# Google Flights Scraper — Airfare, Routes, Prices (`scrape.badger/google-flights-scraper`) Actor
Scrape Google Flights at scale: one-way, round-trip, or multi-city itineraries with per-offer pricing, total duration, stops, layovers, airline metadata, and carbon emissions. Returns Google's Best flights recommendations plus the full Other flights result set.
- **URL**: https://apify.com/scrape.badger/google-flights-scraper.md
- **Developed by:** [Scrape Badger](https://apify.com/scrape.badger) (community)
- **Categories:** Travel
- **Stats:** 2 total users, 0 monthly users, 0.0% runs succeeded, NaN bookmarks
- **User rating**: No ratings yet
## Pricing
from $12.00 / 1,000 flight searches
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/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
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.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use 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
### What does Google Flights Scraper do?
Scrape [Google Flights](https://www.google.com/travel/flights) at scale — one-way, round-trip, and multi-city fares across all airlines, with cabin class, stops, and price filters.
### Why use Google Flights Scraper?
- **Every cabin class.** Economy, Premium Economy, Business, First.
- **One-way, round-trip, multi-city.** All Google Flights trip types.
- **Stops + airline filters.** Non-stop only, one-stop, or all; whitelist / blacklist airlines.
- **Currency + country targeting.** Local prices for your customer base.
- **Price insights.** When Google returns them — typical price range, lowest-price recent history.
### What data can Google Flights Scraper extract?
| Field | Type | Description |
|---|---|---|
| result_group | string | `best` or `other` |
| price / currency | number / string | Total fare |
| airline | string | Primary carrier |
| flights | array | Per-segment info (origin / dest / times / aircraft) |
| duration | string | Total journey time |
| stops | number | Layover count |
| layovers | array | Layover airport + duration |
| carbon_emissions | object | Google's CO2 estimate in kg |
### How to scrape Google Flights
1. Click **Try for free**.
2. Enter `departure_id` (IATA code, e.g. `JFK`) and `arrival_id` (e.g. `LAX`).
3. Set `outbound_date` (and `return_date` if round-trip).
4. Optional: passengers (`adults`, `children`, …), `travel_class`, `stops`, `max_price`, airline filters.
5. Click **Start** — each flight offer streams into the dataset.
### How much will it cost?
**$0.012 per search (≈ $12 per 1,000 searches).** One call per origin-destination-date combo. Multi-city is still one call.
#### Competitor benchmark
| Actor | Author | Price | Notes |
|---|---|---|---|
| kaizu/google-flights-scraper | kaizu | ~$15 / 1k searches | Most popular |
| credible_sandal/google-flights-scraper | credible_sandal | ~$18 / 1k searches | Subscription |
| scrapier/google-flights-scraper | scrapier | ~$20 / 1k searches | Per-result |
| **scrape-badger/google-flights-scraper** | **ScrapeBadger** | **$12 / 1k searches** | **20% below cheapest major** |
### Input
Configure the run in the **Input** tab above, or pass a JSON object matching the fields below when calling the Actor via the Apify API.
| Field | Required | Description |
|---|---|---|
| departure_id | ✅ | IATA airport code (e.g. `JFK`). |
| arrival_id | ✅ | IATA airport code. |
| outbound_date | ✅ | `YYYY-MM-DD`. |
| return_date | Round-trip only | `YYYY-MM-DD`. |
| trip_type | — | `round_trip` (default) / `one_way` / `multi_city`. |
| adults / children / infants_in_seat / infants_on_lap | — | Passenger counts. |
| travel_class | — | `economy` / `premium_economy` / `business` / `first`. |
| stops | — | `any` / `nonstop` / `one_stop` / `two_stops`. |
| max_price | — | Upper price cap in the target currency. |
| currency / gl / hl | — | Currency + country + language (defaults `USD` / `us` / `en`). |
### Output
Every successful run streams records into the run's dataset. Download as JSON, CSV, XML, Excel, or HTML from the **Dataset** tab; consume programmatically via the Apify API or webhooks.
Example record:
```json
{
"result_group": "best",
"price": 412,
"currency": "USD",
"airline": "Delta",
"flights": [
{
"origin": "JFK",
"destination": "LAX",
"departure": "2026-12-01T08:00",
"arrival": "2026-12-01T11:15"
}
],
"duration": "6h 15m",
"stops": 0,
"layovers": [],
"carbon_emissions": {
"this_flight": 203,
"typical_for_this_route": 215
}
}
````
### Tips / Advanced options
- **Run daily for fare tracking.** Prices change hourly — a cron gets you a price history for free.
- **Nonstop = 2-3x the price of one-stop.** Filter on `stops: nonstop` only when your customer specifically needs it.
- **`best` vs. `other`.** `best` is Google's ranked top offers (by convenience + price). `other` is everything else — cheaper but often with worse timings.
- **Carbon emissions for ESG reporting.** Use the `carbon_emissions.this_flight` kg figure for scope-3 tracking.
### FAQ, Disclaimers, Support
#### What IATA codes do you support?
Every airport Google Flights supports (~8,000+). Major hubs + regional airports.
#### Can I search by city?
Google accepts city codes too — `NYC` instead of `JFK` returns all NYC airports. The actor passes through whatever you provide.
#### Does this include award / mileage fares?
No — Google Flights is cash-only. Use your airline's website for award availability.
#### Multi-city?
Yes — set `trip_type: multi_city` and pass an array of legs via the SDK. Apify UI doesn't expose the array input directly; use the API.
#### Disclaimer
This Actor scrapes public Google data only. You're responsible for compliance with Google's Terms of Service and any applicable data-protection laws (GDPR, CCPA, etc.) in your jurisdiction. ScrapeBadger does not store the scraped results — they are delivered directly to your Apify dataset.
#### Support
Something not working? Open a ticket in the **Issues** tab above — we triage within one business day. Full API reference: [docs.scrapebadger.com](https://docs.scrapebadger.com).
#### Related Actors
- [`google-hotels-scraper`](https://apify.com/scrape-badger/google-hotels-scraper) — Hotel search + details
#### Powered by
[ScrapeBadger](https://scrapebadger.com) — Google-optimised residential proxy pool + browser-farm fallback, 99.7% uptime, unmetered bandwidth. No CAPTCHAs reach you.
# Actor input Schema
## `departure_id` (type: `string`):
Departure airport IATA code (e.g. JFK, LAX, LHR) or Google location ID.
## `arrival_id` (type: `string`):
Arrival airport IATA code (e.g. LHR, CDG, NRT) or Google location ID.
## `outbound_date` (type: `string`):
Outbound date in YYYY-MM-DD format. Example: 2026-06-15.
## `return_date` (type: `string`):
Return date in YYYY-MM-DD format. Required when trip\_type is round\_trip. Leave blank for one-way.
## `trip_type` (type: `string`):
Itinerary type: round\_trip (default), one\_way, or multi\_city.
## `adults` (type: `integer`):
Adult passengers (1-9).
## `children` (type: `integer`):
Children passengers (0-8).
## `infants_in_seat` (type: `integer`):
Infants with their own seat (0-4).
## `infants_on_lap` (type: `integer`):
Infants travelling on an adult's lap (0-4).
## `travel_class` (type: `string`):
Cabin class to search.
## `stops` (type: `string`):
Maximum number of stops per leg.
## `max_price` (type: `integer`):
Upper price bound in the currency selected below. Optional.
## `currency` (type: `string`):
ISO-4217 currency code. Example: USD, EUR, GBP.
## `gl` (type: `string`):
ISO 3166-1 alpha-2 country code (lowercase). Example: us, gb, de.
## `hl` (type: `string`):
ISO 639-1 language code. Example: en, es, de.
## Actor input object example
```json
{
"departure_id": "JFK",
"arrival_id": "LHR",
"outbound_date": "2026-06-15",
"trip_type": "round_trip",
"adults": 1,
"children": 0,
"infants_in_seat": 0,
"infants_on_lap": 0,
"travel_class": "economy",
"stops": "any",
"currency": "USD",
"gl": "us",
"hl": "en"
}
```
# Actor output Schema
## `dataset` (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 '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"departure_id": "JFK",
"arrival_id": "LHR",
"outbound_date": "2026-06-15"
};
// Run the Actor and wait for it to finish
const run = await client.actor("scrape.badger/google-flights-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 '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"departure_id": "JFK",
"arrival_id": "LHR",
"outbound_date": "2026-06-15",
}
# Run the Actor and wait for it to finish
run = client.actor("scrape.badger/google-flights-scraper").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"departure_id": "JFK",
"arrival_id": "LHR",
"outbound_date": "2026-06-15"
}' |
apify call scrape.badger/google-flights-scraper --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=scrape.badger/google-flights-scraper",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "Google Flights Scraper — Airfare, Routes, Prices",
"description": "Scrape Google Flights at scale: one-way, round-trip, or multi-city itineraries with per-offer pricing, total duration, stops, layovers, airline metadata, and carbon emissions. Returns Google's Best flights recommendations plus the full Other flights result set.",
"version": "1.0",
"x-build-id": "9vV42kgDowqzyahvn"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/scrape.badger~google-flights-scraper/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-scrape.badger-google-flights-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/scrape.badger~google-flights-scraper/runs": {
"post": {
"operationId": "runs-sync-scrape.badger-google-flights-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/scrape.badger~google-flights-scraper/run-sync": {
"post": {
"operationId": "run-sync-scrape.badger-google-flights-scraper",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"required": [
"departure_id",
"arrival_id",
"outbound_date"
],
"properties": {
"departure_id": {
"title": "Departure airport",
"type": "string",
"description": "Departure airport IATA code (e.g. JFK, LAX, LHR) or Google location ID."
},
"arrival_id": {
"title": "Arrival airport",
"type": "string",
"description": "Arrival airport IATA code (e.g. LHR, CDG, NRT) or Google location ID."
},
"outbound_date": {
"title": "Outbound date",
"type": "string",
"description": "Outbound date in YYYY-MM-DD format. Example: 2026-06-15."
},
"return_date": {
"title": "Return date",
"type": "string",
"description": "Return date in YYYY-MM-DD format. Required when trip_type is round_trip. Leave blank for one-way."
},
"trip_type": {
"title": "Trip type",
"enum": [
"round_trip",
"one_way",
"multi_city"
],
"type": "string",
"description": "Itinerary type: round_trip (default), one_way, or multi_city.",
"default": "round_trip"
},
"adults": {
"title": "Adults",
"minimum": 1,
"maximum": 9,
"type": "integer",
"description": "Adult passengers (1-9).",
"default": 1
},
"children": {
"title": "Children",
"minimum": 0,
"maximum": 8,
"type": "integer",
"description": "Children passengers (0-8).",
"default": 0
},
"infants_in_seat": {
"title": "Infants in seat",
"minimum": 0,
"maximum": 4,
"type": "integer",
"description": "Infants with their own seat (0-4).",
"default": 0
},
"infants_on_lap": {
"title": "Infants on lap",
"minimum": 0,
"maximum": 4,
"type": "integer",
"description": "Infants travelling on an adult's lap (0-4).",
"default": 0
},
"travel_class": {
"title": "Cabin class",
"enum": [
"economy",
"premium_economy",
"business",
"first"
],
"type": "string",
"description": "Cabin class to search.",
"default": "economy"
},
"stops": {
"title": "Stops filter",
"enum": [
"any",
"nonstop",
"one_stop",
"two_stops"
],
"type": "string",
"description": "Maximum number of stops per leg.",
"default": "any"
},
"max_price": {
"title": "Max price",
"minimum": 0,
"type": "integer",
"description": "Upper price bound in the currency selected below. Optional."
},
"currency": {
"title": "Currency",
"type": "string",
"description": "ISO-4217 currency code. Example: USD, EUR, GBP.",
"default": "USD"
},
"gl": {
"title": "Country",
"type": "string",
"description": "ISO 3166-1 alpha-2 country code (lowercase). Example: us, gb, de.",
"default": "us"
},
"hl": {
"title": "Language",
"type": "string",
"description": "ISO 639-1 language code. Example: en, es, de.",
"default": "en"
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```