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An open source web scraping framework for Python

An open source web scraping framework for Python
What is Scrapy? Scrapy is a fast high-level screen scraping and web crawling framework, used to crawl websites and extract structured data from their pages. It can be used for a wide range of purposes, from data mining to monitoring and automated testing. Features Simple Scrapy was designed with simplicity in mind, by providing the features you need without getting in your way

http://scrapy.org/

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Requests and Responses — Scrapy 0.14.4 documentation Using FormRequest to send data via HTTP POST¶ If you want to simulate a HTML Form POST in your spider and send a couple of key-value fields, you can return a FormRequest object (from your spider) like this: Beautiful Soup Documentation — Beautiful Soup v4.0.0 documentation Beautiful Soup is a Python library for pulling data out of HTML and XML files. It works with your favorite parser to provide idiomatic ways of navigating, searching, and modifying the parse tree. It commonly saves programmers hours or days of work. These instructions illustrate all major features of Beautiful Soup 4, with examples. I show you what the library is good for, how it works, how to use it, how to make it do what you want, and what to do when it violates your expectations. The examples in this documentation should work the same way in Python 2.7 and Python 3.2.

Text Analysis 101: Document Classification Document classification is an example of Machine Learning (ML) in the form of Natural Language Processing (NLP). By classifying text, we are aiming to assign one or more classes or categories to a document, making it easier to manage and sort. By Parsa Ghaffari. Introduction Document classification is an example of Machine Learning (ML) in the form of Natural Language Processing (NLP). By classifying text, we are aiming to assign one or more classes or categories to a document, making it easier to manage and sort.

Easy Facebook Scripting in Python « Heterogenous Mixture UPDATED: fbconsole Pypi Package and Github Repository Sometimes you just want to write a little script using Facebook’s api that updates your status, or downloads all your photos, or deletes all those empty albums you accidentally created. In order to streamline my writing of one-off facebook scripts, I created a micro api client that implements the client-side authentication flow and has a few utility functions for accessing the graph api and fql.

Tabula Why Tabula? If you’ve ever tried to do anything with data provided to you in PDFs, you know how painful this is — you can’t easily copy-and-paste rows of data out of PDF files. Tabula allows you to extract that data in CSV format, through a simple interface. And now you can download Tabula and run it on your own computer, like you would with OpenRefine. Download and install Tabula Note: You’ll need a copy of Java installed.

Weblogs Forum - Screen Scraping With Python Summary Web-enabling an old terminal-oriented application turns into more fun than expected. A blow-by-blow account of writing a screen scraper with Python and pexpect. I recently finished a project for a local freight broker. They run their business on an old SCO Unix-based "green screen" terminal application. They wanted to enable some functionality on their web site, so customers could track their shipments, and carriers could update their location and status. By the time the project got to me the client had almost given up on finding a solution. Setting up Python in Windows 7 An all-wise journalist once told me that “everything is easier in Linux,” and after working with it for a few years I’d have to agree — especially when it comes to software setup for data journalism. But … Many newsroom types spend the day in Windows without the option of Ubuntu or another Linux OS. I’ve been planning some training around Python soon, so I compiled this quick setup guide as a reference. I hope you find it helpful. Set up Python on Windows 7

Book Natural Language Processing with Python – Analyzing Text with the Natural Language Toolkit Steven Bird, Ewan Klein, and Edward Loper Parser Combinators Made Simple April 18, 2011 # Parsing theory has been around for quite a long time, but it is often thought of as magic by the swarms of people who haven't bothered to read about it, and see how plain and dry it actually is. Algorithms for parsing LR(k) grammars (meaning Left-to-right, Right-most derivation, k tokens lookahead) for instance, normally just traverse a state machine that was computed before hand (either by hand, or by using a parser generator such as bison or yacc). Sure, there are many things to trip on, tedious to track down ambiguities, and other issues, but the general theory of parsing has remained unchanged for years—one might say, it is a solved problem.[1] When learning about parsing for the first time though, the idea of a recursive descent parser is often taught first.

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