Enhanced descriptions from Syndetics:

The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science.

From the reviews:

Langtangen ... does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objects and functions and embracing the object-oriented paradigm. ... Summing Up: Highly recommended.
F. H. Wild III, Choice, Vol. 47 (8), April 2010

Those of us who have learned scientific programming in Python 'on the streets' could be a little jealous of students who have the opportunity to take a course out of Langtangen's Primer." 
John D. Cook, The Mathematical Association of America, September 2011

This book goes through Python in particular, and programming in general, via tasks that scientists will likely perform. It contains valuable information for students new to scientific computing and would be the perfect bridge between an introduction to programming and an advanced course on numerical methods or computational science.
Alex Small, IEEE, CiSE Vol. 14 (2), March /April 2012  

 

Reviews provided by Syndetics

CHOICE Review

This update to previous editions (CH, Apr'10, 47-4463) continues to serve as an excellent introduction to scientific programming and the Python programming language. The chapters build from basic one-line formula calculations, basic programming structures (loops, lists, branching, etc.), and more complex Python structures (e.g., dictionaries, classes, and objects). Each chapter has a significant collection of exercises, which reinforce the concepts contained in the chapter. Along with the programming techniques developed in the book, the reader will learn a wide variety of mathematical skills, which are mainly contained in the various appendixes. One strong appendix contains significant information about debugging (there are also many examples of this throughout the text) and using a debugger. Another appendix discusses converting Python code to complied code for faster execution. Finally, there is a thorough appendix that deals with numerous technical issues, such as where to get several implementations of Python, "evaluating program efficiency," and testing software. Overall, this is an excellent book for any individual starting to learn scientific programming, and it will serve as a great reference book for those working in the field. Summing Up: Recommended. Lower- and upper-division undergraduates. --Devon B. Mason, Albright College

Author notes provided by Syndetics

Hans Petter Langtangen is a professor of computer science at the University of Oslo. He has formerly been a professor of mechanics and is now the director of a Norwegian Center of Excellence: "Center for Biomedical Computing", at Simula Research Laboratory. Langtangen has published over 100 scientific publications and written several books, including papers and a book on Python's potential for scientific computing. He has also developed open source and commercial software systems for computational sciences.