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https://github.com/daraperini/learning-react-typescript-alfood
Refactoring the original code I created a dinamic restaurants website with an admin area where you can manipulate the website's content through the back-end API
https://github.com/daraperini/learning-react-typescript-alfood
api-rest axios docker mui react typescript
Last synced: 14 days ago
JSON representation
Refactoring the original code I created a dinamic restaurants website with an admin area where you can manipulate the website's content through the back-end API
- Host: GitHub
- URL: https://github.com/daraperini/learning-react-typescript-alfood
- Owner: daraperini
- Created: 2024-01-16T18:56:29.000Z (12 months ago)
- Default Branch: main
- Last Pushed: 2024-01-24T15:23:49.000Z (12 months ago)
- Last Synced: 2024-11-07T10:12:59.618Z (2 months ago)
- Topics: api-rest, axios, docker, mui, react, typescript
- Language: TypeScript
- Homepage: https://learning-react-typescript-alfood.vercel.app/
- Size: 7.22 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Alfood
Alfood is an Ifood-based website developed during Alura's course *React: integrating your React project with APIs*. I used Docker to upload the back-end server and refactored the inicial static code turning it dinamic using API REST. I also created an admin area connected to the website's back-end in wich users can create new restaurants and meals, edit and delete them.
In the class I received the back-end API to work with and used Docker to run it. As the focus of the course was to work with API REST, some components were build using MUI.
> Access the admin area typing: http://localhost:3000/admin
## Used tools:
* React
* TypeScript
* Docker
* Axios
* API REST
* MUI*(Alura is a Brazilian technology school and for acessibility reasons this code is in Portuguese)*
## Initializing the project on your computer
- Install [Docker](https://www.docker.com/products/docker-desktop/) in your computer;
- Clone the repository using the command line:
- git clone *link of the repository*- Clone the API using the command line:
- git clone *[API](https://github.com/alura-cursos/restaurantes_api)*
- cd *API file*- Run the API:
- docker-compose build
- docker-compose up- Open the API on the browser:
- type http://localhost:8000 on your browser
- Go to the projects main file:
- cd *name of the file*
- Run the code:
- npm install (to install all project's dependencies)
- npm start (to open the project on your browser)
* In case the project does not opend automatically type http://localhost:3000 on your browser#
# Alfood
Alfood é um website baseado no Ifood, desenvolvido no curso *React: integrando seu projeto React com APIs*, da Alura. Nele utilizarei o Docker para subir o servidor beck-end e, com o auxílio do API REST, refatorei o código inicial estático e o tornei dinâmico. Além disso criei uma área administrativa conectada com o servidor back-end do site, em que os usuários podem adicionar, editar e deletar restaurantes e pratos.
A API back-end foi disponibilizada no curso e foi rodada utilizando o Docker. Como o foco do curso era o uso de API REST, alguns componentes foram criados utilizando MUI.
> Acesse a área administrativa digitando: http://localhost:3000/admin
## Ferramentas utilizadas:
* React
* TypeScript
* Docker
* Axios
* API REST
* MUI## Iniciando as versões do projeto na sua máquina
- Instale o [Docker](https://www.docker.com/products/docker-desktop/) na sua máquina;
- Clone o repositório através do terminal:
- git clone *link do repositório*
- Clone a API através do terminal:
- git clone *[API](https://github.com/alura-cursos/restaurantes_api)*
- cd *pasta da API*
- Rode a API com os comandos:
- docker-compose build
- docker-compose up- Visualize a API no navegador:
- digite http://localhost:8000 no seu navegador
- Entre na pasta do projeto:
- cd *pasta do projeto*
- Rode o código na sua máquina:
- npm install (para instalar as dependências do projeto)
- npm start (para abrir o projeto no seu navegador)
* Caso o projeto não abra automaticamente, digite http://localhost:3000 no seu navegador