Introduction to Digital Music with Python Programming: Learning Music with Code

✍ Scribed by Michael Horn, Melanie West, Cameron Roberts

• Publisher: Focal Press
• Year: 2022
• Tongue: English
• Leaves: 279
• Edition: 1
• Category: Library

✦ Synopsis

Introduction to Digital Music with Python provides a foundation in music and code for the beginner and shows how coding empowers new forms of creative expression while simplifying and automating many of the tedious aspects of production and composition.

With the help of online, interactive examples on Digital Audio Workstation (DAW) platforms called TunePad and EarSketch, this book covers the fundamentals of rhythm, chord structure and melodic composition alongside the basics of digital production. Each new concept is anchored in a real-world musical example that will have you making beats in a matter of minutes.

Including core programming concepts such as loops, variables, lists and functions, Introduction to Digital Music with Python is designed for beginners of all backgrounds, requiring no previous experience with music or code, including undergraduates and aspiring professionals.

✦ Table of Contents

Cover
Half Title
Title Page
Copyright Page
Dedication
Table of Contents
List of figures
Photo and illustration credits
Foreword
Acknowledgments
1 Why music and coding?
Interlude 1: Basic pop beat
2 Rhythm and tempo
Interlude 2: Custom trap beat
3 Pitch, harmony, and dissonance
Interlude 3: Melodies and lists
4 Chords
Interlude 4: Playing chords
5 Scales, keys, and melody
Interlude 5: Lean on me
6 Diatonic chords and chord progressions
Interlude 6: Random chord progressions
7 Frequency, fourier, and filters
Interlude 7: Creative effects
8 Note-based production effects
Interlude 8: How to make a drum fill
9 Song composition and EarSketch
Interlude 9: How to make a snare drum riser
10 Modular synthesis
Interlude 10: Drum machine function
11 History of music and computing
Appendix A: Python reference
Appendix B: TunePad programming reference
Appendix C: Music reference
Index