About this book

This book is intended to help scientists and engineers learn version 3 of the Python programming language and its associated NumPy, SciPy and Matplotlib libraries. No prior programming experience or scientific knowledge in any particular field is assumed. However, familiarity with some mathematical concepts such as trigonometry, complex numbers and basic calculus is helpful to follow the examples and exercises.

Python is a powerful language with many advanced features and libraries; while the basic syntax of the language is straightforward to learn, it would be impossible to teach it in depth in a book of this size. Therefore, we aim for a balanced, broad introduction to the central features of the language and its important libraries. The text is interspersed with examples relevant to scientific research, and at the end of most sections there are questions (short problems designed to test knowledge) and exercises (longer problems that usually require a short computer program to solve). Although it is not necessary to complete all of the exercises, readers will find it useful to attempt at least some of them. Where a section, example or exercise contains more advanced material that may be skipped on first reading, this is indicated with the symbol ◊.

In Chapter 2 of this book, the basic syntax, data structures and flow control of a Python program are introduced. Chapter 3 is a short interlude on the use of the Pylab library for making graphical plots of data: this is useful to visualize the output of programs in subsequent chapters. Chapter 4 provides more advanced coverage of the core Python language and a brief introduction to object-oriented programming. There follows another short chapter introducing the popular IPython and IPython Notebook environments, before chapters on scientific programming with NumPy, Matplotlib and SciPy. The final chapter covers more general topics in scientific programming, including floating point arithmetic, algorithm stability and programming style.

Readers who are already familiar with the Python programming language may wish to skim Chapters 2 and 4.

Code examples and exercise solutions may be downloaded from the book's website at scipython.com. Note that while comments have been included in these downloadable programs, they are not so extensive in the printed version of this book: instead, the code is explained in the text itself through numbered annotations (such as ➊).