This is a textbook which origins come from a course in an university. On the one hand, this makes the author to explain things absolutely obvious, clearly oriented to students in the first years of their technical degree. On the other hand, some of these explanations become handy if you have to teach this material or even, sometimes, to learn the origins of something that you have accepted as obvious without knowing exactly why is so. This is particularly relevant in those parts dealing with mathematics (many in the book). The book probably is of no use for an expert on SciPy/Numpy, but it is definitely useful for people, like me, that is starting to discover the enormous capabilities of these python language extensions. I clearly recommend this book for such target users. The book is also excellently well written, with a clear and concise style. Errors seem to be absent from the text and exercises are very well targeted to the area of scientific computation. 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 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 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 Langtangens 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 informationfor 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 This fourth edition is a wonderful, inclusive textbook that covers pretty much everything one needs to know to go from zero to fairly sophisticated scientific programming in PythonJoan Horvath, Computing Reviews, March 2015 Theaimofthisbookistoteachcomputerprogrammingusingexamples From Mathematics And The Natural Sciences. We Have Chosen To Use The Python Programming Language Because It Combines Remarkable Power With Very Clean, Simple, And Compact Syntax. Python Is Easy To Learn And Very Well Suited For An Introduction To Computer Programming. Python Is Also Quite Similar To Matlab And A Good Language For Doing Mathematical Computing. It Is Easy To Combine Python With Compiled Languages, Like Fortran, C, And C++, Which Are Widely Used Languages Forscienti?ccomputations.aseamlessintegrationofpythonwithjava Is O?ered By A Special Version Of Python Called Jython. The Examples In This Book Integrate Programming With Appli- Tions To Mathematics, Physics, Biology, And ?nance. The Reader Is - Pected To Have Knowledge Of Basic One-variable Calculus As Taught In Mathematics-intensive Programs In High Schools. It Is Certainly An - Vantage To Take A University Calculus Course In Parallel, Preferably C- Taining Both Classical And Numerical Aspects Of Calculus. Although Not Strictly Required, A Background In High School Physics Makes Many Of The Examples More Meaningful. Computing With Formulas -- Basic Constructions -- Input Data And Error Handling -- Array Computing And Curve Plotting -- Sequences And Difference Equations -- Files, Strings, And Dictionaries -- To Classes -- Random Numbers And Simple Games -- Object-oriented Programming. Hans Petter Langtangen. Includes Bibliographical References (p. 687) And Index. Front Matter....Pages i-xxvii Computing with Formulas....Pages 1-49 Basic Constructions....Pages 51-118 Input Data and Error Handling....Pages 119-167 Array Computing and Curve Plotting....Pages 169-233 Sequences and Difference Equations....Pages 235-268 Files, Strings, and Dictionaries....Pages 269-335 Introduction to Classes....Pages 337-415 Random Numbers and Simple Games....Pages 417-478 Object-Oriented Programming....Pages 479-571 Back Matter....Pages 573-700
