Because reproducible science takes clean tasks. And why don't you have a cup of relaxing jasmin tea?
airoh is a lightweight Python task library built with invoke, designed for reproducible research workflows. It provides pre-written, modular task definitions that can be easily reused in your own tasks.py file — no boilerplate, just useful automation. Access the documentation of the library on the airoh docs website for a list of available airoh tasks.
Installation through PIP:
pip install airohFor local deployment:
git clone https://github.com/simexp/airoh.git
cd airoh
pip install -e .You can use airoh in your project simply by importing tasks in your tasks.py file.
# tasks.py
from airoh.utils import run_figures, setup_env_pythonNow you can call:
invoke run-figures
invoke setup-env-python- Python ≥ 3.8
invoke≥ 2.0- Docker (for container tasks)
- Apptainer (optional, for
.sifsupport) jupyter(if usingrun-figures)
Note that a few more requirements are required for development, in particular pdoc which is used to generate the documentation website.
Inspired by Uncle Iroh from Avatar: The Last Airbender, airoh aims to bring simplicity, reusability, and clarity to research infrastructure — one well-structured task at a time. It is meant to support a concrete implementation of the YODA principles.
MIT © airoh contributors