Further considerations for callModule processing

A long follow-up to #1 and #2 to discuss handling of `callModule` calls.

Using the [nested shiny modules example app](https://github.com/dgkf/scriptgloss/blob/master/app-examples/nested-modules-static-code-generation/app.R), the code it generates looks like this at the moment (below).

It's not particularly pretty, even by automatically generated code standards. It requires wrapping the output list and return result of the callModule call in an additional class structure and then using special accessor functions to extract the various components.

```r
library(scriptgloss)
library(shiny)
library(dplyr)
library(ggplot2)
my_data <- ggplot2::mpg
scatterPlot <- function(data, cols) ggplot(data, aes_string(x = cols[1], y = cols[2])) + geom_point(aes(color = selected_)) + scale_color_manual(values = c("black", "#66D65C"), guide = FALSE)
linkedScatter <- function(input, output, session, data, left, right) {
uniquesTable <- function(input, output, session, data, col) {
filteredData <- function() {
data() %>% dplyr::filter(selected_) %>% .[[col()]]
}
output$table <- function() {
table(filteredData())
}
uniques <- function() {
unique(filteredData())
}
.return <- uniques
return(structure(output, return = .return, submodules = structure(list(), .Names = character(0)), class = c("scriptgloss_module", "list")))
}
uniques_table <- uniquesTable(input = structure(list(), .Names = character(0)), output = list(), session = NULL, data = dataWithSelection, col = function() right()[[1]])
u <- callStaticModule(uniques_table)
dataWithSelection <- function() {
brushedPoints(data(), input$brush, allRows = TRUE)
}
output$plot1 <- function() {
scatterPlot(dataWithSelection(), left())
}
output$plot2 <- function() {
scatterPlot(dataWithSelection(), right())
}
output$uniques <- function() {
paste("Unique Values:", paste(as.character(u()), collapse = ", "))
}
.return <- dataWithSelection
return(structure(output, return = .return, submodules = list(uniques_table = uniques_table), class = c("scriptgloss_module", "list")))
}
scatters <- linkedScatter(input = structure(list(), .Names = character(0)), output = list(), session = NULL, data = function() my_data, left = function() c("cty", "hwy"), right = function() c("drv", "hwy"))
df <- callStaticModule(scatters)
sprintf("%d observation(s) selected", nrow(dplyr::filter(df(), selected_)))
```