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第一个爬虫

import requests
import pandas as pd
from bs4 import BeautifulSoup
import json
import pandas


def comments(newsurl): #获取评论信息
    commentsurl = http://comment5.news.sina.com.cn/page/info?version=1&format=js&channel=gn&newsid=comos-{}&group=&compress=0&ie=utf-8&oe=utf-8&page=1&page_size=20
    x = newsurl.split(/)[-1].lstrip(doc-i).rstrip(.shtml)
    jd = json.loads(requests.get(commentsurl.format(x)).text.strip(var data=http://www.mamicode.com/))
    return jd[result][count][total]

def getNewsDetail(newsurl): #获取新闻内容
    result = {}
    sample = requests.get(newsurl)
    sample.encoding = utf-8
    soup = BeautifulSoup(sample.text,html.parser)
    result[title] = soup.select(.page-header)[0].text
    result[dt] = soup.select(.time-source)[0].contents[0].strip()
    result[article] =      .join([p.text.strip() for p in soup.select(#artibody p)[0:-1]])
    result[resouce] = soup.select(.time-source)[0].contents[1].text
    result[editor] = soup.select(.article-editor)[0].text.lstrip(责任编辑:)
    result[comments] = comments(newsurl)
    return result
    
def getnews(url): #获取主页面新闻连接
    url.encoding=utf-8
    alllist = []
    soup = BeautifulSoup(url.text,html.parser)
    for a in soup.select(.news-item):
        if len(a.select(h2)) > 0:
            newsurl = a.select(a)[0][href]
            alllist.append(getNewsDetail(newsurl))
            df = pandas.DataFrame(alllist)
            df.to_excel(‘news.xlsx‘,sheet_name=‘Random Data‘) #导出数据到excel中
          
            
url = requests.get(http://news.sina.com.cn/china/)
getnews(url)  #新浪国内新闻



    
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将主页面通过get方法拿到--通过BeautifulSoup进行剖析--利用开发者工具找出标题、内文、编辑、评论等信息所在位置--利用BeautifulSoup中的select方法对所需信息进行提取,并且

存入字典resul{}中--通过循环将每则新闻信息append到最后的列表alllist--使用pandas函数、DataFrame方法将列表整理,最终导出为excel表格



 

第一个爬虫