Python网络爬虫 | 易学教程

import requests
from bs4 import BeautifulSoup
from datetime import datetime
import re
import json
import pandas
import sqlite3

commenturl = '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'

#获取评论数量
def getCommentCounts(newsurl):
m = re.search('doc-i(.*).shtml', newsurl)
newsid = m.group(1)
comments = requests.get(commenturl.format(newsid))
jd = json.loads(comments.text.strip('var data='))
return jd['result']['count']['total']

#获取新闻详情
def getNewsDetail(newsurl):
result = {}
res = requests.get(newsurl)
res.encoding = 'utf-8'
soup = BeautifulSoup(res.text, 'html.parser')
result['title'] = soup.select('#artibodyTitle')[0].text
result['newssource'] = soup.select('.time-source span a')[0].text
timesource = soup.select('.time-source')[0].contents[0].strip()
result['dt'] = datetime.strptime(timesource,'%Y年%m月%d日%H:%M')
result['article'] = '@'.join([p.text.strip() for p in soup.select('#artibody p')[:-1]])
result['editor'] = soup.select('.article-editor')[0].text.strip('责任编辑：')
result['comments'] = getCommentCounts(newsurl)
return result

#解析分页连接
def parseListLinks(url):
newsdetails = []
res = requests.get(url)
jd = json.loads(res.text.rstrip(');').lstrip(' newsloadercallback('))
for ent in jd['result']['data']:
newsdetails.append(getNewsDetail(ent['url']))
return newsdetails

#url为分页链接，关键参数page
url = 'http://api.roll.news.sina.com.cn/zt_list?channel=news&cat_1=gnxw&cat_2==gdxw1||=gatxw||=zs-pl||=mtjj&level==1||=2&show_ext=1&show_all=1&show_num=22&tag=1&format=json&page={}&callback=newsloadercallback&_=1509779364426'
news_total = []

#抓取1，2两页新闻信息
for i in range(1,3):
newsurl = url.format(i)
newsary = parseListLinks(newsurl)
news_total.extend(newsary)

#使用sqlite存储数据，pandas清晰展示数据
df = pandas.DataFrame(news_total)
with sqlite3.connect('news.sqlite') as db:
df2 = pandas.read_sql_query('select * from news', con = db)
df2

来源：https://www.cnblogs.com/heguoxiu/p/10441359.html

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网络爬虫

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python