architecture-patterns
Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use this skill when designing clean architecture for a new microservice, when refactoring a monolith to use bounded contexts, when implementing hexagonal
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Skill manifest
Architecture Patterns
Master proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to build maintainable, testable, and scalable systems.
Given: a service boundary or module to architect. Produces: layered structure with clear dependency rules, interface definitions, and test boundaries.
When to Use This Skill
- Designing new backend services or microservices from scratch
- Refactoring monolithic applications where business logic is entangled with ORM models or HTTP concerns
- Establishing bounded contexts before splitting a system into services
- Debugging dependency cycles where infrastructure code bleeds into the domain layer
- Creating testable codebases where use-case tests do not require a running database
- Implementing domain-driven design tactical patterns (aggregates, value objects, domain events)
Core Concepts
1. Clean Architecture (Uncle Bob)
Layers (dependency flows inward):
- Entities: Core business models, no framework imports
- Use Cases: Application business rules, orchestrate entities
- Interface Adapters: Controllers, presenters, gateways — translate between use cases and external formats
- Frameworks & Drivers: UI, database, external services — all at the outermost ring
Key Principles:
- Dependencies point inward only; inner layers know nothing about outer layers
- Business logic is independent of frameworks, databases, and delivery mechanisms
- Every layer boundary is crossed via an abstract interface
- Testable without UI, database, or external services
2. Hexagonal Architecture (Ports and Adapters)
Components:
- Domain Core: Business logic lives here, framework-free
- Ports: Abstract interfaces that define how the core interacts with the outside world (driving and driven)
- Adapters: Concrete implementations of ports (PostgreSQL adapter, Stripe adapter, REST adapter)
Benefits:
- Swap implementations without touching the core (e.g., replace PostgreSQL with DynamoDB)
- Use in-memory adapters in tests — no Docker required
- Technology decisions deferred to the edges
3. Domain-Driven Design (DDD)
Strategic Patterns:
- Bounded Contexts: Isolate a coherent model for one subdomain; avoid sharing a single model across the whole system
- Context Mapping: Define how contexts relate (Anti-Corruption Layer, Shared Kernel, Open Host Service)
- Ubiquitous Language: Every term in code matches the term used by domain experts
Tactical Patterns:
- Entities: Objects with stable identity that change over time
- Value Objects: Immutable objects identified by their attributes (Email, Money, Address)
- Aggregates: Consistency boundaries; only the root is accessible from outside
- Repositories: Persist and reconstitute aggregates; abstract over the storage mechanism
- Domain Events: Capture things that happened inside the domain; used for cross-aggregate coordination
Detailed patterns and worked examples
Detailed pattern documentation lives in references/details.md. Read that file when the navigation tier above is insufficient.
Testing — In-Memory Adapters
The hallmark of correctly applied Clean Architecture is that every use case can be exercised in a plain unit test with no real database, no Docker, and no network:
# tests/unit/test_create_user.py
import asyncio
from typing import Dict, Optional
from domain.entities.user import User
from domain.interfaces.user_repository import IUserRepository
from use_cases.create_user import CreateUserUseCase, CreateUserRequest
class InMemoryUserRepository(IUserRepository):
def __init__(self):
self._store: Dict[str, User] = {}
async def find_by_id(self, user_id: str) -> Optional[User]:
return self._store.get(user_id)
async def find_by_email(self, email: str) -> Optional[User]:
return next((u for u in self._store.values() if u.email == email), None)
async def save(self, user: User) -> User:
self._store[user.id] = user
return user
async def delete(self, user_id: str) -> bool:
return self._store.pop(user_id, None) is not None
async def test_create_user_succeeds():
repo = InMemoryUserRepository()
use_case = CreateUserUseCase(user_repository=repo)
response = await use_case.execute(CreateUserRequest(email="alice@example.com", name="Alice"))
assert response.success
assert response.user.email == "alice@example.com"
assert response.user.id is not None
async def test_duplicate_email_rejected():
repo = InMemoryUserRepository()
use_case = CreateUserUseCase(user_repository=repo)
await use_case.execute(CreateUserRequest(email="alice@example.com", name="Alice"))
response = await use_case.execute(CreateUserRequest(email="alice@example.com", name="Alice2"))
assert not response.success
assert "already exists" in response.error
Troubleshooting
Use case tests require a running database
Business logic has leaked into the infrastructure layer. Move all database calls behind an IRepository interface and inject an in-memory implementation in tests (see Testing section above). The use case constructor must accept the abstract port, not the concrete class.
Circular imports between layers
A common symptom is ImportError: cannot import name X between use_cases and adapters. This happens when a use case imports a concrete adapter class instead of the abstract port. Enforce the rule: use_cases/ imports only from domain/ (entities and interfaces). It must never import from adapters/ or infrastructure/.
Framework decorators appearing in domain entities
If SQLAlchemy Column() or Pydantic Field() annotations appear on domain entities, the entity is no longer pure. Create a separate ORM model in adapters/repositories/ and map to/from the domain entity in the repository's _to_entity() method.
All logic ending up in controllers
When the controller grows beyond HTTP parsing and response formatting, extract the logic into a use case class. A controller method should do three things only: parse the request, call a use case, map the response.
Value objects raising errors too late
Validate invariants in __post_init__ (Python) or the constructor so an invalid Email or Money cannot be constructed at all. This surfaces bad data at the boundary, not deep inside business logic.
Context bleed across bounded contexts
If the Order context is importing User entities from the Identity context, introduce an Anti-Corruption Layer. The Order context should hold its own lightweight CustomerId value object and only call the Identity context through an explicit interface.
Advanced Patterns
For detailed DDD bounded context mapping, full multi-service project trees, Anti-Corruption Layer implementations, and Onion Architecture comparisons, see:
Related Skills
microservices-patterns— Apply these architecture patterns when decomposing a monolith into servicescqrs-implementation— Use Clean Architecture as the structural foundation for CQRS command/query separationsaga-orchestration— Sagas require well-defined aggregate boundaries, which DDD tactical patterns provideevent-store-design— Domain events produced by aggregates feed directly into an event store
Files (agents)
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references
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advanced-patterns.md 15 KB
# Advanced Architecture Patterns — Reference Deep-dive implementation examples for DDD bounded contexts, Onion Architecture, Anti-Corruption Layers, and full project structures. Referenced from SKILL.md. --- ## Full Multi-Service Project Structure A realistic e-commerce system organised by bounded context, each context is a deployable service: ``` ecommerce/ ├── services/ │ ├── identity/ # Bounded context: users & auth │ │ ├── identity/ │ │ │ ├── domain/ │ │ │ │ ├── entities/ │ │ │ │ │ └── user.py │ │ │ │ ├── value_objects/ │ │ │ │ │ ├── email.py │ │ │ │ │ └── password_hash.py │ │ │ │ └── interfaces/ │ │ │ │ └── user_repository.py │ │ │ ├── use_cases/ │ │ │ │ ├── register_user.py │ │ │ │ └── authenticate_user.py │ │ │ ├── adapters/ │ │ │ │ ├── repositories/ │ │ │ │ │ └── postgres_user_repository.py │ │ │ │ └── controllers/ │ │ │ │ └── auth_controller.py │ │ │ └── infrastructure/ │ │ │ └── jwt_service.py │ │ └── tests/ │ │ ├── unit/ │ │ └── integration/ │ │ │ ├── catalog/ # Bounded context: products │ │ ├── catalog/ │ │ │ ├── domain/ │ │ │ │ ├── entities/ │ │ │ │ │ └── product.py │ │ │ │ └── value_objects/ │ │ │ │ ├── sku.py │ │ │ │ └── price.py │ │ │ └── use_cases/ │ │ │ ├── create_product.py │ │ │ └── update_inventory.py │ │ └── tests/ │ │ │ └── ordering/ # Bounded context: orders │ ├── ordering/ │ │ ├── domain/ │ │ │ ├── entities/ │ │ │ │ └── order.py │ │ │ ├── value_objects/ │ │ │ │ ├── customer_id.py # NOT imported from identity! │ │ │ │ └── money.py │ │ │ └── interfaces/ │ │ │ ├── order_repository.py │ │ │ └── catalog_client.py # ACL port to catalog context │ │ ├── use_cases/ │ │ │ ├── place_order.py │ │ │ └── cancel_order.py │ │ └── adapters/ │ │ ├── acl/ │ │ │ └── catalog_http_client.py # ACL adapter │ │ └── repositories/ │ │ └── postgres_order_repository.py │ └── tests/ │ ├── shared/ # Shared kernel (use sparingly) │ └── domain_events/ │ └── base_event.py └── docker-compose.yml ``` --- ## Onion Architecture vs. Clean Architecture Both enforce inward-pointing dependencies. The difference is terminology and layering granularity: | Concern | Clean Architecture | Onion Architecture | |---|---|---| | Innermost ring | Entities | Domain Model | | Second ring | Use Cases | Domain Services | | Third ring | Interface Adapters | Application Services | | Outermost ring | Frameworks & Drivers | Infrastructure / UI / Tests | | Key insight | Controller is an adapter | Application Services = Use Cases | Onion Architecture makes the Domain Services layer explicit — it hosts pure domain logic that spans multiple entities but has no I/O: ```python # onion/domain/services/pricing_service.py from domain.entities.product import Product from domain.value_objects.money import Money from domain.value_objects.discount import Discount class PricingService: """ Domain service: logic that doesn't belong to a single entity. No ports or adapters here — purely domain computation. """ def apply_bulk_discount(self, product: Product, quantity: int) -> Money: if quantity >= 100: discount = Discount(percentage=20) elif quantity >= 50: discount = Discount(percentage=10) else: discount = Discount(percentage=0) return product.price.apply_discount(discount) def calculate_order_total(self, items: list[tuple[Product, int]]) -> Money: subtotals = [self.apply_bulk_discount(p, q) for p, q in items] return sum(subtotals[1:], subtotals[0]) if subtotals else Money(0, "USD") ``` --- ## Anti-Corruption Layer (ACL) When the `Ordering` context must fetch product data from the `Catalog` context, it should never use `Catalog`'s domain model directly. An ACL translates between the two models: ```python # ordering/domain/interfaces/catalog_client.py from abc import ABC, abstractmethod from ordering.domain.value_objects.product_snapshot import ProductSnapshot class CatalogClientPort(ABC): """ Ordering's view of product data. Uses Ordering's own value object, not Catalog's Product entity. """ @abstractmethod async def get_product_snapshot(self, sku: str) -> ProductSnapshot: ... # ordering/domain/value_objects/product_snapshot.py from dataclasses import dataclass from ordering.domain.value_objects.money import Money @dataclass(frozen=True) class ProductSnapshot: """Ordering's local representation of a product at order time.""" sku: str name: str unit_price: Money available: bool # ordering/adapters/acl/catalog_http_client.py import httpx from ordering.domain.interfaces.catalog_client import CatalogClientPort from ordering.domain.value_objects.product_snapshot import ProductSnapshot from ordering.domain.value_objects.money import Money class CatalogHttpClient(CatalogClientPort): """ ACL adapter: calls Catalog's HTTP API and translates Catalog's response schema into Ordering's ProductSnapshot. """ def __init__(self, base_url: str, http_client: httpx.AsyncClient): self._base_url = base_url self._http = http_client async def get_product_snapshot(self, sku: str) -> ProductSnapshot: response = await self._http.get(f"{self._base_url}/products/{sku}") response.raise_for_status() data = response.json() # Translation: Catalog speaks "price_cents" + "currency_code"; # Ordering speaks Money(amount, currency). return ProductSnapshot( sku=data["sku"], name=data["title"], # field name differs between contexts unit_price=Money( amount=data["price_cents"], currency=data["currency_code"], ), available=data["stock_count"] > 0, ) # Test ACL with a stub — no HTTP required class StubCatalogClient(CatalogClientPort): def __init__(self, products: dict[str, ProductSnapshot]): self._products = products async def get_product_snapshot(self, sku: str) -> ProductSnapshot: if sku not in self._products: raise ValueError(f"Unknown SKU: {sku}") return self._products[sku] ``` --- ## Context Map — Relationships Between Bounded Contexts ``` ┌─────────────────────────────────────────────────────────────────┐ │ E-Commerce System │ │ │ │ ┌─────────────┐ Open Host ┌─────────────────────────┐ │ │ │ Identity │──────────────▶│ Ordering │ │ │ │ Context │ │ (uses CustomerId VO, │ │ │ │ │ │ not User entity) │ │ │ └─────────────┘ └─────────────────────────┘ │ │ │ ACL │ │ ▼ │ │ ┌─────────────────┐ │ │ ┌─────────────┐ Shared │ Catalog │ │ │ │ Payments │ Kernel │ Context │ │ │ │ Context │◀─────────────▶│ │ │ │ │ │ (Money VO) └─────────────────┘ │ │ └─────────────┘ │ └─────────────────────────────────────────────────────────────────┘ Relationship types: Open Host Service — upstream provides a stable API for many downstream contexts ACL (Anti-Corruption Layer) — downstream translates upstream model to its own Shared Kernel — two contexts share a small, explicitly governed sub-model Conformist — downstream adopts upstream model as-is (last resort) ``` --- ## Dependency Injection Wiring — Infrastructure Layer All the abstract interfaces are wired to concrete implementations in the infrastructure layer (or a DI container). Nothing else in the codebase knows which concrete class is used: ```python # infrastructure/container.py from functools import lru_cache import asyncpg from adapters.repositories.postgres_user_repository import PostgresUserRepository from adapters.gateways.stripe_payment_gateway import StripePaymentAdapter from use_cases.create_user import CreateUserUseCase from infrastructure.config import Settings @lru_cache def get_settings() -> Settings: return Settings() async def get_db_pool() -> asyncpg.Pool: settings = get_settings() return await asyncpg.create_pool(settings.database_url) async def get_create_user_use_case() -> CreateUserUseCase: pool = await get_db_pool() repo = PostgresUserRepository(pool=pool) return CreateUserUseCase(user_repository=repo) # In tests, replace get_create_user_use_case with a version # that injects InMemoryUserRepository — no other code changes needed. ``` --- ## Aggregate Design Heuristics Use these rules when deciding aggregate boundaries: | Question | Guidance | |---|---| | Should these two objects always be consistent together? | Put them in the same aggregate. | | Can they be eventually consistent? | Put them in separate aggregates; use domain events to sync. | | Is one object the "owner" that controls access? | That object is the aggregate root. | | Does removing the root make the child meaningless? | Child belongs inside the aggregate. | | Are you loading thousands of objects to change one? | Aggregate is too large — split it. | **Practical example — Order vs. Customer:** ```python # Bad: Customer aggregate holds full Order objects class Customer: def __init__(self): self._orders: list[Order] = [] # loads all orders every time # Good: Customer holds Order IDs only; Order is its own aggregate class Customer: def __init__(self): self._order_ids: list[str] = [] # lightweight reference class Order: def __init__(self, id: str, customer_id: str): self.id = id self.customer_id = customer_id # reference back, not the full object ``` --- ## Domain Events — Publishing and Handling Domain events decouple aggregates that need to react to each other's state changes: ```python # domain/events/order_events.py from dataclasses import dataclass, field from datetime import datetime @dataclass class DomainEvent: occurred_at: datetime = field(default_factory=datetime.utcnow) @dataclass class OrderSubmittedEvent(DomainEvent): order_id: str = "" customer_id: str = "" total_cents: int = 0 currency: str = "USD" # adapters/event_publisher/postgres_outbox.py # Transactional outbox pattern: write events to the same DB transaction as state import json class PostgresOutboxPublisher: """ Writes domain events to an outbox table in the same transaction as the aggregate state. A separate relay process reads and publishes to the message broker. Guarantees at-least-once delivery. """ async def publish(self, conn, events: list[DomainEvent]): for event in events: await conn.execute( """ INSERT INTO outbox (event_type, payload, published_at) VALUES ($1, $2, NULL) """, type(event).__name__, json.dumps(event.__dict__, default=str), ) # use_cases/place_order.py — aggregate saves, events are extracted and stored class PlaceOrderUseCase: def __init__(self, order_repo: OrderRepository, event_publisher: PostgresOutboxPublisher): self.orders = order_repo self.publisher = event_publisher async def execute(self, request: PlaceOrderRequest) -> PlaceOrderResponse: order = Order(id=str(uuid.uuid4()), customer_id=request.customer_id) for item in request.items: order.add_item(product=item.product, quantity=item.quantity) order.submit() async with self.db.transaction() as conn: await self.orders.save(order, conn) await self.publisher.publish(conn, order.pop_events()) return PlaceOrderResponse(order_id=order.id, success=True) ``` --- ## Detecting and Breaking Dependency Cycles Common symptoms and their structural fixes: ``` Symptom: use_cases/create_order.py imports from adapters/email_sender.py Fix: Create domain/interfaces/notification_service.py (abstract port). use_cases imports the port. adapters implements it. DI container wires them together. Symptom: domain/entities/user.py imports from infrastructure/config.py Fix: Pass config values as constructor arguments or environment at the infrastructure boundary. Domain entities must not read config. Symptom: Two aggregates import each other Fix: Introduce a domain event. Aggregate A emits OrderPlaced. Aggregate B's use case subscribes and reacts. They never import each other. Symptom: Repository imports a use case to "do extra work" after saving Fix: Extract the extra work into a separate domain service or use case. Repositories persist state only; they do not orchestrate behaviour. ``` Visual dependency check — run this and look for any arrow pointing outward: ```bash # Install: pip install pydeps pydeps app --max-bacon=4 --cluster --rankdir=BT # Expected: domain has no outgoing edges to adapters or infrastructure ``` -
details.md 10.7 KB
# architecture-patterns — detailed patterns and worked examples ## Clean Architecture — Directory Structure ``` app/ ├── domain/ # Entities, value objects, interfaces │ ├── entities/ │ │ ├── user.py │ │ └── order.py │ ├── value_objects/ │ │ ├── email.py │ │ └── money.py │ └── interfaces/ # Abstract ports (no implementations) │ ├── user_repository.py │ └── payment_gateway.py ├── use_cases/ # Application business rules │ ├── create_user.py │ ├── process_order.py │ └── send_notification.py ├── adapters/ # Concrete implementations │ ├── repositories/ │ │ ├── postgres_user_repository.py │ │ └── redis_cache_repository.py │ ├── controllers/ │ │ └── user_controller.py │ └── gateways/ │ ├── stripe_payment_gateway.py │ └── sendgrid_email_gateway.py └── infrastructure/ # Framework wiring, config, DI container ├── database.py ├── config.py └── logging.py ``` **Dependency rule in one sentence:** every `import` statement in `domain/` and `use_cases/` must point only toward `domain/`; nothing in those layers may import from `adapters/` or `infrastructure/`. ## Clean Architecture — Core Implementation ```python # domain/entities/user.py from dataclasses import dataclass from datetime import datetime @dataclass class User: """Core user entity — no framework dependencies.""" id: str email: str name: str created_at: datetime is_active: bool = True def deactivate(self): self.is_active = False def can_place_order(self) -> bool: return self.is_active # domain/interfaces/user_repository.py from abc import ABC, abstractmethod from typing import Optional from domain.entities.user import User class IUserRepository(ABC): """Port: defines contract, no implementation details.""" @abstractmethod async def find_by_id(self, user_id: str) -> Optional[User]: ... @abstractmethod async def find_by_email(self, email: str) -> Optional[User]: ... @abstractmethod async def save(self, user: User) -> User: ... @abstractmethod async def delete(self, user_id: str) -> bool: ... # use_cases/create_user.py from dataclasses import dataclass from datetime import datetime from typing import Optional import uuid from domain.entities.user import User from domain.interfaces.user_repository import IUserRepository @dataclass class CreateUserRequest: email: str name: str @dataclass class CreateUserResponse: user: Optional[User] success: bool error: Optional[str] = None class CreateUserUseCase: """Use case: orchestrates business logic, no HTTP or DB details.""" def __init__(self, user_repository: IUserRepository): self.user_repository = user_repository async def execute(self, request: CreateUserRequest) -> CreateUserResponse: existing = await self.user_repository.find_by_email(request.email) if existing: return CreateUserResponse(user=None, success=False, error="Email already exists") user = User( id=str(uuid.uuid4()), email=request.email, name=request.name, created_at=datetime.now(), ) saved_user = await self.user_repository.save(user) return CreateUserResponse(user=saved_user, success=True) # adapters/repositories/postgres_user_repository.py from domain.interfaces.user_repository import IUserRepository from domain.entities.user import User from typing import Optional import asyncpg class PostgresUserRepository(IUserRepository): """Adapter: PostgreSQL implementation of the user port.""" def __init__(self, pool: asyncpg.Pool): self.pool = pool async def find_by_id(self, user_id: str) -> Optional[User]: async with self.pool.acquire() as conn: row = await conn.fetchrow("SELECT * FROM users WHERE id = $1", user_id) return self._to_entity(row) if row else None async def find_by_email(self, email: str) -> Optional[User]: async with self.pool.acquire() as conn: row = await conn.fetchrow("SELECT * FROM users WHERE email = $1", email) return self._to_entity(row) if row else None async def save(self, user: User) -> User: async with self.pool.acquire() as conn: await conn.execute( """ INSERT INTO users (id, email, name, created_at, is_active) VALUES ($1, $2, $3, $4, $5) ON CONFLICT (id) DO UPDATE SET email = $2, name = $3, is_active = $5 """, user.id, user.email, user.name, user.created_at, user.is_active, ) return user async def delete(self, user_id: str) -> bool: async with self.pool.acquire() as conn: result = await conn.execute("DELETE FROM users WHERE id = $1", user_id) return result == "DELETE 1" def _to_entity(self, row) -> User: return User( id=row["id"], email=row["email"], name=row["name"], created_at=row["created_at"], is_active=row["is_active"], ) # adapters/controllers/user_controller.py from fastapi import APIRouter, Depends, HTTPException from pydantic import BaseModel from use_cases.create_user import CreateUserUseCase, CreateUserRequest router = APIRouter() class CreateUserDTO(BaseModel): email: str name: str @router.post("/users") async def create_user( dto: CreateUserDTO, use_case: CreateUserUseCase = Depends(get_create_user_use_case), ): """Controller handles HTTP only — no business logic lives here.""" response = await use_case.execute(CreateUserRequest(email=dto.email, name=dto.name)) if not response.success: raise HTTPException(status_code=400, detail=response.error) return {"user": response.user} ``` ## Hexagonal Architecture — Ports and Adapters ```python # Core domain service — no infrastructure dependencies class OrderService: def __init__( self, order_repository: OrderRepositoryPort, payment_gateway: PaymentGatewayPort, notification_service: NotificationPort, ): self.orders = order_repository self.payments = payment_gateway self.notifications = notification_service async def place_order(self, order: Order) -> OrderResult: if not order.is_valid(): return OrderResult(success=False, error="Invalid order") payment = await self.payments.charge(amount=order.total, customer=order.customer_id) if not payment.success: return OrderResult(success=False, error="Payment failed") order.mark_as_paid() saved_order = await self.orders.save(order) await self.notifications.send( to=order.customer_email, subject="Order confirmed", body=f"Order {order.id} confirmed", ) return OrderResult(success=True, order=saved_order) # Ports (driving and driven interfaces) class OrderRepositoryPort(ABC): @abstractmethod async def save(self, order: Order) -> Order: ... class PaymentGatewayPort(ABC): @abstractmethod async def charge(self, amount: Money, customer: str) -> PaymentResult: ... class NotificationPort(ABC): @abstractmethod async def send(self, to: str, subject: str, body: str): ... # Production adapter: Stripe class StripePaymentAdapter(PaymentGatewayPort): def __init__(self, api_key: str): import stripe stripe.api_key = api_key self._stripe = stripe async def charge(self, amount: Money, customer: str) -> PaymentResult: try: charge = self._stripe.Charge.create( amount=amount.cents, currency=amount.currency, customer=customer ) return PaymentResult(success=True, transaction_id=charge.id) except self._stripe.error.CardError as e: return PaymentResult(success=False, error=str(e)) # Test adapter: no external dependencies class MockPaymentAdapter(PaymentGatewayPort): async def charge(self, amount: Money, customer: str) -> PaymentResult: return PaymentResult(success=True, transaction_id="mock-txn-123") ``` ## DDD — Value Objects and Aggregates ```python # Value Objects: immutable, validated at construction from dataclasses import dataclass @dataclass(frozen=True) class Email: value: str def __post_init__(self): if "@" not in self.value or "." not in self.value.split("@")[-1]: raise ValueError(f"Invalid email: {self.value}") @dataclass(frozen=True) class Money: amount: int # cents currency: str def __post_init__(self): if self.amount < 0: raise ValueError("Money amount cannot be negative") if self.currency not in {"USD", "EUR", "GBP"}: raise ValueError(f"Unsupported currency: {self.currency}") def add(self, other: "Money") -> "Money": if self.currency != other.currency: raise ValueError("Currency mismatch") return Money(self.amount + other.amount, self.currency) # Aggregate root: enforces all invariants for its cluster of entities class Order: def __init__(self, id: str, customer_id: str): self.id = id self.customer_id = customer_id self.items: list[OrderItem] = [] self.status = OrderStatus.PENDING self._events: list[DomainEvent] = [] def add_item(self, product: Product, quantity: int): if self.status != OrderStatus.PENDING: raise ValueError("Cannot modify a submitted order") item = OrderItem(product=product, quantity=quantity) self.items.append(item) self._events.append(ItemAddedEvent(order_id=self.id, item=item)) @property def total(self) -> Money: totals = [item.subtotal() for item in self.items] return sum(totals[1:], totals[0]) if totals else Money(0, "USD") def submit(self): if not self.items: raise ValueError("Cannot submit an empty order") if self.status != OrderStatus.PENDING: raise ValueError("Order already submitted") self.status = OrderStatus.SUBMITTED self._events.append(OrderSubmittedEvent(order_id=self.id)) def pop_events(self) -> list[DomainEvent]: events, self._events = self._events, [] return events # Repository: persist and reconstitute aggregates class OrderRepository(ABC): @abstractmethod async def find_by_id(self, order_id: str) -> Optional[Order]: ... @abstractmethod async def save(self, order: Order) -> None: ... # Implementations persist events via pop_events() after writing state ```
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SKILL.md 7.8 KB
--- name: architecture-patterns description: Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use this skill when designing clean architecture for a new microservice, when refactoring a monolith to use bounded contexts, when implementing hexagonal or onion architecture patterns, or when debugging dependency cycles between application layers. --- # Architecture Patterns Master proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design to build maintainable, testable, and scalable systems. **Given:** a service boundary or module to architect. **Produces:** layered structure with clear dependency rules, interface definitions, and test boundaries. ## When to Use This Skill - Designing new backend services or microservices from scratch - Refactoring monolithic applications where business logic is entangled with ORM models or HTTP concerns - Establishing bounded contexts before splitting a system into services - Debugging dependency cycles where infrastructure code bleeds into the domain layer - Creating testable codebases where use-case tests do not require a running database - Implementing domain-driven design tactical patterns (aggregates, value objects, domain events) ## Core Concepts ### 1. Clean Architecture (Uncle Bob) **Layers (dependency flows inward):** - **Entities**: Core business models, no framework imports - **Use Cases**: Application business rules, orchestrate entities - **Interface Adapters**: Controllers, presenters, gateways — translate between use cases and external formats - **Frameworks & Drivers**: UI, database, external services — all at the outermost ring **Key Principles:** - Dependencies point inward only; inner layers know nothing about outer layers - Business logic is independent of frameworks, databases, and delivery mechanisms - Every layer boundary is crossed via an abstract interface - Testable without UI, database, or external services ### 2. Hexagonal Architecture (Ports and Adapters) **Components:** - **Domain Core**: Business logic lives here, framework-free - **Ports**: Abstract interfaces that define how the core interacts with the outside world (driving and driven) - **Adapters**: Concrete implementations of ports (PostgreSQL adapter, Stripe adapter, REST adapter) **Benefits:** - Swap implementations without touching the core (e.g., replace PostgreSQL with DynamoDB) - Use in-memory adapters in tests — no Docker required - Technology decisions deferred to the edges ### 3. Domain-Driven Design (DDD) **Strategic Patterns:** - **Bounded Contexts**: Isolate a coherent model for one subdomain; avoid sharing a single model across the whole system - **Context Mapping**: Define how contexts relate (Anti-Corruption Layer, Shared Kernel, Open Host Service) - **Ubiquitous Language**: Every term in code matches the term used by domain experts **Tactical Patterns:** - **Entities**: Objects with stable identity that change over time - **Value Objects**: Immutable objects identified by their attributes (Email, Money, Address) - **Aggregates**: Consistency boundaries; only the root is accessible from outside - **Repositories**: Persist and reconstitute aggregates; abstract over the storage mechanism - **Domain Events**: Capture things that happened inside the domain; used for cross-aggregate coordination ## Detailed patterns and worked examples Detailed pattern documentation lives in `references/details.md`. Read that file when the navigation tier above is insufficient. ## Testing — In-Memory Adapters The hallmark of correctly applied Clean Architecture is that every use case can be exercised in a plain unit test with no real database, no Docker, and no network: ```python # tests/unit/test_create_user.py import asyncio from typing import Dict, Optional from domain.entities.user import User from domain.interfaces.user_repository import IUserRepository from use_cases.create_user import CreateUserUseCase, CreateUserRequest class InMemoryUserRepository(IUserRepository): def __init__(self): self._store: Dict[str, User] = {} async def find_by_id(self, user_id: str) -> Optional[User]: return self._store.get(user_id) async def find_by_email(self, email: str) -> Optional[User]: return next((u for u in self._store.values() if u.email == email), None) async def save(self, user: User) -> User: self._store[user.id] = user return user async def delete(self, user_id: str) -> bool: return self._store.pop(user_id, None) is not None async def test_create_user_succeeds(): repo = InMemoryUserRepository() use_case = CreateUserUseCase(user_repository=repo) response = await use_case.execute(CreateUserRequest(email="alice@example.com", name="Alice")) assert response.success assert response.user.email == "alice@example.com" assert response.user.id is not None async def test_duplicate_email_rejected(): repo = InMemoryUserRepository() use_case = CreateUserUseCase(user_repository=repo) await use_case.execute(CreateUserRequest(email="alice@example.com", name="Alice")) response = await use_case.execute(CreateUserRequest(email="alice@example.com", name="Alice2")) assert not response.success assert "already exists" in response.error ``` ## Troubleshooting ### Use case tests require a running database Business logic has leaked into the infrastructure layer. Move all database calls behind an `IRepository` interface and inject an in-memory implementation in tests (see Testing section above). The use case constructor must accept the abstract port, not the concrete class. ### Circular imports between layers A common symptom is `ImportError: cannot import name X` between `use_cases` and `adapters`. This happens when a use case imports a concrete adapter class instead of the abstract port. Enforce the rule: `use_cases/` imports only from `domain/` (entities and interfaces). It must never import from `adapters/` or `infrastructure/`. ### Framework decorators appearing in domain entities If SQLAlchemy `Column()` or Pydantic `Field()` annotations appear on domain entities, the entity is no longer pure. Create a separate ORM model in `adapters/repositories/` and map to/from the domain entity in the repository's `_to_entity()` method. ### All logic ending up in controllers When the controller grows beyond HTTP parsing and response formatting, extract the logic into a use case class. A controller method should do three things only: parse the request, call a use case, map the response. ### Value objects raising errors too late Validate invariants in `__post_init__` (Python) or the constructor so an invalid `Email` or `Money` cannot be constructed at all. This surfaces bad data at the boundary, not deep inside business logic. ### Context bleed across bounded contexts If the `Order` context is importing `User` entities from the `Identity` context, introduce an Anti-Corruption Layer. The `Order` context should hold its own lightweight `CustomerId` value object and only call the `Identity` context through an explicit interface. ## Advanced Patterns For detailed DDD bounded context mapping, full multi-service project trees, Anti-Corruption Layer implementations, and Onion Architecture comparisons, see: - [`references/advanced-patterns.md`](references/advanced-patterns.md) ## Related Skills - `microservices-patterns` — Apply these architecture patterns when decomposing a monolith into services - `cqrs-implementation` — Use Clean Architecture as the structural foundation for CQRS command/query separation - `saga-orchestration` — Sagas require well-defined aggregate boundaries, which DDD tactical patterns provide - `event-store-design` — Domain events produced by aggregates feed directly into an event store
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