#!/usr/bin/env python3
class Graph:
#constructor
def __init__(self,num_nodes):
self.num_nodes = num_nodes;
self.data = [[] for _ in range(num_nodes)]
self.weight = [[] for _ in range(num_nodes)]
self.lsdb = []# for _ in range(num_nodes)]
#9:55
#self.weight = [[] for _ in range(num_nodes)]
# for n1,n2 in edges:#pair
# self.data[n1].append(n2)
# self.data[n2].append(n1)
def add_edges(self,n1,n2,weight):
if n2 in self.data[n1]:
index1 = self.data[n1].index(n2)
temp_weight = self.weight[n1][index1]
self.weight[n1][index1] = weight
test = f"{n1},{n2},{temp_weight}"
test2 = f"{n1},{n2},{weight}"
index12 = self.lsdb.index(test)
self.lsdb[index12] = test2
index2 = self.data[n2].index(n1)
self.weight[n2][index2] = weight
else:
self.data[n1].append(n2)
test = f"{n1},{n2},{weight}"
self.lsdb.append(test)
self.weight[n1].append(weight)
self.data[n2].append(n1)
#self.lsdb[n2].append(test)
self.weight[n2].append(weight)
def remove_edges(self,n1,n2):
index1 = self.data[n1].index(n2)
weight1 = self.weight[n1][index1]
test = f"{n1},{n2},{weight1}"
self.data[n1].remove(n2)
self.lsdb.remove(test)
self.weight[n1].remove(weight1)
index2 = self.data[n2].index(n1)
weight2 = self.weight[n2][index2]
self.data[n2].remove(n1)
self.weight[n2].remove(weight2)
def bfs(self,src):
visited = [False] * len(self.data)
queue = []
visited[src] = True
queue.append(src)
i = 0
while i < len(queue):
for v in self.data[queue[i]]:
if not visited[v]:
visited[v] = True
queue.append(v)
i+=1
queue.remove(src)
return queue
def lsdb_update(self):
num = []
for i in self.lsdb:
temp = i.split(",")
n = int(temp[0]) + int(temp[1])
num.append(n)
#bubble sort
for i in range (len(num)):
for j in range(0,len(num) - i - 1):
if num[j] > num[j+1]:
t = num[j]
p = self.lsdb[j]
num[j] = num[j+1]
self.lsdb[j] = self.lsdb[j+1]
num[j+1] = t
self.lsdb[j+1] = p
#print("Updated: ",self.lsdb)
def get_neighbour(self,x):
size = len(self.data[x])
st = []
for i in range(size):
#return (x,self.data[x][i],self.weight[x][i])
st.append(f"{self.data[x][i]},{self.weight[x][i]}")
return st
def print_lsdb(self):
for word in self.lsdb:
print(word)
def __repr__(self) :
return "\n".join(["{} {}".format(n,neighbors) for n,neighbors in enumerate(self.data)])
def __str__(self):
return repr(self)
#GLobal Functions
def num_con(arr):
num = []
i = 0
for no in arr:
num.append(i)
i=i+1
return num
def str_con(string,arr):
temp = string.split(",")
ret_str=f"{arr[int(temp[0])]},{arr[int(temp[1])]},{temp[2]}"
return ret_str
def str_con_n(string,arr):
temp = string.split(",")
ret_str=f"{arr[int(temp[0])]},{temp[1]}"
return ret_str
def n_update(arr):
num =[]
for i in arr:
temp = i.split(",")
n = int(temp[0])
num.append(n)
for i in range(len(num)):
for j in range(0,len(num) - i - 1):
if num[j] > num[j+1]:
t = num[j]
p = arr[j]
num[j]=num[j+1]
arr[j]=arr[j+1]
num[j+1] = t
arr[j+1] = p
return arr
#----------------------------------------------------------------------------------------------
def update_distances(graph, current, distance, parent=None):
"""Update the distances of the current node's neighbors"""
neighbors = graph.data[current]
weights = graph.weight[current]
nodel = []
for i, node in enumerate(neighbors):
weight = weights[i]
if distance[current] + weight < distance[node]:
distance[node] = distance[current] + weight
nodel.append[node]
if parent:
parent[node] = current
return nodel
def pick_next_node(distance, visited):
"""Pick the next univisited node at the smallest distance"""
min_distance = float('inf')
min_node = None
for node in range(len(distance)):
if not visited[node] and distance[node] < min_distance:
min_node = node
min_distance = distance[node]
return min_node
def shortest_path(graph, source, dest):
"""Find the length of the shortest path between source and destination"""
#all node unvisted
visited = [False] * len(graph.data)
#
distance = [float('inf')] * len(graph.data)
parent = [None] * len(graph.data)
queue = []
idx = 0
test = []
queue.append(source)
distance[source] = 0
visited[source] = True
j = 0
nodel = []
while idx < len(queue) and not visited[dest]:
current = queue[idx]
#update_distances(graph, current, distance, parent)
#---------------Use Update distance function from above-----------
neighbors = graph.data[current]
weights = graph.weight[current]
for i, node in enumerate(neighbors):
weight = weights[i]
if distance[current] + weight < distance[node]:
distance[node] = distance[current] + weight
nodel.append(node)
if parent:
parent[node] = current
#-------------------
test.append(current)
next_node = pick_next_node(distance, visited)
if next_node is not None:
visited[next_node] = True
if j == 0:
first_node = next_node
queue.append(next_node)
idx += 1
if len(nodel) > 1:
first_node = nodel[1]
if len(queue) == 1:
first_node = queue[0]
print(f"{dest} is {nodel}")
return f"{dest},{first_node},{distance[dest]}",distance
#-----------------------------------------------------------
def bubble_sort(arr):
num = []
for i in arr:
temp = i.split(",")
n = int(temp[0]) + int(temp[1])
num.append(n)
# bubble sort
for i in range(len(num)):
for j in range(0, len(num) - i - 1):
if num[j] > num[j+1]:
t = num[j]
p = arr[j]
num[j] = num[j+1]
arr[j] = arr[j+1]
num[j+1] = t
arr[j+1] = p
# visited = [False] * len(graph.data)
# dist = [float('inf')] * len(graph.data)
# queue = []
# dist[src] = 0
# queue.append(src)
# i = 0
# j = 0
# while i < len(queue) and not visited[target] and not visited[target]:
# current = queue[i]
# visited[current] = True
# i = i + 1
# update_distances(graph,current,dist)
# #find the first univisted node with the smallest distance
# next_node = pick_next_node(dist,visited)
# if j == 0:
# first_node = next_node
# j = j+1
# if next_node:
# queue.append(next_node)
# return dist[target]
if __name__ == '__main__':
#all the inputs
word = []
stop = 'END'
link = 'LINKSTATE'
while True:
val = input()
if val == stop:
break
word.append(val)
node = []
# array of nodes
new_word = word.copy()
step = 'LINKSTATE'
i = 0
while True:
temp = word[i]
if temp == step or i > len(word):
break
node.append(temp)
new_word.remove(temp)
i = i + 1
#print('output', node)
new_word.remove('LINKSTATE')
if "UPDATE" in new_word:
new_word.remove('UPDATE')
num_arr = num_con(node) # 0 1 2 3
num_nodes = len(node)
g = Graph(num_nodes)
for i in new_word:
my_list = i.split(" ")#x z 7 x,y
if not my_list[2] == "-1":
weight = int(my_list[2])
n1 = node.index(my_list[0])
n2 = node.index(my_list[1])
g.add_edges(n1, n2, weight)
g.lsdb_update()
else:
n1 = node.index(my_list[0])
n2 = node.index(my_list[1])
g.remove_edges(n1,n2)
g.lsdb_update()
checker = len(my_list)
if checker == 4:
li = []
t = my_list[3]
my_list2 = t.split(",")
len(my_list2)
for i in my_list2:
if i in node:
p = node.index(i)
print(f"{i} Neighbour Table:")
st = g.get_neighbour(p)
new_st = n_update(st)
for j in new_st:
print(str_con_n(j,node))
print("")
print(f'{i} LSDB')
if g.data[p]: #IF ELEMENT EXIST
t = "\n".join(["{}".format(n) for n in g.lsdb])
s = t.split("\n")
if len(s) > 1:
for j in s:
print(str_con(j,node))
else:
print(str_con(t,node))
print("")
print(f"{i} Routing Table")
r_st = []
for i in g.data[p]:
a,b = shortest_path(g,p,i)
r_st.append(a)
bubble_sort(r_st)
for i in r_st:
print(str_con(i,node))
#print(b)
print("")
# for i in range (len(g.data[p])):
# print("Path")
# print(shortest_path(g,p,i))
# print("")
#---------------------------------------------------------------------------------------------------------------#
# first_print = my_list2[0]
# second_print = my_list2[1]
# p1 = node.index(my_list2[0])
# p2 = node.index(my_list2[1])
# print(f"{first_print} Neighbour Table:")
# st = g.get_neighbour(p1)
# new_st = n_update(st)
# for i in new_st:
# print(str_con_n(i,node))
# print("")
# print(f'{first_print} LSDB')
# if g.data[p1]: #IF ELEMENT EXIST
# t = "\n".join(["{}".format(n) for n in g.lsdb])
# s = t.split("\n")
# if len(s) > 1:
# for i in s:
# print(str_con(i,node))
# else:
# print(str_con(t,node))
# print("")
# print(f"{second_print} Neighbour Table:")
# st = g.get_neighbour(p2)
# new_st = n_update(st)
# for i in new_st:
# print(str_con_n(i,node))
# print("")
# print(f'{second_print} LSDB:')
# if g.data[p2]: #IF ELEMENT EXIST
# t = "\n".join(["{}".format(n) for n in g.lsdb])
# s = t.split("\n")
# if len(s) > 1:
# for i in s:
# print(str_con(i,node))
# else:
# print(str_con(t,node))
# print("")
#---------------------------------------------------------------------------------------------------------------------#
# arr = ['X','Y','Z']
# num_nodes = 2
# g = Graph(3);
# g.add_edges(0,2,7)
# g.lsdb_update()
# print('X LSDB')
# #print(g.bfs(0))
# if g.data[0]: #IF ELEMENT EXIST
# t = "\n".join(["{}".format(n) for n in g.lsdb])
# s = t.split("\n")
# if len(s) > 1:
# for i in s:
# print(str_con(i,arr))
# else:
# print(str_con(t,arr))
# print("")
# print("Y LSDB")
# #print(g.bfs(1))
# if g.data[1]:
# t = "\n".join(["{}".format(n) for n in g.lsdb])
# s = t.split("\n")
# if len(s) > 1:
# for i in s:
# print(str_con(i,arr))
# else:
# print(str_con(t,arr))
# print("")
# g.add_edges(0,1,2)
# g.lsdb_update()
# g.add_edges(1,2,1)
# g.lsdb_update()
# print('X LSDB')
# #print(g.bfs(0))
# if g.data[0]:
# t = "\n".join(["{}".format(n) for n in g.lsdb])
# s = t.split("\n")
# if len(s) > 1:
# for i in s:
# print(str_con(i,arr))
# else:
# print(str_con(t,arr))
# print('')
# print('Z LSDB')
# #print(g.bfs(2))
# if g.data[2]:
# t= "\n".join(["{}".format(n) for n in g.lsdb])
# s = t.split("\n")
# if len(s) > 1:
# for i in s:
# print(str_con(i,arr))
# else:
# print(str_con(t,arr))
# print('')
# #print(g.lsdb)
# print(g)
# g.print_neighbour(0);
#edges = [(0,1),(0,4),(1,2),(1,3),(1,4),(2,3),(3,4)]
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