Introduction
The repana package enhances the setup and management of
analysis environments, particularly integrating with
targets, a pipeline tool for computationally demanding
projects. This vignette outlines how to use repana in
conjunction with targets to streamline your workflows.
Setting up targets with repana
repana includes the function
targets_structure(), which prepares a directory layout
compatible with targets:
- R/ Directory for function source files.
- dat/ Directory to keep source data used in the project
- rmd/ Directory for R Markdown report files.
- out/ Directory to store output or shared artifacts
- _targets.R Skeleton to define targets
- _template_txt Documentation skeleton
- config.yml To handle directories and templates
The .gitignore file is update (or created if missing) to exclude from the Git repository the dat/, out/ and _targets directories.
Managing Project Artifacts
To manage project artifacts efficiently, repana provides
utilities to clear previous results and reset the analysis
environment:
-
tar_destroy()fromtargetsdeletes all existing artifacts, clearing the project’s state. -
clean_structure()fromrepanacleans up all output directories, ensuring no residual files interfere with new runs.
tar_destroy()
clean_structure()Running the Analysis
Once the environment is set up and cleaned, you can run the analysis using:
tar_make()tar_make() executes the analysis pipeline, processing
only the necessary components that have changed or are not up to date.
This ensures your analyses are both fast and reliable.
Conclusion
Integrating repana with targets not only
simplifies the setup and management of your projects but also enhances
the efficiency and reliability of your workflows. By organizing project
elements into a structured directory layout and providing tools for
managing artifacts, repana ensures that your analyses are
robust and your results are trustworthy.