## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  eval = FALSE
)

## ----setup--------------------------------------------------------------------
# library(linkeR)
# library(shiny)
# library(leaflet)
# library(DT)
# library(plotly)

## ----three-component----------------------------------------------------------
# ui <- fluidPage(
#   titlePanel("Multi-Component Dashboard"),
# 
#   fluidRow(
#     column(4,
#       h4("Geographic View"),
#       leafletOutput("map")
#     ),
#     column(4,
#       h4("Data Table"),
#       DTOutput("table")
#     ),
#     column(4,
#       h4("Performance Chart"),
#       plotlyOutput("chart")
#     )
#   ),
# 
#   fluidRow(
#     column(12,
#       h4("Selection Details"),
#       verbatimTextOutput("selection_info")
#     )
#   )
# )
# 
# server <- function(input, output, session) {
# 
#   # Sample business data
#   business_data <- reactive({
#     data.frame(
#       business_id = paste0("BIZ_", 1:20),
#       name = paste("Business", 1:20),
#       latitude = runif(20, 40.7, 40.8),
#       longitude = runif(20, -111.95, -111.85),
#       revenue = runif(20, 100000, 1000000),
#       employees = sample(10:100, 20, replace = TRUE),
#       category = sample(c("Tech", "Retail", "Food"), 20, replace = TRUE)
#     )
#   })
# 
#   # Render map
#   output$map <- renderLeaflet({
#     leaflet(business_data()) %>%
#       addTiles() %>%
#       addCircleMarkers(
#         lng = ~longitude,
#         lat = ~latitude,
#         layerId = ~business_id,
#         radius = 5,
#         popup = ~paste("Business:", name)
#       )
#   })
# 
#   # Render table
#   output$table <- renderDT({
#     data <- business_data()
#     display_data <- data[, c("name", "category", "revenue", "employees")]
# 
#     datatable(
#       display_data,
#       selection = "single",
#       rownames = FALSE
#     ) %>%
#       formatCurrency("revenue", currency = "$", digits = 0)
#   })
# 
#   # Render chart
#   output$chart <- renderPlotly({
#     plot_ly(
#       data = business_data(),
#       x = ~employees,
#       y = ~revenue,
#       key = ~business_id,  # Critical: this enables plotly linking
#       text = ~name,
#       type = "scatter",
#       mode = "markers",
#       source = "business_chart"  # Source ID for plotly events
#     ) %>%
#       layout(
#         title = "Revenue vs Employees",
#         xaxis = list(title = "Employees"),
#         yaxis = list(title = "Revenue")
#       )
#   })
# 
#   # Link the map and table (plotly requires special handling)
#   registry <- link_plots(
#     session,
#     map = business_data,
#     table = business_data,
#     shared_id_column = "business_id"
#   )
# 
#   # Handle plotly clicks separately
#   observeEvent(event_data("plotly_click", source = "business_chart"), {
#     clicked_data <- event_data("plotly_click", source = "business_chart")
#     if (!is.null(clicked_data) && !is.null(clicked_data$key)) {
#       # Update the registry selection
#       registry$set_selection(clicked_data$key, "chart")
#     }
#   })
# 
#   # Display selection info
#   output$selection_info <- renderText({
#     selection <- registry$get_selection()
#     if (!is.null(selection$selected_id)) {
#       data <- business_data()
#       selected <- data[data$business_id == selection$selected_id, ]
#       if (nrow(selected) > 0) {
#         paste0(
#           "Selected: ", selected$name, "\n",
#           "Source: ", selection$source, "\n",
#           "Revenue: $", format(selected$revenue, big.mark = ","), "\n",
#           "Employees: ", selected$employees
#         )
#       }
#     } else {
#       "No selection"
#     }
#   })
# }

## ----summary-table------------------------------------------------------------
# # In your server function
# output$category_summary <- renderDT({
#   data <- business_data()
# 
#   summary_data <- data %>%
#     group_by(category) %>%
#     summarise(
#       count = n(),
#       avg_revenue = mean(revenue),
#       total_employees = sum(employees),
#       .groups = "drop"
#     )
# 
#   datatable(
#     summary_data,
#     selection = "single",
#     rownames = FALSE,
#     options = list(pageLength = 5, searching = FALSE)
#   ) %>%
#     formatCurrency("avg_revenue", currency = "$", digits = 0)
# })
# 
# # Link it by adding to your link_plots call
# link_plots(
#   session,
#   map = business_data,
#   table = business_data,
#   summary = business_data,  # Same data, different view
#   shared_id_column = "business_id"
# )

## ----time-series--------------------------------------------------------------
# # Reactive chart that updates with selection
# output$monthly_trend <- renderPlotly({
#   registry <- get_registry()  # However you store your registry
#   selection <- registry$get_selection()
# 
#   if (!is.null(selection$selected_id)) {
#     # Get monthly data for selected business
#     selected_business <- business_data()[
#       business_data()$business_id == selection$selected_id,
#     ]
# 
#     # Generate monthly data (example)
#     monthly_data <- data.frame(
#       month = 1:12,
#       revenue = selected_business$revenue / 12 * runif(12, 0.8, 1.2)
#     )
# 
#     plot_ly(
#       data = monthly_data,
#       x = ~month,
#       y = ~revenue,
#       type = "scatter",
#       mode = "lines+markers"
#     ) %>%
#       layout(
#         title = paste("Monthly Trend:", selected_business$name),
#         xaxis = list(title = "Month"),
#         yaxis = list(title = "Revenue")
#       )
#   } else {
#     # Empty chart with instructions
#     plot_ly() %>%
#       add_annotations(
#         text = "Select a business to view trends",
#         x = 0.5, y = 0.5,
#         xref = "paper", yref = "paper",
#         showarrow = FALSE
#       )
#   }
# })

## ----state-management---------------------------------------------------------
# server <- function(input, output, session) {
# 
#   # Centralized selection state
#   current_selection <- reactiveVal(NULL)
# 
#   # Business data
#   business_data <- reactive({
#     # your data
#    })
# 
#   # Set up linking with global callback
#   registry <- link_plots(
#     session,
#     map = business_data,
#     table = business_data,
#     shared_id_column = "business_id",
# 
#     # Update centralized state
#     on_selection_change = function(selected_id, selected_data, source_id, session) {
#       current_selection(selected_data)
# 
#       # Log for debugging
#       cat("Selection changed:", selected_id, "from", source_id, "\n")
#     }
#   )
# 
#   # All outputs can react to current_selection()
#   output$detail_panel <- renderUI({
#     selected <- current_selection()
#     if (!is.null(selected)) {
#       # Rich detail panel
#       fluidRow(
#         column(6,
#           h4("Business Details"),
#           p("Name:", selected$name),
#           p("Category:", selected$category)
#         ),
#         column(6,
#           h4("Performance"),
#           p("Revenue:", scales::dollar(selected$revenue)),
#           p("Employees:", selected$employees)
#         )
#       )
#     } else {
#       div("Select a business to view details")
#     }
#   })
# 
#   output$related_businesses <- renderDT({
#     selected <- current_selection()
#     if (!is.null(selected)) {
#       # Show businesses in same category
#       related <- business_data()[
#         business_data()$category == selected$category &
#         business_data()$business_id != selected$business_id,
#       ]
# 
#       datatable(
#         related[, c("name", "revenue", "employees")],
#         caption = paste("Other", selected$category, "businesses"),
#         options = list(pageLength = 5)
#       )
#     }
#   })
# }