This paper presents the design and implementation of a user-friendly, automated web application that simplifies and optimizes the web scraping process for non-technical users. The application breaks down the complex task of web scraping into three main stages: fetching, extraction, and execution. In the fetching stage, the application accesses target websites using the HTTP protocol, leveraging the requests library to retrieve HTML content. The extraction stage utilizes powerful parsing libraries like BeautifulSoup and regular expressions to extract relevant data from the HTML. Finally, the execution stage structures the data into accessible formats, such as CSV, ensuring the scraped content is organized for easy use. To provide personalized and secure experiences, the application includes user registration and login functionalities, supported by MongoDB, which stores user data and scraping history. Deployed using the Flask framework, the tool offers a scalable, robust environment for web scraping. Users can easily input website URLs, define data extraction parameters, and download the data in a simplified format, without needing technical expertise. This automated tool not only enhances the efficiency of web scraping but also democratizes access to data extraction by empowering users of all technical levels to gather and manage data tailored to their needs. The methodology detailed in this paper represents a significant advancement in making web scraping tools accessible, efficient, and easy to use for a broader audience.

翻译：本文介绍了一款面向非技术用户、简化并优化网络爬虫流程的友好型自动化Web应用的设计与实现。该应用将复杂的网络爬虫任务分解为三个主要阶段：获取、提取与执行。在获取阶段，应用通过HTTP协议访问目标网站，利用requests库获取HTML内容。提取阶段采用BeautifulSoup等强大解析库及正则表达式从HTML中提取相关数据。最后在执行阶段，将数据组织为CSV等可访问格式，确保爬取内容有序可用。为提供个性化安全体验，应用包含用户注册与登录功能，由MongoDB支持存储用户数据及爬取历史。该工具基于Flask框架部署，为网络爬虫提供可扩展的稳健环境。用户无需专业技术知识，即可轻松输入网站URL、定义数据提取参数，并以简化格式下载数据。此自动化工具不仅提升了网络爬虫效率，更通过赋能各技术水平的用户按需采集管理数据，实现了数据提取的普及化。本文详述的方法论标志着网络爬虫工具在面向更广泛用户群体时，在可访问性、高效性与易用性方面取得了重要进展。