demarches-normaliennes/app/controllers/stats_controller.rb

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class StatsController < ApplicationController
before_action :authenticate_administration!, only: [:download]
MEAN_NUMBER_OF_CHAMPS_IN_A_FORM = 24.0
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def index
procedures = Procedure.publiees_ou_archivees
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dossiers = Dossier.state_not_brouillon
@procedures_numbers = procedures_numbers(procedures)
@dossiers_numbers = dossiers_numbers(dossiers)
@satisfaction_usagers = satisfaction_usagers
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@contact_percentage = contact_percentage
@contact_percentage_excluded_tags = Helpscout::UserConversationsAdapter::EXCLUDED_TAGS
@dossiers_states = dossiers_states
@procedures_cumulative = cumulative_hash(procedures, :published_at)
@procedures_in_the_last_4_months = last_four_months_hash(procedures, :published_at)
@dossiers_cumulative = cumulative_hash(dossiers, :en_construction_at)
@dossiers_in_the_last_4_months = last_four_months_hash(dossiers, :en_construction_at)
@procedures_count_per_administrateur = procedures_count_per_administrateur(procedures)
if administration_signed_in?
@dossier_instruction_mean_time = Rails.cache.fetch("dossier_instruction_mean_time", expires_in: 1.day) do
dossier_instruction_mean_time(dossiers)
end
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@dossier_filling_mean_time = Rails.cache.fetch("dossier_filling_mean_time", expires_in: 1.day) do
dossier_filling_mean_time(dossiers)
end
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@avis_usage = avis_usage
@avis_average_answer_time = avis_average_answer_time
@avis_answer_percentages = avis_answer_percentages
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@motivation_usage_dossier = motivation_usage_dossier
@motivation_usage_procedure = motivation_usage_procedure
@cloned_from_library_procedures_ratio = cloned_from_library_procedures_ratio
end
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end
def download
headers = [
'ID du dossier',
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'ID de la démarche',
'Nom de la démarche',
'ID utilisateur',
'Etat du fichier',
'Durée en brouillon',
'Durée en construction',
'Durée en instruction'
]
data = Dossier
.includes(:procedure, :user)
.in_batches
.flat_map do |dossiers|
dossiers
.pluck(
"dossiers.id",
"procedures.id",
"procedures.libelle",
"users.id",
"dossiers.state",
"dossiers.en_construction_at - dossiers.created_at",
"dossiers.en_instruction_at - dossiers.en_construction_at",
"dossiers.processed_at - dossiers.en_instruction_at"
)
end
respond_to do |format|
format.csv { send_data(SpreadsheetArchitect.to_xlsx(headers: headers, data: data), filename: "statistiques.csv") }
end
end
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private
def procedures_numbers(procedures)
total = procedures.count
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last_30_days_count = procedures.where(published_at: 1.month.ago..Time.zone.now).count
previous_count = procedures.where(published_at: 2.months.ago..1.month.ago).count
if previous_count != 0
evolution = (((last_30_days_count.to_f / previous_count) - 1) * 100).round(0)
else
evolution = 0
end
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formatted_evolution = format("%+d", evolution)
{
total: total.to_s,
last_30_days_count: last_30_days_count.to_s,
evolution: formatted_evolution
}
end
def dossiers_numbers(dossiers)
total = dossiers.count
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last_30_days_count = dossiers.where(en_construction_at: 1.month.ago..Time.zone.now).count
previous_count = dossiers.where(en_construction_at: 2.months.ago..1.month.ago).count
if previous_count != 0
evolution = (((last_30_days_count.to_f / previous_count) - 1) * 100).round(0)
else
evolution = 0
end
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formatted_evolution = format("%+d", evolution)
{
total: total.to_s,
last_30_days_count: last_30_days_count.to_s,
evolution: formatted_evolution
}
end
def dossiers_states
{
'Brouilllon' => Dossier.state_brouillon.count,
'En construction' => Dossier.state_en_construction.count,
'En instruction' => Dossier.state_en_instruction.count,
'Terminé' => Dossier.state_termine.count
}
end
def satisfaction_usagers
legend = {
Feedback.ratings.fetch(:happy) => "Satisfaits",
Feedback.ratings.fetch(:neutral) => "Neutres",
Feedback.ratings.fetch(:unhappy) => "Mécontents"
}
number_of_weeks = 6
totals = Feedback
.group_by_week(:created_at, last: number_of_weeks, current: false)
.count
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Feedback.ratings.values.map do |rating|
data = Feedback
.where(rating: rating)
.group_by_week(:created_at, last: number_of_weeks, current: false)
.count
.map do |week, count|
total = totals[week]
# By default a week is displayed by the first day of the week but we'd rather display the last day
label = week.next_week
if total > 0
[label, (count.to_f / total * 100).round(2)]
else
[label, 0]
end
end.to_h
{
name: legend[rating],
data: data
}
end
end
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def contact_percentage
from = Date.new(2018, 1)
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to = Date.today.prev_month
adapter = Helpscout::UserConversationsAdapter.new(from, to)
if !adapter.can_fetch_reports?
return nil
end
adapter
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.reports
.map do |monthly_report|
start_date = monthly_report[:start_date].to_time.localtime
end_date = monthly_report[:end_date].to_time.localtime
replies_count = monthly_report[:conversations_count]
dossiers_count = Dossier.where(en_construction_at: start_date..end_date).count
monthly_contact_percentage = replies_count.fdiv(dossiers_count || 1) * 100
[I18n.l(start_date, format: '%b %y'), monthly_contact_percentage.round(1)]
end
end
def cloned_from_library_procedures_ratio
[3.weeks.ago, 2.weeks.ago, 1.week.ago].map do |date|
min_date = date.beginning_of_week
max_date = min_date.end_of_week
all_procedures = Procedure.created_during(min_date..max_date)
cloned_from_library_procedures = all_procedures.cloned_from_library
denominator = [1, all_procedures.count].max
ratio = percentage(cloned_from_library_procedures.count, denominator)
[l(max_date, format: '%d/%m/%Y'), ratio]
end
end
def max_date
if administration_signed_in?
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Time.zone.now.to_date
else
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Time.zone.now.beginning_of_month - 1.second
end
end
def last_four_months_hash(association, date_attribute)
min_date = 3.months.ago.beginning_of_month.to_date
association
.where(date_attribute => min_date..max_date)
.group("DATE_TRUNC('month', #{date_attribute})")
.count
.to_a
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.sort_by { |a| a[0] }
.map { |e| [I18n.l(e.first, format: "%B %Y"), e.last] }
end
def cumulative_hash(association, date_attribute)
sum = 0
association
.where("#{date_attribute} < ?", max_date)
.group("DATE_TRUNC('month', #{date_attribute})")
.count
.to_a
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.sort_by { |a| a[0] }
.map { |x, y| { x => (sum += y) } }
.reduce({}, :merge)
end
def procedures_count_per_administrateur(procedures)
count_per_administrateur = procedures.group(:administrateur_id).count.values
{
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'Une démarche' => count_per_administrateur.select { |count| count == 1 }.count,
'Entre deux et cinq démarches' => count_per_administrateur.select { |count| count.in?(2..5) }.count,
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'Plus de cinq démarches' => count_per_administrateur.select { |count| count > 5 }.count
}
end
def mean(collection)
(collection.sum.to_f / collection.size).round(2)
end
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def percentage(numerator, denominator)
((numerator.to_f / denominator) * 100).round(2)
end
def dossier_instruction_mean_time(dossiers)
# In the 12 last months, we compute for each month
# the average time it took to instruct a dossier
# We compute monthly averages by first making an average per procedure
# and then computing the average for all the procedures
min_date = 11.months.ago
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max_date = Time.zone.now.to_date
processed_dossiers = dossiers
.where(:processed_at => min_date..max_date)
.pluck(:procedure_id, :en_construction_at, :processed_at)
# Group dossiers by month
processed_dossiers_by_month = processed_dossiers
.group_by do |dossier|
dossier[2].beginning_of_month.to_s
end
processed_dossiers_by_month.map do |month, value|
# Group the dossiers for this month by procedure
dossiers_grouped_by_procedure = value.group_by { |dossier| dossier[0] }
# Compute the mean time for this procedure
procedure_processing_times = dossiers_grouped_by_procedure.map do |_procedure_id, procedure_dossiers|
procedure_dossiers_processing_time = procedure_dossiers.map do |dossier|
(dossier[2] - dossier[1]).to_f / (3600 * 24)
end
mean(procedure_dossiers_processing_time)
end
# Compute the average mean time for all the procedures of this month
month_average = mean(procedure_processing_times)
[month, month_average]
end.to_h
end
def dossier_filling_mean_time(dossiers)
# In the 12 last months, we compute for each month
# the average time it took to fill a dossier
# We compute monthly averages by first making an average per procedure
# and then computing the average for all the procedures
# For each procedure, we normalize the data: the time is calculated
# for a 24 champs form (the current form mean length)
min_date = 11.months.ago
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max_date = Time.zone.now.to_date
processed_dossiers = dossiers
.where(:processed_at => min_date..max_date)
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.pluck(
:procedure_id,
Arel.sql('EXTRACT(EPOCH FROM (en_construction_at - created_at)) / 60 AS processing_time'),
:processed_at
)
# Group dossiers by month
processed_dossiers_by_month = processed_dossiers
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.group_by do |(*_, processed_at)|
processed_at.beginning_of_month.to_s
end
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procedure_id_type_de_champs_count = TypeDeChamp
.where(private: false)
.group(:procedure_id)
.count
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processed_dossiers_by_month.map do |month, dossier_plucks|
# Group the dossiers for this month by procedure
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dossiers_grouped_by_procedure = dossier_plucks.group_by { |(procedure_id, *_)| procedure_id }
# Compute the mean time for this procedure
procedure_processing_times = dossiers_grouped_by_procedure.map do |procedure_id, procedure_dossiers|
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procedure_fields_count = procedure_id_type_de_champs_count[procedure_id]
if (procedure_fields_count == 0 || procedure_fields_count.nil?)
next
end
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procedure_dossiers_processing_time = procedure_dossiers.map { |_, processing_time, _| processing_time }
procedure_mean = mean(procedure_dossiers_processing_time)
# We normalize the data for 24 fields
procedure_mean * (MEAN_NUMBER_OF_CHAMPS_IN_A_FORM / procedure_fields_count)
end
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.compact
# Compute the average mean time for all the procedures of this month
month_average = mean(procedure_processing_times)
[month, month_average]
end.to_h
end
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def avis_usage
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[3.weeks.ago, 2.weeks.ago, 1.week.ago].map do |min_date|
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max_date = min_date + 1.week
weekly_dossiers = Dossier.includes(:avis).where(created_at: min_date..max_date).to_a
weekly_dossiers_count = weekly_dossiers.count
if weekly_dossiers_count == 0
result = 0
else
weekly_dossier_with_avis_count = weekly_dossiers.select { |dossier| dossier.avis.present? }.count
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result = percentage(weekly_dossier_with_avis_count, weekly_dossiers_count)
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end
[min_date.to_i, result]
end
end
def avis_average_answer_time
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[3.weeks.ago, 2.weeks.ago, 1.week.ago].map do |min_date|
max_date = min_date + 1.week
average = Avis.with_answer
.where(created_at: min_date..max_date)
.average("EXTRACT(EPOCH FROM avis.updated_at - avis.created_at) / 86400")
result = average ? average.to_f.round(2) : 0
[min_date.to_i, result]
end
end
def avis_answer_percentages
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[3.weeks.ago, 2.weeks.ago, 1.week.ago].map do |min_date|
max_date = min_date + 1.week
weekly_avis = Avis.where(created_at: min_date..max_date)
weekly_avis_count = weekly_avis.count
if weekly_avis_count == 0
[min_date.to_i, 0]
else
answered_weekly_avis_count = weekly_avis.with_answer.count
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result = percentage(answered_weekly_avis_count, weekly_avis_count)
[min_date.to_i, result]
end
end
end
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def motivation_usage_dossier
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[3.weeks.ago, 2.weeks.ago, 1.week.ago].map do |date|
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min_date = date.beginning_of_week
max_date = date.end_of_week
weekly_termine_dossiers = Dossier.where(processed_at: min_date..max_date)
weekly_termine_dossiers_count = weekly_termine_dossiers.count
weekly_termine_dossiers_with_motivation_count = weekly_termine_dossiers.where.not(motivation: nil).count
if weekly_termine_dossiers_count == 0
result = 0
else
result = percentage(weekly_termine_dossiers_with_motivation_count, weekly_termine_dossiers_count)
end
[l(max_date, format: '%d/%m/%Y'), result]
end
end
def motivation_usage_procedure
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[3.weeks.ago, 2.weeks.ago, 1.week.ago].map do |date|
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min_date = date.beginning_of_week
max_date = date.end_of_week
procedures_with_dossier_processed_this_week = Procedure
.joins(:dossiers)
.where(dossiers: { processed_at: min_date..max_date })
procedures_with_dossier_processed_this_week_count = procedures_with_dossier_processed_this_week
.uniq
.count
procedures_with_dossier_processed_this_week_and_with_motivation_count = procedures_with_dossier_processed_this_week
.where
.not(dossiers: { motivation: nil })
.uniq
.count
if procedures_with_dossier_processed_this_week_count == 0
result = 0
else
result = percentage(procedures_with_dossier_processed_this_week_and_with_motivation_count, procedures_with_dossier_processed_this_week_count)
end
[l(max_date, format: '%d/%m/%Y'), result]
end
end
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end