Foodpanda Restaurants & Menus Scraper - Food Delivery Data API

Scrape Foodpanda restaurants and full menus from foodpanda.com.bd, foodpanda.pk, foodpanda.ph, foodpanda.com.tw, foodpanda.my, foodpanda.hk, foodpanda.sg, foodpanda.com.kh, foodpanda.la and foodpanda.com.mm. Each record has the restaurant name, address, GPS coordinates, phone, cuisines, rating and review count, delivery fee, minimum order, delivery time, discounts, opening hours and the complete menu with prices. Paste a city URL, press Start, and export the results as JSON, CSV or Excel, or call the actor as an API.

Target website: foodpanda.com.bd

⚖️ Is it legal to scrape Foodpanda?

This actor only collects data that Foodpanda shows publicly to any visitor, with no login. Scraping publicly available data is generally considered lawful (see hiQ Labs v. LinkedIn), but you are responsible for complying with Foodpanda's Terms of Service and laws such as GDPR when handling personal data like phone numbers.

✨ Features of this Foodpanda restaurant scraper

• Restaurant and menu extraction: restaurant details, contact phone, legal name, ratings, delivery conditions, discounts, opening hours, and every menu item with category, description, price, discounted price, variations and image.
• 10 Foodpanda countries: Bangladesh, Pakistan, Philippines, Taiwan, Malaysia, Hong Kong, Singapore, Cambodia, Laos and Myanmar.
• Pagination support: walks through all restaurants that deliver to a location until Max items is reached.
• Location search: start from a city page, a listing URL or any latitude/longitude pair.
• Keyword filtering: keep only restaurants whose name, chain or cuisine matches, for example pizza or KFC.
• Only-new mode: a cache project name skips restaurants scraped in earlier runs.
• Proxy support: optional Apify Proxy.
• No browser required: plain HTTP requests keep runs fast and cheap.

🚀 How to scrape Foodpanda restaurants in 5 steps

1. Sign up for a free Apify account. It includes $5 monthly credit.
2. Open the actor page and click Try for free.
3. Fill in the Input fields (a city or restaurant URL, or a latitude and longitude, is required).
4. Click Start and wait for the run to complete.
5. Download results from the Output tab in JSON, CSV, or Excel format.

You can also run this actor via the Apify API or integrate it directly into your workflows using Zapier, Make, or n8n.

💰 Foodpanda scraper pricing

This actor uses pay-per-result billing: you pay for each restaurant saved to the dataset.

• New Apify accounts include $5 of free monthly credit.
• It does not use a browser, so it costs significantly less to run than browser-based scrapers.
• Proxies are off by default, which keeps runs cheapest.
• Restaurants skipped by the cache are not charged (see below).

♻️ Scrape only new Foodpanda restaurants with the cache (no repeat charges)

Set a Cache project name (for example dhaka-restaurants) and the scraper remembers every restaurant it saves under that name. On every later run with the same name:

• Already-scraped restaurants are skipped — they are not saved again, so you never get duplicates across runs.
• Skipped restaurants cost nothing — you only pay for restaurants saved to the dataset, and cached ones are never saved.
• Max items counts only new restaurants — the scraper keeps paging past cached restaurants until it finds Max items new ones (or the location runs out).
• New restaurants are marked — each saved record gets changeType: "new".

Example: a weekly schedule on Dhaka with Max items 100. Week 1 saves 100 restaurants. In week 2 those 100 are skipped for free, and you get and pay for only the next 100, including restaurants that newly joined Foodpanda.

The cache is a named key-value store in your own Apify account (foodpanda-<your project name>). Use a different name for each city or location you want to track, and use a new name (or delete that store) to start from scratch. Leave the field empty to scrape everything on every run.

🔧 Foodpanda scraper input configuration

1. City, location or restaurant URLs — paste Foodpanda city pages (for example https://www.foodpanda.com.bd/city/dhaka), location listing URLs or single restaurant pages.
2. Max restaurants per location — how many restaurants to save for each city, location URL or coordinate pair.
3. Cache project name — set a name to skip restaurants already scraped in earlier runs, at no extra cost (see the cache section above).
4. Scrape menus and opening hours — on by default; fetches every restaurant's full menu with prices and its opening hours. Turn off for faster, cheaper runs with restaurant details only.

Field	Type	Required	Default	Description
City, location or restaurant URLs (startUrls)	array	—	Dhaka city URL (prefill)	Foodpanda city, location listing or restaurant URLs.
Max restaurants per location (maxItems)	integer	—	5	Maximum restaurants per city, location URL or coordinate pair.
Cache project name (cacheProjectName)	string	—	—	Same name on every run skips restaurants already scraped; they are not charged and do not count towards Max items.
Scrape menus and opening hours (scrapeMenus)	boolean	—	true	Fetch the full menu and opening hours of every restaurant. Restaurant URLs always include the menu.
Country (country)	string	—	bd	Search by coordinates and keyword section. Country used with the latitude and longitude: bd, pk, ph, tw, my, hk, sg, kh, la, mm.
Latitude (latitude)	number	—	—	Delivery location latitude, for example 23.7925.
Longitude (longitude)	number	—	—	Delivery location longitude, for example 90.4078.
Keyword filter (searchQuery)	string	—	—	Keep only restaurants whose name, chain or cuisine contains this text. Applies to URLs too.
Proxy configuration (proxyConfiguration)	object	—	{"useApifyProxy": false}	Proxy & concurrency section. Optional Apify Proxy settings.
Max concurrency (maxConcurrency)	integer	—	5	Maximum parallel requests.

Supported URL types:

• City page: https://www.foodpanda.com.bd/city/dhaka (searches around the city centre)
• Location listing: https://www.foodpanda.pk/restaurants/new?lat=24.8607&lng=67.0011
• Restaurant page: https://www.foodpanda.com.bd/restaurant/c2m4/degh-c2m4

📦 Foodpanda scraper output data

Every record is a JSON object with the keys id, code, vendorId, name, url, country, city, address, postCode, latitude, longitude, distanceKm, phone, website, description, chainName, chainCode, primaryCuisine, cuisines, foodCharacteristics, rating, reviewCount, budget, currency, minimumDeliveryFee, minimumOrderAmount, minimumDeliveryTime, minimumPickupTime, isDeliveryEnabled, isPickupEnabled, isActive, isTemporarilyClosed, isPremium, isNew, isSuperVendor, discounts, tags, legalName, tradeRegisterNumber, timezone, logo, heroImage, schedules, menuItemCount, menu and scrapedAt (plus changeType when a cache is used). The dataset has one view: Overview, a table with the name, link, country, city, cuisine, rating, reviews, minimum order, delivery fee, delivery time, phone and menu size.

Output at a glance:

Restaurant	Cuisine	Rating	Reviews	Min. order (BDT)	Menu items
Degh	Rice Dishes	4.8	740	50	19
Hakka Dhaka - Banani	Asian	4.8	5877	50	78
Chaap Ghor - Banani	Kebab	4.6	467	50	84
The Great Kabab Factory - Gulshan	Kebab	4.9	816	50	59
Turkey Bliss	Middle Eastern	4.7	120	50	40

Sample output (raw JSON):

{
  "id": "bd-c2m4",
  "code": "c2m4",
  "vendorId": 73835,
  "name": "Degh",
  "url": "https://www.foodpanda.com.bd/restaurant/c2m4/degh-c2m4",
  "country": "BD",
  "city": "Dhaka",
  "address": "House - 109, Ground Floor, Road - 04, Block - B, Near PULSE MEDICAL CENTRE LTD., Banani, Dhaka - 1213",
  "postCode": "1213",
  "latitude": 23.79633464,
  "longitude": 90.40196092,
  "distanceKm": 2.597,
  "phone": "+8801886951955",
  "website": null,
  "description": null,
  "chainName": null,
  "chainCode": null,
  "primaryCuisine": "Rice Dishes",
  "cuisines": ["Rice Dishes", "Curry"],
  "foodCharacteristics": [],
  "rating": 4.8,
  "reviewCount": 740,
  "budget": 2,
  "currency": "BDT",
  "minimumDeliveryFee": 0,
  "minimumOrderAmount": 50,
  "minimumDeliveryTime": 0,
  "minimumPickupTime": 15,
  "isDeliveryEnabled": true,
  "isPickupEnabled": false,
  "isActive": true,
  "isTemporarilyClosed": false,
  "isPremium": false,
  "isNew": false,
  "isSuperVendor": false,
  "discounts": ["15% off"],
  "tags": ["DEAL"],
  "legalName": "Degh",
  "tradeRegisterNumber": null,
  "timezone": "Asia/Dhaka",
  "logo": null,
  "heroImage": "https://images.deliveryhero.io/image/fd-bd/LH/c2m4-hero.jpg",
  "schedules": [
    { "weekday": 1, "type": "delivering", "opens": "07:30", "closes": "23:00" },
    { "weekday": 2, "type": "delivering", "opens": "07:30", "closes": "23:00" }
  ],
  "menuItemCount": 19,
  "menu": [
    {
      "category": "Snacks",
      "productId": 10073818,
      "name": "Chotpoti ( চটপটি )",
      "description": "1:1 , Enjoy tangy, spicy Chotpoti with tender peas and potatoes in a zesty tamarind sauce.\nTopped with egg, fresh coriander, and crispy fuchka for a delicious crunch!",
      "price": 102,
      "priceBeforeDiscount": 120,
      "variations": [],
      "image": "https://foodpanda.dhmedia.io/image/global-menu-service/FP_BD/vendor/c2m4/product/11053126/15de90c0-5d6f-4e18-9158-e53446b58171.jpg",
      "isSoldOut": false
    },
    {
      "category": "Roti & Paratha",
      "productId": 8819980,
      "name": "Fulko Luchi",
      "description": "1 pc - Small deep-fried flatbread fried till perfection",
      "price": 21.25,
      "priceBeforeDiscount": 25,
      "variations": [],
      "image": "https://foodpanda.dhmedia.io/image/fd-bd/Products/8819980.JPG",
      "isSoldOut": false
    }
  ],
  "scrapedAt": "2026-10-15T16:10:22.029Z"
}

🐍 How to scrape Foodpanda with Python, JavaScript or the API

Run the actor programmatically with the official Apify clients. Replace <YOUR_API_TOKEN> with the token from your Apify Console.

Python (pip install apify-client):

from apify_client import ApifyClient

client = ApifyClient("<YOUR_API_TOKEN>")

run = client.actor("confidential_gnat/foodpanda-restaurants-scraper").call(run_input={
    "startUrls": [{"url": "https://www.foodpanda.com.bd/city/dhaka"}],
    "maxItems": 20,
})

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

JavaScript (npm install apify-client):

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_API_TOKEN>' });

const run = await client.actor('confidential_gnat/foodpanda-restaurants-scraper').call({
    startUrls: [{ url: 'https://www.foodpanda.com.bd/city/dhaka' }],
    maxItems: 20,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

cURL: start a run and wait for the dataset:

curl -X POST "https://api.apify.com/v2/acts/confidential_gnat~foodpanda-restaurants-scraper/run-sync-get-dataset-items?token=<YOUR_API_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"startUrls": [{"url": "https://www.foodpanda.com.bd/city/dhaka"}], "maxItems": 20}'

💡 What you can use Foodpanda restaurant data for

• Menu price monitoring: track item prices, discounts and sold-out items across restaurants and cities.
• Lead generation: build lists of restaurants with phone numbers, legal names, addresses and cuisines.
• Market research: map restaurant density, cuisines, ratings and delivery conditions by area.
• Competitor analysis: compare minimum orders, delivery fees, delivery times and promotions with nearby rivals.
• Restaurant discovery datasets: feed ratings, reviews and opening hours into apps, dashboards or AI models.

Food-delivery startups, restaurant chains, FMCG brands, market-research agencies and analysts across South and Southeast Asia use this data for pricing, sales prospecting and expansion planning.

⚠️ Limitations & known issues

• Delivery radius: Foodpanda shows only restaurants that deliver to the given point. A city URL searches around the city centre that Foodpanda publishes, which for some cities (for example Karachi) lies outside every delivery zone and returns nothing. Use a latitude/longitude or a location URL in a busy area instead, and several points to cover a large city.
• Local-language cuisines: in Taiwan, Laos, Myanmar and Cambodia some cuisine names come in the local language, which affects the keyword filter.
• Occasional bot checks: the site sometimes rejects a request; the actor retries automatically.

❓ Frequently asked questions

What data does the Foodpanda scraper return?

Restaurant name, address, coordinates, phone, cuisines, rating, review count, budget level, delivery fee, minimum order, delivery and pickup times, discounts, tags and legal name. With Scrape menus on (the default), each record also has opening hours and the full menu with prices, variations and images.

How many restaurants can I scrape from one city or location?

maxItems limits restaurants per city URL, location URL or coordinate pair. A single point usually returns a few hundred to a few thousand restaurants (about 750 around central Dhaka). Add more points to cover a larger area.

Do I need a proxy to scrape Foodpanda?

No. Proxies are off by default and the actor retries rejected requests itself. If many requests keep failing on your account, enable Apify Proxy (datacenter first, residential only if needed).

How do I scrape Foodpanda with Python?

Use the Python example above: call the actor with your input and iterate over the dataset items.

Can I run this Foodpanda scraper on a schedule?

Yes. Create an Apify Schedule and set Cache project name: each run then skips restaurants already scraped under that name, does not charge for them, and marks new records with changeType: new.

What output formats are supported?

JSON, CSV, Excel, XML and RSS, either from the Output tab or through the Apify API.

Which Foodpanda countries are supported?

Bangladesh, Pakistan, Philippines, Taiwan, Malaysia, Hong Kong, Singapore, Cambodia, Laos and Myanmar. Foodpanda Thailand has closed and is not supported.

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💬 Support & contact

If you encounter any issues or have questions, please open an issue or reach out via the Apify Community Forum.

You can also find more of our actors on the Actor Flow page.