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Learning Python Application Development

You're reading from   Learning Python Application Development Take Python beyond scripting to build robust, reusable, and efficient applications

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Product type Paperback
Published in Sep 2016
Publisher Packt
ISBN-13 9781785889196
Length 454 pages
Edition 1st Edition
Languages
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Author (1):
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Ninad Sathaye Ninad Sathaye
Author Profile Icon Ninad Sathaye
Ninad Sathaye
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Table of Contents (12) Chapters Close

Preface 1. Developing Simple Applications FREE CHAPTER 2. Dealing with Exceptions 3. Modularize, Package, Deploy! 4. Documentation and Best Practices 5. Unit Testing and Refactoring 6. Design Patterns 7. Performance – Identifying Bottlenecks 8. Improving Performance – Part One 9. Improving Performance – Part Two, NumPy and Parallelization 10. Simple GUI Applications Index

Introduction to NumPy


NumPy is a powerful Python package for scientific computing. It provides a multidimensional array object that enables efficient implementation of numerical computations in Python. It also has a relatively smaller memory footprint when compared to a list. An array object is just one of the many important features of NumPy. Among other things, it offers linear algebra and random number generation capabilities. It also provides tools to access codes written in other languages, such as C/C++ and Fortran. Let's start with a short introduction that gives a flavor of its capabilities. What we will discuss in this book is more like scratching the surface of NumPy! This chapter covers some features to be used later to speed up the Gold Hunt application.

Tip

Review the official NumPy documentation (http://docs.scipy.org) to learn about several other features that are not covered here.

If you are already familiar with NumPy, you can optionally skip this introduction and directly...

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