# Airbnb Search Scraper (`scrapecrafter/airbnb-search-scraper`) Actor

Extract Airbnb search listings plus daily price, review, rating, and target-room rank statistics.

- **URL**: https://apify.com/scrapecrafter/airbnb-search-scraper.md
- **Developed by:** [Debashish Biswas](https://apify.com/scrapecrafter) (community)
- **Security:** Limited permissions
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$1,000.00 / 1,000 airbnb search reports

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## Airbnb Search Scraper

Apify Actor for extracting Airbnb search listings and producing a daily report modeled on the legacy Airbnb parser supplied with this project.

### Daily report logic

For every **Check In** date from `startDate` through `endDate` (inclusive):

- `Weekday` = first three letters of the weekday (`Mon`, `Tue`, etc.).
- `Check In` = the current date in the range.
- `Checkout` is calculated internally as `Check In + Nights`.
- `Nights` = the user-selected number of nights.
- `Results` = Airbnb's total search-result count when exposed by the page; otherwise the number of parsed listings.
- `Search Pages` = the configured maximum number of search pages.
- `Search avg_Reviews` = average review count across the parsed listings, excluding listings without a review count.
- `Search avg_PriceD` = average list-page price across the parsed listings, using the legacy parser's denominator behavior.
- `CUR` = currency detected from the search listings.
- `Cal Price` = target room's calendar price for the current Check In date, when a Target Room ID is supplied and the room calendar is present in the room page payload.
- `Room Page` = search page where the target room was found.
- `Room Rank` = target room's sequential position across the collected search pages.
- `Room Price` = target room's price on the search result page.
- second `CUR` = currency of the target room price.
- `avg_Reviews_before` = average review count for listings before the target room.
- `avg_Price_before` = average price for listings before the target room.

The default Dataset output is intentionally limited to these report rows so the Apify Output table closely follows the supplied legacy report format.

Raw listing records are written to a run-scoped secondary dataset alias named `listings`.

### Input

- Search URL or Location
- Start date
- End date (inclusive)
- Nights
- Adults / children / infants / pets
- Search Pages
- Optional Target Room ID
- Maximum results per date
- Apify Proxy settings
- Concurrency, delay and retry settings

When a Search URL is supplied, its `checkin` and `checkout` values are overwritten for each daily search, and pagination parameters are updated for each Search Page.

### Important implementation note

The legacy PHP project contains old Airbnb cookies, API keys, persisted-query hashes and proxy-management code. This Actor does not copy those secrets. The parsing logic is ported from the supplied list-page JSON structure (`demandStayListing`, `structuredDisplayPrice`, `avgRatingLocalized`, coordinates and sequential rank) and the calendar parser's `calendarMonths` / `calendarDate` / `price.localPriceFormatted` concept.

Airbnb can change its page structure, so current-page compatibility must be validated with a live Actor run before publishing.

### Output format (v1.2)

The default dataset contains one report row per check-in date, in this exact order: Weekday, Check In, Nights, Results, Search Pages, Search avg_Reviews, Search avg_PriceD, CUR, Cal Price, Room Page, Room Rank, Room Price, CUR, avg_Reviews_before, avg_Price_before. Raw listing records are not pushed to the default dataset.

# Actor input Schema

## `searchUrl` (type: `string`):

Optional Airbnb search URL. If supplied, the Actor reuses it and updates check-in, check-out and pagination parameters.

## `location` (type: `string`):

Location to search when Search URL is not supplied.

## `startDate` (type: `string`):

First check-in date (inclusive), YYYY-MM-DD. The Actor creates one row/search for every date through End date.

## `endDate` (type: `string`):

Last check-in date (inclusive), YYYY-MM-DD. Checkout for each row is calculated as Check In + Nights.

## `nights` (type: `integer`):

Total nights selected by the user. For each row, Checkout = Check In + Nights.

## `adults` (type: `integer`):

Number of adults.

## `children` (type: `integer`):

Number of children.

## `infants` (type: `integer`):

Number of infants.

## `pets` (type: `integer`):

Number of pets.

## `searchPages` (type: `integer`):

Maximum number of Airbnb search-result pages used for every check-in/check-out combination.

## `roomId` (type: `string`):

Optional target Airbnb listing ID. When found, the Actor reports its page, rank, list-page price, and averages of listings before it. The Actor also attempts to read its calendar price for each check-in date.

## `roomMaxPages` (type: `integer`):

Maximum search pages used when a target Room ID is supplied. The legacy logic can use max(Room max pages, Search pages) when the target room is relevant for the date.

## `maxResults` (type: `integer`):

Maximum listings retained for each check-in date. Use 0 for no explicit limit.

## `deduplicate` (type: `boolean`):

Keep one occurrence of each listing per check-in date.

## `proxySettings` (type: `object`):

Apify Proxy configuration used for Airbnb requests.

## `maxConcurrency` (type: `integer`):

Maximum simultaneous Airbnb search-page requests.

## `requestDelayMs` (type: `integer`):

Delay before each request in milliseconds.

## `maxRetries` (type: `integer`):

Maximum retries after a failed request.

## Actor input object example

```json
{
  "location": "Cologne, Germany",
  "startDate": "2026-09-19",
  "endDate": "2026-09-20",
  "nights": 2,
  "adults": 2,
  "children": 0,
  "infants": 0,
  "pets": 0,
  "searchPages": 3,
  "roomMaxPages": 10,
  "maxResults": 0,
  "deduplicate": true,
  "maxConcurrency": 2,
  "requestDelayMs": 1000,
  "maxRetries": 2
}
```

# Actor output Schema

## `results` (type: `string`):

No description

## `runSummary` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("scrapecrafter/airbnb-search-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("scrapecrafter/airbnb-search-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call scrapecrafter/airbnb-search-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,scrapecrafter/airbnb-search-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/r7BV6lDNYZsh3Vfrz/builds/ZWl2TTjv8zel0J87P/openapi.json