Categorygithub.com/thiagoluis88git/tech1
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0.0.0-20240926010618-b1d94d24917e
Repository: https://github.com/thiagoluis88git/tech1.git
Documentation: pkg.go.dev
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# README

FastFood API - Description

Table of Contents

Description

The Tech Challenge 1 aims to do a solution for a Fast Food restaurant. With this software, the rastaurant can do a all the process of for a place that makes all steps of a fast food dish order, as:

  • Products creation/manipulation by the restaurant owner
  • Customer identification
  • Order creation with given products
  • Payment process
  • Order tracking by the chef
  • Order tracking by the waiter and the customer

This projects only fits the Backend side, which means that customer needs to choose the products or combo by a interface previously. This Backend will only receive the entire order with all chosen products or combos. This Backend will not do a step by step product selecion.

All the Endpoints can be called by accessing http://localhost:3210/api API url.

To build and run this project. Follow the Docker section

Architecture

This project uses a mixin with two architectures to make it scalable and secure by protecting the domain layer. Those are DDD (Domain Driven Design) and Clean Archtecture

DDD

To design this application was chosen DDD (Domain Drive Design) architecture to follow the principle of protecting the model.

ddd_image

Clean Archtecture

The other one is Clean Archtecture. With it, we add some extra layers to organize even more the project.

CleanArchitecture

The folder project was created to follow this main principle:

  • data: Here we have all the implementations, such as Repositories, Remotes and Locals

  • domain: All the application business logic, such as UseCases

  • handler: Also known as presentation layer resides all the Controllers handled by the Web interface given by the /cmd/api Framework & Driver

  • integrations: This is not part of DDD or Clean Arch, but is important separate some external packages or integrations, such Mercado Livre API

Design Patterns

To improve and make a good standard project pattern, some Design Patterns were used in this application.

  • Strategy: All the business logic must be protected by the external implementations. To do it, we use a combo with Interfaces and Dependency Inversion solid principle to inject only interfaces and not real implementations
  • Dependency Injection: Is used in application bootstrap (main.go) to inject all the interfaces implementations.
  • Decorator: To inject Services inside Driver Adapter handler. By doing this, we decorate the Handler with a Service
  • Services or Use Cases: Centralize all the business logic of of the application
  • Repository: Used to integrate with all Driven Adapter like Databases and External Endpoints

Unit Testing

To run all the Unit Testing for this project, just run:

go test ./...

This will run all the Services unit tests and Repository unit Database tests running Testcontainers database container mocks.

Docker build and run

This project was built using Docker and Docker Compose. So, to build and run the API, we need to run in the root of the project:

docker compose build

After the image build finish, run:

docker compose up -d

The command above may take a while.

After all the containers shows these below status:

 ✔ Container fastfood-database  Started
 ✔ Container fastfood-app       Started

we can access http://localhost:3210/api endpoints.

How to use

To use all the endpoints in this API, we can follow these sequence to simulate a customer making an order in a restaurant. We can separate in three moments.

  • Restaurant products manipulation. This is used by the restaurant owner to create all the product portfolio with its images and prices
  • Customer self service. This is used by the customer to choose the products, pay for it and create an order
  • Order preparing and deliver. This is used by the chef and waiter to check the order status

We will divide in 2 sections: Restaurant owner and Customer order

Check app status

After running Docker commands, you can check the application status running:

docker compose logs app

We can see some database errors but at the end of the logs we can see:

fastfood-app  | 2024/05/27 22:57:35 API Tech 1 has started

AWS

The Fast food project uses AWS Cloud to host its software components. To know more about the AWS configuration, read: AWS Readme

Kubernetes

This application has all the K8S YAMLs to be applied in any cluster. To read the specific documentation, read: Kubernetes README

Section 1 Restaurant owner

This section will be used by the restaurant owner to manage the restaurant products

1 Product manipulation

(Owner view)

  • Cal the POST http://localhost:3210/api/products to create a Product
  • Cal the PUT http://localhost:3210/api/products/{id} to update a Product
  • Cal the GET http://localhost:3210/api/products/{id} to get a Product
  • Cal the GET http://localhost:3210/api/products/categories to list all Product Categories
  • Cal the GET http://localhost:3210/api/products/categories/{category} to list all Products by a category
  • Cal the DELETE http://localhost:3210/api/products/{id} to delete a Product

With those endpoints we can follow to Section 2 to start the Order flow

Section 2 Customer order

This section will use all the Endpoints to make a entire order flow.

1 User identification

(Customer view)

[!IMPORTANT] These endpoints have a CPF validation. So be aware that it is needed to pass a correct CPF number.

[!NOTE]
The CPF does not need to be formatted.

  • Cal the POST http://localhost:3210/api/customers to create a Customer and retrieve the [Customer ID]

  • Call the POST http://localhost:3210/api/customers/login to login and get the Customer

  • Call the GET http://localhost:3210/api/customers/{id} to get the Customer by this [Customer ID]

  • Call the PUT http://localhost:3210/api/customers/{id} to update Customer

We can use this site CPF generator to easly generate a new CPF whenever we need.

2 List all the categories

(Customer view)

  • Call the GET http://localhost:3210/api/products/categories to get a string array with all created categories

3 List products by the chosen category

(Customer view)

  • Call the GET http://localhost:3210/api/products/categories/{category} to get all products by a category

With this endpoints we can simulate a screen producst selection by chosing all products IDs we want to deal and create a Order

4 Pay the products amount

(Customer view)

  • Call the GET http://localhost:3210/api/payments/types to show to customer which payment type to choose
  • Call the POST http://localhost:3210/api/payments to pay for the amount and receive the [Payment ID]

4_1 Generate Mercado Livre QR Code

(Customer view)

  • Call the POST http://localhost:3210/api/qrcode/generate to get the QR Code Data to transform in Image to pay with Mercado Pago App. Must send the same post body as 5 create an order needs.

[!WARNING] Sometimes the Mercado Livre server returns 500 Internal Server Error for unknown reason. The error returned by the server is: {"error":"alias_obtainment_error","message":"Get aliases for user failed","status":500,"causes":[]}. When this occurs, IS NOT possible to proceed with QR Code Payment. The main reason for this is on Weekend the Mercado Livre development environment does not work

When the server returns as expected, the response is like:

{
    "data": "00020101021243650016COM.MERCADOLIBRE020130636b624f3f3-d289-453b-a620-a32198e16a235204000053039865802BR5909Test Test6009SAO PAULO62070503***63046773"
}

[!NOTE] This method will CREATE AN ORDER with the status WAITING PAYMENT.

5 Create an order

(Customer view)

  • Call the POST http://localhost:3210/api/orders with:
    • All the [Products IDs] chosen [*required]
    • The [Payment ID] [required]
    • The [Customer ID] [optional]
    • Total price for the all products sum

6 List orders to follow

(Customer and Waiter)

  • Call the GET http://localhost:3210/api/orders/follow to show a list of Orders to be followed by Customer and Waiter. This will list only, CREATED, PREPARING and DONE. This Endpoint will sort the orders wit these business rule:
    • DONE
    • PREPARING
    • CREATED

Here is some response example:

[
    {
        "orderId": 2,
        "orderDate": "2024-07-16T21:41:31.229299-03:00",
        "preparingAt": "2024-07-16T21:53:25.156494-03:00",
        "doneAt": "2024-07-16T22:05:01.067784-03:00",
        "deliveredAt": null,
        "notDeliveredAt": null,
        "ticketNumber": 2,
        "customerName": null,
        "orderStatus": "Finalizado",
        "orderProducts": [
            {
                "id": 9,
                "name": "Combo pequeno",
                "description": "Hamburguer, batata e bebida"
            }
        ]
    },
    {
        "orderId": 3,
        "orderDate": "2024-07-16T21:47:20.122753-03:00",
        "preparingAt": "2024-07-16T22:04:08.225152-03:00",
        "doneAt": null,
        "deliveredAt": null,
        "notDeliveredAt": null,
        "ticketNumber": 3,
        "customerName": null,
        "orderStatus": "Preparando",
        "orderProducts": [
            {
                "id": 6,
                "name": "Hamburguer 1",
                "description": "Hamburguer com 1 carne de 100g e queijo"
            },
            {
                "id": 5,
                "name": "Batata frita 400g + cheddar",
                "description": "Batata frita 400g no prato com cheddar"
            }
        ]
    },
    {
        "orderId": 4,
        "orderDate": "2024-07-16T21:52:31.813815-03:00",
        "preparingAt": null,
        "doneAt": null,
        "deliveredAt": null,
        "notDeliveredAt": null,
        "ticketNumber": 4,
        "customerName": null,
        "orderStatus": "Criado",
        "orderProducts": [
            {
                "id": 4,
                "name": "Batata frita 200g",
                "description": "Batata frita 200g no cone"
            }
        ]
    },
    {
        "orderId": 1,
        "orderDate": "2024-07-16T21:40:11.480459-03:00",
        "preparingAt": null,
        "doneAt": null,
        "deliveredAt": null,
        "notDeliveredAt": null,
        "ticketNumber": 1,
        "customerName": null,
        "orderStatus": "Criado",
        "orderProducts": [
            {
                "id": 9,
                "name": "Combo pequeno",
                "description": "Hamburguer, batata e bebida"
            }
        ]
    }
]

The order can also be followed by its ID:

  • Call the GET http://localhost:3210/api/orders/{id} to show a an Orders to be followed by Customer and Waiter

7 List orders to prepare

(Chef view)

  • Call the GET http://localhost:3210/api/orders/to-prepare to list the Orders with its [Order ID]. This endpoint will be used by the Chef. This will list only CREATED

8 List orders waiting payment

(Owner view)

  • Call the GET http://localhost:3210/api/orders/waiting-payment to list the Orders with its [Order ID]. This endpoint will be used by the Owner. This will list only PAYING.

This Endpoint can be used to see if the Mercado Livre QR Code payment was paid successfully

9 Update order to preparing

(Chef view)

  • Call the PUT http://localhost:3210/api/orders/{id}/preparing to set Preparing status

10 Update order to done

(Chef view)

  • Call the PUT http://localhost:3210/api/orders/{id}/done to set Done status

11 Update order to delivered

(Waiter view)

  • Call the PUT http://localhost:3210/api/orders/{id}/delivered to set Delivered status to indicate that customer receive the meal. This is used to 'finish' the order and can be used to track some convertion rate

12 Update order to not delivered

(Waiter view)

  • Call the PUT http://localhost:3210/api/orders/{id}/not-delivered to set Not Delivered status to indicate that customer does not receive the meal. This is used to 'finish' the order and can be used to track some convertion rate

Mercado Livre Webhook

The Fast Food application can pay the order via QR Code. This is a separate flow and can be read in: Webhook Payment

Documentation

This project uses Swagger to show an site with all Endpoints used by this project to make an order in a Fast Food place. To create/update all Endpoints documentation just run swag init -g cmd/api/main.go. By doing this, we can see the documentation in two different ways:

Event Storming

This project was guided by the DDD Event Storming. This document was made in Miro. The file event_storming.pdf is in the root of this project. We can algo see the Miro project by accessing the link:Event Storming

Postman collection

In the root of this project we can find the file postman_collection.json. With this we can easly test all the Endpoints. It also be in this repo all the postman environments to use in localhost and with EKS LoadBalancer DNS. Just import also these:

  • eks_postman_environment.json
  • localhost_postman_environment.json
  • minikube_postman_environment.json

Swagger

http://localhost:3210/swagger/index.html

Redoc

http://localhost:3211/docs

Opportunities

Even though this project was made by following some Design Patterns like Use Case and Repository it does not separate the Data Source from the Repository. In the future it will be good to use Data Source Pattern to separate Local and Remote from the Repository to make a better separation of concern principle.

It will also a good opportunity to increase the Unit Test coverage.

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