Invoke function within RShiny server call and render result as print output - r

Question

I have written a script which makes use of 2 functions in order to calculate the duration required for a test to run, eg power analysis.
Inputs and code as follows;
## RUN POWER CALCULATION
average_daily_traffic <- 3515/30
control <- 0.47
uplift <- 0.02
num_vars <- 2
sample_size_calculator <- function(control, uplift){
variant <- (uplift + 1) * control
baseline <- ES.h(control, variant)
sample_size_output <- pwr.p.test(h = baseline,
n = ,
sig.level = 0.05,
power = 0.8)
if(variant >= 0)
{return(sample_size_output)}
else
{paste("N/A")}
}
## RUN DAYS CALCULATOR FUNCTION
days_calculator <- function(sample_size_output, average_daily_traffic){
days_required <- c((sample_size_output)*num_vars)/(average_daily_traffic)
if(days_required >= 0)
{paste0("It will take ", round(days_required, digits = 0)*num_vars, " days for this test to reach significance, with a daily average of " , round(average_daily_traffic, digits = 0), " visitors to this page over a 30 day period.")}
else
{paste("N/A")}
}
## RUN FUNCTIONS AND OUTPUT ANSWER
sample_size_calculator <- sample_size_calculator(control, uplift)
sample_size_output <- sample_size_calculator$n
answer <- days_calculator(sample_size_output, average_daily_traffic)
answer
This code is performant and is fit for my purpose in a standalone R script.
However, I need to make these functions executable from within a Shiny app. My attempt is as follows;
library(shiny)
ui <- fluidPage(
actionButton("exe", "Run",
style="color: #fff; background-color: #337ab7; border-color: #2e6da4"),
mainPanel(
textOutput("answer")
))
server <- function(input, output, session) {
sample_size_calculator <- eventReactive(input$exe,{
average_daily_traffic <- 3515/30
control <- 0.47
uplift <- 0.02
num_vars <- 2
variant <- (uplift + 1) * control
baseline <- ES.h(control, variant)
sample_size_output <- pwr.p.test(h = baseline,
n = ,
sig.level = 0.05,
power = 0.8)
if(variant >= 0)
{return(sample_size_output)}
else
{paste("N/A")}
})
days_calculator <- eventReactive (input$exe,{
days_required <- c((sample_size_output)*num_vars)/(average_daily_traffic)
if(days_required >= 0)
{paste0("It will take approximately ", round(days_required, digits = 0)*num_vars, " days or ", round((round(days_required, digits = 0)*num_vars)/365, digits = 1) ," years for this test to reach significance, based on a daily average of " , round(average_daily_traffic, digits = 0), " users to this page in the last 30 days.")}
else
{paste("N/A")}
})
outputs_ <- eventReactive( input$exe, {
req(sample_size_calculator())
req(days_calculator())
sample_size_calculator <- sample_size_calculator(control, uplift)
sample_size_output <- sample_size_calculator$n
answer <- days_calculator(sample_size_output, average_daily_traffic)
output$answer <- renderText(outputs_$answer)
})
}
shinyApp(ui = ui, server = server)
When I run this code, I see the execute button but no output is displayed.
This is very likely due to a limitation in my understanding of how Shiny invokes functions so if there is a better way I would be very grateful to hear it.
Thanks in advance.
* EDITING TO INCLUDE FULL FUNCTIONALITY CODE *
The objective of the code is to use Mark Edmonson's googleAnalyticsR and googleAuthR to enable retrieval of web visit data to a particular URL/page from the Google Analytics account for last 30days and show a trend of this data. This works fine, once the user enters the URL and hits 'Run'.
There is an additional GA call which retrieves additional data for a particular conversion action (see other_data). This is required in order to derive the conversion rate that is used later in the power calculation.
The calculation is cvr <- aeng$users/totalusers
#options(shiny.port = 1221)
## REQUIRED LIBS
library(shiny)
library(googleAnalyticsR)
library(plotly)
library(googleAuthR)
library(markdown)
library(pwr)
gar_set_client(scopes = c("https://www.googleapis.com/auth/analytics.readonly"))
daterange <- function(x) {
as.Date(format(x, "%Y-%m-01"))
}
## DATE PARAMETERS
date_start <- as.Date(Sys.Date(),format='%d-%B-%Y')-31
date_end <- as.Date(Sys.Date(),format='%d-%B-%Y')-1
date_range <- c(date_start, date_end)
## UI SECTION
ui <- fluidPage(
googleAuth_jsUI("auth"),
tags$head(
tags$link(rel = "stylesheet", type = "text/css", href = "dur_calc.css")
),
tags$br(),
sidebarLayout(
sidebarPanel(
code("To begin, select from 'Accounts' and enter URL of page to be tested:"),
tags$p(),
column(width = 12, authDropdownUI("auth_dropdown",
inColumns = FALSE)),
textInput("url", label = h5(strong("Page to be tested")), value = "Enter full page URL..."),
hr(),
fluidRow(column(3, verbatimTextOutput("value")
)
),
actionButton("exe", "Run Calculator",
style="color: #fff; background-color: #337ab7; border-color: #2e6da4"),
),
mainPanel(
plotlyOutput("trend_plot"),
textOutput("page"),
textOutput("answer")
)
)
)
## SERVER SECTION
server <- function(input, output, session) {
auth <- callModule(googleAuth_js, "auth")
## GET GA ACCOUNTS
ga_accounts <- reactive({
req(auth()
)
with_shiny(
ga_account_list,
shiny_access_token = auth()
)
})
view_id <- callModule(authDropdown, "auth_dropdown",
ga.table = ga_accounts)
ga_data <- eventReactive( input$exe, {
x <- input$url
#reactive expression
output$page <- renderText({
paste("You have selected the page:", input$url) })
filterPageurl <- dim_filter("dimension97" , "REGEX", x ,not = FALSE)
filts <- filter_clause_ga4(list( filterPageurl))
req(view_id())
req(date_range)
with_shiny(
google_analytics,
view_id(),
date_range = date_range,
dimensions = "date",
metrics = "users",
dim_filters = filts,
max = -1,
shiny_access_token = auth()
)
})
other_data <- eventReactive( input$exe, {
x <- input$url
filterPageurl <- dim_filter("dimension97" , "REGEX", x ,not = FALSE)
filts <- filter_clause_ga4(list( filterPageurl))
seg_id <- "gaid::uzKGvjpFS_Oa2IRh6m3ACg" #AEUs
seg_obj <- segment_ga4("AEUs", segment_id = seg_id)
req(view_id())
req(date_range)
#req(filts)
with_shiny(
google_analytics,
view_id(),
date_range = date_range,
dimensions = "date",
metrics = "users",
dim_filters = filts,
segments = seg_obj,
max = -1,
shiny_access_token = auth()
)
})
outputly <- eventReactive( input$exe, {
req(other_data())
req(ga_data())
aeng <- other_data()
ga_data <- ga_data()
totalusers <<- sum(ga_data$users)
cvr <- aeng$users/totalusers
average_daily_traffic <- totalusers/30
control <- cvr
uplift <- 0.02
num_vars <- 2
})
sample_size_calculator <- eventReactive(input$exe,{
variant <- (uplift + 1) * control
baseline <- ES.h(control, variant)
sample_size_output <- pwr.p.test(h = baseline,
n = ,
sig.level = 0.05,
power = 0.8)
if(variant >= 0)
{return(sample_size_output)}
else
{paste("N/A")}
})
days_calculator <- eventReactive (input$exe,{
days_required <- c((sample_size_output)*num_vars)/(average_daily_traffic)
if(days_required >= 0)
{paste0("It will take approximately ", round(days_required, digits = 0)*num_vars, " days or ", round((round(days_required, digits = 0)*num_vars)/365, digits = 1) ," years for this test to reach significance, based on a daily average of " , round(average_daily_traffic, digits = 0), " users to this page in the last 30 days.")}
else
{paste("N/A")}
})
output$trend_plot <- renderPlotly({
req(ga_data())
ga_data <- ga_data()
plot_ly(
x = ga_data$date,
y = ga_data$users,
type = 'scatter',
mode = 'lines') %>%
layout(title = "Page Visitors by Day (last 30 days)",
xaxis=list(title="Date", tickformat='%Y-%m-%d', showgrid=FALSE, showline=TRUE),
yaxis=list(title = "Users", showgrid=FALSE, showline=TRUE)
)
})
calc_answer <- eventReactive(input$exe, {
req(outputly)
outputly <- outputly()
sample_size_calculator <- sample_size_calculator()
sample_size_output <- sample_size_calculator$n
days_calculator(sample_size_output, average_daily_traffic)
})
output$answer <- renderText(calc_answer())
}
shinyApp(ui = ui, server = server)

Answer 1

A few suggestions that may help.
Would start with a simplified shiny app before adding all of the calculations, may be easier to work with for now
Would avoid putting output statements inside of eventReactive. See below for example.
Consider having only one observeEvent or eventReactive for the button press instead of multiple, especially since some function results depend on others.
Right now there are no inputs, so don't need additional reactive expressions. When you add inputs, though, you probably will.
If you haven't already, review the R Studio Shiny tutorial on Action Buttons and Reactivity.
Hope this is helpful in moving forward.
library(shiny)
library(pwr)
ui <- fluidPage(
actionButton("exe", "Run", style="color: #fff; background-color: #337ab7; border-color: #2e6da4"),
mainPanel(
textOutput("answer")
)
)
server <- function(input, output, session) {
average_daily_traffic <- 3515/30
control <- 0.47
uplift <- 0.02
num_vars <- 2
sample_size_calculator <- function() {
variant <- (uplift + 1) * control
baseline <- ES.h(control, variant)
sample_size_output <- pwr.p.test(h = baseline,
n = ,
sig.level = 0.05,
power = 0.8)
if(variant >= 0)
{return(sample_size_output)}
else
{return(NA)}
}
days_calculator <- function (sample_size_output, average_daily_traffic) {
days_required <- c((sample_size_output)*num_vars)/(average_daily_traffic)
if(days_required >= 0)
{paste0("It will take approximately ", round(days_required, digits = 0)*num_vars, " days or ", round((round(days_required, digits = 0)*num_vars)/365, digits = 1) ," years for this test to reach significance, based on a daily average of " , round(average_daily_traffic, digits = 0), " users to this page in the last 30 days.")}
else
{paste("N/A")}
}
calc_answer <- eventReactive(input$exe, {
sample_size_calculator <- sample_size_calculator()
sample_size_output <- sample_size_calculator$n
days_calculator(sample_size_output, average_daily_traffic)
})
output$answer <- renderText(calc_answer())
}
shinyApp(ui = ui, server = server)