A primer on scientific programming with Python

Computing with formulas. The first programming encounter : a formula ; Computer science glossary ; Another formula : Celsius-Fahrenheit conversion ; Evaluating standard mathematical functions ; Interactive computing ; Complex numbers ; Summary ; Exercises

Basic constructions. Loops and lists for tabular data ; Functions ; If tests ; Summary ; Exercises

Input data and error handling. Asking questions and reading answers ; Reading from the command line ; Handling errors ; A glimpse of graphical user interfaces ; Making modules ; Summary ; Exercises

Array computing and curve plotting. Vectors ; Arrays in Python programs ; Curve plotting ; Plotting difficulties ; More on numerical Python arrays ; Higher-dimensional arrays ; Summary ; Exercises

Sequences and difference equations. Mathematical models based on difference equations ; Programming with sound ; Summary ; Exercises

Files, strings, and dictionaries. Reading data from file ; Dictionaries ; Strings ; Reading data from web pages ; Writing data from web pages ; Writing data to file ; Summary ; Exercises

Introduction to classes. Simple function classes ; More examples on classes ; Special methods ; Example : solution of differential equations ; Example : class for vectors in the plane ; Example : class for complex numbers ; Static methods and attributes ; Summary ; Exercises

Random numbers and simple games. Drawing random numbers ; Drawing integers ; Computing probabilities ; Simple games ; Monte Carlo integration ; Random walk in one space dimension ; Random walk in two space dimensions ; Summary ; Exercises

Object-oriented programming. Inheritance and class hierarchies ; Class hierarchy for numerical differentiation ; Class hierarchy for numerical integration ; Class hierarchy for numerical methods for ODEs ; Class hierarchy for geometric shapes ; Summary ; Exercises

A discrete calculus. Discrete functions ; Differentiation becomes finite differences ; Integration becomes summation ; Taylor series ; Exercises

Differential equations. The simplest case ; Exponential growth ; Logistic growth ; A general ordinary differential equation ; A simple pendulum ; A model for the spread of disease ; Exercises

A complete project. About the problem : motion and forces in physics ; Program development and testing ; Visualization ; Exercises

Debugging. Using a debugger ; How to debug

Technical topics. Different ways of running Python programs ; Integer and float division ; Visualizing a program with Lumpy ; Doing operating system tasks in Python ; Variable number of function arguments ; Evaluating program efficiency.