ActsAsMongoRateable (with weights!)
Inspired by the old Rails+AR standby "acts_as_rateable," this rating plugin works with MongoDB+MongoMapper and has weighted ratings, as well as bayesian and straight averages, and some friendly class-level helpers.
Intends to be super-performant by taking advantage of the benefits of document-driven db denormalization.
- MongoMapper gem
- Expects you to have a User model that includes MongoMapper::Document
Install the plugin:
./script/plugin install git://github.com/mepatterson/acts_as_mongo_rateable.git
Add the following 2 lines to the Model class that you want to make rateable:
include ActsAsMongoRateable RATING_RANGE = (1..5)
Obviously, change the rating range if you want to rate on a 10-star system or a 14-star or whatever.
class User include MongoMapper::Document end class Widget include ActsAsMongoRateable RATING_RANGE = (1..5) include MongoMapper::Document end widget = Widget.first
To rate it:
widget.rate(score, user, weight)
- score must be an Integer within your RATING_RANGE
- user is the User who is rating this widget
- weight is optional; defaults to 1)
Now try all these fun methods:
widget.average_rating widget.bayesian_rating widget.rating_stats
And some useful class methods:
Widget.highest_rated(how_many) Widget.most_rated(how_many) Widget.most_rated_by_authorities(how_many) Widget.highest_bayesian_rated(how_many)
('how_many' is a limit and is optional. i.e. Do you want a highest_rated list of 5, 10, 15 widgets?
Defaults to just 1 if you don't pass any argument.)
- Tests (I have tests in the project I cut this from, but they need to be extracted out and I'm lazy)
- More helper methods
- Performance improvements as I come across the need
- Investigate using map/reduce to improve the efficiency of the bayesian calc (?)
- John Nunemaker and the rest of the folks on the MongoMapper Google Group
- The MongoDB peoples and the MongoDB Google Group
- juixe for the original acts_as_rateable plugin for ActiveRecord
- sunlightlabs 'datacatalog-api', from which I borrowed the ratings_stats hash methodology
Copyright (c) 2009 [M. E. Patterson], released under the MIT license