使用ExtReactive渲染和下载RmarkDown报告的问题

Question

我想要一个ShinyApp，允许用户选择属性（项目名称，月份），并下载有关这些项目状态的RmarkDown报告。

以下是我到目前为止所做的。我没有遇到任何错误，但是渲染的文档基本上是一个外壳，并且不会带有来自datasetInput（）的任何信息。为了确保DataSetInput（）有效，我使用content = function（file）{write.csv（datasetInput（），file）}创建了一个.csv文件}，而不是呈现rmarkDown文件，并且可以正常工作。我以.CSV格式获得了一个过滤的数据集。关于如何使文档正确渲染的任何想法？

ui <- fluidPage(
  theme = bslib::bs_theme(bootswatch = "flatly"),
  h2("Assessment, Accountability, and Evaluation"),
  h4("Evaluation Project Updates"),
  br(),
  sidebarLayout(
    sidebarPanel(
      pickerInput(inputId = "project",
                  label = "Choose project (one or more):",
                  choices = c(levels(eval$project_name)),
                  options = list(`actions-box` = TRUE),
                  multiple = TRUE),
      pickerInput(inputId = "month",
                  label = "Month:",
                  choices = c(levels(eval$month)),
                  options = list(`actions-box` = TRUE),
                  multiple = TRUE),
      pickerInput(inputId = "year",
                  label = "Year:",
                  choices = c(levels(eval$year)),
                  options = list(`actions-box` = TRUE),
                  multiple = TRUE),
      actionButton("view", "View Selection"),
      downloadButton("report", "Generate report")),
      
      mainPanel(
        tableOutput("table")
      )
    )
  )

server <- function(input, output, session) {
  datasetInput <- eventReactive(input$view,{
    
    datasetInput <- filter(eval, project_name %in% input$project,
                           month %in% input$month, year %in% input$year)
    
    return(datasetInput)
  })
  
  
  output$table <- renderTable({
    
    datasetInput() %>% select(project_name, summary, month, year)
    
  })
  
  
  output$report <- downloadHandler(
    
    filename = function() {
      paste("report-", Sys.Date(), ".html", sep = "")
    },
    
    content = function(file) {
      
      tempReport <- "update.Rmd"

      tempReport <- file.path(tempdir(), "update.Rmd")
      file.copy("update.Rmd", tempReport, overwrite = TRUE)
      
      params <- list(report = datasetInput())
      
      rmarkdown::render(tempReport, output_file = file,
                        params = params,
                        envir = new.env(parent = globalenv())
      )
    }
  )
}

shinyApp(ui = ui, server = server)



update.Rmd file

---
title: "&nbsp;"
header-includes:
fontsize: 11pt
output:
  html_document:
    df_print: paged
  pdf_document: default
  word_document: default
sansfont: Roboto
font: Roboto
geometry: left=1in,right=1in,top=0.35in,bottom=0.6in
urlcolor: blue
params:
  report: NA
---

```{r rmarkdown-setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE)
knitr::opts_chunk$set(message = FALSE)
knitr::opts_chunk$set(warning = FALSE)
knitr::opts_chunk$set(dev = "cairo_pdf")
options(knitr.kable.NA = "")
options(kableExtra.latex.load_packages = FALSE)
```

<center>
## Assessment, Accountability, and Evaluation

### Project Updates

<a href="`r `params$project_folder`" target="_blank">Project Folder</a> | <a href="`r `params$project_website`" target="_blank">Website</a>
</center>
  
##### `r params$project_name`

`r params$month` `r params$year`
<br>

This Project Status Report summarizes information on key activities, risks, and issues for the `r params$project_name` project.

**Project Status:** `r params$project_status`

**Project Summary:** `r params$summary`
<br>

**Project Key Area 1:** `r params$key_area_1`
<br>
Summary of Key Area: `r params$key_area_1_summary`

**Project Key Area 2:** `r params$key_area_2`
<br>
Summary of Key Area: `r params$key_area_2_summary`

**Project Key Area 3:** `r params$key_area_3`
<br>
Summary of Key Area: `r params$key_area_3_summary`
<br>

**Project Risks & Issues**
<br>
`r params$risks`

**Additional Notes**
<br>
`r params$additions`

这是输出。数据不填充报告。

dput(eval)
structure(list(project_name = structure(9L, .Label = c("Equity, Disproportionality, and Design", 
"Coronado: iReady", "Coronado: World Language", "Oceanside: MaSTers", 
"California Literacy State Development Grant: Region 9", "California Literacy State Development Grant: Region 4", 
"National Student Clearinghouse", "iCAN: Improving Chronic Absenteeism Network", 
"ASPIRE: Middle School On-Track Network", "SD9UP: High School On-Track Network", 
"SDCOE: Equity Department", "SDCOE: California Administrative Services Credential"
), class = c("ordered", "factor")), month = structure(6L, .Label = c("January", 
"February", "March", "April", "May", "June", "July", "August", 
"September", "October", "November", "December"), class = c("ordered", 
"factor")), day = structure(15, label = c(Q2_2 = "Entry Date: - Day")), 
    year = structure(2L, .Label = c("2021", "2022", "2023", "2024", 
    "2025"), class = c("ordered", "factor")), project_folder = structure(NA_character_, label = c(Q4 = "Project Folder")), 
    project_website = structure("https://www.sdcoe.net/educators/evaluation\n", label = c(Q5 = "Project Website")), 
    project_status = structure(1L, .Label = c("On-track", "At-risk", 
    "Delayed"), class = c("ordered", "factor")), summary = structure("This ASPIRE Network support middle schools to keep students on track for important high school milestones including college and career readiness. The project is nearing the completion of the planning phase and is set to launch in August/September. Evaluation Services supports the network by collecting data on GPA, course-taking, and other variables. We provide customized dashboards and reports so participants can monitor their progress toward Network goals and to make decisions about changes they wish to implement in their schools. The dashboard is currently in a planning and basic design phase with the goal being a fully deployed dashboard by August 25th.", label = c(Q7 = "Summary")), 
    key_area_1 = structure("Develop Network metrics", label = c(Q8 = "Project Key Area:")), 
    key_area_1_summary = structure("We have started the process of developing key metrics for the dashboard. We are using GPA, passing rates in ELA and Math along with key drivers metrics including growth mindset, school culture, and relationships--all of which are captured using a survey. We have most of the survey items drafted and have developed a data collection guide for the other data elements. We continue to refine the exact criteria for what is on and off track in terms of the network using these data elements.", label = c(Q9 = "Key Area Overview:")), 
    key_area_2 = structure("Gather, clean, and validate data", label = c(Q10 = "Project Key Area (2):")), 
    key_area_2_summary = structure("We have designed a guide for the types of data elements we will collect. However, the Network  currently has one participant. To date, we have not collected data, but have modeled the dashboard design using data from non-participating school systems. We expect to start receiving data by 07/01/2022.", label = c(Q11 = "Key Area (2) Overview:")), 
    key_area_3 = structure("Deploy dashboards", label = c(Q12 = "Project Key Area (3):")), 
    key_area_3_summary = structure("We have designed the dashboard's landing page and are in the process of revising it based on feedback we received. We will continue to add pages. The goal for now is to have 3 dashboard pages: a landing page, an on-track page, and a metrics page. The landing page will house all the basic information for the Network including the Aim. The on-track page will include the criteria for who's on and off-track. It will allow participants to drill down and see actual on and off-track students. The metrics page will include various data elements and allow participants to explore the data using graphs and charts. We expect to have the dashboard finalized (in draft form) by mid July with a deployment data of 08/25/2022.", label = c(Q13 = "Key Area (3) Overview:")), 
    risks = structure("The ASPIRE Network continues to recruit participants, but to date, the network has one school committed. Ideally, we need previous year’s data so that we can see the trends in our metrics prior to starting the work. We need recruitment efforts to identify all network participants by mid-July to stay on track. One recommendation is to devote a team member to recruitment and give this person a timeline and a recruitment goal (e.g., 4 schools).\nWe need to operationalize the network aim and determine a goal for the upcoming year. To address this challenge, we need to identify network participants and collect data from the schools.\nThe survey items (network drivers) examining school culture, growth mindset, and relationships need to be operationalized and finalized. Ideally, the survey should include 10-12 items on a 3-to-5-point scale. One recommendation is to devote 3-4 hours of work time for a small group to develop the survey items fully.\n", label = c(Q14 = "Project Risks & Issues")), 
    additions = structure("The Network's running notes and meeting agendas are available at:\nhttps://docs.google.com/document/d/1waLQOknlFnBILEivbMnKAdzibVhMoiojUn4bkBpfR70/edit\n", label = c(Q15 = "Additional notes or highlights"))), row.names = c(NA, 
-1L), class = c("tbl_df", "tbl", "data.frame"), column_map = structure(list(
    qname = c("StartDate", "EndDate", "Status", "IPAddress", 
    "Progress", "Duration (in seconds)", "Finished", "RecordedDate", 
    "ResponseId", "RecipientLastName", "RecipientFirstName", 
    "RecipientEmail", "ExternalReference", "LocationLatitude", 
    "LocationLongitude", "DistributionChannel", "UserLanguage", 
    "Q1", "Q2_1", "Q2_2", "Q2_3", "Q3", "Q4", "Q5", "Q6", "Q7", 
    "Q8", "Q9", "Q10", "Q11", "Q12", "Q13", "Q14", "Q15"), description = c("Start Date", 
    "End Date", "Response Type", "IP Address", "Progress", "Duration (in seconds)", 
    "Finished", "Recorded Date", "Response ID", "Recipient Last Name", 
    "Recipient First Name", "Recipient Email", "External Data Reference", 
    "Location Latitude", "Location Longitude", "Distribution Channel", 
    "User Language", "Project Name:", "Entry Date: - Month", 
    "Entry Date: - Day", "Entry Date: - Year", "Prepared by:", 
    "Project Folder", "Project Website", "Project Status", "Summary", 
    "Project Key Area:", "Key Area Overview:", "Project Key Area (2):", 
    "Key Area (2) Overview:", "Project Key Area (3):", "Key Area (3) Overview:", 
    "Project Risks & Issues", "Additional notes or highlights"
    ), main = c("Start Date", "End Date", "Response Type", "IP Address", 
    "Progress", "Duration (in seconds)", "Finished", "Recorded Date", 
    "Response ID", "Recipient Last Name", "Recipient First Name", 
    "Recipient Email", "External Data Reference", "Location Latitude", 
    "Location Longitude", "Distribution Channel", "User Language", 
    "Project Name:", "Entry Date:", "Entry Date:", "Entry Date:", 
    "Prepared by:", "Project Folder", "Project Website", "Project Status", 
    "Summary", "Project Key Area:", "Key Area Overview:", "Project Key Area (2):", 
    "Key Area (2) Overview:", "Project Key Area (3):", "Key Area (3) Overview:", 
    "Project Risks & Issues", "Additional notes or highlights"
    ), sub = c("", "", "", "", "", "", "", "", "", "", "", "", 
    "", "", "", "", "", "", "Month", "Day", "Year", "", "", "", 
    "", "", "", "", "", "", "", "", "", ""), ImportId = c("startDate", 
    "endDate", "status", "ipAddress", "progress", "duration", 
    "finished", "recordedDate", "_recordId", "recipientLastName", 
    "recipientFirstName", "recipientEmail", "externalDataReference", 
    "locationLatitude", "locationLongitude", "distributionChannel", 
    "userLanguage", "QID1", "QID5_1", "QID5_2", "QID5_3", "QID6", 
    "QID21_TEXT", "QID20_TEXT", "QID7", "QID10_TEXT", "QID12_TEXT", 
    "QID13_TEXT", "QID14_TEXT", "QID15_TEXT", "QID16_TEXT", "QID17_TEXT", 
    "QID9_TEXT", "QID18_TEXT"), timeZone = c("Z", "Z", NA, NA, 
    NA, NA, NA, "Z", NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA), choiceId = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA)), row.names = c(NA, -34L
), class = c("tbl_df", "tbl", "data.frame")))