A lightweight yet powerful framework for building robust data analysis pipelines. With pipeflow, you initialize a pipeline with your dataset and construct workflows step by step by adding R functions. You can modify, remove, or insert steps and parameters at any stage, while pipeflow ensures the pipeline’s integrity.
Overall, pipeflow offers a beginner-friendly framework that simplifies and streamlines the development of data analysis pipelines by making them modular, intuitive, and adaptable. Thanks to its intuitive interface, using pipeflow quickly pays off.
Why use pipeflow
- Easy to learn yet suited for complex workflows
- Automatically manages function dependencies
- Promotes standardized, modular, and reproducible analyses
- Simplifies error handling, debugging, and reusability
Key features
- Flexible Application: Use interactively or programmatically in R
- Dependency Management: Dependencies checked at definition time always ensure the pipeline’s integrity
- Comprehensive Logging: Logs each step, with customizable logger options
- Parameter Control: View and manage all analysis parameters in one place
- Modular Composition: Modify, extend, and combine pipelines effortlessly
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Intelligent Execution: Skip steps already up-to-date, similar to
make - Visualization: View pipelines in both tabular and graphical formats
Advanced features
- Dynamic Branching: Apply the same pipeline to multiple datasets seamlessly
- Self-Modifying: Pipelines can adapt and modify themselves at runtime
Installation
# Install release version from CRAN
install.packages("pipeflow")
# Install development version from GitHub
devtools::install_github("rpahl/pipeflow")