airoh 0.1.4

A lightweight task library for reproducible workflows

airoh

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.

Installation

Installation through PIP:

pip install airoh

For local deployment:

git clone https://github.com/simexp/airoh.git
cd airoh
pip install -e .

Usage

You can use airoh in your project simply by importing tasks in your tasks.py file.

Minimal Example

# tasks.py
from airoh.utils import run_figures, setup_env_python

Now you can call:

invoke run-figures
invoke setup-env-python

Available Tasks

From containers.py

• docker-build — Build a Docker image from a Dockerfile
• docker-archive — Archive the Docker image to .tar.gz
• docker-setup — Download and load a Docker image from URL
• docker-run — Run an invoke task inside Docker
• apptainer-archive — Build an Apptainer image from Docker
• apptainer-run — Run an invoke task inside Apptainer

From utils.py

• ensure_submodule — Ensure a git submodule is present and up to date
• install_local — Install a local Python package in editable mode using pip
• setup-env-python — Install Python dependencies from a file
• run-figures — Run Jupyter notebooks to generate figures
• ensure-dir-exist: Creates a directory listed in invoke.yaml if it doesn't already exist.
• clean_folder — Remove an entire directory recursively. Use with caution!!!

From datalad.py

• get-data — Install and retrieve a subdataset listed in invoke.yaml
• import-archive — Download a remote archive (e.g. from Zenodo), extract its contents with datalad, and optionally drop the original file
• import-file — Download a remote file (e.g. from Zenodo), using datalad

Requirements

• Python ≥ 3.8
• invoke ≥ 2.0
• Docker (for container tasks)
• Apptainer (optional, for .sif support)
• jupyter (if using run-figures)

Philosophy

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.

License

MIT © Lune Bellec