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: 6.6*

                • Google Colab: pip-wheels for Python 3.10 (Google Colab) are now available.
                • Installation: test script added to test the CASA installation.
                • defintent: new task to modify the scan intents of a measurement set.
                • sdimaging: new parameter convertfirst, to reduce the number of direction conversions.
                • deconvolve: mtmfs enabled as an algorithm option.
                • tclean/deconvolve: return dictionaries added for niter=0 calls.
                • image tool: fitsheader function added to return FITS header as Python dictionary.
                • plotms: parameter colorizeoverlay added to better specify overlay colors.
                • plotms: better specifies values in the legend when coloraxis is set.
                • Multiple MS input: clarifications added to the CASA logger on how CASA handles input of multiple MSs.
                • Telemetry/crash reporter: functionality deprecated.

                 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.