This is mostly true until you need new data that is not a .mat or image, or to deploy to a server for production (licensing Matlab for multi-core servers is pretty rough), or deal with strings, or send stuff over the network, or one of the other thousand things the Python ecosystem does better. For algorithmic experiments, Matlab has an edge but the "with batteries" / overall utility approach has always been the primary strength of Python for science.