As Python continues to grow in popularity, projects are becoming larger and more complex.
Patterns include: Dependency inversion and its links to ports and adapters (hexagonal/clean architecture) Domain-Driven design\'s distinction between Entities, Value Objects, and Aggregates Repository and Unit of Work Patterns for persistent storage Events, commands, and the message bus Command-query responsibility segregation (CQRS) Event-Driven Architecture and reactive microservices.
Each pattern is illustrated with concrete examples in beautiful, idiomatic Python, avoiding some of the verbosity of Java and C# syntax.
with this hands-on guide, Harry Percival and Bob Gregory from MADE.com introduce proven architectural Design Patterns to help Python developers manage application complexity--and get the most value out of their test suites.
But translating those Patterns into Python isn\'t always straightforward.
Many Python developers are taking an interest in high-level software Design Patterns such as hexagonal/clean architecture, Event-Driven architecture, and the strategic Patterns prescribed by Domain-Driven Design (DDD).
As Python continues to grow in popularity, projects are becoming larger and more complex
