The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

Row level access

2025-01-31

Sometimes you do not want to give a user access to the entire dataset. You can either hide rows or give read-only access.

Hide rows completely

In this example we only allow user Mickey to see his own row.

We simply can use dplyr::filter() on the table. Note that is most useful if you combine this with backends that support in_place editing. E.g. you can retrieve only a subset of rows from a database and specifically modify those. Take a look at the ‘relational database’ vignettes for more information on how to work with a database.

library(editbl)
library(shiny)
conn <- DBI::dbConnect(RSQLite::SQLite(), "")
df <- data.frame(
    user = c("Albert","Donald","Mickey"),
    email = c('albert@einstein.com', 'donald@duck.com', 'mickey@mouse.com')
)
DBI::dbWriteTable(conn, "characters", df)
tibble <- dplyr::tbl(conn, 'characters')

CURRENT_USER = 'Mickey'

shiny::shinyApp( 
    ui = editbl::eDTOutput('id'),
    server =  function(input, output,session){
      result <- eDT(id='id',
        data = tibble %>% filter(user == CURRENT_USER),
        in_place = TRUE
      )
    })

print(tibble)
## # Source:   table<characters> [?? x 2]
## # Database: sqlite 3.45.0 []
##   user   email              
##   <chr>  <chr>              
## 1 Albert albert@einstein.com
## 2 Donald donald@duck.com    
## 3 Mickey mickey@mouse.com
DBI::dbDisconnect(conn)

Read-only access

In this example we only allow user Mickey to modify his own row. However he can still read data from others.

The arguments canEditRow and canDeleteRow can be used to specify logic describing if modfications are allowed. The passed on logic shoud be a function with the argument row. This is a single row of the displayed table in datatype tibble.

library(editbl)
df <- tibble::tibble(
    user = c("Albert","Donald","Mickey"),
    email = c('albert@einstein.com', 'donald@duck.com', 'mickey@mouse.com')
)

CURRENT_USER = 'Mickey'

rowModificationLogic <- function(row){
        if (row[,'user'] == CURRENT_USER){
          TRUE
        } else {
          FALSE  
        }
    }

shiny::shinyApp( 
    ui = editbl::eDTOutput('id'),
    server =  function(input, output,session){
      eDT(id='id',
        data = df,
        canEditRow = rowModificationLogic,
        canDeleteRow = rowModificationLogic
        )
    })

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.