The Graph Data Science Library and Path Finding

In this chapter, we will use the Graph Data Science (GDS) library for the first time, which is the successor of the Graph Algorithm library for Neo4j. After an introduction to the main principles of the library, we will learn about the pathfinding algorithms. Following that, we will use implementations in Python and Java to understand how they work. We will then learn how to use the optimized version of these algorithms, implemented in the GDS plugin. We will cover the Dijkstra and A* shortest path algorithms, alongside other path-related methods such as the traveling-salesman problem and minimum spanning trees. 

The following topics will be covered in this chapter:

• Introducing the Graph Data Science plugin
• Understanding the importance of shortest path through its applications
• Going through Dijkstra's shortest path algorithm
• Finding the shortest path with the A* algorithm and its heuristics
• Discovering the other path-related algorithms in the GDS library
• Optimizing our process using graphs