Web Scraping Project - Leather Goods & Handicrafts

A Python web scraping project designed to extract product data from various e-commerce websites specializing in leather goods and handicrafts.

📁 Project Structure

Web-Scrabing/
├── README.md                          # This file
├── requirements.txt                   # Python dependencies
│
├── 🐍 SCRAPERS (Main Scripts)
│   ├── curomania.py                  # Scrapes cuiromania.com leather products
│   ├── simple.py                     # General-purpose web scraper
│   ├── MinAjiliki.py                 # Scrapes MinAjiliki handicrafts
│   └── cleaned.py                    # Data cleaning utility
│
├── 📊 DATA & OUTPUTS
│   ├── data/                         # Directory for organized data files
│   ├── EXCEL/                        # Excel export folder
│   ├── cleaned_data.csv              # Cleaned and processed data
│   ├── cuiromania_products.csv       # Raw cuiromania.com products
│   ├── maleatherdesign_products.csv  # Leather design products (empty)
│   ├── maleatherdesign_products_100.csv  # Leather design products (100 items)
│   ├── leather_goods_cuiromania_*.csv    # Dated extracts
│   ├── leather_goods_morocco_*.csv      # Morocco products
│   ├── cleaned_data.csv              # Processed output
│   └── scraped_product_urls.json     # URLs JSON export
│
├── 💻 WEB CONTENT
│   └── product_page.html             # Sample/cached product page HTML
│
├── ⚙️ UTILITIES & CONFIG
│   ├── utils/                        # Utility functions directory
│   ├── scrapers/                     # Scrapers modules directory
│   ├── blog                          # Blog/documentation file
│   └── .vscode/                      # VS Code settings

🎯 What This Project Does

This project scrapes product data from multiple Moroccan and international leather goods/handicrafts websites:

• Cuiromania (curomania.py) - Premium leather goods
• MaLeatherDesign - Leather product catalog
• Other sources - Via simple.py and MinAjiliki.py

Data extracted:

• Product name & description
• Prices & availability
• Product URLs
• Images/media
• Categories & references

🚀 Getting Started

Prerequisites

• Python 3.x
• Dependencies listed in requirements.txt

Installation

# Clone the repository
git clone https://github.com/DohaSK/Web-Scrabing.git
cd Web-Scrabing

# Install dependencies
pip install -r requirements.txt

Running Scrapers

# Scrape Cuiromania products
python curomania.py

# Run general scraper
python simple.py

# Clean data
python cleaned.py

📋 Data Files Guide

Raw Data (Input)

File	Source	Purpose
cuiromania_products.csv	cuiromania.com	Raw product listings
maleatherdesign_products_100.csv	MaLeatherDesign	100 products sample
leather_goods_*.csv	Various	Dated extractions

Processed Data (Output)

File	Purpose
cleaned_data.csv	Deduplicated & cleaned dataset
scraped_product_urls.json	All product URLs in JSON format

Cache Files

File	Purpose
product_page.html	Sample HTML page for testing/reference

📝 Requirements

See requirements.txt for the complete list. Common dependencies:

• requests - HTTP requests
• BeautifulSoup4 - HTML parsing
• Selenium (optional) - JavaScript rendering
• pandas - Data processing

🔄 Workflow

1. Run Scraper (curomania.py / simple.py)
   ↓
2. Extract Product Data (name, price, URL, images)
   ↓
3. Save to CSV/JSON
   ↓
4. Clean & Deduplicate (cleaned.py)
   ↓
5. Export to Excel (data/EXCEL/)

📌 Important Notes

• Data Updates: Each scraper run overwrites or appends data with timestamps
• CSV Files with Dates: leather_goods_*_[timestamp].csv - These are dated backups
• Empty Files: Some CSVs may be empty if scraping failed or no data was found
• Rate Limiting: Be respectful to target websites; add delays between requests

🛠️ Troubleshooting

No Data Being Scraped?

• Check website URLs in scripts (websites may change structure)
• Verify internet connection
• Check for JavaScript-rendered content (may need Selenium)

Data Cleaning Issues?

• Review cleaned.py for filtering logic
• Check input CSV format matches expected structure

Large HTML Files?

• product_page.html is a cached page - safe to delete if needed

📂 Recommended Next Steps

To improve organization:

1. Move all scrapers → scrapers/ folder
2. Move utility functions → utils/ folder
3. Organize raw data → data/raw/
4. Organize processed data → data/processed/
5. Create config.py for URLs and settings

📝 License

Specify your license here (e.g., MIT, GPL, etc.)

👤 Author

Doha Skouf - Created April 2026

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📞 Support

For issues or questions, create an issue on GitHub or contact the project maintainer.