Rating 4.7
Rating 4.7
Rating 4.5
Rating 4.7
Rating 4.7
Disclaimer : Real Data API only extracts publicly available data while maintaining a strict policy against collecting any personal or identity-related information.
Real Data API offers a powerful Dan Murphy's Scraper designed to collect structured, high-accuracy retail data directly from Australia’s leading liquor retailer. Our solution enables businesses to efficiently Scrape Dan Murphy's wine, beer, and spirits data, including product names, pricing, discounts, stock availability, ratings, categories, and promotional offers. With seamless integration support, our advanced Dan Murphy's API delivers real-time and scheduled data extraction to power pricing intelligence, assortment tracking, and competitive benchmarking strategies. Retailers, distributors, and market analysts can leverage this data to monitor alcohol pricing trends, identify emerging brands, and optimize inventory decisions. Real Data API ensures scalable, compliant, and automated data solutions tailored to beverage market analytics and retail intelligence needs.
A Dan Murphy’s data scraper is a specialized tool designed to collect structured product information from the retailer’s online store. It automatically extracts details such as product names, brands, categories, prices, discounts, ratings, and stock status. Using a Dan Murphy's alcohol data scraping API, businesses can automate data collection in real time or on a scheduled basis. The system works by sending secure requests to targeted pages, parsing relevant fields, and converting unstructured web content into organized datasets. This enables retailers, distributors, and analysts to monitor assortment trends, promotional strategies, and competitive positioning efficiently and accurately.
Extracting data from Dan Murphy’s helps businesses gain insights into pricing strategies, competitor assortments, and promotional campaigns. As one of Australia’s largest liquor retailers, Dan Murphy’s provides a rich source of market intelligence. With a Dan Murphy's liquor product data scraper, companies can track SKU-level details across wine, beer, and spirits categories. This supports competitive benchmarking, dynamic pricing adjustments, and demand forecasting. Suppliers can analyze shelf visibility, while retailers can compare regional availability trends. Access to structured data improves decision-making, strengthens pricing strategies, and identifies emerging beverage trends in a highly competitive alcohol retail market.
Data extraction legality depends on compliance with website terms of service, intellectual property laws, and regional data regulations. Ethical scraping focuses only on publicly available information without accessing restricted systems or personal data. Using Dan Murphy's pricing and availability data scraping solutions responsibly ensures adherence to industry standards and best practices. Businesses should implement rate limits, respect robots.txt policies, and avoid disrupting website operations. Consulting legal counsel before launching large-scale extraction projects is recommended. When conducted transparently and responsibly, web data collection can be a legitimate method for market research and competitive intelligence.
Data can be extracted using automated scraping tools, APIs, or custom-built crawlers designed to capture structured retail information. A professional solution like a Dan Murphy's alcohol retail data extractor enables automated collection of product listings, categories, pricing updates, and stock levels. The process typically includes defining target URLs, mapping required data fields, scheduling extraction frequency, and exporting results into databases or dashboards. Businesses often integrate extracted data into analytics systems for price monitoring, assortment analysis, and reporting. Choosing a scalable and secure extraction solution ensures reliable performance without affecting site functionality.
If you require additional data intelligence solutions, alternative approaches include third-party retail data providers, marketplace aggregators, or advanced API integrations. Leveraging Dan Murphy's wine and spirits catalog data extraction tools allows businesses to access detailed product descriptions, vintage information, alcohol content, and packaging formats. Companies can combine multiple data sources to enrich analytics and validate pricing accuracy. Scalable solutions also support historical data tracking for trend forecasting. Selecting the right provider depends on data volume, refresh frequency, compliance standards, and integration requirements to meet your competitive intelligence goals.
Real Data API offers flexible input options tailored to business intelligence needs. Clients can integrate our Real-time Dan Murphy's liquor pricing data API to receive live updates on product prices, discounts, and promotional changes across categories. This option supports automated dashboards, dynamic pricing engines, and competitive monitoring systems with instant refresh capabilities. For structured catalog tracking, businesses can Extract Dan Murphy's product listings and stock data through scheduled data feeds or custom API endpoints. This includes SKU-level details such as brand, volume, availability status, and category classification. Our scalable input formats—JSON, CSV, or direct database integration—ensure seamless compatibility with analytics platforms and enterprise systems.
import requests
from bs4 import BeautifulSoup
import json
from datetime import datetime
BASE_URL = "https://www.danmurphys.com.au/product/DM-874563"
HEADERS = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64)"
}
def fetch_product_data(url):
response = requests.get(url, headers=HEADERS, timeout=10)
response.raise_for_status()
soup = BeautifulSoup(response.text, "html.parser")
product = {
"product_name": soup.select_one("h1").get_text(strip=True),
"price": soup.select_one(".price").get_text(strip=True),
"stock_status": soup.select_one(".stock-status").get_text(strip=True),
"rating": soup.select_one(".rating-value").get_text(strip=True),
"last_updated": datetime.utcnow().isoformat()
}
return product
if __name__ == "__main__":
try:
data = fetch_product_data(BASE_URL)
print(json.dumps(data, indent=4))
except Exception as e:
print(f"Error: {e}")
Real Data API enables seamless integrations with Dan Murphy’s Scraper to support advanced Dan Murphy's liquor catalog scraper for market insights across retail, distribution, and analytics platforms. Businesses can connect extracted data directly to BI tools, ERP systems, dynamic pricing engines, and inventory management software through REST APIs or scheduled data feeds. Structured outputs help build a centralized Liquor Dataset containing SKU-level details such as pricing, availability, brand segmentation, and promotional activity. These integrations empower retailers and suppliers to automate reporting, monitor competitors, forecast demand trends, and optimize assortment strategies with accurate, real-time alcohol retail intelligence.
Executing Dan Murphy’s data scraping with Real Data API is simple, scalable, and fully automated. Our advanced Dan Murphy's Scraper captures structured product data, including pricing, promotions, availability, categories, and ratings across wine, beer, and spirits segments. Businesses can configure extraction frequency—real-time, daily, or weekly—based on their analytics requirements. Through secure integration with the Dan Murphy's API, clients receive clean, structured datasets in JSON or CSV formats, ready for dashboards, pricing engines, or BI platforms. The system ensures high accuracy, minimal latency, and enterprise-grade reliability, enabling retailers and distributors to make faster, data-driven decisions in a competitive liquor market.
You should have a Real Data API account to execute the program examples.
Replace
in the program using the token of your actor. Read
about the live APIs with Real Data API docs for more explanation.
import { RealdataAPIClient } from 'RealDataAPI-client';
// Initialize the RealdataAPIClient with API token
const client = new RealdataAPIClient({
token: '' ,
});
// Prepare actor input
const input = {
"categoryOrProductUrls": [
{
"url": "https://www.amazon.com/s?i=specialty-aps&bbn=16225009011&rh=n%3A%2116225009011%2Cn%3A2811119011&ref=nav_em__nav_desktop_sa_intl_cell_phones_and_accessories_0_2_5_5"
}
],
"maxItems": 100,
"proxyConfiguration": {
"useRealDataAPIProxy": true
}
};
(async () => {
// Run the actor and wait for it to finish
const run = await client.actor("junglee/amazon-crawler").call(input);
// Fetch and print actor results from the run's dataset (if any)
console.log('Results from dataset');
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
console.dir(item);
});
})();
from realdataapi_client import RealdataAPIClient
# Initialize the RealdataAPIClient with your API token
client = RealdataAPIClient("" )
# Prepare the actor input
run_input = {
"categoryOrProductUrls": [{ "url": "https://www.amazon.com/s?i=specialty-aps&bbn=16225009011&rh=n%3A%2116225009011%2Cn%3A2811119011&ref=nav_em__nav_desktop_sa_intl_cell_phones_and_accessories_0_2_5_5" }],
"maxItems": 100,
"proxyConfiguration": { "useRealDataAPIProxy": True },
}
# Run the actor and wait for it to finish
run = client.actor("junglee/amazon-crawler").call(run_input=run_input)
# Fetch and print actor results from the run's dataset (if there are any)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# Set API token
API_TOKEN=<YOUR_API_TOKEN>
# Prepare actor input
cat > input.json <<'EOF'
{
"categoryOrProductUrls": [
{
"url": "https://www.amazon.com/s?i=specialty-aps&bbn=16225009011&rh=n%3A%2116225009011%2Cn%3A2811119011&ref=nav_em__nav_desktop_sa_intl_cell_phones_and_accessories_0_2_5_5"
}
],
"maxItems": 100,
"proxyConfiguration": {
"useRealDataAPIProxy": true
}
}
EOF
# Run the actor
curl "https://api.realdataapi.com/v2/acts/junglee~amazon-crawler/runs?token=$API_TOKEN" \
-X POST \
-d @input.json \
-H 'Content-Type: application/json'
productUrls
Required Array
Put one or more URLs of products from Amazon you wish to extract.
Max reviews
Optional Integer
Put the maximum count of reviews to scrape. If you want to scrape all reviews, keep them blank.
linkSelector
Optional String
A CSS selector saying which links on the page (< a> elements with href attribute) shall be followed and added to the request queue. To filter the links added to the queue, use the Pseudo-URLs and/or Glob patterns setting. If Link selector is empty, the page links are ignored. For details, see Link selector in README.
includeGdprSensitive
Optional Array
Personal information like name, ID, or profile pic that GDPR of European countries and other worldwide regulations protect. You must not extract personal information without legal reason.
sort
Optional String
Choose the criteria to scrape reviews. Here, use the default HELPFUL of Amazon.
RECENT,HELPFUL
proxyConfiguration
Required Object
You can fix proxy groups from certain countries. Amazon displays products to deliver to your location based on your proxy. No need to worry if you find globally shipped products sufficient.
extendedOutputFunction
Optional String
Enter the function that receives the JQuery handle as the argument and reflects the customized scraped data. You'll get this merged data as a default result.
{
"categoryOrProductUrls": [
{
"url": "https://www.amazon.com/s?i=specialty-aps&bbn=16225009011&rh=n%3A%2116225009011%2Cn%3A2811119011&ref=nav_em__nav_desktop_sa_intl_cell_phones_and_accessories_0_2_5_5"
}
],
"maxItems": 100,
"detailedInformation": false,
"useCaptchaSolver": false,
"proxyConfiguration": {
"useRealDataAPIProxy": true
}
}