Using the Linked List Data Structure in Python
We're almost at the end of the line with this series, having mastered all the Linear Data Structures in Python. To finish things off, we have the most sophisticated Linear Data Structure, the mighty Linked List. 😏
As the meme says, the head is the most integral part of the linked list!
Well, the Linked List is not as sophisticated as you think. It's extremely powerful though.
For more background on the different types of data structures in Python, check out the following articles:
Table of Contents
- Linked List: Introduction
- Uses of Linked Lists
- Implementing Linked Lists
- Practice Linked Lists
- Conclusion
Linked List: Introduction
A Linked List is a linear data structure. They are a sequence of data, connected together by links or pointers.
Linked Lists are a chain of nodes, connected together by links. Every node (fundamental block of a linked list) contains the following fields:
- Data -> The item to be stored in the node.
- Next -> The link or reference to the next node.
In a linked list, the first node is called the head and the last node is determined by the condition that the next points to a null value.
Uses of Linked Lists
- Due to their dynamic size allocation and ease of insertion/deletion, linked lists are applied in a lot of use cases.
- They're used to implement a lot of complex data structures like the adjacency list in graphs.
- They are used for lifecycle management in operating systems.
- A playlist in a music application is implemented using a doubly linked list.
- Blockchain, a complex data structure that is used for cryptocurrencies and ledgers use a linked list at their core.
Implementing Linked Lists
There are two main types of Linked Lists:
- Singly Linked Lists
- Doubly Linked Lists
Singly Linked Lists
In the following example, we'll implement a singly linked list from scratch in Python. This contains the following methods:
ll.search(head, data)-> Search the given element in the Linked List.ll.print_list()-> Print the linked list.ll.size()-> Return the length of the linked list.ll.insert(ele)-> Insert the given node into the linked list.ll.delete(data)-> Delete the given element from the linked list.
class Node(object):
def __init__(self, data):
self.data = data
self.next = None
# Class to create a Linked List
class LinkedList(object):
def __init__(self, head=None):
self.head = head
# Search an element and print its index
def search(self, head, data, index):
if head.data == data:
print (index)
else:
# Make recursive calls
if head.next:
return self.search(head.next, data, index+1)
else:
raise ValueError("Node not in linked list")
# Print the linked list
def print_list(self):
if self.head == None:
raise ValueError("List is empty")
current = self.head
while(current):
print (current.data, end=" ")
current = current.next
print ('\n')
# Find length of Linked List
def size(self):
if self.head == None:
return 0
size = 0
current = self.head
while(current):
size += 1
current = current.next
return size
# Insert a node in a linked list
def insert(self, data):
node = Node(data)
if not self.head:
self.head = node
else:
node.next = self.head
self.head = node
# Delete a node in a linked list
def delete(self, data):
if not self.head:
return
temp = self.head
# Check if head node is to be deleted
if head.data == data:
head = temp.next
print ("Deleted node is " + str(head.data))
return
while(temp.next):
if (temp.next.data == data):
print ("Node deleted is " + str(temp.next.data))
temp.next = temp.next.next
return
temp = temp.next
print ("Node not found")
return
Doubly Linked Lists
A doubly linked list is similar to a singly linked list. It differs in that it also contains a link to the previous node.
We implement the following methods for the Doubly Linked List data structure:
dll.addNodeLast(x)-> Adds a node at the right end of the linked list.dll.insertNode(pos, x)-> Adds a node at the position specified.dll.removeNode(x)-> Removes the specified node.dll.showReverse()-> Prints the linked list in reverse.dll.show()-> Prints the linked list.
class Node:
def __init__(self, val):
self.value = val
self.next = None
self.prev = None
class DoublyList:
def __init__(self, val):
self.head = Node(val)
self.tail = self.head
def addNodeLast(self, val):
current = self.head
while current.next != None:
current = current.next
newNode = Node(val)
current.next = newNode
newNode.prev = current
self.tail = newNode
def insertNode(self, val, newVal):
if self.tail.value == val:
self.addNodeLast(newVal)
elif self.head.value == val:
newNode = Node(newVal)
newNode.next = self.head.next
newNode.prev = self.head
newNode.next.prev = newNode
self.head.next = newNode
else:
current = self.head.next
while current.value != val:
current = current.next
newNode = Node(newVal)
newNode.next = current.next
newNode.next.prev = newNode
newNode.prev = current
current.next = newNode
def removeNode(self, val):
if self.head.value == val:
self.head = self.head.next
self.head.prev = None
elif self.tail.value == val:
self.tail = self.tail.prev
self.tail.next = None
else:
current = self.head.next
while current.value != val:
current = current.next
current.prev.next = current.next
current.next.prev = current.prev
def showReverse(self):
current = self.tail
while current != None:
print(current.value)
current = current.prev
def show(self):
current = self.head
while current != None:
print(current.value)
current = current.next
Practice Linked Lists
First, try implementing the Linked Lists as shown above, and then try running them. Once you've mastered the implementation, try the given problem-sets to master linked lists.
- Merge Two Sorted Lists - LeetCode
- Remove nth Node from the End of the List - LeetCode
- Rotate List - LeetCode
- Palindrome Linked List - LeetCode
- Construct a Doubly Linked List from 2D Matrix - GeeksforGeeks
- Reverse a Doubly Linked List - GeeksforGeeks
Conclusion
Linked Lists can be a little intimidating, but once you understand them you'll find it easy to understand trees, graphs, and other such data structures! Congratulations, you have mastered linear data structures by the end of this article series.
