Google Flights API in Python: scrape flight prices, airlines, stops and layovers from Google Flights to JSON/CSV

A short tutorial for pulling Google Flights search results (total price, Google's low/typical/high price level, airlines, flight numbers, stops, layovers, departure and arrival times, aircraft, legroom, CO2 emissions) into Python with the Google Flights Scraper on Apify. Google has no public Flights API (the old QPX Express API was shut down in 2018); this works as an unofficial one.

Disclosure: I built this actor; it's a paid tool on Apify ($0.50 per 1,000 itineraries). The code in this repo is MIT-licensed.

How it works

You give it a route (IATA codes like JFK and LAX, several comma-separated airports, or a Google city id such as /m/02_286 for all New York airports) and a date. The actor loads the Google Flights results page over plain HTTPS through Apify Proxy and parses the structured itinerary data Google embeds in it. No headless browser, no cookies, no Google account. One-way and round trips are supported; for round trips it can expand the top N outbound flights into full round-trip rows.

Quick start (Python)

pip install apify-client

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")

run = client.actor("rel8ble/google-flights-scraper").call(run_input={
    "origin": "JFK",
    "destination": "LAX",
    "departureDate": "2026-11-12",
    "adults": 1,
    "cabinClass": "economy",
    "maxStops": "0",
    "maxResults": 10,
})

for f in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f["price"], f["priceLevel"], f["departureTime"], f["flightNumbers"])

example.py is the runnable version: it searches one route on 7 departure dates in a single run, prints the cheapest nonstop per day and writes every itinerary to a CSV.

Quick start (Node.js)

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('rel8ble/google-flights-scraper').call({
    origin: 'SFO', destination: 'ORD', departureDate: '2026-10-20', returnDate: '2026-10-23', maxResults: 10,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items.length, 'round trips');

Input

Field	Default	What it does
origin / destination	JFK / LAX	IATA code, comma-separated codes (LHR,LGW) or a Google city id
departureDate	today + 30 days	YYYY-MM-DD, up to ~11 months ahead
returnDate	none (one-way)	Set it for a round trip
searches	none	Many routes/dates in one run: [{"origin": "JFK", "destination": "LAX", "departureDate": "2026-12-03"}]
adults, children, infantsInSeat, infantsOnLap	1, 0, 0, 0	Prices are totals for all passengers (max 9)
cabinClass	economy	premium_economy, business, first
maxStops	any	"0" nonstop only, "1", "2"
airlines	all	IATA codes (["AA", "DL"]) or STAR_ALLIANCE, ONEWORLD, SKYTEAM
currency	USD	Any ISO 4217 code
maxResults	50	Itineraries per search; 0 = everything Google shows
returnFlightsForTopOutbound	3	Round trips: expand the top N outbound flights into full round-trip rows (0-30)
language / country	en / us	Google hl / gl; country can change the fares shown

Output sample (one real itinerary, trimmed)

{
  "searchId": "MAD-BCN 2026-10-15",
  "tripType": "one_way",
  "origin": "MAD",
  "destination": "BCN",
  "cabinClass": "economy",
  "currency": "USD",
  "position": 1,
  "category": "best",
  "price": 59,
  "priceLevel": "typical",
  "airlines": ["Air Europa"],
  "airlineCodes": ["UX"],
  "flightNumbers": ["UX 7701"],
  "stops": 0,
  "totalDurationMinutes": 85,
  "totalDuration": "1 hr 25 min",
  "departureAirport": "MAD",
  "departureDateTime": "2026-10-15T07:30:00+02:00",
  "arrivalAirport": "BCN",
  "arrivalDateTime": "2026-10-15T08:55:00+02:00",
  "layovers": [],
  "segments": [
    { "flightNumber": "UX 7701", "airline": "Air Europa", "aircraft": "Boeing 787",
      "durationMinutes": 85, "legroom": "31 in", "emissionsKg": 51 }
  ],
  "emissionsKg": 51,
  "typicalEmissionsKg": 64,
  "emissionsDifferencePercent": -20,
  "returnFlight": null,
  "googleFlightsUrl": "https://www.google.com/travel/flights/booking?tfs=CBwQAhpAEgoyMDI2LTEwLTE1IiAKA01BRBIKMjAyNi0xMC0xNRoDQkNOKgJVWDIENzcwMWoHCAESA01BRHIHCAESA0JDTkABSAFwAZgBAg&hl=en&gl=us&curr=USD"
}

Round-trip rows carry the same fields for the return leg in returnFlight, and price is the full round-trip total.

Use cases

• Cheapest-day finder: put 7-30 dates for one route in searches and pick the lowest price per date (that's what example.py does).
• Fare alerts: schedule the same route daily on Apify and alert when price drops or priceLevel turns low.
• Route and airline research: compare carriers, nonstop share and durations across city pairs with airlineCodes, stops and totalDurationMinutes.
• Travel and expense tools: price trips per passenger mix and cabin, with CO2 per itinerary for sustainability reporting.

Price

$0.50 per 1,000 itineraries, pay per result. A one-way search usually returns 10-40 itineraries, so one route/date costs about $0.005-$0.02. No start fee, no monthly rental. Apify's free plan includes $5 of monthly credit.

Limits

• Returns what is on Google's initial results page (in tests: 36 JFK-LAX one-way options, 18 Madrid-Barcelona, 7 Charlotte-Tokyo).
• Multi-city (3+ legs) searches are not supported; one-way and round trip are.
• Per-agency booking prices (Expedia vs the airline) and baggage fees are not extracted; googleFlightsUrl opens the booking options on Google.
• Google sells about 11 months ahead, and at most 9 passengers per search.

Links

• Actor on the Apify Store: https://apify.com/rel8ble/google-flights-scraper
• Apify Python client docs: https://docs.apify.com/api/client/python

License

MIT