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Bar data





In [1]:



    


from ib_insync import *
util.startLoop()

ib = IB()
ib.connect('127.0.0.1', 7497, clientId=14)



    


















    
Out[1]:








<IB connected to 127.0.0.1:7497 clientId=14>

Historical data

To get the earliest date of available bar data the "head timestamp" can be requested:





In [2]:



    


contract = Stock('TSLA', 'SMART', 'USD')

ib.reqHeadTimeStamp(contract, whatToShow='TRADES', useRTH=True)



    


















    
Out[2]:








datetime.datetime(2010, 6, 29, 8, 0)

To request hourly data of the last 60 trading days:





In [3]:



    


bars = ib.reqHistoricalData(
        contract,
        endDateTime='',
        durationStr='60 D',
        barSizeSetting='1 hour',
        whatToShow='TRADES',
        useRTH=True,
        formatDate=1)



    











In [4]:



    


bars[0]



    


















    
Out[4]:








BarData(date=datetime.datetime(2019, 10, 4, 15, 30), open=231.82, high=234.78, low=230.29, close=233.06, volume=12066, average=232.914, barCount=5981)

Convert the list of bars to a data frame and print the first and last rows:





In [5]:



    


df = util.df(bars)

display(df.head())
display(df.tail())



    


















    











  
    

      
      date
      open
      high
      low
      close
      volume
      average
      barCount
    

  
  
    

      0
      2019-10-04 15:30:00
      231.82
      234.78
      230.29
      233.06
      12066
      232.914
      5981
    

    

      1
      2019-10-04 16:00:00
      233.02
      233.19
      228.07
      228.69
      15847
      229.846
      7664
    

    

      2
      2019-10-04 17:00:00
      228.62
      230.87
      228.30
      230.56
      8396
      229.421
      4324
    

    

      3
      2019-10-04 18:00:00
      230.56
      231.49
      230.28
      230.85
      7069
      230.899
      3605
    

    

      4
      2019-10-04 19:00:00
      230.84
      231.48
      230.04
      231.00
      3518
      230.765
      2125
    

  













    











  
    

      
      date
      open
      high
      low
      close
      volume
      average
      barCount
    

  
  
    

      409
      2019-12-30 17:00:00
      413.03
      421.06
      412.61
      419.18
      14920
      416.886
      8149
    

    

      410
      2019-12-30 18:00:00
      419.18
      420.45
      417.32
      418.65
      7629
      419.017
      4769
    

    

      411
      2019-12-30 19:00:00
      418.70
      420.78
      416.13
      416.42
      7476
      418.900
      3883
    

    

      412
      2019-12-30 20:00:00
      416.41
      416.78
      413.51
      414.90
      6936
      415.059
      3700
    

    

      413
      2019-12-30 21:00:00
      415.00
      415.00
      413.00
      414.62
      9204
      414.130
      5979

Instruct the notebook to draw plot graphics inline:





In [6]:



    


%matplotlib inline

Plot the close data





In [7]:



    


df.plot(y='close');

There is also a utility function to plot bars as a candlestick plot. It can accept either a DataFrame or a list of bars. Here it will print the last 100 bars:





In [8]:



    


util.barplot(bars[-100:], title=contract.symbol);

Historical data with realtime updates

A new feature of the API is to get live updates for historical bars. This is done by setting endDateTime to an empty string and the keepUpToDate parameter to True.

Let's get some bars with an keepUpToDate subscription:





In [9]:



    


contract = Forex('EURUSD')

bars = ib.reqHistoricalData(
        contract,
        endDateTime='',
        durationStr='900 S',
        barSizeSetting='10 secs',
        whatToShow='MIDPOINT',
        useRTH=True,
        formatDate=1,
        keepUpToDate=True)

Replot for every change of the last bar:





In [10]:



    


from IPython.display import display, clear_output
import matplotlib.pyplot as plt

def onBarUpdate(bars, hasNewBar):
    plt.close()
    plot = util.barplot(bars)
    clear_output(wait=True)
    display(plot)

bars.updateEvent += onBarUpdate

ib.sleep(10)
ib.cancelHistoricalData(bars)

Realtime bars

With reqRealTimeBars a subscription is started that sends a new bar every 5 seconds.

First we'll set up a event handler for bar updates:





In [11]:



    


def onBarUpdate(bars, hasNewBar):
    print(bars[-1])

Then do the real request and connect the event handler,





In [12]:



    


bars = ib.reqRealTimeBars(contract, 5, 'MIDPOINT', False)
bars.updateEvent += onBarUpdate

let it run for half a minute and then cancel the realtime bars.





In [13]:



    


ib.sleep(30)
ib.cancelRealTimeBars(bars)



    


















    






Error 162, reqId 5: Historical Market Data Service error message:API historical data query cancelled: 5










    






RealTimeBar(time=datetime.datetime(2019, 12, 31, 12, 27, 5, tzinfo=datetime.timezone.utc), endTime=-1, open_=1.122925, high=1.122975, low=1.122925, close=1.122975, volume=-1, wap=-1.0, count=-1)
RealTimeBar(time=datetime.datetime(2019, 12, 31, 12, 27, 10, tzinfo=datetime.timezone.utc), endTime=-1, open_=1.122975, high=1.122975, low=1.122975, close=1.122975, volume=-1, wap=-1.0, count=-1)
RealTimeBar(time=datetime.datetime(2019, 12, 31, 12, 27, 15, tzinfo=datetime.timezone.utc), endTime=-1, open_=1.122975, high=1.122975, low=1.122975, close=1.122975, volume=-1, wap=-1.0, count=-1)
RealTimeBar(time=datetime.datetime(2019, 12, 31, 12, 27, 20, tzinfo=datetime.timezone.utc), endTime=-1, open_=1.122975, high=1.123025, low=1.122975, close=1.123025, volume=-1, wap=-1.0, count=-1)
RealTimeBar(time=datetime.datetime(2019, 12, 31, 12, 27, 25, tzinfo=datetime.timezone.utc), endTime=-1, open_=1.123025, high=1.123025, low=1.122975, close=1.122975, volume=-1, wap=-1.0, count=-1)
RealTimeBar(time=datetime.datetime(2019, 12, 31, 12, 27, 30, tzinfo=datetime.timezone.utc), endTime=-1, open_=1.122975, high=1.122975, low=1.122975, close=1.122975, volume=-1, wap=-1.0, count=-1)

The advantage of reqRealTimeBars is that it behaves more robust when the connection to the IB server farms is interrupted. After the connection is restored, the bars from during the network outage will be backfilled and the live bars will resume.

reqHistoricalData + keepUpToDate will, at the moment of writing, leave the whole API inoperable after a network interruption.





In [14]:



    


ib.disconnect()



    











In [ ]:

Content source: erdewit/ib_insync

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