The header linked list is a list that has a header node at the beginning of the linked list. and the head always refers to the header node of the list.
and the linked part of the header node is always referred to as the first node of the linked list.


we can easily perform operations like insertion and deletion because we don't need to check if the list is empty or not.
What is Header Node
the info part of the header node is always None. therefor we can use this part to store some useful information about the linked list. like storing the number of nodes in a list and some of the value of linked list etc.and the linked part of the header node is always referred to as the first node of the linked list.

Advantages of Header linked list
If the list is empty then always the header node is available in the linked list. so we don't need to check whether the linked list is empty or not.
we can easily perform operations like insertion and deletion because we don't need to check if the list is empty or not.
Python program for Implementation of Header linked list
class Node(object): def __init__(self,value): self.info = value self.link = None class HeaderLinkedList(object): def __init__(self): self.head = Node(0) def display_list(self): if self.head.link == None: print("List is empty") return p =self.head.link print("List is : ") while p is not None: print(p.info, " ",end='') p = p.link print() def create_list(self): n = int(input("Enter the number of nodes : ")) for i in range(n): data = int(input("Enter the element to be inserted : ")) self.insert_at_end(data) def insert_at_end(self,data): temp = Node(data) p = self.head while p.link is not None: p = p.link p.link = temp def insert_before(self,data,x): p = self.head while p.link is not None: if p.link.info == x: break p = p.link if p.link is None: print(x, " not present in the list") else: temp = Node(data) temp.link = p.link p.link = temp def insert_at_position(self,data,x): p = self.head i = 1 while i <= k-1 and p is not None: p = p.link i += 1 if p is None: print("You can insert only upto ", (i-1), " th position") else: temp = Node(data) temp.link = p.link p.link = temp def delete_node(self,data): p = self.head while p.link is not None: if p.link.info == data: break p = p.link if p.link == None: print(data, " not found") else: p.link = p.link.link def reverse_list(self): prev = None p = self.head.link while p is not None: next = p.link p.link = prev prev = p p = next self.head.link = prev list = HeaderLinkedList() list.create_list() while True: print("1. Display list") print("2. Insert a node at the end of the list") print("3. Insert a node before a specified node") print("4. Insert a node at a given position") print("5. Delete a node") print("6. Reverse the list") print("9. Quit") option = int(input("Enter your choice : ")) if option == 1: list.display_list() elif option == 2: data = int(input("Enter the element to be inserted : ")) list.insert_at_end(data) elif option == 3: data = int(input("Enter the element to be inserted : ")) x = int(input("Enter the element before which to insert : ")) list.insert_before(data,x) elif option == 4: data = int(input("Enter the element to be inserted : ")) k = int(input("Enter the position at which to insert : ")) list.insert_at_position(data,x) elif option == 5: data = int(input("Enter the element to be deleted : ")) list.delete_node(data) elif option == 7: break else: print("Wrong option") print()
Also, read these posts
- What are Data Structures and algorithms
- Algorithm design and analysis
- Classification of algorithms
- How to calculate the running time of an algorithm.
- Worst Average and Best-case analysis of the algorithm.
- Big o notation
- Big o notation examples
- Linked List in Data Structures
- Traversing in Linked list
- Operations on the linked list
- Insertion in the linked list
- Deletion in a linked list
- Reversing a linked list
- Sorting a linked list
- Find and remove the loop in the linked list
- Doubly linked list
- Insertion in the doubly linked list
- Deletion in the doubly linked list
- Reversing a doubly linked list
- Circular linked list
- Insertion in the circular linked list
- Deletion in the circular linked list
- Merge two linked list
- Sorted linked list
- Stack in data structures
- Queue in data structures
- Circular queue
- Dequeue in the data structure
- Priority queue
- Polish notation
- Tree in the data structure
- Binary tree
- Array representation of the binary tree
- linked representation of a binary tree
- Traversing in the binary tree
- Inorder traversal in the binary tree
- Preorder traversal in the binary tree
- Postorder traversal in the binary tree
- Level order traversal in the binary tree
- Binary search tree
- Insertion in the binary search tree
- Deletion in the binary search tree
- Heap in data structures
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