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GrabFood Scraper - Scrape GrabFood Restaurant Data

RealdataAPI / grabFood-scraper

The GrabFood scraper offered by Real Data API provides an efficient solution to scrape GrabFood restaurant data across multiple countries including the USA, UK, Canada, Australia, Germany, France, Singapore, UAE, and India. Our GrabFood data scraping service extracts detailed information such as restaurant names, menus, prices, ratings, and delivery times. With the GrabFood menu scraper, businesses can access up-to-date menu items, pricing, and availability to support market research, competitor analysis, and app integration. This scalable and reliable service ensures timely and accurate data extraction, enabling businesses to stay competitive in the rapidly evolving food delivery market. Whether you need bulk data or frequent updates, Real Data API’s GrabFood scraper is your go-to tool for comprehensive GrabFood restaurant insights.

What is GrabFood Data Scraper, and how does it work?

The GrabFood scraper is a specialized tool designed to scrape GrabFood restaurant data efficiently from the GrabFood platform. It collects detailed restaurant information such as menus, prices, ratings, and delivery times. The GrabFood restaurant scraper automates data extraction by mimicking user interactions on the website or app, handling dynamic content and pagination. The GrabFood menu scraper captures real-time menu updates to ensure data accuracy. Widely used in regions like Singapore, including the GrabFood scraper Singapore, this tool integrates with other systems through GrabFood API integration, enabling seamless access to fresh data. Businesses rely on it to extract real-time GrabFood data for analytics, competitive analysis, and business intelligence, leveraging comprehensive Food Dataset insights.

Why extract data from GrabFood?

Extracting data using a GrabFood data scraping service provides businesses with crucial market intelligence in the competitive food delivery sector. By leveraging GrabFood data extraction, companies gain insights into menu changes, pricing trends, and restaurant availability. This information helps optimize product offerings, pricing strategies, and marketing campaigns. With access to a rich Food Data Scraping API, businesses can monitor competitors, analyze customer preferences, and identify emerging food trends. Extracted data empowers food aggregators, delivery platforms, and restaurants to enhance customer experience and operational efficiency. Overall, extracting data from GrabFood ensures timely and accurate insights, driving informed decision-making and helping businesses stay ahead in a fast-evolving market.

Is it legal to extract GrabFood data?

The legality of using a GrabFood scraper for data extraction depends on adherence to GrabFood’s terms of service and applicable laws. While public data may be accessible, unauthorized scraping can violate platform policies and lead to legal issues or access restrictions. Companies often choose to use official GrabFood API integration where available, ensuring compliance and data accuracy. Ethical GrabFood data extraction involves respecting site rules, limiting request rates, and protecting user privacy. Businesses should consult legal experts before deploying scraping solutions to avoid infringement risks. Responsible scraping ensures sustainable access to valuable data without violating GrabFood’s policies or regional data protection regulations.

How can I extract data from GrabFood?

To scrape GrabFood restaurant data, you can use a GrabFood scraper that automates the collection of restaurant listings, menus, prices, and ratings. This typically involves web scraping tools or services that mimic user behavior to handle dynamic web content. Alternatively, businesses may opt for a GrabFood data scraping service that provides structured data feeds and ongoing updates. Leveraging GrabFood API integration, if available, offers a more reliable and legal method for accessing data. For technical users, building a custom scraper or using a Food Data Scraping API enables tailored extraction workflows. Always ensure scraping practices respect GrabFood’s terms to maintain uninterrupted data access.

Do You Want More GrabFood Scraping Alternatives?

If you're seeking alternatives to your current GrabFood scraper, several options offer enhanced features like multi-country support, real-time updates, and comprehensive menu extraction. Services providing a GrabFood data scraping service often include scalable solutions for regions such as Singapore, the UAE, and beyond. Some platforms combine API access with scraping to ensure data accuracy and reliability. Depending on your needs—market research, competitor monitoring, or app development—exploring diverse vendors can optimize your data strategy. These alternatives leverage advanced technology to extract rich Food Dataset insights efficiently. Contact us for tailored recommendations on the best GrabFood restaurant scraper alternatives to fit your project goals.

Input options

The GrabFood Scraper provides versatile input options through the Real Data API, enabling precise and targeted food delivery data collection. Users can input parameters like restaurant names, cuisine types, menu keywords, location filters, price ranges, and customer ratings to scrape GrabFood restaurant data efficiently. Scheduling options allow automated extractions daily, weekly, or monthly, ensuring fresh datasets for analysis. Inputs can also include delivery time filters, discount-only menus, or specific meal categories for more focused results. This flexibility ensures the GrabFood data scraping service captures relevant GrabFood menu scraper outputs in a structured format. Businesses can then integrate this data seamlessly into their analytics platforms, market research tools, or competitor tracking systems for strategic decision-making.

Sample Result of GrabFood Data Scraper
{
  "restaurant_id": "67890",
  "name": "Tasty Bites",
  "address": "45 Food Street, Singapore",
  "cuisine": ["Asian", "Fast Food"],
  "rating": 4.3,
  "reviews_count": 150,
  "delivery_time": "25-35 mins",
  "minimum_order": 15,
  "menu": [
    {
      "item_id": "g001",
      "name": "Chicken Rice",
      "description": "Steamed chicken with fragrant rice",
      "price": 7.5,
      "currency": "SGD",
      "availability": true
    },
    {
      "item_id": "g002",
      "name": "Fried Noodles",
      "description": "Stir-fried noodles with vegetables",
      "price": 6.0,
      "currency": "SGD",
      "availability": true
    }
  ],
  "last_updated": "2025-08-12T07:30:00Z"
}


Integrations with GrabFood Data Scraper

The GrabFood scraper integrates seamlessly with various business intelligence and analytics platforms, enabling real-time access to comprehensive restaurant data. By connecting the scraped data with CRM, pricing engines, or market research tools, businesses can automate workflows and enhance decision-making. The GrabFood data scraping service delivers structured, clean data including menus, prices, ratings, and delivery details. Integration with other systems allows for dynamic updates and competitive benchmarking across regions like Singapore, UAE, and more. Leveraging the GrabFood menu scraper within your infrastructure ensures accurate, timely insights for marketing, inventory, and customer experience optimization. This integration empowers businesses to respond swiftly to market changes and customer preferences, driving growth and operational efficiency.

Executing GrabFood Data Scraping Actor with Real Data API

Using Real Data API, the GrabFood restaurant scraper actor automates the extraction of restaurant information from GrabFood, including menus, prices, ratings, and delivery times. This GrabFood data scraping service supports scheduled runs, ensuring the latest data is captured regularly. The actor handles dynamic web content and anti-bot protections, delivering clean, structured JSON data suitable for analytics or integration. With the GrabFood menu scraper embedded, the actor extracts detailed item-level data, enabling granular insights. This approach simplifies GrabFood API integration, making data accessible for real-time market analysis and competitive intelligence. The solution is scalable, reliable, and reduces manual effort, helping businesses maintain a competitive edge with fresh, accurate food delivery data.

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'

Place the Amazon product URLs

productUrls Required Array

Put one or more URLs of products from Amazon you wish to extract.

Max reviews

Max reviews Optional Integer

Put the maximum count of reviews to scrape. If you want to scrape all reviews, keep them blank.

Link selector

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.

Mention personal data

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.

Reviews sort

sort Optional String

Choose the criteria to scrape reviews. Here, use the default HELPFUL of Amazon.

Options:

RECENT,HELPFUL

Proxy configuration

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.

Extended output function

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
  }
}
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