This book is about complexity science, data structures and algorithms,
intermediate programming in Python, and the philosophy of science:

• Data structures and algorithms: A data structure is
  a collection that contains data elements organized in a way
  that supports particular operations. For example, a dictionary
  organizes key-value pairs in a way that provides fast
  mapping from keys to values, but mapping from values to
  keys is generally slower.

  
  An algorithm is a mechanical process for performing a computation.
  Designing efficient programs often involves the co-evolution of data
  structures and the algorithms that use them. For example, the first
  few chapters are about graphs, a data structure that is a good
  implementation of a graph---nested dictionaries---and several graph
  algorithms that use this data structure.

• Python programming: This book picks up
  where Think
  Python leaves off. I assume that you have read that book or
  have equivalent knowledge of Python. As always, I will try to
  emphasize fundmental ideas that apply to programming in many
  languages, but along the way you will learn some useful features that
  are specific to Python.

• Computational modeling: A model is a simplified description
  of a system that is useful for simulation or analysis. Computational
  models are designed to take advantage of cheap, fast computation.

• Philosophy of science: The models and results in this book
  raise a number of questions relevant to the philosophy of science,
  including the nature of scientific laws, theory choice,
  realism and instrumentalism, holism and reductionism, and Bayesian
  epistemology.

This book focuses on discrete models, which include graphs, cellular
automata, and agent-based models. They are often characterized
by structure, rules and transitions rather than by equations.
They tend to be more abstract than continuous models; in some
cases there is no direct correspondence between the model and
a physical system.

Complexity science is an interdisciplinary field---at the
intersection of mathematics, computer science and physics---that
focuses on these kinds of models. That's what this book is about.

Print versions for purchase and TeX Source are available from the book's web page at Green Tea Press.