DoorDash Scraper

DoorDash Scraper creates a structured dataset of DoorDash store, menu, product, collection, and deal records for a US delivery location. Each dataset item can include the item or store name, price, description, category, rating, merchant identifiers, and the resolved delivery location. Query the source using a search term, a DoorDash store or collection URL, or both, control the result limit with maxItems, and retrieve records through the Apify Dataset API or export them as JSON, CSV, Excel, or XML.

Dataset at a glance

Property	Value
Source	doordash.com
Record unit	One store, menu/retail product, product detail, store collection, or deal item
Input methods	Delivery location, search queries, DoorDash start URLs
Main identifiers	storeId, productId, collectionId, url
Delivery	Apify Dataset and API
Export formats	JSON, CSV, Excel, XML
Update model	Fresh records per Actor run
Pricing	Pay per event, from $1.50 per 1,000 events

Coverage and available records

The Actor resolves records for the delivery location you supply (address, city, or postal code) and returns the following record types, controlled by the extraction toggles:

• Products (scrapeProducts) — menu items and retail/grocery products. scrapeProductDetails switches to a fuller product payload.
• Store information (scrapeStoreDetails) — store address, ratings, hours-related flags, and delivery/pickup options.
• Store collections (scrapeStoreCollections) — menu categories and grocery/retail collections. Collection URLs always extract the opened collection.
• Deals (scrapeDeals) — featured deal products from the grocery and retail deal surfaces at the delivery location.

Location-specific availability means prices and search results are tied to the resolved delivery pin. A US residential proxy is used by default; results are not currently collected for non-US delivery locations.

Data dictionary

Field	Type	Nullable	Description	Example
recordType	string	No	product, product-details, store, or store-collection; drives pay-per-event billing	product
name	string	No	Menu item, product, store, or collection title	Big Mac
description	string	Yes	Item description when exposed	Two beef patties...
price	string	Yes	Localized price string	$5.99
storeName	string	Yes	Merchant name for the record	McDonald's
storeId	string	Yes	DoorDash store identifier	24508264
productId	string	Yes	Product identifier	104892...
collectionId	string	Yes	Collection identifier	12345
category	string	Yes	Menu category or retail collection name	Burgers
rating	string	Yes	Item- or store-level rating text when exposed	4.6 (1.2k)
url	string	Yes	Canonical DoorDash link for the record	https://www.doordash.com/...
imageUrl	string	Yes	Product or store image	https://...
searchQuery	string	Yes	Search term that discovered the record	McDonald's
sourceQuery	string	Yes	Source query context	McDonald's
source	string	Yes	How the record was discovered (search, URL type)	search

Store records (recordType: store) additionally include address, phone, website, DashPass flags, delivery/pickup options, and business tags. Collection records describe menu categories or retail aisles.

Example dataset record

{
  "recordType": "product",
  "name": "Big Mac",
  "price": "$5.99",
  "storeName": "McDonald's",
  "storeId": "24508264",
  "productId": "1048928277",
  "category": "Burgers",
  "url": "https://www.doordash.com/store/24508264",
  "imageUrl": "https://img.cdn4dd.com/...",
  "searchQuery": "McDonald's",
  "source": "search"
}

The record above was produced by the input in the next section: a delivery location of 72076 with the search query McDonald's.

Query and input reference

Input	Type	Required	Default	Accepted values	Description
location	string	Yes	—	Any address, city, or postal code	DoorDash drop-off location used to resolve search, availability, and prices
searchQueries	array	No	—	List of search terms	Cuisine, store name, or item searches
startUrls	array	No	—	DoorDash URLs	Search, store, collection, grocery/retail tab, or product URLs
scrapeProducts	boolean	No	true	true / false	Extract menu and retail products
scrapeProductDetails	boolean	No	false	true / false	Fuller product payload; charges product-details instead of product
scrapeStoreDetails	boolean	No	false	true / false	Push store information records
scrapeStoreCollections	boolean	No	false	true / false	Push category/collection records
scrapeDeals	boolean	No	false	true / false	Extract featured deal products
maxItems	integer	No	0	0 = unlimited	Maximum records across all types
proxyConfiguration	object	No	US residential	Apify proxy settings	Proxy configuration for the run

Minimal request:

{
  "location": "72076",
  "searchQueries": ["McDonald's"]
}

Advanced request:

{
  "location": "72076",
  "searchQueries": ["McDonald's"],
  "maxItems": 200,
  "scrapeProducts": true,
  "scrapeStoreDetails": true,
  "scrapeStoreCollections": true,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"],
    "apifyProxyCountry": "US"
  }
}

Retrieve the data through the API

1. Start the Actor with a JSON input containing at least a location.
2. Wait for the run to finish, or use the synchronous dataset endpoint for smaller jobs.
3. Read records from the run's default dataset.
4. Paginate or export the dataset.

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("datascrapers/doordash-scraper").call(
    run_input={
        "location": "72076",
        "searchQueries": ["McDonald's"],
        "maxItems": 8,
        "scrapeProducts": True,
    }
)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item["recordType"], item["name"], item.get("price"))

Apify's generated API tab documents the equivalent calls for other languages.

Data quality and record handling

• Completeness — fields such as description, price, rating, category, and imageUrl are conditional on what the source exposes for a given record and location.
• Record-type-specific fields — store and collection records carry fields not present on product records.
• Deduplication — the Actor does not deduplicate across runs; within a run, a product should appear once per discovery path.
• Recommended dedup key — combine productId, storeId, and the resolved postal code for recurring monitoring.
• Retry/error behavior — records that cannot be resolved are skipped; the run continues.
• Normalization — prices are localized strings; identifiers are passed through as source values.

Export and pipeline examples

Destination	Recommended method	Typical use
PostgreSQL/Supabase	Dataset API or webhook consumer	Price history and menu intelligence
Google Sheets	Apify integration	Competitive menu tracking
S3/cloud storage	Scheduled export or integration	Archival snapshots per location

Pricing and cost examples

Billing is pay per event: each dataset record pushed is one charge, and each event type is priced the same. Platform compute is included in the actor usage fee.

Event	What counts	Price (no plan discount)
product	Standard menu or retail product listing	$1.50 / 1,000
product-details	Fuller product payload	$1.50 / 1,000
store	Store profile record	$1.50 / 1,000
store-collection	Menu category or retail collection	$1.50 / 1,000

Records	Estimated base cost
1,000	$1.50
10,000	$15.00
100,000	$150.00

Apify plan discounts reduce the per-event rate (for example Gold plans pay about $1.20 per 1,000 events). Estimates depend on the verified pricing model and the extraction toggles you enable.

Limitations and responsible data use

• Only publicly accessible DoorDash data is returned.
• Availability and pricing are location-specific and tied to the delivery pin you provide.
• Fields may be missing or conditional depending on the store, record type, and region.
• No historical snapshots are stored unless you keep them yourself.
• You are responsible for complying with DoorDash's terms and applicable laws.

Dataset questions

What does one dataset item represent?

One store, product, product detail, store collection, or deal item, depending on the extraction toggles enabled.

Which field should I use as a unique identifier?

Use productId for products and storeId for stores; combine them with the resolved postal code for location-aware deduplication.

Are fields nullable or conditional?

Yes. description, price, rating, category, and imageUrl are conditional on the source, and store/collection records carry fields that product records do not.

Can I retrieve the records as CSV or JSON?

Yes. Export the default dataset as JSON, CSV, Excel, or XML, or read it through the Apify Dataset API.

How do I paginate large datasets?

Read items through the Dataset API in pages, or export the full dataset once the run completes.

What counts as a billable result?

Each record pushed to the dataset is one event charge, at the same per-event rate regardless of record type.

Related datasets from Data Scrapers

• Instacart Scraper — grocery and store data from Instacart, for the same competitive assortment and pricing analyses.
• Publix Scraper — grocery product records for price monitoring across delivery regions.
• OpenTable Scraper — restaurant records with availability for the food-service market.
• Yelp Scraper — business and rating records that join with DoorDash store identifiers.

Data Scrapers support

Need an additional field, record type, or export workflow? Contact Data Scrapers at stardustspotlight@gmail.com. Include a sample source URL, required fields, expected record volume, and preferred delivery format.