不是目标代码不处理

admin

2025-04-07 400efb993a97e2aaacb3442d46178a125b26bea6

不是目标代码不处理

 main.py

@@ -19,7 +19,7 @@
# 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
    order_methods, local_data_management, kpl_data_manager, market_sentiment_analysis
from huaxin_client import l2_market_client
from log_module import async_log_util
from trade import huaxin_trade_data_update
@@ -89,7 +89,7 @@
    # 实时运行定时器线程【定时器函数目前 只管理 15:00 后运行一次 整理当日涨停信息 和 获取所有个股的板块概念】
    threading.Thread(target=lambda: check_timer.check_time(), daemon=True).start()
    # 获取实时大盘行情情绪综合强度 [分数] 线程
    threading.Thread(target=lambda: kpl_api.get_real_time_market_strong(), daemon=True).start()
    threading.Thread(target=lambda: market_sentiment_analysis.get_real_time_market_strong(), daemon=True).start()
    # 实时检测是否拉取K线线程
    threading.Thread(target=lambda: all_K_line.check_time_and_data_date(), daemon=True).start()
    # print(f"all_stocks_all_K_line_property_dict== {type(data_cache.all_stocks_all_K_line_property_dict)}")

 strategy/account_management.py

@@ -74,7 +74,6 @@
                        logger.info(f"昨日持仓==={securityName}  挂单中》》 挂单数量：{historyPosFrozen}")
                    if availablePosition != 0:
                        logger.info(f"昨日持仓==={securityName}  持仓可用：{availablePosition}")

        # 及时查询持仓字典数据有用，整理持仓集合也有用。整理持仓集合就是仓位管理的一部分功能。
        logger.info(f"今日持仓集合====================================【{data_cache.position_symbols_set}】")
        logger.info(f"今日可用持仓数量====================================【{len(data_cache.available_symbols_set)}】")

 strategy/data_cache.py

@@ -164,10 +164,12 @@
limit_up_block_names = []
# 初始化板块强度下的个股强度
market_sift_plate_stock_dict = {}
# 初始化实时大盘行情市场情绪综合强度【完整】字典
rise_and_fall_statistics_dirt = {}
# 初始化实时大盘行情情绪综合强度[分数]
real_time_market_strong = 0
# 初始化实时大盘行情情绪综合强度分时列表
time_sharing_market_strong_dirt = {}
# 初始化实时大盘行情市场情绪 涨跌统计 字典
real_time_market_sentiment_dirt = {}


# 为所有个股的带属性K线 字典初始化

 strategy/kpl_api.py

@@ -17,8 +17,6 @@
from strategy import data_cache
from strategy import basic_methods
from strategy.kpl_data_manager import KPLStockOfMarketsPlateLogManager
from strategy.market_sentiment_analysis import index_trend_expectation

from trade import middle_api_protocol
from utils import hx_qc_value_util, tool

@@ -187,37 +185,60 @@
    return json.dumps({"errcode": 0, "list": fresults})


# if __name__ == "__main__":


# print(f"打板列表t(pidType)====={daBanList(2)}")
# print(f"获取个股代码的板块==={getStockIDPlate('002766')}")
# print((f"获取个股代码的精选板块==={getCodeJingXuanBlocks('002878')}"))
# print(f"获取该概念下的个股代码及其他====={getCodesByPlate(885500)}")   《《《《《《《《《《
# print(f"获取概念中的板块中的子板块====={json.loads(getSonPlate(801085))}")
# 获取涨停信息数据
def get_limit_up_info():
    # 获取涨停信息列表
    limit_up_info = json.loads(getLimitUpInfoNew())['list']
    return limit_up_info

# print(f"获取概念中的板块强度====={getSonPlate(getCodesByPlate(getCodeJingXuanBlocks('002452')[2][0]))}")
# print(f"市场行情-行业板块 数==={len(getMarketIndustryRealRankingInfo(True))}")
# print(f"市场行情-行业板块==={json.loads(getMarketIndustryRealRankingInfo(True))}")

# 返回格式：['板块ID','板块名称','强度','涨幅','未知','成交额','''''''''强度','未知']
# print(f"市场行情-精选板块 数==={getMarketJingXuanRealRankingInfo(True)}")
# print(f"市场行情-精选板块==={json.loads(getMarketJingXuanRealRankingInfo(True))}")
# print(f"股票代码：{Market_situation_selected_sectors_No1[0]}")
# jingxuanbankuai = json.loads(getMarketJingXuanRealRankingInfo(True))
# print(f"jingxuanbankuai==={type(jingxuanbankuai)}")
# print(f"板块代码：{jingxuanbankuai['list'][0][0]}，板块名称：{jingxuanbankuai['list'][0][1]}，强度：{jingxuanbankuai['list'][0][2]}，涨幅：{jingxuanbankuai['list'][0][3]}，未知：{jingxuanbankuai['list'][0][4]}，成交额：{round(jingxuanbankuai['list'][0][5]/100000000)}亿，主力净额：{round(jingxuanbankuai['list'][0][6]/100000000,2)}亿，主买：{round(jingxuanbankuai['list'][0][7]/100000000,2)}亿，主卖：{round(jingxuanbankuai['list'][0][8]/100000000,2)}亿，未知：{jingxuanbankuai['list'][0][9]}，流通值：{round(jingxuanbankuai['list'][0][10]/100000000,2)}亿，未知/或为最大涨跌幅：{round(jingxuanbankuai['list'][0][11],2)}，未知：{round(jingxuanbankuai['list'][0][12]/100000000,2)}亿，总市值：{round(jingxuanbankuai['list'][0][13]/100000000,2)}亿，第一季度机构持仓：{round(jingxuanbankuai['list'][0][14]/100000000,2)}亿，未知：{round(jingxuanbankuai['list'][0][15],2)}，未知：{round(jingxuanbankuai['list'][0][16],2)}，强度：{round(jingxuanbankuai['list'][0][17],2)}")
# # 部分板块没有子板块
# print(f"获取概念中的板块中的子板块====={json.loads(getSonPlate(801248))}")
# 获取市场情绪综合强度【完整】
def changeStatistics():
    """
    获取市场强度
    :return:
    """
    result = __base_request("https://apphwhq.longhuvip.com/w1/api/index.php",
                            f"a=ChangeStatistics&apiv=w35&c=HomeDingPan&PhoneOSNew=1&UserID=0&DeviceID=d6f20ce9-fa08-31c9-a493-536ebb8e9774&VerSion=5.13.0.0&Token=0&")
    # data = result.text
    data = json.loads(result)
    return data["info"][0]

# print(f"自由流通市值==={getZYLTAmount('603319')}")
# print((f"获取个股代码的精选板块列表==={getCodeJingXuanBlocks('002452')}"))
# print((f"获取个股代码的精选第一板块代码==={getCodeJingXuanBlocks('002452')[0][0]}"))
# print(f"获取该概念下的个股代码及其他====={json.loads(getCodesByPlate(getCodeJingXuanBlocks('002452')[0][0]))}")
# print(f"获取该概念下的个股代码及其他dddddd====={json.loads(its_strongest_sector_situation)}")
# print(f"涨停列表及概念板块={json.loads(getLimitUpInfoNew())['list']}")

########################################################################################################################################################################################################################
# 获取市场情绪综合强度
def get_market_strong():
    """
    获取市场强度
    :return:
    """
    result = __base_request("https://apphwhq.longhuvip.com/w1/api/index.php",
                            f"a=DiskReview&apiv=w35&c=HomeDingPan&VerSion=5.13.0.0&PhoneOSNew=1&DeviceID=d6f20ce9-fa08-31c9-a493-536ebb8e9773&")
    data = json.loads(result)
    return int(data["info"]["strong"])


# 市场情绪--涨跌统计
# 数据格式：
# SJZT:实际涨停  SJDT:实际跌停 SZJS:涨数量 ZT:涨停 DT:跌停  XDJS:跌数量  sign:人气概述
def getMarketFelling():
    result = __base_request("https://apphwhq.longhuvip.com/w1/api/index.php",
                            f"a=ZhangFuDetail&apiv=w35&c=HomeDingPan&PhoneOSNew=1&DeviceID=d6f20ce9-fa08-31c9-a493-536ebb8e9774&VerSion=5.13.0.0&")
    data = json.loads(result)
    return data["info"]
# market_strong = get_market_strong()
# print(f"market_strong==={market_strong}")


if __name__ == "__main__":
    MarketFelling = getMarketFelling()
    print(f"MarketFelling==={MarketFelling}")
    changeStatistics = changeStatistics()
    print(f"changeStatistics==={changeStatistics}")

# --------------------------------------------------------------------------------------------------------------------------------------------------------------


# 获取行情精选板块 强度排名
def get_market_sift_plate_its_stock_power():
@@ -332,29 +353,6 @@
            logger.error(f"开盘啦板块强度线程报错An error occurred: {e}")
        finally:
            time.sleep(2)


# 获取涨停信息数据
def get_limit_up_info():
    # 获取涨停信息列表
    limit_up_info = json.loads(getLimitUpInfoNew())['list']
    return limit_up_info


# 获取市场行情情绪综合强度
def get_market_strong():
    """
    获取市场强度
    :return:
    """
    result = __base_request("https://apphwhq.longhuvip.com/w1/api/index.php",
                            f"a=DiskReview&apiv=w35&c=HomeDingPan&VerSion=5.13.0.0&PhoneOSNew=1&DeviceID=d6f20ce9-fa08-31c9-a493-536ebb8e9773&")
    data = json.loads(result)
    return int(data["info"]["strong"])


# market_strong = get_market_strong()
# print(f"market_strong==={market_strong}")


# 获取涨停板块名称列表并存储本地的函数
@@ -742,79 +740,9 @@
    print(f"写入精选板块文件完成！::{now_time}")


# 获取实时大盘行情情绪综合强度 [分数] 函数 并 计算当日计划持仓数量
def get_real_time_market_strong():
    while True:
        try:
            if data_cache.position_automatic_management_switch is True:
                now_time = tool.get_now_time_str()
                if data_cache.L1_DATA_START_TIME < now_time < data_cache.CLOSING_TIME:
                    # 获取大盘综合强度分数
                    data_cache.real_time_market_strong = get_market_strong()
                    # data_cache.time_sharing_market_strong_dirt = time_sharing_market_strong_dirt.update({now: data_cache.real_time_market_strong})
                    # 该logger.info的的日志不再需要打印，后续将转入到GUI客户端上直接显示，该数据的打印交由下方的打印机制异步执行单独存储，以便后续可视化呈现后进行更高效的数据分析
                    # logger.info(f"大盘行情情绪综合强度 [分数]==={data_cache.real_time_market_strong}分")
                    if data_cache.MORN_MARKET_CLOSING_TIME < now_time < data_cache.NOON_MARKET_OPENING_TIME:
                        pass
                        logger.info(f"午间休市时间内 不打印大盘综合强度分数")
                    else:
                        # 大盘综合强度分数 的 异步日志
                        # logger_Overall_market_strength_score.info(data_cache.real_time_market_strong)
                        async_log_util.info(logger_Overall_market_strength_score,
                                            f"{data_cache.real_time_market_strong}")
                    usefulMoney = data_cache.account_finance_dict[0].get('usefulMoney', 0)
                    logger.info(f"账户可用资金==={usefulMoney}元")
                    # 低迷情绪比例
                    low_emotion_mood_ratio = 1
                    # 33分是个两级分化阶梯不好，目前不好拿捏，暂时不用
                    # if data_cache.real_time_market_strong <= 33:
                    if data_cache.real_time_market_strong < 30:
                        # 如果大盘综合强度分数小于30，将低迷情绪分数比例设置为0.01，可用资金缩小一百倍
                        low_emotion_mood_ratio = 0.01
                        if data_cache.real_time_market_strong <= 10:
                            low_emotion_mood_ratio = 0
                    logger.info(f"极端低迷情绪比例===={low_emotion_mood_ratio * 100}%")

                    data_cache.index_trend_expectation_score = index_trend_expectation()
                    logger.info(f"大盘指数情绪预期分数==={data_cache.index_trend_expectation_score}分")
                    # # 目前大盘指数情绪预期分数 尚不科学 强制设置为初始0值
                    # index_trend_expectation_score = 0

                    # 获取计算今天新增的持仓数量
                    addition_position_number = len(data_cache.addition_position_symbols_set)
                    # 定义一个今日的剩余新增持仓数量的变量
                    Unfinished_opening_plan_number = 3 - addition_position_number
                    logger.info(f"今日的剩余新增持仓数量==={Unfinished_opening_plan_number}")
                    if Unfinished_opening_plan_number != 0:
                        # 如果GUI看盘上没有手动设置具体的下单金额，就按照评分策略的金额下单，否则就按照GUI设置的金额下单。
                        if data_cache.BUY_MONEY_PER_CODE < 0:
                            # 根据账户可用金额 计算今日计划下单金额
                            # 账户可用金额 默认乘以0.9，永远留一点钱，一方面也冗余一些计算误差
                            #  ((大盘综合强度分数 + 大盘指数情绪预期分数) * 0.01) * (账户可用金额 * 0.9 * 极端低迷情绪比例 / 今日最大新增持仓票数)
                            # data_cache.today_planned_order_amount = ((data_cache.real_time_market_strong + data_cache.index_trend_expectation_score) * 0.01) * (
                            #                                                 usefulMoney * 0.9 * low_emotion_mood_ratio / Unfinished_opening_plan_number)
                            data_cache.today_planned_order_amount = (usefulMoney * 0.95 * low_emotion_mood_ratio / Unfinished_opening_plan_number)
                            logger.info(f"采用开仓策略计算方式=》今日计划下单金额:{data_cache.today_planned_order_amount}，")
                        else:
                            data_cache.today_planned_order_amount = data_cache.BUY_MONEY_PER_CODE
                            logger.info(f"采用GUI设置方式=》今日计划下单金额:{data_cache.today_planned_order_amount}")

        except Exception as error:
            logger.error(f"获取实时大盘行情情绪综合强度[分数] 函数报错: {error}")
        finally:
            time.sleep(3)


# kpl_stocks_list_selected_blocks_process()   #在 kpl_api.py中可以调用
# stocks_list_selected_blocks(min_stocks)   #在 kpl_api.py中可以调用
# list = ['SHSE.600805','SHSE.600804']
#
# all_stocks_plate_dict(list)


if __name__ == "__main__":
    # start_time = time.time()
    # get_market_sift_plate_its_stock_power()
    # print("耗时：", time.time() - start_time)
    get_market_sift_plate_its_stock_power()
    # get_market_sift_plate_its_stock_power_process(None)

 strategy/market_sentiment_analysis.py

@@ -5,18 +5,17 @@
# import decimal
import datetime
import json
import time

import constant
from log_module.log import logger_common
from log_module import async_log_util
from log_module.log import logger_common, logger_Overall_market_strength_score
# import time
# 引入掘金API
# from gm.api import *
from strategy import basic_methods
from strategy import basic_methods, kpl_api
from strategy import data_cache

# import account_management
from strategy import order_methods
from strategy.all_K_line import k_line_history
from utils import tool, juejin_api

# 获取logger实例
@@ -562,9 +561,95 @@
    logger.info(f"加属性的指数k线写完了！{tool.get_now_time_str()}")


# 获取实时大盘行情情绪综合强度 [分数] 函数 并 计算当日计划持仓数量
def get_real_time_market_strong():
    while True:
        try:
            if data_cache.position_automatic_management_switch is True:
                now_time = tool.get_now_time_str()
                if data_cache.L1_DATA_START_TIME < now_time < data_cache.CLOSING_TIME:
                    # 获取大盘综合强度分数
                    data_cache.real_time_market_strong = kpl_api.get_market_strong()
                    # 获取市场情绪字典【完整】，并整理
                    data_cache.real_time_market_sentiment_dirt = kpl_api.changeStatistics()
                    date_today = data_cache.real_time_market_sentiment_dirt.get(['Day'], None)
                    significant_drawdown = data_cache.real_time_market_sentiment_dirt.get(['df_num'], None)
                    sentiment_indicators = data_cache.real_time_market_sentiment_dirt.get(['ztjs'], None)
                    limit_up_amount = data_cache.real_time_market_sentiment_dirt.get(['ztjs'], None)
                    connecting_board_height = data_cache.real_time_market_sentiment_dirt.get(['lbgd'], None)
                    # 获取市场情绪-涨跌统计
                    data_cache.rise_and_fall_statistics_dirt = kpl_api.getMarketFelling()
                    limit_up_numbers = data_cache.rise_and_fall_statistics_dirt.get(['ZT', None])
                    actual_limit_up_numbers = data_cache.rise_and_fall_statistics_dirt.get(['SJZT', None])
                    ST_limit_up_numbers = data_cache.rise_and_fall_statistics_dirt.get(['STZT', None])
                    limit_down_numbers = data_cache.rise_and_fall_statistics_dirt.get(['DT', None])
                    actual_limit_down_numbers = data_cache.rise_and_fall_statistics_dirt.get(['SJDT', None])
                    ST_limit_down_numbers = data_cache.rise_and_fall_statistics_dirt.get(['STDT', None])

                    rise_numbers = data_cache.rise_and_fall_statistics_dirt.get(['SZJS', None])
                    fall_numbers = data_cache.rise_and_fall_statistics_dirt.get(['XDJS', None])

                    # 该logger.info的的日志不再需要打印，后续将转入到GUI客户端上直接显示，该数据的打印交由下方的打印机制异步执行单独存储，以便后续可视化呈现后进行更高效的数据分析
                    # logger.info(f"大盘行情情绪综合强度 [分数]==={data_cache.real_time_market_strong}分")
                    if data_cache.MORN_MARKET_CLOSING_TIME < now_time < data_cache.NOON_MARKET_OPENING_TIME:
                        pass
                        logger.info(f"午间休市时间内 不打印大盘综合强度分数")
                    else:
                        # 大盘综合强度分数 的 异步日志
                        # logger_Overall_market_strength_score.info(data_cache.real_time_market_strong)
                        async_log_util.info(logger_Overall_market_strength_score, f"{data_cache.real_time_market_strong}")
                        logger.info(f"日期：{date_today}，情绪指标：{sentiment_indicators}分，大幅回撤：{significant_drawdown}，涨停家数：{limit_up_amount}，连板高度：{connecting_board_height}")
                        logger.info(f"上涨家数：{rise_numbers}分，下跌家数：{fall_numbers}，实际涨停家数：{actual_limit_up_numbers}，实际跌停家数：{actual_limit_down_numbers}")
                        logger.info(f"涨跌统计字典{data_cache.rise_and_fall_statistics_dirt}")

                    usefulMoney = data_cache.account_finance_dict[0].get('usefulMoney', 0)
                    logger.info(f"账户可用资金==={usefulMoney}元")
                    # 低迷情绪比例
                    low_emotion_mood_ratio = 1
                    # 33分是个两级分化阶梯不好，目前不好拿捏，暂时不用
                    # if data_cache.real_time_market_strong <= 33:
                    if data_cache.real_time_market_strong < 30:
                        # 如果大盘综合强度分数小于30，将低迷情绪分数比例设置为0.01，可用资金缩小一百倍
                        low_emotion_mood_ratio = 0.01
                        if data_cache.real_time_market_strong <= 10:
                            low_emotion_mood_ratio = 0
                    logger.info(f"极端低迷情绪比例===={low_emotion_mood_ratio * 100}%")

                    data_cache.index_trend_expectation_score = index_trend_expectation()
                    logger.info(f"大盘指数情绪预期分数==={data_cache.index_trend_expectation_score}分")
                    # # 目前大盘指数情绪预期分数 尚不科学 强制设置为初始0值
                    # index_trend_expectation_score = 0

                    # 获取计算今天新增的持仓数量
                    addition_position_number = len(data_cache.addition_position_symbols_set)
                    # 定义一个今日的剩余新增持仓数量的变量
                    Unfinished_opening_plan_number = 3 - addition_position_number
                    logger.info(f"今日的剩余新增持仓数量==={Unfinished_opening_plan_number}")
                    if Unfinished_opening_plan_number != 0:
                        # 如果GUI看盘上没有手动设置具体的下单金额，就按照评分策略的金额下单，否则就按照GUI设置的金额下单。
                        if data_cache.BUY_MONEY_PER_CODE < 0:
                            # 根据账户可用金额 计算今日计划下单金额
                            # 账户可用金额 默认乘以0.9，永远留一点钱，一方面也冗余一些计算误差
                            #  ((大盘综合强度分数 + 大盘指数情绪预期分数) * 0.01) * (账户可用金额 * 0.9 * 极端低迷情绪比例 / 今日最大新增持仓票数)
                            # data_cache.today_planned_order_amount = ((data_cache.real_time_market_strong + data_cache.index_trend_expectation_score) * 0.01) * (
                            #                                                 usefulMoney * 0.9 * low_emotion_mood_ratio / Unfinished_opening_plan_number)
                            data_cache.today_planned_order_amount = (usefulMoney * 0.95 * low_emotion_mood_ratio / Unfinished_opening_plan_number)
                            logger.info(f"采用开仓策略计算方式=》今日计划下单金额:{data_cache.today_planned_order_amount}，")
                        else:
                            data_cache.today_planned_order_amount = data_cache.BUY_MONEY_PER_CODE
                            logger.info(f"采用GUI设置方式=》今日计划下单金额:{data_cache.today_planned_order_amount}")

        except Exception as error:
            logger.error(f"获取实时大盘行情情绪综合强度[分数] 函数报错: {error}")
        finally:
            time.sleep(3)


if __name__ == '__main__':
    market_strong = kpl_api.get_market_strong()
    print(f"{market_strong}")
    # all_index_K_line_dict = get_index_K_line()

    # all_index_k_line_dict_write()
    # print(f"指数K线{data_cache.all_index_k_line_property_dict}")
    all_index_k_line_dict_write()
    # all_index_k_line_dict_write()