The complete beginners guide to creating generative graphics for print, video and the web.

The philosophy and practice of using a programming language as an artistic tool.

Includes an easy introduction to Processing, and applied tutorials on subjects such as Perlin Noise, Randomness, Fractals, Emergence, Agent Oriented Programming, Three Dimensional Drawing, and Cellular Automata.

Featuring the work of Robert Hodgin, Jared Tarbell, Aaron Koblin, Casey Reas and many more of the finest contemporary generative artists.

32-page full-color section. Foreword by Marius Watz.

Generative Art book cover

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Translated by Keisuke Oki. Available from


Every Manning print copy includes a download code+url to get FREE Kindle, PDF or ePub versions of the book. The Kindle version is text only, but the PDF includes all the code and imagery.

If, for whatever reason, you want to get an electronic format without having the print copy, this can be purchased from Manning direct.


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Chapter 1
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Generative Art in HTML5


Reviews below are from the (anonymous) pre-publication review panels. For post-publication reader reviews, see, and goodreads.

"The book's approach is unique and Matt's style of writing is wonderfully personal. It is not only educational but also entertaining. I'll definitely add to my library."

"Matt's approach is unique in that he focusses on core concepts of genart instead of core concepts of programming. He succeeds in teaching about variables, functions, OOP and recursion without the reader realising what he's doing."

"Matt Pearson succeeds in teaching without lecturing. Generative Art approaches its subject in a practical and immersive way, building abstract programming skills without the reader, or rather the participant, ever realising it. This is the first book on Processing or creative coding that had me following the code examples throughout. Especially the later chapters devoted on agents and recursion provide enough ideas to fuel many explorations."

"Matt succeeds in tying dull core programming concepts into fun explorations in genart concepts. I'm really impressed by this."

"Its construction is unique and the chapter titles reveal this. It doesn't feel like a hard-copy of a course given somewhere by someone. Browsing the TOC, I was tempted to read each chapter. Due to the very personal approach throughout the book, I even read the chapters where Matt couldn't teach me anything new."

"Matt Pearson has provided an excellent introduction to generative art using Processing. With just the right mix of instruction and inspiration, working through the book was a pleasure, and I was producing interesting and rewarding results right from the start. This book should be considered as a stepping stone to experimentation, rather than a comprehensive review of the (many) facets of generative art and it's certainly set me along an interesting and rewarding path into the area."


About this book

Introduction: The organic vs. the mechanical

Part 1: Creative Coding
1. Generative art: In theory and practice
2. Processing: A programming language for artists

Part 2: Randomness and Noise
3. The wrong way to draw a line
4. The wrong way to draw a circle
5. Adding dimensions

Part 3: Complexity
6. Emergence
7. Autonomy
8. Fractals

(Expanded Table of Contents)


Artists have always explored new media, and computer-based artists are no exception. Generative art, an emerging technique where print or onscreen images are created by use of computer algorithms, finds the artistic intersection between programming, computer graphics, and individual expression.

Generative Art presents both the technique and the beauty of algorithmic art. In it, you'll find dozens of high-quality examples of generative art, along with the specific programmatic steps author and artist Matt Pearson followed to create each unique piece. The book includes concise tutorials for each of the technical components required to create the book's examples, and it offers countless suggestions for how you can combine and reuse the various techniques to create your own works.