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Validate associated models, and aggregate their errors onto the primary model

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AlsoValidates

An ActiveModel validator that validates associated models, copying any errors from composed models up to their parent.

Installation

Add this line to your application's Gemfile:

gem 'also_validates'

And then execute:

$ bundle

Or install it yourself as:

$ gem install also_validates

Usage

Given existing models with their own validations:

class Beer
  include ActiveModel::Validations
  attr_accessor :hops
  validates_presence_of :hops

  def initialize(attrs = {})
    @hops = attrs[:hops]
  end
end

class Belly
  include ActiveModel::Validations
  attr_accessor :button
  validates_presence_of :button

  def initialize(attrs = {})
    @button = attrs[:button]
  end
end

And you need a model that composes those models:

class MonsterTruckRally
  include ActiveModel::Validations

  attr_accessor :beer, :belly, :truck_count

  validates_presence_of :truck_count
  also_validates :beer, :belly

  def initialize(attrs = {})
    @beer = attrs[:beer]
    @belly = attrs[:belly]
    @truck_count = attrs[:truck_count]
  end
end

Calling valid? on an instance of monster truck rally, will run validations on both the monster truck rally as well as any models specified by also_validates. If there are any validation errors on the composed model, they are copied up (to the "base") of the parent model (in this case a MonsterTruckRally).

Note: Currently does not pass the attribute information (the field of the composed model) along to its parent. Errors are added to "base".

Only supported option currently is allow_nil: true:

also_validates :beer, :belly, allow_nil: true

Which, as the option states, allows nil values and will not attempt to validate those models.

Contributing

  1. Fork it
  2. Create your feature branch (git checkout -b my-new-feature)
  3. Commit your changes (git commit -am 'Added some feature')
  4. Push to the branch (git push origin my-new-feature)
  5. Create new Pull Request

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Validate associated models, and aggregate their errors onto the primary model

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