1.已成交股票详情列表 添加逻辑提前 2.打印收盘涨停概念列表

admin

3 天以前 084d7337165d6d17b77392054c984dbf9916169a

 main.py

@@ -1,6 +1,7 @@
# coding=utf-8
from __future__ import print_function, absolute_import, unicode_literals
import logging
import multiprocessing
import threading
import time

@@ -17,9 +18,11 @@
# 引入瞬时分时行情模块
# 引入账户管理模块【进行资金和仓位管理】
from strategy import kpl_api, data_cache, check_timer, all_K_line, instant_time_market, account_management, \
    order_methods, local_data_management, kpl_data_manager, market_sentiment_analysis, plate_strength_analysis
from huaxin_client import l2_market_client, l2_client
from log_module import async_log_util
    order_methods, local_data_management, kpl_data_manager, market_sentiment_analysis, plate_strength_analysis, \
    selling_strategy
from huaxin_client import l2_market_client, l2_client, trade_client
from log_module import async_log_util, log
from strategy.order_methods import TodayBuyCodeManager
from trade import huaxin_trade_data_update, huaxin_trade_api
from utils import hx_qc_value_util, huaxin_util, juejin_api, tool

@@ -65,19 +68,9 @@
    local_data_management.read_local_K_line_data()
    # 读取本地个股所属板块数据 并更新到data_cache
    local_data_management.read_local_all_stocks_plate_data()
    # 初始化拉取当日买入代码
    TodayBuyCodeManager()

    # todo 2025-03-25 测试无误即可删除下部注释
    # # 先使用json.load()直接从文件中读取【已经存储在本地的K线指标属性字典】并解析JSON数据
    # if os.path.exists(constant.K_BARS_PATH):
    #     with open(constant.K_BARS_PATH, 'r', encoding='utf-8') as f:
    #         data_cache.all_stocks_all_K_line_property_dict = json.load(f)
    #         print(
    #             f"data_cache.all_stocks_all_K_line_property_dict的个数==={len(data_cache.all_stocks_all_K_line_property_dict)}")

    # # 获取目标标的K线---初始化
    # all_K_line.main_index_k_line_history.init(data_cache.DataCache().today_date, data_cache.DataCache().next_trading_day, data_cache.DataCache().main_index_stocks)
    # # 直接调用主要指数K线写入本地文件
    # all_K_line.main_index_k_line_dict_write()


# 第一步：初始化context函数，并开启获取实时数据的线程
@@ -99,8 +92,11 @@
    #  开盘啦的涨停概念的回调函数
    def kpl_limit_up_process(datas):
        # print(f"回调成功==={datas}")
        now_time = tool.get_now_time_str()
        if datas is not None and len(datas) > 0:
            data_cache.limit_up_block_names = datas
            if data_cache.CLOSING_TIME < now_time < data_cache.AFTER_CLOSING_TIME:
                logger_common.info(f"收盘涨停概念列表更新==={now_time}=={datas}")
        else:
            data_cache.limit_up_block_names = []

@@ -110,13 +106,17 @@
    # 开启开盘啦 涨停列表 和 全盘个股概念板块 接口线程
    # 涨停概念线程
    # threading.Thread(target=plate_strength_analysis.kpl_limit_up_process, daemon=True).start()    #该行代码为只运行单一线程不回调数据的方式
    threading.Thread(target=plate_strength_analysis.kpl_limit_up_process, args=(kpl_limit_up_process,), daemon=True).start()
    threading.Thread(target=plate_strength_analysis.kpl_limit_up_process, args=(kpl_limit_up_process,),
                     daemon=True).start()

    # # 开盘啦的板块强度下的个股强度回调函数
    def get_market_sift_plate_its_stock_power_process(market_sift_plate_stock_dict):
    def get_market_sift_plate_its_stock_power_process(market_sift_plate_info):
        # print(f"回调成功===精选板块股票强度数据更新==={market_sift_plate_stock_dict}")
        # logger_kpl_jingxuan_in.info(f"{market_sift_plate_stock_dict}")
        data_cache.market_sift_plate_stock_dict = market_sift_plate_stock_dict
        market_sift_plate_stock_dict,  market_sift_plates = market_sift_plate_info[0], market_sift_plate_info[1]
        if market_sift_plate_stock_dict:
            data_cache.market_sift_plate_stock_dict = market_sift_plate_stock_dict
            data_cache.market_sift_plates = market_sift_plates

    # 板块强度下个股强度线程
    threading.Thread(target=plate_strength_analysis.get_market_sift_plate_its_stock_power_process,
@@ -157,6 +157,8 @@
        :return:
        """
        if datas:
            start_time = time.time()
            # logger_debug.debug(f"{code} - L2逐笔成交上报：{len(datas)}")
            price, time_str = datas[-1][1], huaxin_util.convert_time(datas[-1][3])
            try:
                # 获取最近的成交价
@@ -165,17 +167,28 @@
                    results = juejin_api.JueJinApi.history_n(tool.get_symbol(code), "1d", 1, 1, "close")
                    if results:
                        self.__pre_close_price_dict[code] = results[0]["close"]
                        logger_debug.debug(f"{code} - 获取到昨日收盘价：{results[0]['close']}")
                if self.__last_price_dict.get(code) == price:
                    return
                limit_up_price = tool.get_limit_up_price(code, self.__pre_close_price_dict[code])
                if code in self.__last_price_dict:
                    if abs(limit_up_price - self.__last_price_dict[code]) < 0.0001 < abs(limit_up_price - price):
                        # TODO 处理炸板逻辑

                        # 炸板
                        logger_debug.info(f"炸板:{code}-({price},{time_str})")
                        # 处理炸板逻辑
                        # 监听了炸板了要做的函数
                        try:
                            selling_strategy.explosion_strategy(code)
                            # 炸板s
                        finally:
                            logger_debug.info(f"炸板:{code}-({price},{time_str})")
            except Exception as e:
                logger_debug.exception(e)
            finally:
                self.__last_price_dict[code] = price
                data_cache.latest_deal_price_dict[code] = price
                use_time = time.time() - start_time
                if use_time > 0.1:
                    logger_debug.warning(f"L2逐笔成交处理耗时：{use_time} 最后一条数据：{datas[-1]}")


    def OnMarketData(self, code, datas):
        # logger_debug.info(f"收到L2Market数据：{datas}")
@@ -185,14 +198,17 @@

    # 实时L2买1成交量
    def OnRealTimeBuy1Info(self, code, buy1_info):
        pass
        # buy1_info: [买1时间,买1价格, 原始买1量, 实时买1量]
        async_log_util.info(logger_debug, f"OnRealTimeBuy1Info：{code}-{buy1_info}")
        # 最终的买1为： 原始买1量+实时买1量
        # async_log_util.info(logger_debug, f"OnRealTimeBuy1Info：{code}-{buy1_info}")
        # L1DataProcessor.excute_sell_rule(code, buy1_info[3], buy1_info[1], "l2-real")


l2_data_callbacks = []


# 订阅持仓L2数据
def __subscript_position_l2():
    """
    订阅持仓L2数据
@@ -217,6 +233,7 @@

# 第三步：执行策略的初始设置
if __name__ == '__main__':
    log.close_print()
    class MyMarketDataCallback(l2_market_client.L2MarketDataCallback):
        def on_markets(self, datas):
            """
@@ -225,8 +242,6 @@
            :return:
            """
            data_cache.latest_code_market_info_dict = {x[0]: x for x in datas}
            if datas:
                print(datas[0])
            if constant.is_windows():
                instant_time_market.get_current_info()
            else:
@@ -234,7 +249,8 @@


    # 加载开盘啦板块日志数据
    kpl_data_manager.KPLStockOfMarketsPlateLogManager()
    kpl_data_manager.KPLMarketsSiftPlateLogManager()
    kpl_data_manager.KPLMarketStockHeatLogManager()

    # 启动异步日志
    threading.Thread(target=async_log_util.run_sync, daemon=True).start()
@@ -242,8 +258,16 @@
    # redis 数据同步
    threading.Thread(target=RedisUtils.run_loop, daemon=True).start()

    # 策略与交易通信队列
    queue_strategy_r_trade_w, queue_strategy_w_trade_r, queue_strategy_w_trade_for_query_r = multiprocessing.Queue(), multiprocessing.Queue(), multiprocessing.Queue()

    # 不是模拟盘的时候启动交易
    if not constant.IS_SIMULATED_TRADE:
        multiprocessing.Process(target=trade_client.run, args=(
            queue_strategy_r_trade_w, queue_strategy_w_trade_r, queue_strategy_w_trade_for_query_r,)).start()

    # 启动交易
    order_methods.run()
    order_methods.run(queue_strategy_r_trade_w, queue_strategy_w_trade_r, queue_strategy_w_trade_for_query_r)

    # 运行华鑫增值服务进程,用于获取K线与交易日历
    threading.Thread(target=hx_qc_value_util.run, daemon=True).start()