An opinionated lightweight template for smooth targets flows.

A sibling of dflow

remotes::install_github("milesmcbain/tflow")

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

tflow::use_tflow():

 ./
 |_ R/
 |_ _targets.R
 |_ packages.R
 |_ .env

tflow::use_rmd("analysis"):

√ Creating 'doc/'
√ Writing 'doc/analysis.Rmd'
Add this target to your tar_plan():

tar_render(report, "doc/analysis..Rmd")

√ library(rmarkdown) added to ./packages.R

tflow::use_gitignore():

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

tflow is a port of dflow from drake to targets. targets can be used many ways, and it turns out it can be used in an almost identical workflow to dflow.

tflow tries to set up a minimalist ergonomic workflow for targets 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 the plan in _targets.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 tar_make() to kick off building your plan in a new R session.

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 targets targets at the cursor with the 'load target at cursor' addin. Or the tflow addin: 'load editor targets' to load all targets referred to in the current editor.

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