August 2022
Intermediate to advanced
441 pages
11h 26m
Chinese
Content preview from Python文本分析
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100
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第
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Reporting Jacqueline Tempera in Brookline and Boston, Massachusetts, and
Jonathan Allen in New York; Editing by Frank McGurty and Bill Berkrot'
在这个例子中，输出的结果非常好。在大多数情况下，
python-readability
的效果
都很不错，而且无需考虑太多特殊情况。但是，使用该库的代价是不确定性。它是
否能够始终以预期的方式工作，是否无法提取时间戳、作者之类的结构化数据（尽
管我们可能还有其他启发式的方式）？
3.15.2
总结基于密度的文本提取
基于密度的文本提取方法是一种非常强大的方法，它同时使用了启发式和有关
HTML
页面上信息分布的统计信息。不过请注意，这种方法所得出的结果自然无法
与专用的提取实现相比。然而，如果你需要从许多不同类型的页面提取内容，或者
从某个根本没有固定版式的存档中提取内容，则这种方法值得一试。
与结构化方法相比，在提取之后执行严格的质量保证尤为重要，因为启发式和统计
的方法有时可能会走错方向。
3.16
一体化解决方案
Scrapy
（
https://scrapy.org
）也是一个
Python
的软件包，它提供了爬虫以及内容提
取的一体化解决方案。尽管
Scrapy
更适合下载整个网站，而不仅仅是网站的一部分，
但这些方法与我们前面介绍的方法相似。
Scrapy
是一个非常出色的、面向对象、整体分析式解决方案，而且代码易于阅读。 ...
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