The Project

This project was developed to the university subject of Tecnologia e Programação para Web e para Dispositivos Móveis where we learn back and frontend applications development.

MedTech

MedTech is an idea of a smart medical clinic appointment management system where medics and patients can use it to organize and communicate between themselves and also use it as a calendar center for they medical appointments.

Table of Contents

• The Project
• MedTech
• Table of Contents
• Features
• Setup
  • Pre-requisites
  • Instructions
• Docker
• Technologies
• Environment

Features

• Create, read, update and soft delete users (admin, patient and medic)
• Create, read, update and soft delete appointments
• AWS S3 Bucket Integrations to user profile photos
• Mailing ready system (only Gmail) with Google OAuth2
• Docker Compose ready project (see Docker section)
• MVC based project

Setup

Pre-requisites

• Node 12.19.0 LTS -> To run the application
• Yarn -> If you want to use the package.json scripts
• PostgreSQL -> If you will not use Docker
• Google Developer account -> In order to use the mailing system
• AWS S3 Bucket -> If you want to use the AWS S3 Bucket Integration
• Windows WSL -> If at Windows, necessary to run some package.json scripts that uses Linux terminal commands

Instructions

Done with the pre-requisites, the next step is to follow these instructions:

1. Clone the repository
2. Open the terminal at the project root folder and type "yarn" to install all dependencies
3. Create a file named as ".env-development" at the root of the project. We will start using a development environment
4. Use the following code in the created file:

PORT=YOUR_PREFERRED_PORT_NUMBER
HOST=YOUR_HOST #(default: 0.0.0.0)

NODE_ENV=development

DATABASE_PORT=YOUR_POSTGRES_DATABASE_PORT #(default: 5432)
DATABASE_HOST=YOUR_POSTGRES_DATABASE_HOST
DATABASE_NAME=YOUR_POSTGRES_DATABASE_NAME
DATABASE_USER=YOUR_POSTGRES_USER
DATABASE_PASSWORD=YOUR_POSTGRES_DATABASE_PASSWORD

SYSTEM_PASSWORD=YOUR_PREFERRED_ADMIN_PASSWORD

AUTH_JWT_SECRET=YOUR_PREFERRED_JWT_SECRET
AUTH_ACCESS_TOKEN_LIFETIME=YOUR_PREFERRED_TOKEN_LIFETIME #(example: 12h)
AUTH_REFRESH_TOKEN_LIFETIME=YOUR_PREFERRED_TOKEN_LIFETIME #(example: 14d)

MAILING_EMAIL=YOUR_GOOGLE_MAILING_EMAIL
MAILING_ALIAS=YOUR_PREFERRED_MAILING_ALIAS

GOOGLE_CLIENT_ID=YOUR_GOOGLE_CLIENT_ID
GOOGLE_CLIENT_SECRET=YOUR_GOOGLE_CLIENT_SECRET
GOOGLE_REFRESH_TOKEN=YOUR_GOOGLE_REFRESH_TOKEN

AWS_ACCESS_KEY=YOUR_AWS_ACCESS_KEY
AWS_SECRET_ACCESS_KEY=YOUR_AWS_SECRET_ACCESS_KEY
AWS_REGION=YOUR_AWS_REGION
AWS_BUCKET_NAME=YOUR_AWS_BUCKET

For every environment variable you need to substitute with your own configured data.

5. With setup done, you just need to test running yarn env:dev and yarn start at the terminal
6. If everything's OK, you should see a result like the image below:

7. You could test the server status through your_domain/api/status, which returns a JSON with basic information and the terminal should show a log like GET /api/status 200 1.152 ms.
8. Have fun! :)

To change the environment, just create a file named .env-production and use the corresponding scripts. You are also able to use Docker on the entire process, go to the section below.

Docker

This project is Docker Compose compatible, and I've used the following configuration in order to set-up the project with Docker:

Dockerfile

FROM node:12-alpine

ENV HOME=/home/app/medtech
WORKDIR ${HOME}

COPY package*.json ./

RUN yarn

COPY . .

RUN chmod +x docker-entrypoint.sh
ENTRYPOINT [ "./docker-entrypoint.sh" ]

docker-compose.yml

version: "3.8"

x-common_env: &common_env
  PORT: ${PORT}
  HOST: ${HOST}
  NODE_ENV: ${NODE_ENV}
  SYSTEM_PASSWORD: ${SYSTEM_PASSWORD}
  DATABASE_PORT: ${DATABASE_PORT}
  DATABASE_HOST: ${DATABASE_HOST}
  DATABASE_NAME: ${DATABASE_NAME}
  DATABASE_USER: ${DATABASE_USER}
  DATABASE_PASSWORD: ${DATABASE_PASSWORD}
  AUTH_JWT_SECRET: ${AUTH_JWT_SECRET}
  AUTH_ACCESS_TOKEN_LIFETIME: ${AUTH_ACCESS_TOKEN_LIFETIME}
  AUTH_REFRESH_TOKEN_LIFETIME: ${AUTH_REFRESH_TOKEN_LIFETIME}

services:
  api:
    build:
      context: .
      dockerfile: Dockerfile
    ports:
      - ${PORT}:${PORT}
    environment:
      <<: *common_env
    depends_on:
      - database
    links:
      - database:database
    volumes:
      - type: bind
        source: ./
        target: /home/app/medtech
    deploy:
      resources:
        limits:
          memory: 384M
        reservations:
          memory: 128M
  database:
    image: postgres:alpine
    ports:
      - "5432:5432"
    environment:
      POSTGRES_USER: ${DATABASE_USER}
      POSTGRES_DB: ${DATABASE_NAME}
      POSTGRES_PASSWORD: ${DATABASE_PASSWORD}
    volumes:
      - medtech-data:/var/lib/postgresql/data
    deploy:
      resources:
        limits:
          memory: 256M
        reservations:
          memory: 64M

volumes:
  medtech-data:
    name: "medtech"

At package.json we also have the properly scripts in order to build and run with Docker. With a configured environment (see setup section to more details) we can run as dev through the following scripts:

1. yarn build:dev
2. yarn docker:dev

Technologies

• ⭐ Node.js
• ⭐ Express
• ⭐ Sequelize ORM
• ⭐ PostgreSQL
• ⭐ Docker
• ⭐ AWS S3
• ⭐ Nodemailer
• ⭐ Babel
• ⭐ JSON Web Token
• ⭐ MJML

Environment

• 🖥️ Visual Studio Code for coding
• 🖥️ JetBrains DataGrip for database management
• 🖥️ Postman for API testing
• 🖥️ Git for code versioning
• 🖥️ Notion for annotating
• 🖥️ Spotify music for focusing
• 🪲 Stack Overflow for debugging