Overview

‘archetyper’ initializes data mining and data science projects by generating common workflow components as well as peripheral files needed to support technical best practices.

Installation

CRAN

The easiest way to get archetyper is to install it from CRAN:

install.packages("archetyper")

To get a bug fix or use a feature from the development version, you can install the development version of ‘archetyper’ from GitHub.

Development Version

#install.packages("devtools")
devtools::install_github("mkorvink/archetyper")

Usage

A new project can be instantiated using the generate() function.

#> library(archetyper)
#> archetyper::generate("majestic_12")
#> list.files("majestic_12/")
[1] "data_input"        "data_output"       "data_working"      "docs"             
[5] "majestic_12.Rproj" "models"            "R"                 "readme.md"
[9] ".gitignore"

#> list.files("majestic_12/R")
 [1] "0_test.R"      "1_integrate.R" "2_enrich.R"    "3_model.R"     "4_evaluate.R" 
 [6] "5_present.Rmd" "api.R"         "common.R"      "explore.R"     "lint.R"       
[11] "mediator.R"    "utilities.R"

A runnable demo project will be created with the generate_demo().

#> archetyper::generate_demo()

You can learn more about ‘archetyper’ in vignette("archetyper").

Acknowledgments

This readme was modeled after the dplyr readme. The ‘archetyper’ hex image was designed by Matthew Nethery. Thanks to Gregor Seyer for the helpful comments in reviewing this package.

Code of conduct

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.