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

Parallelization with the multiprocessing module


Before jumping onto the discussion of the multiprocessing module, let's first understand what we mean by parallelization. This will be a very short introduction to parallelization, just enough to understand how to use some features of the multiprocessing module.

Introduction to parallelization

Imagine you are standing in a long queue at a checkout counter in a grocery store, waiting for your turn. Now, three more counters are opened to serve the customers and the existing queue is split. As a result, you can pay and get out of the store quickly.

Parallelization, in some sense, accomplishes similar results. In this example, each counter can be imagined as a separate process, carrying out independent tasks of accepting payments. The initial queue of the customers can be imagined as your program. This long queue is then divided into independent queues (or tasks), processing them parallely on separate counters (processes).

The Gold Hunt program we...