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GoPuff Scraper - Scrape GoPuff Restaurant Data

RealdataAPI / goPuff-scraper

Our goPuff scraper lets you extract accurate and up-to-date restaurant information from GoPuff across USA, UK, Canada, Australia, Germany, France, Singapore, UAE, and India. With our goPuff data scraping service, you can easily scrape goPuff restaurant data including menus, pricing, ratings, locations, and more. Whether you need a goPuff menu scraper for competitor analysis, market research, or app integration, Real Data API delivers clean, structured, and ready-to-use data. We ensure reliable, scalable, and fast data extraction from GoPuff’s platform, helping your business stay competitive. Access GoPuff’s vast restaurant and food item listings without manual work, saving time and resources. Power your applications with fresh, real-time data through our specialized GoPuff scraping solutions.

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

An A goPuff restaurant scraper is a specialized tool that extracts restaurant-related data from the GoPuff platform, including menus, prices, locations, ratings, and images. Our goPuff scraper USA and global solutions work by sending automated requests to GoPuff’s website or app, collecting the displayed information, and converting it into a clean, structured format such as JSON or CSV. This process enables businesses to access real-time food delivery and restaurant data without manual entry. With goPuff API integration, the scraped data can be seamlessly connected to your apps, dashboards, or analytics tools. Whether for market research, competitor tracking, or app development, our GoPuff scraping service delivers accurate, fast, and scalable data solutions tailored to your needs.

Why extract data from GoPuff?

Businesses choose to extract real-time goPuff data to gain instant access to updated restaurant menus, pricing, product availability, and delivery details. With goPuff data extraction, companies can track market trends, analyze competitor strategies, and optimize their offerings for different regions. Using Web Scraping GoPuff Dataset techniques, data is collected in bulk, structured into usable formats, and integrated into analytics systems. This helps food delivery platforms, market researchers, and app developers stay ahead in a competitive landscape. Through GoPuff Delivery API integration, the extracted data can be synced directly into applications, dashboards, or CRM systems, enabling automation and efficiency. Real-time GoPuff insights empower better decision-making, customer targeting, and business growth in the online delivery market.

Is it legal to extract GoPuff data?

Using a goPuff scraper to collect publicly available information can be legal if done in compliance with local laws, GoPuff’s terms of service, and data privacy regulations. Our goPuff data scraping service focuses on ethical, non-intrusive methods to scrape goPuff restaurant data such as menus, prices, and locations for research, analysis, or integration purposes. We avoid accessing private user data or engaging in activities that could harm the platform’s functionality. A goPuff menu scraper is designed for transparency, gathering only publicly displayed information and converting it into structured datasets. Always consult legal experts to ensure your scraping practices align with applicable laws and GoPuff’s policies before implementation.

How can I extract data from GoPuff?

To collect restaurant information from GoPuff, you can use a goPuff restaurant scraper that automates the process of gathering menus, prices, ratings, and delivery details. For region-specific needs, a goPuff scraper USA or other country-targeted solution ensures accurate, location-based results. The scraper works by sending requests to GoPuff’s platform, capturing the displayed data, and organizing it into formats like JSON or CSV. For seamless workflows, goPuff API integration allows this data to flow directly into your applications, dashboards, or analytics tools. This enables businesses to monitor competitors, analyze trends, and update product databases in real time. With the right tools, GoPuff data extraction becomes fast, scalable, and highly efficient.

Do you want more GoPuff scraping alternatives?

Yes, beyond direct tools to extract real-time goPuff data, there are multiple alternatives for collecting restaurant and product details. One option is using third-party goPuff data extraction platforms that specialize in web scraping and offer pre-built datasets. Another is Web Scraping GoPuff Dataset services, where you purchase regularly updated data without building your own scraper. For developers, integrating the GoPuff Delivery API (or similar APIs) can provide structured, on-demand access to menu items, pricing, and delivery zones. Cloud-based scraping tools and managed services are also popular, allowing you to scale data collection without hosting infrastructure. The best choice depends on your technical expertise, budget, and whether you need one-time data or continuous updates.

Input Options

When extracting data from GoPuff, various input options help customize the scraping process for your needs. You can start with specific URLs of restaurants or product categories, ensuring targeted goPuff data extraction. Location-based inputs, such as city names or postal codes, allow you to extract real-time goPuff data relevant to a geographic area. Keyword search inputs help narrow results to certain cuisines, dishes, or brands within the Web Scraping GoPuff Dataset process. For automated workflows, GoPuff Delivery API integration can accept structured requests containing filters like price range, rating, or availability. Combining these input options ensures your scraper collects exactly the data you need, improving efficiency, accuracy, and the value of your GoPuff dataset.

Sample Result of GoPuff Data Scraper

                                                sample_result = {
    "restaurant_name": "Pasta Express",
    "restaurant_id": "12345",
    "location": {
        "city": "New York",
        "state": "NY",
        "country": "USA",
        "latitude": 40.7128,
        "longitude": -74.0060
    },
    "menu": [
        {
            "item_name": "Spaghetti Bolognese",
            "price": 12.99,
            "currency": "USD",
            "category": "Pasta",
            "availability": True
        },
        {
            "item_name": "Garlic Bread",
            "price": 4.50,
            "currency": "USD",
            "category": "Sides",
            "availability": True
        }
    ],
    "ratings": 4.5,
    "reviews_count": 248
}

print(sample_result)
Integrations with GoPuff Data Scraper

The GoPuff Data Scraper can be seamlessly integrated with various tools and platforms to maximize its value. With GoPuff API integration, scraped data can automatically flow into analytics dashboards, CRM systems, or business intelligence tools. For developers, integrating with Python or Node.js scripts enables automation and custom processing of goPuff data extraction. E-commerce teams can connect the scraper to inventory management systems, ensuring extract real-time GoPuff data updates product availability instantly. Data analysts can link it to Google BigQuery, Excel, or Tableau for visualization, while marketing teams can sync datasets with email automation tools for targeted campaigns. These integrations streamline workflows, reduce manual work, and unlock deeper insights from your Web Scraping GoPuff Dataset.

Executing GoPuff Data Scraping Actor with Real Data API

Executing the GoPuff Data Scraping Actor with Real Data API is a straightforward way to extract real-time GoPuff data at scale. First, configure the Actor by specifying input parameters such as location, keywords, or restaurant URLs for targeted goPuff data extraction. Once triggered, the Actor uses automated crawling techniques to perform Web Scraping GoPuff Dataset operations, collecting menus, prices, ratings, and delivery details. The scraped data is then cleaned, structured, and delivered in JSON, CSV, or database-ready formats. Through GoPuff Delivery API integration, results can be instantly sent to your application, analytics dashboard, or cloud storage. This approach ensures fast, accurate, and reliable GoPuff restaurant data collection without manual work, enabling smarter business decisions.

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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'

Additional Resources

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Documentation

Learn more about Real Data API actors
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API reference

Consists of program examples

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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