[Python] loading historical data i appending to Realtime n Python from IB API

How can i load historical data from IB api and append to realtime current bars ona 1 min chart?

def get_front_month_contract(symbol, exchange="CME", currency="USD", secType="FUT"):
ib = IB()
st.info("Connecting to IBKR Gateway via IB Insync...")
try:
ib.connect('--------', 48879, clientId=1)
except Exception as e:
st.error(f"Error connecting to IBKR Gateway: {e}")
return None
contract = Future()
contract.symbol = symbol
contract.secType = secType
contract.exchange = exchange
contract.currency = currency
st.info(f"Requesting contract details for {symbol} futures...")
details = ib.reqContractDetails(contract)
if not details:
st.error(f"No contract details found for {symbol}.")
ib.disconnect()
return None
today = datetime.today()
valid_contracts = []
for d in details:
expiry_str = d.contract.lastTradeDateOrContractMonth
expiry_date = parse_expiry(expiry_str)
if expiry_date and expiry_date > today:
valid_contracts.append((expiry_date, d.contract))
if not valid_contracts:
st.error(f"No active futures contracts found for {symbol}.")
ib.disconnect()
return None
valid_contracts.sort(key=lambda x: x[0])
front_month_contract = valid_contracts[0][1]
st.info(f"Selected front month contract: {front_month_contract.localSymbol}")
ib.disconnect()
return front_month_contract

def get_historical_data(contract, durationStr, barSizeSetting, whatToShow='TRADES', useRTH=True):
ib = IB()
try:
ib.connect('127.0.0.1', 4002, clientId=10)
except Exception as e:
st.error(f"Error connecting for historical data: {e}")
return pd.DataFrame()
bars = ib.reqHistoricalData(
contract,
endDateTime='',
durationStr=durationStr,
barSizeSetting=barSizeSetting,
whatToShow=whatToShow,
useRTH=useRTH,
formatDate=1
)
ib.disconnect()
if not bars:
st.error("No historical data returned from IB.")
return pd.DataFrame()
data = []
for bar in bars:
data.append({
"Datetime": pd.to_datetime(bar.date),
"Open": bar.open,
"High": bar.high,
"Low": bar.low,
"Close": bar.close,
"Volume": bar.volume
})
df = pd.DataFrame(data)
df.set_index("Datetime", inplace=True)
return

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