dflow

An opinionated lightweight template for smooth drake flows.

Installation

remotes::install_github("milesmcbain/dflow")

Set dependencies = TRUE to also install capsule, conflicted, dontenv, and drake.

Usage

dflow::use_dflow():

 ./
 |_ R/
 |  |_ plan.R
 |
 |_ _drake.R
 |_ packages.R
 |_ .env

dflow::use_rmd("analysis.Rmd"):

v Creating 'doc/'
v Writing 'doc/analysis.Rmd'
Add this target to your drake plan:

target_name = target(
  command = {
    rmarkdown::render(knitr_in("doc/analysis.Rmd")),
    file_out("doc/analysis.html")
  }
)

(change output extension as appropriate if output is not html)
library(rmarkdown) added to ./packages.R

dflow::use_gitignore():

Drop in a starter ./.gitignore with ignores for drake and renv among others.

About

dflow tries to set up a minimalist ergonomic workflow for drake pipeline development. To get the most out of it follow these tips:

1. Put all your target code in separate functions in R/. Use fnmate to quickly generate function definitions in the right place. Let plan.R define the structure of the workflow and use it as a map for your sources. Use 'jump to function' to quickly navigate to them.

2. Use a call r_make() to kick off building your plan in a new R session (via callr). _drake.R is setup to make this work. Bind a keyboard shortcut to this using the addin in drake.

3. Put all your library() calls into packages.R. This way you'll have them in one place when you go to add sandboxing with renv, packarat, and switchr etc.

4. Take advantage of automation for loading drake targets at the cursor with the 'loadd target at cursor' addin.

Opinions

Some things are baked into the template that will help you avoid common pitfalls and make your project more reproducible:

1. library(conflicted) is called in packages.R to detect package masking issues.

2. .env is added carrying the following options to avoid misuse of logical vector tests:

_R_CHECK_LENGTH_1_LOGIC2_=verbose
_R_CHECK_LENGTH_1_CONDITION_=true