Collectors · Local & Maps

DoorDash Scraper API in Python

Restaurants delivering in a US city — rating, exact review count, cuisine, address. One POST from Python with location, rows back as JSON with 25 fields, $0.003 per delivered restaurant. No proxies or parsers to maintain.

Get an API key See the collector

A Python requests snippet that posts { — A Python requests call to the doordash_restaurants collector returns one dict per restaurant, at $0.003 each.

First call

Install, call, read the rows.

pip install requests

The only dependency.

import os, requests

r = requests.post(
    "https://api.quanticdata.io/v1/scraper/collectors/doordash_restaurants/run",
    headers={"Authorization": f"Bearer {os.environ['QD_API_KEY']}"},
    json={
        "location": "Austin, TX",
        "max_results": 50,
    },
    timeout=120,
)
r.raise_for_status()
run = r.json()["payload"]
print(run["count"], "rows,", run["cost"]["usd"], "USD")
for row in run["results"]:
    print(row.get("id"), row.get("name"), row.get("rating"), row.get("reviews"))

Python: one DoorDash restaurants run (Austin), printing id, name, rating, reviews

The key comes from an environment variable, never from the code. The run answers in the same request when it finishes in time; payload.results holds the rows and payload.cost what they cost.

Request parameters

What the collector takes.

Input of the DoorDash restaurants collector
Parameter	Type	Required	Meaning
`location`	string	yes	US city and state, e.g. "Austin, TX".
`cuisine`	string	no	Narrow to one cuisine, e.g. "mexican" or "sushi". Each cuisine is its own full page, so this is how you collect more than one page's worth for a city.
`country`	string	no	ISO 3166-1 alpha-2 code — proxy exit geo and Google locale (gl). Omit for the default pool.
`max_results`	integer	no (default 50)	How many restaurants to deliver at most (1–50). You pay only for delivered restaurants.

Response fields

25 fields per restaurant.

Fields of each row (restaurant)
Field	Type	What it holds
`rank`	integer	Position in DoorDash's order for this city.
`id`	string, nullable	DoorDash store id.
`name`	string	Restaurant name.
`rating`	number, nullable	Average rating out of 5. Null on stores with too few ratings.
`reviews`	integer, nullable	Exact review count — the rendered page only shows it rounded.
`cuisine`	string, nullable	Primary cuisine.
`price_range`	string, nullable	Price band ($ to $$$$).
`street`	string, nullable	Street address.
`city`	string, nullable	City.
`state`	string, nullable	State code.
`postal_code`	string, nullable	ZIP code.
`country`	string, nullable	Country.
`image`	string, nullable	Store photo URL.
`url`	string, nullable	Store page URL.
`address`	string, nullable	Full address on one line as DoorDash prints it, ZIP included.
`latitude`	number, nullable	Store latitude.
`longitude`	number, nullable	Store longitude.
`categories`	string[], nullable	Every cuisine/category tag on the store; `cuisine` is the primary one.
`delivery_fee`	string, nullable	Delivery fee as displayed, e.g. "$0 delivery fee".
`distance`	string, nullable	Distance from the city centre the page is built around, as displayed ("0.5 mi", "800 ft").
`eta_minutes`	integer, nullable	Estimated delivery time in minutes when DoorDash shows one.
`promotions`	string[], nullable	Promotion and highlight tags on the card, e.g. "$5 off on $35+", "Newly Added".
`popular_items`	object[], nullable	Up to 8 popular menu items: name, description, price, currency, image.
`offers_pickup`	boolean, nullable	True when the store offers pickup.
`sponsored`	boolean, nullable	True when the card is a sponsored placement.

Add ?format=csv to the runs endpoint to get the same rows as CSV.

Long runs

Run in the background, then poll.

A run that needs more time can go to the background: send "async": true, get 202 with the run id, and poll the runs endpoint until the status is done. Reading a run is free.

import os, time, requests

H = {"Authorization": f"Bearer {os.environ['QD_API_KEY']}"}
r = requests.post("https://api.quanticdata.io/v1/scraper/collectors/doordash_restaurants/run", headers=H,
                  json={**{"location":"Austin, TX","max_results":50}, "async": True}, timeout=30)
run_id = r.json()["payload"]["run_id"]
while True:
    run = requests.get(f"https://api.quanticdata.io/v1/scraper/collectors/runs/{run_id}", headers=H, timeout=30).json()["payload"]
    if run["status"] in ("done", "failed"):
        break
    time.sleep(5)
print(run["status"], run["count"])

Python: background run and polling

Errors

What can come back, and what is billed.

Collector run errors
Status	Meaning	Billed
`400`	The input does not match the collector (`payload.errors`)	No
`401`	Missing or wrong API key	No
`402`	Balance and free credit do not cover the run: top up	No
`422`	The input can never resolve; retrying the same input cannot help	No
`424`	The run failed at the source (blocked, timed out, layout changed); safe to retry	No
`429`	Rate limit or a per-account brake; wait for `Retry-After`	No

Only delivered rows are billed: a run that delivers nothing costs nothing.

Price

$0.003 per delivered restaurant.

What DoorDash restaurants rows cost at list price
Rows	Cost
1	$0.003
1,000	$3.00
10,000	$30.00

Up to 50 restaurants per run; split larger jobs into several runs. The $2 free credit every month covers about 666 restaurants. No subscription; paid tiers lower the unit price. All collector prices: collector pricing.

Before you run it

Questions developers ask

Is there a free DoorDash restaurants API?

Every account gets $2 of free usage each month, about 666 restaurants of this collector at $0.003 each, with no card.

Do I have to handle proxies, retries or blocks?

No. The collector runs on our network and handles them; a run blocked at the source returns 424 and is not billed.

How many rows can one run return?

Up to 50 restaurants per run (the max_results input, where the collector has one).

Can an AI agent run it?

Yes: the MCP server exposes it as the run_collector tool, with the same input and price. See the MCP server.

Run it on the free credit.

Create an API key, export it as QD_API_KEY and run the example. $0.003 per delivered restaurant, no subscription.

Get an API key DoorDash Scraper API