RCPCHGrowth Python library
Calculations for children's measurements against UK and international growth references.
For AI/LLM agents working on this repository: Please read AGENTS.md for project context, development workflow, and testing strategy.
Please go to https://growth.rcpch.ac.uk/products/python-library/ for full documentation.
Issues can be raised here https://github.com/rcpch/rcpchgrowth-python/issues
Installation
Docker
If you want to avoid setting up docker environments, there are shortcut scripts the create a dockerized environment with RCPCHGrowth already installed.
This will generate a container which will launch some Jupyter notebooks in a browser and allow local dev (with hot reload).
Convenience Scripts
The s/ folder contains helper scripts for common development tasks:
| Script | Purpose |
|---|---|
s/up |
Start the development container |
s/down |
Stop the development container |
s/test |
Run pytest (auto-starts container if needed; use --running flag for already-running container) |
s/notebook |
Launch JupyterLab in your browser |
s/shell |
Open an interactive bash shell in the container |
s/python |
Launch Python REPL in the container |
Quick start:
# Start the container and launch notebooks
s/notebook
# Run tests (in a separate terminal)
s/test
# Or run tests in an already-running container
s/test --running
# Run the UK-WHO integration suite
s/test rcpchgrowth/tests/test_uk_who.py -v
# Reference WHO test datasets and under-2 gold-standard rationale
# (192 deterministic anthro-generated cases)
# See rcpchgrowth/tests/who_test_data/README.md
# Stop when done
s/down
Minimal installation (without docker) assuming you have a python virtual env setup
pip install rcpchgrowth
With notebook & package dependencies:
pip install "rcpchgrowth[notebook]"
The notebook extra currently pulls in: pandas, matplotlib, jupyterlab, ipykernel.
Data handling / privacy
|
Data handling & privacy Never commit identifiable patient data. • Keep raw identifiable data outside version control (secure, access‑controlled). • De‑identify before analysis (remove names, NHS numbers, full DOB; date‑shift if required). • Do not push raw exports to forks, PRs or gists. • Use ResearchTemplate.ipynb for generating de‑identified derived outputs.If in doubt, stop and seek local information governance guidance. |
Contributing
See issues list and please open discussions before large changes.
Copyright © Royal College of Paediatrics and Child Health
Release files for rcpchgrowth 4.6.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| rcpchgrowth-4.6.4.tar.gz | 4.1 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| rcpchgrowth-4.6.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 8.3 MB
Release files / rcpchgrowth-4.6.4.tar.gz
| Download URL | rcpchgrowth-4.6.4.tar.gz |
|---|---|
| Size | 4.1 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Transparency logRelease files / rcpchgrowth-4.6.4-py3-none-any.whl
| Download URL | rcpchgrowth-4.6.4-py3-none-any.whl |
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| Size | 4.2 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 6, 2026.
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