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Coronavirus - (COVID-19) Full Stack Application

The idea behind this application is to displays the statistics of Coronavirus COVID-19 around the world and the data are being collected from Johns Hopkins University Center for Systems Science and Engineering JHU CSSE and it updates the cases constantly on this website around the world.

Technical Overview

This is a full-stack application which runs react.js in front-end and node.js in the back-end and it parses the data from JHU CSSE and stored in MongoDB database.

And it uses Mapbox to populate the coordinates on the map using GeoJSON format.

MongoDB sample database import command

After git clone import the dummy statistics into your local MongoDB database, which will help you to start the project.

git clone https://github.com/anshumanpattnaik/covid19-full-stack-application.git

cd covid19-full-stack-application

mongod (Start MongoDB database)

mongoimport --uri "mongodb://127.0.0.1:27017/covid-19" --collection covid_statistics --file dummy_statistics.json

Server Installation

cd server 
npm install
npm start

Open http://localhost:9000 to view it in the browser.

Client Installation

cd client 
npm install
npm start

Open http://localhost:3000 to view it in the browser.

Change the constants values in Client app

export const BASE_URL = `http://YOUR_LOCAL_IP_ADDRESS:9000`;
export const MAPBOX_ACCESS_TOKEN = `YOUR_MAPBOX_API_TOKEN`;

MAPBOX Styles

These two below styles i have made public and it should work when you use your own MAPBOX_API_TOKEN

mapbox://styles/hackbotone/ck8vtayrp0x5f1io3sakcmpnv
mapbox://styles/hackbotone/ck8vt8vdj2fz91ilax6nwtins

Note

If you face any problem or have any suggestion on improving the code then feel free to raise an issue.

Youtube explanation

https://www.youtube.com/watch?v=dth5jfLDuus

Website Design & Developed by

[Rushi Patel] (https://www.linkedin.com/in/rushi-patel-193079266/)

License

This project is licensed under the MIT License

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Coronavirus - (COVID-19) Full Stack Application

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  • JavaScript 67.2%
  • CSS 30.1%
  • HTML 2.7%