Python Graph Algorithms: Modified Dijkstra and Path Constraints

Graph algorithms are essential for solving complex routing and network problems, but real-world scenarios often come with unique constraints. Standard pathfinding isn't always enough when you need to calculate paths with specific cost rules, such as modular arithmetic constraints. This text-only course guides you through the fundamentals of graph theory and Dijkstra's algorithm, showing you how to modify standard pathfinding logic in Python to handle custom teleportation and cost constraints. What you'll learn: - Understand foundational graph theory concepts, representations, and terminology - Implement standard Dijkstra's algorithm from scratch using Python's modern type hints and dataclasses - Modify pathfinding logic to handle unique constraints, such as costs divisible by specific factors - Analyze spatial routing scenarios modeled as teleportation networks with custom edge weights - Practice debugging and optimizing graph traversals through step-by-step written walkthroughs You will start with the core definitions of vertices, edges, and adjacency lists before building up to priority queues. From there, you will step through the process of adapting Dijkstra's algorithm to enforce custom cost constraints using clean, modern Python. This course is designed for beginner to intermediate Python programmers who want to master graph algorithms and custom pathfinding, with no prior algorithm design experience required. Start reading today to level up your algorithmic thinking and solve complex routing problems with confidence.