Flight information scraping is the automation of the extraction of data from flight-related websites, through a tool developed for the purpose of extracting. This method can be used to extract key details on flight schedules, ticket prices, and availability using real-time data for analysis.
For a foundational understanding of web scraping and to explore its various applications across different industries, be sure to visit our comprehensive guide on web scraping.
There are several popular flight aggregation websites from which flight data can be scraped, with the three top ones being:
- Google Flights: a major source of aggregated flight data, providing information from multiple airlines.
- Skyscanner: another widely used platform that helps travelers search for flights, hotels, and car rentals.
- Expedia: a comprehensive travel booking platform, offering detailed flight data alongside other travel services.
These sites have a multitude of data that can be useful for businesses and individuals alike. It is possible to extract information on flight schedules including detailed departure and arrival times for flights, or sales volumes to provide information about the volume of tickets sold and demand over any particular route.
Through scraping, businesses can also collect information about customer reviews and ratings for various airlines. Some scrapers can even scrape carbon emissions and environmental information, allowing users to make choices about flight bookings with the environment in mind.
Datamam, the global specialist data extraction company, works closely with customers to get exactly the data they need through developing and implementing bespoke web scraping solutions.
Datamam’s CEO and Founder, Sandro Shubladze, says: “Flight scraping is a powerful means for companies to derive real-time critical data that will drive smarter decisions in the travel industry. The key to success lies in how the data is used to bring efficiency in pricing, customer satisfaction, and operations.”
Why scrape flight data?
Flight data scraping can be useful for travel agencies, businesses, and individual travelers, giving them access to insights that empower them to make decisions in the competitive market. Some of the key reasons to scrape flight information are as follows:
Price monitoring and comparison
Airlines constantly adjust their prices concerning demand, and external factors like fuel prices. By scraping flight pricing data, businesses can quickly react to fluctuations, while travel agencies can provide better services in terms of offering their clients the best available deals. Individuals can benefit from being informed about price shifts to make smarter decisions while booking.
Scraping flight information gives the capability to pursue and compare prices from several airlines or booking platforms. Companies and travelers can make use of this data to lock in the best deals related to flying or hotels.
By scraping platforms like Google Flights or Skyscanner, users can track prices over time, pinpoint the most economical tickets, and book at the perfect time.
Market research
It is possible to scrape travel patterns, the peak travel seasons, and the popular routes over time. This is not only essential to airlines but also to the hospitality and tourism industries.
For example, a hotel might use flight data to identify where there will be an increase in visitors going forward and price and prepare accordingly to meet demand.
Competitor analysis
Most airlines offer special deals and promotions quite frequently. Scraping can give travelers immediate access to promotions, so they don’t miss any opportunities, and other airlines and travel agencies can update to offer competitive prices.
Web scraping gives airlines meaningful insights into their competitors’ pricing strategies, flight scheduling, and how they manage popular routes.
The data may be used to make necessary changes in pricing, adjusting schedules, or adding new routes. Since the accessed data is real-time, airlines will remain competitive and have a better positioning in the market.
Optimizing flight schedules
Scraping flight data can enable airlines to optimize their scheduling. By integrating booking trends, demand, and competitor schedules, for example, carriers are better placed to make informed decisions on adjusting flight frequencies or adding new routes, or discontinuing those that are poorly performing.
If you’re working with large online catalogs or product listings, you might also be interested in our article on product information scraping
Sandro says: “Scraping flight data gives businesses a competitive advantage. It’s not just about gathering data; it’s about using it to stay ahead in a fast-moving market.”
What do I need to consider before I scrape flight details?
Before extracting any kind of flight information, the legal and ethical aspects must be considered. Most flight booking websites and platforms have explicit terms of service that restrict scraping activities, and violation of these guidelines could lead to legal consequences.
One way to make sure all flight data is obtained legally and with adherence to the rules is by the use of Application Programming Interfaces (APIs). APIs allow legal access to flight information without violating a website’s terms of service, affording an efficient means of obtaining data on flight schedules, prices, and availability without directly scraping from the website.
Some of the most commonly used APIs for flight data include:
- Amadeus API: Provides global travel data and flight schedules.
- Skyscanner API: Offers data on flights, hotels, and car rentals.
- FlightAware API: Focuses on live flight tracking and aviation data.
- kiwi.com API: Delivers flight booking and price comparison data.
- Aviationstack API: Provides real-time flight status and aviation data.
By using these APIs, you can collect accurate, up-to-date flight data while staying within legal boundaries. Take a look at our article for more on API scraping.
Sandro says: “Using official APIs not only ensures compliance but also provides reliable, structured access to the data you need.
How can I scrape flight details?
Scraping flight details requires a structured and methodical approach. Below is a step-by-step guide to help you get started with scraping flight data efficiently and ethically.
1. Set up and planning
Before beginning the scraping project, take a moment to reflect on what you need. Which data is most useful to scrape from the website – is it most useful to get the time of flights, the price of separate tickets, or seat availability?
Ensure that the project complies with the law, as well as the terms of services for the website you are looking to scrape. Read our article for more on ethical web scraping.
2. Install relevant libraries
Before you start, you will need the proper tools. Python is one of the most frequently used languages because it has powerful libraries that are ideal for web scraping. Check out our article for more information about how Python is used in web scraping.
You should also install Python libraries like BeautifulSoup, which parses HTML, and Selenium, an interaction driver with dynamic sites.
3. Extract data
After setting up the libraries, the next process is data extraction. Assuming that one is scraping Skyscanner or Google Flights, tools such as Selenium can scroll through results pages, click buttons, or load more results.
As an example:
from selenium import webdriver
from bs4 import BeautifulSoup
driver = webdriver.Chrome()
driver.get("https://www.skyscanner.net")4. Parse the data
You will then parse specific HTML tags using libraries like BeautifulSoup to extract the data you are interested in.
Ensure the data is structured somehow in a useful way, whether text, numbers, or links. You can go ahead and organize the parsed data into a structured file format like CSV or JSON format for storage with ease.
soup = BeautifulSoup(driver.page_source, 'html.parser')
# Extract flight details
flights = soup.find_all('div', {'class': 'flight-details'})
for flight in flights:
print(flight.text)5. Handling anti-scraping measures
Most of the flight-booking websites have anti-scraping to keep their data safe, which includes CAPTCHAs, rate limiting, and IP blocking. These can be countered with rotating proxies, delays between requests, and handling of CAPTCHAs with third-party services.
If engaging in this, is very important to respect the rate limit for ethical scraping reasons and not overload the server with too many requests. For more on this, read our article on common anti-scraping techniques.
6. Storage and analysis
The final stage is data summarizing. You can save the extracted flight data into a database, a CSV, or in JSON-whichever that fits your needs.
import pandas as pd
import json
# Save data in CSV format
df = pd.DataFrame(flight_data)
df.to_csv('flight_data.csv', index=False, encoding='utf-8')
# Save data in JSON format
with open('flight_data.json', 'w') as json_file:
json.dump(flight_data, json_file, indent=4)Sandro says: “Scraping flight data is a complex process that requires careful planning and the right tools. Using libraries like Selenium and BeautifulSoup can streamline the extraction process, but always consider APIs for a more reliable and legal approach.”
What are the challenges of scraping flight data?
Although flight data scraping offers rich insights there are also some challenges to consider, from technical problems to legal and ethical issues.
One of the most significant challenges in scraping flight data is that the content is dynamic. Prices, availability, and schedules change very frequently and websites like Google Flights and Skyscanner load information with dynamic elements like JavaScript, which makes traditional scraping harder.
The constantly updating information makes any data gathered susceptible to becoming outdated, and scrapers would have to be run frequently and efficiently to capture the most up-to-date information.
Scraping of flight data is very resource-intensive and can get costly. Gathering information from various sources and handling high-volumes of data can typically drive up the cost of operation, as can infrastructure maintenance.
The other challenge is scalability. Scraping any few flight details for personal use can be straightforward, but when businesses need to scrape high volumes over various sources, it can be more difficult.
Handling volume, store information, and process that information for analysis takes proper planning with correct technical resources. Process management is complex, which can cause bottlenecks.
Sandro says: “Scraping flight data presents unique challenges, from handling dynamic content to dealing with anti-scraping measures.”
“At Datamam, we help businesses navigate these hurdles by offering scalable, efficient solutions that ensure access to real-time data while staying compliant with legal guidelines.”
At Datamam, we take pride in our ability to solve flight data scraping problems. Our team dynamically constructs scalable solutions that get through anti-scraping mechanisms and process large volumes of data. We go out of our way to ensure you receive reliable, timely data using the best tools and technologies without sacrificing affordability and legal compliance.
By partnering with Datamam, businesses can not only navigate the complexities associated with web scraping but also maximize the potential benefits it has to offer. For more information on how we can assist with your scraping needs, contact us.
