E-Book Overview
With a primary focus on examples and applications of relevance to computational scientists, this brilliantly useful book shows computational scientists how to develop tailored, flexible, and human-efficient working environments built from small scripts written in the easy-to-learn, high-level Python language. All the tools and examples in this book are open source codes. This third edition features lots of new material. It is also released after a comprehensive reorganization of the text. The author has inserted improved examples and tools and updated information, as well as correcting any errors that crept in to the first imprint.
E-Book Content
Python Scripting for Computational Science Hans Petter Langtangen Simula Research Laboratory and Department of Informatics University of Oslo
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Preface
The primary purpose of this book is to help scientists and engineers who work intensively with computers to become more productive, have more fun, and increase the reliability of their investigations. Scripting in the Python programming language can be a key tool for reaching these goals [28,30]. The term scripting means different things to different people. By scripting I mean developing programs of an administering nature, mostly to organize your work, using languages where the abstraction level is higher and programming is more convenient than in Fortran, C, C++, or Java. Perl, Python, Ruby, Scheme, and Tcl are examples of languages supporting such high-level programming or scripting. To some extent Matlab and similar scientific computing environments also fall into this category, but these environments are mainly used for computing and visualization with built-in tools, while scripting aims at gluing a range of different tools for computing, visualization, data analysis, file/directory management, user interfaces, and Internet communication. So