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This release is a pre-release and may not be stable for production use.

stimela-ninja (Stimela 3.0)

Stimela 3.0 is a Python framework for reproducible radio astronomy pipelines. It builds on Stimela classic with typed task inputs and outputs, Python recipes, and execution on local machines, containers, and computing clusters.

Use it to compose radio astronomy tools into workflows, run independent tasks concurrently, cache results, and record provenance for reproducible runs. dosho provides ready-to-use task definitions for tools such as WSClean, CASA, QuartiCal, and simms.

Academic attribution

Please acknowledge this project and its contributors when using the work in research, and cite the associated publications and software release where applicable. This is a scholarly request, not an additional licence condition. Citation information can be found in CITATION.cff.

Installation

Requires Python 3.11 or newer:

pip install stimela-ninja

This installs the ninja command and the importable shinobi package. For the companion task library:

pip install dosho

External tools must be installed locally or available through the container or cluster backend you use. See the installation guide.

Quick start

Save this minimal Python step as myrecipe.py:

from shinobi import pystep


@pystep()
def greet(name: str = "world") -> None:
    print(f"Hello, {name}!")

Run it from the command line; the function parameters become CLI options:

ninja run myrecipe.py:greet --name astronomer

For an imaging workflow that combines multiple tools, follow the pipeline tutorial.

Documentation

Contributing

Bug reports and contributions are welcome. See CONTRIBUTING.md for development setup and testing, and use the issue tracker for bugs and feature requests. Report security issues as described in SECURITY.md.

License

Apache License 2.0 — see LICENSE and NOTICE.

Metadata

Release files for stimela-ninja 0.1.0b7

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