README.md

In beerda/rmake: Makefile Generator for R Analytical Projects

rmake

Makefile generator for R analytical projects

Installation

To install rmake, simply issue the following command within your R session:

install.packages("devtools")
library(devtools)
devtools::install_github("beerda/rmake")

Setup

The package requires the R_HOME environment variable to be properly set.

Basic Usage

Suppose you have a file dataset.csv. You want to pre-process it and store the results into dataset.rds within the preprocess.R R script. After that, dataset.rds is then an input file for report.Rmd and details.Rmd, which are R-Markdown scripts that generate report.pdf and details.pdf. The whole project can be initialized with rmake as follows:

1. Let us assume that you have rmake package as well as the make tool properly installed.
2. Create a new directory (or an R studio project) and copy your dataset.csv into it.
3. Load rmake and create skeleton files for rmake: r library(rmake) rmakeSkeleton('.') Makefile.R and Makefile will be created.
4. Create your file preprocess.R, report.Rmd and details.Rmd.
5. Edit Makefile.R as follows: r library(rmake) job <- c('dataset.csv' %>>% rRule('preprocess.R') %>>% 'dataset.rds' %>>% markdownRule('report.Rmd') %>>% 'report.pdf', 'dataset.rds' %>>% markdownRule('details.Rmd') %>>% 'details.pdf') ) makefile(job, 'Makefile') This will create three build rules: processing of preprocess.R and execution of report.Rmd and details.Rmd in order to generate resulting PDF files.
6. Run make or build your project in R Studio (Build/Build all). This will automatically re-generate Makefile and execute preprocess.R and the generation of report.Rmd and details.Rmd accordingly to the changes made to source files.

Advanced Usage

Coming soon.

beerda/rmake documentation built on July 2, 2022, 6:24 p.m.