FNAC Scraper: Scalable Marketplace Data Extraction for E-Commerce Growth

import requests
from bs4 import BeautifulSoup

DEFAULT_HEADERS = {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:109.0)",
    "Accept-Language": "fr-FR,fr;q=0.9,en;q=0.8",
    "Accept-Encoding": "gzip, deflate",
    "Connection": "keep-alive"
}

def scrape_fnac_product(product_url):
    try:
        response = requests.get(product_url, headers=DEFAULT_HEADERS, timeout=15)
        response.raise_for_status()
    except requests.RequestException:
        return {"error": "Unable to fetch product page"}

    soup = BeautifulSoup(response.text, "html.parser")

    def safe_extract(selector, attribute=None):
        element = soup.select_one(selector)
        if not element:
            return "N/A"
        return element.get(attribute).strip() if attribute else element.get_text(strip=True)

    product_data = {
        "Product_Name": safe_extract("h1"),
        "Current_Price": safe_extract(".userPrice, .price"),
        "Product_Rating": safe_extract(".rating, .customerRating"),
        "Availability_Status": safe_extract(".availability, .stock"),
        "Product_SKU": safe_extract("[data-product-id]", "data-product-id")
    }

    return product_data

# Example FNAC product page
fnac_product_url = "https://www.fnac.com/example-product"
result = scrape_fnac_product(fnac_product_url)

print(result)