Mining Amazon.com Catalog Data with Ruby | Linux Today

Mining Amazon.com Catalog Data with Ruby

Written By
Web Webster
Web Webster
Oct 11, 2010

“Amazon.com introduced one of the world’s first online affiliate
programs in 1996, a mere two years after the company’s founding.
The enormous popularity of the Amazon Associates Program is widely
considered to have played a significant role in the company’s early
growth. In 2002 the company launched a catalog API intended for use
in conjunction with the Associates Program called the Amazon
E-Commerce Service (later retitled the Product Advertising
API).

“Amazon’s Product Advertising API provides developers with an
interface for creating interesting new services that mine Amazon’s
enormous product catalog. Using this API, access to typical product
information such as the, price and manufacturer is just the tip of
the iceberg; it’s also possible to retrieve information about the
sales volume (via the sales rank), product reviewers, product
descriptions, related products, and much, much more.

“The popularity of this API has prompted the development of
libraries that facilitate application integration using all of the
most popular programming languages, among them PHP, Ruby, Perl and
C#. Ruby offers a particularly powerful library known as Ruby/AWS.
This library (or gem in Ruby parlance) provides an easy way to
begin programmatically perusing and mining the Amazon catalog in
every conceivable manner, a characteristic I recently came to fully
appreciate while integrating Ruby/AWS into a new project.

“In this tutorial I’ll introduce you to Ruby/AWS, showing you
how to use this great library to bend the Product Advertising API
to your will.”


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Web Webster

Web Webster

Web Webster has more than 20 years of writing and editorial experience in the tech sector. He’s written and edited news, demand generation, user-focused, and thought leadership content for business software solutions, consumer tech, and Linux Today, he edits and writes for a portfolio of tech industry news and analysis websites including webopedia.com, and DatabaseJournal.com.

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