new_contents: import json
  import networkx as nx
  from networkx.readwrite import json_graph
  
  with open("/query_results.json") as f:
      json_data = f.read()
  x = json.loads(json_data)
  doc_graphs = list()
  
  for corpus_name, data in x.iteritems():
      for query, results in data["queries"].iteritems():
          new_graph = nx.Graph()
          new_graph.add_node(query)
  
          for result in results.itervalues():
              new_graph.add_node(result["file"])
              if "similarity" in results:
                  sim = results["similarity"]
              else:
                  print "no sim"
                  sim = 1
              print sim
              new_graph.add_edge(query, result["file"], weight=sim)
  
          doc_graphs.append(new_graph)
  
  for graph in doc_graphs:
      for n in graph:
          graph.node[n]['name'] = n
          similarity_graph_json = json_graph.node_link_data(graph)
          # Todo: Save json file
  
subject: Add skeleton script to draw similarites between objects