Python Data Structure and Algorithm Tutorial – LinkedList Data Structure

In this tutorial, you will learn about linked list data structure and it’s implementation in Python.

A linked list data structure includes a series of connected nodes. Here, each node store the data and the address of the next node. For example,

You have to start somewhere, so we give the address of the first node a special name called HEAD.

Also, the last node in the linked list can be identified because its next portion points to NULL.

You might have played the game Treasure Hunt, where each clue includes the information about the next clue. That is how the linked list operates.

In just a few steps, we have created a simple linked list with three nodes.

The power of LinkedList comes from the ability to break the chain and rejoin it. E.g. if you wanted to put an element 4 between 1 and 2, the steps would be:

• Create a new struct node and allocate memory to it.
• Add its data value as 4
• Point its next pointer to the struct node containing 2 as the data value
• Change the next pointer of “1” to the node we just created.

Doing something similar in an array would have required shifting the positions of all the subsequent elements.

In python and Java, the linked list can be implemented using classes as shown in the codes below.

Lists are one of the most popular and efficient data structures, with implementation in every programming language like C, C++, Python, Java, and C#.

Apart from that, linked lists are a great way to learn how pointers work. By practicing how to manipulate linked lists, you can prepare yourself to learn more advanced data structures like graphs and trees.

Linked List Implementations in Python Examples

``````/* Linked list implementation in Python */

class Node:
/* Creating a node */
def __init__(self, item):
self.item = item
self.next = None

def __init__(self):

if __name__ == '__main__':

/* Assign item values */
second = Node(2)
third = Node(3)

/* Connect nodes */
second.next = third

/* Print the linked list item */
``````

Time Complexity

Worst case Average Case
Search O(n) O(n)
Insert O(1) O(1)
Deletion O(1) O(1)

Space Complexity: O(n)

• Dynamic memory allocation
• Implemented in stack and queue
• In undo functionality of software
• Hash tables, Graphs

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