Food delivery platforms protect their pricing data with CAPTCHAs and bot detection. Price comparison services, market researchers, and restaurant analytics tools need automated access to compare menu prices, delivery fees, and promotions across DoorDash, Uber Eats, Grubhub, and other platforms.
CAPTCHAs on Delivery Platforms
| Platform | CAPTCHA Type | Trigger | Protected Data |
|---|---|---|---|
| DoorDash | reCAPTCHA v3 + Cloudflare | Bot detection | Menus, prices, fees |
| Uber Eats | Cloudflare Turnstile | Automated access | Restaurant listings, prices |
| Grubhub | reCAPTCHA v2 | Rate limiting | Menu items, promotions |
| Postmates | Cloudflare Challenge | Scraping detection | Delivery fees, ETAs |
| Just Eat | reCAPTCHA v2 | Repeated searches | Restaurant data |
| Instacart | reCAPTCHA v3 | Bot detection | Grocery prices |
Multi-Platform Price Comparator
import requests
import time
import re
from bs4 import BeautifulSoup
import json
CAPTCHAAI_KEY = "YOUR_API_KEY"
CAPTCHAAI_URL = "https://ocr.captchaai.com"
def solve_captcha(method, sitekey, pageurl, **kwargs):
data = {
"key": CAPTCHAAI_KEY, "method": method,
"googlekey": sitekey, "pageurl": pageurl, "json": 1,
}
data.update(kwargs)
resp = requests.post(f"{CAPTCHAAI_URL}/in.php", data=data)
task_id = resp.json()["request"]
for _ in range(60):
time.sleep(5)
result = requests.get(f"{CAPTCHAAI_URL}/res.php", params={
"key": CAPTCHAAI_KEY, "action": "get",
"id": task_id, "json": 1,
})
r = result.json()
if r["request"] != "CAPCHA_NOT_READY":
return r["request"]
raise TimeoutError("Timeout")
class FoodDeliveryComparator:
def __init__(self, proxy=None):
self.session = requests.Session()
if proxy:
self.session.proxies = {"http": proxy, "https": proxy}
self.session.headers.update({
"User-Agent": "Mozilla/5.0 (iPhone; CPU iPhone OS 17_5 like Mac OS X) "
"AppleWebKit/605.1.15 (KHTML, like Gecko) Version/17.5 "
"Mobile/15E148 Safari/604.1",
"Accept-Language": "en-US,en;q=0.9",
})
def search_restaurants(self, platform_url, location, cuisine=None):
"""Search restaurants on a delivery platform."""
params = {"address": location}
if cuisine:
params["cuisine"] = cuisine
url = f"{platform_url}/search"
resp = self.session.get(url, params=params, timeout=30)
if self._has_captcha(resp.text):
resp = self._solve_and_retry(resp.text, url)
return self._parse_restaurants(resp.text)
def get_menu(self, restaurant_url):
"""Get menu with prices from a specific restaurant."""
resp = self.session.get(restaurant_url, timeout=30)
if self._has_captcha(resp.text):
resp = self._solve_and_retry(resp.text, restaurant_url)
return self._parse_menu(resp.text)
def compare_restaurant_across_platforms(self, restaurant_name, platforms, location):
"""Compare same restaurant's pricing across delivery platforms."""
results = []
for platform in platforms:
try:
restaurants = self.search_restaurants(
platform["url"], location,
)
# Find matching restaurant
match = None
for r in restaurants:
if restaurant_name.lower() in r["name"].lower():
match = r
break
if match and match.get("url"):
menu = self.get_menu(match["url"])
results.append({
"platform": platform["name"],
"restaurant": match["name"],
"delivery_fee": match.get("delivery_fee", ""),
"delivery_time": match.get("delivery_time", ""),
"menu_items": len(menu),
"sample_prices": menu[:5],
})
else:
results.append({
"platform": platform["name"],
"restaurant": restaurant_name,
"status": "not found",
})
except Exception as e:
results.append({
"platform": platform["name"],
"error": str(e),
})
time.sleep(5)
return results
def track_delivery_fees(self, platforms, location, output_file):
"""Track delivery fees across platforms for analysis."""
all_data = []
for platform in platforms:
try:
restaurants = self.search_restaurants(
platform["url"], location,
)
for r in restaurants[:20]: # Top 20 per platform
all_data.append({
"platform": platform["name"],
"restaurant": r["name"],
"delivery_fee": r.get("delivery_fee", ""),
"delivery_time": r.get("delivery_time", ""),
"rating": r.get("rating", ""),
})
time.sleep(5)
except Exception as e:
print(f"Error on {platform['name']}: {e}")
with open(output_file, "w") as f:
json.dump(all_data, f, indent=2)
return all_data
def _has_captcha(self, html):
return any(tag in html.lower() for tag in [
'data-sitekey', 'g-recaptcha', 'cf-turnstile',
'challenge-platform',
])
def _solve_and_retry(self, html, url):
match = re.search(r'data-sitekey="([^"]+)"', html)
if not match:
return self.session.get(url)
sitekey = match.group(1)
if 'cf-turnstile' in html:
token = solve_captcha("turnstile", sitekey, url)
return self.session.post(url, data={"cf-turnstile-response": token})
token = solve_captcha("userrecaptcha", sitekey, url)
return self.session.post(url, data={"g-recaptcha-response": token})
def _parse_restaurants(self, html):
soup = BeautifulSoup(html, "html.parser")
restaurants = []
for card in soup.select(".restaurant-card, .store-card, .merchant"):
name_el = card.select_one(".name, .store-name, h3")
if name_el:
restaurants.append({
"name": name_el.get_text(strip=True),
"url": self._link(card),
"delivery_fee": self._text(card, ".delivery-fee, .fee"),
"delivery_time": self._text(card, ".delivery-time, .eta"),
"rating": self._text(card, ".rating, .stars"),
})
return restaurants
def _parse_menu(self, html):
soup = BeautifulSoup(html, "html.parser")
items = []
for item in soup.select(".menu-item, .item-card"):
items.append({
"name": self._text(item, ".item-name, .name"),
"price": self._text(item, ".price, .item-price"),
"description": self._text(item, ".description, .item-desc"),
})
return items
def _text(self, el, selector):
found = el.select_one(selector)
return found.get_text(strip=True) if found else ""
def _link(self, card):
a = card.select_one("a")
return a.get("href", "") if a else ""
# Usage
comparator = FoodDeliveryComparator(
proxy="http://user:pass@mobile.proxy.com:5000"
)
# Compare platforms
platforms = [
{"name": "Platform A", "url": "https://delivery-a.example.com"},
{"name": "Platform B", "url": "https://delivery-b.example.com"},
{"name": "Platform C", "url": "https://delivery-c.example.com"},
]
comparison = comparator.compare_restaurant_across_platforms(
restaurant_name="Pizza Palace",
platforms=platforms,
location="10001",
)
for result in comparison:
print(f"{result.get('platform')}: Fee={result.get('delivery_fee')} "
f"ETA={result.get('delivery_time')}")
Proxy Recommendations
| Platform | Best Proxy | Why |
|---|---|---|
| DoorDash | Mobile (4G) | Heavy bot detection, expects mobile |
| Uber Eats | Mobile (4G) | Mobile-first platform |
| Grubhub | Residential | Standard protection |
| Instacart | Residential | Moderate bot detection |
| Just Eat | Rotating residential | Standard Cloudflare |
Delivery apps are mobile-first — mobile proxies with mobile User-Agents produce the best results.
Data Points to Track
| Metric | Business Value |
|---|---|
| Menu item prices | Price parity and markup analysis |
| Delivery fees | Platform fee comparison |
| Minimum order amounts | Access barrier analysis |
| Delivery time estimates | Service level comparison |
| Promotions/discounts | Marketing intelligence |
| Restaurant availability | Coverage analysis |
Troubleshooting
| Issue | Cause | Fix |
|---|---|---|
| Empty restaurant results | Location not served or CAPTCHA page | Set correct delivery address zip |
| Menu prices different from app | Web vs app pricing discrepancy | Use mobile UA to get app-equivalent pricing |
| Cloudflare challenge loop | Fingerprint mismatch | Use mobile proxy + mobile UA |
| Restaurant found on one platform but not another | Different coverage | Mark as "not available" in comparison |
| Incorrect delivery fees | Location-dependent pricing | Match proxy geo to target location |
FAQ
Why are prices different across delivery platforms?
Restaurants set different prices per platform to account for varying commission rates (15-30%). Delivery fees and service charges also vary by platform.
Should I use mobile or desktop for scraping delivery apps?
Mobile — these are mobile-first platforms. A mobile proxy with iPhone/Android User-Agent produces the most authentic-looking traffic.
How often should I compare prices?
Weekly for general market analysis. Daily during promotional periods or competitive research sprints.
Related Guides
Compare food delivery prices at scale — get your CaptchaAI key and automate cross-platform analysis.
Discussions (0)
Join the conversation
Sign in to share your opinion.
Sign InNo comments yet.