Collections and algorithms form the backbone of many software applications, enabling programmers to store, manipulate, and process data efficiently. In Python, a rich set of built-in data structures and algorithms make it easy to handle complex tasks with elegance and simplicity.
In this article, we’ll explore the world of collections and algorithms in Python, providing practical examples to demonstrate their usage and importance.
Introduction to Collections and Algorithms
Collections, also known as data structures, are containers that hold collections of items. They provide various operations for accessing, adding, and removing elements. Algorithms, on the other hand, are step-by-step procedures for solving problems, often involving manipulating data stored in collections.
1. Collections in Python
Python offers a diverse set of built-in collections, including lists, tuples, dictionaries, sets, and more. These collections serve different purposes and have distinct characteristics.
