How to Scrape DoorDash, Uber Eats, and Grubhub Menu Data in 2026

How to Scrape DoorDash, Uber Eats, and Grubhub Menu Data in 2026 Food delivery platforms are among the harder scraping targets — they use aggressive anti-bot measures, require location parameters, and structure their data differently across platforms. Here's what actually works for extracting menu data, restaurant listings, and pricing. DoorDash: Menu Data Extraction DoorDash embeds menu data in the page's server-side rendered HTML as a JSON blob. This is the cleanest approach — no API authentication needed: import requests, re, json from curl_cffi import requests as cf_requests def scrape_doordash_menu(store_url: str) -> dict: """ Extract menu data from a DoorDash restaurant page. URL format: https://www.doordash.com/store/restaurant-name-city-12345/ """ session = cf_requests.Session() headers = { "User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/124.0.0.0 Safari/537.36", "Accept": "text/html,application/xhtml+xml,applicati