析解析三个不同方法的速度性能

import requests
import re
from bs4 import BeautifulSoup
from lxml import etree
import time
headers = {
'User-Agent':'Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; Win64; x64; Trident/5.0)'
}
urls = ['http://www.qiushibaike.com/text/page/{}/'.format(str (i)) for i in range(1,12)]
def re_scraper(url):
res = requests.get(url,headers=headers)
ids = re.findall('<h2>(.*?)</h2>',res.text,re.S)
contents = re.findall('<div class="content">.*?<span>(.*?)</span>',res.text,re.S)
laughs = re.findall('<span class="stats-vote"><i class="number">(\d+)</i>',res.text,re.S)
comments = re.findall('<i class="number">(\d+)</i>评论',res.text,re.S)
for id,content,laugh,comment in zip(ids,contents,laughs,comments):
info = {
'id':id,
"content":content,
'laugh':laugh,
'comment':comment
}
return info
def bs_scraper(url):
res = requests.get(url,headers=headers)
soup = BeautifulSoup(res.text,'lxml')
ids = soup.select('a > h2')
contents = soup.select('div > span')
laughs = soup.select('span.stats-vote > i')
comments = soup.select('i.number')
for id,content,laugh,comment in zip(ids,contents,laughs,comments):
info = {
'id':id.get_text(),
'content':content.get_text(),
'laugh':laugh.get_text(),
'comment':comment.get_text()
}
return info
def Lxml_scraper(url):
res = requests.get(url,headers=headers)
selector = etree.HTML(res.text)
url_infos = selector.xpath('//div[@class="article block untagged mb15"]')
try:
for url_info in url_infos:
id = url_info.xpath('div[1]/a[2]/h2/text()')[0]
content = url_info.xpath('a[1]/div/span/text()')[0]
laugh = url_info.xpath('div[2]/span[1]/i/text()')[0]
comment = url_info.xpath('div[2]/span[2]/a/i/text()')[0]
info = {
'id':id,
'content':content,
'laugh':laugh,
'comment':comment
}
return info
except IndexError:
pass

if __name__ == '__main__':
for name,scraper in [('Regular expressions',re_scraper),('BeautifulSoup',bs_scraper),('Lxml',Lxml_scraper)]:
start = time.time()
for url in urls:
scraper(url)
end = time.time()
print(name,end-start)
问题：对比不明显 可能数据不够多
Regular expressions 7.845419406890869
BeautifulSoup 7.966017246246338
Lxml 7.645357131958008