Book Image

Learning Python Application Development

By : Ninad Sathaye
Book Image

Learning Python Application Development

By: Ninad Sathaye

Overview of this book

Python is one of the most widely used dynamic programming languages, supported by a rich set of libraries and frameworks that enable rapid development. But fast paced development often comes with its own baggage that could bring down the quality, performance, and extensibility of an application. This book will show you ways to handle such problems and write better Python applications. From the basics of simple command-line applications, develop your skills all the way to designing efficient and advanced Python apps. Guided by a light-hearted fantasy learning theme, overcome the real-world problems of complex Python development with practical solutions. Beginning with a focus on robustness, packaging, and releasing application code, you’ll move on to focus on improving application lifetime by making code extensible, reusable, and readable. Get to grips with Python refactoring, design patterns and best practices. Techniques to identify the bottlenecks and improve performance are covered in a series of chapters devoted to performance, before closing with a look at developing Python GUIs.
Table of Contents (18 chapters)
Learning Python Application Development
Credits
Disclaimers
About the Author
About the Reviewer
www.PacktPub.com
Preface
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...