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Implementing Hash Tables and Linked Lists in Python: No External Libraries

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Hash tables and linked lists are essential data structures widely used in computer science to improve application performance. In this blog post, we'll demonstrate how to develop your own implementations of these structures without using external Python libraries. This exercise will help you deepen your understanding of these concepts and develop valuable problem-solving skills.

First, let's take a look at a simple hash table implementation. A hash table is a data structure that uses an array as its underlying container, along with a hash function to calculate an index for the array based on the key. This way, we can store and retrieve data efficiently using the key. We'll walk through how to create a hash table from scratch, calculate the hash index, handle collisions, and create a table with separate chaining.

Next, we'll explore how to implement a singly-linked list without external libraries. A singly-linked list consists of nodes, each containing data and a reference to the next node in the list. By the end of this section, you'll know how to create nodes, manipulate linked lists, insert, delete and traverse the list.

Lastly, let's discuss how to merge these data structures, resulting in an efficient hash map implementation based on a linked list. This hash map will allow us to look up, add, and remove items efficiently.


Additional Resources:
[[Python Hash Table](https://docs.python.org/3/tutorial/da...)]
[[Python Linked List](https://realpython.com/python-linked-...)]

#STEM #Programming #Python #DataStructures #HashTable #LinkedList #CodingChallenge

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