PYTHON Lecture 15

Python Lecture 15: Advanced Data Structures
*1. Introduction to Advanced Data Structures*
Recap of basic data structures (lists, tuples, dictionaries, sets).
Importance of choosing the right data structure for efficiency.
*2. Stacks and Queues*
Definition and use cases.
Implementing stacks using lists and the `collections.deque` class.
Implementing queues using lists and `collections.deque`.
Examples of applications (e.g., undo mechanisms, breadth-first search).
*3. Linked Lists*
Explanation of singly and doubly linked lists.
Implementation of linked lists in Python.
Advantages and disadvantages compared to lists.
*4. Trees*
Introduction to tree structures.
Binary trees and binary search trees (BST).
Basic tree operations: insertion, deletion, and traversal (in-order, pre-order, post-order).
Use cases for trees in databases and hierarchical data representation.
*5. Heaps*
Definition of heaps and the heap property.
Implementing a min-heap and max-heap using lists.
Applications of heaps (e.g., priority queues, scheduling algorithms).
*6. Graphs*
Overview of graph theory concepts (vertices, edges, directed vs. undirected).
Representing graphs in Python (adjacency list vs. adjacency matrix).
Basic graph algorithms (DFS, BFS).
*7. Practical Examples and Exercises*
Coding exercises to reinforce concepts.
Real-world problems that can be solved using the data structures covered.
*8. Summary and Q&A*
Recap key points from the lecture.
Open the floor for questions and clarification.