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| |_) || | / _ \    _____    / _ \ | |/ _` |/ _ \| '__| | __| '_ \| '_ ` _ \ 
|  _ < | |/ ___ \  |_____|  / ___ \| | (_| | (_) | |  | | |_| | | | | | | | |
|_| \_\|_/_/   \_\         /_/   \_\_|\__, |\___/|_|  |_|\__|_| |_|_| |_| |_|
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  Goals
  ------------
  This is an algorithmic trading platform for professional traders. It providers technical analysis of 200+ popular indicators and trading signals. You can program your trading strategies and backtest them against historical data. 
 
 Technology stack
 ----------------
 1. Flask for back-end api
    Python is known for its ease of use and best ecosystem in scientific field. It really shines when u use Numpy, Pandas and Pytables for large computational work. I see python a perfect fit in financial world.
    
  2. client-side MVC: Backbone.js and Brunch
     Node and client-side MVC framework have become popular over the recent years. so i thought of giving it a try ( which is excellent till now. ). Brunch is used for automatic compiling of coffeescript files and serve them in dev mode.
     
    
  
 How to Run:
 1. start mongodb
 
 2.
   $] cd js && brunch watch
   $] python manage.py runserver 
 
   $] open http://localhost:3000