inst/application/helpers/process_upload_data_demo.R

In Samantha-Lui/EZRecords: Easy Bookkeeping and Stock Management for Retails

# Demonstration of the process_upload_data function which behaves the same as the original function except for
# the restriction of the scope of the saved data to only the current session.
process_upload_data.demo <- function(data, append = TRUE, 
                                     ex_prod_skel, ex_prod_log, ex_other_skel, ex_other_log,
                                     xps_fname = 'ps.Rds', xpl_fname = 'pl.Rds', xos_fname = 'os.Rds', xol_fname = 'ol.Rds'){
  if(nrow(data) == 0)
    return(list(ex_prod_skel, ex_prod_log, ex_other_skel, ex_other_log, character(0)))
  names(data) <- tolower(names(data))
  data$id <- 1:nrow(data); duplicate_rows <- c()
  data$date <- as.Date(data$date, date_format(data$date[1]))
  data$sample <- ifelse(grepl('no', data$sample, ignore.case = TRUE), 'No', 'Yes')
  data$sampling <- ifelse(grepl('no', data$sampling, ignore.case = TRUE), 'No', 'Yes')
  data$transac <- tolower(data$transac)
  data$code <- paste(data$supplier_customer, data$order_no, data$date)
  data <- data[with(data, order(code)), ]
  prod <- subset(data, transac %in% c('sale', 'purchase'))
  other <- subset(data, transac == 'other')
  # Check if any of the uploaded entries have already existed in the database
  # if the uploaded data is opted to append to the existing data.
  # The duplicate rows will be ignored in the process.
  rows_already_existed <- '<font size=\'4\', color=\"#42d162\"><b>Uploaded data has been successfully processed.</b></font>'
  if(append){
    duplicate_prod <- prod$id[duplicate_records(ex_prod_log, prod$date, prod$order_no, prod$supplier_customer)]
    duplicate_other <- other$id[duplicate_records(ex_other_log, other$date, other$order_no, other$supplier_customer)]
    d <- sort(c(duplicate_prod, duplicate_other))
    if(!identical(d, integer(0))){
      rows_already_existed <- paste('<font size=\'4\', color=\"#C65555\"><b>', 'Row(s):', paste(d, collapse=', '), 
                                    'already existed in the database and was/were ignored.', '</b></font>')
      data <- subset(data, ! id %in% d)
    }
    data$id <- NULL
    prod <- subset(data, transac %in% c('sale', 'purchase'))
    other <- subset(data, transac == 'other')
  }
  # This block processes uploaded data of sales and purchases.
  pl <- new('product_logs')
  skeleton_prod <- data.frame()
  for(code in unique(prod$code)){
    p <- prod[prod$code == code, ]
    pt <- new('product_transac')
    pt@date <- unique(p$date)
    pt@transac <- unique(ifelse(p$transac=='sale', 'credit', 'debit'))
    pt@category <- unique(p$transac)
    pt@supplier_customer <- unique(p$supplier_customer)
    pt@order_no <- unique(p$order_no)
    pt@shipment <- unique(p$shipment)
    pt@tax <- unique(p$tax)
    ai <- new('all_items')
    for(i in 1:nrow(p)){
      item <- new('single_item')
      item@category <- p$category[i]
      item@descrp <- p$descrp[i]
      item@model <- p$model[i]
      item@quant <- p$quant[i]
      item@price <- p$price[i]
      item@discount <- p$discount[i]
      item@amount <- amount(item)
      item@sample <- p$sample[i]
      item@sampling <- p$sampling[i]
      ai <- add(ai, item)
      df <- data.frame(supplier=pt@supplier_customer, 
                       model=p$model[i],  
                       mcat=p$mcat[i],            
                       category=p$category[i],
                       descrp=p$descrp[i],
                       stringsAsFactors = FALSE)
      skeleton_prod <- rbind(df, skeleton_prod, stringsAsFactors = FALSE)
    }
    pt@descrp <- ai
    pt@value <- amount(pt@descrp)
    pt@total <- sum(pt@value, pt@shipment, pt@tax)
    pt@time_stamp <- Sys.time()
    pl <- add(pl, pt)
  }
  # This block processes uploaded data of transactions other than sale and purchase.
  ol <- new('product_logs')
  skeleton_other <- data.frame()
  for(code in unique(other$code)){
    o <- other[other$code == code, ]
    ot <- new('product_transac')
    ot@date <- unique(o$date)
    ot@transac <- 'debit'
    ot@category <- unique(o$transac)
    ot@supplier_customer <- unique(o$supplier_customer)
    ot@order_no <- unique(o$order_no)
    ot@shipment <- unique(o$shipment)
    ot@tax <- unique(o$tax)
    ai <- new('all_items')
    for(i in 1:nrow(o)){
      item <- new('single_item')
      item@category <- o$category[i]
      item@descrp <- o$descrp[i]
      item@model <- o$model[i]
      item@quant <- o$quant[i]
      item@price <- o$price[i]
      item@discount <- o$discount[i]
      item@amount <- amount(item)
      item@sample <- o$sample[i]
      item@sampling <- o$sampling[i]
      ai <- add(ai, item)
      df <- data.frame(supplier_customer=ot@supplier_customer, 
                       model=o$model[i],  
                       category=o$category[i],
                       stringsAsFactors = FALSE)
      skeleton_other <- rbind(df, skeleton_other, stringsAsFactors = FALSE)
    }
    ot@descrp <- ai
    ot@value <- amount(ot@descrp)
    ot@total <- sum(ot@value, ot@shipment, ot@tax)
    ot@time_stamp <- Sys.time()
    ol <- add(ol, ot)
  }
  # Append the uploaded data to the database
  if(append){
    pl <- join(ex_prod_log, pl)
    skeleton_prod <- unique(rbind(skeleton_prod, ex_prod_skel, stringsAsFactors = FALSE))
    ol <- join(ex_other_log, ol)
    skeleton_other <- unique(rbind(skeleton_other, ex_other_skel, stringsAsFactors = FALSE))
  }
  
  ## Commented for demo
  # # Save results to the files
  # saveRDS(skeleton_prod, file = xps_fname)
  # saveRDS(pl, file = xpl_fname)
  # saveRDS(skeleton_other, file = xos_fname)
  # saveRDS(ol, file = xol_fname)
  
  # Return results to continue calulations in the app
  results <- list(skeleton_prod, pl, skeleton_other, ol, rows_already_existed)
  return(results)
}