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TripAdvisor Reviews Scraper
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TripAdvisor Reviews Scraper

TripAdvisor Reviews Scraper

epctex/tripadvisor-reviews-scraper
Try for free

1 day trial then $15.00/month - No credit card required now

Gather any feedback, ratings, and comments on TripAdvisor. Ideal for market analysts, hospitality businesses, content creators, and researchers, this tool offers an easy way to collect and analyze traveler reviews. Streamline your research with quick, reliable, and user-friendly data extraction.

The code examples below show how to run the Actor and get its results. To run the code, you need to have an Apify account. Replace <YOUR_API_TOKEN> in the code with your API token, which you can find under Settings > Integrations in Apify Console. Learn more

1from apify_client import ApifyClient
2
3# Initialize the ApifyClient with your Apify API token
4client = ApifyClient("<YOUR_API_TOKEN>")
5
6# Prepare the Actor input
7run_input = {
8    "startUrls": [
9        "https://www.tripadvisor.com/Restaurant_Review-g60763-d25324283-Reviews-Allora_Fifth_Ave-New_York_City_New_York.html",
10        "https://www.tripadvisor.com/Hotel_Review-g60763-d15288822-Reviews-SpringHill_Suites_New_York_Manhattan_Times_Square_South-New_York_City_New_York.html?spAttributionToken=MjMyMTAzMzg",
11    ],
12    "languages": ["all"],
13    "ratings": ["all"],
14    "maxItems": 20,
15    "endPage": 1,
16    "customMapFunction": "(object) => { return {...object} }",
17    "proxy": { "useApifyProxy": True },
18}
19
20# Run the Actor and wait for it to finish
21run = client.actor("epctex/tripadvisor-reviews-scraper").call(run_input=run_input)
22
23# Fetch and print Actor results from the run's dataset (if there are any)
24print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
25for item in client.dataset(run["defaultDatasetId"]).iterate_items():
26    print(item)
27
28# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
Developer
Maintained by Community
Actor metrics
  • 23 monthly users
  • 2 stars
  • 99.4% runs succeeded
  • 3.7 hours response time
  • Created in Feb 2024
  • Modified 2 days ago