return to slow app

app.R

@@ -1,12 +1,9 @@
 library(shiny)
 library(bslib)
 library(tidyverse)
-library(future)
-library(promises)
 
-plan(multisession)
-
-survey <- arrow::read_parquet("data/survey.parquet")
+survey <- read.csv("data/survey.csv") |> 
+  slice_sample(n = 5000, by = region)  
 
 ui <- page_sidebar(
 
@@ -23,77 +20,65 @@ ui <- page_sidebar(
       max = 100,
       value = 100,
       step = 10
-    ),
-    input_task_button(
-      id = "compute", 
-      label = "Calcular"
     )
   ),
 
   useBusyIndicators(),
 
   card(
     max_height = "50%",
-    DT::DTOutput("table")
+    tableOutput("table")
   ),
 
   layout_columns(
     col_widths = c(4, 4, 4),
 
     card(
-      plotly::plotlyOutput("histogram")
+      plotOutput("histogram")
     ),
     card(
       full_screen = TRUE,
-      plotly::plotlyOutput("by_transport")
+      plotOutput("by_transport")
     ),
     card(
       full_screen = TRUE,
-      plotly::plotlyOutput("by_type")
+      plotOutput("by_type")
     )
 
   )
 
 )
 
 server <- function(input, output, session) {
-  filter_task <- ExtendedTask$new(function(p_survey, p_region, p_age) {
-    future_promise({
-      p_survey |> 
-        dplyr::filter(region == p_region) |> 
-        dplyr::filter(age <= p_age)
-    })
-  }) |> 
-    bind_task_button("compute")
-
-  observe(filter_task$invoke(survey, input$region, input$age)) |> 
-    bindEvent(input$compute, ignoreNULL = FALSE)
-
-  filtered <- reactive({
-    filter_task$result()
-  })
-
-  output$table <- DT::renderDT({
-    filtered()
+  output$table <- renderTable({
+    survey |> 
+      filter(region == input$region) |> 
+      filter(age <= input$age)
   })
 
-  output$histogram <- plotly::renderPlotly({
-    filtered() |> 
+  output$histogram <- renderPlot({
+    survey |> 
+      filter(region == input$region) |> 
+      filter(age <= input$age) |> 
       ggplot(aes(temps_trajet_en_heures)) +
       geom_histogram(bins = 20) +
       theme_light()
   })
 
-  output$by_transport <- plotly::renderPlotly({
-    filtered() |> 
+  output$by_transport <- renderPlot({
+    survey |> 
+      filter(region == input$region) |> 
+      filter(age <= input$age) |> 
       ggplot(aes(temps_trajet_en_heures)) +
       geom_histogram(bins = 20) +
       facet_wrap(~transport) +
       theme_light()
   })
 
-  output$by_type <- plotly::renderPlotly({
-    filtered() |> 
+  output$by_type <- renderPlot({
+    survey |> 
+      filter(region == input$region) |> 
+      filter(age <= input$age) |> 
       ggplot(aes(temps_trajet_en_heures)) +
       geom_histogram(bins = 20) +
       facet_wrap(~type) +