三种数据抓取的方法
- 正则表达式（re库）
- BeautifulSoup（bs4）
- lxml
*利用之前构建的下载网页函数，获取目标网页的html，我们以https://guojiadiqu.bmcx.com/AFG__guojiayudiqu/为例，获取html。
from get_html import download url = 'https://guojiadiqu.bmcx.com/AFG__guojiayudiqu/' page_content = download(url)
*假设我们需要爬取该网页中的国家名称和概况，我们依次使用这三种数据抓取的方法实现数据抓取。
1.正则表达式
from get_html import download
import re
url = 'https://guojiadiqu.bmcx.com/AFG__guojiayudiqu/'
page_content = download(url)
country = re.findall('class="h2dabiaoti">(.*"#FFFFFF" id="wzneirong">(.*"htmlcode">
from get_html import download
from bs4 import BeautifulSoup
url = 'https://guojiadiqu.bmcx.com/AFG__guojiayudiqu/'
html = download(url)
#创建 beautifulsoup 对象
soup = BeautifulSoup(html,"html.parser")
#搜索
country = soup.find(attrs={'class':'h2dabiaoti'}).text
survey_info = soup.find(attrs={'id':'wzneirong'}).text
print(country,survey_info)
3.lxml
from get_html import download
from lxml import etree #解析树
url = 'https://guojiadiqu.bmcx.com/AFG__guojiayudiqu/'
page_content = download(url)
selector = etree.HTML(page_content)#可进行xpath解析
country_select = selector.xpath('//*[@id="main_content"]/h2') #返回列表
for country in country_select:
print(country.text)
survey_select = selector.xpath('//*[@id="wzneirong"]/p')
for survey_content in survey_select:
print(survey_content.text,end='')
运行结果：
最后，引用《用python写网络爬虫》中对三种方法的性能对比，如下图：
仅供参考。
总结