Xtquant

from xtquant import xtdata

xtdata.connect()

# Get the full list of Shanghai & Shenzhen A-shares
stock_list = xtdata.get_stock_list_in_sector('沪深A股')
print(f"Total {len(stock_list)} A-shares")

# Batch download daily K-line data (recommended to download in batches to avoid timeout)
batch_size = 50
for i in range(0, len(stock_list), batch_size):
    batch = stock_list[i:i+batch_size]
    for stock in batch:
        try:
            xtdata.download_history_data(stock, '1d', start_time='20240101', end_time='20240630')
        except Exception as e:
            print(f"Failed to download {stock}: {e}")
    print(f"Downloaded {min(i+batch_size, len(stock_list))}/{len(stock_list)}")

# Batch retrieve data
data = xtdata.get_market_data_ex(
    [], stock_list[:10], period='1d',
    start_time='20240101', end_time='20240630',
    dividend_type='front'
)
for code, df in data.items():
    print(f"{code}: {len(df)} records, latest close={df['close'].iloc[-1]}")

from xtquant import xtdata, xtconstant
from xtquant.xttrader import XtQuantTrader, XtQuantTraderCallback
from xtquant.xttype import StockAccount
import threading

# === Trading Callbacks ===
class MyCallback(XtQuantTraderCallback):
    def on_stock_order(self, order):
        print(f'Order: {order.stock_code} status={order.order_status} {order.status_msg}')
    def on_stock_trade(self, trade):
        print(f'Trade: {trade.stock_code} {trade.traded_volume}@{trade.traded_price}')
    def on_order_error(self, error):
        print(f'Error: {error.error_msg}')

# === Initialize Trading ===
path = r'D:\券商QMT\userdata_mini'
xt_trader = XtQuantTrader(path, 888888)
xt_trader.register_callback(MyCallback())
xt_trader.start()
xt_trader.connect()
account = StockAccount('your_account')
xt_trader.subscribe(account)

# === Quote Monitoring Parameters ===
target_stock = '000001.SZ'
buy_price = 10.50    # Target buy price
sell_price = 11.50   # Target sell price
bought = False

def on_tick(datas):
    """Real-time tick callback: automatically places orders when price hits target"""
    global bought
    for code, tick in datas.items():
        price = tick['lastPrice']
        print(f'{code}: latest price={price}')

        # Price drops to or below target buy price, buy
        if price <= buy_price and not bought:
            order_id = xt_trader.order_stock(
                account, code, xtconstant.STOCK_BUY, 100,
                xtconstant.FIX_PRICE, buy_price, 'auto_buy', '条件触发买入'
            )
            print(f'Buy triggered: order_id={order_id}')
            bought = True

        # Price rises to or above target sell price, sell
        elif price >= sell_price and bought:
            order_id = xt_trader.order_stock(
                account, code, xtconstant.STOCK_SELL, 100,
                xtconstant.FIX_PRICE, sell_price, 'auto_sell', '条件触发卖出'
            )
            print(f'Sell triggered: order_id={order_id}')
            bought = False

# === Start quote subscription (separate thread) ===
xtdata.connect()
def run_data():
    xtdata.subscribe_quote(target_stock, period='tick', callback=on_tick)
    xtdata.run()

t = threading.Thread(target=run_data, daemon=True)
t.start()

# Keep the main thread running
xt_trader.run_forever()

from xtquant import xtdata, xtconstant
from xtquant.xttrader import XtQuantTrader, XtQuantTraderCallback
from xtquant.xttype import StockAccount
import pandas as pd

xtdata.connect()

# Define stock pool
stock_pool = ['000001.SZ', '600036.SH', '601318.SH', '000858.SZ', '300750.SZ']

# Download historical data
for stock in stock_pool:
    xtdata.download_history_data(stock, '1d', start_time='20240101', end_time='20241231')

# Retrieve data and compute signals
signals = {}
for stock in stock_pool:
    data = xtdata.get_market_data_ex([], [stock], period='1d',
        start_time='20240101', end_time='20241231', dividend_type='front')
    df = data[stock]

    # Calculate 5-day and 20-day moving averages
    df['ma5'] = df['close'].rolling(5).mean()
    df['ma20'] = df['close'].rolling(20).mean()

    # Determine the latest signal
    if len(df) >= 21:
        latest = df.iloc[-1]
        prev = df.iloc[-2]
        if prev['ma5'] <= prev['ma20'] and latest['ma5'] > latest['ma20']:
            signals[stock] = 'BUY'   # 金叉
        elif prev['ma5'] >= prev['ma20'] and latest['ma5'] < latest['ma20']:
            signals[stock] = 'SELL'  # 死叉
        else:
            signals[stock] = 'HOLD'  # Hold

print("Trading signals:")
for stock, signal in signals.items():
    print(f"  {stock}: {signal}")

from xtquant import xtdata

xtdata.connect()

# Get the list of Shanghai & Shenzhen A-shares
stock_list = xtdata.get_stock_list_in_sector('沪深A股')

# Download financial data
xtdata.download_financial_data(stock_list[:100])  # Download the first 100

# Retrieve financial data
for stock in stock_list[:10]:
    data = xtdata.get_financial_data([stock])
    if stock in data and 'PershareIndex' in data[stock]:
        psi = data[stock]['PershareIndex']
        if len(psi) > 0:
            latest = psi[-1]
            roe = latest.get('du_return_on_equity', 0)
            eps = latest.get('s_fa_eps_basic', 0)
            print(f"{stock}: ROE={roe}, EPS={eps}")