A lightweight yet powerful framework for building robust data analysis
pipelines. With pipeflow, you initialize a pipeline with your dataset
and construct your workflow step by step by seamlessly adding R
functions. Modify, remove, or insert steps at any stage while pipeflow
ensures the integrity and correctness of your pipeline.
Designed to help you focus on the what rather than the how, this package simplifies the implementation of complex workflows, making even large-scale data analysis projects manageable, adaptable, and reusable with ease.
- Easy to learn yet suited for complex workflows
- Automatically manages function dependencies
- Promotes standardized, reproducible analysis
- Simplifies error handling, debugging, and reusability
- Flexible Application: Use interactively or programmatically in R
- Dependency Management: Dependencies checked at definition, ensuring reliable workflows
- 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: