How to Scrape Google Flights Data with Python

Google Flights is one of the most popular flight search engines, providing real-time flight prices, schedules, and route information. But how can you efficiently collect and analyze this data for your own use? In this guide, we'll show you how to automatically scrape Google Flights data using the Scrapeless Python library. This tool makes it easy to collect and analyze Google Flights data by streamlining the process and ensuring that your scraping workflow is optimized for speed and reliability.

Can I scrape data from Google Flights?

The data on Google Flights is considered public data, which means there is no law that explicitly prohibits the collection of this information. However, it is key to scrape Google Flights data ethically:

• Comply with the Terms of Service: Review and understand Google's terms to avoid violations.
• Respect Robots.txt: Follow the instructions provided in this file to ensure that you comply with the site's rules regarding automated access

Why scrape Google Flights data?

Why do you want to scrape Google Flights data? I can give you an example.

That is...

Hopper is a popular travel platform that focuses on fare prediction. It scrapes flight information from Google Flights and other online travel platforms to provide users with suggestions on whether the prices of certain flights will rise or fall in the coming months. According to Hopper's public data, they have helped users save billions of dollars through accurate price predictions, and the platform's own profits have also increased significantly.

What data can you extract from Google Flights?

Google Flights has a lot of valuable information. First, apply filters to your origin and destination. For example, I'm looking for a one-way flight from New York to Boston. Once you set the filters, you'll see a list of flight options.

We’re going to extract several key details, including:

• Flight name
• Departure time
• Arrival time
• Flight duration
• Prices
• Number of stops
• CO2 emissions (to help you choose more eco-friendly travel options)
• CO2 emissions change.

What are the obstacles when scraping Google Flights information?

When attempting to scrape Google Flights, there are several key obstacles that can arise:

1. IP Blocking: Google employs anti-scraping measures like IP blocking to prevent excessive automated requests. Scrapers can easily get blocked after a few requests.
2. CAPTCHA Challenges: Google frequently presents CAPTCHA challenges, especially when too many requests are made within a short period. This makes it difficult to extract data without human intervention.
3. Dynamic Website Structure: Google Flights often changes its page layout and HTML structure, which can cause scraping scripts to break, requiring continuous updates and maintenance.
4. Rate Limiting: Google restricts the number of requests you can make in a short time frame. This limits how much data you can scrape in one session.

By understanding these challenges, using advanced tools like Scrapeless, which automate IP rotation, CAPTCHA solver, and data extraction from dynamic pages, you can efficiently scrape Google Flights without encountering these issues.

How to Scrape Google Flights Data with Python

Scraping Google Flights data using Python is an effective way to collect valuable travel information such as flight prices, schedules, and availability for analysis or comparison. In this section, we will walk you through the necessary steps to scrape Google Flights, from setting up the environment to implementing a scraping script so that you can automate the extraction process and collect the data you need while adhering to ethical guidelines and legal constraints.

First, we need to build a data crawling environment and prepare the following tools:

1. Python: https://www.python.org/downloads/ This is the core software for running Python. You can download the version we need from the official website, as shown in the figure below, but it is recommended not to download the latest version. You can download 1-2 versions before the latest version.
2. Python IDE: Any IDE that supports Python will do, but we recommend PyCharm, which is an IDE development tool software designed specifically for Python. For the PyCharm version, we recommend the free PyCharm Community Edition.

1. pip: You can use the Python Package Index to install the libraries needed to run the program with a single command.

Note: If you are a Windows user, don't forget to check the "Add python.exe to PATH" option in the installation wizard. This will allow Windows to use Python and commands in the terminal. Since Python 3.4 or later includes it by default, you don't need to install it manually.

Through the above steps, the environment for crawling Google Flights data is set up. Next, you can use the downloaded PyCharm combined with scraperless to crawl Google Flights data.

Step 1: Start PyCharm and select File > New Project... in the menu bar.

Step 2: Then, in the pop-up window, select Pure Python from the left menu, and then set up your project as shown below:

Note: In the red box in the figure below, select the Python installation path you downloaded in the first step of the environment configuration

Step 3: You can create a project called python-scraper, check the "Create main.py welcome script option" in the folder, and then click the "Create" button. After a while of PyCharm setting up your project, you should see the following:

Step 4: Then, right-click to create a new Python file.

Step 5: To verify that everything is working properly, open the Terminal tab at the bottom of the screen and type: python main.py. After launching this command, you should get: Hi, PyCharm.

Now you can directly copy the code to PyCharm using scraperless and run it, so that we can get the JSON format data of Google Flights.

The following is an example of the output result code：

```{
"best_flights": [
{
"flights": [
{
"departure_airport": {
"name": "Paris Orly Airport",
"id": "ORY",
"time": "2025-01-14 9:10"
},
"arrival_airport": {
"name": "Josep Tarradellas Barcelona-El Prat Airport",
"id": "BCN",
"time": "2025-01-14 10:50"
},
"duration": 100,
"airplane": "Airbus A321",
"airline": "Vueling",
"airline_logo": "https://www.gstatic.com/flights/airline_logos/70px/VY.png",
"travel_class": "Economy",
"flight_number": "VY 8001",
"extensions": [
"Below average legroom (29 in)",
"In-seat USB outlet",
"Emissions estimate: 93 kg CO2e"
],
"ticket_also_sold_by": null,
"legroom": "29 in",
"overnight": false,
"often_delayed_by_over_30_min": false
}
],
"layovers": null,
"total_duration": 100,
"carbon_emissions": {
"this_flight": 93000,
"typical_for_this_route": 86000,
"difference_percent": 8
},
"price": 94,
"type": "One-Way",
"airline_logo": "https://www.gstatic.com/flights/airline_logos/70px/VY.png",
"extensions": [
"Checked baggage for a fee",
"Fare non-refundable, taxes may be refundable",
"Ticket changes for a fee"
],
"booking_token": "WyJDalJJZHpkT1dYVXRZWE5DVTJ0QlNFSnhPVkZDUnkwdExTMHRMUzB0TFhaMGRtVXhOMEZCUVVGQlIyVkZaVEYzVG5ocVdESkJFZ1pXV1Rnd01ERWFDZ2puU0JBQ0dnTlZVMFE0SEhEblNBPT0iLFtbIk9SWSIsIjIwMjUtMDEtMTQiLCJCQ04iLG51bGwsIlZZIiwiODAwMSJdXV0="
},
...
],
"other_flights": [
{
"flights": [
{
"departure_airport": {
"name": "Paris Orly Airport",
"id": "ORY",
"time": "2025-01-14 6:30"
},
"arrival_airport": {
"name": "Josep Tarradellas Barcelona-El Prat Airport",
"id": "BCN",
"time": "2025-01-14 8:10"
},
"duration": 100,
"airplane": "Airbus A320",
"airline": "Vueling",
"airline_logo": "https://www.gstatic.com/flights/airline_logos/70px/VY.png",
"travel_class": "Economy",
"flight_number": "VY 8005",
"extensions": [
"Below average legroom (29 in)",
"In-seat USB outlet",
"Emissions estimate: 91 kg CO2e"
],
"ticket_also_sold_by": null,
"legroom": "29 in",
"overnight": false,
"often_delayed_by_over_30_min": false
}
],
"layovers": null,
"total_duration": 100,
"carbon_emissions": {
"this_flight": 92000,
"typical_for_this_route": 86000,
"difference_percent": 7
},
"price": 94,
"type": "One-Way",
"airline_logo": "https://www.gstatic.com/flights/airline_logos/70px/VY.png",
"extensions": [
"Checked baggage for a fee",
"Fare non-refundable, taxes may be refundable",
"Ticket changes for a fee"
],
"booking_token": "WyJDalJJZHpkT1dYVXRZWE5DVTJ0QlNFSnhPVkZDUnkwdExTMHRMUzB0TFhaMGRtVXhOMEZCUVVGQlIyVkZaVEYzVG5ocVdESkJFZ1pXV1Rnd01EVWFDZ2puU0JBQ0dnTlZVMFE0SEhEblNBPT0iLFtbIk9SWSIsIjIwMjUtMDEtMTQiLCJCQ04iLG51bGwsIlZZIiwiODAwNSJdXV0="
},
...
],
"price_insights": {
"lowest_price": 94,
"price_level": "high",
"typical_price_range": [
30,
65
],
"price_history": [
[
1731452400,
40
],
[
1731538800,
36
],
...
]
},
"airports": [
{
"departure": [
{
"airport": {
"id": "ORY",
"name": "Paris Orly Airport"
},
"city": "Paris",
"country": "France",
"country_ode": "FR",
"image": "https://encrypted-tbn3.gstatic.com/images?q=tbn:ANd9GcQGx8ii2KbSDdbdzfKye5oDN2bwBA6audqI7XUEf2iMRZezpn_ZbQe1ZIuvUSH-8XOMe958umDwSsAF1w",
"thumbnail": "https://encrypted-tbn3.gstatic.com/images?q=tbn:ANd9GcSyQJ-woNs0iO22mPSkmRUM5gcsTbbYeypQ6BBTeFxXr90mqTxZl57Fdq2CDuLn4w7cKZ8TT9_zZhOpF57rIpA7yWKQnqKvkKIf9Y-qJDo"
}
],
"arrival": [
{
"airport": {
"id": "BCN",
"name": "Josep Tarradellas Barcelona-El Prat Airport"
},
"city": "Barcelona",
"country": "Spain",
"country_ode": "ES",
"image": "https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcQOk3xypjQxrqfZPlTUH5lubWcGBzOkdXv7IVkOL--w1FYohepC2Y1hN69JZMcmQsAOt2hIy7EWP0SfXA",
"thumbnail": "https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcSm8RLrNH5mwpZ7VV_y8imJgifZndKGVUDYaU5-3_hF41Qrpet1SbU1az4wU48pwjNcbuAC9cYwCNqDCxMF1MgcMCvzO0P__9pb0Q9JBGM"
}
]
}
]
}

**Through the above steps, you can scrape the following information:**
- Scrape Google Flights Company Name：


```language
"name": "Paris Orly Airport",

• Scrape Google Flights Flight Times：

"price": 94,

• Scrape Google Flights Departure and Arrival Dates：

  "departure_airport": {
            "name": "Paris Orly Airport",
            "id": "ORY",
            "time": "2025-01-14 9:10"
          },
          "arrival_airport": {
            "name": "Josep Tarradellas Barcelona-El Prat Airport",
            "id": "BCN",
            "time": "2025-01-14 10:50"
          },

• Scrape Google Flights CO2 Emission：

 "carbon_emissions": {
        "this_flight": 92000,
        "typical_for_this_route": 86000,
        "difference_percent": 7
      },

Scraping Google Flights with Scrapeless

Scrapeless provides a reliable solution to handle dynamic content on Google Flights and ensure smooth data extraction at scale. By leveraging Scrapeless’s Google Flights scraping api, you can overcome challenges like IP blocking, CAPTCHA challenges, and anti-scraping measures implemented by Google Flights.

Scrapeless provides a Python library that can be seamlessly integrated into your scraping workflow. You can easily replace traditional HTTP requests with Scrapeless Google Flights scraping API calls to scrape web pages.

Sign in to Scrapeless now and start your free trial! With just a few simple steps, you can easily scrape Google Flights data and get real-time flight information. No complicated settings required, get started quickly

Main Features：

1. Scrapeless Google Flights Scraping API can scrape real-time flight data, including flight prices, departure times, arrival times, flight status, airline information, etc.
2. Scrapeless Google Flights Scraping API supports a variety of customized functions, and users can filter flight data according to their needs.
3. Scrapeless focuses on providing legal and compliant data scraping services to ensure compliance with relevant laws and regulations when scraping Google Flights data and avoid infringing Google's terms of use.
4. Scrapeless API is particularly suitable for projects that require high-frequency scraping, and can handle multiple requests and return results in a short time. Suitable for business scenarios that require fast and large-scale data scraping.

Additionally, you can explore our guides on scraping other Google services like Google search results data, Google Trends, and more.

How to integrate Google Flights Scraper into your system

You can refer to the following API examples:

• Round trip

import requests
import json

url = "https://api.scrapeless.com/api/v1/scraper/request"

payload = json.dumps({
   "actor": "scraper.google.flights",
   "input": {
      "departure_id": "ORY",
      "arrival_id": "BCN",
      "data_type": 1,
      "outbound_date": "2025-01-05",
      "return_date": "2025-01-11"
   }
})
headers = {
   'Content-Type': 'application/json'
}

response = requests.request("POST", url, headers=headers, data=payload)

print(response.text)

- One way

import http.client
import json

conn = http.client.HTTPSConnection("api.scrapeless.com")
payload = json.dumps({
   "actor": "scraper.google.flights",
   "input": {
      "departure_id": "ORY",
      "arrival_id": "BCN",
      "data_type": 2,
      "outbound_date": "2025-01-11"
   }
})
headers = {
   'Content-Type': 'application/json'
}
conn.request("POST", "/api/v1/scraper/request", payload, headers)
res = conn.getresponse()
data = res.read()
print(data.decode("utf-8"))

If you need more detailed information or need to integrate other API tools, you can also refer to our complete documentation.

Faq about Google Flights

1. What is Google Flights data scraping?

Google Flights data scraping refers to the process of extracting information, such as flight prices, routes, schedules, and airlines, from Google Flights using web scraping tools or APIs. This data can be used for market analysis, price tracking, or travel trend predictions.

2. Is it legal to scrape google flights?

Scraping publicly accessible data is generally legal. This includes information provided on Google Flights, as long as the data does not require a warrant to access. The Supreme Court has clarified that accessing publicly accessible information does not violate the Computer Fraud and Abuse Act (CFAA)

3. How do I get a free trial of Scrapeless Google Flights?

You can join the Scrapeless discord group, and once you join, someone will help you get the free trial.

Conclusion

Through the introduction of this article, you have learned how to use Scrapeless to crawl Google Flights data. Scrapeless simplifies the crawling process, allowing users without a deep programming background to easily obtain and analyze flight information from Google Flights. With this tool, you can efficiently scrape Google flights prices, airline dynamics, and market trends from Google Flights to optimize business strategies and drive growth. Scrapeless enables you to focus on data analysis without worrying about technical details, and helps you easily respond to rapidly changing market demands.