python-ddd

Structure a Python domain-driven design project using a four-layer architecture: domain, application, infrastructure, and adapters. This separation enforces clear boundaries between business logic and infrastructure, ensuring the domain layer remains free of framework dependencies.

Domain-driven design fully supports async Python workflows by utilizing an async-friendly CQRS architecture. This allows scalable and testable services where the application layer coordinates use cases and emits domain events asynchronously.

Implement aggregates and value objects in Python as first-class domain concepts with explicit invariants. Using modern tooling like Pydantic v2, you can enforce strict validation rules and maintain clear boundaries within the domain layer.

You can use SQLAlchemy 2.0 for repositories in a DDD architecture by placing it strictly in the infrastructure layer. This ensures the domain layer has no framework dependencies while repositories handle data persistence asynchronously.

The best way to separate domain logic from infrastructure in Python is by applying a CQRS-oriented architecture with well-defined repositories. This isolates business rules into aggregates and domain events, while the application layer coordinates use cases.

You need CQRS in a Python domain-driven design project when building scalable, testable services with async workflows. It separates read and write operations, allowing the application layer to coordinate use cases and emit domain events efficiently.