A lightweight task library for reproducible workflows
Project description
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
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_notebooks, setup_env_python
Now you can call:
invoke run-notebooks
invoke setup-env-python
Requirements
- Python ≥ 3.8
invoke≥ 2.0- Docker (for container tasks)
- Apptainer (optional, for
.sifsupport) jupyter(if usingrun-notebooks)
Note that a few more requirements are required for development, in particular pdoc which is used to generate the documentation website.
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 © airoh contributors
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