[Python] Interactive Brokers Python Multiple Symbol Request

I was able to piece together a script from IB's documentation/examples and forums on this site. I am getting the output I want for a single symbol, however, if I use a list of stocks, I cannot figure out a way to pass the ticker symbol through to the DF output file. My workaround was to create a dictionary that uses the list sequence (see below) however the output from IB's API changes slightly each time rendering the symbols mostly pointless. The list I am using below normally has 20+ names but may change, i cut it down to make it easier to view.

@Brian/and or other developers, if there is a way to create either a unique ID/sequence for each symbol call and stamp it to data that is brought back, i can then utilize a dictionary to apply the symbol. In the other forum, you passed in a line where n_id = n_id +1, if that can be applied and is linked to each specific call which is done in order of the list, then that could work?

from ibapi.client import EClient
from ibapi.wrapper import EWrapper
from ibapi.contract import Contract
import pandas as pd
import threading
import time
from datetime import timedelta
import datetime

class IBapi(EWrapper, EClient):
def __init__(self):
EClient.__init__(self, self)
self.data = [] #Initialize variable to store candle

def historicalData(self, reqId, bar):
#print(f'Time: {bar.date} Close: {bar.close} Volume: {bar.volume}',reqId)
self.data.append([bar.date, bar.close, bar.volume, reqId])

def run_loop():
app.run()

app = IBapi()
app.connect('127.0.0.1', 7496, 123)

#Start the socket in a thread
api_thread = threading.Thread(target=run_loop, daemon=True)
api_thread.start()

time.sleep(1) #Sleep interval to allow time for connection to server

symbols = ['SPY','MSFT','GOOG','AAPL','QQQ','IWM','TSLA']

for sym in symbols:
contract = Contract()
contract.symbol = str(sym)
contract.secType = "STK"
contract.exchange = "SMART"
contract.currency = "USD"
#contract.primaryExchange = "ISLAND"
app.reqHistoricalData(1, contract, "", "1 D", "10 mins", "ADJUSTED_LAST", 1, 2, False, [])

time.sleep(5) #sleep to allow enough time for data to be returned

df = pd.DataFrame(app.data, columns=['DateTime', 'ADJUSTED_LAST','Volume','reqId'])
df['DateTime'] = pd.to_datetime(df['DateTime'],unit='s') #,unit='s')

df['Count'] = df.groupby('DateTime').cumcount()+1
sym_dict = {1:'SPY',2:'MSFT',3:'GOOG',4:'AAPL',5:'QQQ',6:'IWM',7:'TSLA'}

df['Ticker'] = df['Count'].map(sym_dict)

print(df)


#edit, adding in @Brian's detail:

from ibapi.client import EClient
from ibapi.wrapper import EWrapper
from ibapi.contract import Contract
import pandas as pd
import time
from datetime import timedelta
import datetime

start = datetime.datetime.utcnow()

class IBapi(EWrapper, EClient):
def __init__(self):
EClient.__init__(self, self)
self.data = []

def error(self, reqId, errorCode, errorString):
print("Error. Id: " , reqId, " Code: " , errorCode , " Msg: " , errorString)

def historicalData(self, reqId, bar):
self.data.append([bar.date, bar.close, bar.volume, sym_dict[reqId]])
print("HistoricalData. ReqId:", sym_dict[reqId], "BarData.", bar)

# include this callback to track progress and maybe disconnectwhen all are finished
def historicalDataEnd(self, reqId: int, start: str, end: str):
print("finished", sym_dict[reqId])

def run_loop():
app.run()

app = IBapi()
app.connect('127.0.0.1', 7496, 123)

# you should wait for nextValidId instead of sleeping, what if it takes more than 1 second? @john: how do i do this?
time.sleep(5) @john: how do i do this? wait for nextValidId?

symbols = ['SPY','MSFT','GOOG','AAPL','QQQ','IWM','TSLA']

reqId = 1
sym_dict = {}
for sym in symbols:
contract = Contract()
contract.symbol = str(sym)
sym_dict[reqId] = sym
contract.secType = "STK"
contract.exchange = "SMART"
contract.currency = "USD"
#contract.primaryExchange = "ISLAND" # you may need this for msft
app.reqHistoricalData(reqId, contract, "", "1 D", "10 mins", "ADJUSTED_LAST", 1, 2, False, [])
reqId += 1
time.sleep(5)

df = pd.DataFrame(app.data, columns=['DateTime', 'ADJUSTED_LAST','Volume','sym'])
df['DateTime'] = pd.to_datetime(df['DateTime'],unit='s') #,unit='s')
df = df.set_index(['sym','DateTime']).sort_index()
print(df)
app.disconnect()

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