https://github.com/beerda/rmake

Makefile generator for analytical projects in R
https://github.com/beerda/rmake

makefile r rmake

Last synced: 5 months ago
JSON representation

Makefile generator for analytical projects in R

• Host: GitHub
• URL: https://github.com/beerda/rmake
• Owner: beerda
• Created: 2018-01-22T08:34:28.000Z (about 7 years ago)
• Default Branch: master
• Last Pushed: 2022-06-30T09:06:32.000Z (almost 3 years ago)
• Last Synced: 2024-08-13T07:11:13.204Z (8 months ago)
• Topics: makefile, r, rmake
• Language: R
• Homepage:
• Size: 269 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

• jimsghstars - beerda/rmake - Makefile generator for analytical projects in R (R)

README

        
[![Travis Build Status](https://travis-ci.org/beerda/rmake.svg?branch=master)](https://travis-ci.org/beerda/rmake) [![AppVeyor Build Status](https://ci.appveyor.com/api/projects/status/github/beerda/rmake?branch=master&svg=true)](https://ci.appveyor.com/project/beerda/rmake) [![codecov](https://codecov.io/gh/beerda/rmake/branch/master/graph/badge.svg)](https://codecov.io/gh/beerda/rmake) [![CRAN\_Status\_Badge](http://www.r-pkg.org/badges/version/rmake)](https://cran.r-project.org/package=rmake)

rmake

=====

Makefile generator for R analytical projects

Installation

------------

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

``` r

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.