文章目录

• 前言
• 一、南阳理工学院ACM题目网站爬取
• • 1.引入库
  • 1.爬取代码
  • 3.运行结果
• 二、学校官网新闻信息爬取
• • 1.引入库
  • 2.爬取代码
  • 3.爬取结果
• 参考

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前言

网络爬虫(又被称为网页蜘蛛，网络机器人，在FOAF社区中间，更经常的称为网页追逐者)，是一种按照一定的规则，自动的抓取万维网信息的程序或者脚本。另外一些不常使用的名字还有蚂蚁，自动索引，模拟程序或者蠕虫。

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一、南阳理工学院ACM题目网站爬取

1.引入库

import requests
from bs4 import BeautifulSoup
import csv
from tqdm import tqdm

1.爬取代码

# 模拟浏览器访问
Headers = 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.25 Safari/537.36 Core/1.70.3741.400 QQBrowser/10.5.3863.400'

# 表头
csvHeaders = ['题号', '难度', '标题', '通过率', '通过数/总提交数']

# 题目数据
subjects = []

# 爬取题目
print('题目信息爬取中：\n')
for pages in tqdm(range(1, 11 + 1)):

    r = requests.get(f'http://www.51mxd.cn/problemset.php-page={pages}.htm', Headers)

    r.raise_for_status()

    r.encoding = 'utf-8'

    soup = BeautifulSoup(r.text, 'html5lib')

    td = soup.find_all('td')

    subject = []

    for t in td:
        if t.string is not None:
            subject.append(t.string)
            if len(subject) == 5:
                subjects.append(subject)
                subject = []

# 存放题目
with open('NYOJ_Subjects.csv', 'w', newline='') as file:
    fileWriter = csv.writer(file)
    fileWriter.writerow(csvHeaders)
    fileWriter.writerows(subjects)

print('\n题目信息爬取完成！！！')

3.运行结果

存储文件：

二、学校官网新闻信息爬取

1.引入库

import requests
from bs4 import BeautifulSoup
import csv
from tqdm import tqdm
import urllib.request, urllib.error  # 制定URL 获取网页数据

2.爬取代码

# 所有新闻
subjects = []

# 模拟浏览器访问
Headers = {  # 模拟浏览器头部信息
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/95.0.4638.69 Safari/537.36 Edg/95.0.1020.53"
}

# 表头
csvHeaders = ['时间', '标题']


print('信息爬取中：\n')
for pages in tqdm(range(1, 66 + 1)):
    # 发出请求
    request = urllib.request.Request(f'http://news.cqjtu.edu.cn/xxtz/{pages}.htm', headers=Headers)
    html = ""
    # 如果请求成功则获取网页内容
    try:
        response = urllib.request.urlopen(request)
        html = response.read().decode("utf-8")
    except urllib.error.URLError as e:
        if hasattr(e, "code"):
            print(e.code)
        if hasattr(e, "reason"):
            print(e.reason)
    # 解析网页
    soup = BeautifulSoup(html, 'html5lib')

    # 存放一条新闻
    subject = []
    # 查找所有li标签
    li = soup.find_all('li')
    for l in li:
        # 查找满足条件的div标签
        if l.find_all('div',class_="time") is not None and l.find_all('div',class_="right-title") is not None:
            # 时间
            for time in l.find_all('div',class_="time"):
                subject.append(time.string)
            # 标题
            for title in l.find_all('div',class_="right-title"):
                for t in title.find_all('a',target="_blank"):
                    subject.append(t.string)
            if subject:
                print(subject)
                subjects.append(subject)
        subject = []

# 保存数据
with open('CQJTUnews.csv', 'w', encoding='utf-8') as file://encodeing='utf-8'使用utf-8编码，如果空着可能会出现编码出错
    fileWriter = csv.writer(file)
    fileWriter.writerow(csvHeaders)
    fileWriter.writerows(subjects)

print('\n信息爬取完成！！！')

3.爬取结果

保存文件：

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参考

https://blog.csdn.net/qq_47281915/article/details/121344160