R/app_server.R

In piotrgruszecki/sw.dashboard: Sellwerk Dashboard

#' The application server-side
#'
#' @param input,output,session Internal parameters for {shiny}.
#'     DO NOT REMOVE.
#' @import shiny
#' @import R6
#' @noRd
app_server <- function( input, output, session ) {
  # Your application server logic

    #-- 0. read config file
    if (!exists("config")) config <<- config::get(file = app_sys("golem-config.yml"), use_parent = TRUE)

    #-- 1. data
    #-- 1.1 initiate R6 object
    AwsBuffer <- R6Class(classname = "Buffer", list(

        raw_dt = 0,                         # full data.table, input data
        migrated_dt = 0,                    # user_logged == "production : DE : logged in" & migrated =="true"
        time_dt = 0,                        # subset of columns: user_id, session_id, timestamp

        sessions_enriched_dt = 0,           # parsing info to get company nam, id, address, zip

        cohort_users_dt = 0,                # user_id's of users assigned to a cohort
        cohort_sessions_dt = 0,             # session_id's assigned to a cohort

        sunburst_sessions_dt = 0,

        pull_leads    = function(dates_range) {2 + 2},
        pull_profiles = function(dates_range) {3 + 3}
    ))

    aws_buffer <- AwsBuffer$new()

    #-- 1.1 for now, from Rds file
    aws_buffer$raw_dt  <- readRDS(config$data_file)

    #-- 1.2 trim to logged and migrated
    aws_buffer$migrated_dt <-  aws_buffer$raw_dt[user_logged == "production : DE : logged in" & migrated =="true", ]

    #-- 1.3 subset of columns
    aws_buffer$time_dt <- aws_buffer$migrated_dt[, .(user_id, session_id, timestamp)]

    #-- 1.3 enrich sessions; we do it for the whole dataset, which might look redundatnt, but we do that only once, and will not recalculate each time a new cohort is selected
    enrich_sessions(aws_buffer)


    #-- 2. run modules
    mod_cohort_server("cohort_ui_1", aws_buffer)

}