The {drake} package by Will Landau 'is a pipeline toolkit and a scalable, R-focused solution for reproducibility and high-performance computing.' Tagline: 'what gets done stays done'.

This repo contains a {drake} workflow for creating a demo statistics publication using the latest UK egg statistics as its input.

You can:

• read my blog post about how {drake} could be helpful for the UK government's Reproducible Analytical Pipelines approach to producing statistical publications
• launch the contents of this repo in a live browser instance of RStudio by clicking the 'launch binder' badge above (read another blog post about why this is awesome
• take a look at a presentation I gave about {drake} at a couple of cross-government Coffee & Coding events
• download or clone this repo to serve as the basis for your own {drake} pipeline
• download a clean {drake} project template example with drake::drake_example("main").

In short:

1. Run make.R to execute the workflow that creates the report
2. Change stuff
3. Run make.R again to bring everything up to date ({drake} only runs the things that are out-of-date)

You need only run the contents of make.R to execute the workflow, which will source files from R/ and Rmd/ folders and create the output report in the Rmd/ folder (intermediate objects are added to the hidden .drake/ folder).

If you change part of the workflow (e.g. change the chart title in the create_plot() function of the functions.R script) you don't have to re-run everything, or try to remember exactly which files need to be re-run. {drake} does this for you.

Instead, you can redo source(functions.R) and outdated(egg_plan) will tell you the files that have been updated or impacted by that update. You can bring up to date by executing make(egg_plan) again.

A helpful addition is that you can visualise the dependency network (and its outdated version) by passing the drake_config() object to vis_drake_graph() (code is supplied for this in make.R file).

For purposes of recreating this demo, the relevant file structure is as follows:

drake-egg-rap/
├── .drake/
├── data/
│   └── eggs-packers-02may19a.ods
├── egg-report.Rmd
├── R/
│   ├── functions.R
│   ├── packages.R
│   └── plan.R
└── make.R

All other files and folders are related to git, GitHub or Binder and can be ignored. It might be helpful to use the 'drake-egg-rap.Rproj' file if you're familiar with RStudio Projects.