matt-dray

# The Strategy Unit C&C, 2025-11-06: collaborating using Github

## Focus

This is about using the GitHub interface for [pull requests (PRs)](https://docs.github.com/en/pull-requests) from the perspective of the assignee (submitter) and reviewer.
I'm concentrating on a pull request to a repository that you have access to, e.g. in [The-Strategy-Unit GitHub organisation](https://github.com/The-Strategy-Unit/).

## Why?

Pull requests are important because they help:

matt-dray

#!/usr/bin/env -S uv run

# /// script
# requires-python = ">=3.12"
# dependencies = [
#     "datetime",
#     "httpx",
# ]
# ///

matt-dray

ui <- bslib::page_fillable(
  bslib::card(
    bslib::card_header("Gacha"),
    shiny::textOutput("rolled_details"),
    shiny::textOutput("rolled_emoji"),
    shiny::actionButton("btn_roll", "Roll!")
  ),
  bslib::card(
    bslib::card_header("Collection"),
    shiny::tableOutput("dex")

matt-dray

# hex sticker for {aftables}:
#  https://github.com/best-practice-and-impact/aftables

# having installed the Free Sans font:
#   https://www.fontspace.com/freesans-font-f13276
# and installed {gex}:
remotes::install_github("matt-dray/gex")
# and {ggplotify}:
install.packages("ggplotify")

matt-dray

set.seed(123)
n <- 5
scheme <- paste("Scheme", 1:n)
mitigator <- paste("Mitigator", LETTERS[1:n])
combos <- tidyr::crossing(scheme, mitigator)
nrows <- nrow(combos)
dat <- combos |>
  dplyr::mutate(
    mitigator_group = dplyr::if_else(
      stringr::str_detect(mitigator, " [ABC]$"),

matt-dray

# Calculate how many plots will be produced
count_plots <- function(df, var) {
  length(unique(df[[var]]))
}

# Plot faceted chart, save with height dependent on plot count
write_responsive_facets <- function(
  df, 
  var = "species",
  plot_count = count_plots(df, var), 

matt-dray

# {nara} by Mike Cheng: https://coolbutuseless.github.io/package/nara/index.html
# Kenney by Kenney: https://www.kenney.nl

# Read png tiles

tile_paths <- list.files(
  "~/Desktop/kenney/kenney_tiny-dungeon/Tiles",
  pattern = ".png$",
  full.names = TRUE,
  recursive = TRUE

matt-dray

# 1. Generate temporary Excel files ----

# Make a temporary spreadsheet with named sheets
make_temp_xlsx <- function(sheet_names) {
  wb <- openxlsx2::wb_workbook()
  for (sheet in sheet_names) wb <- wb |> openxlsx2::wb_add_worksheet(sheet)
  temp <- openxlsx::temp_xlsx()
  openxlsx2::wb_save(wb, temp)
}

matt-dray

#' Convenience Function: Read a (Zipped) JSON File from an Azure Container
#'
#' @param container A blob_container/storage_container object. Probably
#'     generated by [connect_to_container].
#' @param file Character. Path to file within the container named by
#'     `container`.
#'
#' @return A list.
#' @export
#'

matt-dray

generate_num_format <- function(number = 8634567.890) {
  
  num_val <- number %/% 1
  num_dp <- number %% 1
  
  num_split <- strsplit(as.character(number), "\\.")[[1]]
  n_dp <-  nchar(num_split[2])
  
  num_commas <- scales::number(as.numeric(num_val), big.mark = ",")
  fmt_out <- gsub("[[:digit:]]", "#", num_commas)