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
Metadata
Release files for rcpchgrowth 4.6.5
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-4.6.5.tar.gz | 384.8 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| rcpchgrowth-4.6.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 797.3 kB
Release files / rcpchgrowth-4.6.5.tar.gz
| Download URL | rcpchgrowth-4.6.5.tar.gz |
|---|---|
| Size | 384.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Download URL | rcpchgrowth-4.6.5-py3-none-any.whl |
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| Size | 412.5 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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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.
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