Do you want to learn how to create music using a computer programming language? Are you looking for a good introductory book on both music theory and computer-generated music? This book addresses these subjects and many more. It explains music-related topics, such as musical history, notes, scales, chords, musical instruments, musical structure, and canons, in a clear and concise manner. Since the book also covers computer-aided music creation, it discusses the musical instrument digital interface (MIDI) and the open sound control (OSC) protocols, interfacing digital instruments, the Python programming language and its application in music, and other related computing concepts.

The book is well organized. It comprises 11 chapters. The first four chapters explain computer music history, an introduction to music-related topics, and the basics of computer music programming using the Python programming language. Chapters 5 and 6 offer advanced topics on music creation and Python programming, such as random functions in Python and randomness in music. Chapter 7 is a compelling one, devoted to sonification. Data sonification is a branch of computing that studies how to convey meaningful information using auditory parameters. This chapter also explains how to use Python for rendering musical sonifications of big data (extensive datasets that are nontrivial to analyze in computing). For example, a section explains how to use Python to “sonificate” (map) biosignal data to pitch. Chapter 8 describes how to interact with digital musical instruments, and how to design and create related graphical user interfaces (GUIs) using Python. Chapter 9 is devoted to the MIDI and OSC protocols. Chapter 10 goes on to describe the relationships of mathematics and music, applying Python programming. The last chapter is related to chapter 10, and envisions special and powerful ideas on how to create music employing Python and mathematics. For instance, it explores how the golden ratio and fractals can be used for generating music. The chapters also contain case studies describing a musical or computing concept and practical applications of Python programs that complement the described concept. The appendices show very useful Python functions.

This will be a great supporting text for applied music, music in digital media, music education, and related courses. It can also be useful for computing courses where music composition and creation are included to support learning programming, such as Python programming and software engineering. The book will definitively serve computer-generated music and sonification researchers and practitioners.