1.修改有概念的强拉参数 2.修改充分交易量函数基础条件 3.GUI新增及修改 行情板块强度模块，服务端解析日志数据及应答 4.

admin

2025-05-26 e59b4e4ae8e4861d850b208ffac75c0b967c6500

1.修改有概念的强拉参数
2.修改充分交易量函数基础条件
3.GUI新增及修改 行情板块强度模块，服务端解析日志数据及应答
4.

 data_server.py

@@ -17,7 +17,7 @@
from log_module import log_export, async_log_util
from log_module.log import hx_logger_l2_transaction, logger_debug, logger_request_api
from strategy import data_cache
from strategy.kpl_data_manager import KPLStockOfMarketsPlateLogManager
from strategy.kpl_data_manager import KPLStockOfMarketsPlateLogManager, KPLMarketStockHeatLogManager
from strategy.trade_setting import TradeSetting
from trade import huaxin_trade_api, huaxin_trade_data_update
from trade.huaxin_trade_record_manager import DelegateRecordManager, DealRecordManager, MoneyManager, PositionManager
@@ -192,19 +192,41 @@
            finally:
                if use_time_list and use_time_list[-1][1] > 10:
                    logger_debug.warning(f"环境获取时间大于10s({request_id}):{use_time_list}")

        elif url.path == "/load_kpl_stock_of_markets_plate":
        # 获取板块强度数据
        elif url.path == "/load_get_kpl_market_sift_plate":
            # 加载数据
            KPLStockOfMarketsPlateLogManager().load_data()
            response_data = json.dumps({"code": 0, "msg": "暂无内容"})
        elif url.path == "/get_kpl_stock_of_markets_plate":
        elif url.path == "/get_kpl_market_sift_plate":
            # 获取开盘啦流入板块详细信息
            print("==========get_kpl_market_sift_plate==========")
            try:
                time_str = params_dict.get("time")
                if not time_str:
                    time_str = tool.get_now_time_str()
                fdatas = KPLStockOfMarketsPlateLogManager().get_filter_log_datas()
                response_data = json.dumps({"code": 1, "msg": "暂无内容"})
                for i in range(len(fdatas) - 1, -1, -1):
                    if fdatas[i][0] <= time_str:
                        response_data = json.dumps({"code": 0, "data": fdatas[i]})
                        break
            except Exception as e:
                logging.exception(e)
                response_data = json.dumps({"code": 1, "msg": str(e)})

        # 获取个股强度数据
        elif url.path == "/load_get_kpl_market_stock_heat":
            # 加载数据
            KPLMarketStockHeatLogManager().load_data()
            response_data = json.dumps({"code": 0, "msg": "暂无内容"})
        elif url.path == "/get_get_kpl_market_stock_heat":
            # 获取开盘啦流入板块详细信息
            print("==========get_kpl_stock_of_markets_plate==========")
            try:
                time_str = params_dict.get("time")
                if not time_str:
                    time_str = tool.get_now_time_str()
                fdatas = KPLStockOfMarketsPlateLogManager().get_filter_log_datas()
                fdatas = KPLMarketStockHeatLogManager().get_filter_log_datas()
                response_data = json.dumps({"code": 1, "msg": "暂无内容"})
                for i in range(len(fdatas) - 1, -1, -1):
                    if fdatas[i][0] <= time_str:

 log_module/log_export.py

@@ -53,6 +53,31 @@
    return contents


def load_market_stock_heat(date=tool.get_now_date_str()):
    """
     获取精选流入的成分股
    :param date:
    :return:
    """
    path = f"{constant.get_path_prefix()}/low_suction_log/gp/kpl/market_sift_plate.{date}.log"
    fdatas = []
    if os.path.exists(path):
        with open(path, 'r', encoding="utf-8") as f:
            lines = f.readlines()
            for line in lines:
                if line:
                    time_str = __get_async_log_time(line)
                    try:
                        data = line.split(" - ")[1].strip()
                        if data.startswith("["):
                            data = data[data.find("]") + 1:].strip()
                        data_dict = eval(data)
                        fdatas.append((time_str, data_dict))
                    except:
                        pass
    return fdatas


def load_stock_of_markets_plate(date=tool.get_now_date_str()):
    """
     获取精选流入的成分股

 strategy/basic_methods.py

@@ -210,10 +210,11 @@

# 充分交易量公式 用于计算日内涨幅段理论的安全交易量值
def sufficient_volume(current_volume, yesterday_volume, today_growth):
    if current_volume < yesterday_volume * today_growth:
        return False
    else:
        return True
    if today_growth > 0:
        if current_volume < yesterday_volume * today_growth:
            return False
        else:
            return True


# 计算 委买和委卖的比例函数(获取买盘强度数据)【掘金数据结构】

 strategy/buying_strategy.py

@@ -315,13 +315,13 @@
                                        logger_info(f"重复相交概念==={intersection_plate}")
                                    # 调用充分交易量函数
                                    sufficient_volume = basic_methods.sufficient_volume(current_volume, k_line_data[0]['volume'], today_growth)
                                    logger_info(f"【{k_line_data[0]['sec_name']}】当日当时量是否相对涨幅充足？===【{sufficient_volume}】 ！当日当时总成交量：{round(current_volume / 10000, 2)}万，昨日的总成交量{round(k_line_data[0]['volume'] / 10000, 2)}万，当日当时涨幅：{today_growth}%。")
                                    logger_info(f"【{k_line_data[0]['sec_name']}】当日当时量是否相对涨幅充足？===【{sufficient_volume}】 ！当时与昨日成交率占比:{round(current_volume/k_line_data[0]['volume'], 2)}%，当日当时总成交量：{round(current_volume / 10000, 2)}万，昨日的总成交量{round(k_line_data[0]['volume'] / 10000, 2)}万，当日当时涨幅：{today_growth}%。")
                                    logger_info(f"【有概念】(涨停列表中包含自身概念 且 不是唯一包含概念不可用) ！最新价: {current_price}，，当日当时涨幅：{today_growth}%。")
                                    # 有概念有强度视界
                                    if strength_list_have_it is True:
                                        logger_info(f"【有概念 有强度】出现在板块强度大于2的列表中 瞬时量幅比：{round(last_volume_to_growth_ratio, 2)}%，当日当时涨幅：{today_growth}%。")
                                        if tick_growth < 0.8 and (free_market_value <= 100 and current_price <= 10):
                                            logger_info(f"【有概念 有强度 有强拉】瞬时涨幅 > 0.8% ！瞬时涨幅：{round(tick_growth, 2)}%")
                                        if tick_growth < 0.5 and (free_market_value <= 100 and current_price <= 10):
                                            logger_info(f"【有概念 有强度 无强拉】瞬时涨幅 < 0.5% ！瞬时涨幅：{round(tick_growth, 2)}%")
                                            return
                                        if last_volume_to_growth_ratio > 0.8 and (free_market_value <= 100 and current_price <= 10):
                                            logger_info(f"【不利】瞬时量幅比> 0.8 且 (小自由市值<40亿 或 最新价小于20元 )！，瞬时量幅比：{round(last_volume_to_growth_ratio, 2)}%，自由市值：{free_market_value} 亿。")

 strategy/kpl_data_manager.py

@@ -1,8 +1,42 @@
from log_module import log_export, async_log_util
from log_module.log import logger_stock_of_markets_plate, logger_debug
from log_module.log import logger_stock_of_markets_plate, logger_debug, logger_kpl_market_sift_plate
from utils import tool

# 开盘啦个股强度日志管理
@tool.singleton
class KPLMarketStockHeatLogManager:
    """
    精选流入板块与板块代码日志管理
    """

    def __init__(self):
        # 过滤后的日志数据
        self.__filter_log_datas = []

    def __load_data(self):
        if tool.get_now_time_str() > '13:10:00':
            logger_debug.info("KPLMarketStockHeatLogManager 开始加载数据")
            datas = log_export.load_market_stock_heat()
            for data in datas:
                # (发生时间,[净流入板块], {"板块":(代码, 名称, 涨幅)})
                self.__filter_log_datas.append(self.__filter_origin_data(data))
            logger_debug.info("KPLMarketStockHeatLogManager 数据加载完成：{}", len(self.__filter_log_datas))

    def load_data(self):
        self.__load_data()

    def __filter_origin_data(self, data):
        return (data[0], [x[1] for x in data[1][0]],
                {p: [xx for xx in data[1][1][p]] for p in data[1][1]})

    def add_log(self, in_plates_info, plate_codes_info):
        oringin_data = (tool.get_now_time_str(), in_plates_info, plate_codes_info)
        async_log_util.info(logger_kpl_market_sift_plate, f"{(oringin_data[1], oringin_data[2])}")

    def get_filter_log_datas(self):
        return self.__filter_log_datas

# 开盘啦个股强度日志管理
@tool.singleton
class KPLStockOfMarketsPlateLogManager:
    """

 strategy/plate_strength_analysis.py

@@ -75,13 +75,14 @@
    # print(f"market_sift_plate 数 ======{len(market_sift_plate['list'])}")

    # 精选板块【前20】 market_sift_plate['list'] ======
    if data_cache.OPENING_TIME < now_time < data_cache.CLOSING_TIME:
    if data_cache.OPENING_TIME < now_time < data_cache.AFTER_CLOSING_TIME:
        logger_kpl_market_sift_plate.info(f"{market_sift_plate['list']}")
    # 总控制时间段
    if not (data_cache.OPENING_TIME < now_time < data_cache.NOON_MARKET_TIME):
        return
    # ['801235', '化工', 6996, 0.027, 2.43, 117836347690, -122548038, 8105997595, -8228545633, 0.92, 8595377775454, 0.09, 332297449, 9954902621130, -192457252, 24.0487, 17.1809, 6996, 0.027]
    # market_sift_plate['list'][0] = ['801062', '军工', 3520, -0.49, 0.666, 139133934669, 383864272, 9077352839, -8693488567, 1.183, 6129448037490,-0.12, 168245858, 7088854452019, -290614763, 50.2408, 30.3672, 3520, 0]
    # 行情精选板块列表 前20 中的 第一个板块列表数据 = 【代码，板块名称，强度，涨幅？，0.666？，成交额？，现额？，主买，主卖，1.183？，流通值？，-0.12？，300W大单净额？，总市值？，上季度机构增仓，今年平均PE，次年平均PE，强度，未知0值】
    # 行情精选板块列表 前20 中的 第一个板块列表数据 = 【代码，板块名称，强度，涨幅？，量比？，成交额？，现额？，主买，主卖，1.183？，流通值？，-0.12？，300W大单净额？，总市值？，上季度机构增仓，今年平均PE，次年平均PE，强度，未知0值】
    # logger.info(f"market_sift_plate['list'][0]  ======{market_sift_plate['list'][0]}")
    # 初始化精选板块对应个股字典
    market_sift_plate_stock_dict = {}