尝试使用 python 和 IB API 获取多种证券的历史数据 - df 不在循环之间清除

Question

I'm trying to get historical data for several products through the IB API, and store each product in a dataframe (which I need to save in separate csv files).

This is my code, the main issue is that the dataframe isn't clearing between loops, when moving onto the second loop the df contains data for 2 products, the third for 3. I'm not sure where / how to clear the df.

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

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

    def historicalData(self, reqId, bar):
        self.data.append([bar.date, bar.open, bar.high, bar.low, bar.close, bar.volume])
           
    def error(self, reqId, errorCode, errorString):
        print("Error. Id: " , reqId, " Code: " , errorCode , " Msg: " , errorString)

    def historicalDataEnd(self, reqId: int, start: str, end: str):
        print("HistoricalDataEnd. ReqId:", reqId, "from", start, "to", end)
        self.df = pd.DataFrame(self.data)

def run_loop():
    app.run()
    
app = IBapi()

#Create contract object
ES_contract = Contract()
ES_contract.symbol = 'ES'
ES_contract.secType = 'FUT'
ES_contract.exchange = 'GLOBEX'
ES_contract.lastTradeDateOrContractMonth  = '202209'

#Create contract object
VIX_contract = Contract()
VIX_contract.symbol = 'VIX'
VIX_contract.secType = 'IND'
VIX_contract.exchange = 'CBOE'
VIX_contract.currency = 'USD'

#Create contract object
DAX_contract = Contract()
DAX_contract.symbol = 'DAX'
DAX_contract.secType = 'FUT'
DAX_contract.exchange = 'EUREX'
DAX_contract.currency = 'EUR'
DAX_contract.lastTradeDateOrContractMonth  = '202209'
DAX_contract.multiplier = '25'

products={'ES': ES_contract, 'VIX': VIX_contract,  'DAX': DAX_contract}

nid=1

app.connect('127.0.0.1', 4001, 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

def fetchdata_function(name,nid):
    df=pd.DataFrame()
    #Request historical candles
    app.reqHistoricalData(nid, products[name], '', '1 W', '5 mins', 'TRADES', 0, 2, False, [])
    time.sleep(10) #sleep to allow enough time for data to be returned
    df = pd.DataFrame(app.data, columns=['Date', 'Open', 'High', 'Low', 'Close', 'Volume'])
    df['Date'] = pd.to_datetime(df['Date'],unit='s')
    df=df.set_index('Date')
    df.to_csv('1week'+str(name)+'5min.csv')  
    print(df)

names=['ES', 'DAX', 'VIX']

for name in names:     
    fetchdata_function(name,nid)
    nid=nid+1   
    
app.disconnect()

Answer 1

create a dictionary and append the app.data as a key value pair in the historicaldata callback. Then you can access them separately - in fact converting a dict to multi-level dataframe is also possible