How to write a code on Link prediction on dynamic network in python?

I have read plenty of papers on link prediction on dynamic networks, but I am getting confusion on how to do it. I know link prediction on dynamic networks is different from static network.In dynamic network your given a series of snapshots of the graphs(G=(G1, G2....Gn)) and trying to predict link in time T+1

For example, I have a file with a bunch of edge lists (link here) each edge list is associated with the time in which the edge was formed, here is the example on how I read the datasets

G=nx.read_edgelist('enron.txt',create_using=nx.Graph(), nodetype=int)

but the final graph when you draw it is just one graph, how can I have those series of graphs? for example if I want to find the adjacency matrix for each snapshot, how to do it?