  Python implementation of selected weighted graph algorithms is presented. The
minimal graph interface is defined together with several classes implementing
this interface. Graph nodes can be any hashable Python objects. Directed edges
are instances of the Edge class. Graphs are instances of the Graph class. It is
based on the adjacency-list representation, but with fast lookup of nodes and
neighbors (dict-of-dict structure). Other implementations of this class are
also possible.
  In this work, many algorithms are implemented using a unified approach. There
are separate classes and modules devoted to different algorithms. Three
algorithms for finding a minimum spanning tree are implemented: the Boruvka's
algorithm, the Prim's algorithm (three implementations), and the Kruskal's
algorithm. Three algorithms for solving the single-source shortest path problem
are implemented: the dag shortest path algorithm, the Bellman-Ford algorithm,
and the Dijkstra's algorithm (two implementations). Two algorithms for solving
all-pairs shortest path problem are implemented: the Floyd-Warshall algorithm
and the Johnson's algorithm.
  All algorithms were tested by means of the unittest module, the Python unit
testing framework. Additional computer experiments were done in order to
compare real and theoretical computational complexity. The source code is
available from the public GitHub repository.
