Extracting Flight Prices and Schedules from Google Flights Efficiently

Flight prices change by the minute. Savvy travelers and analysts want that edge. Google Flights holds a goldmine of data: schedules, fares, airlines, routes—you name it. However, Google doesn’t hand out a public API. That means if you want to track airfare trends or build a flight comparison tool, you’ll have to roll up your sleeves and scrape.
This guide presents three effective methods to collect data from Google Flights. It also covers strategies to overcome anti-scraping measures and how to navigate them successfully. Let’s get started.

Collecting Google Flights with Python and Playwright

Google Flights is built on JavaScript and loads results dynamically. That kills any hope of scraping with simple HTTP requests. Instead? You need a real browser running your code.
Playwright is your best friend here. It launches a headless browser that mimics human interaction perfectly.

Step 1: Get Started

pip install playwright
playwright install

You’re set to control a Chromium browser from Python.

Step 2: Search Flights, Grab Data
Here’s the core:

import asyncio
from playwright.async_api import async_playwright

async def fetch_flights(departure, destination, date):
    async with async_playwright() as p:
        browser = await p.chromium.launch(headless=True)
        context = await browser.new_context()
        page = await context.new_page()
        await page.goto("https://www.google.com/travel/flights")

        # Fill search form
        await page.fill("input[aria-label='Where from?']", departure)
        await page.fill("input[aria-label='Where to?']", destination)
        await page.fill("input[aria-label='Departure date']", date)
        await page.keyboard.press("Enter")

        # Wait for results
        await page.wait_for_selector("li.pIav2d")

        flights = []
        flight_items = await page.query_selector_all("li.pIav2d")

        for item in flight_items:
            airline = await item.query_selector("div.sSHqwe.tPgKwe.ogfYpf")
            price = await item.query_selector("div.FpEdX span")
            time = await item.query_selector("span[aria-label^='Departure time']")

            flights.append({
                "airline": await airline.inner_text() if airline else None,
                "price": await price.inner_text() if price else None,
                "departure_time": await time.inner_text() if time else None
            })

        await browser.close()
        return flights

# Run example
results = asyncio.run(fetch_flights("LAX", "JFK", "2025-12-01"))
print(results)

This script launches a browser, fills the flight search, waits for the listings, and pulls airline, price, and departure time info. Simple and effective.

Step 3: Load More, Scrape More
Google Flights shows limited results by default. To scrape everything, you’ll need to simulate clicking “Show more flights” until it’s gone.

while True:
    try:
        more_button = await page.wait_for_selector('button[aria-label*="more flights"]', timeout=5000)
        await more_button.click()
        await page.wait_for_timeout(2000)
    except TimeoutError:
        break

Keep clicking until Google stops giving you more flights. Then scrape away.

Step 4: Proxies for Scale
Scraping at scale? Google notices repeated requests from the same IP. Use rotating residential proxies to blend in and avoid blocks. Playwright lets you set proxies per browser context — a must-have for reliable scraping.

Method to Use a Google Flights API

Don’t want to wrestle with Playwright? Enter third-party scraping APIs like SerpApi. They do the browser automation, IP rotation, and CAPTCHA solving behind the scenes. You just get clean JSON.

import requests

params = {
    "engine": "google_flights",
    "q": "Flights from NYC to LON, one-way, 2025-12-25",
    "api_key": "YOUR_SERPAPI_API_KEY"
}

response = requests.get("https://serpapi.com/search", params=params)
data = response.json()

for flight in data.get("best_flights", []):
    print(flight.get("airline"), flight.get("price"))

In a few lines, you have reliable, parsed flight data. The trade-off? You pay for convenience. But if time is money, it’s often worth it.

Method to Implement Zero Code

Tools like Octoparse, ParseHub, and Apify let you scrape Google Flights without writing a single line of code.
Here’s how Octoparse makes it painless:
Paste your Google Flights URL.
Use auto-detect to capture flight listings, prices, and times.
Configure pagination or “load more” clicks with visual wizards.
Run it and watch your data flow in real time.
Export in CSV, Excel, JSON, or push directly to Google Sheets.

Overcoming Google’s Scraping Barriers

Google knows scraping threatens their data monopoly. They fight back with IP bans and CAPTCHAs. Here’s how to stay ahead:
Rotate IPs. Use high-quality residential proxies that mimic real users.
Slow it down. Avoid blasting requests too fast. Add randomized delays.
Solve CAPTCHAs. Integrate services like 2Captcha or AntiCaptcha to automate solving challenges.
Use headful browsers. Sometimes, running browsers with UI (not headless) helps avoid suspicion.
Mimic human behavior. Vary user agents, add mouse movements, and randomize actions.
Start small, monitor blocks, then adjust. This dance between scraper and defender is ongoing but manageable.

Final Thoughts

Scraping Google Flights unlocks rich, actionable flight data—from price trends to booking timing insights. Whether you prefer coding your own scraper, outsourcing to an API, or using no-code tools, your choice boils down to flexibility, speed, and scale.
For many, combining Playwright with proxies offers the ultimate control. For others, APIs and no-code platforms get the job done fast and easy.