Chapter 3: Data Structures Every Network Engineer Should Know

Understanding Data Structures for Network Engineers

When you start learning how to code, especially with the goal of automating networks, one of the first concepts that will shape the way you design your scripts and tools is data structures.

Data structures are the building blocks that help you organize, store, and work with information efficiently in your programs. Just like routing tables, interface lists, or neighbor states help structure information on a network device, data structures in programming are how you shape and make sense of the data your scripts will handle.

As a network engineer, you’ll deal with lots of structured information: IP addresses, interface states, device inventories, BGP sessions, routing tables, VLAN mappings, and your automation scripts will need a way to represent and process all of that. That’s exactly where data structures come in.

In this post, we’ll explore some of the most common data structures you’ll use when automating networks with Python and other languages. And we won’t just list them, we’ll tie each one to network-specific use cases so you can see how they show up in real-world tasks like parsing device configs, building interface maps, or validating routing behavior.

Let’s begin by understanding what these structures are, how they behave, and how they can help you think more clearly as you turn your engineering logic into clean, scalable automation code.

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