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Test AWS Worker CloudFlare Pages Weather

Climatempo

Video

Skills

  • HTML5/CSS3/Javascript
  • React.js/Typescript/ES-6/JSX
  • Node.js/Typescript/REST API
  • Docker
  • Responsiveness
  • Dynamic auto complete search
  • 1 card for each daily weather provision
  • FE/BE User input validation
  • Cache (to save customization)
  • Use of Elasticsearch as db
  • Jest unit tests
  • Good code/design practices
  • Accessibility ready page
  • Real updated data usage
  • Improved search performance with client filtering
  • Make my bed

How to run using Docker

Go to the challenge root source and run:

docker-compose up

or, if you have npm available

npm run docker
Endpoints:

How to run locally

Requirements
  • Elastic search ^8 running without TLS
  • Node.js ^19 installed
  • npm ^8 installed

Set the following environment variables

  • ELASTIC_HOST=[elastic address with port]
  • ELASTIC_USER=[elastic user]
  • ELASTIC_PASSWORD=[elastic password]

You can create a .env file on the /server folder to declare these variables in.

Go to challenge root and type:

npm install
npm start
Endpoints:

How to run tests

Go to challenge root and type:

npm install
npm run test

To test just server, use:

npm run test:server

To test just web, use:

npm run test:web

Approach

Server

First I started understanding the dummy data offered on the repo. As the data was too outdated I started searching if the data was available publicly, I find out the Clima Tempo Advisor API, which only let limited search of one city per token per 24hs.

I saw the Clima Tempo site offers weather of any city on the base for free, so I decided to implement web scrapping to dynamically collect weather data. That is what ClimaTempo.engine does.

So the used dummy data is updated with real data of the period from 26/11/2022 to 10/12/2022 of the following cities:

  • Osasco, SP (Brasil) *
  • São Paulo, SP (Brasil) *
  • Juiz de Fora, MG (Brasil) **
  • Chácara, MG (Brasil) **
  • Fortaleza, CE (Brasil)
  • Gramado, RS (Brasil)
  • Porto de Galinhas, PE (Brasil)
  • Rio de Janeiro, RJ (Brasil)
  • Curitiba, PR (Brasil)
  • Arraial do Cabo, RJ (Brasil)
  • Natal, RN (Brasil)
  • Campos do Jordão, SP (Brasil)
  • Belo Horizonte, MG (Brasil)
  • Angra dos Reis, RJ (Brasil)
* Required city on the challenge
** Cities that I'm on

When the server is started first time the dummy data is indexed on elastic to be ready available to the user search.

The server will automatically fall back any request to the ClimaTempo engine and index the response making elastic act like a cache. If elastic has the data already, it will be quickly sent to the client and posteriorly fall back to the ClimaTempo engine to update elastic data.

The available endpoint are:
GET /search/[string] # to search cities by name
GET /ping # To ping-pong the server
GET /city/[id] # To get city's basic info
GET /city/[id]/now # To get current weather
GET /city/[code]/weather # To get the current day weather
GET /city/[code]/weathers # To get the current and next 14 days weather

Frontend

The frontend is using MUI design kit and Tailwindcss for style, it's designed responsively for desktop, tablet and mobile. On the header you can:

  • Search the city with dynamic auto complete options
  • Switch between dark and light mode (it first will follow system default, and cache option if you manually change it)
  • Switch between °C and °F units (default is °C, it caches if you manually change it)
  • Switch between mm and inch units (default is mm, it caches if you manually change it)

The web scraping data format:

City basic info
id: number # The city's id
name: string # The city's name
uf: string # The city's state
city: number # The city's code
region: string # The city's region
acronym: string # The city's country acronym
City detailed info
idlocale: number # The city's id
idcity: number # The city's code
capital: boolean # If city is a capital
idcountry: number # The country's id
ac: string # The country's acronym
country: string # The country's name
uf: string # The city's state
city: string # The city's name
region: string # The city's region
seaside: boolean # If it's a coast city
latitude: number # The city's latitude
longitude: number # The city's longitude
tourist: boolean # If it's a tourism city
agricultural: boolean # If it's a agricultural city
base: string # Looks like city's collection name
searchPoints: number # How likely its desired
Instant WeatherController info
idlocale: number # The city's id
temperature: number # The current temperature
icon: string # The alias for weather icons
condition: string # A description of the current weather
humidity: number # The current humidity level
sensation: number # The current temperature sensation
windVelocity: number # The current wind velocity
pressure: number # The current atmospheric pressure
date: string # The date and time of this weather info
Daily WeatherController info
idcity: number # The city's code
moon: string[] # The day's list of moons
rainbow: string # The description of probability of a rainbow
description: string # The day's WeatherController resume
date: string # The day's date
temperature:
  min: number # The day's minimum temperature
  max: number # The day's maximum temperature
rain:
  precipitation: number # The day's rain preciptation
  probability: number # The day's raining probabilily
wind:
  compass: string # The wind direction in cartesian
  velocity: number # The wind average velocity
humidity:
  min: number # The minimum humidity of the day
  max: number # The maximum humidity of the day
sun:
  morning: string # The sunshine hour
  afternoon: string # The sunrise hour