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Lxml - Processing XML and HTML with Python

Lxml - Processing XML and HTML with Python
lxml is the most feature-rich and easy-to-use library for processing XML and HTML in the Python language. The lxml XML toolkit is a Pythonic binding for the C libraries libxml2 and libxslt. It is unique in that it combines the speed and XML feature completeness of these libraries with the simplicity of a native Python API, mostly compatible but superior to the well-known ElementTree API. The latest release works with all CPython versions from 2.4 to 3.3. See the introduction for more information about background and goals of the lxml project. Some common questions are answered in the FAQ.

http://lxml.de/

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Pattern Pattern is a web mining module for the Python programming language. It has tools for data mining (Google, Twitter and Wikipedia API, a web crawler, a HTML DOM parser), natural language processing (part-of-speech taggers, n-gram search, sentiment analysis, WordNet), machine learning (vector space model, clustering, SVM), network analysis and <canvas> visualization. The module is free, well-document and bundled with 50+ examples and 350+ unit tests. Download

HTML Scraping Web Scraping Web sites are written using HTML, which means that each web page is a structured document. Sometimes it would be great to obtain some data from them and preserve the structure while we’re at it. Web sites don’t always provide their data in comfortable formats such as csv or json. This is where web scraping comes in. karrigell - A web framework for Python 3.2+ Karrigell is a Pythonic web framework, very simple to learn and to use Karrigell's design is about simplicity for the programmer and integration of all the web environment in the scripts namespace. All the HTML tags are available as classes in the scripts namespace : def index(): return HTML(BODY("Hello world")) To build an HTML document as a tree, the HTML tags objects support the operators + (add brother) and <= (add child) :

Beautiful Soup documentation by Leonard Richardson (leonardr@segfault.org) 这份文档也有中文版了 (This document is also available in Chinese translation) Этот документ также доступен в русском переводе. [Внешняя ссылка] (This document is also available in Russian translation. [External link]) Beautiful Soup 3 has been replaced by Beautiful Soup 4. mechanize Stateful programmatic web browsing in Python, after Andy Lester’s Perl module WWW::Mechanize. The examples below are written for a website that does not exist (example.com), so cannot be run. There are also some working examples that you can run. import reimport mechanize br = mechanize.Browser()br.open(" follow second link with element text matching regular expressionresponse1 = br.follow_link(text_regex=r"cheese\s*shop", nr=1)assert br.viewing_html()print br.title()print response1.geturl()print response1.info() # headersprint response1.read() # body

Item Pipeline — Scrapy 0.21.0 documentation After an item has been scraped by a spider, it is sent to the Item Pipeline which process it through several components that are executed sequentially. Each item pipeline component (sometimes referred as just “Item Pipeline”) is a Python class that implements a simple method. They receive an Item and perform an action over it, also deciding if the Item should continue through the pipeline or be dropped and no longer processed. Typical use for item pipelines are: Python Extension Packages for Windows - Christoph Gohlke by Christoph Gohlke, Laboratory for Fluorescence Dynamics, University of California, Irvine. This page provides 32- and 64-bit Windows binaries of many scientific open-source extension packages for the official CPython distribution of the Python programming language. The files are unofficial (meaning: informal, unrecognized, personal, unsupported, no warranty, no liability, provided "as is") and made available for testing and evaluation purposes. If downloads fail reload this page, enable JavaScript, disable download managers, disable proxies, clear cache, and use Firefox. Please only download files manually as needed.

lxml: an underappreciated web scraping library When people think about web scraping in Python, they usually think BeautifulSoup . That’s okay, but I would encourage you to also consider lxml . First, people think BeautifulSoup is better at parsing broken HTML. lxml parses broken HTML quite nicely. Category:LanguageBindings -> PySide EnglishEspañolMagyarItalian한국어日本語 Welcome to the PySide documentation wiki page. The PySide project provides LGPL-licensed Python bindings for the Qt.

Link Extractors — Scrapy 0.20.2 documentation Link Extractors¶ LinkExtractors are objects whose only purpose is to extract links from web pages (scrapy.http.Response objects) which will be eventually followed. There are two Link Extractors available in Scrapy by default, but you create your own custom Link Extractors to suit your needs by implementing a simple interface. The only public method that every LinkExtractor has is extract_links, which receives a Response object and returns a list of scrapy.link.Link objects. Link Extractors are meant to be instantiated once and their extract_links method called several times with different responses, to extract links to follow.

Pylogsparser : a use case, analysing ssh attacks digg In this article we will see how easy it is to use the pylogsparser library through a simple use case. It should help you start working on your own project involving log analysis.

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