Domain Layer Design - tonglam/letletme_data GitHub Wiki
Overview
The domain layer is the core of our application, implementing business logic using Domain-Driven Design (DDD) principles and Functional Programming (FP) patterns. This document outlines the high-level architecture and design decisions.
Architecture
graph TD
A[API Layer] --> B[Domain Layer]
B --> C[Infrastructure Layer]
B --> D[Repository Layer]
B --> E[Cache Layer]
D --> F[Database]
E --> G[Cache]
subgraph Domain Layer
H[Domain Operations]
I[Domain Types]
J[Domain Logic]
K[Domain Events]
H --> I
H --> J
J --> K
end
Domain Layer Structure
graph LR
A[Domain Operations] --> B[Cache Layer]
A --> C[Repository Layer]
A --> D[Infrastructure Layer]
B --> E[Cache Store]
C --> F[Database]
subgraph Domain Core
G[Domain Types]
H[Business Rules]
I[Value Objects]
J[Domain Events]
G --> H
H --> I
I --> J
end
Design Principles
1. Domain-Driven Design
- Bounded Contexts: Each domain is self-contained with clear boundaries
- Ubiquitous Language: Consistent terminology throughout the codebase
- Value Objects: Immutable domain objects with identity
- Domain Events: State changes represented as events
2. Functional Programming
- Pure Functions: No side effects in core business logic
- Immutability: All state changes create new objects
- Type Safety: Strong typing with branded types
- Error Handling: Explicit error handling with TaskEither
3. Layered Architecture
graph TD
A[API Layer] --> B[Domain Layer]
B --> C[Infrastructure Layer]
subgraph Domain Layer
D[Operations]
E[Repository]
F[Cache]
G[Types]
D --> E
D --> F
D --> G
end
Data Flow
sequenceDiagram
participant A as API Layer
participant O as Domain Operations
participant C as Cache Layer
participant R as Repository Layer
participant D as Database
A->>O: Request Data
O->>C: Check Cache
alt Cache Hit
C-->>O: Return Cached Data
else Cache Miss
O->>R: Fetch Data
R->>D: Query Database
D-->>R: Return Data
R-->>O: Transform Data
O->>C: Update Cache
end
O-->>A: Return Domain Model
Domain Organization
1. Core Components
- Domain Types: Core business models and types
- Domain Operations: Business logic implementation
- Repository Layer: Data access abstraction
- Cache Layer: Performance optimization
2. Cross-Cutting Concerns
- Error Handling: Consistent error types and handling
- Validation: Input validation and business rules
- Type Safety: Branded types and type guards
- Performance: Caching and optimization strategies
Implementation Strategy
1. Domain Isolation
- Self-contained domains with explicit interfaces
- Clear dependencies through repository pattern
- No cross-domain knowledge leakage
- Pure functional core with side effects at edges
2. Type Safety
- Branded types for domain identifiers
- Explicit validation at boundaries
- No implicit type coercion
- Comprehensive type definitions
3. Error Handling
- TaskEither for all operations
- Explicit error types and messages
- Consistent error creation patterns
- Error transformation at boundaries
Performance Considerations
1. Caching Strategy
graph TD
A[Request] --> B{Cache?}
B -- Yes --> C[Return Cached]
B -- No --> D[Fetch Data]
D --> E[Update Cache]
E --> F[Return Data]
2. Data Access Patterns
- Cache-first architecture
- Batch operations for bulk data
- Optimized database queries
- Connection pooling
Testing Strategy
1. Test Pyramid
graph TD
A[E2E Tests] --> B[Integration Tests]
B --> C[Unit Tests]
subgraph Test Coverage
D[Domain Logic]
E[Repository Layer]
F[Cache Layer]
D --> E
E --> F
end
2. Test Types
- Unit tests for pure functions
- Integration tests for repositories
- E2E tests for domain operations
- Property-based tests for validation
Maintenance and Evolution
1. Code Organization
- Consistent file structure
- Clear module boundaries
- Explicit dependencies
- Functional composition
2. Documentation
- API documentation
- Domain model documentation
- Implementation guides
- Architecture decision records
3. Monitoring
- Performance metrics
- Error tracking
- Cache hit rates
- Database performance