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IDE - Overview. NetBeans IDE lets you quickly and easily develop Java desktop, mobile, and web applications, as well as HTML5 applications with HTML, JavaScript, and CSS.

IDE - Overview

The IDE also provides a great set of tools for PHP and C/C++ developers. It is free and open source and has a large community of users and developers around the world. Best Support for Latest Java Technologies NetBeans IDE provides first-class comprehensive support for the newest Java technologies and latest Java specification enhancements before other IDEs. It is the first free IDE providing support for JDK 8, JDK 7, Java EE 7 including its related HTML5 enhancements, and JavaFX 2. With its constantly improving Java Editor, many rich features and an extensive range of tools, templates and samples, NetBeans IDE sets the standard for developing with cutting edge technologies out of the box. Fast & Smart Code Editing. Screen_scraping. Screen_scraping. Pyquery: a jquery-like library for python — pyquery 1.2.4 documentation. Pyquery allows you to make jquery queries on xml documents.

pyquery: a jquery-like library for python — pyquery 1.2.4 documentation

The API is as much as possible the similar to jquery. pyquery uses lxml for fast xml and html manipulation. This is not (or at least not yet) a library to produce or interact with javascript code. I just liked the jquery API and I missed it in python so I told myself “Hey let’s make jquery in python”. Ironmacro - GUI Automation for .NET. Pyscraper - simple python based HTTP screen scraper. Xkcd-viewer - A small test project using screen scraping. Juicedpyshell - This Python Firefox Shell Mashup lets you automate Firefox browser using python scripts. The Juiced Python Firefox Shell lets you automate a browser using python scripts.

juicedpyshell - This Python Firefox Shell Mashup lets you automate Firefox browser using python scripts

It requires that the pyxpcomext extension be installed. It is useful for browser automation, including automated testing of web sites. It makes it easy to do screen scraping and html manipulation using Python. Examples — webscraping documentation. Simple extraction Except project title from the Google Code page: from webscraping import download, xpathD = download.Download()# download and cache the Google Code webpagehtml = D.get(' use xpath to extract the project titleproject_title = xpath.get(html, '//div[@id="pname"]/a/span') Blog scraper Scrape all articles from a blog import itertoolsimport urlparsefrom webscraping import common, download, xpath DOMAIN = ...writer = common.UnicodeWriter('articles.csv')writer.writerow(['Title', 'Num reads', 'URL'])seen_urls = set() # track which articles URL's already seen, to prevent duplicatesD = download.Download() # iterate each of the categoriesfor category_link in ('/developer/knowledge-base?

Examples — webscraping documentation

Business directory threaded scraper Scrape all businesses from this popular directory. Scrapemark - Documentation. ScrapeMark is analagous to a regular expression engine.

Scrapemark - Documentation

A ‘pattern’ with special syntax is applied to the HTML being scraped. 12.2 Parsing HTML documents. 12.2 Parsing HTML documents This section only applies to user agents, data mining tools, and conformance checkers.

12.2 Parsing HTML documents

The rules for parsing XML documents into DOM trees are covered by the next section, entitled "The XHTML syntax". User agents must use the parsing rules described in this section to generate the DOM trees from text/html resources. Together, these rules define what is referred to as the HTML parser. Mechanize. Stateful programmatic web browsing in Python, after Andy Lester’s Perl module WWW::Mechanize.

mechanize

Scrapemark - Easy Python Scraping Library. NOTE: This project is no longer maintained!

Scrapemark - Easy Python Scraping Library

(more info) It utilizes an HTML-like markup language to extract the data you need. You get your results as plain old Python lists and dictionaries. Scrapemark internally utilizes regular expressions and is super-fast. As an example, here is a way you could scrape all the links on the Digg homepage in one fell swoop: import scrapemark print scrapemark.scrape(""" {* <div class='news-summary'><h3><a href='{{ [links].url }}'>{{ [links].title }}</a></h3><p>{{ [links].description }}</p><li class='digg-count'><strong>{{ [links].diggs|int }}</strong></li></div> *} """, url=' How to get along with an ASP webpage. Fingal County Council of Ireland recently published a number of sets of Open Data, in nice clean CSV, XML and KML formats.

How to get along with an ASP webpage

Unfortunately, the one set of Open Data that was difficult to obtain, was the list of sets of open data. That’s because the list was separated into four separate pages. The important thing to observe is that Next >> link is no ordinary link. You can see something is wrong when you hover your cursor over it. Here’s what it looks like in the HTML source code: Mechanize. Screen_scraping. Using A Gui To Build Packages. Not everyone is a command line junkie.

Using A Gui To Build Packages

Some folks actually prefer the comfort of a Windows GUI application for performing tasks such as package creation. The NuGet Package Explorer click-once application makes creating packages very easy. It's also a great way to examine packages and learn how packages are structured. If you’re integrating building packages into a build system, then using NuGet.exe to create and publish packages is a better choice. Installation Installing Package Explorer is easy, click here and you’re done! Package Explorer is a click-once application which means every time you launch it, it will check for updates and allow you to keep the application up to date. Creating a Package To create a package, launch Package Explorer and select File > New menu option (or hit CTRL + N). C# - Scraping Content From Webpage? Sponsored Links: Related Forum Messages For ASP.NET category: Scraping Text Of A Webpage? Web scraping with Python. What are good Perl or Python starting points for a site scraping library.

Using A Gui To Build Packages. C# - Scraping Content From Webpage? Webscraping with Python. Scrape.py. Scrape.py is a Python module for scraping content from webpages. Using it, you can easily fetch pages, follow links, and submit forms. Cookies, redirections, and SSL are handled automatically.

(For SSL, you either need a version of Python with the socket.ssl function, or the curl command-line utility.) Julian_Todd / Python mechanize cheat sheet. Mechanize — Documentation. Full API documentation is in the docstrings and the documentation of urllib2. The documentation in these web pages is in need of reorganisation at the moment, after the merge of ClientCookie and ClientForm into mechanize. Tests and examples Examples The front page has some introductory examples. The examples directory in the source packages contains a couple of silly, but working, scripts to demonstrate basic use of the module. See also the forms examples (these examples use the forms API independently of mechanize.Browser).

Tests To run the tests: Screen Scraping. Probabilistic Graphical Models. What are Probabilistic Graphical Models? Uncertainty is unavoidable in real-world applications: we can almost never predict with certainty what will happen in the future, and even in the present and the past, many important aspects of the world are not observed with certainty. Probability theory gives us the basic foundation to model our beliefs about the different possible states of the world, and to update these beliefs as new evidence is obtained. These beliefs can be combined with individual preferences to help guide our actions, and even in selecting which observations to make. While probability theory has existed since the 17th century, our ability to use it effectively on large problems involving many inter-related variables is fairly recent, and is due largely to the development of a framework known as Probabilistic Graphical Models (PGMs).

Topics covered include: Introduction and Overview. Cryptography. Cryptography is an indispensable tool for protecting information in computer systems. This course explains the inner workings of cryptographic primitives and how to correctly use them. Students will learn how to reason about the security of cryptographic constructions and how to apply this knowledge to real-world applications. The course begins with a detailed discussion of how two parties who have a shared secret key can communicate securely when a powerful adversary eavesdrops and tampers with traffic.

We will examine many deployed protocols and analyze mistakes in existing systems. The second half of the course discusses public-key techniques that let two or more parties generate a shared secret key. The course will include written homeworks and programming labs. Game Theory. Machine Learning. Khan Academy. Computer Science 101. About the Course UPDATE: we're doing a live, updated MOOC of this course at stanford-online July-2014 (not this Coursera version). Noticeboard for all MSc in Computing Students - DIT.