Get a 1-month FREE trial of Bito’s AI Code Review Agent  
Get a 1-month FREE trial
of Bito’s AI Code Review Agent

Linked List Python: Python Explained

Table of Contents

Linked list is an essential topic in computer science and is used extensively in Python programming language. It is a data structure which contains information components and forms a linear ordering. Unlike other data structures like an array, linked list elements are not stored in contiguous memory. It also stores data more efficiently and has fewer memory overhead compared to other data types.

Introduction to Linked List in Python

Linked list is a linear data structure which resembles a chain. It is made up of sequence of nodes, each node has a data field, address field and pointer field. The data field stores the information of the node, the address or reference field stores the address of the succeeding node, and the pointer field links the preceding node and succeeding nodes. The nodes are relatively related, forming a chain-like structure; hence the name ‘Linked List’.

Linked lists are used to store data in a linear fashion, and are often used in applications such as databases, stacks, and queues. Linked lists are also used to implement dynamic data structures, such as linked stacks and linked queues. Linked lists are also used to implement graph algorithms, such as depth-first search and breadth-first search.

What is a Linked List?

A Linked List consists of nodes that are connected through links (or references) from one node to another. Each node consists of an element and a reference to the next element, thus forming a chain-like structure. The end of the list is marked by a tail node which contains null reference indicating the end of the list.

Linked Lists are often used in computer programming as they are a dynamic data structure, meaning that the size of the list can be changed as needed. This makes them a great choice for applications that require frequent insertions and deletions of data. Additionally, Linked Lists are often used to implement stacks and queues, which are important data structures in computer science.

Benefits of Using Linked List in Python

Linked List offers a number of advantages when compared to other data types in Python. The most significant benefit is that it is suitable for dynamic memory allocation. It eliminates chunks of unused memory. Secondly, linked lists are faster than arrays when it comes to adding and deleting elements as no shifting of elements is required in Linked List. Furthermore, Linked List has greater flexibility with regards to data moves. That is why it is a great tool for huge databases as well as for complex applications.

In addition, linked lists are more efficient in terms of memory usage as they only store the address of the next node, rather than the entire data set. This makes them ideal for applications that require large amounts of data to be stored. Furthermore, linked lists are easier to manipulate than arrays, as they can be easily traversed in both directions. This makes them ideal for applications that require frequent data manipulation.

Creating a Linked List in Python

Creating a linked list in Python is a straightforward process. You can create a Linked List by simply defining a class and adding functions for insertions, retrievals and display. Also, the fundamental component of a linked list is its node which consists of the element itself and a reference to the succeeding node. These classes and functions can be used to simply create and control the linked list.

When creating a linked list, it is important to consider the memory usage of the list. Linked lists are dynamic data structures, meaning that they can grow and shrink in size as needed. This makes them ideal for applications where the size of the data is not known in advance. However, this also means that linked lists can use more memory than other data structures, such as arrays, which have a fixed size.

Adding Elements to a Linked List in Python

Adding elements to a Linked List in Python requires two steps. Firstly, you need to create an instance of the Node class with the element passed as an argument, then attach it at the end of the linked list. To do this, look up until you reach the last node then set its next attribute to the newly created node.

It is important to note that when adding a new element to the linked list, the element must be of the same type as the other elements in the list. Additionally, the order in which the elements are added is important, as it will determine the order in which they are accessed when traversing the list.

Deleting Elements from a Linked List in Python

The process for deleting elements from a Linked List in Python is similar to adding elements. First you need to traverse the linked list until you encounter the element which needs to be deleted. Secondly, assign the reference of the predecessor node to its next attribute to the next of the current node. Finally, delete the current node.

It is important to note that when deleting a node from a linked list, the memory allocated to the node is not automatically freed. Therefore, it is important to manually free the memory allocated to the node after it has been deleted.

Traversing a Linked List in Python

To traverse a Linked List in Python, you need to follow along the chain of references from one node to another until you reach the tail node. The outward display of traversing a linked list resembles looping with either ‘while’ or ‘for’…‘in’ loop. Every element or value can be accessed with the help of this loop until you reach on its terminating condition.

It is important to note that the order of traversal is determined by the order of the nodes in the linked list. If the nodes are arranged in a certain order, then the traversal will follow that order. Additionally, the time complexity of traversal is O(n), where n is the number of nodes in the linked list.

Reversing a Linked List in Python

The process for reversing a linked list in Python involves traversing the linked list until you reach its tail node, building a new list with Nodes containing each traversed element in reverse order and switching reference between Links accordingly as each Node is built.

The process of reversing a linked list is a common operation in computer science and can be used to solve a variety of problems. It is important to understand the underlying principles of linked lists and how they are manipulated in order to successfully reverse a linked list in Python.

Conclusion

Linked List offers an efficient way of managing extensive data and maintaining flexibility and speed when adding, deleting and traversing elements compared to other data types in Python. It is also useful when dynamic memory allocation is needed making it suitable for large databases and complex applications. With its straightforward ways of creating, adding, deleting, traversing and reversing elements, Linked List is an essential part of computer science.

Linked List is a powerful data structure that can be used to solve a variety of problems. It is also a great tool for implementing algorithms such as sorting, searching, and graph traversal. Linked List is a versatile data structure that can be used in many different applications, from web development to game development.

Anand Das

Anand Das

Anand is Co-founder and CTO of Bito. He leads technical strategy and engineering, and is our biggest user! Formerly, Anand was CTO of Eyeota, a data company acquired by Dun & Bradstreet. He is co-founder of PubMatic, where he led the building of an ad exchange system that handles over 1 Trillion bids per day.

From Bito team with

This article is brought to you by Bito – an AI developer assistant.

Latest posts

Mastering Python’s writelines() Function for Efficient File Writing | A Comprehensive Guide

Understanding the Difference Between == and === in JavaScript – A Comprehensive Guide

Compare Two Strings in JavaScript: A Detailed Guide for Efficient String Comparison

Exploring the Distinctions: == vs equals() in Java Programming

Understanding Matplotlib Inline in Python: A Comprehensive Guide for Visualizations

Top posts

Mastering Python’s writelines() Function for Efficient File Writing | A Comprehensive Guide

Understanding the Difference Between == and === in JavaScript – A Comprehensive Guide

Compare Two Strings in JavaScript: A Detailed Guide for Efficient String Comparison

Exploring the Distinctions: == vs equals() in Java Programming

Understanding Matplotlib Inline in Python: A Comprehensive Guide for Visualizations

Get Bito for IDE of your choice