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

Part III

Implementation

Designing is an important stage to have a plan of action, but really the meat of the developing process is in the implementation.

Implementing the general architecture design will require multiple smaller design decisions about how the code needs to be structured and developed. It doesn't matter how good the design is, the execution is critical and will validate or adjust the prepared plan.

A solid implementation, then, requires developers to be skeptical about their own coding abilities and code needs to be tested thoroughly before it can be considered "done." This is a normal operation, and when done constantly, it produces good cascading effects, not only improving the quality of the code and reducing the number of problems but also increasing the capacity of the team to foresee weak points and harden them to be sure that, once in operation, the software is reliable and works with as few problems as possible.

...