#Summary
The assignment was to implement a Weighted Graph in Python containing the following methods:
* g.nodes(): return a list of all nodes in the graph
* g.edges(): return a list of all edges in the graph
* g.add_node(n): adds a new node 'n' to the graph
* g.add_edge(n1, n2): adds a new edge to the graph connecting 'n1' and 'n2', if either n1 or n2 are not already present in the graph, they should be added.
* g.del_node(n): deletes the node 'n' from the graph, raises an error if no such node exists
* g.del_edge(n1, n2): deletes the edge connecting 'n1' and 'n2' from the graph, raises an error if no such edge exists
* g.has_node(n): True if node 'n' is contained in the graph, False if not.
* g.neighbors(n): returns the list of all nodes connected to 'n' by edges, raises an error if n is not in g
* g.adjacent(n1, n2): returns True if there is an edge connecting n1 and n2, False if not, raises an error if either of the supplied nodes are not in g
* g.depth_first_traversal(start): Returns the path list for the entire graph with a depth first traversal.
* g.breadth_first_travers(start): Returns the path list for the entire graph with a breadth first traversal.
---------- coverage: platform darwin, python 3.5.2-final-0 -----------
| Name | Stmts | Miss | Cover |
|---|---|---|---|
| weighted_graph.py | 78 | 3 | 96% |
| test_weighted_graph.py | 178 | 0 | 100% |
| ----------------------- | --- | -- | ---- |
| TOTAL | 256 | 3 | 98% |