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

Abstractions

An API allows us to use a piece of software without totally understanding all the different steps that are involved. It presents a clear menu of actions that can be performed, enabling an external user, who doesn't necessarily understand the complexities of the operation, to perform them efficiently. It presents a simplification of the process.

These actions can be purely functional, where the output is only related to the input; for example, a mathematical function that calculates the barycenter of a planet and a star, given their orbits and masses.

Alternatively, they can deal with state, as the same action repeated twice may have different effects; for example, retrieving the time in the system. Perhaps even a call allows the time zone of the computer to be set, and two subsequent calls to retrieve the time may return very different results.

In both cases, the APIs are defining abstractions. Retrieving the time of the system in a single operation...