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Python Architecture Patterns

Python Architecture Patterns

By : Jaime Buelta
4.6 (22)
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Python Architecture Patterns

Python Architecture Patterns

4.6 (22)
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)
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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

Testing philosophy

A key element of everything involved with testing is another question: Why test? What are we trying to achieve with it?

As we've seen, testing is a way of ensuring that the behavior of the code is the expected one. The objective of testing is to detect possible problems (sometimes called defects) before the code is published and used by real users.

There's a subtle difference between defects and bugs. Bugs are a kind of defect where the software behaves in a way that it's not expected to. For example, certain input produces an unexpected error. Defects are more general. A defect could be that a button is not visible enough, or that the logo on a page is not the correct one. In general, tests are way better at detecting bugs than other defects, but remember what we said about exploratory testing.

A defect that goes undetected and gets deployed into a live system is pretty expensive to repair. First of all, it needs to be detected...

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