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The targets R package (Landau, 2020) is a pipeline toolkit for computationally intense reproducible research. It reduces the time and effort required to develop a data analysis project and maintain a trustworthy set of results. targets uses static code analysis to detect dependency relationships among interconnected computational tasks and construct a directed acyclic graph (DAG), which researchers can visualize in order to understand and communicate the structure of a complicated workflow. To run the pipeline at scale, targets leverages implicit parallel computing and optional cloud storage. In subsequent runs, targets, skips tasks that are already synchronized with their upstream dependencies, which not only reduces the runtime of rapidly developing workflows, but also provides tangible evidence of reproducibility.

The targets R package: a dynamic Make-like function-oriented pipeline toolkit for reproducibility and high-performance computing