Graphs.jl

Inspired by the Boost Graph Library, it allows algorithms to work across different graph types, promoting code reuse and abstraction as highlighted in the README.

Includes BFS, DFS, shortest paths (Dijkstra, A*), minimum spanning trees, and more, covering essential graph theory needs for analysis and traversal.

Benchmarks show efficient execution, e.g., 15ms for Dijkstra on a graph with 10k vertices and 1M edges, due to pure Julia implementation and optimization.

Offers adjacency lists, incidence lists, and compact graphs, tailored for different use cases like labeled attributes or efficient storage.