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A Primer on Scientific Programming with Python (Texts in Computational Science and Engineering)

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The aim of this book is to teach computer programming using examples 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 for scientific computations. A seamless integration of Python with Java is offered by a special version of Python called Jython.

The examples in this book integrate programming with applications to mathematics, physics, biology, and finance. The reader is expected to have knowledge of basic one-variable calculus as taught in mathematics-intensive programs in high schools. It is certainly an advantage to take a university calculus course in parallel, preferably containing both classical and numerical aspects of calculus. Although not strictly required, a background in high school physics makes many of the examples more meaningful.

Many introductory programming books are quite compact and focus on listing functionality of a programming language. However, learning to program is learning how to think as a programmer. This book has its main focus on the thinking process, or equivalently: programming as a problem solving technique. That is why most of the pages are devoted to case studies in programming, where we define a problem and explain how to create the corresponding program. New constructions and programming styles (what we could call theory) is also usually introduced via examples. Special attention is paid to verification of programs and to finding errors. These topics are very demanding for mathematical software, because the unavoidable numerical approximation errors are possibly mixed with programming mistakes.

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Deep Learning with Swift for TensorFlow: Differentiable Programming with Swift
Deep Learning with Swift for TensorFlow: Differentiable Programming with Swift

About this book

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Expert F# 2.0 (Expert's Voice in F#)
Expert F# 2.0 (Expert's Voice in F#)

Expert F# 2.0 is about practical programming in a beautiful language that puts the power and elegance of functional programming into the hands of professional developers. In combination with .NET, F# achieves unrivaled levels of programmer productivity and program clarity.

Expert F# 2.0 is

web2py
web2py

The official web2py manual. 3rd Edition. Includes many new pages (537 total).

web2py was launched in 2007 and now, after three years of continuous development, we have reached a very much needed third edition of this book. During this time web2py has managed to win the affection of many knowledgeable users and developers who share...


The Formal Semantics of Programming Languages: An Introduction (Foundations of Computing)
The Formal Semantics of Programming Languages: An Introduction (Foundations of Computing)

The Formal Semantics of Programming Languages provides the basic mathematical techniques necessary for those who are beginning a study of the semantics and logics of programming languages. These techniques will allow students to invent, formalize, and justify rules with which to reason about a variety of programming languages. Although...

Arduino: A Quick Start Guide
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With this Quick-Start Guide you'll be creating your first gadgets within a few minutes, following the step-by-step instructions and photos throughout the book. You'll build your own motion-sensing game controller with a three-axis accelerometer, connect the Arduino to the Internet and program both client and server...

Data Structures and Algorithms Using Python
Data Structures and Algorithms Using Python

The standard second course in computer science has traditionally covered the fun- damental data structures and algorithms, but more recently these topics have been included in the broader topic of abstract data types. This book is no exception, with the main focus on the design, use, and implementation of abstract data types. The...

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