use onStop() for one of the Shiny vignette examples

vignettes/shiny.Rmd

@@ -26,7 +26,7 @@ mirai natively supports Shiny ExtendedTask to create scalable Shiny apps, which
 
 In the example below, the app remains responsive, with the clock continuing to tick whilst the simulated expensive computation is running asynchronously in a parallel process. Also the button is disabled and the plot greyed out until the computation is complete.
 
-By wrapping the `runApp()` call in `with(daemons(...), ...)` the daemons are set up for the duration of the app, exiting automatically when the app is stopped.
+The call to `daemons()` is made at the top level, and `onStop()` may be used to automatically shut them down when the app exits.
 
 
 ``` r
@@ -59,10 +59,13 @@ server <- function(input, output, session) {
 
 }
 
-app <- shinyApp(ui = ui, server = server)
-
 # run app using 2 local daemons
-with(daemons(2), runApp(app))
+daemons(2)
+
+# automatically shutdown daemons when app exits
+onStop(function() daemons(0))
+
+shinyApp(ui = ui, server = server)
 ```
 *Thanks to Joe Cheng for providing examples on which the above is based.*
 
@@ -107,6 +110,8 @@ The user can add multiple plots, making use of Shiny modules, each having a diff
 
 The plots are generated asynchronously, and it is easy to see the practical limitations of the number of daemons set. For example, if updating 4 plots, and there are only 3 daemons, the 4th plot will not start to be generated until one of the other plots has finished.
 
+By wrapping the `runApp()` call in `with(daemons(...), ...)` the daemons are set up for the duration of the app, exiting automatically when the app is stopped.
+
 
 ``` r
 library(shiny)

vignettes/shiny.Rmd.orig

@@ -26,7 +26,7 @@ mirai natively supports Shiny ExtendedTask to create scalable Shiny apps, which
 
 In the example below, the app remains responsive, with the clock continuing to tick whilst the simulated expensive computation is running asynchronously in a parallel process. Also the button is disabled and the plot greyed out until the computation is complete.
 
-By wrapping the `runApp()` call in `with(daemons(...), ...)` the daemons are set up for the duration of the app, exiting automatically when the app is stopped.
+The call to `daemons()` is made at the top level, and `onStop()` may be used to automatically shut them down when the app exits.
 
 ```{r shinyextended, eval=FALSE}
 library(shiny)
@@ -58,10 +58,13 @@ server <- function(input, output, session) {
 
 }
 
-app <- shinyApp(ui = ui, server = server)
-
 # run app using 2 local daemons
-with(daemons(2), runApp(app))
+daemons(2)
+
+# automatically shutdown daemons when app exits
+onStop(function() daemons(0))
+
+shinyApp(ui = ui, server = server)
 ```
 *Thanks to Joe Cheng for providing examples on which the above is based.*
 
@@ -102,6 +105,8 @@ The user can add multiple plots, making use of Shiny modules, each having a diff
 
 The plots are generated asynchronously, and it is easy to see the practical limitations of the number of daemons set. For example, if updating 4 plots, and there are only 3 daemons, the 4th plot will not start to be generated until one of the other plots has finished.
 
+By wrapping the `runApp()` call in `with(daemons(...), ...)` the daemons are set up for the duration of the app, exiting automatically when the app is stopped.
+
 ```{r shinyextend2, eval=FALSE}
 library(shiny)
 library(mirai)