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

Summary

In this chapter, we started by presenting the basic elements of logs. We defined how logs contain messages plus some metadata like a timestamp, and considered the different severity levels. We also described the need to define request IDs to group logs related to the same task. We also discussed how, in the Twelve-Factor App methodology, logs should be sent to stdout to detach log generation from the process of handling and routing them to the proper destination to allow the collection of all logs in the system.

We then showed how to produce logs in Python using the standard logging module, describing the three key elements of the logger, the handler, and the formatter. Next, we showed the two different errors that can be produced in a system: expected, understood as errors that were foreseen as possible and are handled; and unexpected, meaning those that were not foreseen and occurred out of our control. We then went through the different strategies and cases for these...