Airbnb Data Scraper for Apify

This project is an Apify actor designed to scrape detailed data from Airbnb listings, including SEO metadata, pricing details, and other key information. The actor supports dynamic date generation for flexible booking queries and stores the extracted data in an Apify dataset.

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Features

• Dynamic Date Generation: Automatically generates check-in and check-out dates based on user input.
• Comprehensive Data Extraction:
  • SEO Metadata: Title, meta description, canonical URL, and more.
  • Pricing Details: Breakdown of prices, including cleaning fee, service fee, and taxes.
  • Property Information: Room type, location, capacity, rating, and reviews.
• Error Handling: Gracefully handles API errors and continues processing other listings.
• Data Storage:
  • Outputs data to the Apify dataset.
  • Optionally saves data to a local CSV file for offline use.

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Input Parameters

The actor accepts the following input parameters:

Parameter	Description	Example Value
startUrls	List of Airbnb listing URLs to scrape.	[{"url": "https://www.airbnb.com/rooms/12345"}]
checkInDate	Starting date for check-in.	"2024-11-21"
Stay_Days	Duration of each stay in days.	1
numberOfDays	Total number of days to iterate.	10
adults	Number of adults for the booking.	2
children	Number of children for the booking.	0
pets	Indicates if pets are included.	0

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Output Data

The scraper outputs a dataset with detailed information for each listing and date range:

Field Name	Description
Check-In Date	Generated check-in date.
Check-Out Date	Generated check-out date.
Booking Available	Indicates if instant booking is available.
Title	SEO title of the listing.
Meta Description	SEO meta description of the listing.
Canonical URL	Canonical URL of the listing page.
Room Info	General description of the room.
Property Type	Type of property (e.g., apartment, house).
Room Rating	Star rating of the listing.
Total Reviews	Total number of reviews.
Location	Location of the listing.
Capacity	Maximum number of guests the property can accommodate.
Image URL	URL of the primary listing image.
Price Breakdown Title	Title of the price breakdown section.
Strike Through Price	Original price before discounts.
Primary Price	Current price after discounts.
Cleaning Fee	Cleaning fee for the booking.
Service Fee	Service fee for the booking.
Taxes	Tax amount for the booking.
Total Price	Total price for the stay, including fees and taxes.

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How It Works

1. Dynamic Date Generator:

   • Generates a sequence of check-in and check-out dates based on the input checkInDate, Stay_Days, and numberOfDays.

2. Data Extraction:

   • Makes a GraphQL API call to Airbnb using dynamically generated queries.
   • Extracts specific SEO and pricing details using a recursive function to traverse JSON paths.

3. Data Storage:

   • Stores data in the Apify dataset for further processing or integration.
   • Optionally saves the data to a local CSV file.

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Example Input

1{
2  "startUrls": [
3    { "url": "https://www.airbnb.com/rooms/12345" },
4    { "url": "https://www.airbnb.com/rooms/67890" }
5  ],
6  "checkInDate": "2024-11-21",
7  "Stay_Days": 1,
8  "numberOfDays": 5,
9  "adults": "2",
10  "children": "0",
11  "pets": "0"
12}

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Example Output

Check-In Date	Check-Out Date	Title	Total Price	Room Rating	Total Reviews
2024-11-21	2024-11-22	Cozy Apartment in City	$120	4.8	120
2024-11-22	2024-11-23	Spacious Condo by Beach	$200	4.9	85

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Logging and Debugging

The script uses Python's logging module to log:

• Progress of the scraping process.
• Errors encountered during API calls or data processing.

Logs are displayed in the console and can be used to debug issues.

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License

This project is licensed under the MIT License.