What is a mixed R-Python pipeline?

It is a data analysis workflow that utilizes both R (often for statistics and visualization) and Python (for data processing and logic), typically orchestrated by a tool like Snakemake.

Why turn a Snakemake project into a CLI tool?

Packaging your workflow as a CLI makes it portable, version-controlled, and significantly easier for others to deploy on new datasets without manually copying scripts and Snakefiles.

Can I use this for projects outside of omics or bioinformatics?

Absolutely. While the reference implementation is omics-focused, the logic for wrapping Snakemake into a CLI applies to any data science or engineering pipeline.

Does this skill support the 'uv' package manager?

Yes, the implementation steps utilize 'uv' for rapid project initialization and managing the Python packaging environment.

Mixed R/Python Pipeline CLI Creator

Name: Mixed R/Python Pipeline CLI Creator
Author: CodingKaiser

byCodingKaiser

0•

Data Science & ML

Converts existing Snakemake analysis projects into pip-installable CLI tools for automated workflow deployment.

This skill provides expert guidance for transforming standalone Snakemake analysis projects containing R and Python scripts into professional, pip-installable CLI tools. It automates the process of wrapping a Snakefile and src/ directory into a structured Python package, enabling users to deploy workflows to new project environments using commands like init, validate, and update. It is particularly useful for researchers and data scientists who want to standardize their bioinformatics or omics pipelines into reusable software that handles data discovery and configuration generation automatically.

Key Features

01Includes CLI commands for initialization, validation, and cleanup

02Converts Snakemake workflows into pip-installable CLI packages

03Generates project-specific YAML configurations and boilerplate

040 GitHub stars

05Provides standardized template path resolution for installed packages

06Implements automated data discovery using glob-based patterns

Use Cases

01Deploying a complex R/Python analysis pipeline to multiple new datasets

02Packaging academic research code for reproducibility and easier installation

03Standardizing bioinformatics workflows for team-wide distribution

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add codingkaiser/kaiser-skills mixed-r-python-pipeline

For use in Claude.ai and ChatGPT

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