0.从新闻url获取点击次数,并整理成函数
- newsUrl
- newsId(re.search())
- clickUrl(str.format())
- requests.get(clickUrl)
- re.search()/.split()
- str.lstrip(),str.rstrip()
- int
- 整理成函数
- 获取新闻发布时间及类型转换也整理成函数
1.从新闻url获取新闻详情: 字典,anews
2.从列表页的url获取新闻url:列表append(字典) alist
3.生成所页列表页的url并获取全部新闻 :列表extend(列表) allnews
*每个同学爬学号尾数开始的10个列表页
4.设置合理的爬取间隔
import time
import random
time.sleep(random.random()*3)
5.用pandas做简单的数据处理并保存
保存到csv或excel文件
newsdf.to_csv(r'F:duym爬虫gzccnews.csv')
6.代码示例
import re from bs4 import BeautifulSoup from datetime import datetime import requests import pandas as pd import time import random """新闻点击次数""" def newsClick(newsUrl): newsId = re.findall('(d+)', newsUrl)[-1] clickUrl = 'http://oa.gzcc.cn/api.php?op=count&id={}&modelid=80'.format(newsId) resClicks = requests.get(clickUrl).text resClick = int(re.search("hits'[)].html[(]'(d*)'[)]", resClicks).groups(0)[0]) return resClick """新闻发布时间""" def newsDateTime(showinfo): newsDate = showinfo.split()[0].split(':')[1] newsTime = showinfo.split()[1] newsDateTime = newsDate + ' ' + newsTime dateTime = datetime.strptime(newsDateTime, '%Y-%m-%d %H:%M:%S') #类型转换 return dateTime """新闻字典""" def newsDicts(newsUrl): newsText = requests.get(newsUrl) newsText.encoding = 'utf-8' newsSoup = BeautifulSoup(newsText.text, 'html.parser') newsDict = {} newsDict['newsTitle'] = newsSoup.select('.show-title')[0].text showinfo = newsSoup.select('.show-info')[0].text newsDict['newsDateTime'] = newsDateTime(showinfo) newsDict['newsClick'] = newsClick(newsUrl) return newsDict """新闻列表""" def newsList(newsUrl): newsText = requests.get(newsUrl) newsText.encoding = 'utf-8' newsSoup = BeautifulSoup(newsText.text, 'html.parser') newsList = [] for news in newsSoup.select('li'): if len(news.select('.news-list-title')) > 0: url = news.select('a')[0]['href'] newsDesc = news.select('.news-list-description')[0].text newsDict = newsDicts(url) newsDict['newsUrl'] = url newsDict['description'] = newsDesc newsList.append(newsDict) return newsList """27-37页新闻列表""" def allNews(): allnews = [] for i in range(24,35): newsUrl = 'http://news.gzcc.cn/html/xiaoyuanxinwen/{}.html'.format(i) allnews.extend(newsList(newsUrl)) time.sleep(random.random() * 3) #爬取间隔 return allnews newsDF = pd.DataFrame(allNews()) newsDF.to_csv('gzccnews.csv') #保存为csv文件