how-to-scrape-flight-schedules-from-expedia

How to Scrape Flight Schedules and Prices from Expedia.com using Python and LXML

Gathering data regarding flights is a mammoth task when done manually. There are hundreds of thousands of combinations of airports, routes, timings and ever changing prices. Ticket prices tend to vary daily (or even hourly), and there are a large number of flights available per day. Web Scraping is one of the solutions to keep track of this data. You could scrape data for any combinations of airports, timings, and flights and use this information to monitor and analyze ticket prices, pricing trends, cheap routes etc.

This tutorial is about scraping airline prices and schedules. You could scrape ticket prices, flight schedules, or even go a bit deeper and get flight prices per kilometer for each airline and plot amazing graphs.

In this tutorial, we will scrape Expedia.com, a leading travel booking website to extract details on flights. Our scraper will extract the flight schedules and prices for a source and destination pair.

Here is a list of fields that we will be extracting:

  1. Arrival Airport
  2. Arrival Time
  3. Departure Airport
  4. Departure Time
  5. Plane Name
  6. Airline
  7. Flight Duration
  8. Plane Code
  9. Ticket Price
  10. No of Stops

 

Below is a screenshot of some of the data we will be extracting

details-for-scraping-expedia

Scraping Logic

  1. Construct the URL of the search results from Expedia- Here is one for the available flights listed from New York to Miami –https://www.expedia.com/Flights-Search?trip=oneway&leg1=from:New%20York,%20NY%20(NYC-All%20Airports),to:Miami,%20Florida,departure:04/01/2017TANYT&passengers=children:0,adults:1,seniors:0,infantinlap:Y&mode=search
  2. Download HTML of the search result page using Python Requests.
  3. Parse the page using LXML – LXML lets you navigate the HTML Tree Structure using Xpaths. We have predefined the XPaths for the details we need in the code.
  4. Save the data to a JSON file. You can later modify this to write to a database.

 

Requirements

For this web scraping tutorial using Python, we will need some packages for downloading and parsing the HTML. Below are the package requirements.

  • Python 2.7 ( https://www.python.org/downloads/ )
  • PIP to install the following packages in Python (https://pip.pypa.io/en/stable/installing/ )
  • Python Requests, to make requests and download the HTML content of the pages ( http://docs.python-requests.org/en/master/user/install/).
  • Python LXML, for parsing the HTML Tree Structure using Xpaths ( Learn how to install that here – http://lxml.de/installation.html )

The Code

The code is self-explanatory.

 

If the embed above doesn’t work, you can download the code from the link here

Running The Scraper

Assume the script is named expedia.py. If you type in the script name in command prompt or terminal along with a -h

usage: expedia.py [-h] source destination date

positional arguments:
source            Source airport code
destination       Destination airport code
date              MM/DD/YYYY

optional arguments:
     -h, --help show this help message and exit

 

The arguments source and destination are the airport codes for the source and destination airports. The date argument should be in the format MM/DD/YYYY.

As an example, to find the flights listed from New York to Miami we would put the arguments like this:

python expedia.py nyc mia 04/01/2017

This will create a JSON output file called nyc-mia-flight-results.json that will be in the same folder as the script. 

The output file will look similar to this:

{
    "arrival": "Miami Intl., Miami",
    "timings": [
      {
        "arrival_airport": "Miami, FL (MIA-Miami Intl.)",
        "arrival_time": "12:19a",
        "departure_airport": "New York, NY (LGA-LaGuardia)",
        "departure_time": "9:00p"
      }
    ],
    "airline": "American Airlines",
    "flight duration": "1 days 3 hours 19 minutes",
    "plane code": "738",
    "plane": "Boeing 737-800",
    "departure": "LaGuardia, New York",
    "stops": "Nonstop",
    "ticket price": "1144.21"
  },
  {
    "arrival": "Miami Intl., Miami",
    "timings": [
      {
        "arrival_airport": "St. Louis, MO (STL-Lambert-St. Louis Intl.)",
        "arrival_time": "11:15a",
        "departure_airport": "New York, NY (LGA-LaGuardia)",
        "departure_time": "9:11a"
      },
      {
        "arrival_airport": "Miami, FL (MIA-Miami Intl.)",
        "arrival_time": "8:44p",
        "departure_airport": "St. Louis, MO (STL-Lambert-St. Louis Intl.)",
        "departure_time": "4:54p"
      }
    ],
    "airline": "Republic Airlines As American Eagle",
    "flight duration": "0 days 11 hours 33 minutes",
    "plane code": "E75",
    "plane": "Embraer 175",
    "departure": "LaGuardia, New York",
    "stops": "1 Stop",
    "ticket price": "2028.40"
  },

 

You can download the code at https://gist.github.com/scrapehero/bc34513e2ea72dc0890ad47fbd8a1a4f 

Let us know in the comments how this scraper worked for you.

Known Limitations

This scraper should work for extracting most flight details available on Expedia unless the website structure changes drastically. If you would like to scrape the details of thousands of pages at very short intervals, this scraper is probably not going to work for you. You should read  Scalable do-it-yourself scraping – How to build and run scrapers on a large scale and How to prevent getting blacklisted while scraping.

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Disclaimer: Any code provided in our tutorials is for illustration and learning purposes only. We are not responsible for how it is used and assume no liability for any detrimental usage of the source code. The mere presence of this code on our site does not imply that we encourage scraping or scrape the websites referenced in the code and accompanying tutorial. The tutorials only help illustrate the technique of programming web scrapers for popular internet websites. We are not obligated to provide any support for the code, however, if you add your questions in the comments section, we may periodically address them.

3 thoughts on “How to Scrape Flight Schedules and Prices from Expedia.com using Python and LXML

  1. This was an exciting tutorial as I am new to python, however I received the error below after running the code:

    Traceback (most recent call last):
    File “expedia.py”, line 100, in
    scraped_data = parse(source,destination,date)
    File “expedia.py”, line 24, in parse
    departure_location_airport = flight_data[‘legs’][i][‘departureLocation’][‘airportLongName’]
    KeyError: ‘airportLongName’

    I’m researching what this error message means, but if you all happen to know what the issue is, I would love to know myself! Cheers!

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