A free tool used to get data from Google Flights for a provided Google Flights URL.
To run this tool, you need to have Python 3.11 installed in your system.
Open up a terminal window, navigate to this repository and run this command:
make install
First of all, go to Google Flights in your browser and select your desired departure and arrival locations along with the dates.
For this example, we'll be scraping flights from Berlin to Paris, two weeks apart.
After clicking Search, you should see something like this.
Copy and save the URL from your browser, it will be used for scraping the data for this flight configuration.
Here's the URL for this example
https://www.google.com/travel/flights/search?tfs=CBwQAhooEgoyMDI0LTA5LTA0agwIAxIIL20vMDE1NnFyDAgDEggvbS8wNXF0ahooEgoyMDI0LTA5LTE4agwIAxIIL20vMDVxdGpyDAgDEggvbS8wMTU2cUABSAFwAYIBCwj___________8BmAEB
To get results from Google Flights, simply run this command in your terminal:
make scrape URL="<your_google_flights_url>"
With the URL we retrieved earlier, the command would look like this:
make scrape URL="https://www.google.com/travel/flights/search?tfs=CBwQAhooEgoyMDI0LTA5LTA0agwIAxIIL20vMDE1NnFyDAgDEggvbS8wNXF0ahooEgoyMDI0LTA5LTE4agwIAxIIL20vMDVxdGpyDAgDEggvbS8wMTU2cUABSAFwAYIBCwj___________8BmAEB"
Make sure to surround the URL with quotation marks, otherwise the tool might have trouble parsing it.
After running the command, your terminal should look something like this:
After the tool has finished running, you should notice that a flights.csv file appeared in your current directory.
This data in this file has these columns for the Google Flights data based on your provided URL:
price- The full price of a flight.departure_time- The departure time of a flight.arrival_time- The arrival time of a flight.airline- The airline, or multiple airlines that operate the flight.stops- The number of stops between the departure and arrival locations.full_detail- The full detail of the flight in plain text.
Here's an example of how the data can look like:
In case the code doesn't work or your project is of bigger scale, please refer to the second part of the tutorial. There, we showcase how to scrape public data with Oxylabs Scraper API.
In case you were not able to carry out your project with the free scraper, you may use Oxylabs API instead.
In this section of the guide, we’re going to demonstrate how to scrape public data from flight pages and generate search results with Python and Oxylabs Google Flights API (a part of Web Scraper API). To use the Oxylabs API, you'll need an active subscription – you can get a free trial by signing up via the self-service dashboard.
We’ll gather all sorts of data, including price, flight time, and airline name.
Head to our blog to see the complete article with in-depth explanations and images for a visual reference.
- 1. Installing prerequisite libraries
- 2. Creating core structure
- 3. Getting the price
- 4. Getting the flight time
- 5. Getting the airline name
- 6. Final result
pip install bs4To start off, let’s create a function that will take a URL as a parameter, scrape that URL with Google Flights API (you can get a free 7-day trial for it) and return the scraped HTML:
def get_flights_html(url):
payload = {
'source': 'google',
'render': 'html',
'url': url,
}
response = requests.request(
'POST',
'https://realtime.oxylabs.io/v1/queries',
auth=('username', 'password'),
json=payload,
)
response_json = response.json()
html = response_json['results'][0]['content']
return htmlMake sure to change up USERNAME and PASSWORD with your actual Oxylabs credentials.
Next up, we’ll create a function that accepts a BeautifulSoup object created from the HTML of the whole page. This function will create and return an array of objects containing information from individual flight listings. Let’s try to form the function in such a way that makes it easily extendible if required:
def extract_flight_information_from_soup(soup_of_the_whole_page):
flight_listings = soup_of_the_whole_page.find_all('li','pIav2d')
flights = []
for listing in flight_listings:
if listing is not None:
# Add some specific data extraction here
flight = {}
flights.append(flight)
return flightsNow that we can get the HTML and have a function to hold our information extraction, we can organize both of those into one:
def extract_flights_data_from_urls(urls):
constructed_flight_results = []
for url in urls:
html = get_flights_html(url)
soup = BeautifulSoup(html,'html.parser')
flights = extract_flight_information_from_soup(soup)
constructed_flight_results.append({
'url': url,
'flight_data': flights
})
return constructed_flight_resultsThis function will take an array of URLs as a parameter and return an object of extracted flight data.
One thing left for our core is a function that takes this data and saves it as a file:
def save_results(results, filepath):
with open(filepath, 'w', encoding='utf-8') as file:
json.dump(results, file, ensure_ascii=False, indent=4)
returnWe can finish by creating a simple main function to invoke all that we’ve created so far:
def main():
results_file = 'data.json'
urls = [
'https://www.google.com/travel/flights?tfs=CBsQAhooEgoyMDI0LTA3LTI4agwIAxIIL20vMDE1NnFyDAgCEggvbS8wNGpwbBooEgoyMDI0LTA4LTAxagwIAhIIL20vMDRqcGxyDAgDEggvbS8wMTU2cUABSAFSA0VVUnABemxDalJJTkRCNVRGbDBOMU5UVEdOQlJ6aG5lRUZDUnkwdExTMHRMUzB0TFMxM1pXc3lOMEZCUVVGQlIxZ3dhRWxSUVRoaWFtTkJFZ1pWTWpnMk1qSWFDZ2lRYnhBQ0dnTkZWVkk0SEhEN2VBPT2YAQGyARIYASABKgwIAxIIL20vMDRqcGw&hl=en-US&curr=EUR&sa=X&ved=0CAoQtY0DahgKEwiAz9bF5PaEAxUAAAAAHQAAAAAQngM',
'https://www.google.com/travel/flights/search?tfs=CBwQAhooEgoyMDI0LTA3LTI4agwIAxIIL20vMDE1NnFyDAgDEggvbS8wN19rcRooEgoyMDI0LTA4LTAxagwIAxIIL20vMDdfa3FyDAgDEggvbS8wMTU2cUABSAFwAYIBCwj___________8BmAEB&hl=en-US&curr=EUR'
]
constructed_flight_results = extract_flights_data_from_urls(urls)
save_results(constructed_flight_results, results_file)def get_price(soup_element):
price = soup_element.find('div','BVAVmf').find('div','YMlIz').get_text()
return pricedef get_time(soup_element):
spans = soup_element.find('div','Ir0Voe').find('div','zxVSec', recursive=False).find_all('span', 'eoY5cb')
time = ""
for span in spans:
time = time + span.get_text() + "; "
return timedef get_airline(soup_element):
airline = soup_element.find('div','Ir0Voe').find('div','sSHqwe')
spans = airline.find_all('span', attrs={"class": None}, recursive=False)
result = ""
for span in spans:
result = result + span.get_text() + "; "
return resultHaving all of these functions for data extraction, we just need to add them to the place we designated earlier to finish up our code.
def extract_flight_information_from_soup(soup_of_the_whole_page):
flight_listings = soup_of_the_whole_page.find_all('li','pIav2d')
flights = []
for listing in flight_listings:
if listing is not None:
price = get_price(listing)
time = get_time(listing)
airline = get_airline(listing)
flight = {
"airline": airline,
"time": time,
"price": price
}
flights.append(flight)
return flightsIf we add all of it together, the final product should look something like this.
from bs4 import BeautifulSoup
import requests
import json
def get_price(soup_element):
price = soup_element.find('div','BVAVmf').find('div','YMlIz').get_text()
return price
def get_time(soup_element):
spans = soup_element.find('div','Ir0Voe').find('div','zxVSec', recursive=False).find_all('span', 'eoY5cb')
time = ""
for span in spans:
time = time + span.get_text() + "; "
return time
def get_airline(soup_element):
airline = soup_element.find('div','Ir0Voe').find('div','sSHqwe')
spans = airline.find_all('span', attrs={"class": None}, recursive=False)
result = ""
for span in spans:
result = result + span.get_text() + "; "
return result
def save_results(results, filepath):
with open(filepath, 'w', encoding='utf-8') as file:
json.dump(results, file, ensure_ascii=False, indent=4)
return
def get_flights_html(url):
payload = {
'source': 'google',
'render': 'html',
'url': url,
}
# Get response.
response = requests.request(
'POST',
'https://realtime.oxylabs.io/v1/queries',
auth=('username', 'password'),
json=payload,
)
response_json = response.json()
html = response_json['results'][0]['content']
return html
def extract_flight_information_from_soup(soup_of_the_whole_page):
flight_listings = soup_of_the_whole_page.find_all('li','pIav2d')
flights = []
for listing in flight_listings:
if listing is not None:
price = get_price(listing)
time = get_time(listing)
airline = get_airline(listing)
flight = {
"airline": airline,
"time": time,
"price": price
}
flights.append(flight)
return flights
def extract_flights_data_from_urls(urls):
constructed_flight_results = []
for url in urls:
html = get_flights_html(url)
soup = BeautifulSoup(html,'html.parser')
flights = extract_flight_information_from_soup(soup)
constructed_flight_results.append({
'url': url,
'flight_data': flights
})
return constructed_flight_results
def main():
results_file = 'data.json'
urls = [
'https://www.google.com/travel/flights?tfs=CBsQAhooEgoyMDI0LTA3LTI4agwIAxIIL20vMDE1NnFyDAgCEggvbS8wNGpwbBooEgoyMDI0LTA4LTAxagwIAhIIL20vMDRqcGxyDAgDEggvbS8wMTU2cUABSAFSA0VVUnABemxDalJJTkRCNVRGbDBOMU5UVEdOQlJ6aG5lRUZDUnkwdExTMHRMUzB0TFMxM1pXc3lOMEZCUVVGQlIxZ3dhRWxSUVRoaWFtTkJFZ1pWTWpnMk1qSWFDZ2lRYnhBQ0dnTkZWVkk0SEhEN2VBPT2YAQGyARIYASABKgwIAxIIL20vMDRqcGw&hl=en-US&curr=EUR&sa=X&ved=0CAoQtY0DahgKEwiAz9bF5PaEAxUAAAAAHQAAAAAQngM',
'https://www.google.com/travel/flights/search?tfs=CBwQAhooEgoyMDI0LTA3LTI4agwIAxIIL20vMDE1NnFyDAgDEggvbS8wN19rcRooEgoyMDI0LTA4LTAxagwIAxIIL20vMDdfa3FyDAgDEggvbS8wMTU2cUABSAFwAYIBCwj___________8BmAEB&hl=en-US&curr=EUR'
]
constructed_flight_results = extract_flights_data_from_urls(urls)
save_results(constructed_flight_results, results_file)
if __name__ == "__main__":
main()By employing Python and Oxylabs Web Scraper API, you can easily deal with the dynamic nature of Google Flights and gather public data successfully.
Read More Google Scraping Related Repositories: Google Sheets for Basic Web Scraping, How to Scrape Google Shopping Results, Google Play Scraper, How To Scrape Google Jobs, Google News Scrpaer, How to Scrape Google Scholar, How To Scrape Google Images, Scrape Google Search Results, Scrape Google Trends