数据结构化与保存

Posted 2020-10-31 标弟

1. 将新闻的正文内容保存到文本文件。

def writeNewsDetail(content):
    f = open(\'content.text\',\'a\',\'utf-8\')
    f.write(content)
    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)

from datetime import datetime
import requests
import re
from bs4 import BeautifulSoup

def getClickCount(newsUrl):
    newsId = re.search(\'\\_(.*).html\', newsUrl).group(1).split(\'/\')[1]
    clickUrl = \'http://oa.gzcc.cn/api.php?op=count&id={}&modelid=80\'.format(newsId)
    return (int(requests.get(clickUrl).text.split(\'.html\')[-1].lstrip("(\'").rstrip("\');")))

def getNewsDetail(newsUrl):
    res = requests.get(newsUrl)
    res.encoding = \'utf-8\'
    Ssoup = BeautifulSoup(res.text, \'html.parser\')

    title = Ssoup.select(\'.show-title\')[0].text
    info = Ssoup.select(\'.show-info\')[0].text
    dt = datetime.strptime(info.lstrip(\'发布时间:\')[0:19], \'%Y-%m-%d %H:%M:%S\')
    source = info[info.find(\'来源：\'):].split()[0].lstrip(\'来源:\')
    content = Ssoup.select(\'.show-content\')[0].text.strip()
    click = getClickCount(newsUrl)
    print(dt, title, newsUrl, source, click)

def writeNewsDetail(content):
    f = open(\'content.text\',\'a\',\'utf-8\')
    f.write(content)
    f.close()

def getNewsDetail(newsUrl):
    res = requests.get(newsUrl)
    res.encoding = \'utf-8\'
    Ssoup = BeautifulSoup(res.text, \'html.parser\')

    news={}
    news[\'title\'] = Ssoup.select(\'.show-title\')[0].text
    info = Ssoup.select(\'.show-info\')[0].text
    news[\'dt\'] = datetime.strptime(info.lstrip(\'发布时间:\')[0:19], \'%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\'] = Ssoup.select(\'.show-content\')[0].text.strip()
    # writeNewsDetail(news[\'content\'])
    news[\'click\'] = getClickCount(newsUrl)
    news[\'newsUrl\'] = newsUrl
    return(news)

def getListPage(pageUrl):
    res = requests.get(pageUrl)
    res.encoding = \'utf-8\'
    soup = BeautifulSoup(res.text, \'html.parser\')

    newslist = []
    for news in soup.select("li"):
        if len(news.select(".news-list-title")) > 0:  # 排除为空的li
            newsUrl = news.select(\'a\')[0].attrs[\'href\']
            newslist.append(getNewsDetail(newsUrl))
    return (newslist)

def getPageN():
    res = requests.get(firstPageUrl)
    res.encoding = \'utf-8\'
    soup = BeautifulSoup(res.text, \'html.parser\')
    n = int(soup.select(\'.a1\')[0].text.rstrip(\'条\'))
    return (n // 10 + 1)


newstotal = []
firstPageUrl = \'http://news.gzcc.cn/html/xiaoyuanxinwen/\'
newstotal.extend(getListPage(firstPageUrl))

n = getPageN()
for i in range(n, n+1):
    listPageUrl = \'http://news.gzcc.cn/html/xiaoyuanxinwen/{}.html\'.format(i)
    newstotal.extend(getListPage(listPageUrl))
print(newstotal)

　　

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

import pandas
df = pandas.DataFrame(newstotal)

4. 通过df将提取的数据保存到csv或excel 文件。

import openpyxl
df.to_excel(\'1234.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

  print(df[[\'click\',\'title\',\'source\']].head(6))　　

• 

   

• 提取‘学校综合办’发布的，‘点击次数’超过3000的新闻。

  print(df[(df[\'click\']>3000)&(df[\'source\']==\'学校综合办\')])

• 

   

• 提取\'国际学院\'和\'学生工作处\'发布的新闻。

  print(df[(df[\'source\']==\'国际学院\')|(df[\'source\']==\'学生工作处\')])

• 

   

• 进取2018年3月的新闻

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。）