非结构化数据与结构化数据提取---- 案例:使用bs4的爬虫

案例:使用BeautifuSoup4的爬虫

我们以腾讯社招页面来做演示:http://hr.tencent.com/position.php?&start=10#a

使用BeautifuSoup4解析器,将招聘网页上的职位名称、职位类别、招聘人数、工作地点、发布时间,以及每个职位详情的点击链接存储出来。

# bs4_tencent.py


from bs4 import BeautifulSoup
import urllib2
import urllib import json # 使用了json格式存储 def tencent(): url = 'http://hr.tencent.com/' request = urllib2.Request(url + 'position.php?&start=10#a') response =urllib2.urlopen(request) resHtml = response.read() output =open('tencent.json','w') html = BeautifulSoup(resHtml,'lxml') # 创建CSS选择器 result = html.select('tr[class="even"]') result2 = html.select('tr[class="odd"]') result += result2 items = [] for site in result: item = {} name = site.select('td a')[0].get_text() detailLink = site.select('td a')[0].attrs['href'] catalog = site.select('td')[1].get_text() recruitNumber = site.select('td')[2].get_text() workLocation = site.select('td')[3].get_text() publishTime = site.select('td')[4].get_text() item['name'] = name item['detailLink'] = url + detailLink item['catalog'] = catalog item['recruitNumber'] = recruitNumber item['publishTime'] = publishTime items.append(item) # 禁用ascii编码,按utf-8编码 line = json.dumps(items,ensure_ascii=False) output.write(line.encode('utf-8')) output.close() if __name__ == "__main__": tencent()

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转载自www.cnblogs.com/joshuazc/p/9790796.html