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

Chapter 9. Deploying Python Applications

Pushing code to production is often the last step in taking an application from development to the customer. Though this is an important activity, it often gets overlooked in the scheme of importance in a software architect's checklist.

It is a pretty common and fatal mistake to assume that if a system works in the development environment, it will work dutifully in production also. For one thing, the configuration of a production system is often very different from that of a development environment. Many optimizations and debugging that are available and taken for granted in a developer's box, are often not available in the production setup.

Deployment to production is an art rather than an exact science. The complexity of deployment of a system depends on a number of factors, such as the language the system is developed in, its runtime portability and performance, the number of configuration parameters, whether the system is deployed in a homogeneous...