In RinteRface/connectViz: Visualize Your 'RStudio Connect' Server Usage Data

#remotes::install_github("RinteRface/connectViz")
library(connectapi) # Tested with 0.1.0.9031
library(connectViz)
library(dplyr)
library(shiny)
library(bslib)

rsc_client <- create_rsc_client()
knitr::opts_chunk$set(echo = FALSE, warning=FALSE)

# Get raw data from RSC database
apps_usage <- rsc_client %>% get_usage_shiny(limit = Inf)
rsc_content <- rsc_client %>% get_content()
# Remove locked users?
rsc_users <- rsc_client %>% get_users(limit = Inf) %>% 
  filter(locked == FALSE)
publishers <- rsc_users %>% filter(user_role == "publisher") 
shiny_apps <- rsc_content %>% filter(app_mode == "shiny")

# TO DO
# rsc_static <- rsc_client %>% get_usage_static(limit = Inf)

General metrics (n)

general_metrics <- list(
  "Onboarded Users" = nrow(rsc_users),
  "Publishers" = nrow(publishers),
  "Deployments" = nrow(rsc_content),
  "Shiny Apps" = nrow(shiny_apps)
)

general_metrics_cards <- purrr::map(
  seq_along(general_metrics),
  function(i) {
    value_box(
      value = general_metrics[[i]],
      title = names(general_metrics)[[i]]
    )
  }
)

layout_column_wrap(
  width = 1/4,
  !!!general_metrics_cards
)

Shiny Apps usage

Important note: with a basic publisher API key, we can only recover the data for the app we own. It means that we are not able to track any other apps, including the one shared with us as maintainer. An admin API has access to all usage data.

Most used apps

dateRangeInput(
  "date_range",
  "Select the app usage range:",
  start = Sys.Date() - 10,
  end = Sys.Date()
)
apps_ranking <- create_app_ranking(
  rsc_content, 
  rsc_users, 
  apps_usage,
  start_date = reactive(input$date_range[1]),
  end_date = reactive(input$date_range[2])
)

renderUI({
  card(
    full_screen = TRUE,
    title = sprintf("Ranking between %s and %s", input$date_range[1], input$date_range[2]),
    create_app_ranking_table(apps_ranking),
  )
})

Daily app usage

daily_app_usage <- get_app_daily_usage(apps_ranking()[[2]], reactive(input$selected_app))

renderUI({
  card(
    full_screen = TRUE,
    card_header("App usage"),
    layout_sidebar(
      sidebar = sidebar(
        width = 150,
        selectInput(
          "selected_app", 
          "Select an application", 
          apps_ranking()[[2]]$app_name
        )
      ),
      p("Daily app usage"),
      create_app_daily_usage_chart(daily_app_usage),
      create_cumulated_duration_per_user(
        apps_ranking()[[1]],
        selected_app = reactive(input$selected_app)
      ),
      create_cumulated_hits_per_user(
        apps_ranking()[[1]], 
        selected_app = reactive(input$selected_app)
      )
    )
  )
})

Consumer data

consumer_ranking <- create_apps_consumer_ranking(apps_usage, rsc_users)
consumer_ranking_card <- card(
  full_screen = TRUE,
  card_header("Consumer ranking"),
  layout_sidebar(
    sidebar = sidebar(
      width = 150,
      numericInput(
        "views_threshold",
        "N view threshold",
        1,
        min = 0
      )
    ),
    create_apps_consumer_ranking_chart(
      consumer_ranking, reactive(input$views_threshold)
    )
  )
)

daily_consumption <- get_user_daily_consumption(rsc_content, rsc_users, apps_usage, reactive(input$selected_user))
daily_consumption_card <- card(
  full_screen = TRUE,
  card_header("Daily app consumption"),
  layout_sidebar(
    sidebar = sidebar(
      width = 150,
      selectInput("selected_user", "Select a user", rsc_users$username)
    ),
    create_user_daily_consumption_chart(daily_consumption[[2]])
  )
)

layout_column_wrap(
  width = 1/2,
  daily_consumption_card,
  consumer_ranking_card
)

Developers data

developers_apps_ranking <- create_dev_ranking(rsc_users, rsc_content)
max_app <- developers_apps_ranking %>% pull(n_apps) %>% max()
dev_ranking_card <- card(
  full_screen = TRUE,
  card_header("Developers ranking n deployments (static, shiny, rmd, ...)"),
  layout_sidebar(
    sidebar = sidebar(
      width = 150,
      numericInput(
        "apps_threshold",
        "N app threshold",
        round(max_app / 2),
        min = 1,
        max = max_app
      )
    ),
    create_dev_ranking_chart(
      developers_apps_ranking, 
      reactive(input$apps_threshold)
    )
  )
)

dev_projects_card <- card(
  full_screen = TRUE,
  card_header("Dev projects overview (Shiny apps only)"),
  layout_sidebar(
    sidebar = sidebar(
      width = 150,
      selectInput(
        "app_developer",
        "Select a developer",
        developers_apps_ranking$username
      )
    ),
    create_dev_project_overview(
      rsc_client, apps_ranking()[[1]], 
      reactive(input$app_developer)
    )
  )
)

layout_column_wrap(
  width = 1/2,
  dev_ranking_card,
  dev_projects_card
)

General data

# I realized some users are not active (ie active_time is NA).
# Maybe to remove from the viz in the future?
user_roles <- card(
  full_screen = TRUE,
  card_header("User roles"),
  sort_users_by_role(rsc_users) |> create_pie_chart("user_role")
)

content_access <- card(
  full_screen = TRUE,
  card_header("Content access type"),
  sort_content_by_access(rsc_content) |> create_pie_chart("access_type")
)

r_versions <- card(
  full_screen = TRUE,
  card_header("R versions"),
  sort_content_by_rversion(rsc_content) |> create_pie_chart("r_version")
)

py_versions <- card(
  full_screen = TRUE,
  card_header("Python versions"),
  sort_content_by_pyversion(rsc_content) |> create_pie_chart("py_version")
)

content_type <- card(
  full_screen = TRUE,
  card_header("Content type"),
  sort_content_by_appmode(rsc_content) |> create_pie_chart("app_mode")
)

layout_column_wrap(
  width = 1/2,
  user_roles,
  content_access,
  r_versions,
  py_versions,
  content_type
)

RinteRface/connectViz documentation built on Feb. 3, 2024, 10:40 a.m.