python爬虫(1)

上传者: 33979657 | 上传时间: 2025-12-25 00:11:58 | 文件大小: 701KB | 文件类型: ZIP
在本教程中,我们将探讨如何使用Python编程语言编写一个简单的爬虫程序,以实现自动、实时地从广西空气质量实时发布系统获取南宁市各个监测站点的PM2.5数值,并将这些数据存储到Python内置的SQLite数据库中。这涉及到几个关键知识点,包括网页抓取、后台运行以及数据库操作。 我们需要了解Python中的网络爬虫技术。Python有许多强大的库用于网页抓取,如BeautifulSoup和Requests。Requests库用于发送HTTP请求,获取网页HTML内容;BeautifulSoup则是一个解析库,它能解析HTML或XML文档,帮助我们提取所需信息。在这个案例中,我们将用这两个库来访问空气质量网站并解析出PM2.5数据。 1. **Requests库的使用**: - 发送GET请求:`response = requests.get(url)` - 处理响应:`html_text = response.text` 2. **BeautifulSoup的使用**: - 解析HTML:`soup = BeautifulSoup(html_text, 'html.parser')` - 查找特定元素:`element = soup.find('tag_name', attrs={'attribute': 'value'})` - 提取数据:`data = element.text` 为了让爬虫程序在后台持续运行,可以采用Python的定时任务库,如APScheduler。它可以设置定时任务,定期执行爬虫脚本,确保实时获取数据。 1. **APScheduler的使用**: - 引入库:`from apscheduler.schedulers.blocking import BlockingScheduler` - 创建调度器:`scheduler = BlockingScheduler()` - 添加定时任务:`scheduler.add_job(function, 'interval', minutes=15)` - 启动调度器:`scheduler.start()` 我们将使用Python内置的SQLite数据库来存储数据。SQLite是一个轻量级的数据库,无需单独的服务器进程,可以直接在Python环境中操作。 1. **SQLite的使用**: - 连接数据库:`conn = sqlite3.connect('air_quality.db')` - 创建游标对象:`cursor = conn.cursor()` - 执行SQL语句:`cursor.execute('CREATE TABLE IF NOT EXISTS pm25 (id INTEGER PRIMARY KEY, value REAL)')` - 插入数据:`cursor.execute('INSERT INTO pm25 VALUES (?, ?)', (timestamp, pm2.5_value))` - 提交事务:`conn.commit()` - 关闭连接:`conn.close()` 为了实现以上功能,你需要确保安装了以下Python库: - requests - beautifulsoup4 - apscheduler - sqlite3(Python标准库) 可以通过pip安装它们: ``` pip install requests beautifulsoup4 apscheduler ``` 这个项目涵盖了Python爬虫的基础知识,包括网络请求、HTML解析、后台定时任务以及数据库操作。通过学习和实践,你可以掌握如何利用Python来获取实时数据并进行持久化存储。记得在实际操作时遵守网站的robots.txt协议,合法合规地进行网络爬虫。

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