def GetPredictions():
"""Returns all of the predictions (and can filter by org)."""
org_filter = request.args.get('org', False)
if org_filter:
predictions = Prediction.query(Prediction.org == org_filter).fetch()
else:
predictions = Prediction.query().fetch()
for prediction in predictions:
# TODO(goldhaber): add these to the datastore
prediction.url = 'predictions/' + prediction.key.urlsafe()
prediction.price = GetPriceByPredictionId(
prediction.key.urlsafe()) * 100
return render_template('predictions.html', predictions=predictions)
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