Airbnb Scraper

A fast, no-code tool for extracting Airbnb listing data — including host details, pricing, location, and reviews — without any API restrictions. Ideal for researchers, developers, and analysts who need clean, structured Airbnb data at scale.

This Airbnb scraper simplifies how you gather vacation rental insights by turning Airbnb search results into a ready-to-use dataset.

     

Created by Bitbash, built to showcase our approach to Scraping and Automation!
If you are looking for Airbnb Scraper you've just found your team — Let’s Chat. 👆👆

Introduction

The Airbnb Scraper helps users collect listing data for specific cities or destinations. It removes the hassle of manual data collection by automating searches, filtering options, and extracting detailed property and host information.

Why Use This Scraper

• Get complete Airbnb listings from any destination.
• Collect detailed pricing, rating, and location data.
• Filter results by price range, stay duration, and amenities.
• Export in JSON, CSV, XML, RSS, or HTML formats.
• Automate recurring data collection or integrate with cloud services.

Features

Feature	Description
Location-Based Extraction	Retrieve Airbnb listings from any city or region.
Custom Filters	Set check-in/out dates, price range, and guest count.
Host and Property Details	Extract host names, ratings, and property types.
Amenities Mapping	Capture all listed amenities with icons and availability.
Data Export Options	Download results in JSON, CSV, XML, or HTML formats.
Cost Efficiency	Pay only for successfully retrieved results.
Integration Ready	Connect results to tools like Google Sheets or Slack.

---

What Data This Scraper Extracts

Field Name	Field Description
id	Unique identifier of the Airbnb listing.
coordinates	Latitude and longitude of the property.
title	Full title of the Airbnb listing.
description	Summary of the accommodation and features.
url	Direct Airbnb link to the listing.
rating	Guest review metrics across multiple criteria.
host	Host information including name, profile, and experience.
amenities	Grouped amenities with availability status.
price	Detailed pricing breakdown per night and total.
locationDescriptions	Additional neighborhood and transport info.

---

Example Output

[
  {
    "id": "14926879",
    "coordinates": {
      "latitude": 51.5101,
      "longitude": -0.1949
    },
    "title": "Terrific Notting Hill Studio - Apartments for Rent in London, England, United Kingdom - Airbnb",
    "url": "https://www.airbnb.com/rooms/14926879",
    "roomType": "Entire home/apt",
    "isSuperHost": false,
    "personCapacity": 1,
    "rating": {
      "accuracy": 4.76,
      "cleanliness": 4.77,
      "communication": 4.84,
      "location": 4.95,
      "value": 4.58,
      "reviewsCount": 371
    },
    "host": {
      "name": "Max And Billie",
      "profileImage": "https://a0.muscache.com/im/pictures/user/ddc3b1ab-e2d5-4953-8295-bbefa7a5e808.jpg",
      "highlights": ["8 years hosting"]
    },
    "price": {
      "label": "$107 per night",
      "totalBeforeTaxes": "$302"
    },
    "amenities": ["Wifi", "Heating", "Washer", "TV with cable", "Kitchen"],
    "locationDescriptions": [
      {
        "title": "Neighborhood highlights",
        "content": "Located near Notting Hill, close to parks, bars, and restaurants."
      }
    ]
  }
]

---

Directory Structure Tree

airbnb-scraper/
├── src/
│   ├── main.py
│   ├── extractors/
│   │   ├── listing_parser.py
│   │   └── amenities_mapper.py
│   ├── outputs/
│   │   └── export_manager.py
│   └── config/
│       └── settings.example.json
├── data/
│   ├── inputs.sample.json
│   └── listings.sample.json
├── requirements.txt
└── README.md

---

Use Cases

• Market researchers use it to gather pricing and occupancy data to compare rental trends across cities.
• Real estate analysts leverage it for understanding neighborhood-level rental values and host density.
• Travel startups integrate it into dashboards for competitive accommodation insights.
• Data scientists collect structured Airbnb data for predictive modeling or pricing algorithms.
• Hospitality consultants analyze reviews to benchmark quality and customer satisfaction.

---

FAQs

How many results can I scrape per query? You can retrieve up to 240 listings per location query, depending on search parameters and data variability.

What formats can I download the data in? Data can be exported in JSON, CSV, XML, RSS, or HTML Table formats.

Does it require any coding? No — it’s fully automated and doesn’t require programming knowledge.

Is there a cost per use? Yes, it follows a pay-per-result model — approximately $1.25 per 1,000 successful results.

---

Performance Benchmarks and Results

Primary Metric: Processes up to 240 Airbnb listings per query within 2–3 minutes. Reliability Metric: Maintains over 95% success rate in data extraction. Efficiency Metric: Uses lightweight queries optimized for minimal resource consumption. Quality Metric: Delivers 98% field completeness and accurate mapping for price, host, and amenities data.

“Bitbash is a top-tier automation partner, innovative, reliable, and dedicated to delivering real results every time.” Nathan Pennington Marketer ★★★★★

“Bitbash delivers outstanding quality, speed, and professionalism, truly a team you can rely on.” Eliza SEO Affiliate Expert ★★★★★

“Exceptional results, clear communication, and flawless delivery. Bitbash nailed it.” Syed Digital Strategist ★★★★★