基于“互联网+”数据自动提取的网络爬虫的设计与实现

Lulu Zhang, Junru Li, Dacheng Feng, Junjie Sun
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引用次数: 0

摘要

“互联网+”战略的兴起,打破了数据和信息的壁垒。在海量的互联网+信息中,网络爬虫被广泛应用于数据采集和数据分析。本文以“IMDB top250电影”为目标,利用基于Python语言的爬虫技术,详细阐述了网络爬虫的四个步骤,比较了BeautifulSoup、正则表达式(Re)和XPath三种网页解析方法的差异,完成了目标数据的爬虫。实验结果表明,Re在数据分析速度上是最好的;在网页解析逻辑方面,美汤是最好的;从综合使用的角度来看,XPath更合适。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design And Implementation of Web Crawler Based on 'Internet +'Data Automatic Extraction
The rise of the strategy of “Internet +” breaks the barriers of data and information. Web crawler is widely used in data acquisition and data analysis in the massive Internet plus information. Taking “IMDB top250 movies” as the goal, using the crawler technology based on Python language, this paper explains the four steps of web crawler in detail, compares the differences of three web page parsing methods: BeautifulSoup, Regular Expression(Re) and XPath, and completes the crawling of target data. The experimental results show that Re is the best in data analysis speed; In terms of web page parsing logic, beautiful soup is the best; From the perspective of comprehensive use, XPath is more suitable.
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