爬取全部的校园新闻

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