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A tool that scrapes images and details of products from specific e-commerce websites, focusing on categories like shoes, bags, and accessories. It automates the downloading of high-quality images and essential product information for efficient data collection.

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Abdelmathin/product-scraper

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Product Scraper

A powerful tool for scraping product images and details from various e-commerce websites. This repository contains scripts designed to extract valuable information, enabling users to gather product data efficiently.


🛠 Features

  • Image Scraping: Download high-quality images of products.
  • Detail Extraction: Gather essential product details such as names, prices, and descriptions.
  • Multi-Site Support: Easily extendable to support multiple e-commerce platforms.

📦 Installation

  1. Clone the Repository
git clone https://github.com/Abdelmathin/product-scraper.git
cd product-scraper
  1. Install Dependencies

Make sure to install the required Python packages:

pip install -r requirements.txt

🚀 Usage

To run the scraper, execute the desired script. Here’s an example of how to use the main scraping script:

python main.py

The script will automatically scrape product details from the following categories:

  • Shoes
  • Bags
  • Accessories

Example

The main script will use the following code structure to scrape each category:

for product in ['shoes', 'bags', 'acc']:
    link = 'http://' + product + '.ygshoes188.com/'
    s = Scraper(product, link)
    s.run()

🛡 License

This project is licensed under the MIT License - see the LICENSE file for details.

🤝 Contributing

Contributions are welcome! If you have suggestions or find issues, feel free to submit a pull request or open an issue in this repository.

📧 Contact

For questions or support, please reach out via GitHub Issues or contact me at abdelmathinhabachi@gmail.com.

🌟 Fun Fact

Web scraping opens up a world of data collection possibilities, making it easier to analyze market trends and compare products across platforms!

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A tool that scrapes images and details of products from specific e-commerce websites, focusing on categories like shoes, bags, and accessories. It automates the downloading of high-quality images and essential product information for efficient data collection.

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