Expressing Nodes in Python

This trippy graphic brought to you by the Medium article “Visualizing Graphs in 3D with WebGL.”

This requires some knowledge with object-oriented programming in Python, which is a method that allows for structuring programs so that each property and behavior can be bundled into a single object. It’s pretty useful—check it out here. I’ll make a writeup on it soon.

A node in computer science is defined as a basic unit of a data structure. Many situations can be described with nodes:

• Your social network. You (a node) are connected with a friend (another node) who is also connected with their friend (another node) who may or may not be connected to Kevin Bacon

• You taking the London tube and want to get from your apartment in Borough to your 9:00 AM lecture at King’s College London. You hop onto a train from Borough Station (a node) and take it through Monument (another node) and Bank (another node) where you get off the train and get on a bus and pass Mansion House (another node) and eventually reach the Somerset House bus stop where it’s now 9:08 AM and you can’t get in because the lecturer has a strict policy of not letting anyone in 5 minutes after lecture starts. The worst.

• Your playlist. After a song (a node) finishes playing it’ll go to the next song (another node). If you have shuffle on, it’ll go to a random song (or a random node).

• Literally a tree.

Let’s kick off with the basics and define our Node object

class Node:
    def __init__(self, id=None):
        self.id = id
        self.nextNode = None

That’s pretty much the most basic form of a node we need to define. Now here’s how we implement this.

n1 = Node("A")
n2 = Node("B")
n3 = Node("C")

We instantiate three nodes: “A”, “B”, and “C”. These strings are passed in as each respective node’s identification (we can pass in anything else, but for simplicity’s sake let’s stick to strings for now).

Let’s say we want to describe this (directed) graph:

Here’s how we describe that.

n1.nextNode = n2
n2.nextNode = n3

Great! We’re done. But how can we verify that these nodes are connected?

We’ll need to transverse through the graph. We first define a starting node.

currentNode = n1

Great! Next, we transverse. While we are on a node, we are going to print the node ID and move on to the next node.

while currentNode:
    print(currentNode.id)
    currentNode = currentNode.nextNode

Done! When we run this, we should get the following output:

[OUT]:
A
B
C

Since we defined the default value of self.nextNode to be None, when we arrived at node C there were no more nodes available for us to move to. This is called a leaf node because, like a leaf, we have reached the end of that traversal. Thus, we broke out of the while loop.

Let’s try one more graph.

If you’ve been following through, you only need one more line to describe this.

n3.nextNode = n1

Let’s transverse through this. Remember, we need to set our starting node again.

currentNode = n1
while currentNode:
    print(currentNode.id)
    currentNode = currentNode.nextNode

[OUT]:
A
B
C
A
B
C
A
B
C
A
B
C
.
.
.

Ohhh nooooo you broke it. Just kidding. It’s supposed to loop indefinitely. If you did this in terminal, then break out of that loop by pressing CTRL + C.

There you have it—your (barely of an) intro to expressing and implementing nodes in Python.