py-hexagonal-arch 1.0.3

A comprehensive Python framework implementing Hexagonal Architecture with multi-framework, multi-database, and multi-messaging support

Python Hexagonal Architecture Package

A Python package implementing hexagonal architecture pattern with multi-framework web support.

Features

• ✅ Hexagonal Architecture: Clean separation of concerns with ports and adapters
• ✅ Multi-Framework Support: FastAPI, Flask, and Tornado support out of the box
• ✅ Base Controllers: Generic CRUD operations with filtering
• ✅ Multi-Database Support: PostgreSQL, MariaDB, SQL Server, Oracle
• ✅ Multi-Messaging Support: Kafka, RabbitMQ, AWS Kinesis, GCP Pub/Sub
• ✅ Multi-Cache Support: Redis, MemCache, and In-Memory caching
• ✅ Type Safety: Full type hints support

Structure

src/
├── adapters/           # External adapters (web, db, cache, etc.)
│   ├── routers/       # Web framework routers
│   ├── repositories/  # Data access implementations
│   ├── caches/        # Cache implementations
│   └── events/        # Event handlers
├── controllers/        # Application controllers
├── models/            # Domain models
├── ports/             # Application ports (interfaces)
├── schemas/           # Data schemas
└── config/            # Configuration

Installation

Quick Install

# Basic installation (includes PostgreSQL and FastAPI)
pip install py-hexagonal-arch

# Install with specific extras
pip install py-hexagonal-arch[redis,kafka,flask]

# Install everything (all adapters)
pip install py-hexagonal-arch[all]

Available Extras

# Web frameworks
pip install py-hexagonal-arch[flask]      # Flask support
pip install py-hexagonal-arch[tornado]    # Tornado support

# Databases  
pip install py-hexagonal-arch[mysql]      # MariaDB/MySQL support
pip install py-hexagonal-arch[sqlserver]  # SQL Server support
pip install py-hexagonal-arch[oracle]     # Oracle support

# Cache systems
pip install py-hexagonal-arch[redis]      # Redis support
pip install py-hexagonal-arch[memcache]   # MemCache support

# Event messaging
pip install py-hexagonal-arch[kafka]      # Kafka support
pip install py-hexagonal-arch[rabbitmq]   # RabbitMQ support  
pip install py-hexagonal-arch[kinesis]    # AWS Kinesis support
pip install py-hexagonal-arch[pubsub]     # GCP Pub/Sub support

# Development tools
pip install py-hexagonal-arch[dev]        # Development dependencies
pip install py-hexagonal-arch[docs]       # Documentation tools

Quick Start

1. Create a Model

from py_hexagonal_arch import CustomModel
from typing import Optional

class User(CustomModel):
    id: Optional[str] = None
    name: str
    email: str
    age: int

2. Create a Controller

from py_hexagonal_arch import BaseController

class UserController(BaseController[User]):
    # Implement your business logic
    pass

3. Set Up Repository

from py_hexagonal_arch import BaseRepository

class UserRepository(BaseRepository[User]):
    def __init__(self):
        super().__init__(model=User, schema=UserSchema)

# PostgreSQL (default)
user_repo = UserRepository()

# MariaDB/MySQL
user_repo = UserRepository(db_type="mariadb")

# SQL Server
user_repo = UserRepository(db_type="sqlserver")

# Oracle
user_repo = UserRepository(db_type="oracle")

# Basic operations
user = User(name="John", email="[e-mail]")
created_user = await user_repo.create(user)
users = await user_repo.list()

📖 For detailed repository documentation, configuration, and advanced usage, see: src/adapters/repositories/README.md

4. Create a Router

from py_hexagonal_arch import BaseRouter

# FastAPI (default)
user_router = BaseRouter(
    model=User,
    controller=UserController,
    prefix="/users",
    tags=["users"]
)

# Flask
user_router = BaseRouter(
    model=User,
    controller=UserController,
    prefix="/users",
    tags=["users"],
    framework="flask"
)

# Tornado
user_router = BaseRouter(
    model=User,
    controller=UserController,
    prefix="/users",
    tags=["users"],
    framework="tornado"
)

📖 For detailed router documentation, patterns, and advanced usage, see: src/adapters/routers/README.md

5. Set Up Caching

from py_hexagonal_arch import BaseCache

class UserCache(BaseCache[User]):
    def __init__(self):
        super().__init__(model=User)

# Redis (default)
user_cache = UserCache()

# MemCache
user_cache = UserCache(
    cache_type="memcache",
    servers=["localhost:11211"]
)

# In-Memory (for testing)
user_cache = UserCache(cache_type="memory")

# Usage
user = User(id="1", name="John", email="[e-mail]", age=30)
await user_cache.set("user:1", user)
cached_user = await user_cache.get("user:1")

📖 For detailed cache documentation, patterns, and advanced usage, see: src/adapters/caches/README.md

6. Set Up Events

from py_hexagonal_arch import BaseEvent

class UserEvent(BaseEvent[User]):
    def __init__(self):
        super().__init__(model=User)

# Kafka (default)
user_events = UserEvent()

# RabbitMQ
user_events = UserEvent(event_type="rabbitmq")

# AWS Kinesis
user_events = UserEvent(event_type="kinesis")

# Basic operations
await user_events.push("created", user, key=user.id)
async for user_data in user_events.pull("created"):
    print(f"User event: {user_data.name}")

📖 For detailed event documentation, patterns, and advanced usage, see: src/adapters/events/README.md

Examples

See the examples/ directory for complete working examples with each framework and caching system.

• fastapi_example.py - FastAPI implementation
• flask_example.py - Flask implementation
• tornado_example.py - Tornado implementation
• repositories_example.py - Multi-database repository examples
• cache_example.py - Comprehensive caching examples
• events_example.py - Multi-backend event messaging examples

License

MIT License