Merge pull request #1 from dfe-analytical-services/initial-setup

Initial setup

global.R

@@ -1,122 +1,123 @@
-# -----------------------------------------------------------------------------
-# This is the global file.
-#
-# Use it to store functions, library calls, source files etc.
-#
-# Moving these out of the server file and into here improves performance as the
-# global file is run only once when the app launches and stays consistent
-# across users whereas the server and UI files are constantly interacting and
-# responsive to user input.
-#
-# Library calls ---------------------------------------------------------------
-shhh <- suppressPackageStartupMessages # It's a library, so shhh!
-
-# Core shiny and R packages
-shhh(library(shiny))
-shhh(library(bslib))
-shhh(library(rstudioapi))
-
-# Custom packages
-shhh(library(dfeR))
-shhh(library(dfeshiny))
-shhh(library(shinyGovstyle))
-
-# Creating charts and tables
-shhh(library(ggplot2))
-shhh(library(DT))
-
-# Data and string manipulation
-shhh(library(dplyr))
-shhh(library(stringr))
-shhh(library(ggiraph))
-
-# Shiny extensions
-shhh(library(shinyjs))
-shhh(library(tools))
-shhh(library(shinydashboard))
-shhh(library(shinyWidgets))
-shhh(library(shinytitle))
-shhh(library(xfun))
-shhh(library(metathis))
-shhh(library(shinyalert))
-
-# Dependencies needed for testing or CI but not for the app -------------------
-# Including them here keeps them in renv but avoids the app needlessly loading
-# them, saving on load time.
-if (FALSE) {
-  shhh(library(shinytest2))
-  shhh(library(testthat))
-}
-
-# Source scripts --------------------------------------------------------------
-
-# Source any scripts here. Scripts may be needed to process data before it gets
-# to the server file or to hold custom functions to keep the main files shorter
-#
-# It's best to do this here instead of the server file, to improve performance.
-
-# Source script for loading in data
-source("R/read_data.R")
-
-# Source custom functions script
-source("R/helper_functions.R")
-
-# Source all files in the ui_panels folder
-lapply(list.files("R/ui_panels/", full.names = TRUE), source)
-
-# Set global variables --------------------------------------------------------
-
-site_title <- "Department for Education (DfE) Shiny Template" # name of app
-parent_pub_name <- "Statistical publication" # name of source publication
-parent_publication <- # link to source publication
-  "https://explore-education-statistics.service.gov.uk/find-statistics/apprenticeships"
-
-# Set the URLs that the site will be published to
-site_primary <- "https://department-for-education.shinyapps.io/dfe-shiny-template/"
-site_overflow <- "https://department-for-education.shinyapps.io/dfe-shiny-template-overflow/"
-
-# Combine URLs into list for disconnect function
-# We can add further mirrors where necessary. Each one can generally handle
-# about 2,500 users simultaneously
-sites_list <- c(site_primary, site_overflow)
-
-# Set the key for Google Analytics tracking
-google_analytics_key <- "Z967JJVQQX"
-
-# End of global variables -----------------------------------------------------
-
-# Enable bookmarking so that input choices are shown in the url ---------------
-enableBookmarking("url")
-
-# Read in the data ------------------------------------------------------------
-df_revbal <- read_revenue_data()
-
-# Get geographical areas from data
-df_areas <- df_revbal %>%
-  select(
-    geographic_level, country_name, country_code,
-    region_name, region_code,
-    la_name, old_la_code, new_la_code
-  ) %>%
-  distinct()
-
-# Extract lists for use in drop downs -----------------------------------------
-# LA list
-choices_las <- df_areas %>%
-  filter(geographic_level == "Local authority") %>%
-  select(geographic_level, area_name = la_name) %>%
-  arrange(area_name)
-
-# Full list of areas
-choices_areas <- df_areas %>%
-  filter(geographic_level == "National") %>%
-  select(geographic_level, area_name = country_name) %>%
-  rbind(
-    df_areas %>%
-      filter(geographic_level == "Regional") %>%
-      select(geographic_level, area_name = region_name)
-  ) %>%
-  rbind(choices_las)
-
-# List of phases
-choices_phase <- unique(df_revbal$school_phase)
+# -----------------------------------------------------------------------------
+# This is the global file.
+#
+# Use it to store functions, library calls, source files etc.
+#
+# Moving these out of the server file and into here improves performance as the
+# global file is run only once when the app launches and stays consistent
+# across users whereas the server and UI files are constantly interacting and
+# responsive to user input.
+#
+# Library calls ---------------------------------------------------------------
+shhh <- suppressPackageStartupMessages # It's a library, so shhh!
+
+# Core shiny and R packages
+shhh(library(shiny))
+shhh(library(bslib))
+shhh(library(rstudioapi))
+
+# Custom packages
+shhh(library(dfeR))
+shhh(library(dfeshiny))
+shhh(library(shinyGovstyle))
+
+# Creating charts and tables
+shhh(library(ggplot2))
+shhh(library(DT))
+
+# Data and string manipulation
+shhh(library(dplyr))
+shhh(library(stringr))
+shhh(library(ggiraph))
+
+# Shiny extensions
+shhh(library(shinyjs))
+shhh(library(tools))
+shhh(library(shinydashboard))
+shhh(library(shinyWidgets))
+shhh(library(shinytitle))
+shhh(library(xfun))
+shhh(library(metathis))
+shhh(library(shinyalert))
+
+# Dependencies needed for testing or CI but not for the app -------------------
+# Including them here keeps them in renv but avoids the app needlessly loading
+# them, saving on load time.
+if (FALSE) {
+  shhh(library(shinytest2))
+  shhh(library(testthat))
+  shhh(library(lintr))
+}
+
+# Source scripts --------------------------------------------------------------
+
+# Source any scripts here. Scripts may be needed to process data before it gets
+# to the server file or to hold custom functions to keep the main files shorter
+#
+# It's best to do this here instead of the server file, to improve performance.
+
+# Source script for loading in data
+source("R/read_data.R")
+
+# Source custom functions script
+source("R/helper_functions.R")
+
+# Source all files in the ui_panels folder
+lapply(list.files("R/ui_panels/", full.names = TRUE), source)
+
+# Set global variables --------------------------------------------------------
+
+site_title <- "Local Authority Interactive Tool (LAIT)" # name of app
+parent_pub_name <- "LAIT publication" # name of source publication
+parent_publication <- # link to source publication
+  "https://www.gov.uk/government/publications/local-authority-interactive-tool-lait"
+
+# Set the URLs that the site will be published to
+site_primary <- "https://department-for-education.shinyapps.io/local-authority-interactive-tool/"
+site_overflow <- "https://department-for-education.shinyapps.io/local-authority-interactive-tool-overflow/"
+
+# Combine URLs into list for disconnect function
+# We can add further mirrors where necessary. Each one can generally handle
+# about 2,500 users simultaneously
+sites_list <- c(site_primary, site_overflow)
+
+# Set the key for Google Analytics tracking
+google_analytics_key <- "Z967JJVQQX"
+
+# End of global variables -----------------------------------------------------
+
+# Enable bookmarking so that input choices are shown in the url ---------------
+shiny::enableBookmarking("url")
+
+# Read in the data ------------------------------------------------------------
+df_revbal <- read_revenue_data()
+
+# Get geographical areas from data
+df_areas <- df_revbal |>
+  dplyr::select(
+    geographic_level, country_name, country_code,
+    region_name, region_code,
+    la_name, old_la_code, new_la_code
+  ) |>
+  dplyr::distinct()
+
+# Extract lists for use in drop downs -----------------------------------------
+# LA list
+choices_las <- df_areas |>
+  dplyr::filter(geographic_level == "Local authority") |>
+  dplyr::select(geographic_level, area_name = la_name) |>
+  dplyr::arrange(area_name)
+
+# Full list of areas
+choices_areas <- df_areas |>
+  dplyr::filter(geographic_level == "National") |>
+  dplyr::select(geographic_level, area_name = country_name) |>
+  rbind(
+    df_areas |>
+      dplyr::filter(geographic_level == "Regional") |>
+      dplyr::select(geographic_level, area_name = region_name)
+  ) |>
+  rbind(choices_las)
+
+# List of phases
+choices_phase <- unique(df_revbal$school_phase)