1.修改 下单方法中计算价格笼子的参数price = price + 0.05 2.解决 下单金额计算及大盘理想行情分数计算问题

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2025-05-16 35d1015d2fa002ac965352d72858a9d0bcaf7427

1.修改 下单方法中计算价格笼子的参数price = price + 0.05
2.解决 下单金额计算及大盘理想行情分数计算问题

 strategy/buying_strategy.py

@@ -377,7 +377,7 @@
                                            logger_info(
                                                f"最新价: {current_price}, 当日最高价：{current_high},瞬时涨幅: {tick_growth:.2f}%,当日当时涨幅：{today_growth}%，公司名称：{k_line_data[0]['sec_name']},当前时间：{current_created_at},低于水位线：{deep_low:.2f},交易量今日与昨日的比例{round(current_volume / k_line_data[0]['volume'], 2)}")
                                            logger_info(
                                                f"大盘综合强度分数：{data_cache.real_time_market_strong}，大盘指数情绪预期分数==={data_cache.index_trend_expectation_score}分，设想的下单金额：{get_order_money()}")
                                                f"大盘综合强度分数：{data_cache.real_time_market_strong}，理想交易行情分数==={data_cache.ideal_trading_market_score}分，设想的下单金额：{get_order_money()}")
                                            # 调用下单方法下单
                                            order_methods.buy_order_by_value(symbol,
                                                                             get_order_money(),
@@ -466,14 +466,6 @@
                                                    f"************************************************【有概念无强度指标下单】************************************************")
                                                logger_info(
                                                    f"最新价: {current_price}, 当日最高价：{current_high},瞬时涨幅: {tick_growth:.2f}%,当日当时涨幅：{today_growth}%，公司名称：{k_line_data[0]['sec_name']},当前时间：{current_created_at},低于水位线：{deep_low:.2f},交易量今日与昨日的比例{round(current_volume / k_line_data[0]['volume'], 2)}")
                                                # 调用下单方法下单
                                                # order_methods.buy_order_by_value(symbol, 1000,
                                                #                                  k_line_data[0]['sec_name'],
                                                #                                  current_price)
                                                # # 将有概念买入次数自加1
                                                # data_cache.have_plate_buy_times += 1
                                                # # 将买入个股的当时概念添加到全局变量中存储
                                                # data_cache.bought_plate.extend(limit_up_plate_included_list)
                                                # 检测持仓代码集合中有无下单个股，才认为交易成功
                                                if symbol_code not in data_cache.position_symbols_set:
                                                    logger_info(
@@ -564,16 +556,12 @@
                                                    logger_info(
                                                        f"最新价: {current_price}, 当日最高价：{current_high},瞬时涨幅: {tick_growth:.2f}%,当日当时涨幅：{today_growth}%，公司名称：{k_line_data[0]['sec_name']},当前时间：{current_created_at},低于水位线：{deep_low:.2f},交易量今日与昨日的比例{round(current_volume / k_line_data[0]['volume'], 2)}")  # 输出当前价格和3秒涨幅信息
                                                    logger_info(
                                                        f"大盘综合强度分数：{data_cache.real_time_market_strong}，大盘指数情绪预期分数==={data_cache.index_trend_expectation_score}分，设想的下单金额：{get_order_money()}")
                                                        f"大盘综合强度分数：{data_cache.real_time_market_strong}，理想交易行情分数==={data_cache.ideal_trading_market_score}分，设想的下单金额：{get_order_money()}")
                                                    # 调用下单方法下单
                                                    order_methods.buy_order_by_value(symbol,
                                                                                     get_order_money(),
                                                                                     k_line_data[0]['sec_name'],
                                                                                     current_price)
                                                    # # 将有强度买入次数自加1
                                                    # data_cache.have_strength_buy_times += 1
                                                    # # 将买入个股的当时概念添加到全局变量中存储
                                                    # data_cache.bought_plate.extend(strength_plate)
                                                    # 检测持仓代码集合中有无下单个股，才认为交易成功
                                                    if symbol_code not in data_cache.position_symbols_set:
                                                        logger_info(
@@ -673,15 +661,6 @@
                                                        f"最新价: {current_price}, 当日最高价：{current_high},瞬时涨幅: {tick_growth:.2f}%,当日当时涨幅：{today_growth}%，公司名称：{k_line_data[0]['sec_name']},当前时间：{current_created_at},低于水位线：{deep_low:.2f},交易量今日与昨日的比例{round(current_volume / k_line_data[0]['volume'], 2)}")  # 输出当前价格和3秒涨幅信息
                                                    logger_info(
                                                        f"目前获取的精选板块股票强度数据  ==  {data_cache.market_sift_plate_stock_dict}")
                                                    # buying_ratio = basic_methods.maximum_buying_ratio(len(data_cache.addition_position_symbols_set))
                                                    # 调用下单方法下单
                                                    # order_methods.buy_order_by_value(symbol, 1000,
                                                    #                                  k_line_data[0]['sec_name'],
                                                    #                                  current_price)
                                                    # # 将有小量换大涨幅买入次数自加1
                                                    # data_cache.have_small_turn_large_buy_times += 1
                                                    # # 将买入个股的当时概念添加到全局变量中存储
                                                    # data_cache.bought_plate.append(k_line_data[0]['sec_name'])
                                                    # 检测持仓代码集合中有无下单个股，才认为交易成功
                                                    if symbol_code not in data_cache.position_symbols_set:
                                                        logger_info(
@@ -699,8 +678,7 @@
                                '''
                                if k_line_data[0]['attribute'] in data_cache.limit_up_type:
                                    # logger_info(f"昨日涨停")
                                    if k_line_data[1]['attribute'] not in data_cache.limit_up_type and k_line_data[2][
                                        'attribute'] not in data_cache.limit_up_type:
                                    if k_line_data[1]['attribute'] not in data_cache.limit_up_type and k_line_data[2]['attribute'] not in data_cache.limit_up_type:
                                        # logger_info(f"前日大前日未涨停")
                                        if today_open_growth > 1:
                                            logger_info(

 strategy/data_cache.py

@@ -259,6 +259,8 @@
TSXV_open_growth = 0
# 大盘指数情绪预期分数
index_trend_expectation_score = 0
# 理想交易行情比率分 满分=1
ideal_trading_market_score = 1

# 可以板上盯卖的代码
LIMIT_UP_SELL_CODES = set()

 strategy/market_sentiment_analysis.py

@@ -734,60 +734,65 @@
                        for i, signal in enumerate(signals, 1):
                            logger.info(f"信号{i}: {signal}")

                    # 理想交易行情分数【评估当前行情是否有利于低吸策略取得更高抓板率的分数（是否是理想的交易行情）】
                    ideal_trading_market_score = 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:   实际跌停大于10个
                    if data_cache.real_time_market_strong < 30 and int(actual_limit_down_numbers) > 10:
                        # 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
                        ideal_trading_market_score = 0.01

                    logger.info(f"理想交易行情分数===={ideal_trading_market_score * 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")
                    # print(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 【目前策略默认一日三仓 所以设置常量3】
                    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}")
                    usefulMoney = data_cache.account_finance_dict[0].get('usefulMoney', 0)
                    logger.info(f"账户可用资金==={usefulMoney}元")
                    # 开仓策略计算结果
                    # 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0.95，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(常量：3))
                    # 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)
                    # 除以3应该是一个常量，如果以Unfinished_opening_plan_number，会出现float division by zero

                    # 如果不为空 或 计划金额为默认值，那么就计算第一次计划金额，并固定记录下来
                    if not data_cache.today_planned_order_amount or data_cache.today_planned_order_amount <= 0:
                        data_cache.today_planned_order_amount = usefulMoney * 0.95 * ideal_trading_market_score / 3
                        logger.info(f"第一次计划下单金额==={data_cache.today_planned_order_amount}元")
                    # 开仓计划运行时间段
                    # 只有在开盘时具体计算 计划下单金额
                    if data_cache.OPENING_TIME < now_time < data_cache.NOON_MARKET_TIME:
                        # # 如果一日三仓的计划还未完成 且 首次开仓金额为0
                        if Unfinished_opening_plan_number != 0 and data_cache.today_first_planned_order_amount <= 0:
                            # 如果GUI看盘手动设置了具体的下单金额【data_cache.BUY_MONEY_PER_CODE 中默认值为-1，只有当GUI看盘手动设置了并提交才会>=0】，就按照GUI设置的金额下单。否则就按照评分策略的金额下单，
                            # if data_cache.BUY_MONEY_PER_CODE >= 0:
                            #     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}")
                            # else:
                            #     # 如果今日还没有一个新增仓位，就不停计算更新计划金额
                            #     if addition_position_number > 0:
                            #         data_cache.today_planned_order_amount = data_cache.opening_strategy_results
                            #         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}")
                            if addition_position_number > 0:
                                # 下过一次单过后再计算动态下单金额
                                data_cache.today_first_planned_order_amount = float(
                                    data_cache.today_planned_order_amount)
                                logger.info(
                                    f"采用开仓策略计算方式--》今日(首个)新增持仓产生，将实时计算金额赋值给首笔持仓金额=》今日计划下单金额:{data_cache.today_planned_order_amount}")
                        # 理想交易行情分数【评估当前行情是否有利于低吸策略取得更高抓板率的分数（是否是理想的交易行情）】
                        ideal_trading_market_score = 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:   实际跌停大于10个
                        if data_cache.real_time_market_strong < 30 and int(actual_limit_down_numbers) > 10:
                            # 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
                            ideal_trading_market_score = 0.01

                        logger.info(f"理想交易行情分数===={ideal_trading_market_score * 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")
                        # print(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 【目前策略默认一日三仓 所以设置常量3】
                        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}")
                        usefulMoney = data_cache.account_finance_dict[0].get('usefulMoney', 0)
                        logger.info(f"账户可用资金==={usefulMoney}元")
                        # 开仓策略计算结果
                        # 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0.95，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(常量：3))
                        # 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)
                        # 除以3应该是一个常量，如果以Unfinished_opening_plan_number，会出现float division by zero

                        # 如果今日计划下单数量不为空 或 计划金额为默认值，那么就实时计算第一次计划金额，并固定记录下来
                        if not data_cache.today_planned_order_amount or data_cache.today_first_planned_order_amount <= 0:
                            data_cache.today_planned_order_amount = usefulMoney * 0.95 * ideal_trading_market_score / 3
                            logger.info(f"第一次实时计算计划下单金额==={data_cache.today_planned_order_amount}元")

                        # 老的计算方案先后顺序方法
                        # 开仓计划运行时间段
                        # if data_cache.OPENING_TIME < now_time < data_cache.NOON_MARKET_TIME:
                        #     # # 如果一日三仓的计划还未完成 且 首次开仓金额为0
                        #     if Unfinished_opening_plan_number != 0 and data_cache.today_first_planned_order_amount <= 0:
                        #         # 如果GUI看盘手动设置了具体的下单金额【data_cache.BUY_MONEY_PER_CODE 中默认值为-1，只有当GUI看盘手动设置了并提交才会>=0】，就按照GUI设置的金额下单。否则就按照评分策略的金额下单，
                        #         # if data_cache.BUY_MONEY_PER_CODE >= 0:
                        #         #     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}")
                        #         # else:
                        #         #     # 如果今日还没有一个新增仓位，就不停计算更新计划金额
                        #         #     if addition_position_number > 0:
                        #         #         data_cache.today_planned_order_amount = data_cache.opening_strategy_results
                        #         #         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}")
                        #         if addition_position_number > 0:
                        #             # 下过一次单过后再计算动态下单金额
                        #             data_cache.today_first_planned_order_amount = float(
                        #                 data_cache.today_planned_order_amount)
                        #             logger.info(
                        #                 f"采用开仓策略计算方式--》今日(首个)新增持仓产生，将实时计算金额赋值给首笔持仓金额=》今日计划下单金额:{data_cache.today_planned_order_amount}")

        except Exception as error:
            logger_debug.exception(error)

 utils/tool.py

@@ -304,7 +304,7 @@
        price1 = math.ceil(price1 * 1000) / 1000
    else:
        price1 = math.ceil(price1 * 100) / 100
    price2 = price + 0.1
    price2 = price + 0.05
    return max(price1, price2)