数据结构化与保存

1. 将新闻的正文内容保存到文本文件。

def writeNewsDetails(contents):
    f = open('gzccnews.txt', 'a', encoding='utf-8')
    f.write(contents)
    f.close()

2. 将新闻数据结构化为字典的列表:

• 单条新闻的详情-->字典news
• 一个列表页所有单条新闻汇总-->列表newsls.append(news)
• 所有列表页的所有新闻汇总列表newstotal.extend(newsls)

  import requests
  from bs4 import BeautifulSoup
  from datetime import datetime
  import re
  import pandas
  import openpyxl
  import sqlite3
   
  url = "http://news.gzcc.cn/html/xiaoyuanxinwen/"
  res = requests.get(url);
  res.encoding = "utf-8"
  soup = BeautifulSoup(res.text,"html.parser");
   
  def writeNewsDetails(contents):
      f = open('gzccnews.txt',"a",encoding="utf-8")
      f.write(contents)
      f.close()
   
   
  def getClickCount(newUrl):
      newsId = re.findall("\_(.*).html",newUrl)[0].split("/")[-1];
      res = requests.get("http://oa.gzcc.cn/api.php?op=count&id= {}&modelid=80".format(newsId))
      return int(res.text.split(".html")[-1].lstrip("('").rsplit("');")[0])
   
   
  #获取新闻详情
  def getNewDetails(newsDetailUrl):
      detail_res = requests.get(newsDetailUrl)
      detail_res.encoding = "utf-8"
      detail_soup = BeautifulSoup(detail_res.text, "html.parser")
   
      news={}
      news['title'] = detail_soup.select(".show-title")[0].text
      info = detail_soup.select(".show-info")[0].text
      news['date_time'] = datetime.strptime(info.lstrip('发布时间:')[:19], "%Y-%m-%d %H:%M:%S")
      if info.find('来源：')>0:
          news['source'] = info[info.find("来源："):].split()[0].lstrip('来源：')
      else:
          news['source'] = 'none'
      news['content'] = detail_soup.select("#content")[0].text
      writeDetailNews(news['content'])
      news['click'] = getClickCount(newsDetailUrl)
      return news
      # print(news)
   
  # 获取总页数
  def getPageN(url):
      res = requests.get(url)
      res.encoding = 'utf-8'
      soup = BeautifulSoup(res.text, 'html.parser')
      return int(soup.select(".a1")[0].text.rstrip("条"))//10+1
   
  # 获取新闻一页的所有信息
  def getListPage(url):
     newsList = []
     for news in soup.select("li"):
          if len(news.select(".news-list-title"))>0:  #排除为空的li
              # time = news.select(".news-list-info")[0].contents[0].text
              # title = news.select(".news-list-title")[0].text
              # description = news.select(".news-list-description")[0].text
              detail_url = news.select('a')[0].attrs['href']
              newsList.append(getNewDetails(detail_url))
              return newsList
   
  newsTotal = []
  totalPageNum = getPageN(url)
  firstPageUrl = "http://news.gzcc.cn/html/xiaoyuanxinwen/"
  newsTotal.extend(getListPage(firstPageUrl))
   
  for num in range(totalPageNum,totalPageNum+1):
          listpageurl="http://news.gzcc.cn/html/xiaoyuanxinwen/{}.html".format(num)
          getListPage(listpageurl)
   
  print(newsTotal)

3. 安装pandas，用pandas.DataFrame(newstotal)，创建一个DataFrame对象df.

df = pandas.DataFrame(newsTotal)
print(df)

4. 通过df将提取的数据保存到csv或excel 文件。

df.to_excel('gzcss.xlsx')

5. 用pandas提供的函数和方法进行数据分析：

• 提取包含点击次数、标题、来源的前6行数据
• 提取‘学校综合办’发布的，‘点击次数’超过3000的新闻。
• 提取'国际学院'和'学生工作处'发布的新闻。
• 进取2018年3月的新闻

  print(df[['title','clickCount','source']][:6])
   
  print(df[(df['clickCount']>3000)&(df['source']=='学校综合办')])
   
  sou = ['国际学院','学生工作处']
  print(df[df['source'].isin(sou)])
   
  # 进取2018年3月的新闻
  df1 = df.set_index('time')
  print(df1['2018-03'])

6. 保存到sqlite3数据库

import sqlite3
with sqlite3.connect('gzccnewsdb.sqlite') as db:
df3.to_sql('gzccnews05',con = db, if_exists='replace')

7. 从sqlite3读数据

with sqlite3.connect('gzccnewsdb.sqlite') as db:
df2 = pandas.read_sql_query('SELECT * FROM gzccnews05',con=db)
print(df2)

8. df保存到mysql数据库

安装SQLALchemy
安装PyMySQL
MySQL里创建数据库：create database gzccnews charset utf8;

import pymysql
from sqlalchemy import create_engine
conn = create_engine('mysql+pymysql://root:root@localhost:3306/gzccnews?charset=utf8')
pandas.io.sql.to_sql(df, 'gzccnews', con=conn, if_exists='replace')

MySQL里查看已保存了数据。（通过MySQL Client或Navicate。）