We extract restaurant profiles, menu catalogues, delivery estimates, promotional pricing, and user ratings from Hungerstation. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Restaurant Profiles objects from hungerstation.com. All fields typed and schema-versioned.
"restaurant_id": "RS-8921", "name": "Al Baik", "cuisine_types": "['Fast Food', 'Chicken', 'Middle Eastern']", "rating": 4.8, "review_count": 14205, "delivery_fee": 15.0, "delivery_time_min": 25, "is_open": true
| # | restaurant_id | name | cuisine_types | rating | review_count | delivery_fee |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Menu Categories objects from hungerstation.com. All fields typed and schema-versioned.
"category_id": "CAT-441", "restaurant_id": "RS-8921", "category_name": "Combo Meals", "item_count": 12, "display_order": 1, "is_active": true, "description": "Meals served with fries and a drink."
| # | category_id | restaurant_id | category_name | item_count | display_order | is_active |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Menu Items objects from hungerstation.com. All fields typed and schema-versioned.
"item_id": "ITM-99234", "restaurant_id": "RS-8921", "name": "Spicy Chicken Meal", "price": 28.5, "original_price": 32.0, "discount_pct": 11, "is_available": true, "calories": 950
| # | item_id | restaurant_id | category_id | name | description | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Delivery & Fees objects from hungerstation.com. All fields typed and schema-versioned.
"restaurant_id": "RS-8921", "user_zone_id": "ZN-RUH-04", "base_delivery_fee": 12.0, "surge_fee_active": true, "total_fee": 18.5, "estimated_eta_mins": 45, "distance_km": 4.2, "timestamp": "2026-05-12T19:30:00Z"
| # | restaurant_id | user_zone_id | base_delivery_fee | surge_fee_active | service_fee | total_fee |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Promotions objects from hungerstation.com. All fields typed and schema-versioned.
"promo_id": "PRM-552", "restaurant_id": "RS-8921", "title": "Weekend Special", "discount_type": "PERCENTAGE", "discount_value": 20, "min_order_requirement": 50.0, "is_platform_funded": false, "promo_code": "WEEKEND20"
| # | promo_id | restaurant_id | title | description | discount_type | discount_value |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Hungerstation scraper maps the entire food delivery ecosystem: restaurant profiles, menu hierarchies, dynamic delivery fees, and promotional tags: with location spoofing and session management built in.
Extract titles, cuisines, ratings, operational hours, and precise geolocation coordinates for every listed venue.
Capture categories, items, prices, nutritional information, and deep modifier hierarchies.
Track base delivery fees, surge pricing multipliers, and distance calculations mapped to specific delivery zones.
Monitor minimum and maximum delivery estimates during peak and off-peak operational hours.
Extract discount types, free delivery eligibility, minimum order requirements, and active promo codes.
Simulate specific GPS coordinates to load hyper-local restaurant lists and accurate delivery radiuses.
Scrape supermarket catalogues, stock availability, and FMCG pricing on Hungerstation Quick Commerce.
Capture aggregate rating scores and review volume trends to measure customer satisfaction.
Extract nested modifier groups, extra toppings, mandatory selections, and their associated upcharges.
Brief in. Clean data out.
Provide GPS polygons, city lists, or specific restaurant IDs. We design the extraction schema together.
We configure Scrapy crawlers, location spoofing, and API request replication for hungerstation.com.
Schema validation, null-rate checks, and menu completeness verification before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Food delivery platforms rely on complex geospatial APIs and dynamic pricing. Here is how we maintain stable extraction.
Loading accurate restaurant lists and delivery fees requires precise coordinate simulation. We inject exact latitude and longitude headers into API requests to map entire cities systematically.
Instead of scraping DOM elements, we interface directly with Hungerstation mobile and web backend endpoints. This guarantees structured JSON payloads and eliminates rendering overhead.
Delivery fees and ETAs fluctuate wildly during peak meal hours. Our infrastructure supports high-frequency polling to capture surge multipliers and delivery time volatility.
Restaurant menus feature deeply nested arrays of categories, items, and modifier groups. Our pipeline normalises this unstructured data into clean relational tables ready for SQL ingestion.
We utilise dedicated KSA and Bahrain residential IP networks to prevent geo-blocking and ensure the platform returns accurate local pricing and promotional campaigns.
Ghost kitchens monitor local cuisine gaps, pricing strategies, and delivery times to optimise their menu offerings.
Restaurant chains track rival promotional campaigns, combo pricing, and delivery fee subsidies.
Aggregators and analysts measure restaurant density, exclusivity agreements, and category saturation across neighbourhoods.
Grocery brands track product availability, shelf pricing, and out-of-stock rates on Hungerstation Quick Commerce.
Pricing teams correlate competitor surge fees and delivery estimates with weather and time-of-day variables.
Private equity firms evaluate market penetration, active restaurant counts, and rating distributions for food-tech investments.
"Hungerstation holds the most precise hyper-local commerce data in the region: but extracting it requires rigorous geospatial simulation."
Most data teams fail at food delivery scraping because they underestimate the complexity of location-based APIs and dynamic pricing. DataFlirt handles the coordinate spoofing, mobile endpoint reverse-engineering, and residential proxy rotation so your engineers can focus on yield management and market analysis.
Everything supported by our hungerstation.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles grid-based coordinate iteration to ensure full city coverage without overlapping zones or missing neighbourhoods.
Playwright intercepts network requests to isolate backend JSON payloads, bypassing frontend rendering overhead and extracting clean data.
Airflow schedules hourly sweeps during peak meal times, storing state in Postgres and pushing deduplicated records to S3.
Data delivered to where your team already works — no new tooling required.
About hungerstation.com scraping, legality, and pipeline operations.
Ask us directly →We simulate exact GPS coordinates (latitude and longitude) during the crawl process. This allows us to map specific delivery zones, capture accurate delivery fees, and retrieve hyper-local restaurant availability just as a real user would experience it.
Yes. We traverse the entire menu hierarchy, capturing categories, base items, and nested modifier groups. This includes mandatory selections, extra toppings, and their associated price increments, all normalised into relational structures.
For dynamic pricing models, we can configure high-frequency polling pipelines that update delivery fees, surge multipliers, and ETA estimates every 15 to 30 minutes during peak operational hours.
Yes. We scrape supermarket catalogues, FMCG pricing, and real-time stock availability indicators from the Quick Commerce section of the platform.
We support data extraction across all Hungerstation operational territories, primarily focusing on Saudi Arabia (KSA) and Bahrain, using dedicated regional residential proxies to ensure accurate localised data.
Our smallest packages start at a defined list of coordinates or a specific city zone with weekly delivery. For nation-wide coverage or high-frequency polling, we price based on request volume and delivery cadence.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off menu catalogue dump or continuous delivery fee monitoring across Riyadh: we scope, build, and operate the pipeline. Tell us what you need.
