@MrGumble is correct in his comments. The files need to downloaded before being read. The drop_dir() function lists file paths on dropbox server and we can only read in data saved locally to our machine. If you have .csv files then this can be down in 1 step with the drop_read_csv() function. But since you have excel files these need to first to be downloaded explicitly with drop_download() and then read in with read_excel().
library(rdrop2)
library(tidyverse)
library(readxl)
#install.packages("xlsx")
library(xlsx)
token <- drop_auth()
#make a few excel file with iris dataset, save locally, and upload to dropbox root
iris_filenames <- paste0("iris", 1:3, ".xlsx")
walk(iris_filenames, ~write.xlsx(iris, file = .x, row.names = FALSE))
walk(iris_filenames, drop_upload)
#list all files on dropbox root and filter for only iris ones
iris_files_on_dropbox <- drop_dir(dtoken = token) %>%
filter(str_detect(name, 'iris'))
#make new filenames so we can see that the download worked correctly
#you could do overwrite = TRUE and not pass through new filenames
#see ?drop_download for all options
new_iris_filenames <- paste0("iris", 1:3, "-from-dropbox.xlsx")
#download the files first
walk2(iris_files_on_dropbox$name, new_iris_filenames, ~drop_download(path = .x, local_path = .y))
#then read them all in
df <- bind_rows(map(new_iris_filenames, read_xlsx))
Additionally, we can create our own custom function to do the download and reading in 1 step just as drop_read_csv() does by altering the source code for this function. All we need to do is change the read...() function from read.csv to read_excel and the reference to the dtoken default get_drop_token() to rdrop2:::get_drop_token() which is an un-exported function from the rdrop2 package so we need the three ':::'.
#source for drop_read_csv we can rewrite for excel files
# drop_read_csv <- function(file, dest = tempdir(), dtoken = get_dropbox_token(), ...) {
# localfile = paste0(dest, "/", basename(file))
# drop_download(file, localfile, overwrite = TRUE, dtoken = dtoken)
# utils::read.csv(localfile, ...)
# }
drop_read_excel <- function(file, dest = tempdir(), dtoken = rdrop2:::get_dropbox_token(), ...) {
localfile = paste0(dest, "/", basename(file))
drop_download(file, localfile, overwrite = TRUE, dtoken = dtoken)
readxl::read_excel(localfile, ...)
}
df2 <- bind_rows(map(iris_files_on_dropbox$name, drop_read_excel))
To work in a shiny app we first need to save the drop_auth token so we can authenticate while using the shiny app. Save this into your shiny app directory.
saveRDS(token, file = "token.rds")
Now here is a shiny app. When the 'go' button is clicked the iris excel files are downloaded and shown in the UI. We need to call drop_auth() in the global environment or global.R along with the custom drop_read_excel() function to use it.
library(shiny)
library(rdrop2)
library(tidyverse)
#saveRDS(token, file = "token.rds") into shiny app directory
#authenticate in global.R or outside of ui/server
drop_auth(rdstoken = "token.rds")
drop_read_excel <- function(file, dest = tempdir(), dtoken = rdrop2:::get_dropbox_token(), ...) {
localfile = paste0(dest, "/", basename(file))
drop_download(file, localfile, overwrite = TRUE, dtoken = dtoken)
readxl::read_excel(localfile, ...)
}
ui <- fluidPage(
actionButton("go", "go"),
tableOutput("table")
)
server <- function(input, output, session) {
df <- eventReactive(input$go, {
withProgress(message = 'Downloading from dropbox',
detail = 'This may take a while...', value = 0.5, {
iris_files_on_dropbox <- drop_dir() %>%
filter(str_detect(name, 'iris'))
setProgress(value = 0.75)
df <- bind_rows(map(iris_files_on_dropbox$name, drop_read_excel))
setProgress(value = 1)
})
return(df)
})
output$table <- renderTable({
df()
})
}
shinyApp(ui, server)
