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Channable is a tool for marketeers and webshop owners that connects shops to market places, affiliate platforms, and comparison websites. We download product data through a feed or API connection, clean it up using our configurable rules engine, and we send the transformed data to any platform.
In this post, we will describe our quest to create Alfred–Margaret, the fastest Haskell implementation of the Aho–Corasick string searching algorithm, which powers string search in Channable.
For small programs, where it would be a question of a few days or a few weeks to rewrite them, it will generally not be worth pondering this question for very long, and in most cases it will be better to just get started on either fixing the existing implementation or on rewriting it. For small programs it is possible…
At Channable, we process several billion product data records for our customers every day according to user-customizable rules. Internally, this work is subdivided into jobs, where one job takes a set of products and the rules for how to process them as input, and returns the transformed set of products as output…