Which Python libraries are supported by these guidelines?

The guidelines are optimized for FastAPI, Pydantic, SQLAlchemy or SQLModel, Alembic for migrations, and Pytest for testing.

Does it provide directory structure examples?

Yes, it includes specific templates for directory organization to help developers place domain logic, repositories, and controllers in the correct locations.

Does this skill work with existing FastAPI projects?

Yes, it includes specific procedures for refactoring existing codebases to align with domain, application, and infrastructure layer boundaries.

How does it handle database transactions?

The skill utilizes the Unit of Work (UoW) pattern and FastAPI's 'Depends' system to manage one session per request, ensuring atomic transactions.

What is the primary benefit of the FastAPI DDD Guidelines skill?

It provides a standardized architectural blueprint that ensures your FastAPI project is modular, testable, and follows enterprise-grade Domain-Driven Design principles.

FastAPI DDD Guidelines

Name: FastAPI DDD Guidelines
Author: Higashi-Masafumi

byHigashi-Masafumi

Desarrollo de API

Standardizes FastAPI backend development using Domain-Driven Design (DDD) principles and structured layered architecture.

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This skill provides a comprehensive framework for architecting FastAPI applications following Domain-Driven Design (DDD) patterns. It guides developers through defining clear layer boundaries—including domain, application, infrastructure, and controllers—while enforcing strict dependency directions and robust session management. Whether you are bootstrapping a new project or refactoring an existing codebase, this skill ensures best practices for Pydantic models, SQLAlchemy/SQLModel integration, and the Unit of Work (UoW) pattern to create scalable and maintainable Python backends.

Características Principales

Enforces clear rules for dependency direction and responsibility boundaries across the codebase.
Standardizes session management using the Unit of Work (UoW) pattern and FastAPI Dependency Injection.
0 GitHub stars
Provides implementation templates for Pydantic schemas and SQLModel/SQLAlchemy database models.
Includes best practices for database migrations with Alembic and automated testing with Pytest.
Implements a structured four-layer DDD architecture: Domain, Application, Infrastructure, and Controller.

Casos de Uso

Architecting a new enterprise-grade FastAPI backend with a focus on long-term maintainability.
Establishing consistent transaction management and repository patterns across a development team.
Refactoring a monolithic or disorganized FastAPI codebase into a clean, layered DDD structure.

Acerca de

Características Principales

Enforces clear rules for dependency direction and responsibility boundaries across the codebase.
Standardizes session management using the Unit of Work (UoW) pattern and FastAPI Dependency Injection.
0 GitHub stars
Provides implementation templates for Pydantic schemas and SQLModel/SQLAlchemy database models.
Includes best practices for database migrations with Alembic and automated testing with Pytest.
Implements a structured four-layer DDD architecture: Domain, Application, Infrastructure, and Controller.

Casos de Uso

Architecting a new enterprise-grade FastAPI backend with a focus on long-term maintainability.
Establishing consistent transaction management and repository patterns across a development team.
Refactoring a monolithic or disorganized FastAPI codebase into a clean, layered DDD structure.