Radio Astronomy Reduction Pipelines Using Python and Various Container Technologies
summary
Framework called Stimela packages radio‑astronomy tools as container images (built from PyPI and Debian/PPA artifacts) and runs them via Docker/Podman/Singularity/uDocker under a Python API; CI (Travis) pushes tagged releases so users can pin reproducible stacks. Pipeline work targets MeerKAT‑style arrays (64 dishes, ~8 km baselines), uses CASA plus alternative imaging tools in modular containers, produces FITS images and source catalogs, and supports parallel execution across data sets while scalability and smart cluster scheduling remain active development.
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