问我如何密码保护一个发亮的应用程序？+命名空间错误

EN

library(shiny)
library(data.table)
library(DT)
library(ggpubr)
library(ggrepel)
library(ggplot2)



# create random data
Total <- rnorm(10, 30, 5)
Yrs <- rnorm(10, 10, 7)
Level <-c("Senior Project Manager", "PM (Border Senior PM)",
          "Project Manager", "Senior Project Manager","PM (Border Senior PM)", 
          "PM (Border Senior PM)","Project Manager","Project Manager",
          "Project Manager","Senior Project Manager")
Modality <- c("Small Molecules", "Biologics",
              "Both","Both","Both","Biologics","Small Molecules","Small Molecules",
              "Biologics","Biologics")
ID <- 1:10
pm <- data.frame(ID,Modality,Level,Yrs,Total)

server <- function(input, output) {
  # # choose columns to display
  output$mytable1 <- DT::renderDataTable({
    # delete ID column
    pm$ID <-NULL
    DT::datatable(pm[, input$show_vars, drop = FALSE])
    if (input$Level != 'Not Relevant') {
      pm <-pm[ which(pm$Level==as.character(input$Level)),] 
    }
    else {
      pm <- pm}
    if (input$Modality != 'Not Relevant') {
      pm <-pm[ which(pm$Modality==as.character(input$Modality)),] 
          }
    else
    {
       pm 
    }

  })
  #create scatterplot
  output$scatter <- renderPlot({

    pm$Level <- factor(pm$Level, levels = c("Senior Project Manager", "PM (Border Senior PM)",
                                            "Project Manager"))
    pm$Modality <- factor(pm$Modality, levels = c("Small Molecules", "Biologics",
                                                  "Both"))
      temp <-ggplot(data=pm, aes(x=Total, y=Yrs, label = ID)) +
      geom_point(size = 13,aes(color = Level, shape = Modality),
                 alpha = 0.5)+
      theme(axis.text.y=element_blank())+
      scale_y_continuous(expand = c(0,0),limits=c(1,20))+
      scale_x_continuous(expand = c(0,0),limits=c(20,36), breaks = c(20,25,30,35))+
      ylab("Years of Experience")+
      xlab("Total Competency Score")+
      scale_color_manual(values = c("#00CCCC", "#CC0099", "#3366FF"))+
      scale_shape_manual(values = c(17,19, 15)) +
      theme(legend.text = element_text(size = 13),
            legend.title = element_text(size = 12))+
      ggtitle("Project Manager Ranking", subtitle = "Competency by Years of Experience")+
      theme_classic(base_size = 12)
          temp+ geom_label_repel(size = 3.5,point.padding = NA)

    })

}

ui <- fluidPage(
  # title = "Looking for the right candidate for your business?",
  titlePanel("Wave 1 - Talent Pipelining"),
  setBackgroundColor(
    color = c("lightseagreen", "ghostwhite"),
    gradient = "linear",
    direction = "top"),

  sidebarLayout(
    sidebarPanel(
      ### if one of the competencies are selected, they can be sorted by descending order on the table itself
      #img(src = "logo.jpg", height = 292, width = 560),
      conditionalPanel(
        'input.dataset === "Talent Ranking"',
        #  checkboxGroupInput("show_vars", "Columns in dataset to show:",
        #                     names(pm), selected = names(pm)),
        selectInput("Level", "Choose Level of Expertise:",
                    choices = c("Not Relevant",  
                                "Senior Project Manager" ,"PM (Border Senior PM)", "Project Manager")),
        selectInput("Modality", "Choose Modality:",
                    choices = c("Not Relevant","Both","Biologics", "Small Molecules"))

      ),
      ### create a new tab to show venn diagramm and scatterplot
      conditionalPanel(
        'input.dataset === "Level vs Competency"',
        helpText("This scatterplot shows each candidates overall competency score (X-axis) and their respective years of experience (Y-axis) 
                  within their respective fields. Shapes reflect modalities and colours show level of expertise.")
      )
    ),


    # Show a summary of the dataset and an HTML table with the requested
    # number of observations
    mainPanel(
      tabsetPanel(
        id = 'dataset',
        tabPanel("Talent Ranking", DT::dataTableOutput("mytable1")),
        tabPanel("Level vs Competency", plotOutput("scatter"))
      )
    )
  )
)