Book Image

Hands-On Enterprise Application Development with Python

By : Saurabh Badhwar
Book Image

Hands-On Enterprise Application Development with Python

By: Saurabh Badhwar

Overview of this book

Dynamically typed languages like Python are continuously improving. With the addition of exciting new features and a wide selection of modern libraries and frameworks, Python has emerged as an ideal language for developing enterprise applications. Hands-On Enterprise Application Development with Python will show you how to build effective applications that are stable, secure, and easily scalable. The book is a detailed guide to building an end-to-end enterprise-grade application in Python. You will learn how to effectively implement Python features and design patterns that will positively impact your application lifecycle. The book also covers advanced concurrency techniques that will help you build a RESTful application with an optimized frontend. Given that security and stability are the foundation for an enterprise application, you’ll be trained on effective testing, performance analysis, and security practices, and understand how to embed them in your codebase during the initial phase. You’ll also be guided in how to move on from a monolithic architecture to one that is service oriented, leveraging microservices and serverless deployment techniques. By the end of the book, you will have become proficient at building efficient enterprise applications in Python.
Table of Contents (24 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
Index

Concurrent programming with Python


Python provides a number of ways through which parallelism or concurrency can be achieved. All of these methods have their own pros and cons, and differ fundamentally in terms of how they are implemented, and a choice needs to be made about which method to use when, keeping the use case in mind.

One of the methods provided by Python for implementing concurrency is performed at the thread level by allowing the application to launch multiple threads, each executing a job. These threads provide an easy-to-use concurrency mechanism and execute inside a single Python interpreter process, and hence are lightweight.

 

 

Another mechanism for achieving parallelism is through the use of multiple processes in place of multiple threads. With this approach, every process performs a separate task inside its own separate Python interpreter process. This approach provides some workarounds to the problems that a multithreaded Python program may face in the presence of the...