title: Updating weight information depending on repeat of edges with networkx
body: <p>I have a JSON feed data with lots of user relation in it such as:</p>
  
  <pre><code>"subject_id = 1, object_id = 2, object = added 
  subject_id = 1, object_id = 2, object = liked
  subject_id = 1, object_id = 3, object = added
  subject_id = 2, object_id = 1, object = added"
  </code></pre>
  
  <p>Now I've used following code to convert JSON to networkx Graph:</p>
  
  <pre><code>def load(fname):
  G = nx.DiGraph()
  d = simplejson.load(open(fname))
  for item in d:
      for attribute, value in item.iteritems():
          G.add_edge(value['subject_id'],value['object_id'])
  return G
  </code></pre>
  
  <p>And the result is something like:</p>
  
  <pre><code>[('12820', '80842'), ('12820', '81312'), ('12820', '81311'), ('13317', '29'), ('12144', '81169'), ('13140', '16687'), ('13140', '79092'), ('13140', '78384'), ('13140', '48715'), ('13140', '54151'), ('13140', '13718'), ('13140', '4060'), ('13140', '9914'), ('13140', '32877'), ('13140', '9918'), ('13140', '4740'), ('13140', '47847'), ('13140', '29632'), ('13140', '72395'), ('13140', '48658'), ('13140', '78394'), ('13140', '4324'), ('13140', '4776'), ('13140', '78209'), ('13140', '51624'), ('13140', '66274'), ('13140', '38009'), ('13140', '80606'), ('13140', '13762'), ('13140', '28402'), ('13140', '13720'), ('13140', '9922'), ('13303', '81199'), ('13130', '70835'), ('13130', '7936'), ('13130', '30839'), ('13130', '11558'), ('13130', '32157'), ('13130', '2785'), ('13130', '9914'), ('13130', '73597'), ('13130', '9918'), ('13130', '49879'), ('13130', '62303'), ('13130', '64275'), ('13130', '48123'), ('13130', '8722'), ('13130', '43303'), ('13130', '39316'), ('13130', '78368'), ('13130', '28328'), ('13130', '57386'), ('13130', '30739'), ('13130', '9922'), ('13130', '71464'), ('13130', '50296'), ('12032', '65338'), ('13351', '81316'), ('13351', '16926'), ('13351', '80435'), ('13351', '79086'), ('12107', '16811'), ('12107', '70310'), ('12107', '10008'), ('12107', '25466'), ('12107', '36625'), ('12107', '81320'), ('12107', '48912'), ('12107', '62209'), ('12816', '79526'), ('12816', '79189'), ('13180', '39769'), ('13180', '81319'), ('12293', '70918'), ('12293', '59403'), ('12293', '76348'), ('12293', '12253'), ('12293', '65078'), ('12293', '61126'), ('12293', '12243'), ('12293', '12676'), ('12293', '11693'), ('12293', '78387'), ('12293', '54788'), ('12293', '26113'), ('12293', '50472'), ('12293', '50365'), ('12293', '66431'), ('12293', '29781'), ('12293', '50435'), ('12293', '48145'), ('12293', '79170'), ('12293', '76730'), ('12293', '13260'), ('12673', '29'), ('12672', '29'), ('13559', '9327'), ('12583', '25462'), ('12252', '50754'), ('12252', '11778'), ('12252', '38306'), ('12252', '48170'), ('12252', '5488'), ('12325', '78635'), ('12325', '4459'), ('12325', '68699'), ('12559', '80285'), ('12559', '78273'), ('12020', '48291'), ('12020', '4498'), ('12746', '48916'), ('13463', '56785'), ('13463', '47821'), ('13461', '80790'), ('13461', '4425'), ('12550', '48353')]
  </code></pre>
  
  <p>What I want to do is I want to increase weight if there are more than 1 relation between these users. So, as I demonstrated in JSON relation, subject_id 1 has 3 relations with subject_id 2 therefore their weight should be 3 whereas user 3 has only 1 relation with subject_id 1 and so it should be 1 as weight.</p>
  
  <h2>Update:</h2>
  
  <p>I suppose I've solved my problem with using:</p>
  
  <pre><code>def load(fname):
  G = nx.MultiDiGraph()
  d = simplejson.load(open(fname))
  for item in d:
      for attribute, value in item.iteritems():
          if (value['subject_id'], value['object_id']) in G.edges():
              data = G.get_edge_data(value['subject_id'], value['object_id'], key='edge')
              G.add_edge(value['subject_id'], value['object_id'], key='edge', weight=data['weight']+1)
          else:
              G.add_edge(value['subject_id'], value['object_id'], key='edge', weight=1)
  
  print G.edges(data=True)
  </code></pre>
  
  <p>But still your help would be nice about improving.</p>