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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() from targets deletes all existing artifacts, clearing the project’s state.
  • clean_structure() from repana cleans up all output directories, ensuring no residual files interfere with new runs.

Running the Analysis

Once the environment is set up and cleaned, you can run the analysis using:


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.


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.