Traditional web scrapers break when websites update their HTML structure. Pangolin adapts automatically.

• ✅ Zero Maintenance — Our AI detects page changes and updates parsers automatically
• ✅ 99.9% Uptime — Enterprise-grade infrastructure with automatic retry logic
• ✅ No Proxies Needed — Built-in anti-bot bypass (CAPTCHA, rate limits, fingerprinting)
• ✅ Multi-Format Output — Get data as JSON, HTML, or Markdown — whatever your app needs
• ✅ Real-Time Data — Fresh product prices, inventory, reviews in milliseconds

Perfect for: E-commerce sellers, price monitoring tools, market research, product analytics, and dropshipping businesses.

For Open Source Community:

🌏 International Users: Prefer email or Telegram? Contact csm@pangolinfo.com
🇨🇳 中国用户： 添加微信 Pangolin-Scraper 备注「GitHub免费额度」

Claim your 200 free API calls

Python:

import requests API_KEY = "your_free_api_key_here" response = requests.post( "http://scrapeapi.pangolinfo.com/api/v1/scrape", headers={"Authorization": f"Bearer {API_KEY}"}, json={ "url": "https://www.amazon.com/dp/B0DYTF8L2W", "parserName": "amzProductDetail", "formats": ["json"] } ) print(response.json())

JavaScript:

const response = await fetch("http://scrapeapi.pangolinfo.com/api/v1/scrape", { method: "POST", headers: { "Authorization": `Bearer YOUR_API_KEY`, "Content-Type": "application/json" }, body: JSON.stringify({ url: "https://www.amazon.com/dp/B0DYTF8L2W", parserName: "amzProductDetail", formats: ["json"] }) }); const data = await response.json(); console.log(data);

cURL:

curl -X POST http://scrapeapi.pangolinfo.com/api/v1/scrape \ -H "Authorization: Bearer YOUR_API_KEY" \ -H "Content-Type: application/json" \ -d '{  "url": "https://www.amazon.com/dp/B0DYTF8L2W",  "parserName": "amzProductDetail",  "formats": ["json"]  }'

{ "asin": "B0DYTF8L2W", "title": "Product Title Here", "price": 29.99, "rating": 4.5, "reviews": 1234, "imageUrl": "https://...", "inStock": true, ... }

🎉 That's it! You're now scraping e-commerce data with zero infrastructure setup.

💡 Recommendation:

• Learning web scraping? → Start with open source parser
• Building a side project? → Use free API tier
• Running a business? → Upgrade to paid for reliability

Amazon

Walmart

Shopify

eBay

• Product Details: ASIN, title, price, images, variants
• Rankings: Best Sellers Rank, category position
• Reviews: Rating, review count, top reviews
• Seller Info: FBA/FBM, seller name, shipping
• Inventory: Stock status, availability date

Similar comprehensive data extraction for each platform.

📖 Full API Documentation: https://docs.pangolinfo.com/api-reference

# Monitor competitor prices daily products = ["B08N5WRWNW", "B08L5VFJ2C", "B07ZPKN6YR"] for asin in products: data = scrape_amazon_product(asin) if data['price'] < my_price: send_alert(f"Competitor lowered price: {data['title']}")

Result: Stay competitive by adjusting prices based on real-time market data.

// Analyze product trends in a category const category = "Electronics > Headphones"; const results = await scrape_amazon_search(category, pages=10); const avgPrice = results.reduce((sum, p) => sum + p.price, 0) / results.length; const topBrands = getMostFrequent(results.map(p => p.brand));

Result: Generate market reports with pricing trends, top brands, and customer sentiment.

# Build a price drop notification service def check_wishlist(user_id): wishlist = get_user_wishlist(user_id) for item in wishlist: current_price = scrape_product(item.url)['price'] if current_price < item.target_price: send_email(user_id, f"Price drop alert: {item.name}")

Result: Create a valuable service without managing scraping infrastructure.

# Collect training data for price prediction models import pandas as pd data = [] for asin in asin_list: product = scrape_amazon_product(asin) data.append({ 'title': product['title'], 'price': product['price'], 'rating': product['rating'], 'reviews': product['reviews'], 'category': product['category'] }) df = pd.DataFrame(data) df.to_csv('amazon_products.csv')

Result: Build ML models with clean, structured e-commerce data.