๐Ÿด Uber Eats Scraper [PPR] avatar

๐Ÿด Uber Eats Scraper [PPR]

Pricing

from $4.99 / 1,000 results

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๐Ÿด Uber Eats Scraper [PPR]

๐Ÿด Uber Eats Scraper [PPR]

๐Ÿด Uber Eats Scraper [PPR] pulls restaurant and menu data from Uber Eats with precision. ๐Ÿš€ Great for lead gen, market research, and competitive analysis. โšก Fast, reliable, and SEO-ready dataโ€”automate insights today!

Pricing

from $4.99 / 1,000 results

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0.0

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Developer

Scraper Engine

Scraper Engine

Maintained by Community

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0

Bookmarked

2

Total users

1

Monthly active users

5 days ago

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Fast, cost-effective Uber Eats scraper that turns a search query + location โ€” or a list of store URLs โ€” into clean, structured store and menu data. Built for scale, with an automatic anti-block proxy ladder and pay-per-result pricing, so you only pay for stores you actually get.

โœจ Why Choose Us?

  • ๐ŸŽฏ Two ways to scrape โ€” search by address (+ optional query) or paste store URLs directly.
  • ๐Ÿ›ก๏ธ Self-healing connection โ€” starts direct (cheapest), and only escalates to datacenter โ†’ residential proxies when Uber Eats blocks. No fiddly config.
  • ๐Ÿ• Deep menu data โ€” full menu sections, items, prices, images, and optional customizations (modifiers / add-ons).
  • โšก Live results โ€” every store is saved the instant it's collected; a crash never loses progress.
  • ๐Ÿ’ธ Pay per result โ€” billed per store, not per minute.

๐Ÿ”‘ Key Features

FeatureDescription
๐Ÿ“ Address searchFind stores near any address, optionally filtered by query
๐Ÿช Store verticalsRestaurants, grocery, convenience, pharmacy, alcohol, retail & more
๐Ÿ”— URL modeScrape specific Uber Eats store pages in bulk
๐Ÿ” Menu extractionSections, items, prices, availability, tags, images
๐Ÿงฉ CustomizationsOptional full modifier/add-on trees per item
โญ Reviews & ratingsStore rating, review count, featured reviews
๐Ÿ›ก๏ธ Proxy fallbackDirect โ†’ Datacenter โ†’ Residential, sticky once escalated
๐ŸŒ 55+ localesScrape Uber Eats across the US, EU, LATAM, APAC and more

๐Ÿ“ฅ Input

Choose one mode. If urls is provided, address and query are ignored.

{
"locale": "en-US",
"address": "1600 Pennsylvania Avenue, Washington DC",
"query": "Pizza",
"storeType": "RESTAURANTS",
"maxRows": 10,
"urls": [],
"getMenuCustomizations": false,
"proxyConfiguration": { "useApifyProxy": true },
"concurrency": 5,
"maxRetries": 3
}
FieldTypeDescription
localestringUber Eats locale, e.g. en-US, fr-FR. Applies to both modes.
addressstringDelivery address to search around (search mode).
querystringOptional search term (cuisine, brand, dish).
storeTypestringVertical tab: ALL, RESTAURANTS, GROCERY, PHARMACY, โ€ฆ
maxRowsintegerMax stores in search mode (0 = all).
urlsarrayUber Eats store URLs to scrape directly (bulk).
getMenuCustomizationsbooleanFetch full customization trees per item.
proxyConfigurationobjectApify Proxy used for the datacenter โ†’ residential fallback.
concurrencyintegerStores scraped in parallel (1โ€“20).
maxRetriesintegerRetries per blocked request (1โ€“10).

๐Ÿ“ค Output

Each dataset item is one store:

{
"title": "District Detroit Pizza",
"sanitizedTitle": "District Detroit Pizza",
"phoneNumber": "+12025551234",
"emails": [],
"cuisineList": ["Pizza"],
"location": { "address": "โ€ฆ", "city": "Washington", "country": "US", "latitude": 38.9, "longitude": -77.0 },
"currencyCode": "USD",
"rating": { "ratingValue": 4.8, "reviewCount": "260+" },
"storeAvailablityStatus": "AVAILABLE",
"isOpen": true,
"etaRange": "Delivered in 20 to 30 min",
"hours": [ โ€ฆ ],
"categories": ["$", "Pizza"],
"categoriesLink": [ โ€ฆ ],
"menu": [ { "catalogName": "Pizzas", "catalogItems": [ โ€ฆ ] } ],
"logoImageUrl": "https://โ€ฆ",
"heroImageUrl": "https://โ€ฆ",
"uuid": "โ€ฆ",
"url": "https://ubereats.com/store/โ€ฆ",
"merchantType": "MERCHANT_TYPE_RESTAURANT",
"distance": { "text": "2.2 mi", "accessibilityText": "2.2 miles" },
"supportedDiningModes": [ โ€ฆ ],
"storeReviews": [ โ€ฆ ],
"featuredReviews": [ โ€ฆ ]
}

๐Ÿš€ How to Use (Apify Console)

  1. Log in at console.apify.com โ†’ Actors.
  2. Open ๐Ÿด Uber Eats Scraper [PPR].
  3. Either enter an address (and optional query + store type), or paste store URLs.
  4. Click Start.
  5. Watch stores stream into the Output tab in real time.
  6. Export to JSON / CSV / XLSX / Excel when the run completes.

๐Ÿค– Use via API

curl -X POST "https://api.apify.com/v2/acts/<ACTOR_ID>/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
-H "Content-Type: application/json" \
-d '{"address":"1600 Pennsylvania Avenue, Washington DC","query":"Pizza","storeType":"RESTAURANTS","maxRows":10}'

๐ŸŽฏ Best Use Cases

  • ๐Ÿ“Š Competitor menu & price monitoring
  • ๐Ÿฝ๏ธ Restaurant & store discovery / market research
  • ๐Ÿ“ˆ Lead lists of local merchants by category and area
  • ๐Ÿ—บ๏ธ Delivery coverage and ETA analysis across locations

๐Ÿ’ฐ Pricing

Pay per result โ€” you are billed a flat price for each store written to the dataset (the apify-default-dataset-item event). No charge for stores that fail to collect. Failed targets never cost you anything; partial runs still return everything collected so far.

โ“ FAQ

Do I need a proxy? No. The scraper starts direct and only uses Apify Proxy if Uber Eats blocks it.

Search returns fewer than maxRows? Uber Eats only lists so many stores for a given area/query โ€” that's the ceiling, not a bug.

Why are some menus empty? Some stores (e.g. certain alcohol/convenience listings) expose no public catalog; the store record is still returned.

Which countries are supported? Anywhere Uber Eats operates โ€” pick the matching locale (55+ supported).

๐Ÿ›Ÿ Support & Feedback

Open an issue on the Actor's Issues tab in Apify Console with your run ID and input, and we'll take a look.


Data is collected only from publicly available Uber Eats pages. You are responsible for compliance with applicable laws and Uber's Terms of Service.