"Peninsula Restaurant" project aims to provide a simple API solution for restaurant owners to streamline the process of managing restaurant tables, operating hours and reservations.
The project is built with KoaJS, JEST, MongoDB (with Mongoose), Docker (with docker-compose).
Clone the project
git clone https://github.com/ozgurhalilince/peninsulaRestaurant
Create your .env file
cd peninsulaRestaurant && cp -r .env.example .env
Up
docker-compose up
Seed the database
docker exec -it api npm run db:seed
After seeding you will have
- a dummy user with email "[email protected]" and password "example"
- dummy daily working hours for a week
- dummy tables for the restaurant
Running tests
docker exec -it test npm test
The architecture of the "Peninsula Restaurant" API project has been carefully designed, incorporating a set of technologies that align with the project's requirements and objectives. The selected technologies offer a range of benefits that contribute to the project's efficiency, scalability, maintainability and the ability to handle evolving requirements.
KoaJS was chosen as the web framework for building the API due to its lightweight nature and asynchronous middleware architecture. This allows for better control over the request-response flow, making it ideal for building APIs with high concurrency and performance demands. Koa's use of async/await simplifies asynchronous code handling, promoting cleaner and more readable code.
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Mongoose provides a straight-forward, schema-based solution to model your application data. It includes built-in type casting, validation, query building, business logic hooks and more, out of the box.
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Docker is a platform designed to help developers build, share, and run container applications. It handles the tedious setup.
Multi-stage builds are useful to anyone who has struggled to optimize Dockerfiles while keeping them easy to read and maintain.
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MongoDB, a NoSQL database, was chosen for its flexibility and scalability. In a dynamic environment like a restaurant, where requirements might evolve, MongoDB's schema-less structure allows for easy adaptation without requiring extensive schema changes.
Benefits:
- Flexible Schema: MongoDB's schema-less nature accommodates changes in data structure without requiring database migrations, making it well-suited for evolving requirements.
- Scalability: MongoDB's horizontal scaling capabilities support the potential growth of the restaurant's data, ensuring the system can handle increased demand.
- Document-Oriented: Storing data in documents enhances data locality and reduces the need for complex joins, which can lead to improved query performance.
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