Tree Data Structures Explained Simply (With Real Python Examples)

Master tree data structures in Python with real-world examples, simple explanations, and code walkthroughs perfect for beginners and aspiring developers.

When you first start learning about data structures in computer science, you usually begin with things like arrays, lists, and dictionaries. These are simple, straight-line ways to store and work with data.

But in real life, not everything fits into a straight line. Think about your family tree, a company’s structure with bosses and employees, or how folders are organized on your computer.

These are all systems where things branch out from one main starting point. That’s what we call a hierarchy. To work with that kind of setup in programming, we use something called a Tree.

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In this article, I’m going to breakdown what tree structures are, when and why you’d use them, how they work, and how to build one in Python.

I’ll keep things easy by using clear examples, easy-to-follow code, and real-world comparisons. I’ll even walk through building a family tree step by step, so you can see how useful and straightforward it really is.

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What Is a Tree Data Structure?

Basically, it’s a way to organize information that starts at one main point—called the root—and then splits off into different parts. Each piece of data in the tree is called a node.

A node can have a bunch of smaller parts under it, which we call children. The very first node, the one everything else comes from, like I said is the root. And if a node doesn’t have anything under it—no children—it’s called a leaf.

An easy way to picture it is with a family tree. Imagine your grandpa at the top. He has two kids—your dad and your aunt. Then your dad has you, and your aunt has her kids. That’s a tree. Each person is a node, and the way they’re connected shows how the family is laid out.