Extract Schwan

Array ( [as_domain] => amazon.com [as_name] => Amazon.com, Inc. [asn] => AS14618 [continent] => North America [continent_code] => NA [country] => United States [country_code] => US )

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Schwan's Grocery Data Scraping API – Web Scraping Schwan's APIs

Actowiz Solutions offers the Schwan's Grocery Data Scraping API, a powerful tool for businesses looking to scrape Schwan's supermarket data efficiently. Web Scraping Schwan's APIs enables you to gather comprehensive grocery data, including product listings, prices, and availability across multiple countries, including the USA, UK, India, UAE, Japan, Italy, Germany, Canada, Australia, China, Switzerland, Qatar, Singapore, Ireland, Macao SAR, Luxembourg, Austria, Denmark, and Norway. With our Grocery Data Scraping Services, you can effortlessly scrape Schwan's product data and integrate it into your systems through seamless Schwan's API Integration. Enhance your competitive edge with accurate, real-time grocery data at your fingertips.

API Response Format

All responses are returned in JSON format for easy integration into your application.

from flask import Flask, jsonify, request app = Flask(__name__) # Sample data for demonstration purposes products = [ {"id": "1", "name": "Apple", "price": 1.00, "rating": 4.5, "description": "Fresh apples"}, {"id": "2", "name": "Banana", "price": 0.50, "rating": 4.0, "description": "Ripe bananas"}, # Add more products as needed ] # Sample data for reviews reviews = { "1": [ {"reviewer": "Alice", "rating": 5, "text": "Great apples!", "helpfulness": 10}, {"reviewer": "Bob", "rating": 4, "text": "Very fresh.", "helpfulness": 5} ], "2": [ {"reviewer": "Charlie", "rating": 4, "text": "Tasty bananas.", "helpfulness": 3} ] } @app.route('/products', methods=['GET']) def get_products(): keyword = request.args.get('keyword', '') category = request.args.get('category', '') sort = request.args.get('sort', 'name') page = int(request.args.get('page', 1)) # Filter and sort products (basic implementation) filtered_products = [p for p in products if keyword.lower() in p['name'].lower()] sorted_products = sorted(filtered_products, key=lambda x: x[sort]) return jsonify(sorted_products) @app.route('/product/', methods=['GET']) def get_product(product_id): product = next((p for p in products if p['id'] == product_id), None) if product: return jsonify(product) return jsonify({"error": "Product not found"}), 404 @app.route('/reviews', methods=['GET']) def get_reviews(): product_id = request.args.get('product_id') product_reviews = reviews.get(product_id, []) return jsonify(product_reviews) @app.route('/offers', methods=['GET']) def get_offers(): product_id = request.args.get('product_id') # This is a placeholder; implement offer logic as needed offers = {"product_id": product_id, "offers": [{"discount": "10%", "availability": "In Stock"}]} return jsonify(offers) @app.route('/related', methods=['GET']) def get_related(): product_id = request.args.get('product_id') # This is a placeholder; implement related product logic as needed related_products = [{"id": "3", "name": "Orange"}, {"id": "4", "name": "Grapes"}] return jsonify(related_products) @app.route('/categories', methods=['GET']) def get_categories(): categories = [{"id": "1", "name": "Fruits"}, {"id": "2", "name": "Vegetables"}] return jsonify(categories) @app.route('/search', methods=['GET']) def search_products(): query = request.args.get('query', '') sort = request.args.get('sort', 'name') page = int(request.args.get('page', 1)) # Implement search logic (basic implementation) searched_products = [p for p in products if query.lower() in p['name'].lower()] sorted_products = sorted(searched_products, key=lambda x: x[sort]) return jsonify(sorted_products) @app.route('/price-history', methods=['GET']) def get_price_history(): product_id = request.args.get('product_id') # This is a placeholder; implement price history logic as needed price_history = [{"date": "2023-10-01", "price": 1.00}, {"date": "2023-10-10", "price": 1.20}] return jsonify(price_history) @app.route('/store-locations', methods=['GET']) def get_store_locations(): zipcode = request.args.get('zipcode') # This is a placeholder; implement location logic as needed locations = [{"name": "Store A", "address": "123 Main St", "hours": "9am-9pm"}] return jsonify(locations) @app.route('/cart', methods=['POST']) def manage_cart(): user_id = request.json.get('user_id') action = request.json.get('action') product_id = request.json.get('product_id') # Implement cart management logic here return jsonify({"status": "success", "message": f"Product {action} to cart for user {user_id}."}) @app.route('/checkout', methods=['POST']) def checkout(): user_id = request.json.get('user_id') payment_info = request.json.get('payment_info') # Implement checkout logic here return jsonify({"status": "success", "message": "Checkout completed successfully."}) if __name__ == '__main__': app.run(debug=True)

Optimize Product Data with Our Schwan's Scraping API

Optimize your product data with our Schwan's Grocery Data Scraping API. Our powerful Schwan's Scraping API allows businesses to efficiently scrape Schwan's product data from various supermarkets, ensuring you stay updated with the latest product information. With our comprehensive Grocery Data Scraping Services, you can access critical insights into pricing, availability, and promotions across multiple regions. This enables informed decision-making and enhances competitive advantage in the ever-evolving market. Trust our reliable solutions to streamline your data extraction processes, ensuring you have the most accurate and timely data at your fingertips. Experience the difference with our Schwan's data solutions today!

Array ( [as_domain] => amazon.com [as_name] => Amazon.com, Inc. [asn] => AS14618 [continent] => North America [continent_code] => NA [country] => United States [country_code] => US )

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