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

Performance improvement goodies


Let's spend some time discussing miscellaneous tips and tricks that help improve the runtime performance of the code. You can still apply a few of these techniques to the Gold Hunt problem, but let's just use generic examples to explain these concepts.

Tip

All the illustrations in this section can be found in the supporting file, misc_performance.py. To compare the performance, we will use the timeit module that was discussed in Chapter 7, Performance – Identifying Bottlenecks (refer to the Measuring runtime of small code snippets section). See also the timeit documentation, https://docs.python.org/3/library/timeit.html.

List comprehension

List comprehension is a compact way of creating a Python list. It is often used to replace the nested for loops or the map and filter functionality. Besides being compact, it is also efficient compared to, for instance, an equivalent for loop. The basic syntax is as follows:

a = [i*i for i in range(5)] 

This creates a list with...