How to track Google Flights prices with Python (no API key)

#python #webscraping #travel #automation

Google Flights has no public API. If you want to watch fares for a route every day, compare dozens of dates, or feed flight prices into a spreadsheet, you need a scraper. In this tutorial we'll collect Google Flights prices for many routes and dates in one run, export them to CSV, and schedule a daily price check.

Disclosure: I built the Apify Actor used below (Google Flights Scraper). It costs $0.20 per 1,000 flights and runs on Apify's free plan.

What you get

For every flight shown by Google Flights:

total price and currency, rank on the results page
airlines, departure / arrival time, duration, number of stops and layovers
every leg: flight number, aircraft, legroom, codeshares
CO2 emissions vs. the typical value for the route
a direct Google Flights link

1. Try it without code

Open Google Flights Scraper and click Try for free.
Fill in origins, destinations and dates:

{ "origins": ["JFK"], "destinations": ["LHR"], "departureDates": ["2026-12-03"] }

Click Start. After a few seconds you can export the results as CSV, Excel or JSON.

2. Many routes × many dates in one run

You can give several airports and a date range (start..end). Every origin × destination × date becomes a search:

{
  "origins": ["JFK", "EWR"],
  "destinations": ["LHR", "CDG"],
  "departureDates": ["2026-12-01..2026-12-14"],
  "tripLengthDays": 7,
  "cabinClass": "economy",
  "stops": "nonstop",
  "currency": "USD"
}

tripLengthDays: 7 turns every search into a round trip returning 7 days later. Use returnDate instead for a fixed return day.

3. Run it from Python

pip install "apify-client>=3"

from apify_client import ApifyClient
import csv

client = ApifyClient("YOUR_APIFY_TOKEN")  # Apify Console → Settings → API & Integrations

run = client.actor("rt-solutions/google-flights-scraper").call(run_input={
    "origins": ["JFK"],
    "destinations": ["LHR"],
    "departureDates": ["2026-12-01..2026-12-07"],
    "stops": "nonstop",
})

rows = list(client.dataset(run.default_dataset_id).iterate_items())

# Cheapest flight per departure date
best = {}
for f in rows:
    d = f["departureDate"]
    if f.get("price") and (d not in best or f["price"] < best[d]["price"]):
        best[d] = f

with open("cheapest_jfk_lhr.csv", "w", newline="") as fh:
    w = csv.writer(fh)
    w.writerow(["date", "price", "currency", "airlines", "departure", "durationMinutes"])
    for d, f in sorted(best.items()):
        w.writerow([d, f["price"], f["currency"], "/".join(f["airlines"]), f["departure"], f["durationMinutes"]])

print(f"{len(rows)} flights, cheapest per day saved to cheapest_jfk_lhr.csv")

A flight item looks like this (shortened):

{
  "origin": "JFK", "destination": "LHR", "departureDate": "2026-12-03",
  "price": 711, "currency": "EUR", "airlines": ["American"],
  "departure": "2026-12-03T18:25", "arrival": "2026-12-04T06:20",
  "durationMinutes": 415, "stops": 0, "co2Kg": 421,
  "legs": [{ "flightNumber": "AA 100", "aircraft": "Boeing 777", "legroom": "31 inches" }]
}

4. Track fares every day

In Apify Console open the Actor → Schedules → run it daily with the same input. Each run is a new dataset, so you can append the cheapest price per date to a Google Sheet (Apify has a Google Sheets integration) or to your database and watch prices move.

Cost

$0.20 per 1,000 flights on the free plan ($0.08–0.10 on paid plans)
searches that return no flights are not charged
a 7-day × 1-route check (~150 flights) costs about $0.03

Notes

price is the total for all passengers; for round trips it is the round-trip price shown with the outbound flight, as on Google Flights.
No Google account or API key is needed.

That's it — a few lines of Python and you have a daily fare tracker. Questions or a missing field? Open an issue on the Actor page.

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