/make_tutorial

Primary LanguageR

Make tutorial

End-to-end reproducibility

TL; DR

  • Clone this repo (make sure to start a new Rproject associated with it)
  • Check that you have GNU Make on your device
  • Make sure you have these three packages installed: here, tidyverse, modelsummary

The goal

We'll simulate everyone's nightmare:

  • You have built your "coding pipeline" (see scripts and draft.Rmd) and are ready to do something with it
  • Then, you (or a colleague) finds an error in the raw data (crisis!!!)
  • You fix the error, and now have to rerun the ENTIRE analysis (which script did what, again? What depended on what?)
  • By the time you are done figuring this out, you've also gotten your hands on more data so... gotta re-run everything again

The solution to this: one file (Makefile) and one command: Make

What you'll need

Get the materials

This repository contains everything we'll need for the session. Having git installed will make it easier (simply clone this repo). But, if you don't have it yet you can either follow this other tutorial or, simply download the entire thing as a compressed folder.

Do I have GNU make?

Open a terminal (or use the Terminal pane in RStudio) and type:

make -v                                     #checks version of GNU make

Should show something like this (really, anything that is not an error should work):

>GNU Make 3.81
>Copyright (C) 2006  Free Software Foundation, Inc.
>This is free software; see the source for copying conditions.
>There is NO warranty; not even for MERCHANTABILITY or FITNESS FOR A
>PARTICULAR PURPOSE.

Don't have it? This might help:

R packages

There are two options to make sure you have all the dependencies for this project.

Simply use the included renv environment:

renv::restore()                                # Follow the instructions

OR, manually install them if you don't already have them

renv::deactivate()                             # Deactivate the renv environment first
pkgs <- c("tidyverse", "here", "modelsummary") # List of packages needed
lapply(pkgs, install.packages)                 # Install all packages

Optional dependencies

To install both, follow the instructions here

Other resources

General

R-specific: