2

我正在开发我的第一个闪亮应用程序——它在本地运行良好,但是当我发布到 shinyapps.io: 时会产生错误Error in data.table: object '.R.listCopiesNamed' not found

我以前在本地遇到过这个错误,但是当我更新我的包时问题得到了解决。因为该错误很容易在本地解决,并且因为该错误似乎取决于应用程序使用的包的版本,所以我怀疑我的本地环境中有一些东西 Shinyapps.io 没有在服务器上重新创建 - - 但我不知道如何追踪未重新创建的内容以便将其添加到我的代码中。

我尝试过的事情(都产生相同的错误):

  • 更新我所有的包。
  • 回溯到旧版本data.table.
  • 明确告诉应用程序使用本地加载的包的版本。

任何人都可以对未在 shinyapps.io 服务器上复制的本地可能发生的事情有所了解吗?谢谢!

可重现的例子:

library(shiny)
library(data.table)
library(expss)
library(DT)
library(lubridate)
library(tidyverse)

# define UI for application
ui <- fixedPage(
# sidebar with dropdown menus for selecting year, month, and question
fixedRow(
    column(4,
           # dropdown menu for year
           selectInput(inputId = "myYear",
                       label = "Year",
                       choices = c("2018"), # update this list once per year
                       selected = "2018"),  # change this to current year
           # dropdown menu for month
           selectInput(inputId = "myMonth",
                       label = "Month",
                       choices = c(# "January" = 01, 
                           # "February" = 02, 
                           # "March" = 03, 
                           # "April" = 04, 
                           # "May" = 05,
                           # "June" = 06, 
                           # "July" = 07, 
                           # "August" = 08, 
                           "September" = "09", 
                           "October" = "10" #, 
                           # "November" = "11", 
                           # "December" = "12"
                       )),
           # dropdown menu for question
           selectInput(inputId = "myQuestion",
                       label = "Question",
                       choices = c("Q2_awareness", "Q3_association"))),

    # show a data table
    column(8, dataTableOutput("myBrandTable"))
)
)



# ------------------------------------------------------------------------ #
##### LOAD THE DATA FRAMES TO WORK WITH #####
# ------------------------------------------------------------------------ #

# create data
set.seed(123)
myBrandData <- data.frame(
brand = sample(c("Brand A", "Brand B", "Brand C", "Brand D", "Brand E", "Brand F", "Brand G"),
               100, replace = TRUE),
report_date = sample(c("Benchmark", "September 2018", "October 2018"),
                     100, replace = TRUE),
Q2_awareness = sample(c(0, 1), 100, replace = TRUE),
Q3_awareness = sample(c(0, 1), 100, replace = TRUE)
)

# relevel some factors so they show up in the desired order
myBrandData <- myBrandData %>%
mutate(report_date = fct_relevel(report_date,
                                 "Benchmark",
                                 "September 2018",
                                 "October 2018")) %>%
mutate_at(vars(starts_with("Q")), funs(as.numeric(.)))

# ------------------------------------------------------------------------ #
###### HELPER FUNCTIONS #####
# ------------------------------------------------------------------------ #

# a function from Gregory Demin for calculating stats on dichotomous multiple response variables
tab_stat_dich = function(data, total_label = NULL, total_statistic = "u_cases",
                     label = NULL){

if (missing(total_label) && !is.null(data[["total_label"]])) {
    total_label = data[["total_label"]]
}
if(is.null(total_label)){
    total_label = "#Total"
}

# calculate means
res = eval.parent(
    substitute(
        tab_stat_mean_sd_n(data,
                           weighted_valid_n = "w_cases" %in% total_statistic,
                           labels = c("|", "@@@@@", total_label),
                           label = label)
    )
)
curr_tab = res[["result"]][[length(res[["result"]])]]
# drop standard deviation
curr_tab = curr_tab[c(TRUE, FALSE, TRUE), ]

# convert means to percent
curr_tab[c(TRUE, FALSE), -1] = curr_tab[c(TRUE, FALSE), -1] * 100
## clear row labels
curr_tab[[1]] = gsub("^(.+?)\\|(.+)$", "\\2", curr_tab[[1]], perl = TRUE )

res[["result"]][[length(res[["result"]])]] = curr_tab
res
}


# define server logic required to create the line graph & data table
server <- function(input, output) {
# ------------------------------------------------------------------------ #
##### MODIFY THE DATA FRAMES THAT GO INTO THE OUTPUTS ####
# ------------------------------------------------------------------------ #

myBrandTableData <- reactive({
    myBrandData %>%
        mutate(brand = fct_relevel(brand,
                                   "Brand A",
                                   "Brand B",
                                   "Brand C", 
                                   "Brand D", 
                                   "Brand E", 
                                   "Brand F", 
                                   "Brand G")) %>%
        select(report_date, Brand = brand, Variable = input$myQuestion)
})

# ------------------------------------------------------------------------ #
##### BUILD THE OUTPUTS #####
# ------------------------------------------------------------------------ #

# build the data table for brand comparisons
output$myBrandTable <- renderDataTable({
    # some note about the table
    as.datatable_widget(
        myBrandTableData() %>%
                tab_cells(Variable) %>%
                tab_cols(Brand) %>%
                tab_total_label("# Responses") %>%
                tab_stat_dich() %>%
                tab_last_sig_cpct() %>%
                tab_pivot()
    )
})
}

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

sessionInfo()

R version 3.4.4 (2018-03-15)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Sierra 10.12.6

Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib

locale:
[1] en_CA.UTF-8/en_CA.UTF-8/en_CA.UTF-8/C/en_CA.UTF-8/en_CA.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] bindrcpp_0.2.2    forcats_0.3.0     stringr_1.3.1     dplyr_0.7.7       purrr_0.2.5       readr_1.1.1      
 [7] tidyr_0.8.2       tibble_1.4.2      ggplot2_3.1.0     tidyverse_1.2.1   lubridate_1.7.4   DT_0.5           
[13] expss_0.8.7       data.table_1.11.8 shiny_1.2.0      

loaded via a namespace (and not attached):
[1] Rcpp_0.12.19       lattice_0.20-35    assertthat_0.2.0   digest_0.6.18      mime_0.6          
 [6] R6_2.3.0           cellranger_1.1.0   plyr_1.8.4         backports_1.1.2    httr_1.3.1        
[11] pillar_1.3.0       rlang_0.3.0.1      lazyeval_0.2.1     readxl_1.1.0       rstudioapi_0.8    
[16] checkmate_1.8.5    labeling_0.3       foreign_0.8-71     htmlwidgets_1.3    RCurl_1.95-4.11   
[21] munsell_0.5.0      broom_0.5.0        compiler_3.4.4     httpuv_1.4.5       modelr_0.1.2      
[26] pkgconfig_2.0.2    htmltools_0.3.6    tidyselect_0.2.5   htmlTable_1.12     matrixStats_0.54.0
[31] crayon_1.3.4       withr_2.1.2        later_0.7.5        bitops_1.0-6       grid_3.4.4        
[36] nlme_3.1-131.1     jsonlite_1.5       xtable_1.8-3       gtable_0.2.0       magrittr_1.5      
[41] scales_1.0.0       cli_1.0.1          stringi_1.2.4      promises_1.0.1     xml2_1.2.0        
[46] tools_3.4.4        RJSONIO_1.3-0      glue_1.3.0         hms_0.4.2          crosstalk_1.0.0   
[51] rsconnect_0.8.8    yaml_2.2.0         colorspace_1.3-2   rvest_0.3.2        knitr_1.20        
[56] bindr_0.1.1        haven_1.1.2       

日志文件中的行:

2018-11-07T15:12:29.128343+00:00 shinyapps[556963]: ✖ lubridate::intersect()   masks base::intersect()
2018-11-07T15:12:29.128348+00:00 shinyapps[556963]: ✖ dplyr::na_if()           masks expss::na_if()
2018-11-07T15:12:29.128349+00:00 shinyapps[556963]: ✖ tidyr::nest()            masks expss::nest()
2018-11-07T15:12:29.128349+00:00 shinyapps[556963]: ✖ lubridate::quarter()     masks data.table::quarter()
2018-11-07T15:12:29.128350+00:00 shinyapps[556963]: ✖ dplyr::recode()          masks expss::recode()
2018-11-07T15:12:29.128345+00:00 shinyapps[556963]: ✖ dplyr::lst()             masks tibble::lst(), expss::lst()
2018-11-07T15:12:29.128350+00:00 shinyapps[556963]: ✖ stringr::regex()         masks expss::regex()
2018-11-07T15:12:29.128346+00:00 shinyapps[556963]: ✖ lubridate::mday()        masks data.table::mday()
2018-11-07T15:12:29.128351+00:00 shinyapps[556963]: ✖ lubridate::second()      masks data.table::second()
2018-11-07T15:12:29.128346+00:00 shinyapps[556963]: ✖ lubridate::minute()      masks data.table::minute()
2018-11-07T15:12:29.128351+00:00 shinyapps[556963]: ✖ lubridate::setdiff()     masks base::setdiff()
2018-11-07T15:12:29.128347+00:00 shinyapps[556963]: ✖ purrr::modify()          masks expss::modify()
2018-11-07T15:12:29.128352+00:00 shinyapps[556963]: ✖ purrr::transpose()       masks expss::transpose(), data.table::transpose()
2018-11-07T15:12:29.128347+00:00 shinyapps[556963]: ✖ purrr::modify_if()       masks expss::modify_if()
2018-11-07T15:12:29.128352+00:00 shinyapps[556963]: ✖ lubridate::union()       masks base::union()
2018-11-07T15:12:29.128347+00:00 shinyapps[556963]: ✖ lubridate::month()       masks data.table::month()
2018-11-07T15:12:29.128353+00:00 shinyapps[556963]: ✖ dplyr::vars()            masks ggplot2::vars(), expss::vars()
2018-11-07T15:12:29.128353+00:00 shinyapps[556963]: ✖ lubridate::wday()        masks data.table::wday()
2018-11-07T15:12:29.128353+00:00 shinyapps[556963]: ✖ lubridate::week()        masks data.table::week()
2018-11-07T15:12:29.128354+00:00 shinyapps[556963]: ✖ lubridate::yday()        masks data.table::yday()
2018-11-07T15:12:29.128354+00:00 shinyapps[556963]: ✖ lubridate::year()        masks data.table::year()
2018-11-07T15:12:29.329815+00:00 shinyapps[556963]: 
2018-11-07T15:12:29.329817+00:00 shinyapps[556963]: Listening on http://127.0.0.1:42714
2018-11-07T15:12:39.608656+00:00 shinyapps[556963]: Warning: Error in data.table: object '.R.listCopiesNamed' not found
2018-11-07T15:12:39.615998+00:00 shinyapps[556963]:   135: data.table
2018-11-07T15:12:39.615999+00:00 shinyapps[556963]:   134: elementary_cro_fun_df
2018-11-07T15:12:39.616000+00:00 shinyapps[556963]:   133: FUN
2018-11-07T15:12:39.616000+00:00 shinyapps[556963]:   132: lapply
2018-11-07T15:12:39.616001+00:00 shinyapps[556963]:   131: FUN
2018-11-07T15:12:39.616001+00:00 shinyapps[556963]:   130: lapply
2018-11-07T15:12:39.616002+00:00 shinyapps[556963]:   129: cro_fun
2018-11-07T15:12:39.616002+00:00 shinyapps[556963]:   128: tab_stat_fun_internal
2018-11-07T15:12:39.616003+00:00 shinyapps[556963]:   127: tab_stat_mean_sd_n
2018-11-07T15:12:39.616004+00:00 shinyapps[556963]:   121: freduce
2018-11-07T15:12:39.616003+00:00 shinyapps[556963]:   122: function_list[[i]]
2018-11-07T15:12:39.616004+00:00 shinyapps[556963]:   120: _fseq
2018-11-07T15:12:39.616005+00:00 shinyapps[556963]:   119: eval
2018-11-07T15:12:39.616005+00:00 shinyapps[556963]:   118: eval
2018-11-07T15:12:39.616006+00:00 shinyapps[556963]:   116: %>%
2018-11-07T15:12:39.616007+00:00 shinyapps[556963]:   114: exprFunc [/srv/connect/apps/test/app.R#133]
2018-11-07T15:12:39.616007+00:00 shinyapps[556963]:   113: widgetFunc
2018-11-07T15:12:39.616008+00:00 shinyapps[556963]:   112: func
2018-11-07T15:12:39.616044+00:00 shinyapps[556963]:    99: origRenderFunc
2018-11-07T15:12:39.616045+00:00 shinyapps[556963]:    98: renderFunc
2018-11-07T15:12:39.616046+00:00 shinyapps[556963]:    94: origRenderFunc
2018-11-07T15:12:39.616047+00:00 shinyapps[556963]:    93: output$myBrandTable
2018-11-07T15:12:39.616084+00:00 shinyapps[556963]:    12: fn
2018-11-07T15:12:39.616085+00:00 shinyapps[556963]:     6: eval
2018-11-07T15:12:39.616083+00:00 shinyapps[556963]:    13: runApp
2018-11-07T15:12:39.616085+00:00 shinyapps[556963]:     5: eval
2018-11-07T15:12:39.616084+00:00 shinyapps[556963]:     7: connect$retry
4

1 回答 1

1

解决方案:更新 R&RStudio 软件。

于 2018-11-07T18:45:43.123 回答