Practical Methods to Extract Data from Google Flights

Google Flights is a wealth of flight data. Airfares, schedules, airline details—you name it. However, Google doesn't offer an official API. That means if you want to grab this data at scale, you need to scrape the site yourself.
Lucky for you, there are solid ways to do this without losing your mind. In this guide, we'll walk you through three practical methods: coding a scraper in Python with Playwright, leveraging third-party APIs, and using no-code tools. Plus, we'll tackle the headaches like anti-scraping defenses and proxies.
Let's jump in and see how to unlock Google Flights’ data efficiently and reliably.

Scraping Google Flights with Python

Google Flights isn't your typical static webpage. It loads data dynamically with JavaScript, so a simple HTTP request won't cut it. Instead, you need a headless browser that mimics real user behavior.

Step 1: Set up Playwright

Install Playwright and its browser engines:

pip install playwright
playwright install

If you want to parse HTML further, bring in libraries like BeautifulSoup—but Playwright's CSS selectors often handle what you need.

Step 2: Automate a Headless Browser

Your script will open Google Flights, fill out the search, wait for results, and scrape data. Here's a simplified example using async Playwright:

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")

        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")

        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

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

Step 3: Load All Results

Google Flights shows limited results upfront. To get everything, you'll need to scroll or click “Show more flights” repeatedly.
Here's a quick loop idea:

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

Step 4: Scale with Proxies

Hit Google too often from one IP? Expect blocks or CAPTCHAs. Rotate your IPs with proxies. Residential proxies mimic real users and keep your scraper under the radar. Playwright supports proxy settings per browser context—use them.

Step 5: Save & Analyze

Dump your scraped data into JSON or CSV files. Analyze pricing trends, build dashboards, or feed this into apps. The sky's the limit.

Using an API for Google Flights Data

No time to code? APIs can save the day. Companies like SerpApi scrape Google Flights for you and return neat JSON results.
Here's a quick Python snippet hitting SerpApi's Google Flights endpoint:

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"))

This method offloads scraping headaches—IP rotation, CAPTCHA solving, page rendering—to the API. You get reliable data fast. But expect subscription fees and query limits.

No-Code Tools for Google Flights Scraping

Not a coder? No problem.
Tools like Octoparse and ParseHub let you scrape visually. Point them at a Google Flights search, and they auto-detect flight listings, prices, and times.
Setup is quick:

Input your Google Flights URL.

Let the tool auto-identify data fields or tweak selectors manually.

Configure pagination or scrolling to load all flights.

Run the scrape and export CSV, JSON, or Excel.

Many of these tools include proxy support and CAPTCHA bypassing baked in. It's a smooth, fast way to grab data without writing a line of code. Downsides? Less flexibility and occasional breaks if Google changes its page.

Navigating Anti-Scraping Defenses

Google wants to stop bots. That means IP blocks and CAPTCHAs.
How to stay ahead:

Rotate IPs: Use high-quality residential proxies that switch IP addresses frequently.

Throttle requests: Don't hammer the site. Randomize delays and mimic real browsing speeds.

Handle CAPTCHAs: Integrate third-party CAPTCHA solvers if you hit challenges.

Mimic browsers: Run headful (non-headless) browsers with realistic user-agent strings to appear human.

Test with small batches first. Watch for blocks and adjust your strategy.

Final Thoughts

Scraping Google Flights can give you a competitive edge: tracking price trends, spotting deals, or powering your own travel app. Whether you build your own scraper, rely on an API, or use no-code tools, the key is smart setup and respect for site defenses.