Allen B. Downey擁有加州大學伯剋利分校的計算機科學博土學位和MIT的碩士與學土學位，現任美國歐林工程學院計算機科學係的教授，曾經在威爾斯利大學、科爾比學院和加州大學伯剋利分校教授計算機科學相關的課程。曾經擔任 Google的訪問科學傢，對復雜性科學和Python十分著迷，有較為深入的研究和豐富的實踐經驗。

Dive into Python's advanced possibilities, including algorithm analysis, graphs, scale-free networks, and cellular automata with this in-depth, hands-on guide. Whether you're an intermediate-level Python programmer, or a student of computational modeling, you'll examine data structures, complexity science, and other fascinating topics through a series of exercises, easy-to-understand explanations, and case studies. Think Complexity presents features that make Python such a simple and powerful language. Author Allen Downey provides code to help you get started, along with a solution for each exercise. With this book, you will: Work with graphs and graph algorithms, NumPy arrays and SciPy methods, basic signal processing and Fast Fourier Transform, and hash tables. Discover complexity science, the field that studies abstract models of complex physical systems, including power laws, fractals and pink noise, and Turing machines. Explore the philosophy of science through the models and results in this book about the nature of scientific laws, theory choice, and realism and instrumentalism, and more.