數據結構化與保存

1. 將新聞的正文內容保存到文本文件。

import requests
from bs4 import BeautifulSoup

url = "http://news.gzcc.cn/html/xiaoyuanxinwen/"
res = requests.get(url)
res.encoding = "utf-8"
soup = BeautifulSoup(res.text, "html.parser")

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

2. 將新聞數據結構化爲字典的列表:

• 單條新聞的詳情-->字典news
• 一個列表頁全部單條新聞彙總-->列表newsls.append(news)
• 全部列表頁的全部新聞彙總列表newstotal.extend(newsls)

def getNewsDetail(url):
    resd = requests.get(url)
    resd.encoding = 'utf-8'
    soupd = BeautifulSoup(resd.text,'html.parser')
    # print(resd.text)
    news = {}
    news['title'] = soupd.select('.show-title')[0].text
    info = soupd.select('.show-info')[0].text
    news['time'] = datetime.strptime(info.lstrip('發佈時間:')[0:19],'%Y-%m-%d %H:%M:%S')
    if info.find('來源：')>0:
        news['source'] = info[info.find('來源：'):].split()[0].lstrip('來源：')
    else:
        news['source'] = 'none'

    news['clickCount'] = int(getClickCount(url))
    news['newsUrl'] = url
    news['content'] = soupd.select('.show-content')[0].text.strip()

    writeNewsDetail(news['content'])
    return(news)

3. 安裝pandas，用pandas.DataFrame(newstotal)，建立一個DataFrame對象df.

import pandas
newstotal = [{}]
df = pandas.DataFrame(newstotal)

4. 經過df將提取的數據保存到csv或excel 文件。

import openpyxl
df.to_excel('gzccnews.xlsx')

5. 用pandas提供的函數和方法進行數據分析：

• 提取包含點擊次數、標題、來源的前6行數據
• 提取‘學校綜合辦’發佈的，‘點擊次數’超過3000的新聞。
• 提取'國際學院'和'學生工做處'發佈的新聞。
• 進取2018年3月的新聞

print(df[['title','clickCount','source']][:6])
print(df[(df['clickCount']>3000)&(df['source']=='學校綜合辦')])
  
sou = ['國際學院','學生工做處']
print(df[df['source'].isin(sou)])
  
df1 = df.set_index('time')
print(df1['2018-03'])

6. 保存到sqlite3數據庫

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

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

7. 從sqlite3讀數據

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

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數據庫

安裝SQLALchemy
安裝PyMySQL
MySQL裏建立數據庫：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裏查看已保存了數據。（經過MySQL Client或Navicate。）

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')