Graph Algorithms in Python: Finding Paths with Breadth-First Search

Graphs are fundamental data structures used to model networks, social connections, and routing paths. Understanding how to navigate these structures and verify connections between points is an essential skill for any software developer or computer science student. This written course guides you through the concepts of graph representation and traversal. You will learn how to construct clear graph models and implement a robust Breadth-First Search (BFS) algorithm to check if a valid path exists between any two vertices in a bidirectional graph. What you'll learn: Understand the core concepts of vertices, edges, and bidirectional graphs; Represent graphs programmatically using adjacency lists and modern Python type hints; Implement the Breadth-First Search (BFS) algorithm step-by-step using queue data structures; Trace and analyze the path existence logic to find connections between nodes; Write clean, readable code with structured testing patterns to verify your graph solutions. The course begins with foundational graph terminology and structural representations. You will then progress to implementing the search logic in Python, culminating in practical written exercises to test your algorithm on various network scenarios. This course is designed for beginner programmers, computer science students, and developers looking to solidify their understanding of fundamental graph algorithms. Start reading today and master the basics of graph traversal.