python静态网页爬虫实例01

前些日子学习了一些爬虫知识,鉴于时间较短,就只看了静态网页爬虫内容,而有关scrapy爬虫框架将在后续继续探索。

以下以重庆市统计局官网某页面爬取为例(http://tjj.cq.gov.cn/tjsj/sjjd/201608/t20160829_434744.htm):

 

0、程序代码

 1 import requests
 2 from bs4 import BeautifulSoup
 3 
 4 headers = {'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/65.0.3325.146 Safari/537.36'}
 5 url = 'http://tjj.cq.gov.cn/tjsj/sjjd/201608/t20160829_434744.htm'
 6 res = requests.get(url, headers=headers)
 7 res.encoding = res.apparent_encoding
 8 soup = BeautifulSoup(res.text, 'html.parser')
 9 trs = soup.find_all('table')[2].find_all('tr')
10 # print(trs)
11 data = []
12 for tr in trs:
13     info = []
14     tds = tr.find_all('td')
15     if(len(tds) ==5 ):
16         for td in tds:
17             info.append(td.text.replace('\u3000', ''))
18         print(info)
19     else:
20         continue
21     data.append(info)
View Code

1、准备工作

1.1  打开所给的url,我们发现该网页包含三个表,选取第三个表作为提取对象。

python静态网页爬虫实例01_第1张图片

 

1.2  观察网页源代码,发现该表包含在……
里面,表中每一行包含在……里,而该行的每一列又被包含在
…… 里。

 

2、获取网址请求

2.1  首先导入requests库和美丽的汤——BeautifulSoup库

1 import requests
2 from bs4 import BeautifulSoup

2.2  利用requests库中的requests.get()方法以及相关属性完成网址请求

1 headers = {'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/65.0.3325.146 Safari/537.36'}
2 url = 'http://tjj.cq.gov.cn/tjsj/sjjd/201608/t20160829_434744.htm'
3 res = requests.get(url, headers=headers)
4 res.encoding = res.apparent_encoding

3、网页解析

之前准备工作中,已经对网页源代码有了一定的分析。接下来,直接利用BeautifulSoup库完成网页解析。

 1 soup = BeautifulSoup(res.text, 'html.parser')
 2 trs = soup.find_all('table')[2].find_all('tr')
 3 # print(trs)
 4 data = []
 5 for tr in trs:
 6     info = []
 7     tds = tr.find_all('td')
 8     if(len(tds) ==5 ):
 9         for td in tds:
10             info.append(td.text.replace('\u3000', ''))
11         print(info)
12     else:
13         continue

 

4、代码优化

利用pandas库可以将提取数据并形成Excel表格输出,优化后的代码如下:

 1 # -*- coding: utf-8 -*-
 2 
 3 import requests
 4 from bs4 import BeautifulSoup
 5 import pandas as pd
 6 
 7 class CQstat(object):
 8     def __init__(self):
 9         self.headers = {
10                 'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/77.0.3865.120 Safari/537.36'
11                 }
12         
13     def get_html(self,url):
14         try:
15             r = requests.get(url,headers=self.headers)
16             r.raise_for_status()
17             r.encoding = r.apparent_encoding
18             return r.text
19         except:
20             return None
21     
22     def get_info(self):
23         url = 'http://tjj.cq.gov.cn/tjsj/sjjd/201608/t20160829_434744.htm'
24         html = self.get_html(url)
25         soup = BeautifulSoup(html,'lxml')
26         trs = soup.find_all('table')[2].find_all('tr')
27         data = []
28         for tr in trs:
29             info = []
30             tds = tr.find_all('td')
31             if len(tds) == 3:
32                 for td in tds:
33                     info.append(td.text.replace('\u3000',''))
34                 info.insert(2,'主营业务收入')
35                 info.append('利润总额')
36             elif len(tds) == 4:
37                 for td in tds:
38                     info.append(td.text.replace('\u3000',''))
39                 info.insert(0,'行业')
40             elif len(tds) == 5:
41                 for td in tds:
42                     info.append(td.text.replace('\u3000',''))
43             else:
44                 continue
45             data.append(info)
46         df = pd.DataFrame(data)
47         df.to_excel('1-7月份规模以上工业企业主要财务指标(分行业).xlsx',index=None,header=None)
48         
49 cq = CQstat()
50 cq.get_info()
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