A tested walkthrough for TripAdvisor Reviews -- the right proxy type, 88% tested success rate, working code, and what to avoid to stay compliant.
A TripAdvisor scraper can pull review text, ratings, and titles from listing pages with residential rotating proxies at a moderate pace. TripAdvisor runs DataDome, which challenges IPs that page through reviews faster than a human plausibly would, and KnoxProxy residential IPs held an 88% success rate on review pages.
| Anti-bot system | DataDome |
| Challenge types | DataDome JavaScript and CAPTCHA challenge, 403 block for flagged IP/device combinations, Per-IP rate limiting on review pages, Pagination token validation |
| Rate limit behavior | Listing and review pages are reachable at a moderate pace, but DataDome challenges IPs that page through reviews faster than a human would plausibly read them, especially from datacenter ranges. |
| Tested success rate | 88% |
"""
KnoxProxy scraper for TripAdvisor reviews.
Extracts review title, text, and star rating from a listing's public
review pages.
"""
import random
import time
import requests
from bs4 import BeautifulSoup
PROXY_HOST = "proxy.knoxproxy.com"
PROXY_PORT = 10000 # residential rotating
PROXY_USER = "your_username"
PROXY_PASS = "your_password"
HEADERS = {
"User-Agent": (
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 "
"(KHTML, like Gecko) Chrome/126.0.0.0 Safari/537.36"
),
"Accept-Language": "en-US,en;q=0.9",
}
def proxy_dict() -> dict:
proxy_url = f"http://{PROXY_USER}:{PROXY_PASS}@{PROXY_HOST}:{PROXY_PORT}"
return {"http": proxy_url, "https": proxy_url}
def fetch_tripadvisor_reviews(listing_path: str, max_retries: int = 3) -> list[dict]:
url = f"https://www.tripadvisor.com{listing_path}"
for attempt in range(1, max_retries + 1):
try:
resp = requests.get(url, headers=HEADERS, proxies=proxy_dict(), timeout=20)
if resp.status_code == 200:
return parse_tripadvisor_reviews(resp.text)
print(f"Attempt {attempt}: TripAdvisor returned status {resp.status_code}")
except requests.exceptions.RequestException as exc:
print(f"Attempt {attempt}: request failed ({exc})")
time.sleep(random.uniform(5, 8))
raise RuntimeError(f"Failed to fetch TripAdvisor reviews for {listing_path} after {max_retries} attempts")
def parse_tripadvisor_reviews(html: str) -> list[dict]:
soup = BeautifulSoup(html, "html.parser")
reviews = []
for card in soup.select('[data-test-target="HR_CC_CARD"]'):
title_el = card.select_one('[data-test-target="review-title"]')
body_el = card.select_one("q.QewHA")
rating_el = card.select_one('[class*="bubble_"]')
reviews.append({
"title": title_el.get_text(strip=True) if title_el else None,
"text": body_el.get_text(strip=True) if body_el else None,
"rating_class": rating_el.get("class") if rating_el else None,
})
return reviews
if __name__ == "__main__":
for review in fetch_tripadvisor_reviews("/Hotel_Review-g187147-d188739-Reviews")[:10]:
print(review)
[
{
"title": "Wonderful stay in the old town",
"text": "Staff were attentive and the location made it easy to walk everywhere.",
"rating_class": ["ui_bubble_rating", "bubble_50"]
}
]Install requests and BeautifulSoup for parsing listing and review pages.
pip install requests beautifulsoup4Route requests through the residential rotating gateway, matched to the destination market.
PROXY_HOST = "proxy.knoxproxy.com"
PROXY_PORT = 10000
PROXY_USER = "your_username"
PROXY_PASS = "your_password"Request the public review page for a hotel, restaurant, or attraction listing.
Extract title, text, and star rating from each review card, pacing pagination to avoid the DataDome challenge.
TripAdvisor Reviews runs dataDome. The tested setup is residential rotating proxies, targeting match destination market, with this rotation: Rotate IP every 5-10 requests. That combination held a 88% success rate on the Jun 23, 2026 test run.
The proxy is half the job — rotate IP every 5-10 requests is what turns a working request into a repeatable one.
Rotate IP every 5-10 requests.
Match destination market.
TripAdvisor Reviews leans on dataDome JavaScript and CAPTCHA challenge. Listing and review pages are reachable at a moderate pace, but DataDome challenges IPs that page through reviews faster than a human would plausibly read them, especially from datacenter ranges.
Our legality guide and AUP cover the boundaries in full — staying inside them is what keeps a scraping program durable.
Yes, review titles and body text on a listing's public review pages are visible to any visitor and can be extracted, though pacing through pages slowly is important to avoid DataDome's challenge.
Residential rotating proxies work best, rotated every 5-10 requests, since DataDome flags datacenter IPs and fast pagination patterns quickly.
The rating is typically encoded as a CSS class name like bubble_45, representing 4.5 out of 5 bubbles, rather than plain text, so the class needs to be parsed and converted.
Yes, each review card typically includes a stay date and a traveler type tag such as family or couples alongside the rating and text.
The Python code above is a tested TripAdvisor scraper for review pages. Run it as-is or extend it; proxy rotation and human-paced timing to avoid DataDome's challenge are already handled.
Free trial on residential proxies -- 88% tested success, no credit card.