As we all know, Python is growing rapidly, so there are many topics that we need to learn that are very basic and everyone should know, so in this blog, we will discuss what is linked list in Python and how it works and functions applied on linked list.
As a student, you have heard many basic fundamentals that you should learn, for example, data types, strings, arrays, sorting techniques, tuples in python, etc. In this, we will focus on a linked list in python. So let us start with the basics.
What is a Linked List?
A linked list in python is stored as a linear data structure that does not store data in contiguous memory locations like arrays of data items connected by links. Each node in a linked list in Python has a data field and a reference to the next node in the linked list. Each element in linked is referred to as a node, and pointers are used to connect them. The head is the first node in the linked list.
The linked list’s size is variable. So, unless the device has enough storage, we can have an unlimited number of nodes. There are two sorts of linked lists, and we’ll go over them one by one in this tutorial.
A linked list in python is a chain of the node, and each node contains the data and address or reference of the next node. The starting point of the linked list is called the head, which stores the reference of the first node.
The Head of the linked list in python
The ‘head node,’ or top node in the list, is the initial architectural item of the linked list. Because there are no nodes in the list when it is first created, the Head is set to None. (Note that the linked list doesn’t always need a node to start, and if one isn’t provided, the head parameter will default to None.)
Singly Linked List in python
A single pointer connects the next node in a singly linked list to the next node in the linked list in python. Every node in the linked list must have its data and pointer stored. The next pointer in the linked list’s last node is null, which represents the linked list’s end.
Some Features of Singly Linked List
- The dataset’s header will always point to the first data element, and each node will contain data and links to the following data element.
- The last node’s link is empty.
- Because the data items may only be accessed in one direction, from start to last, this list is a one-way chain. It is not feasible to navigate through the dataset in the opposite direction.
- Any data element in this list can’t be retrieved at random. Therefore we’ll have to go from the first node to the last one by one.
What is a node in a python linked list?
A node is a linked list object with a data field and a pointer to another node. We can say that a node is the following diagram that depicts the basic structure of a node.
Doubly Linked List in Python
It is easier to implement a singly linked list or a linked list, but traversing it in reverse is much more difficult. To overcome this, we can use a Doubly LinkedList, in which each node takes an additional pointer to point the previous node to the element and the pointer for the next node.
Iteration is more efficient in a doubly-linked list in python especially if you need to repeat in reverse, and deletion of specific nodes is more efficient.
To summarise, a doubly linked list is a more complicated linked list in which each node carries a pointer to the previous and next node in the series. A node in a doubly-linked list thus has node data, a pointer to the next node (next pointer), and a pointer to the prior node (previous pointer) (previous pointer).
Features of Doubly linked list in python
- As in the singly linked list, each data node has actual data and two connections, the Previous link to connect to the previous node and the following link to connect to the next node.
- The preceding link will be null for the first node, and the following link will be null for the last node.
- It is possible to navigate in both forward and reverse directions, and data can be read from the beginning to the end or from the end to the beginning. However, random access is not possible.
Some of the functions used for python linked list
This insert method takes some data, creates a new node with it, and adds it to the list. You may technically insert a node anywhere in the list, but the simplest way is to put it at the top and point the new node at the old one (sort of pushing the other nodes down the line).
The size method is quite straightforward; it simply counts nodes until it runs out and then returns the number of nodes found. The procedure begins at the top node and proceeds down the line of nodes until it reaches the end (at which point the current will be None), keeping track of how many nodes it has seen.
Search is similar to size, except that instead of traversing the entire list of nodes, it checks at each stop to determine if the current node has the desired data, and if it does, it returns the node that holds that data. If the method searches the entire list and still doesn’t find the data, it returns a value error and informs the user that it isn’t in the list.
You’ll be pleased to learn that delete and search are extremely similar! The delete function explores the list similarly to search, except instead of maintaining track of the current node. When the delete method reaches the node it wants to delete, it looks at the previous node it visited (the ‘prior’ node) and resets its pointer to point to the next node in line rather than the soon-to-be-deleted node. The unlucky node that is being erased is essentially gone from the list because no nodes point to it!
Let us Consider Some important differences
The distinction between a singly linked list and a circular singly linked list is as follows:
- The memory address of the first node is constantly updated in the link in the last node.
- It turns circular, making it easier to navigate across the data pieces.
- There is no first node or last node in this list, strictly speaking.
The distinction between a circular doubly linked list and a doubly-linked list is.
- The memory address of the first node is constantly updated in the following link in the last node.
- The memory address of the last node is constantly updated in the last link in the first node.
- Data can be accessible in any order, from any location to any other location.
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In this blog, we’ve covered the linked list and two forms of linked list in Python, singly and doubly-linked lists. Although Linked Lists can be scary at first, once you understand them, you’ll find that trees, graphs, and other data structures become much easier to comprehend! Keep an eye out for additional Python-related blogs in the future.
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FAQ’s (Frequently Asked Questions)
Why do we utilize linked lists in the first place?
When we compared to alternative linear data structures, linked lists have many significant advantages. They are a dynamic data structure that may be resized at runtime, unlike arrays. In addition, the insertion and deletion processes are quick and simple to apply.
Is it true that a linked list is faster than an array?
A linked list is much faster than an array at adding and removing entries. In a linked list and an array, iterating through the list one by one is about the same time, but obtaining one specific member in the middle is much faster in an array.