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: 6.5*

                • imbaseline: new task for image-based baseline subtraction for single-dish data.
                • corrbit(): new method in msmetadata tool for returning the value in SPECTRAL_WINDOW:: SDM_CORR_BIT column.
                • plotms: added support for additional axes of calibration tables.
                • setjy: parameter "modimage" removed (use parameter "model" instead).
                • tclean: return dictionary now includes additional information about the minor cycles.
                • Mac OS 12: bug fixed that prevented the OS 11/Python 3.6 package to open on Mac OS 12.
                • tclean: bug fixed that prevented UV taper to work with weighting=’natural’.

                 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.