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 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))
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- 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')])
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- 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')])
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- 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。)