Rakefile

# frozen_string_literal: true
require_relative 'spec/spec_cache_retriever'
if !ENV['deployment']
  Dir["lib/tasks/machine_learning/*.rake"].each { |file| import file }
end

namespace :tmp do
  desc 'Clears all cached artifacts'
  task :clear do
    files = Dir['./tmp/**/*.*']
    FileUtils.rm(files, verbose: true)
  end
end

task :setup_processing do
  require 'colorize'
  require_relative './lib/logging'
  require 'logger'

  Logging.logger = Logger.new(STDOUT)
end

desc 'Process unprocessed bills'
task process: :setup_processing do
  process(:unprocessed, :to_process_queue) do |recognition_result, _bill, meteor|
    include Logging

    id = recognition_result.delete :id
    logger.info ["result for bill #{id}:", recognition_result].map(&:to_s)
      .map(&:yellow).join(' ')
    meteor.write_detection_result(id, recognition_result)
  end
end

desc 'Reprocess bills from older versions of the processor'
task reprocess: :setup_processing do
  process(:toReprocess, :to_reprocess_queue) do |recognition_result, _bill, meteor|
    include Logging

    id = recognition_result.delete :id
    logger.info ["result for bill #{id}:", recognition_result].map(&:to_s)
      .map(&:yellow).join(' ')
    meteor.write_detection_result(id, recognition_result)
  end
end

def process(bill_kind, queue, &bill_proc)
  require 'erb'
  require 'yaml'
  require_relative 'lib/hub'

  environment = ENV['RECOGNIZER_ENV'] || 'development'
  config_yaml = ERB.new(IO.read('config.yml')).result
  config = YAML.load(config_yaml)[environment].freeze

  hub = Hub.new(bills: bill_kind, config: config, queue: queue)
  hub.run(&bill_proc)
end