全国蔬菜批发价格分析与展示平台设计与实现-计算机毕业设计源码+LW文档

摘  要
随着蔬菜行业的迅速发展，对于大量蔬菜数据的深入分析变得尤为重要。数据分析已经成为各行各业的核心，而在蔬菜领域，它扮演着更为关键的角色。了解消费者的蔬菜偏好、蔬菜批发价格趋势、蔬菜热度等信息对于蔬菜领域的运营和提供更优质服务至关重要。本研究旨在构建一个全国蔬菜批发价格分析与展示平台，以帮助业界更好地理解消费者行为、优化服务流程，并为业务决策提供有力支持。
本文首先探讨了全国蔬菜批发价格分析与展示平台的背景和意义，随后深入研究了爬虫原理、获取策略、信息提取等常见技术。随后，采用Python进行系统开发，并以MySQL数据库搭建基础，实现了蔬菜数据的爬取。对数据库查询结果进行了检测和可视化分析，并对系统的前台界面进行了有效管理。通过对爬取结果的分析，将蔬菜批发价格数据以大屏显示形式呈现。最后，进行了全面测试，确保了数据爬取、存储过滤、数据预测、数据可视化分析以及系统管理等功能的实现。

关键词：爬虫；python；大数据；MySQL；蔬菜批发价格

 
The Design of National Vegetable Wholesale Price Analysis and Display Platform
Abstract
With the rapid development of the agricultural product industry, in-depth analysis of a large amount of agricultural product data has become particularly important. Data analysis has become the core of various industries, and in the field of agricultural products, it plays a more critical role. Understanding consumer preferences for agricultural products, price trends, and popularity of agricultural products is crucial for the operation and provision of better services in the agricultural product field. This study aims to build a Spark based agricultural product price data analysis and prediction system to help the industry better understand consumer behavior, optimize service processes, and provide strong support for business decision-making.
This article first explores the background and significance of the Spark based agricultural product price data analysis and prediction system, and then delves into common technologies such as spider principles, acquisition strategies, and information extraction. Subsequently, the system was developed using Python and built on a MySQL database to achieve the crawling of agricultural product data. Detected and visualized the database query results, and effectively managed the front-end interface of the system. By analyzing the crawling results, present agricultural product price data in a large screen format. Finally, comprehensive testing was conducted to ensure the implementation of functions such as data crawling, storage filtering, data prediction, data visualization analysis, and system management.

Key words: Crawler;Python;big data;MySQL;agricultural product prices  

在计算机信息化快速发展的背景下，蔬菜行业逐渐转向网络领域。本文主要探讨了蔬菜数据系统的设计和开发。该系统旨在收集并处理蔬菜数据，包括爬取、清理、存储和统计等功能。作为现代化蔬菜管理的重要组成部分，该系统为商家的蔬菜推荐提供了便捷的模式。本文主要针对蔬菜网上的蔬菜信息进行爬取，收集各类蔬菜数据。通过对蔬菜数据的分析，整理并提取相关信息。首先，系统分析了蔬菜网的网站结构，观察网页布局，并读取其中的蔬菜信息。具体操作步骤包括指定蔬菜网的URL、爬取网页信息、获取特定的URL并将其存入队列中。之后，从网页中提取蔬菜数据信息，将其存入数据库，并针对蔬菜进行详细分析。最后，得出蔬菜数据的可视化视图。

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