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Access product data from multiple countries effortlessly and efficiently.
Receive immediate notifications on product changes and pricing fluctuations.
Tailor scraping parameters to fit specific business needs and goals.
Analyze product performance and customer insights for informed decision-making.
Easily integrate with existing systems for smooth data management.
Navigate and manage scraped data through an intuitive dashboard.
Generate regular reports for tracking performance and market trends.
Ensure protection and confidentiality of sensitive ecommerce data at all times.
Integrate the Bigbasket.com API to obtain real-time updates on product listings, availability, and pricing changes seamlessly.
Utilize the Bigbasket.com Order Data API to streamline order processing, tracking, and fulfillment for efficient e-commerce operations.
Leverage comprehensive API data to analyze sales performance metrics, identify trends, and drive informed strategic decision-making processes.
Use customer behavior data from the API to enhance personalized product recommendations, thereby increasing customer engagement and boosting sales.
Implement the API to effectively monitor competitors’ products, pricing strategies, and market positioning for informed competitive advantage insights.
Description: Fetch detailed product information based on various criteria.
keyword (string): Search term to find products.
category (string): Filter by specific product categories.
sort (string): Sorting options (e.g., price, popularity).
page (int): Pagination for large datasets.
Response: JSON object containing product name, ID, price, rating, and description.
Description: Retrieve detailed information for a specific product using its unique ID.
product_id (string): Unique ID for the product.
Response: JSON object with product details including title, price, features, and customer reviews.
Description: Fetch customer reviews and ratings for a specific product.
product_id (string): Unique ID for the product.
Response: JSON object containing reviewer names, ratings, review texts, and helpfulness votes.
Description: Retrieve current offers, discounts, and availability for a specific product.
product_id (string): Unique ID for the product.
Response: JSON object with offer details, including price, discount percentages, and stock availability.
Description: Get recommendations for related products based on a specific product.
product_id (string): Unique ID for the product.
Response: JSON object containing a list of related product IDs and names.
Description: Retrieve a list of available product categories on Bigbasket.com.
Response: JSON object containing category names and IDs for filtering products.
Description: Search for products based on various criteria like keywords and filters.
query (string): Search term to find products.
sort (string): Sorting options (e.g., price, rating).
page (int): Pagination for large datasets.
Response: JSON object with a list of products matching the search criteria.
Description: Retrieve historical pricing data for a specific product.
product_id (string): Unique ID for the product.
Response: JSON object containing price changes over time, including dates and corresponding prices.
All responses are returned in JSON format for easy integration into your application.
from flask import Flask, jsonify, request
app = Flask(__name__)
# Mock data for demonstration
products = {
"1": {
"name": "Wireless Headphones",
"price": 59.99,
"rating": 4.5,
"description": "High-quality wireless headphones with noise cancellation.",
"reviews": [
{"name": "Alice", "rating": 5, "text": "Great sound quality!"},
{"name": "Bob", "rating": 4, "text": "Comfortable and good battery life."}
],
"offers": {"price": 49.99, "discount": 20, "available": True}
},
"2": {
"name": "Bluetooth Speaker",
"price": 29.99,
"rating": 4.0,
"description": "Portable Bluetooth speaker with great sound.",
"reviews": [],
"offers": {"price": 25.99, "discount": 13, "available": True}
}
}
@app.route('/products', methods=['GET'])
def get_products():
keyword = request.args.get('keyword', '')
category = request.args.get('category', '')
sort = request.args.get('sort', 'price')
page = int(request.args.get('page', 1))
# Filtering and sorting logic would go here (mock data only)
return jsonify(products), 200
@app.route('/product/', methods=['GET'])
def get_product(product_id):
product = products.get(product_id)
if not product:
return jsonify({"error": "Product not found"}), 404
return jsonify(product), 200
@app.route('/reviews', methods=['GET'])
def get_reviews():
product_id = request.args.get('product_id')
product = products.get(product_id)
if not product:
return jsonify({"error": "Product not found"}), 404
return jsonify(product['reviews']), 200
@app.route('/offers', methods=['GET'])
def get_offers():
product_id = request.args.get('product_id')
product = products.get(product_id)
if not product:
return jsonify({"error": "Product not found"}), 404
return jsonify(product['offers']), 200
@app.route('/related', methods=['GET'])
def get_related():
product_id = request.args.get('product_id')
# Logic to find related products would go here (mock example)
related_products = {"related": ["3", "4", "5"]}
return jsonify(related_products), 200
@app.route('/categories', methods=['GET'])
def get_categories():
# Mock category data
categories = ["Electronics", "Books", "Home Appliances"]
return jsonify(categories), 200
@app.route('/search', methods=['GET'])
def search_products():
query = request.args.get('query', '')
sort = request.args.get('sort', 'price')
page = int(request.args.get('page', 1))
# Mock response for search (replace with actual search logic)
search_results = {"results": products}
return jsonify(search_results), 200
@app.route('/price-history', methods=['GET'])
def get_price_history():
product_id = request.args.get('product_id')
# Mock price history data
price_history = [
{"date": "2024-01-01", "price": 59.99},
{"date": "2024-02-01", "price": 49.99},
]
return jsonify(price_history), 200
if __name__ == '__main__':
app.run(debug=True)
Optimize your product data with our Bigbasket.com Scraping API designed for seamless Bigbasket.com API Integration. Our solution enables you to scrape Bigbasket.com product data efficiently, providing accurate and comprehensive insights into product listings, pricing, and availability. With advanced features like Bigbasket.com Product Scraping and Bigbasket.com Customer Reviews Scraping, you can enhance your competitive edge and make informed decisions. Leverage the Bigbasket.com Product Data API for real-time data retrieval, ensuring your inventory management is always up-to-date. Our Bigbasket.com Order Data API streamlines order processing, while Automated Bigbasket.com Data Extraction simplifies the entire data collection process, saving you valuable time and resources.
Whatever your project size is, we will handle it well with all the standards fulfilled! We are here to give 100% satisfaction.