# implementation of an undirected graph using Adjacency Matrix, with weighted or unweighted edges
class Vertex:
	def __init__(self, n):
		self.name = n

class Graph:
	vertices = {}
	edges = []
	edge_indices = {}
	
	def add_vertex(self, vertex):
		if isinstance(vertex, Vertex) and vertex.name not in self.vertices:
			self.vertices[vertex.name] = vertex
			for row in self.edges:
				row.append(0)
			self.edges.append([0] * (len(self.edges)+1))
			self.edge_indices[vertex.name] = len(self.edge_indices)
			return True
		else:
			return False
	
	def add_edge(self, u, v, weight=1):
		if u in self.vertices and v in self.vertices:
			self.edges[self.edge_indices[u]][self.edge_indices[v]] = weight
			self.edges[self.edge_indices[v]][self.edge_indices[u]] = weight
			return True
		else:
			return False
			
	def print_graph(self):
		for v, i in sorted(self.edge_indices.items()):
			print(v + ' ', end='')
			for j in range(len(self.edges)):
				print(self.edges[i][j], end='')
			print(' ')    

g = Graph()
# print(str(len(g.vertices)))
a = Vertex('A')
g.add_vertex(a)
g.add_vertex(Vertex('B'))
for i in range(ord('A'), ord('K')):
	g.add_vertex(Vertex(chr(i)))

edges = ['AB', 'AE', 'BF', 'CG', 'DE', 'DH', 'EH', 'FG', 'FI', 'FJ', 'GJ', 'HI']
for edge in edges:
	g.add_edge(edge[:1], edge[1:])

g.print_graph()