DoorDash Restaurant Scraper

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Extract restaurant info + complete menus from DoorDash store pages — restaurant name, address, city, cuisine breadcrumbs, FAQ, and full menu sections with item names, descriptions, and prices.

Features

• 16 output fields per restaurant — flat schema with typed defaults (zero nulls)
• Complete menu extraction — every section + item with name, description, and price
• FAQ extraction — questions and answers about the restaurant
• Breadcrumb extraction — cuisine type and neighborhood
• Cloudflare bypass via Patchright Chromium + RESIDENTIAL US proxy (typically clears in 2–15 seconds)
• Hardcoded RESIDENTIAL US proxy — required, applied automatically

Input

Example Input

{
"storeUrls":[
"https://www.doordash.com/store/15034",
"https://www.doordash.com/store/6422"
],
"maxItems":10
}

Output

Each restaurant has 16 fields. All fields are always present — empty strings, zero, or empty array as typed defaults, never null.

Identity

Location

Categorization

Menu

FAQ

Metadata

Example Output

{
"storeId":"15034",
"storeName":"UBURGER",
"storeUrl":"https://www.doordash.com/store/15034",
"address":"636 Beacon Street",
"city":"Boston",
"state":"MA",
"breadcrumbs":["Home","Boston","Burgers","UBURGER"],
"menuSectionCount":11,
"menuItemCount":37,
"menuSections":["Usalads","Burgers","Sandwiches","Sides"],
"menuItems":[
{"section":"Usalads","name":"Greek Salad","description":"Romaine lettuce, cherry tomatoes, ...","price":"$8.50"}
],
"faqCount":3,
"faq":[
{"question":"How can I order from UBURGER on DoorDash?","answer":"..."}
],
"scrapedAt":"2026-04-13T05:55:00+00:00"
}

FAQ

Q: Why doesn't this scrape user reviews? DoorDash removed user-facing reviews from store pages and now only shows aggregate ratings via menu items. The reference actor labeled "DoorDash Reviews Scraper" is misleading — there are no individual reviews to extract. This actor instead extracts everything DoorDash actually exposes: menu, address, FAQ, and breadcrumbs.

Q: Why is a RESIDENTIAL proxy required? DoorDash's www.doordash.com/store/* paths are protected by Cloudflare which blocks Apify datacenter IPs with 403 Just a moment.... A real Chrome browser (Patchright) on a US residential IP solves the Cloudflare challenge automatically in 2–15 seconds. The proxy is hardcoded and applied automatically — no configuration needed.

Q: How long does each restaurant take? Roughly 15–25 seconds per restaurant (Cloudflare solve + page load + JSON-LD parse). Limited by the browser session, not by network throughput.

Q: Can I get prices in dollars (not strings)? Prices are kept as strings ("$8.50") because DoorDash sometimes uses ranges or currency symbols. Cast to float in your downstream pipeline if you need numerics: float(price.replace("$", "").split("-")[0]).

Q: Will this work for all DoorDash stores? Yes for restaurants with a published menu schema. About 40% of DoorDash stores don't expose a Menu JSON-LD on their store page (closed restaurants, brand aggregators like ezCater, certain catering platforms). For those stores the scraper still returns full restaurant info, FAQ, breadcrumbs and address — but menuSections and menuItems come back as empty arrays. Convenience-store / grocery URLs (e.g., /store/cvs, /store/walgreens) have a different page structure and may return fewer fields.

Use Cases

• Restaurant menu intelligence — track competitor pricing across markets
• Cuisine analysis — group restaurants by breadcrumb cuisine tag
• Market research — identify chains operating in specific cities
• Menu engineering — see which items / sections are common across restaurants
• Lead generation — find independent restaurants by city + cuisine