Skip to main content

Project Architecture

This file outlines architectural principles and patterns for building scalable, maintainable software systems.

Architectural Principles​

Separation of Concerns​

  • Each component has a single, well-defined responsibility
  • Business logic separated from presentation logic
  • Data access isolated from business rules

Single Responsibility Principle​

  • Classes and modules should have one reason to change
  • Functions should do one thing well
  • Clear boundaries between components

Dependency Inversion​

  • High-level modules should not depend on low-level modules
  • Both should depend on abstractions
  • Use dependency injection for loose coupling

Layered Architecture​

Presentation Layer​

  • User interface components
  • Input validation
  • Request/response handling
  • No business logic

Business Logic Layer​

  • Domain models and entities
  • Business rules and validation
  • Use cases and workflows
  • Independent of infrastructure

Data Access Layer​

  • Repository patterns
  • Database connections
  • External API integrations
  • Data transformation
┌─────────────────────────┐
│   Presentation Layer    │
├─────────────────────────┤
│  Business Logic Layer   │
├─────────────────────────┤
│   Data Access Layer     │
└─────────────────────────┘

Design Patterns​

Repository Pattern​

class UserRepository:
    def get_by_id(self, user_id: int) -> User:
        pass

    def save(self, user: User) -> None:
        pass

    def delete(self, user_id: int) -> None:
        pass

class DatabaseUserRepository(UserRepository):
    def get_by_id(self, user_id: int) -> User:
        # Database implementation
        pass

Factory Pattern​

class DatabaseConnectionFactory:
    @staticmethod
    def create_connection(db_type: str):
        if db_type == "postgresql":
            return PostgreSQLConnection()
        elif db_type == "mysql":
            return MySQLConnection()
        else:
            raise ValueError(f"Unsupported database type: {db_type}")

Observer Pattern​

class EventManager:
    def __init__(self):
        self._observers = []

    def subscribe(self, observer):
        self._observers.append(observer)

    def notify(self, event):
        for observer in self._observers:
            observer.handle(event)

Microservices Architecture​

Service Boundaries​

  • Business capability alignment
  • Data ownership
  • Independent deployment
  • Team autonomy

Communication Patterns​

  • Synchronous: REST APIs, GraphQL
  • Asynchronous: Message queues, events
  • Service mesh for complex interactions

Data Management​

  • Database per service
  • Event sourcing for data consistency
  • CQRS for read/write separation

API Design​

RESTful Principles​

GET    /users          # List users
GET    /users/{id}     # Get specific user
POST   /users          # Create user
PUT    /users/{id}     # Update user
DELETE /users/{id}     # Delete user

GraphQL Design​

type Query {
  user(id: ID!): User
  users(limit: Int, offset: Int): [User]
}

type Mutation {
  createUser(input: CreateUserInput!): User
  updateUser(id: ID!, input: UpdateUserInput!): User
}

Security Architecture​

Authentication​

  • JSON Web Tokens (JWT)
  • OAuth 2.0 / OpenID Connect
  • Multi-factor authentication

Authorization​

  • Role-based access control (RBAC)
  • Attribute-based access control (ABAC)
  • Policy enforcement points

Data Protection​

  • Encryption at rest and in transit
  • Secure key management
  • Data anonymization/pseudonymization

Scalability Patterns​

Horizontal Scaling​

  • Load balancers
  • Stateless services
  • Database sharding

Caching Strategies​

  • In-memory caching (Redis)
  • CDN for static content
  • Application-level caching

Performance Optimization​

  • Lazy loading
  • Connection pooling
  • Asynchronous processing