#Summary

This Repository contains python implementations of common datastructures.

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:

---------- 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%

#Hash Functions: Additive hash: init : O(n) get: O(1) + O(k) set: O(k) + O(1) _hash: O(m)

FNV hash:
__init__ : O(n)
get: O(1) + O(n)
set: O(n) + O(1)
_hash: O(n)

#Trie insert: O(n) contains: O(n) + O(k) size: O(1) remove: O(n**2) traversal: O(k) + O(2n)