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

Package Management

When working in complex systems, especially in microservices or similar architectures, there is sometimes a need to share code so it's available at different, unconnected parts of the system. That's normally code that will help to abstract some functions, which can vary greatly, from security purposes (for example, calculating a signature in a way that's understood by other systems that will have to verify it), to connecting to databases or external APIs, or even helping to monitor the system consistently.

Instead of reinventing the wheel each time, we can reuse the same code multiple times to be certain that it's properly tested and validated, and consistent throughout the entire system. Some modules may be interesting to share not only across the organization but even outside it, creating a standard module others can take advantage of.

Others have done that before, and a lot of common use cases, such as connecting to existing databases...