⭐ FiveStar ⭐ is a library to build a rating system - it allows you to rate something in your domain by various classification or criteria you define. This library gives you the structure to rate your object with as many of these different classifications as you like with the overall rating calculated from the weighted average.
This gem uses Plain Old Ruby Objects so it can be used in any project.
Say you implemented a film rating system, you have lots of Film
objects each with different attributes and you would like to show an overall rating for each film based on classifications below. You might give the amount of swearing in the film slightly less weighting that the amount of sex and violence.
- Gore - Amount of blood in the movie - weighting: 40%
- Sex - Number of references to sex in the movie - weighting: 40%
- Swearing - Number of swear words in the movie - weighting: 20%
This could be implemented as follows.
class Film
include FiveStar.rateable
rate_with GoreRater, SwearingRater, SexRater
# rest of your implementation
def blood_spilt
# ...
end
def number_of_swear_words
# ...
end
end
class GoreRater < FiveStar.base_rater
rating_weight 0.4
def description
"The film #{film.title} was rated #{rating} for gore"
end
def rating
# count the pints of blood spilt in the film and return a rating
if film.blood_spilt == :a_lot
10
elsif film.blood_spilt == :a_little
5
else
0
end
end
end
class SwearingRater < FiveStar.base_rater
rating_weight 0.2
def description
"The film #{film.title} has #{film.number_of_swear_words} and was rated at #{rating}"
end
def rating
# count the number of swear words in the film & convert to our rating scale
linear_conversion(film.number_of_swear_words)
end
end
film = Film.new
film.rating # => 6.0
film.rating_descriptions # => ["The film Alien was rated 8 for gore", ...]
Add this line to your application's Gemfile:
gem 'five-star'
And then execute:
$ bundle
Or install it yourself as:
$ gem install five-star
There are two components required, the thing being rated and how it is rated - the thing you want rated is defined as being rateable and you can have one or more rating classes to give it a rating. You must implement your these raters and provide the classes to the item being rated, this library takes care of the rest.
rateable
- This is the object that can be rated - this is your domain model that has various attributes that you need rated.rater
- A class that knows how to give a rating to the object being rated based on classification of the rateable's attributes.
Each rater
must return a rating within the scale given and a weighting which will be used to calculate the overall rating.
The default rating scale used is 0 - 10 as floating point numbers although this can be overriden and customised.
The rating calculation will take the rating value from each rater along with the weighting to calculate the overall average rating.
This module when included gives the object the following interface on the instance.
rating
-@return [Float]
- The overall rating calculated for the rateable object.rating_descriptions
-@return [Array]
- A list of description from each raters. This is delegated to the rater.
The classes used to rate the object can be specified using the class method rate_with(*class_names)
and passing in one or more rating classes.
class Film
include FiveStar.rateable
rate_with GoreRater, SwearingRater, SexRater
# ...
end
film = Film.new
film.rating # => 6.0
film.rating_descriptions # => ["The film Alien was rated 8 for gore", ...]
You can create your own rating classes however you like but they should respond to the following methods;
build
-@param [Rateable], @return [instance of rater]
- Create a new instance of rater with rateable as argument.rating
-@return [Float]
- The rating for the object being rated. Calculate this by your own classification.description
-@return [String]
- A description of the rating, eg reason it was rated at that value.weighting
-@return [Float]
- The weighting for this classification. Withing range 0.0 - 1.0
The FiveStar library will call the build
method on the Rater
with the argument of the instance of class being rated which should do any setup and return an instance of the rater.
For simplicity you can subclass FiveStar.base_rater
and get the following for free. If the above methods are not overriden then the default implementation will be used.
rating_weight
-@param [Float]
- Class method to set the weighting for this raterrateable
-@return [Rateable]
- Instance method referencing the object being ratedmin_rating
-@return [Float]
- Instance method returning the minimum rating valuemax_rating
-@return [Float]
- Instance method returning the maximum rating value
For example a basic version could be something like this;
class GoreRater < FiveStar.base_rater
rating_weight 0.4
def description
"The film #{film.title} has #{film.number_of_swear_words} and was rated at #{rating}"
end
def rating
# calculate rating somehow
end
end
The calculation used will be a weighted average based on each rating and the weighting defined in that class. If weighting is not required then all will be use the default value (of 1.0) and therefore be weighted the same, this being just a normal mean average calculation.
The default rating scale used is 0 - 10 as floating point numbers although this can be customised.
After checking out the repo, run bin/setup
to install dependencies. Then, run rake spec
to run the tests. You can also run bin/console
for an interactive prompt that will allow you to experiment.
To install this gem onto your local machine, run bundle exec rake install
. To release a new version, update the version number in version.rb
, and then run bundle exec rake release
, which will create a git tag for the version, push git commits and tags, and push the .gem
file to rubygems.org.
Bug reports and pull requests are welcome on GitHub at https://github.com/rob-murray/five-star. This project is intended to be a safe, welcoming space for collaboration, and contributors are expected to adhere to the Contributor Covenant code of conduct.
The gem is available as open source under the terms of the MIT License.