scorer.py 文件源码

def scoring():
  #go through all predictions, check if should be scored
  predictions = Prediction.query(
      ndb.AND(Prediction.outcome != "UNKNOWN", Prediction.resolved == False)).fetch()
  audit = []
  # Get all trades by prediction_id
  for p in predictions:
    resolve = p.outcome
    trades = Trade.query(Trade.prediction_id == p.key).fetch()
    # Get user id from those trades
    users = [trade.user_id.get() for trade in trades]
    for u in users:
      # check user ledger, map outcome to 1 or 0 based on prediction outcome
      ledger = [i for i in u.user_ledger if i.prediction_id == p.key.urlsafe()]
      if resolve == 'CONTRACT_ONE':
        earned = ledger[0].contract_one
      else:
        earned = ledger[0].contract_two
      u.balance += earned
      audit.append({'user': u, 'earned': earned})
      u.put()
    p.resolved = True
    p.put()
  return audit