Processing audio in the spectral domain has become a practical proposition for a variety of applications in computer music, composition, and sound design, making it an area of significant interest for musicians, programmers, sound designers, and researchers. While spectral processing has been explored already from a variety of perspectives, previous approaches tended to be piecemeal: some dealt with signal processing details, others with a high-level music technology discussion of techniques, some more compositionally focused, and others at music/audio programming concerns. As author Victor Lazzarini argues, the existing literature has made a good footprint in the area but has failed to integrate these various approaches within spectral audio. In Spectral Sound Design: A Computational Approach, Lazzarini provides an antidote. Spectral Sound Design: A Computational Approach gives authors a set of practical tools to implement processing techniques and algorithms in a balanced way, covering application aspects as well the fundamental theory that underpins them, within the context of contemporary and electronic music practice. The book employs a mix of Python for prototyping and Csound for deployment and music programming. The tight integration of these three languages as well as the wide scope offered by the combination (going from embedded to supercomputing, and including web-based and mobile applications) makes it the go-to resource to deal with the practical aspects of the subject.