pydantic-ddd-interface 0.1.2

A Python library providing interface definitions for Domain-Driven Design (DDD) patterns using Pydantic for type safety and validation.

🏛️ Pydddi

Pydantic-powered Domain-Driven Design Interfaces

A modern Python library for building clean, type-safe DDD applications

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Transform your Python applications with enterprise-grade DDD patterns 🚀

✨ What is Pydddi?

Pydddi brings the power of Domain-Driven Design to Python with type safety at its core. Built on top of Pydantic, it provides clean interfaces and patterns that make your code more maintainable, testable, and scalable.

🎯 Why Choose Pydddi?

Feature	Benefit
🔒 Type Safety	Catch errors at development time with Pydantic validation
🏗️ Clean Architecture	Enforce separation of concerns with clear layer boundaries
🧩 Modular Design	Mix and match interfaces based on your needs
⚡ Modern Python	Leverages Python 3.12+ features for optimal performance
📖 Self-Documenting	Interfaces serve as living documentation

🚀 Features

🏛️ Domain Layer Type-safe entities with identity Value objects using Pydantic Domain service abstractions Rich domain modeling	⚙️ Application Layer Command/Result pattern Use case interfaces Structured error handling Business workflow orchestration
🗄️ Infrastructure Layer Repository patterns (CRUD, Read, Aggregate) Schema-based operations Database abstraction External service integration	🧪 Developer Experience Full type hints support IDE autocompletion Runtime validation Clear error messages

📦 Quick Start

# Install the package
pip install pydantic-ddd-interface

# Start building your domain
from pydddi import IEntity, IUseCase, ICrudRepository

# You're ready to build enterprise-grade applications! 🎉

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🔧 Usage Examples

💡 Tip: Each layer has a specific responsibility. Start with the domain and work your way out!

🏛️ Domain Layer

Define your business entities and value objects

from pydddi import IEntity, IModel

class User(IEntity[int]):
    """Lightweight user entity - just identity and core attributes"""
    id: int
    name: str
    email: str
    
    def get_id(self) -> int:
        return self.id

class UserProfile(IModel):
    """Heavy model with relationships - used in domain logic processing"""
    user: User
    posts: List["Post"]
    followers: List["User"]
    settings: "UserSettings"
    activity_history: List["ActivityLog"]
    
    # Domain logic methods can access all related data
    def get_total_engagement(self) -> int:
        return sum(post.likes + post.comments for post in self.posts)

⚙️ Application Layer

Orchestrate business workflows with use cases

from pydddi import IUseCase, IUseCaseCommand, IUseCaseResult

class CreateUserCommand(IUseCaseCommand):
    """Command to create a new user"""
    name: str
    email: str

class CreateUserResult(IUseCaseResult):
    """Result of user creation"""
    user_id: int
    success: bool
    message: str

class CreateUserUseCase(IUseCase[CreateUserCommand, CreateUserResult]):
    """Use case for creating users with business validation"""
    
    async def execute(self, command: CreateUserCommand) -> CreateUserResult:
        # Your business logic here
        # - Validate email uniqueness
        # - Apply business rules
        # - Persist user
        pass

🗄️ Infrastructure Layer

Handle data persistence and external integrations

from pydddi import ICrudRepository, IReadRepository, IReadAggregateRepository
from pydddi import ICreateSchema, IUpdateSchema

class UserCreateSchema(ICreateSchema):
    """Schema for user creation"""
    name: str
    email: str

class UserUpdateSchema(IUpdateSchema):
    """Schema for user updates"""
    name: str | None = None
    email: str | None = None

🔍 Click to see repository implementations

# 🔨 CRUD Repository - for lightweight entity operations
class UserCrudRepository(ICrudRepository[User, UserCreateSchema, User, UserUpdateSchema]):
    async def create(self, schema: UserCreateSchema) -> User:
        """Create a new user entity (lightweight)"""
        pass
    
    async def read(self, id: int) -> User:
        """Get user entity by ID (no relationships)"""
        pass
    
    # ... other CRUD methods

# 📖 Read Repository - for simple read operations on lightweight entities  
class UserReadRepository(IReadRepository[User, User]):
    async def read(self, id: int) -> User:
        """Get user entity without relationships"""
        pass
    
    async def list(self, limit: int = None, **filters) -> List[User]:
        """List user entities (lightweight)"""
        pass

# 🔗 Read Aggregate Repository - for heavy models with full relationships
class UserProfileRepository(IReadAggregateRepository[UserProfile, User]):
    async def read(self, id: int) -> UserProfile:
        """Get heavy UserProfile with all related data (posts, followers, etc.)"""
        pass
    
    async def list(self, limit: int = None, **filters) -> List[UserProfile]:
        """List UserProfile with full relationship data for domain processing"""
        pass

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🏗️ Architecture Overview

graph TB
    subgraph "🖥️ Presentation Layer"
        API[REST API / GraphQL]
        CLI[CLI Commands]
    end
    
    subgraph "⚙️ Application Layer"
        UC[Use Cases]
        CMD[Commands & Results]
    end
    
    subgraph "🏛️ Domain Layer"
        ENT[Entities]
        VO[Value Objects]
        DS[Domain Services]
    end
    
    subgraph "🗄️ Infrastructure Layer"
        REPO[Repositories]
        DB[(Database)]
        EXT[External APIs]
    end
    
    API --> UC
    CLI --> UC
    UC --> ENT
    UC --> REPO
    REPO --> DB
    REPO --> EXT
    
    style UC fill:#e1f5fe
    style ENT fill:#f3e5f5
    style REPO fill:#e8f5e8

🎯 Design Principles

Principle	Implementation
🔒 Dependency Inversion	Infrastructure depends on domain abstractions
🧩 Single Responsibility	Each interface has one clear purpose
⚡ Open/Closed	Extend behavior without modifying existing code
🎭 Interface Segregation	Small, focused interfaces over large ones

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📚 API Reference

🏛️ Domain Layer APIs

Entities & Models

• IEntity - Base class for entities with identity and lifecycle
• IModel - Base class for value objects using Pydantic validation
• IDomainService - Interface for domain services containing business logic

⚙️ Application Layer APIs

Use Cases & Commands

• IUseCase[TCommand, TResult] - Generic interface for business use cases
• IUseCaseCommand - Base class for use case input commands
• IUseCaseResult - Base class for use case output results

Exception Handling

• UseCaseError - Base exception for use case operations
• UseCaseCommandError - Command validation errors
• UseCaseResultError - Result validation errors
• UseCaseExecutionError - Execution-time errors

🗄️ Infrastructure Layer APIs

Repository Patterns

• ICrudRepository[TEntity, TCreateSchema, TReadSchema, TUpdateSchema] - Full CRUD operations
• IReadRepository[TEntity, TReadSchema] - Read-only operations for entities
• IReadAggregateRepository[TModel, TReadAggregateSchema] - Complex reads with relationships

Data Schemas

• ICreateSchema - Schema for create operations
• IReadSchema - Schema for read operations
• IUpdateSchema - Schema for update operations
• IReadAggregateSchema - Schema for aggregate read operations

Exception Handling

• RepositoryError - Base repository exception
• RecordNotFoundError - Entity not found errors
• DuplicateRecordError - Duplicate entity errors

🎯 Repository Usage Guide

Repository Type	Use Case	Returns	Example	Weight
ICrudRepository	Lightweight entity lifecycle	IEntity	User CRUD operations	🪶 Light
IReadRepository	Simple entity queries	IEntity	User identity lookup	🪶 Light
IReadAggregateRepository	Heavy models with relationships	IModel	UserProfile with posts/followers	🏋️ Heavy

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🤝 Contributing

We welcome contributions! Here's how you can help:

🐛 Found a Bug?	💡 Have an Idea?	📖 Improve Docs?
Open an Issue	Start a Discussion	Submit a PR

🛠️ Development Setup

# Clone the repository
git clone https://github.com/nodashin/pydantic-ddd-interface.git
cd pydantic-ddd-interface

# Install dependencies
poetry install

# Run tests
poetry run pytest

# Format code
poetry run black .

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📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

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Made with ❤️ for the Python DDD community

Star ⭐ this repo if you find it useful!