Does Python Have a Tree Data Structure?


Heather Bennett

Python is a versatile programming language that offers a wide range of data structures to cater to various needs. One common question that often arises is whether Python has a built-in tree data structure. In this article, we will explore this topic in detail and shed light on the possibilities of using trees in Python.

Understanding Trees

Before delving into Python’s tree data structure, let’s take a moment to understand what a tree is. In computer science, a tree is an abstract data type that represents hierarchical relationships between elements. It consists of nodes connected by edges, with one node being designated as the root.

Types of Trees in Computer Science

In computer science, there are several types of trees commonly used for different purposes. Some popular ones include:

  • Binary Trees: These trees have at most two children for each parent node – a left child and a right child.
  • Binary Search Trees: Similar to binary trees, these trees follow specific ordering rules such as the left child being smaller than the parent and the right child being larger.
  • Balanced Trees: These trees maintain balance by ensuring that the heights of their subtrees are not significantly different.
  • B-Trees: These trees are commonly used in databases and file systems due to their efficient search and insert operations.

Trees in Python

While Python does not have a built-in tree data structure like it has for lists or dictionaries, it provides ample support through its rich standard library and other external libraries.

One approach to implementing a tree in Python is by using classes and object-oriented programming. We can define a Node class representing each node in the tree and use references between nodes to establish relationships.

Here’s an example implementation of a simple binary tree in Python:

class Node:
def __init__(self, data): = data
self.left = None
self.right = None

# Create root node
root = Node(‘A’)

# Create child nodes
root.left = Node(‘B’)
root.right = Node(‘C’)

# Accessing the tree nodes
print( # Output: ‘A’
print( # Output: ‘B’
print( Output: ‘C’

While this implementation is basic, it demonstrates the concept of building a tree structure using classes in Python.

Another option is to utilize external libraries such as the `anytree` library. The `anytree` library provides a flexible and powerful way to create, manipulate, and traverse trees in Python.

To use `anytree`, you can install it using pip:

pip install anytree

Here’s an example of creating a binary tree using `anytree`:

from anytree import Node, RenderTree

# Create nodes
root = Node(“A”)
b_node = Node(“B”, parent=root)
c_node = Node(“C”, parent=root)
d_node = Node(“D”, parent=b_node)

# Print the tree structure
for pre, fill, node in RenderTree(root):

# Output:
# A
# ├── B
# │ └── D
# └── C


As you can see, `anytree` simplifies the process of creating and visualizing trees in Python.


While Python does not have a built-in tree data structure like some other programming languages, it offers various ways to implement and work with trees effectively. By utilizing classes and object-oriented programming or leveraging external libraries like `anytree`, you can create and manipulate trees to suit your specific needs.

Remember, trees are a powerful data structure for organizing hierarchical relationships, making them valuable in many areas of computer science and programming. With Python’s flexibility and rich ecosystem, you can harness the power of trees to solve complex problems efficiently.

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