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Tripadvisor Scraper helps you scrape Tripadvisor Hotels and Restaurants. 🚀

⚡ Benefits

  1. Easily access Tripadvisor Hotels and Restaurants through our user-friendly dashboard.

  2. Get 101% accurate, fresh results in realtime, allowing you to use the results to their full potential.

  3. Get Website, Email, Phone, Address, and other details of Hotels and Restaurants.

To use this tool, you'll need:

  • Node.js version 16 or later to run the UI Dashboard (please check your Node.js version by running node -v)
  • Python for running the scraper

Don't have Node.js or Python? No problem!

You can easily run this tool within Gitpod, a cloud-based development environment, by following these steps

🚀 Getting Started

Let's get started by following these super simple steps:

1️⃣ Clone the Magic 🧙‍♀️:

git clone https://github.com/magiccoder815/tripadvisor_scraping.git
cd tripadvisor_scraping

2️⃣ Install Dependencies 📦:

python -m pip install -r requirements.txt
python run.py install

3️⃣ Launch the UI Dashboard 🚀:

python run.py

4️⃣ Open your browser and go to http://localhost:3000, then press the Run button to see Tripadvisor Products. 😎

Tripadvisor Result

⚡ Enlightening Questions

❓ How to Get Results for My Queries?

  1. Visit http://localhost:3000 and enter your queries

Queries

  1. Now, simply press the Run button.

Run

❓ What Data Points Are Scraped?

We scrape over 45+ data points, important among them are:

  • Name
  • Reviews
  • Rating
  • Website
  • Email
  • Phone
  • Address
  • And many more...

❓ How to Scrape More Hotels and Restaurants?

Kindly follow these steps to use our Rapid API and easily get the tripadvisor product details:

  1. Sign up on RapidAPI by visiting this link.

  2. Subscribe to the Free Plan by visiting this link.

Subscribe to Free Plan

  1. Copy the API key. Copy the API Key

  2. Put the Key in the "Rapid API Key" textbox and simply run it:

api-key

The first 200 requests are free with the API. After that, you can upgrade to the Pro Plan to scrape 10000 listings for $16, which is a really great price, considering that the data is 101% accurate, fresh, and comprehensive with 45+ fields.