CASA, the Common Astronomy Software Applications package, is the primary data processing software for the Atacama Large Millimeter/submillimeter Array (ALMA) and NSF's Karl G. Jansky Very Large Array (VLA), and is frequently used also for other radio telescopes. The CASA software can process data from both single-dish and aperture-synthesis telescopes, and one of its core functionalities is to support the data reduction and imaging pipelines for ALMA, VLA and the VLA Sky Survey (VLASS).

Latest CASA Release: 6.4*

                • OS Support: RedHat 8 and Mac OS with Python 3.8, for monolithic and modular versions.
                • plotcal/plotms: Funtionality for plotcal has been migrated to plotms, and plotcal was deprecated.
                • plotms: calibration table averaging with channel selection is now supported.
                • fringefit: memory usage has been reduced, allowing larger datasets to be processed.
                • imhead: updated to display micro-arcsecond precision.
                • caltables: storage of frequency meta information improved.
                • sdintimaging: now adds information to the history of produced images
                • T+dT timerange selection improved in accuracy.

                 For details and more, see

The CASA team has begun exploring options for a new generation of software to meet the growing demands of current and future radio telescopes. This CASA Next Generation Infrastructure (CNGI) prototype package is a demonstration of the current state of our research efforts. Its primary purpose is to showcase new data structures for MeasurementSet and Image contents built entirely in Python atop the popular technology stack of numpy, dask, and xarray.

The CNGI prototype documentation contains Visibility and Image overview sections that describe a selection of core mathematics, manipulation, middleware and analysis functions to demonstrate the simplicity and scalability of the technology choices. Notional examples of Calibration, Flagging and Imaging are provided to illustrate future design and implementation direction. A detailed explanation of technology choices, including the xarray and dask frameworks, the zarr storage format, and the functional design architecture can be found in the Development section.

Finally, the most compute intensive areas of CASA imaging are implemented and benchmarked to demonstrate the parallel scalability and raw performance now possible from a pure-Python software stack.

We invite anyone interested to explore the new cngi_prototype package. We welcome your feedback at

CASA is being developed by an international team of scientists based at the National Radio Astronomical Observatory (NRAO), the European Southern Observatory (ESO), and the National Astronomical Observatory of Japan (NAOJ), under the guidance of NRAO.