Notice: While JavaScript is not essential for this website, your interaction with the content will be limited. Please turn JavaScript on for the full experience.

Python Success Stories

Introduction began as an online travel site under the domain name which catered to the traveler looking to make online flight, hotel and car reservations. As our customer base grew we started seeing a need to allow our customers to report on their journeys in the form of travel reviews, blogs, sharing photos and other post trip needs. While we've continued to develop and improve our online booking engines and related systems that communicate with large Global Distribution Systems (GDS), as well as directly to suppliers' Central Reservation Systems (CRS), we've now developed a social network to support the growing travel consumer generated content niche.

Booking Systems

Most GDS's were built in the late 1960's and early 1970's and are mainframe based OLAP systems that handle millions of transactions per day. GDS's work incredibly well and are testament to the skill of the early developers that built them, but they have severe limitations when it comes to the data that can be entered into them, and the formats that the data is allowed to take. Although some CRS's used by individual suppliers are more modern, they inherit many of the limitations of the GDS's as a result of their tight data-level integration with them.

This is a problem when using these systems in the context of a web-based applications like Also, GDS's are not relational systems and lack a query language like SQL, so queries are limited by the API provided by its developers.

During the past 4 years our online processing systems have been developed in Java because many of the GDS's provide a low level Java or C API, and most of our developers have experience building J2EE applications. While Java is a great language for building a large web presence with persistent data, many aspects of our development would quickly become unmanageable and prohibitively expensive using Java alone. Python and Jython are used instead for many of the day to day integration tasks and the large amount of data "cleaning" that are required to provide customers with a user-friendly interface.

Green Screens

The travel industry is much like the financial industry in that "screen scraping" is often required to integrate older systems that provide no interface other than the textual screen interface used by its original human users.

Screen scraping makes heavy use of text processing tools, regular expressions, and string manipulation, all of which are built into Python and are very easy to work with. Python also provides the ability to communicate easily with other operating system processes, which made it possible to leverage external tools like sed and awk for the processing tasks This flexibility in choosing the right tool for the job was critical to the rapid development of the custom screen scrapers needed to interface to the very many unique travel supplier's systems. uses Python's OO aspects heavily and has built an extensive class library that allows new developers to come up to speed quickly when working on new GDS data access tasks.

Text, Text, Text

Text processing is where Python really shines for us. Almost all the data handled at is text-based. From screen scraping GDS data to data mining vendors' websites, Python tools munge text day in and day out, and have yet to run into any problems with the language or it's performance. For these tasks, Python is fast.

One of the tools currently being worked on is a localization system that allows generation of localized versions of hotel property descriptions without requiring human translators for every one of the 100,000 hotels in the network. This tool will increase market size 10 fold, and is a project that is coming along much faster than anticipated. Python's text processing capabilities helped make it possible to build a solution with much higher productivity per man hour than would have been possible using Java as the development language.

Web Services To The Rescue

In the past year or so, the larger suppliers have been slowly rolling out Web services for some of their products and services. These also work seamlessly with our Python code. The XML processing tools in Python are, like everything else included with Python, well thought out, spec compliant, and powerful. often builds automated test suites in Python, in order to validate a new supplier Web service before rolling it into its web presence. Python's rapid development times and capacity for automating this kind of testing makes it possible to quickly find and work around bugs in the supplier's code, resulting in a more a robust web application.

Social Network

Building a social network for travelers was not a trivial paradigm shift for us. We researched the current crop of social communities to try and find a blend of features that would best suit our customer base. During R&D we used Python's rapid development capabilities extensively to get an idea of which features were feasible within our development timeline. Python once again shined for us during this transition. Large data sets had to be shuttled between systems during the creation of our new database model and Python proved it's mettle by allowing rapid development, testing and implementation of our back end systems.

Why Python?

The author originally came across Python in 1999 while working on a large Java-based website. Like many developers new to Python, the use of indentation to indicate program structure was a stumbling block during this initial contact and Python was not adopted for use with that project. On second look, after actual experience with the language, the language's indentation-defined structure became a virtue, an important part of the overall power and simplicity of the language.

In addition to Python's clean design, the following factors make Python a good choice for enterprise integration tasks, like those undertaken at

  • OS Independence - The ability to develop code on one operating system, email it to a travel suppliers IT group, and have it work seamlessly on another operating system has been a godsend in deploying and maintaining the many components of
  • Database Integration - Python's database tools are top notch, allowing for quick and painless development of data mining tools in a matter of hours, rather than the days or weeks it would take in a language like Java.
  • Batteries Included - Except for a few database libraries and domain-specific libraries developed in-house, almost everything needed by developers is included in the Python distribution. Nevertheless, Python has managed to avoid the bloat seen in many other languages.
  • Community - The Python community is fantastic. The amount of online technical information available for Python is vast. A good internet search engine will almost always find the answers a developer needs, any time of the day or night. In those cases where developers have had questions not answered by a web search, for example about the LDAP library or a database library, the developers of those projects have always been willing to provide an answer quickly. This has been invaluable as a time saver, and in keeping development costs down.
  • Jython - Jython is an implementation of Python that is written in Java and runs on the Java Virtual Machine. It provides a powerful tool for scripting Java, and a more productive way to develop components for use in a Java system. For, Jython has bridged the gap between the front-end Java-based web systems and the back-end Python tools that do much of the heavy lifting.


One unexpected bonus discovered in the 4 years has been using Python is its support for new developers and interns, and its ability to make existing code more approachable and maintainable. Python has exhibited an uncanny ability to teach and encourage good coding skills, enabling developers to write clear and concise code. Python is very well designed, and this quality tends to transfer into the software that is written with it.


Python has helped in countless ways. It has reduced costs by speeding development time, improved integration with myriad suppliers, provided a solid backbone to the behind-the-scenes development that continues to strengthen, and made it possible to meet the many goals faced as the business has grown. Without Python, would not be as successful in the online travel space as it has been in such a short period of time.

About the Author

Michael Engelhart is the CTO and lead software engineer for He previously worked at Apple computer as senior software engineer for worldwide corporate travel, and has been a travel technology consultant to several major travel industry suppliers over the past 10 years.