数据结构化与保存


2 将新闻数据结构转化为字典列表
import pandas import requests import re from bs4 import BeautifulSoup from datetime import datetime def writeNewsDatail(content): f=open('gzccnews1.txt','a',encoding='utf-8') f.write(content) f.close()#dui # 获取新闻点击次数 def getNewsId(url):#dui newsId = re.findall(r'\_(.*).html', url)[0][-4:] clickUrl = 'http://oa.gzcc.cn/api.php?op=count&id={}&modelid=80'.format(newsId) clickRes = requests.get(clickUrl) # 利用正则表达式获取新闻点击次数 clickCount = int(re.search("hits'\).html\('(.*)'\);", clickRes.text).group(1)) return clickCount def getNewsDetail(newsUrl):#dui # 读取新闻细节 resd = requests.get(newsUrl) resd.encoding = "utf-8" soupd = BeautifulSoup(resd.text, 'html.parser')#打开详情页并解析 news={} news['title']=soupd.select('.show-title')[0].text info = soupd.select(".show-info")[0].text # info相关内容 news['dt']=datetime.strptime(info.lstrip('发布时间:')[0:19],'%Y-%m-%d %H:%M:%S') if info.find('来源:')>0:#作者:审核:来源:摄影:一样处理 news['source']=info[info.find('来源:'):].split()[0].lstrip('来源:') else: news['source']='none' news['content'] = soupd.select(".show-content")[0].text.strip() # 正文 news['count'] = getNewsId(newsUrl) news['newsUrl']=newsUrl return(news) def getListPage(pageUrl):#dui res=requests.get(pageUrl) res.encoding='utf-8' soup=BeautifulSoup(res.text, 'html.parser') newsList=[] for news in soup.select('li'): if len(news.select('.news-list-title')) > 0: newsUrl = news.select('a')[0].attrs['href'] # 链接 newsList.append(getNewsDetail(newsUrl)) #把详情的字典插进列表(一个新闻是字典 多个新闻是列表) return newsList def getPageN(): #新闻列表页的总页数 res=requests.get('http://news.gzcc.cn/html/xiaoyuanxinwen/') res.encoding='utf-8' soup=BeautifulSoup(res.text,'html.parser') n=int(soup.select('.a1')[0].text.rstrip('条')) return(n//10+1) newsTotal=[] n=getPageN() p= [2, n] for i in p: listPageUrl = "http://news.gzcc.cn/html/xiaoyuanxinwen/{}.html".format(i) print(listPageUrl) newsTotal.extend(getListPage(listPageUrl)) for news in newsTotal: print(news)
3·安装pandas,使用pandas.Dataframe(newstotal)创建DataFrame对象df.
4.通过df将提取的数据保存到cvs或excel文件
5.
df.head(6)
df[['click','title','source']]
df[(df['click']>3000) | (df['source']=='学校综合办')]
list=['学生工作处','国际学院']

 print(df[df['sources'].isin(list)])

 

 

posted @ 2018-04-17 19:44  090伍明航  阅读(131)  评论(0编辑  收藏  举报