Book contents
- Frontmatter
- Contents
- Preface
- 1 Introduction to Python
- 2 Systems of Linear Algebraic Equations
- 3 Interpolation and Curve Fitting
- 4 Roots of Equations
- 5 Numerical Differentiation
- 6 Numerical Integration
- 7 Initial Value Problems
- 8 Two-Point Boundary Value Problems
- 9 Symmetric Matrix Eigenvalue Problems
- 10 Introduction to Optimization
- Appendices
- List of Program Modules (by Chapter)
- Index
1 - Introduction to Python
Published online by Cambridge University Press: 05 June 2014
- Frontmatter
- Contents
- Preface
- 1 Introduction to Python
- 2 Systems of Linear Algebraic Equations
- 3 Interpolation and Curve Fitting
- 4 Roots of Equations
- 5 Numerical Differentiation
- 6 Numerical Integration
- 7 Initial Value Problems
- 8 Two-Point Boundary Value Problems
- 9 Symmetric Matrix Eigenvalue Problems
- 10 Introduction to Optimization
- Appendices
- List of Program Modules (by Chapter)
- Index
Summary
General Information
Quick Overview
This chapter is not a comprehensive manual of Python. Its sole aim is to provide sufficient information to give you a good start if you are unfamiliar with Python. If you know another computer language, and we assume that you do, it is not difficult to pick up the rest as you go.
Python is an object-oriented language that was developed in the late 1980s as a scripting language (the name is derived from the British television series, Monty Python's Flying Circus). Although Python is not as well known in engineering circles as are some other languages, it has a considerable following in the programming community. Python may be viewed as an emerging language, because it is still being developed and refined. In its current state, it is an excellent language for developing engineering applications.
Python programs are not compiled into machine code, but are run by an interpreter. The great advantage of an interpreted language is that programs can be tested and debugged quickly, allowing the user to concentrate more on the principles behind the program and less on the programming itself. Because there is no need to compile, link, and execute after each correction, Python programs can be developed in much shorter time than equivalent Fortran or C programs. On the negative side, interpreted programs do not produce stand-alone applications. Thus a Python program can be run only on computers that have the Python interpreter installed.
- Type
- Chapter
- Information
- Numerical Methods in Engineering with Python 3 , pp. 1 - 30Publisher: Cambridge University PressPrint publication year: 2013