# Skyscanner Scraper — Flight Prices & Destinations (`thenetaji/skyscanner-scraper`) Actor

Both Skyscanner fare datasets behind one mode picker: prices for a city pair, or the cheapest flights into a place from anywhere. Each row is a whole page — quoted deals with carriers and dates, twelve months of prices, nearby airports, airlines and route Q\&A.

- **URL**: https://apify.com/thenetaji/skyscanner-scraper.md
- **Developed by:** [The Netaji](https://apify.com/thenetaji) (community)
- **Categories:** Travel, Automation, Lead generation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $8.50 / 1,000 page priceds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

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

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Skyscanner Scraper

Both Skyscanner fare datasets behind one mode picker. Pick `routeFares` to price a city pair,
or `destinationFares` for the cheapest flights into a place from anywhere. Either way a row is
a whole page: the headline fare and its currency, every quoted deal with legs, carriers, dates
and the moment each fare was quoted, twelve months of cheapest-by-month, the airports serving
the destination, the airlines flying it, the page's own Q\&A, and fifteen route facts from the
cheapest month to the destination's wettest.

The two modes cost the same because they *are* the same amount of work — one page read, one
row, no pagination on either surface. That is the whole reason they sit in one Actor rather
than being sold as one product with an asterisk.

### Accepted input

`scraperType` picks the mode and is required.

**`routeFares`** reads `routes` — city pairs, one per line, written as the code to fly from and
the code to fly to:

```
lond-nyca
```

`lond/nyca`, `lond nyca` and a pasted route page link all work too.

**`destinationFares`** reads `places` — place codes, one per line, such as `nyca` or `lax`, or
pasted destination page links.

**A place code is two to four characters, and a place name is not a place code.** `lond` is
London, `nyca` is New York; `lhr`, `sfo` and `lax` are airports. `london` is refused before any
request is made, by name, with real codes in the message — there is no place-name lookup on this
site, and a name sent anyway returns a page that does not exist, which reads as "Skyscanner has
no London" rather than "that was the wrong kind of value".

Codes come from results. Every row publishes `origin_code` and `destination_code`, every deal
names its own places, every leg names its airports and every nearby airport carries a code — all
of them valid inputs to either mode.

`maxItems` caps how many pages a run reads and defaults to `100`. One page is one row and one
request. Set `0` for no limit.

```json
{
  "scraperType": "routeFares",
  "routes": ["lond-nyca", "lhr-jfk"],
  "maxItems": 10
}
```

### Response fields

One row per page read. This is the row that exact run produced for `lond-nyca`, with the long
lists shortened:

```json
{
  "requested_origin": "lond",
  "requested_destination": "nyca",
  "url": "https://www.skyscanner.net/routes/lond/nyca",
  "origin_code": "LOND",
  "origin_name": "London",
  "origin_country": "United Kingdom",
  "destination_code": "NYCA",
  "destination_name": "New York",
  "destination_country": null,
  "title": "£146 Cheap Flights from London (LOND) to New York (NYCA) | Skyscanner",
  "cheapest_price": 146,
  "currency": "GBP",
  "deals_count": 16,
  "deals": [
    {
      "id": "{bl}:202608211200*I*SEN*EWR*20261205*skyp*EZY",
      "price": 188,
      "formatted_price": "£188",
      "direct": false,
      "legs": [
        {
          "date": "2026-12-05",
          "quoted_at": "2026-08-21T12:00Z",
          "origin": { "sky_code": "SEN", "name": "London Southend" },
          "destination": { "sky_code": "EWR", "name": "New York Newark" },
          "carrier_name": "easyJet",
          "carrier_code": "EZY"
        }
      ]
    }
  ],
  "cheapest_by_month": [
    { "month": "2026-09", "month_name": "September", "price": 227, "formatted_price": "£227" },
    { "month": "2026-10", "month_name": "October", "price": 226, "formatted_price": "£226" }
  ],
  "nearby_airports": [
    {
      "airport_name": "New York Newark",
      "sky_code": "EWR",
      "distance": 9,
      "formatted_price": "£188",
      "carrier_name": "easyJet",
      "is_cheapest": true,
      "is_closest": false
    }
  ],
  "faqs": [
    {
      "question": "How many airports are there in New York?",
      "answer": "There are 6 airports in New York: New York LaGuardia, New York Newark, New York John F. Kennedy, Westchester County, Islip, and Stewart International."
    }
  ],
  "cheapest_month": "October",
  "most_expensive_month": "August",
  "cheapest_airline": "Ryanair",
  "most_popular_airline": "British Airways",
  "average_flight_time": "8 hours",
  "warmest_month": "July",
  "wettest_month": "August"
}
```

The full row carries all 16 deals, 12 months, 6 nearby airports, 26 direct airlines, 6 popular
airlines, 13 FAQs and all fifteen route facts.

The two modes fill different identity columns and share everything else. A route row carries
`requested_origin`, `requested_destination` and the origin columns; a destination row carries
`requested_place` and no origin at all, because that page prices fares *into* a place and each
deal names its own origin instead.

**These are cached quotes, not a live search.** Every leg states its own `quoted_at` — the fare
above was quoted two days before the run.

`currency` is stated on every row and is not the caller's. This storefront serves one currency
regardless of where a request comes from.

`requested_origin` and `origin_code` are both published because they are not always equal:
Skyscanner canonicalises an airport to its city, so a run that asks for `lhr` gets a page whose
origin is `LOND`. The run log says so when it happens.

### Behaviour on partial results

A pair or place with no page of its own is logged and skipped, and the run continues with the
next one. A page that exists but quotes nothing comes back as a normal row with an empty
`deals` list and `deals_count` of 0, counted from what arrived rather than copied off the page.

A value that is a place name rather than a code stops the run before any request is made.

On `destinationFares`, the run log states how many distinct origins the deals actually came
from. That matters: on one measured destination page, all sixteen deals departed from the same
city. "From anywhere" means the page picks an origin, not that it surveys the world.

### Frequently asked questions

**Which mode should I pick?**
`routeFares` when you know both ends. `destinationFares` when you know only where you want to
go — then take an origin code off any deal and run `routeFares` on that pair.

**Why can't I type a city name?**
Because there is no place-name lookup on this site to call, and a made-up one would be right for
a hundred cities and wrong for the rest. Codes are two to four characters and every result
publishes them.

**How current are the prices?**
As current as `quoted_at` on each leg says. They are cached quotes rather than a live search.

**Why did a page take longer than its size suggests?**
Because this surface occasionally serves an empty shell instead of its fares and is asked again
before the row is built. That recovery happens inside the request — still one request, still one
charge — so a page that takes a while is not stuck.

**Can I ask for a specific date?**
Not as an input. What arrives is the cheapest fare per month for twelve months and the exact
dates on the quoted deals.

**Is a Skyscanner account, cookie or API key required?**
No. No account, session cookie or key of any kind is supplied to the Actor or needed by it.

### Related Actors

[Skyscanner Route Scraper](https://apify.com/thenetaji/skyscanner-flight-route-scraper) is the
route mode on its own, for a run that only ever prices pairs.

[Skyscanner Destination Scraper](https://apify.com/thenetaji/skyscanner-destination-scraper) is
the destination mode on its own, for a run that only ever asks where cheap flights land.

# Actor input Schema

## `scraperType` (type: `string`):

Choose the dataset for this run, then fill in the section for that mode below.

## `routes` (type: `array`):

City pairs to price, one per line, written as `lond-nyca` — the code to fly from, then the code to fly to. `lond/nyca`, `lond nyca` and a pasted route page link all work too. A place code is two to four characters — "lond" for London, "nyca" for New York, "lhr", "sfo", "lax". A place NAME is not a code and there is no name lookup on this site, so "london" cannot be resolved. Every result publishes the codes it names, and each of those can be pasted straight back in.

## `places` (type: `array`):

Places to price flights INTO, one per line, as codes such as `nyca` or `lax`, or as pasted destination page links. Each result carries the cheapest quotes into that place with the origin named on every deal. A place code is two to four characters — "lond" for London, "nyca" for New York, "lhr", "sfo", "lax". A place NAME is not a code and there is no name lookup on this site, so "london" cannot be resolved. Every result publishes the codes it names, and each of those can be pasted straight back in.

## `maxItems` (type: `integer`):

Maximum number of rows to save. Set 0 for no limit. One row is one whole page, so this counts pages read rather than fares collected.

## Actor input object example

```json
{
  "scraperType": "routeFares",
  "routes": [
    "lond-nyca"
  ],
  "places": [
    "nyca"
  ],
  "maxItems": 10
}
```

# Actor output Schema

## `dataset` (type: `string`):

All records scraped by this run

# 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 = {
    "scraperType": "routeFares",
    "routes": [
        "lond-nyca",
        "lhr-jfk"
    ],
    "places": [
        "nyca"
    ],
    "maxItems": 10
};

// Run the Actor and wait for it to finish
const run = await client.actor("thenetaji/skyscanner-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 = {
    "scraperType": "routeFares",
    "routes": [
        "lond-nyca",
        "lhr-jfk",
    ],
    "places": ["nyca"],
    "maxItems": 10,
}

# Run the Actor and wait for it to finish
run = client.actor("thenetaji/skyscanner-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 '{
  "scraperType": "routeFares",
  "routes": [
    "lond-nyca",
    "lhr-jfk"
  ],
  "places": [
    "nyca"
  ],
  "maxItems": 10
}' |
apify call thenetaji/skyscanner-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,thenetaji/skyscanner-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/8VKcWfharhqZtbeaN/builds/CCEV15sXd4zgkylJw/openapi.json