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.
- Easy to learn yet suited for complex workflows
- Automatically manages function dependencies
- Promotes standardized, modular, and reproducible analyses
- Simplifies error handling, debugging, and reusability
- 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
- Intelligent Execution: Skip steps already up-to-date, similar to
make - Visualization: View pipelines in both tabular and graphical formats
- Dynamic Branching: Apply the same pipeline to multiple datasets seamlessly
- Self-Modifying: Pipelines can adapt and modify themselves at runtime
# Install release version from CRAN
install.packages("pipeflow")
# Install development version from GitHub
devtools::install_github("rpahl/pipeflow")library(pipeflow)It is recommended to read the vignettes in the order they are listed below: