Scrapy Montreal – How to Extract Structured Data From Websites

Scrapy is a Python application framework designed to crawl web sites and extract structured data in a quick, simple and extensible manner. It can be used in a variety of applications such as data mining, information processing and historical archiving.

From a technical standpoint, it is also a good example of how the web has evolved over the years to make data available in a form that is easy to understand and use.

Its most recent iteration is the version 3.1, which offers more robust support for new and emerging technologies such as cloud computing.

The scrapy aficionado will likely be enchanted with the plethora this link of tools, libraries and modules that are available for this powerful programming language.

One of the most notable features is that Scrapy supports multiple languages and platforms. This includes Windows, Linux and Mac OS X as well as BSD and open source systems such as ipython and nio-python.

The best part is that Scrapy is able to handle a wide range of complex web pages in a way that is both elegant and efficient.

This is all the more important given the fact that most of the Internet is made up of unstructured data, and the most cost-effective ways to access it is through raw HTML.

In this tutorial we will show you how to extract the most important items from the most complex of websites in the shortest time possible and without breaking a sweat! The key is to know how to inspect the page and the best way to do this is to use the handy dandy inspector from your website of choice.