Ceratec-PDP-Scraper

A Python-based web scraping project to extract Product Detail Page (PDP) data from Ceratec Surfaces product pages.

This project is built specifically around the Ceratec PDP structure (example: Alchemy series) and demonstrates how to reliably collect structured product data for e-commerce, cataloging, or analytics use cases.

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🔍 Example Product Page

https://www.ceratec.com/fr/RSS-2048-Alchemy-2

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📌 Data Points Extracted

The scraper follows the navigation and data mapping shown in the provided screenshots and documentation.

#	Field
1	Product URL
2	Product Title
3	Breadcrumbs
4	Product Description
5	Image URLs (all variants)
6	Color of Variant
7	Color Grouping
8	Surface Finish / Material
9	Dimension / Size Grouping
10	Technical Documents (PDF links)

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📂 Project Structure

ceratec-pdp-scraper/
│
├── pdp_ceratec.py          # Main scraper logic
├── constants.py           # Headers & cookies
├── Navigatin_document.pptx # Navigation & field mapping reference
├── Pending_todo_Website.txt
├── product_data_*.csv     # Output (CSV)
├── product_data_*.xlsx    # Output (Excel)
└── README.md

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⚙️ Tech Stack

• Python 3.9+
• requests
• beautifulsoup4
• pandas

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🚀 How to Run

1️⃣ Install Dependencies

pip install requests beautifulsoup4 pandas

2️⃣ Run the Scraper

python pdp_ceratec.py

3️⃣ Output

The script automatically generates timestamped files:

• product_data_YYYYMMDD_HHMMSS.csv
• product_data_YYYYMMDD_HHMMSS.xlsx

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🧠 How It Works

• Sends a browser-like request using realistic headers
• Parses the HTML with BeautifulSoup
• Extracts variant attributes using label-based matching
• Collects technical document download links
• Stores structured output using Pandas

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🧩 Key Functions

• get_product_title()
• get_breadcrumbs()
• get_description()
• get_image_urls()
• get_color_grouping_by_tag()
• get_size_grouping()
• get_material()
• get_technical_document()

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📎 Notes

• Cookies are optional but included for stability
• Script retries requests automatically
• Easy to scale for multiple product URLs

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📈 Use Cases

• E-commerce catalog scraping
• Product data enrichment
• Variant image & color extraction
• Market research & analytics

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👤 Author

Shoeb Ahmed Web Scraping | Python | Data Extraction

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⚠️ Disclaimer

This project is for educational and portfolio purposes only. Please respect website terms of service before scraping.

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