Think Complexity: Complexity Science and Computational Modeling (Kindle Edition) newly tagged "photography"

Are you a reasonably competent Python programmer yearning for new challenges? "Think Complexity" definitely delivers some.

Allen B. Downey's well-written new book can help you dive into complexity science and improve your Python skills along the way. It's not just another hello-world, learn-to-program-in-Python text.

"This book," Downey states, "is about data structures and algorithms, intermediate programming in Python, computational modeling, and the philosophy of science." Hello, NEW world.

His new work, he adds, sprang out of a blending of "boredom and fascination: boredom with the usual presentation of data structures and algorithms and fascination with complex systems. The problem with data structures is that they are often taught without a motivating context; the problem with complexity science is that it usually is not taught at all."

Complexity science is the scientific study of complex systems - which can be anything from computer networks to the human brain, global markets, ecosystems, metropolitan areas, space shuttles, ant trails, and so forth. Complexity science is practiced "at the intersection of mathematics, computer science, and natural science," Downey says.

How does "the philosophy of science" fit into Downey's book? "Think Complexity" offers "experiments and results [that] raise questions relevant to the philosophy of science, including the nature of scientific laws, theory choice, realism and instrumentalism, holism and reductionism, and epistemology."

Downey's new work "picks up where Think Python left off" and is intended to appeal to the "broad intellectual curiosity" of software engineers and their "drive to expand their knowledge and skills." There are case studies, exercises, code samples and even mini-lessons within the exercises.

So, before you jump into this book, be sure you are reasonably competent at Python programming and are open to some wide-ranging challenges.

Students at Olin College, where the author is a computer science professor, wrote the case studies for this book. The case studies then were edited by Downey and his wife and reviewed by other Olin faculty members. Appendix A of this book contains a call for readers to submit additional case studies: "Reports that meet the criteria [explained in the appendix] will be published in an online supplement to this book, and the best of them will be included in future print editions."

This might be an offer -- and a Python challenge -- you can't refuse.