Q:

python graph-tool load csv file

I'm loading directed weighted graph from csv file into graph-tool graph in python. The organization of the input csv file is:
1,2,300
2,4,432
3,89,1.24
...
Where the fist two entries of a line identify source and target of an edge and the third number is the weight of the edge.  
Currently I'm using: 
g = gt.Graph()
e_weight = g.new_edge_property("float")
csv_network = open (in_file_directory+ '/'+network_input, 'r')
csv_data_n = csv_network.readlines()
for line in csv_data_n:
    edge = line.replace('\r\n','')
    edge = edge.split(delimiter)
    e = g.add_edge(edge[0], edge[1])
    e_weight[e] = float(edge[2])

However it takes quite long to load the data (I have network of 10 millions of nodes and it takes about 45 min). 
I have tried to make it faster by using g.add_edge_list, but this works only for unweighted graphs. Any suggestion how to make it faster?

A:

This has been answered in graph-tool's mailing list:
http://lists.skewed.de/pipermail/graph-tool/2015-June/002043.html
In short, you should use the function g.add_edge_list(), as you said, and and put the weights separately
via the array interface for property maps:
e_weight.a = weight_list

The weight list should have the same ordering as the edges you passed to
g.add_edge_list().

