.png)
DSA SERIES — LINKED LISTS IN PYTHON
1. Introduction to Linked Lists in Python
Although Python provides high-level dynamic structures like lists, DSA implementations require manual node-and-pointer-based linked lists to understand real system-level behavior.
A linked list stores data using node objects connected through references.
[DATA | NEXT] → [DATA | NEXT] → [DATA | NEXT] → None
2. Node Structure in Python
class Node:
def __init__(self, data):
self.data = data
self.next = None
3. Linked List Class (Head Pointer)
class LinkedList:
def __init__(self):
self.head = None
4. Basic Operations — Python Implementations
4.1 Insert at Beginning
def insert_at_beginning(self, data):
new_node = Node(data)
new_node.next = self.head
self.head = new_node
4.2 Insert at End
def insert_at_end(self, data):
new_node = Node(data)
if self.head is None:
self.head = new_node
return
temp = self.head
while temp.next:
temp = temp.next
temp.next = new_node
4.3 Insert at Given Position
def insert_at_position(self, data, pos):
new_node = Node(data)
if pos == 1:
new_node.next = self.head
self.head = new_node
return
temp = self.head
for _ in range(pos - 2):
if temp is None:
return
temp = temp.next
if temp is None:
return
new_node.next = temp.next
temp.next = new_node
4.4 Delete from Beginning
def delete_beginning(self):
if self.head is None:
return
self.head = self.head.next
4.5 Delete from End
def delete_end(self):
if self.head is None:
return
if self.head.next is None:
self.head = None
return
temp = self.head
prev = None
while temp.next:
prev = temp
temp = temp.next
prev.next = None
4.6 Delete at Position
def delete_at_position(self, pos):
if self.head is None:
return
if pos == 1:
self.head = self.head.next
return
temp = self.head
for _ in range(pos - 2):
if temp is None:
return
temp = temp.next
if temp is None or temp.next is None:
return
temp.next = temp.next.next
4.7 Search for a Value
def search(self, key):
temp = self.head
while temp:
if temp.data == key:
return True
temp = temp.next
return False
4.8 Display Linked List
def display(self):
temp = self.head
while temp:
print(temp.data, end=" → ")
temp = temp.next
print("None")
5. Time Complexity Analysis
| Operation | Time Complexity |
|---|---|
| Insert at Beginning | O(1) |
| Insert at End | O(n) |
| Insert at Position | O(n) |
| Delete Beginning | O(1) |
| Delete End | O(n) |
| Delete Position | O(n) |
| Search | O(n) |
6. Conceptual Notes — Python vs C Linked Lists
* Python does not use raw pointers
But object references behave like pointers.
* Memory is dynamically managed
Nodes are allocated on heap automatically.
* Garbage Collector handles freed nodes
No manual free() as in C.
* Still suitable for DSA practice
Students understand logical links, traversal, and node manipulation.
7. Professional Engineering Insights
-
Linked list is fundamental for understanding reference-based memory.
-
Useful for implementing:
-
Hash map chaining
-
Graph adjacency lists
-
Queues and stacks
-
-
Used internally in schedulers, memory blocks, and interpreters.
8. Common Mistakes in Python DSA Code
* Forgetting to update head
* Breaking links accidentally
* Infinite loops if next is not updated
* Wrong position indexing
* Confusing Python lists ([]) with Linked Lists (DSA)
9. 20 Practice Questions — With Answers
Questions
-
What is a linked list?
-
Define node in Python.
-
Why linked lists are dynamic?
-
What does head reference store?
-
Insert at beginning logic.
-
Searching logic.
-
Time complexity of end insertion?
-
Meaning of
Nonein linked list. -
Why Python lists ≠ Linked Lists?
-
Purpose of references.
-
Delete last node logic.
-
What is traversal?
-
Why linked lists are slower than arrays in Python?
-
What is a dangling reference?
-
How to check empty list?
-
Difference between
node.nextandnode.data. -
Why head must be updated in insertion at beginning?
-
Insert at position logic.
-
Delete at position logic.
-
When to choose linked lists over Python lists?
Answers
-
Dynamic linear structure of nodes.
-
Object storing data and next reference.
-
Nodes created at runtime.
-
Address of first node.
-
New node → next=head → head=new node.
-
Traverse and compare each value.
-
O(n).
-
End of list.
-
Python list is dynamic array.
-
Connect nodes sequentially.
-
Traverse to second last → next=None.
-
Visiting nodes one by one.
-
Because elements are not contiguous.
-
Reference to deleted memory.
-
head is None.
-
One is link, one is stored value.
-
To attach new node at front.
-
Traverse to pos-1 and insert.
-
Link around skipped node.
-
When frequent insert/delete at beginning/middle.
ALSO CHECK
ALSO CHECK
Comments
Post a Comment