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 Installation Pattern is written for Python 2.5+ (no support for Python 3 yet). To install Pattern so that the module is available in all Python scripts, from the command line do: > cd pattern-2.6 > python setup.py install If you have pip, you can automatically download and install from the PyPi repository: If none of the above works, you can make Python aware of the module in three ways: Quick overview pattern.web pattern.en The pattern.en module is a natural language processing (NLP) toolkit for English. pattern.search pattern.vector Case studies
Beautiful Soup documentation by Leonard Richardson (firstname.lastname@example.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 [External link]) Beautiful Soup 3 has been replaced by Beautiful Soup 4. Beautiful Soup 3 only works on Python 2.x, but Beautiful Soup 4 also works on Python 3.x. Beautiful Soup 3已经被Beautiful Soup 4替代.请在新的项目中查看Beautiful Soup 4的文档. Beautiful Soup 3只能在python2.x版本中运行,而Beautiful Soup 4还可以在python3.x版本中运行.Beautiful Soup 4速度更快,特性更多,而且与第三方的文档解析库(如lxml和html5lib)协同工作.推荐在新的项目中使用Beautiful Soup 4. Beautiful Soup is an HTML/XML parser for Python that can turn even invalid markup into a parse tree. This document illustrates all major features of Beautiful Soup version 3.0, with examples. Table of Contents Quick Start Get Beautiful Soup here. Include Beautiful Soup in your application with a line like one of the following: from bs4 import BeautifulSoup # To get everything
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) : def index(): form = FORM(action="insert",method="post") form <= INPUT(name="foo")+BR()+INPUT(name="bar") form <= INPUT(Type="submit",value="Ok") return HTML(BODY(form)) The scripts can be served by a built-in web server, or through the Apache server, either on CGI mode or using the WSGI interface This project is a rewriting of the Python 2.x version, adapted to Python version 3.2 and over, with some incompatibilies BuanBuan is a wiki application based on Karrigell 4 kforum is a forum application kftp is a FTP-like program to manage files and folders on line
Python Script - Plugin for Notepad++ 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. Second, people feel lxml is harder to install. $ STATIC_DEPS=true easy_install 'lxml>=2.2alpha1' One you have lxml installed, you have a great parser (which happens to be super-fast and that is ). One of the features that should be appealing to many people doing screen scraping is that you get CSS selectors. from BeautifulSoup import BeautifulSoup import urllib2 soup = BeautifulSoup ( urllib2 . urlopen ( ' ) . read ( ) ) for subMenu in menu: links = subMenu. findAll ( 'a' ) for link in links: print "%s : %s" % ( link. string , link [ 'href' ] ) Here’s the same example in lxml: from lxml. html import parse doc = parse ( ' ) . getroot ( ) for link in doc. cssselect ( 'div.pad a' ) : doc. make_links_absolute ( )
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. lxml and Requests lxml is a pretty extensive library written for parsing XML and HTML documents very quickly, even handling messed up tags in the process. Let’s start with the imports: from lxml import htmlimport requests Next we will use requests.get to retrieve the web page with our data, parse it using the html module and save the results in tree: page = requests.get(' = html.fromstring(page.content) (We need to use page.content rather than page.text because html.fromstring implicitly expects bytes as input.) XPath is a way of locating information in structured documents such as HTML or XML documents.
Beautiful Soup: We called him Tortoise because he taught us. You didn't write that awful page. You're just trying to get some data out of it. Beautiful Soup is here to help. If you have questions, send them to the discussion group. Beautiful Soup is a Python library designed for quick turnaround projects like screen-scraping. Beautiful Soup provides a few simple methods and Pythonic idioms for navigating, searching, and modifying a parse tree: a toolkit for dissecting a document and extracting what you need. Beautiful Soup parses anything you give it, and does the tree traversal stuff for you. Valuable data that was once locked up in poorly-designed websites is now within your reach. Interested? Download Beautiful Soup The current release is Beautiful Soup 4.6.0 (May 7, 2017). In Debian and Ubuntu, Beautiful Soup is available as the python-bs4 package (for Python 2) or the python3-bs4 package (for Python 3). Beautiful Soup 4 works on both Python 2 (2.7+) and Python 3. Beautiful Soup 3 Beautiful Soup 3 works only under Python 2.x. Hall of Fame
CubicWeb Semantic Web Framework 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 br.select_form(name="order")# Browser passes through unknown attributes (including methods)# to the selected HTMLForm.br["cheeses"] = ["mozzarella", "caerphilly"] # (the method here is __setitem__)# Submit current form. # print currently selected form (don't call .submit() on this, use br.submit())print br.form mechanize exports the complete interface of urllib2: