old_contents: import pandas as pd
  import pymongo
  from bokeh.plotting import cursession, figure, show, output_server
  import time
  
  client = pymongo.MongoClient()
  db = client['bitmicro']
  predictions = db['btc_predictions']
  
  cursor = predictions.find().limit(60*10).sort('_id', pymongo.DESCENDING)
  data = pd.DataFrame(list(cursor))
  data = data.set_index('_id')
  data = data.sort_index(ascending=True)
  x = pd.to_datetime(data.index, unit='s').to_series()
  y = data.prediction*100
  
  output_server('model_signal')
  p = figure(title='30-second Prediction',
             x_axis_type='datetime',
             y_axis_label='Basis Points')
  p.line(x, y, name='signal')
  show(p)
  
  renderer = p.select(dict(name='signal'))
  ds = renderer[0].data_source
  
  while True:
      cursor = predictions.find().limit(60*10).sort('_id', pymongo.DESCENDING)
      data = pd.DataFrame(list(cursor))
      data = data.set_index('_id')
      data = data.sort_index(ascending=True)
      ds.data['x'] = pd.to_datetime(data.index, unit='s').to_series()
      ds.data['y'] = data.prediction*100
      cursession().store_objects(ds)
      time.sleep(1)
  
new_contents: import pandas as pd
  import pymongo
  from bokeh.plotting import cursession, figure, show, output_server
  import time
  
  client = pymongo.MongoClient()
  db = client['bitmicro']
  predictions = db['btc_predictions']
  
  cursor = predictions.find().limit(60*60).sort('_id', pymongo.DESCENDING)
  data = pd.DataFrame(list(cursor))
  data = data.set_index('_id')
  data = data.sort_index(ascending=True)
  x = pd.to_datetime(data.index, unit='s').to_series()
  y = data.prediction*100
  
  output_server('model_signal')
  p = figure(title='30-second Prediction',
             x_axis_type='datetime',
             y_axis_label='Basis Points')
  p.line(x, y, name='signal')
  show(p)
  
  renderer = p.select(dict(name='signal'))
  ds = renderer[0].data_source
  
  while True:
      cursor = predictions.find().limit(60*60).sort('_id', pymongo.DESCENDING)
      data = pd.DataFrame(list(cursor))
      data = data.set_index('_id')
      data = data.sort_index(ascending=True)
      ds.data['x'] = pd.to_datetime(data.index, unit='s').to_series()
      ds.data['y'] = data.prediction*100
      cursession().store_objects(ds)
      time.sleep(1)
  
subject: change to full hour of data