perf analysis script

analysis.rb

class PerformanceReportRow
  include ActiveModel::Model
  ATTRIBUTES = %w(bids wins impressions clicks conversions buying_price cost app_opens profit)

  attr_accessor *ATTRIBUTES

  def initialize(attributes = {})
    ATTRIBUTES.each do |attr|
      self.send("#{attr}=", 0)
    end
    super(attributes)
  end

  def +(other)
    ATTRIBUTES.each do |attr|
      self.send("#{attr}=", self.send(attr) + other.send(attr))
    end
    return self
  end

  def compare_to(other)
    result = {}
    ATTRIBUTES.each do |attr|
      change_factor = self.send(attr).to_f / other.send(attr).to_f
      change_in_percent = (change_factor -1)*100.0
      puts "#{attr}: #{fi other.send(attr)}->#{fi self.send(attr)} #{change_in_percent.round(2)} %"
    end
    puts "margin: #{other.margin.round(2)}->#{self.margin.round(2)} %"
    puts "cr: #{other.cr.round(2)}->#{self.cr.round(2)} %"
    return result
  end


  def fi(i)
    i.to_s
  end

  def profit
    self.buying_price - self.cost
  end

  def margin
    1 - (self.cost.to_f/self.buying_price.to_f)
  end

  def cr
    self.conversions.to_f / self.clicks.to_f
  end

end

class PerformanceReport
  include ActiveModel::Model

  attr_accessor :org_ids, :start_date, :end_date

  def run
    r = SimpleReport.new()
    r.query = query()
    r.run()
    @result = r.result
  end

  def total
    total = PerformanceReportRow.new()
    @result.map do |r|
      puts "row", r
      total = total + PerformanceReportRow.new(r["event"])
    end
    return total
  end

  def query
    query =  {
      dataSource: 'bids',
      queryType: 'groupBy',
      granularity: 'all',
      intervals: ["#{@start_date}/#{@end_date}"],
      aggregations: [
        { type: 'longSum', name: 'bids', fieldName: 'bids' },
        { type: 'longSum', name: 'wins', fieldName: 'wins' },
        { type: 'longSum', name: 'impressions', fieldName: 'impressions' },
        { type: 'longSum', name: 'clicks', fieldName: 'clicks' },
        { type: 'longSum', name: 'buying_price', fieldName: 'buying_price_eur' },
        { type: 'longSum', name: 'cost', fieldName: 'win_price_eur' },
        { type: 'longSum', name: 'conversions', fieldName: 'conversions' },
        { type: 'longSum', name: 'app_opens', fieldName: 'app_opens' },
      ],
      postAggregations: [ ],
      filter: Druid::BooleanFilter.new(type: 'or', fields: add_orglist_filter),
    }
  end

  def add_orglist_filter
    @org_ids.map { |org_id| { type: 'selector', dimension: 'organization', value: org_id } }
  end

end

default_before = {
  start_date: "2016-03-19",
  end_date: "2016-03-21"
}
default_after = {
  start_date: "2016-04-16",
  end_date: "2016-04-18"
}
default_dates = [default_before, default_after ]

orgs_and_dates = {
  default_dates => [
    # ACTIVE in default dates:
    # ORG ID, ORG NAME, SWITCH DATES:
    10, #HelloFood, 2016-04-01, 2016-04-13
    176, #Talabat, 2016-04-01
    26, #Lieferheld, 2016-03-29, 2016-04-05
    34, # Die Welt, 2016-03-24
    35,# pizza.de, 2016-04-01
    41,#  Delivery Club, 2016-03-24
    43,#  Zalora, 2016-04-01, 2016-04-17
    97,#  Doubledown Interactive, 2016-03-29
    175,# # CJMall, 2016-04-06, 2016-04-13, 2016-04-15
    5, #Funstage, 2016-03-24, 2016-04-11
    53,#  CBS Interactive, 2016-03-30
    67,# LaModa, 2016-04-01
    7,#  KaufDa, 2016-04-04, 2016-04-17
    149,#  Gilt, 2016-04-05
    183,#  MachineZone, 2016-04-05
    19,#  Aviasales, 2016-04-05, 2016-04-06
    47,#  wego, 2016-04-05
    86, #Xyrality, 2016-04-05
    54,#  Product Madness, 2016-04-05
    94,#  Foodora, 2016-04-05, 2016-04-12
    92,#  Kama Games, 2016-04-05
    74,#  Bravofly, 2016-04-05
    127,# Linio, 2016-04-05
    129,#  NetShoes, 2016-04-05
    143,#  Electronic Arts, 2016-04-06
    158,#  Yoshirt, 2016-04-06
    145,#  Ponos US, 2016-04-06
    142,#  AGS RocketPlay, 2016-04-06
    159,#  Jump Ramp Games, 2016-04-06
    16,#  GSN Games, 2016-04-06
    91,#  Redmart, 2016-04-06
    104,#  Dena, 2016-04-06
    122,#  ATeam, 2016-04-06
    123,#  Clover Lab.,inc., 2016-04-06
    134,#  Rocket Games, 2016-04-06
    154,#  Seatgeek, 2016-04-08, 2016-04-15
    117,#  Konami, 2016-04-12
    138,#  Storm8, 2016-04-17

    # QUESTION IF TO INCLUDE?
    8,#  ??? HRS, 2016-04-05, slowed down?
    9, # ??? Foodpanda, 2016-03-24, 2016-04-05, 2016-04-13, slowed down?
    21,# ??? Game Insight, 2016-04-05, slowed down?

    # BLACKLISTED for various reasons
    # 171,#  Retailmenot, 2016-03-31, stopped on 2016-04-02
    # 148, Otlob, 2016-04-01, was not running before
    #55, Yemeksepeti, 2016-04-01, was not running before
    # 128, Knip, 2016-04-01, # Knip stopped on 2016-04-12
    # 102, One Two Trip, 2016-04-05, Did not have significant scale before 2016-04-12
    # 156, G5 Games, 2016-04-06, stopped after 2016-04-11
    # 161, Ponos JP, 2016-04-06, stopped after 2016-04-11
    # 136, PeixeUrbano, 2016-04-06, 2016-04-17, did not run until 2016-04-06
    # 192, TodayTix, 2016-04-07, did not run until 2016-04-08
    # 15, GameSys, 2016-04-07, did not run until 2016-04-12
    # 165, Hailo, 2016-04-08, did not run until 2016-04-12
  ],

  [{
    start_date: "2016-03-26",
    end_date: "2016-03-28"
  }, default_after] => [
    101,#  Gumi, 2016-04-04
    85,# Innogames, 2016-03-31
  ],

  [{
    start_date: "2016-04-02",
    end_date: "2016-04-04"
  }, default_after] => [
    33, #PedidosYa, 2016-04-05
  ],

}

# empty results
before_result = PerformanceReportRow.new()
after_result = PerformanceReportRow.new()

orgs_and_dates.each do |dates, org_ids|
  before, after = dates

  r_before = PerformanceReport.new(
    { org_ids:  org_ids }.merge(before)
  )
  r_before.run
  before_result += r_before.total

  r_after = PerformanceReport.new(
    { org_ids:  org_ids }.merge(after)
  )
  r_after.run
  after_result += r_after.total
end

diff = after_result.compare_to(before_result)