# Load required libraries
library(shiny)
library(readxl)
library(tidyverse)
library(stringr)
library(openxlsx)


# Define the timeout period in seconds
timeoutSeconds <- 1200

# Create the JavaScript code to handle user inactivity
inactivity <- sprintf("
function idleTimer() {
    var t;
    var timeout = %s * 1000; // Convert seconds to milliseconds

    // Events that reset the timer
    var events = ['mousemove', 'mousedown', 'click', 'scroll', 'keypress'];

    // Function to log out and notify the user
    function logout() {
        alert('You have been disconnected due to inactivity. Refresh your browser to use the webapp again. - Dr. Eduardo');
        Shiny.setInputValue('timeOut', '%s');
    }

    // Function to reset the timer
    function resetTimer() {
        clearTimeout(t);
        t = setTimeout(logout, timeout);
    }

    // Attach resetTimer to each event
    events.forEach(function(event) {
        window.addEventListener(event, resetTimer);
    });

    // Initialize the timer
    t = setTimeout(logout, timeout);
}

// Initialize the idle timer when the document is ready
document.addEventListener('DOMContentLoaded', function() {
    idleTimer();
});
", timeoutSeconds, timeoutSeconds)


#####
read_and_preprocess <- function(path, filename) {
  df <- read_excel(path)
  
  # Remove columns with entirely NA entries
  df <- df[, colSums(is.na(df)) != nrow(df), drop = FALSE]
  
  columns_selected <- c("ID number", "Last name", "Time taken", "State", "Grade/5.00")
  new_column_names <- c("ID_Number", "Last_Name", "Time_Taken", "State", "Grade")
  
  # Select and rename columns
  df <- df[, columns_selected, drop = FALSE]
  colnames(df) <- new_column_names
  
  # Convert Grade to numeric and Last_Name to title case
  df$Grade <- as.numeric(df$Grade)
  df$Last_Name <- str_to_title(df$Last_Name)
  
  # Remove rows with missing values
  df <- df[complete.cases(df), ]
  
  return(df)
}

# Function to calculate additional columns
calculate_additional_columns <- function(df, attempted, filename) {
  avg_col_name <- paste("Average", filename, sep = "_")
  
  df <- df %>%
    group_by(ID_Number) %>%
    mutate(nAttempt = n(),
           !!avg_col_name := ifelse(nAttempt >= attempted,
                                    round(mean(sort(Grade, decreasing = TRUE)[1:attempted]),0),
                                    round(sum(Grade) / attempted))) %>%
    distinct(ID_Number, .keep_all = TRUE)
  
  return(df)
}
#####



# Define UI
ui <- fluidPage(
  #tags$script(HTML(inactivity)),
  titlePanel(
    h4("UTAS - Online Marks Aggregator"),
    windowTitle = "Marks Aggregator"
  ),
  
  sidebarLayout(
    sidebarPanel(
      numericInput(
        "attempt",
        "Min Number of Attempts",
        value = 1, min = 1, max = 10, step = 1
      ),
      
      fileInput(
        "files",
        "Upload Excel file(s)",
        accept = c(".xlsx"),
        multiple = TRUE,
        placeholder = "Please select excel file/s"
      ),
      
      helpText("Upload only Excel files with .XLSX extension to ensure consistency."),
      br(),
      downloadButton("downloadData", "Download"),
      hr(),
      
      div(
        class = "fluent-footer",
        div(
          class = "fluent-footer-legal",
          div(
            class = "fluent-footer-legal-left",
            a("Privacy Policy", href = "#"),
            " | ",
            a("Terms of Use", href = "#")
          ),
          div(
            class = "fluent-footer-legal-right",
            "© 2023 College of Computing and Information Sciences"
          )
        )
      ),
      
      tags$footer(
        style = "text-align: left; padding-top: 10px; font-size: 12px;",
        "Built by ",
        tags$a(href = "https://www.google.com/search?q=dr.+eduardo+lacap+jr&sca_esv=4136c3af1df3852c&sca_upv=1&sxsrf=ADLYWIIeq7fb1cWKSiyieFVwGRe7qJ40NA%3A1716361100562&ei=jJdNZqHvIZbeseMPj4O8sAs&oq=dr.+eduardo+lacap&gs_lp=Egxnd3Mtd2l6LXNlcnAiEWRyLiBlZHVhcmRvIGxhY2FwKgIIATIHECMYsAMYJzIHECMYsAMYJzILEAAYgAQYsAMYogQyCxAAGIAEGLADGKIEMgsQABiwAxiiBBiJBTILEAAYgAQYsAMYogRIuA1QAFgAcAF4AJABAJgBAKABAKoBALgBAcgBAJgCAaACBJgDAIgGAZAGBpIHATGgBwA&sclient=gws-wiz-serp", "Dr. Eduardo M. Lacap, Jr.")
      )
    ),
    
    mainPanel(
      tableOutput("table")
    )
  )
)


# Define server logic
server <- function(input, output, session) {
  
  # Reactive expression for the number of attempts
  attempted <- reactive({ input$attempt })
  
  # Reactive expression for the nature of the files uploaded
  
  independnt <- reactive({input$independent})
  
  # Reactive expression to read and combine uploaded Excel files
  combined_df <- reactive({
    req(input$files$datapath)  # Ensure files are uploaded
    
    df_list <- mapply(function(path, name) {
      df <- read_and_preprocess(path, tools::file_path_sans_ext(basename(name)))
      df <- calculate_additional_columns(df, attempted(), tools::file_path_sans_ext(basename(name)))
      return(df)
    }, input$files$datapath, input$files$name, SIMPLIFY = FALSE)
    
    combined_df <- bind_rows(df_list)
    
    combined_df <- if (length(df_list) == 1) {
      df_list[[1]] %>% 
        select(ID_Number, Last_Name, starts_with("Average"))
    } else {
          as.data.frame(combined_df) %>%
          select(ID_Number, Last_Name, starts_with("Average")) %>% 
          pivot_longer(cols = starts_with("Average_"), names_to = "Average_Type", values_to = "Average_Value") %>%
          filter(!is.na(Average_Value)) %>%
          pivot_wider(names_from = "Average_Type", values_from = "Average_Value") %>% 
          mutate_at(., vars(starts_with("Average_")), ~replace(., is.na(.), 0), values_fn = list) %>%  
          mutate(Marks = round(rowMeans(select(., starts_with("Average_")), na.rm = TRUE)+0.1,0))
      }
    return(combined_df)
  })
  
  
  # Display combined data as a table
  output$table <- renderTable({
    combined_df()
  })
  
  # Download combined data
  output$downloadData <- downloadHandler(
    filename = function() {
      paste("MarksAggregated_", attempted(), "_MinAttempt.xlsx", sep = "")
    },
    content = function(file) {
      write.xlsx(combined_df(), file)
    }
  )
}


# Run the application
shinyApp(ui = ui, server = server)