Book Image

Python Architecture Patterns

By : Jaime Buelta
Book Image

Python Architecture Patterns

By: Jaime Buelta

Overview of this book

Developing large-scale systems that continuously grow in scale and complexity requires a thorough understanding of how software projects should be implemented. Software developers, architects, and technical management teams rely on high-level software design patterns such as microservices architecture, event-driven architecture, and the strategic patterns prescribed by domain-driven design (DDD) to make their work easier. This book covers these proven architecture design patterns with a forward-looking approach to help Python developers manage application complexity—and get the most value out of their test suites. Starting with the initial stages of design, you will learn about the main blocks and mental flow to use at the start of a project. The book covers various architectural patterns like microservices, web services, and event-driven structures and how to choose the one best suited to your project. Establishing a foundation of required concepts, you will progress into development, debugging, and testing to produce high-quality code that is ready for deployment. You will learn about ongoing operations on how to continue the task after the system is deployed to end users, as the software development lifecycle is never finished. By the end of this Python book, you will have developed "architectural thinking": a different way of approaching software design, including making changes to ongoing systems.
Table of Contents (23 chapters)
2
Part I: Design
6
Part II: Architectural Patterns
12
Part III: Implementation
15
Part IV: Ongoing operations
21
Other Books You May Enjoy
22
Index

The key factor – team communication

A key element of the difference between microservices and monolithic architecture is the difference in the communication structure that they support.

If the monolithic application has grown organically from a small project, as usually happens, the internal structure can become messy, and requires developers with experience in the system who can change and adapt it for any change. In bad cases, the code can become very chaotic and be more and more complicated to work with.

Increasing the size of the development team becomes complicated, as each engineer requires a lot of contextual information, and learning how to navigate the code is difficult. The older teammates who have been around can help to train new team members, but they'll act as bottlenecks, and mentoring is a slow process that has limits. Each new member of the team will require a significant amount of training time until they can be productive in fixing bugs and adding...