Put an element in the right position in defaultdict

Question

Hi im new to python and im trying to create my first program to find clusters of nodes which have +1 sign. I have a file with 3 columns(starting node, ending node, sign between the nodes) like this:

1   2   1
1   3   1
2   3   1
2   4   -1
2   5   1
3   6   -1
4   7   -1
4   9   -1

I create the graph an i save all the adjacencies in a dictionary. Now i want to save in another dictionary(defaultdict(list)) all the supernodes(team nodes that have +1 sign between them). So i wrote the following code:

G = nx.Graph()
G = nx.read_edgelist('example.txt', delimiter='\t', nodetype=int, data=(('sign', int),))
adjacencies = {}
supernodes = defaultdict(list)

for i in G.nodes:
    adjacencies[i] = list(G.neighbors(i))


flag = 0
if flag == 0:
    for node in G.nodes:
        supernodes[node].append(node)
        flag = 1
        break
else:
    for i in G.nodes():
        for j in adjacencies[i]:
            if G.get_edge_data(i,j) == 1:
                for v in supernodes.values():

i stop the code here because i dont know how to put an element to the right position of dict. The steps that i want to do are: i have supernodes like:

1 : [1,2,3,5]
2 : [4]
3 : [6,8]

etc

1. check if edge(i,j) is +1 and then
2.      if i is in supernodes then add j in the same list where i is
3.      if j is in supernodes then add i in the same list where j is
4.      if i and j is not in supernodes the add a new list in supernodes and add 
        i,j elements

Answer 1

Any particular reason you want to use collections.defaultdict?

You can use the following code to find your supernodes whether you use a deafaultdict or a regular dict. The method setdefault works in both. Check out what setdefault does here.

G = nx.read_edgelist('example.txt', delimiter='\t', nodetype=int, data=(('sign', int),))

supernodes = dict()
for edge in G.edges(data='sign'):
    sign = edge[2]
    if sign == 1:
        node1 = edge[0]
        node2 = edge[1]
        supernodes.setdefault(node1, [node1])
        supernodes.setdefault(node2, [node2])
        supernodes[node1].append(node2)
        supernodes[node2].append(node1)

[edit] Looking at the figure of the graph and understanding what OP wanted, here's a way to do it:

import networkx as nx

G = nx.read_edgelist('example.txt', delimiter='\t', nodetype=int, data=(('sign', int),))
G1 = nx.Graph()
G1.add_weighted_edges_from([edge for edge in G.edges(data='sign') if edge[2]==1])
G1.add_nodes_from(list(G.nodes))
supernodes = list(nx.connected_components(G1))

supernodes is a list of sets where each set of nodes is one blob in your picture.