Restaurant Recommendation Website Based On Scrapped Data

This project aims to scrape restaurant data from https://afar.com and store it in both a JSON file and a MySQL database. The stored data can then be retrieved and displayed on a website built using React.

Table of Contents

• Getting Started
  • Prerequisites
  • Installation
• Usage
• Contributions
• Acknowledgments

Getting Started

Prerequisites

To run this project, you will need the following installed on your local machine:

• Python 3.x
• Django
• MySQL Connector for Python
• React

Installation

1. Clone the repository to your local machine:

git clone https://github.com/mimidoox/-Restaurant-Recommendation-Website.git

Usage

1. Scrape restaurant data and store it in a file:

• Execute the my_spider.py to scrape the data and save it in a JSON file.

  scrapy crawl my_spider -o data.json
  

2. Load the scraped data into the MySQL database:

• Execute the scrapy_to_db.py script to load the data from the file into the database.

  python3 scrapy_to_db.py /path/to/your/data.json
  

3. Display the restaurant data on the website:

• The React frontend retrieves the data from the Django backend using Axios and displays it on the website.

Contributions

• ARRAJ Mohamed
• ABERANE Dia Eddine
• Benaalioua Hicham

Acknowledgments

• Scrapy
• Django
• MySQL
• React
• Axios