Book Image

Software Architecture with Python

By : Anand Balachandran Pillai
Book Image

Software Architecture with Python

By: Anand Balachandran Pillai

Overview of this book

This book starts by explaining how Python fits into an application's architecture. As you move along, you will get to grips with architecturally significant demands and how to determine them. Later, you’ll gain a complete understanding of the different architectural quality requirements for building a product that satisfies business needs, such as maintainability/reusability, testability, scalability, performance, usability, and security. You will also use various techniques such as incorporating DevOps, continuous integration, and more to make your application robust. You will discover when and when not to use object orientation in your applications, and design scalable applications. The focus is on building the business logic based on the business process documentation, and understanding which frameworks to use and when to use them. The book also covers some important patterns that should be taken into account while solving design problems, as well as those in relatively new domains such as the Cloud. By the end of this book, you will have understood the ins and outs of Python so that you can make critical design decisions that not just live up to but also surpassyour clients’ expectations.
Table of Contents (18 chapters)
Software Architecture with Python
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
Index

Multithreading versus multiprocessing


Now that we have come to the end of our discussion on multi-processing, it is a good time to compare and contrast the scenarios where one needs to choose between scaling using threads in a single process or using multiple processes in Python.

Here are some guidelines.

Use multithreading in the following cases:

  1. The program needs to maintain a lot of shared states, especially mutable ones. A lot of the standard data structures in Python, such as lists, dictionaries, and others, are thread-safe, so it costs much less to maintain a mutable shared state using threads than via processes.

  2. The program needs to keep a low memory foot-print.

  3. The program spends a lot of time doing I/O. Since the GIL is released by threads doing I/O, it doesn't affect the time taken by the threads to perform I/O.

  4. The program doesn't have a lot of data parallel operations which it can scale across multiple processes

Use multiprocessing in these scenarios:

  1. The program performs a lot of CPU...