The goal of this book is to teach computational scientists how to develop
tailored, flexible, and human-efficient working environments built from small programs
(scripts) written in the easy-to-learn, high-level language Python.
The focus is on examples and applications of relevance to computational scientists:
gluing existing applications and tools,
e.g. for automating simulation, data analysis, and visualization;
steering simulations and computational experiments;
equipping old programs with graphical user interfaces;
making computational Web applications;
and creating interactive interfaces with a Maple/Matlab-like syntax
to numerical applications in C/C++ or Fortran.
In short, scripting with Python makes you much more productive,
increases the reliability of your scientific work
and lets you have more fun – on Unix, Windows and Macintosh.
All the tools and examples in this book are open source codes.