Code recipes

Collection of useful patterns, snippets and recipes.

Fetching consecutive historical data

Suppose we want to get the 1 min bar data of Tesla since the very beginning up until now. The best way is to start with now and keep requesting further and further back in time until there is no more data returned.

import datetime
from ib_insync import *

ib = IB()
ib.connect('127.0.0.1', 7497, clientId=1)

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

dt = ''
barsList = []
while True:
    bars = ib.reqHistoricalData(
        contract,
        endDateTime=dt,
        durationStr='10 D',
        barSizeSetting='1 min',
        whatToShow='MIDPOINT',
        useRTH=True,
        formatDate=1)
    if not bars:
        break
    barsList.append(bars)
    dt = bars[0].date
    print(dt)

# save to CSV file
allBars = [b for bars in reversed(barsList) for b in bars]
df = util.df(allBars)
df.to_csv(contract.symbol + '.csv')

Scanner data (blocking)

allParams = ib.reqScannerParameters())
print(allParams)

sub = ScannerSubscription(
    instrument='FUT.US',
    locationCode='FUT.GLOBEX',
    scanCode='TOP_PERC_GAIN')
scanData = ib.reqScannerData(sub)
print(scanData)

Scanner data (streaming)

def onScanData(scanData):
    print(scanData[0])
    print(len(scanData))

sub = ScannerSubscription(
    instrument='FUT.US',
    locationCode='FUT.GLOBEX',
    scanCode='TOP_PERC_GAIN')
scanData = ib.reqScannerSubscription(sub)
scanData.updateEvent += onScanData
ib.sleep(60)
ib.cancelScannerSubscription(scanData)

Option calculations

option = Option('EOE', '20171215', 490, 'P', 'FTA', multiplier=100)

calc = ib.calculateImpliedVolatility(
    option, optionPrice=6.1, underPrice=525))
print(calc)

calc = ib.calculateOptionPrice(
    option, volatility=0.14, underPrice=525))
print(calc)

Order book

eurusd = Forex('EURUSD')
ticker = ib.reqMktDepth(eurusd)
while ib.sleep(5):
    print(
        [d.price for d in ticker.domBids],
        [d.price for d in ticker.domAsks])

Minimum price increments

usdjpy = Forex('USDJPY')
cd = ib.reqContractDetails(usdjpy)[0]
print(cd.marketRuleIds)

rules = [
    ib.reqMarketRule(ruleId)
    for ruleId in cd.marketRuleIds.split(',')]
print(rules)

News articles

newsProviders = ib.reqNewsProviders()
print(newsProviders)
codes = '+'.join(np.code for np in newsProviders)

amd = Stock('AMD', 'SMART', 'USD')
ib.qualifyContracts(amd)
headlines = ib.reqHistoricalNews(amd.conId, codes, '', '', 10)
latest = headlines[0]
print(latest)
article = ib.reqNewsArticle(latest.providerCode, latest.articleId)
print(article)

News bulletins

ib.reqNewsBulletins(True)
ib.sleep(5)
print(ib.newsBulletins())

Dividends

contract = Stock('INTC', 'SMART', 'USD')
ticker = ib.reqMktData(contract, '456')
ib.sleep(2)
print(ticker.dividends)

Output:

Dividends(past12Months=1.2, next12Months=1.2, nextDate=datetime.date(2019, 2, 6), nextAmount=0.3)

Fundemental ratios

contract = Stock('IBM', 'SMART', 'USD')
ticker = ib.reqMktData(contract, '258')
ib.sleep(2)
print(ticker.fundamentalRatios)

Integration with PyQt5 or PySide2

This example of a ticker table shows how to integrate both realtime streaming and synchronous API requests in a single-threaded Qt application. The API requests in this example are connect and ib.qualifyContracts(); The latter is used to get the conId of a contract and use that as a unique key.

The Qt interface will not freeze when a request is ongoing and it is even possible to have multiple outstanding requests at the same time.

This example depends on PyQt5:

pip3 install -U PyQt5.

It’s also possible to use PySide2 instead; To do so uncomment the PySide2 import and util.useQt lines in the example and comment out their PyQt5 counterparts.

Integration with Tkinter

To integrate with the Tkinter event loop, take a look at this example app.