stimela-ninja¶

Stimela 3.0 – a simple but flexible framework for reproducible radio astronomy pipelines.

A spiritual successor to Stimela classic, built around the same core philosophy. Recipes are plain Python: a step is a function call, and a step’s output is a Python value you wire into the next call. There is no YAML expression/substitution language, no alias-propagation system, and no stacked config libraries – control flow is just Python, and it doesn’t need reinventing.

Note

Early scaffolding. The interfaces documented here are real and tested (pytest), but the project is not yet ready to run real pipelines.

from pydantic import BaseModel

from shinobi import Cab, step


class ImageInputs(BaseModel):
    ms: str = "obs.ms"
    prefix: str = "img"


wsclean = Cab(
    name="wsclean",
    command="wsclean",
    image="quay.io/stimela/wsclean:latest",
    inputs_model=ImageInputs,
)


@step(wsclean, backend="native")
def image(ctx):
    return ctx.run()

$ ninja run myrecipe.py:image --ms data.ms --prefix out

Getting started

Using ninja

Reference

API reference

Project

Contributing
- Contributing to stimela-ninja

stimela-ninja¶

Indices¶