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

Local debugging

Debugging locally means exposing and fixing a problem once we have a local reproduction.

The basic steps of debugging are reproducing the problem, knowing what the current, incorrect result is, and knowing what the correct result should be. With that information, we can start debugging.

A great way of creating the reproduction of the problem is with a test, if that's possible. As we saw in Chapter 10, Testing and TDD, this is the basis of TDD. Create a test that fails and then change the code to make it pass. This approach is very usable when fixing bugs.

Taking a step back, any debugging process follows the following process:

  1. You realize there's a problem
  2. You understand what the correct behavior should be
  3. You investigate and discover why the current system behaves incorrectly
  4. You fix the problem

Keeping this process in mind is also useful from a local debugging perspective, though at this point...