数据结构化与保存

Posted 2020-10-31 有志气的骚年

1. 将新闻的正文内容保存到文本文件。

def writeDetailNews(content):
    f = open(\'gzccnews.txt\',"a",encoding="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) 

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 writeDetailNews(content):
    f = open(\'gzccnews.txt\',"a",encoding="utf-8")
    f.write(content)
    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 getNewDetail(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(getNewDetail(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.

import pandas
df = pandas.DataFrame(newstotal)

4. 通过df将提取的数据保存到csv或excel 文件。

df.to_excel(\'cwh.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[[\'clickCount\',\'title\',\'source\']].head(6))

 

 

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

 

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

 

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)

with sqlite3.connect(\'cwhdb.sqlite\') as db:
    df.to_sql(\'cwh\',con=db,if_exists=\'replace\')
with sqlite3.connect(\'cwhdb.sqlite\') as db:
    df10 = pandas.read_sql_query(\'select * from cwh\',con=db)
print(df10)

　　

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。）

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