NHS RAP Cookiecutter Template

A Cookiecutter template for creating standardised NHS England Reproducible Analytical Pipeline (RAP) projects.

Introduction

This template provides a standardised project structure for developing Reproducible Analytical Pipelines within NHS England. It includes pre-configured tooling for testing, linting, documentation, and dependency management following modern Python development practices.

What is RAP?

Reproducible Analytical Pipelines (RAP) is a set of tools, principles, and techniques to help you improve your analytical processes. With RAP, you leverage open-source tools to make your work more efficient, more reusable, and less error-prone.

The core RAP principles from the NHS RAP Community of Practice are:

Principle	Description
Automation	Minimise manual, error-prone steps through automation
Modular, reusable code	Write code in independent, loosely-coupled functions
Transparency	Publish code openly under appropriate licences
Open-source tools	Use Python, R, and other freely available languages
Version control	Use Git to track changes to code
Good coding practices	Follow standards like PEP8, use clear documentation
Testing	Implement automated tests for reliability
Peer review	Review code collaboratively to ensure quality

Learn more about RAP at the NHS RAP Community of Practice website.

Installation

This template requires Python 3.10 or higher. This package is not published to PyPI, so install directly from GitHub:

pipx (recommended for CLI tools):

pipx install git+https://github.com/nhsengland/nhse-rap-cookiecutter.git

See the pipx documentation for installation instructions.

uv:

uv tool install git+https://github.com/nhsengland/nhse-rap-cookiecutter.git

See the uv documentation for installation instructions.

pip:

pip install git+https://github.com/nhsengland/nhse-rap-cookiecutter.git

Quick Start

Generate a new project using the CLI tool:

nhs-rap-template

Or use the official cookiecutter command:

cookiecutter gh:nhsengland/nhse-rap-cookiecutter

Configuration Options

The template prompts for the following information:

Category	Option	Description	Choices
Project	project_name	Human-readable project name	Text
	description	Brief project description	Text
	author_name	Your full name	Text
	author_email	Your email address	Text
	organization_name	Your organisation (fixed: NHS England)	Text
	team_name	Your team name	Text
	team_email	Team contact email (optional)	Text
Python	python_version_number	Minimum Python version	3.10, 3.11, 3.12
	environment_manager	Virtual environment tool	virtualenv, conda, pipenv, uv, pixi, poetry, none
	dependency_file	Dependency management file	requirements.txt, pyproject.toml, environment.yml, Pipfile
	pydata_packages	Include pandas, numpy, matplotlib	yes, no
Options	include_code_scaffold	Include example code modules	yes, no
	testing_framework	Testing framework	pytest, unittest
	license	Project licence	MIT, BSD-3-Clause, none
	documentation	Documentation tool	mkdocs, none

Generated Project Structure

your-project/
├── data/
│   ├── external/        # Data from third-party sources
│   ├── interim/         # Intermediate transformed data
│   ├── processed/       # Final canonical datasets
│   └── raw/             # Original immutable data
├── docs/                # MkDocs documentation with NHS styling
├── models/              # Trained models and predictions
├── notebooks/           # Jupyter notebooks for exploration
├── references/          # Data dictionaries and documentation
├── reports/
│   └── figures/         # Generated graphics
├── tests/
│   ├── pytest/          # Pytest tests
│   └── unittest/        # Unittest tests
├── your_module/         # Source code package
│   ├── __init__.py
│   ├── config.py        # Configuration management
│   ├── dataset.py       # Data loading and processing
│   ├── features.py      # Feature engineering
│   ├── plots.py         # Visualisation functions
│   └── modeling/
│       ├── train.py     # Model training
│       └── predict.py   # Model inference
├── LICENSE
├── Makefile             # Convenience commands
├── README.md
└── pyproject.toml       # Project configuration and dependencies

Using the Generated Project

After generating a project:

cd your-project-name
uv sync                      # Set up environment
uv run pre-commit install    # Install pre-commit hooks
make test                    # Run tests
make docs                    # Build documentation

Documentation

Full documentation: https://nhsengland.github.io/nhse-rap-cookiecutter

Development

See CONTRIBUTING.md for development setup and contribution guidelines.

uv run pytest tests/ -v                                              # Run tests
uv run pytest tests/ --cov=nhse_rap_cookiecutter --cov-report=term   # With coverage
uv run ruff format . && uv run ruff check .                                    # Format and lint
make docs-serve                                                                # Serve docs with live reload

Licence

Unless stated otherwise, the codebase is released under the MIT Licence. This covers both the codebase and any sample code in the documentation.

HTML and Markdown documentation is © Crown copyright and available under the terms of the Open Government 3.0 licence.

Acknowledgements

This template is based on Cookiecutter Data Science, adapted for NHS England RAP standards and modern Python tooling.