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Textrank: complementing pagerank for sentence extraction using networkx
import networkx as nx
D=nx.DiGraph()
D.add_weighted_edges_from([('A','B',0.5),('A','C',1)])
print nx.pagerank(D)

import networkx as nx

# Undirected Network
D = nx.Graph()
D.add_weighted_edges_from([('A', 'B', 0.5),('A', 'C', 1)])

# Default max number of iterations failed to converge for me
print nx.pagerank(D, max_iter=200)

# Outputs:
{'A': 0.48648648872844047, 'C': 0.32567567418103965, 'B': 0.18783783709051982}

import networkx as nx

# Directed Network
D = nx.DiGraph()
D.add_weighted_edges_from([('A', 'B', 0.5), ('A', 'C', 1)])

# Convert to undirected
G = D.to_undirected()

# Default max number of iterations failed to converge for me
print nx.pagerank(G, max_iter=200)

# Outputs:
{'A': 0.48648648872844047, 'C': 0.32567567418103965, 'B': 0.18783783709051982}