Writing a web spider in python

Stories[ edit ] Anansi tales are some of the best-known amongst the Ashanti people of Ghana. Anansi is able to turn the tables on his powerful oppressors by using his cunning and trickery, a model of behaviour utilised by slaves to gain the upper hand within the confines of the plantation power structure.

Writing a web spider in python

I am well aware that there are perfectly adequate ruby crawlers available to use, such RDig or Mechanize. Since the main idea is to learn while doing something fun and interesting and the best way to learn is to sometimes do things the hard way.

I will examine all the different aspects of what makes a search engine the anatomy in a later post. In the meantime I believe doing something like this gives you an opportunity to experience first-hand all the different things you have to keep in mind when writing a search engine.

It gives you chance to learn why we do SEO the way we do; it lets you play with different ruby language features, database access, ranking algorithms, not to mention simply cut some code for the experience. And you get all this without touching Rails, nothing against Rails, but I prefer to get comfortable with Ruby by itself first.

First thing first, some basic features: For the rest, here is how it works. Firstly to run it do the following: The Spider The main worker class here is the Spider class. Crawling the web looks like this: You can also tell that we take special care to handle server side redirects.

The class also keeps the urls already visited in memory, so as to guard against us getting into loops visiting the same several pages over and over. This is not the most efficient way, obviously, and will not scale anywhere past a few thousand pages, but for our simple crawler this is fine.

We can improve this later. Crawling a domain looks like this: Everything else is pretty much the same except we take special care to only crawl links on the same domain and we no longer need to care about redirection. To get the links from the page I use Hpricot.

Here how I find all the links: There is a helper module that I created UrlUtils — yeah I know, great name: Now there are a few points that we need to note about this crawler. Some other limitations are as follows: This would be the next thing to do cause, even a simple little search engine would need some indexing.

Anyway, have a play with it if you like, and feel free to suggest improvements and point out issues or just say hello in general while I start thinking about an indexer. Images by jpctalbot and mkreyness Victor.Scrapy is a free and open source web crawling framework, written in Python.

Scrapy is useful for web scraping and extracting structured data which can be used for a wide range of useful applications, like data mining, information processing or historical archival.

Started in by the Dark Tangent, DEFCON is the world's longest running and largest underground hacking conference.

writing a web spider in python

Hackers, corporate IT professionals, and three letter government agencies all converge on Las Vegas every summer to absorb cutting edge hacking research from the most brilliant minds in the world and test their skills in contests of hacking might.

Quynh Nguyen Anh, Kuniyasu Suzaki Virt-ICE: next generation debugger for malware analysis. Dynamic malware analysis is an important method to analyze malware. The SPIDER Python Library was developed to provide functions for handling SPIDER files in your Python programs.

In particular, your scripts can read or write Spider document files in a single line. Data columns from doc files can be treated as arrays.

There are many web data extractors available for you like mozenda, nationwidesecretarial.com and etc. But if there is such a free software program that could meet your various needs, I think you would willing to have a try.

Using Python to Access Web Data from University of Michigan. This course will show how one can treat the Internet as a source of data.

We will scrape, parse, and read web data as well as access data using web APIs. We will work with HTML, XML.

Practical Introduction to Web Scraping in Python – Real Python