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

Summary


This chapter was all about performance. At the start of the chapter, we discussed performance and SPE. We looked at the two categories of performance testing and diagnostic tools – namely, stress testing tools and profiling/instrumentation tools.

We then discussed what performance complexity really means in terms of the Big-O notation and discussed briefly the common time orders of functions. We looked at the time taken by functions to execute and learned the three classes of time usage – namely real, user, and sys in POSIX systems.

We moved on to measuring performance and time in the next section – starting with a simple context manager timer and moving on to more accurate measurements using the timeit module. We measured the time taken for certain algorithms for a range of input sizes. By plotting the time taken against the input size and superimposing it on the standard time complexity graphs, we were able to get a visual understanding of the performance complexity of functions...