获取qmt账号的资金账号后，我们进入下一步，如何获得当前账号的持仓情况

还是之前的步骤，打开qmt，选择独立交易，

之后使用pycharm，编写py文件。

from xtquant import xtdata
from xtquant.xttrader import XtQuantTrader, XtQuantTraderCallback
from xtquant.xttype import StockAccount
import time, datetime, traceback, sys
import pandas as pd

连接miniqmt系统：

path = r'C:\国金QMT交易端模拟\userdata_mini'
# QMT账号
account = '55003243'
# 取账号信息
session_id = int(time.time())
xt_trader = XtQuantTrader(path, session_id)
acc = StockAccount(account, 'STOCK')
# 启动交易线程
xt_trader.start()
# 建立交易连接，返回0表示连接成功
connect_result = xt_trader.connect()
print('建立交易连接，返回0表示连接成功', connect_result)
# 对交易回调进行订阅，订阅后可以收到交易主推，返回0表示订阅成功
subscribe_result = xt_trader.subscribe(acc)
print('对交易回调进行订阅，订阅后可以收到交易主推，返回0表示订阅成功', subscribe_result)

获取账号持仓：

# 查账号持仓
positions = xt_trader.query_stock_positions(acc)
data = pd.DataFrame()
if len(positions) != 0:
    for i in range(len(positions)):
        df = pd.DataFrame()
        df['账号类型'] = [positions[i].account_type]
        df['资金账号'] = [positions[i].account_id]
        df['证券代码'] = [positions[i].stock_code]
        df['证券代码'] = df['证券代码'].apply(lambda x: str(x)[:6])
        df['持仓数量'] = [positions[i].volume]
        df['可用数量'] = [positions[i].can_use_volume]
        df['平均建仓成本'] = [positions[i].open_price]
        df['市值'] = [positions[i].market_value]
        data = pd.concat([data, df], ignore_index=True)
print('持仓', data)