P3 Template | Project, Process, Presentation

🚀 Comprehensive R Project Structure for Efficient Workflows 🛠️
A template designed to streamline your R projects from setup to final presentation, powered by LLMs.
_{Ideal for data scientists, researchers, and R developers seeking a standardized project structure}

_{The R project template. Built with ❤︎ by cedanl and contributors}

📋 Table of Contents

• Motivation
• What P3 Stans For
• Quick Start
• Features
• Project Structure
• Contributing
• License
• Additional Resources

💡 Motivation

The P3 Template addresses common challenges in R project start-up, organization and reproducibility. It provides a standardized structure that:

• Enables secure and high-performance LLM-usage from the IDE.
• Improves project maintainability
• Streamlines the transition from explorative analysis to final presentation

What P3 Stands For:

• Project: A complete, well-organized codebase with good practices incorporated
• Process: A way-of-work and guide to help you being more productive
• Presentation: Professional, adaptable and beautiful outputs

🚀 Quick Start

1. Ensure you have R (>= 4.0.0) and RStudio installed.

2. Click "Use this template" in the top right corner

3. Clone your new repository and navigate to it:

git clone https://github.com/yourusername/your-repo-name.git
cd your-repo-name

4. Open the project in RStudio and run the setup script by clicking Enter:

Setup script detected. Run 00_setup.R? (press ENTER to run, ESC to skip): 

5. 🚧 Explore the template🚧:

• Open how-to.qmd for a step-by-step guide

6. To see the use of this template in other projects look instroomprognose-mbo.

Troubleshooting:

• If you encounter package installation issues, try updating R and RStudio to their latest versions.
• For renv-related problems, refer to the renv documentation.

🌟 Features

• Quarto-based workflow
  • Quick stream-of-consciousness programming (literate programming)
  • Easily move code from development to production due due to render-functionality
  • Documentation is directly next to the code
  • Export text and code output (tables and visualisation) quickly to pptx, html and pdf
• Standardized project structure following R package conventions (functional programming)
  • This enables automated code checks and clear structure
• Integrated renv for reproducible package management
  • Built-in tidyverse packages
  • Built-in LLM-enabling package and settings
  • No interference with other locally installed R packages
• Automated setup script for quick initialization
• Easy customization for project defaults
• Data folders with synthetic and reference data synced and other data kept local

📁 Project Structure

🚧 The P3 Template follows a well-organized directory structure to enhance productivity and maintainability. Here's an overview of the key directories:

project-root/
├── data/
│   └── synthetic/       # Synthetic data for testing and examples
│   └── reference/       # Reference data like mapping tables etc can be shared widely
├── man/                 # Auto-generated documentation
├── R/                   # R functions and scripts
└── utils/               # Utility files and tools, all adaptable by user
    ├── pal_prompts/     # AI assistant prompts for 'chores' like documentation and testing
├── how_to.qmd           # The how-to analysis file that demonstrates built-in functionality
├── how_to_success.qmd   # Potential Quarto file after all instructions are worked through successfully
├── how_to_success.html  # Visual presentation of success how-to
├── 00_set_up.R          # Ensuring all basic steps are done and project is ready-for-analysis
├── config.yml           # Configuration settings, like which data folder to use (by default synthetic)

🤝 Contributing

• Thanks to Npuls for providing the opportunity to develop this package
• Thank you to CEDA-colleagues for stimulating conversations and feedback Bram, Tomer, Amir, Tony, Theo, Ash, Steven, Caspar, Shirley and Martine
• Thanks to SURF Developer Program for sparking interest in templates

Contribute as well! Please see our Contributing Guide for details.

Key ways to contribute:

• Report bugs or suggest features by opening an issue
• Submit pull requests for bug fixes or new features
• Improve documentation or add usage examples

📄 License

This project is licensed under the Apache License.

📚 Additional Resources

• Quarto Documentation
• R Packages (2e) by Hadley Wickham and Jenny Bryan
• renv: Project Environments for R