# coding:utf-8
import time, datetime, traceback, sys, json
import redis
from xtquant import xtdata
from xtquant.xttrader import XtQuantTrader, XtQuantTraderCallback
from xtquant.xttype import StockAccount
from xtquant import xtconstant

# ================= 配置区域 =================
QMT_PATH = r'D:\qmt\投研\迅投极速交易终端睿智融科版\userdata'
ACCOUNT_ID = '2000128'
ACCOUNT_TYPE = 'STOCK'

REDIS_HOST = '127.0.0.1'
REDIS_PORT = 6379
REDIS_PASS = None

# 策略基础名称 (不需要加 _real，代码会自动加)
STRATEGY_BASE_NAME = 'default_strategy'
# ===========================================

# 定义监听的队列名称 (只监听实盘队列，物理屏蔽回测数据)
LISTEN_QUEUE = f"{STRATEGY_BASE_NAME}_real"


class MyXtQuantTraderCallback(XtQuantTraderCallback):
    def on_disconnected(self):
        print("连接断开")

    def on_stock_order(self, order):
        print(f"委托回报: {order.order_id} {order.order_remark}")

    def on_stock_trade(self, trade):
        print(f"成交: {trade.stock_code} {trade.traded_volume}")

    def on_order_error(self, order_error):
        print(f"下单失败: {order_error.error_msg}")


def init_redis():
    try:
        r = redis.Redis(host=REDIS_HOST, port=REDIS_PORT, password=REDIS_PASS, decode_responses=True)
        r.ping()
        return r
    except Exception as e:
        print(f"Redis连接失败: {e}")
        return None


def is_msg_valid(data):
    """
    【安全核心】校验消息时效性与合法性
    """
    try:
        # 1. 检查是否为回测标记 (防御性编程，虽然队列已物理隔离)
        if data.get('is_backtest', False):
            print(f"警报：拦截到回测数据，已丢弃！")
            return False

        # 2. 检查时间戳
        msg_time_str = data.get('timestamp')
        if not msg_time_str:
            print("数据缺失时间戳，丢弃")
            return False

        # 解析消息时间
        # 格式必须匹配策略端发送的 '%Y-%m-%d %H:%M:%S'
        msg_dt = datetime.datetime.strptime(msg_time_str, '%Y-%m-%d %H:%M:%S')
        msg_date = msg_dt.date()

        # 获取当前服务器日期
        today = datetime.date.today()

        # 3. 【核心】判断是否为当天的消息
        if msg_date != today:
            print(f"拦截过期消息: 消息日期[{msg_date}] != 今日[{today}]")
            return False

        # 可选：如果你想更严格，可以判断时间差不能超过5分钟
        # delta = datetime.datetime.now() - msg_dt
        # if abs(delta.total_seconds()) > 300: ...

        return True

    except Exception as e:
        print(f"校验逻辑异常: {e}")
        return False


def process_redis_signal(r_client, xt_trader, acc):
    try:
        msg_json = r_client.lpop(LISTEN_QUEUE)
        if not msg_json: return

        print(f"收到信号: {msg_json}")
        data = json.loads(msg_json)

        if not is_msg_valid(data): return  # 之前的校验逻辑

        stock_code = data['stock_code']
        action = data['action']
        price = float(data['price'])

        # 获取切分份数
        # 兼容性处理：如果redis里还是旧key 'weight'，也可以尝试获取
        div_count = float(data.get('div_count', data.get('weight', 1)))

        # =========================================================
        #   买入逻辑：资金切片法
        # =========================================================
        if action == 'BUY':
            # 1. 必须查最新的可用资金 (Available Cash)
            asset = xt_trader.query_stock_asset(acc)
            if not asset:
                print("错误：无法查询资产")
                return

            current_cash = asset.cash

            # 2. 计算下单金额
            # 逻辑：Amount = Cash / div_count
            if div_count <= 0: div_count = 1  # 防止除0

            target_amount = current_cash / div_count

            # 3. 打印调试信息 (非常重要)
            print(f"【资金分配】可用现金:{current_cash:.2f} / 切分份数:{div_count} = 下单金额:{target_amount:.2f}")

            # 4. 计算股数
            if price <= 0: price = 1.0

            # 过滤小额杂单
            if target_amount < 2000:
                print(f"忽略：金额过小 ({target_amount:.2f})")
                return

            vol = int(target_amount / price / 100) * 100

            if vol >= 100:
                xt_trader.order_stock(acc, stock_code, xtconstant.STOCK_BUY, vol, xtconstant.FIX_PRICE, price,
                                      STRATEGY_BASE_NAME, 'PyBuy')
                print(f"买入下单: {stock_code} {vol}股")
            else:
                print(f"计算股数不足100股")

        # =========================================================
        #   卖出逻辑 (清仓)
        # =========================================================
        elif action == 'SELL':
            positions = xt_trader.query_stock_positions(acc)
            target_pos = next((p for p in positions if p.stock_code == stock_code), None)

            if target_pos and target_pos.can_use_volume > 0:
                xt_trader.order_stock(acc, stock_code, xtconstant.STOCK_SELL, target_pos.can_use_volume,
                                      xtconstant.FIX_PRICE, price, STRATEGY_BASE_NAME, 'PySell')
                print(f"卖出下单: {stock_code} {target_pos.can_use_volume}股")
            else:
                print(f"无可用持仓: {stock_code}")

    except Exception as e:
        print(f"处理异常: {e}")
        traceback.print_exc()


if __name__ == '__main__':
    r_client = init_redis()
    session_id = int(time.time())
    xt_trader = XtQuantTrader(QMT_PATH, session_id)
    acc = StockAccount(ACCOUNT_ID, ACCOUNT_TYPE)
    callback = MyXtQuantTraderCallback()
    xt_trader.register_callback(callback)
    xt_trader.start()
    xt_trader.connect()
    xt_trader.subscribe(acc)

    print(f"=== 启动监听: {LISTEN_QUEUE} ===")
    print("只处理当日的实盘/模拟信号，自动过滤回测数据及历史遗留数据。")

    while True:
        if r_client:
            process_redis_signal(r_client, xt_trader, acc)
        time.sleep(60)