Quantitative Development and Research-Oriented Systems: R Package Development

This article is part of a series on the design and development of research-grade quantitative software systems, highlighting how software engineering principles improve the scalability, maintainability, and reproducibility of analytical workflows.

In quantitative research, data processing, modeling, and visualization often rely on recurring computational routines. Encapsulating these routines into reusable functions reduces code duplication, improves consistency, and simplifies maintenance.

As projects grow, managing functions through standalone scripts becomes increasingly inefficient. Organizing them into an R package provides a structured framework for code reuse, testing, documentation, version control, and distribution, supporting the development of modular and extensible analytical systems.

The R ecosystem offers a mature set of tools for package development, enabling researchers and quantitative developers to build reusable analytical components following established software engineering practices.

The examples below present a practical workflow for creating and maintaining custom R packages based on my own development experience.

While the exact implementation may vary across projects, the process presented here has proven effective and can serve as a starting point for further refinement.

 Set up the core tools of the R ecosystem: 

These select tools are for the development, documentation, testing and maintenance. 

install.packages(c("devtools", "usethis", "testthat", "roxygen2"))

Some times the installation process will return an error associated to dependencies. If this happens, only update it and reinstall the development tools.

install.packages("promises")

update.packages(ask = FALSE)

install.packages(c("shiny", "miniUI", "devtools"))

Start, practice, practice and practice:

# //////////////////////////////////////////////////////////////////////////// #

# //////////////////////////////////////////////////////////////////////////// #

# //////////////////////////////////////////////////////////////////////////// #

# //////////////////////////////////////////////////////////////////////////// #

# ------------------------------------------------------------------------------

# CREAR UN PAQUETE DE R

# ------------------------------------------------------------------------------

 

library(devtools)

library(usethis)

# ------------------------------------------------------------------------------

# Crear la estructura base del paquete

create_package("./repo/package_name")

setwd("./repo/package_name")

getwd()

# Configurar tests (crea la estructura)

use_testthat()

# ------------------------------------------------------------------------------

# Crear archivo para funciones de R (R/line_fig.R)

use_r("line_fig")

# Escribir la función en R/line_fig.R con documentación roxygen2

# Ejemplo:

#

# #' Create a line plot

# #'

# #' @param x Numeric vector

# #' @param y Numeric vector

# #' @return A line plot

# #' @export

# line_fig <- function(x, y) {

#   plot(x, y, type = "l")

# }

# ------------------------------------------------------------------------------

# Crear archivo de test (genera un archivo tests/testthat/test-line_fig.R)

use_test("line_fig")

# Ilustracion de un test:

# test_that("line_fig runs without error", {

#   expect_no_error(line_fig(1:10, 1:10))

# })

# ------------------------------------------------------------------------------

# Generar documentación y NAMESPACE

document()

# Ejecutar pruebas

test()

# Revisión completa

check()

# Construir paquete (genera un archivo package_name_1.0.0.tar.gz)

build()

# Instalar paquete localmente

install()

# devtools::install() #desde la carpeta del paquete

# o:

# install.packages("package_name_1.0.0.tar.gz", repos = NULL, type = "source")

# ------------------------------------------------------------------------------

 

# ------------------------------------------------------------------------------

# ACTUALIZATION OF PACKAGES

setwd("./GitHub/package_name")

library(devtools)

# editar funciones y tests

document()

test()

check()

build()

# detach("package:package_name", unload = TRUE)

install()

# update.packages("autoecoreportpk_1.0.tar.gz")

# ------------------------------------------------------------------------------

 Base on my experience, be careful with special characters in .Rd files. Because It could cause fail errors in too many cases.