A modern TypeScript project demonstrating best practices for testing AWS serverless applications using Jest, Faker, and mock data generation.
This project showcases a robust testing framework for AWS-based microservices, with a focus on:
- TypeScript - Strongly-typed interfaces and model definitions
- Jest - Comprehensive test suites with mocking capabilities
- AWS SDK Integration - DynamoDB, KMS, and serverless patterns
- Data Generation - Dynamic test data using Faker.js
- DevOps Automation - CI/CD configuration with quality gates
The codebase demonstrates how to effectively test complex business logic for shipping/logistics applications that integrate with third-party APIs.
- Strong typing with interfaces and type definitions
- Module organization and clean separation of concerns
- ES6+ features and functional programming patterns
- Jest configuration for TypeScript projects
- Test coverage reporting and badges
- Mock data generation with Faker.js
- DynamoDB local integration for database testing
- AWS SDK for JavaScript/TypeScript
- DynamoDB document client patterns
- KMS client implementation
- Serverless framework configuration
- ESLint and Prettier configuration
- Husky pre-commit hooks
- Conventional commits enforcement
- CI/CD integration
/
├── jest-dynamodb-config.js # DynamoDB local configuration
├── jest.config.js # Jest configuration
├── src/
│ ├── CommonTypes.ts # Shared type definitions
│ ├── helpers/ # Utility functions with tests
│ ├── libs/ # AWS service clients
│ ├── mocks/ # Mock data generators
│ └── model/ # Interface definitions
- Clone the repository
git clone https://github.com/yourusername/jest-faker-example.git
cd jest-faker-example- Install dependencies
npm install- Run tests
npm test- Generate test coverage report
npm run test:coverage- Helper Functions - Utility functions for calculations, time handling, and data processing
- Mock Data Generation - Realistic test data creation with Faker.js
- AWS Service Mocking - Local DynamoDB testing and service client mocking
- Type Safety - Comprehensive type definitions for all data models
This project demonstrates:
- Test-driven development methodology
- Clean code principles
- Effective mocking strategies
- Separation of concerns
- Type-safe programming
ISC