stimela provides a system-agnostic scripting framework for simulating, processing, and imaging radio interferometric data. The framework executes radio interferometry related tasks such as imaging, calibration, and data synthesis in Docker containers using Python modules. stimela offers a simple interface to packages that perform these tasks rather than doing any data processing, synthesis or analysis itself. stimela only requires Docker and Python. Moreover, because of Docker, a stimela script runs the same way (in the same iso­lated environment) regardless of the host machine’s settings, thus providing a user-friendly and modular scripting environment that gives general users easy access to novel radio interferometry calibration, imaging, and synthesis packages.

This package is no longer under active development and has been superseded by Stimela2 (ascl:2412.002).

Stimela2 develops data reduction workflows and is a significant update of Stimela (ascl:2305.007). Though designed for radio astronomy data, it can be adapted for other data processing applications. Stimela2 represents workflows by linear, concise and intuitive YAML-format "recipes". Atomic data reduction tasks (binary executables, Python functions and code, and CASA tasks) are described by YAML-format "cab definitions" detailing each task's "schema" (inputs and outputs). Stimela2 provides a rich syntax for chaining tasks together, and encourages a high degree of modularity: recipes may be nested into other recipes, and configuration is cleanly separated from recipe logic. Tasks can be executed natively or in isolated environments using containerization technologies such as Apptainer. Stimela2 facilitates the deployment of scalable, distributed workflows by interfacing with the Slurm scheduler and the Kubernetes API, the latter allowing workflows to be readily deployed in the cloud.