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How-to-Extract-Airlines-and-Flight-Ticket-Pricing-Data-Using-Selenium-and-Python

In this blog post, we will learn how to extract airlines and flight ticket pricing data using Selenium, Python, and ChromeDriver.

Background

Are you stuck at home during the COVID-19 outbreak and passionate about traveling and data science? If so, you can combine these interests to your advantage by learning how to create a web scraper that can help you find cheap flights. This tutorial blog will focus on scraping Expedia data, one of the world's largest Online Travel Agencies (OTA). Expedia, owned and operated by Expedia Group, holds the top position in terms of earnings among travel companies.

However, it's essential to acknowledge that web scraping is generally against the terms of service of most websites, which means there's a risk of having your IP address banned from the website.

Please keep in mind that while web scraping can be a helpful tool, it's essential to respect website policies and legal boundaries. Always ensure that you're not violating any terms of service or infringing on anyone's rights when scraping data from websites.

Environment Arrangement

To effectively scrape airlines data, ensure that your Python environment has the following packages and drivers installed:

  • Selenium Package: Selenium is a widely used web browser automation tool that allows you to interact with websites programmatically.
  • ChromeDriver: ChromeDriver is a necessary driver that enables you to open a browser and perform tasks as if you were using it manually. It is specifically designed for Google Chrome.
  • DateTime package
  • Pandas Package

Scraping Approach

Before diving into the code, let's outline the web scraping strategy for this project. The strategy involves inserting the desired routes and dates into a CSV file. It is crucial to use the specific column names outlined below. It's important to note that the scraper is designed to work only for roundtrip flights.

Scraping-Approach

Run the complete code.

The result for every flight is the CSV file. The file name would be the date & time that data scraping was done.

All the flights of the same route would automatically be positioned by the flight price data scraper in a suitable folder (name of a route).

Sounds difficult? It is not! Let’s take an example.

These are extracted routes as given in a CSV file (data scraper makes folders automatically):

These-are-extracted-routes-as-given

You can see here multiple extracted dates in the route of Athens — Abu Dhabi:

You-can-see-here-multiple-extracted-dates

The screenshot here shows a sole CSV file given for every data extraction sample for route of Athens — Abu Dhabi. Its name shows the time and date that a web scraper has been performed.

The-screenshot-here-shows-a-sole-CSV

We hope that you are clear in your mind about the process!

Output Structures

Output-Structures

The scraper results will provide these data points:

  • Arrival Time
  • Departure Time
  • Airline
  • Airplane Types
  • Arrival Airport’s Name
  • Arrival Coach
  • Departure Airport’s Name
  • Departure Coach
  • Exact Time When Scraping Was Done
  • Flight Duration
  • Layovers
  • Price
  • Total Stops

In case, it’s not the direct flight, the web scraper will provide you extra information (airline name, airport, Etc.) for every connection.

Code

In the code section, we will observe the key parts of a code. You can get the complete code Here

Initially, one will have to import relevant libraries, describe a chrome driver and make round trip types.

Code

In the following step, you will make some functions with Selenium to get different features on a webpage. A function’s names suggest about the role.

In-the-following-step

Every flight row in CSV roads file goes over the given procedure:

Every-flight-row-in-CSV

Now, you can collect data online and insert that into Pandas DataFrame.

Now-you-can-collect-data-online

In the end, export data into a CSV file straight to the anticipated folder.

In-the-end-export-data-into-a-CSV-file

Conclusion

In summary, you have learned how to utilize the Selenium package to scrape flight prices from Expedia. By grasping the fundamentals, you can apply this knowledge to develop your web scraping tool for other websites.

As passionate travelers, you can leverage data science techniques to uncover incredible deals for enchanting destinations worldwide. Combining data science and a love for exploration allows for an exciting journey in finding the best travel opportunities. Happy traveling and data exploration!

For more information, contact Actowiz Solutions. You can also call us for all your mobile app scraping or web scraping service requirements.

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