如何在闪亮的应用程序中响应用户输入进行pdf下载？

Question

我想将我闪亮的应用程序生成的表格和条形图下载为pdf报告。第一次在本地计算机上启动应用程序时，我可以使用选定的输入生成报告，但是当我切换输入时，它不会在pdf上生成新输入的报告。

这是我的用户界面代码

require(shiny)
require(shinydashboard)
require(ggplot2)
require(ggthemes)

sample <- read.csv("new_sample2.csv", stringsAsFactors = FALSE)

header <- dashboardHeader(title = "XYZ School Student Dashboard", titleWidth = 370)

body <- dashboardBody(
tags$head(tags$style(HTML('
  .main-header .logo {
                        font-family: "Georgia", Times, "Times New Roman", serif;
                        font-weight: bold;
                        font-size: 20px;
                        }
                        '))),
fluidRow(
column(width = 9,
box(title = "Selected Student", width = NULL, solidHeader = TRUE, status = "info",
           textOutput("summary1"),
           textOutput("summary2"),
           textOutput("summary3")
),

       box(title = "Marks card", status = "info", width = NULL, solidHeader = TRUE, collapsible = TRUE,
           tableOutput("table")),
       box(title = "Marks card bar plot", status = "info", width = NULL, solidHeader = TRUE, collapsible = TRUE,
           plotOutput("plot"))
),

column(width = 3,
       box(title = "Select", background = "blue" ,width = NULL,
           selectInput("class", "Class", unique(sample$class)),
           selectInput("name", "Name", unique(sample$name)),
           selectInput("exams", "Exams", choices = c("1st Periodic Test", "1st Term", "2nd Periodic Test",
                                                     "2nd Term", "3rd Periodic Test", "4th Periodic Test",
                                                     "Final")),

           "Note: In the Bar Plot", 
           br(),
           "1. The black line is the average class mark for that particular subject.",
           br(),
           "2. The red line is the pass mark for that particular subject.",
           hr(),
           downloadButton("downloadReport", "Download report")
           )
       )
  )
)


ui <- dashboardPage(skin = "blue",
    header,
      dashboardSidebar(disable = TRUE),
        body
)  

这是我的服务器代码

server <- function(input, output, session){

output$summary1 <- renderText({
paste("Student Name: ", input$name)
})

output$summary2 <- renderText({
paste("Class: ", input$class)
})
output$summary3 <- renderText({
paste("Examination: ", input$exams)
})


getdataset <- reactive({
dataset <- sample[sample$class == input$class & sample$name == input$name & sample$examination == input$exams, ]
})

observe({
classInput <- input$class
updateSelectInput(session, "name", choices = sample$name[sample$class == classInput])
})

output$table <- renderTable({
dataset <- getdataset()
dataset[, c("date", "subject", "maximum_mark", "pass_mark", "obtain_mark", "class_ave", "pc", "exam_pc")]
})

plotInput <- reactive({
df <- getdataset()
ggplot(df, aes(x = subject, y = obtain_mark)) +
  theme_fivethirtyeight() +
  geom_bar(stat = "identity", fill = "#006699") +
  geom_text(aes(label = obtain_mark),vjust = -0.4) +
  geom_errorbar(data = getdataset(),
                aes(y = class_ave, ymax = class_ave,
                    ymin = class_ave), colour = "#000000") +
  geom_errorbar(data = getdataset(),
                aes(y = pass_mark, ymax = pass_mark,
                    ymin = pass_mark), colour = "red") +
  labs(title = paste(input$name,"'s", input$exams, "marks"), x = "", y = "Marks") +
  theme(axis.text=element_text(size=10, face = "bold")
  )
})

output$plot <- renderPlot({
print(plotInput())
 })

output$downloadReport <- downloadHandler(
filename = "Student-report.pdf",
content = function(file){
  inputEnv <- new.env()
  inputEnv$class <- input$class
  inputEnv$name <- input$name
  inputEnv$exams <- input$exams
  inputEnv$data <- getdataset()
  out = rmarkdown::render("student_report.Rmd", envir = inputEnv)
  file.rename(out, file)
     }
    )
   }

 shinyApp(ui, server)  

这是我放置在app.R所在文件夹中的.Rmd文件。

---
title: "school_report"
author: "Management"
date: "May 4, 2016"
output: pdf_document
---

```{r echo=FALSE}
plotInput()
```  

```{r echo=FALSE}
dataset <- getdataset()
dataset[, c("date", "subject", "maximum_mark", "pass_mark", "obtain_mark", "class_ave", "pc", "exam_pc")]
```  

数据是学生在学校进行的考试中获得的分数的样本。

head(sample)
 class   name       examination       date        subject maximum_mark pass_mark obtain_mark  pc class_ave
1   1 Adison 1st Periodic Test 2015-03-23      English-I        20         8          14     70      15
2   1 Adison 1st Periodic Test 2015-03-24    Mathematics        20         8          19     95      16
3   1 Adison 1st Periodic Test 2015-03-25        Science        20         8          18     90      12
4   1 Adison 1st Periodic Test 2015-03-26          Hindi        20         8          20    100      15
5   1 Adison 1st Periodic Test 2015-03-27 Social Studies        20         8          19     95      11
6   1 Adison 1st Periodic Test 2015-03-28            M.M        20         8          20    100      14
 exam_pc
1 92.86
2 92.86
3 92.86
4 92.86
5 92.86
6 92.86  

tail(sample)
     class   name examination       date       subject maximum_mark pass_mark obtain_mark  pc class_ave
1851   2   Denver       Final 2015-12-10    English-II          100        40          93  93        59
1852   2   Denver       Final 2015-12-02       Drawing           50        20          25  50        34
1853   2   Denver       Final 2015-11-30            GK           50        20          50 100        42
1854   2   Denver       Final 2015-12-01 Moral Science           50        20          50 100        41
1855   2   Denver       Final 2015-12-02     Dictation           25        10          25 100        20
1856   2   Denver       Final 2015-11-30  Hand Writing           25        10          25 100        20
       exam_pc
 1851   87.89
 1852   87.89
 1853   87.89
 1854   87.89
 1855   87.89
 1856   87.89  

我将衷心感谢您的帮助。

Answer 1

我很抱歉花了我很长时间才回到这个问题上。在看完我所做的事情之后，结果发现它比我记得的要复杂得多。

这是我的示例应用代码

library(shiny)
library(ggplot2)
library(magrittr)

ui <- shinyUI(
  fluidPage(
    column(
      width = 2,
      selectInput(
        inputId = "x_var",
        label = "Select the X-variable",
        choices = names(mtcars)
      ),
      selectInput(
        inputId = "y_var",
        label = "Select the Y-variable",
        choices = names(mtcars)
      ),
      selectInput(
        inputId = "plot_type",
        label = "Select the plot type",
        choices = c("scatter plot", "boxplot")
      ),
      downloadButton(
        outputId = "downloader",
        label = "Download PDF"
      )
    ),
    column(
      width = 3,
      tableOutput("table")
    ),
    column(
      width = 7,
      plotOutput("plot")
    )
  )
)

server <- shinyServer(function(input, output, session){

  #****************************************
  #* Reactive Values

  table <- reactive({
    mtcars[, c(input[["x_var"]], input[["y_var"]])]
  })

  plot <- reactive({
    p <- ggplot(data = mtcars,
                mapping = aes_string(x = input[["x_var"]],
                                     y = input[["y_var"]]))
    if (input[["plot_type"]] == "scatter plot")
    {
      p + geom_point()
    }
    else
    {
      p + geom_boxplot()
    }
  })

  #****************************************
  #* Output Components

  output$table <- 
    renderTable({
      table()
    })

  output$plot <- 
    renderPlot({
      plot()
    })

  #****************************************
  #* Download Handlers

  output$downloader <- 
    downloadHandler(
      "results_from_shiny.pdf",
      content = 
        function(file)
        {
          rmarkdown::render(
            input = "report_file.Rmd",
            output_file = "built_report.pdf",
            params = list(table = table(),
                          plot = plot())
          ) 
          readBin(con = "built_report.pdf", 
                  what = "raw",
                  n = file.info("built_report.pdf")[, "size"]) %>%
            writeBin(con = file)
        }
    )
})

shinyApp(ui, server)

这是我的RMD（标题为report_file.Rmd）

---
title: "Parameterized Report for Shiny"
output: pdf_document
params:
  table: 'NULL'
  plot: 'NULL'
---

```{r}
params[["plot"]]
```

```{r}
params[["table"]]
```

寻找一些亮点

• 请注意，paramsRMarkdown脚本的YAML前端问题存在。这使我们可以在调用时传递要在脚本中使用的值列表rmarkdown::render(..., params = list(...))
• 我总是将我的PDF生成为虚拟文件。这样很容易找到。
• 我始终构建为虚拟文件的原因是，要使下载处理程序正常工作，您需要读取PDF的位内容，然后使用将其推入file参数writeBin。看看我的downloadHandler建筑。
• 使用参数化的报告意味着您不必在rmarkdown脚本中重新创建输出。该工作是在Shiny应用程序中完成的，参数化报告仅可帮助您正确发送对象。它与来回传递文件​​并不完全相同（尽管可能很简单，但我很想知道）。

在此处阅读有关参数化报告的更多信息：http : //rmarkdown.rstudio.com/developer_parameterized_reports.html