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Azin Azadi's Projects

active_merchant icon active_merchant

Active Merchant is a simple payment abstraction library extracted from Shopify. The aim of the project is to feel natural to Ruby users and to abstract as many parts as possible away from the user to offer a consistent interface across all supported gateways.

acts-as-taggable-on icon acts-as-taggable-on

A tagging plugin for Rails applications that allows for custom tagging along dynamic contexts.

fitvids.js icon fitvids.js

A lightweight, easy-to-use jQuery plugin for fluid width video embeds.

jquery-tokeninput icon jquery-tokeninput

Tokeninput is a jQuery plugin which allows your users to select multiple items from a predefined list, using autocompletion as they type to find each item. You may have seen a similar type of text entry when filling in the recipients field sending messages on facebook.

music-organizer icon music-organizer

this program re-orders your music files (mp3s) in a nice directory structure according to their artist, album and track number

nanoc-template icon nanoc-template

A simple template project for websites built with Nanoc. My fork is designed to work with SLIM.

pngqr icon pngqr

Pure Ruby Gem to generate PNG files of QR codes

rails-simple-cms icon rails-simple-cms

A simple cms based on rails, with Inline editing for any field. make it no need for an admin backend.

rich icon rich

Rich is an opinionated WYSIWYG editor (based on CKEditor) for Rails with flexible image uploads (using Paperclip).

sleek icon sleek

:chart_with_upwards_trend: Sleek is a modern Jekyll theme focused on speed performance & SEO best practices

spree icon spree

Spree is a complete open source e-commerce solution for Ruby on Rails.

tripnet icon tripnet

TripNet is an algorithm for constructing phylogenetic networks from sparse sets of rooted triplets. TripNet is a word made of Triplet and Network. This algorithm provides a new method for creating phylogenetic networks from triplets. The importance of this algorithm is that there isn’t any known algorithm for creating phylogenetic networks from sparse triplet datasets. It also introduces a heuristic method for doing this. Currently known non-heuristic methods are often very slow and thus can’t work on medium and large size networks. This new algorithm may produce networks with slightly higher level, but it works faster on larger networks, and also works for sparse datasets. (Having biological data, it is common to have 3 incomparable species, so sparse data sets are unavoidable.)

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