日志修改

admin

2025-03-26 ac7125f8ce3457378edc261a9800828db5185cd5

日志修改

 data_server.py

@@ -11,6 +11,7 @@

from db import redis_manager_delegate as redis_manager, mysql_data_delegate as mysql_data
from db.redis_manager_delegate import RedisUtils
from log_module import log_export
from log_module.log import hx_logger_l2_transaction, logger_debug, logger_request_api
from strategy import data_cache
from strategy.trade_setting import TradeSetting
@@ -173,6 +174,33 @@
                response_data = json.dumps(result)
            except Exception as e:
                response_data = json.dumps({"code": 1, "msg": str(e)})
        elif url.path == "/get_kpl_stock_of_markets_plate":
            # 获取开盘啦流入板块详细信息
            time_str = params_dict.get("time")
            if not time_str:
                time_str = tool.get_now_time_str()
            datas = log_export.load_stock_of_markets_plate()
            fdatas = []
            for data in datas:
                # (发生时间,[净流入板块], {"板块":(代码, 名称, 涨幅)})
                fdatas.append((data[0], [x[1] for x in data[1][0]],
                               {p: [(xx[0], xx[1], xx[6]) for xx in data[1][1][p]] for p in data[1][1]}))
            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
        elif url.path == "/get_kpl_market_strong_records":
            # 获取开盘啦市场强度记录
            time_str = params_dict.get("time")
            if not time_str:
                time_str = tool.get_now_time_str()
            datas = log_export.load_kpl_market_strong()
            fdatas = []
            for data in datas:
                # (距离09:15:00的秒数, 时间, 强度)
                fdatas.append((tool.trade_time_sub(data[0], "09:15:00"), data[0], data[1]))
            response_data = json.dumps({"code": 0, "data": fdatas})

        self.send_response(200)
        # 发给请求客户端的响应数据

 log_module/log_export.py

@@ -77,5 +77,37 @@
                        pass
    return fdatas


def load_kpl_market_strong(date=tool.get_now_date_str()):
    """
     获取开盘啦历史强度
    :param date:
    :return: [("时间","分数")]
    """
    path = f"{constant.get_path_prefix()}/low_suction_log/gp/kpl/Overall_market_strength_score.{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()
                        fdatas.append((time_str, int(data)))
                    except:
                        pass
    return fdatas


if __name__ == '__main__':
    load_stock_of_markets_plate()
    datas = load_kpl_market_strong()
    fdatas = []
    for data in datas:
        # (距离09:15:00的秒数, 时间, 强度)
        if "11:30:00"<= data[0]<="13:00:00":
            continue
        fdatas.append([tool.trade_time_sub(data[0], "09:15:00"), data[0], data[1]])
    print(fdatas)

 strategy/account_management.py

@@ -2,13 +2,8 @@
账户管理模块【管理账户下面的资金管理方法及仓位管理方法等】
"""
from log_module.log import logger_common
# import time
# import datetime
# import decimal
from trade import huaxin_trade_api

# import logging
# import threading
# 引入全局变量模块
from strategy import data_cache

@@ -32,23 +27,6 @@
        logger.info(f"冻结的资金==={frozenCash}")
        logger.info(f"可取资金==={fetchLimit}")
        logger.info(f"上日结存==={preDeposit}")


# finance_management()

# 构造循环请求资金管理线程
# def finance_management_process():
#     while True:
#         try:
#             # now_start = time.time()
#             # print(f"finance_management开始{now_start}")
#             finance_management()
#             # now_end = time.time()
#             # print(f"finance_management完成一下{now_end}")
#         except Exception as error:
#             print(f"获取资金管理线程报错An error occurred: {error}")
#         finally:
#             time.sleep(1)


# 仓位管理函数
@@ -101,18 +79,3 @@
        logger.info(
            f"今日新增持仓数量====================================【{len(data_cache.addition_position_symbols_set)}】")

# position_management()

# # 构造循环请求仓位管理线程
# def position_management_process():
#     while True:
#         try:
#             # now_start = time.time()
#             # print(f"position_management开始{now_start}")
#             position_management()
#             # now_end = time.time()
#             # print(f"position_management完成一下{now_end}")
#         except Exception as error:
#             print(f"获取仓位管理线程报错An error occurred: {error}")
#         finally:
#             time.sleep(1)

 strategy/buying_strategy.py

@@ -569,8 +569,7 @@
                                                if current_volume < k_line_data[0]['volume'] * ratios:
                                                    logger.info(
                                                        f"【不利】今日成交量 < 昨日的{ratios}倍，不买！！公司名称：{k_line_data[0]['sec_name']}，今日目前成交量为昨日的{round(current_volume / k_line_data[0]['volume'], 2)}")
                                                elif buying_strong is not True and current_volume <= k_line_data[0][
                                                    'volume'] * ratios and now_time > data_cache.MORN_MARKET_TIME:
                                                elif buying_strong is not True and current_volume <= k_line_data[0]['volume'] * ratios and now_time > data_cache.MORN_MARKET_TIME:
                                                    logger.info(
                                                        f"【不利】买一量小于卖一量 且 挂买总量小于挂卖总量 且 当日量不足 (9:35后实施)！不买！！公司名称：{k_line_data[0]['sec_name']}，自由市值：{free_market_value} 亿,最新价: {current_price}")
                                                    # logger.info(

 strategy/data_cache.py

@@ -98,7 +98,7 @@
                # print(f"非ST, 退市, 退, XD, N==={basic_info['sec_name']} 继续判断")
                no_k_line_stocks.append(i['symbol'])
        # 将列表推导式移出循环 过滤出昨日收盘价在2-30元的股票
        min_instruments = [stock for stock in instruments if 2 < stock['pre_close'] < 30]
        min_instruments = [stock for stock in instruments if 3 < stock['pre_close'] < 30]
        # print(f"min_instruments  数量==={len(min_instruments)}")
        # 使用 get 方法安全地获取 symbol 字段的值
        self.min_stocks = [stock.get('symbol') for stock in min_instruments if stock.get('symbol') is not None]

 strategy/index_market_trend_strategy.py

@@ -98,7 +98,7 @@

# 大盘指数趋势预期函数（用于对大盘开盘后短期内的趋势预测）
def index_trend_expectation():
    index_trend_expectation_score = 0
    index_trend_expectation_score = 100
    # 判断三大指数开盘涨幅 预期
    if data_cache.Shanghai_open_growth > 0 and data_cache.Shenzhen_open_growth > 0 and data_cache.TSXV_open_growth > 0:
        index_composite_open_increase = '三大指数：高开'
@@ -147,6 +147,8 @@
    if len(data_cache.all_index_k_line_property_dict) > 0 or data_cache.all_index_k_line_property_dict is not None:
        logger.info(f"指数带属性K线数据的昨日是否为空:{data_cache.all_index_k_line_property_dict['SHSE.000001'][0]}")
        # print(f"指数带属性K线数据的昨日是否为空:{data_cache.all_index_k_line_property_dict['SHSE.000001'][0]['open']}")
    if index_trend_expectation_score > 100:
        index_trend_expectation_score = 100
    return index_trend_expectation_score



 strategy/instant_time_market.py

@@ -101,7 +101,7 @@
                # logger.info(f"【没有】在集合竞价内启动，采用【掘金数据】记录")
                print(f"【没有】在开盘前内启动，采用【掘金数据】记录 开盘价")
                data_cache.record_current_open_execution = True
                current_datas = utils.juejin_api.JueJinApi.get_codes_open(data_cache.DataCache().filtered_stocks, fields='symbol,open')
                current_datas = utils.juejin_api.JueJinApi.get_codes_open(data_cache.DataCache().min_stocks, fields='symbol,open')
                # print(f"current_datas=={current_datas}")
                for current_data in current_datas:
                    # print(f"current_data=={current_data}")
@@ -212,9 +212,9 @@
            # print(f"当前时间更新时间：{now_time}")
            if not __current_high_or_low_dict:
                # 还没初始化
                # current_datas = current(symbols=data_cache.DataCache().filtered_stocks, fields='symbol,high,low')
                # current_datas = current(symbols=data_cache.DataCache().min_stocks, fields='symbol,high,low')
                current_datas = utils.juejin_api.JueJinApi.get_codes_high_and_low(
                    data_cache.DataCache().filtered_stocks, fields='symbol,high,low')
                    data_cache.DataCache().min_stocks, fields='symbol,high,low')
                # print(f"current_datas=={current_datas}")
                for current_data in current_datas:
                    symbol, high, low = current_data['symbol'], current_data['high'], current_data['low']
@@ -224,7 +224,7 @@
            for current_info in current_infos:
                # print(f"开始循环current_infos")
                symbol = basic_methods.format_stock_symbol(current_info[0])
                if symbol not in data_cache.DataCache().filtered_stocks:
                if symbol not in data_cache.DataCache().min_stocks:
                    continue
                # if symbol.find("300810") > 0:
                #     print(f"开始循环current_infos："+symbol)
@@ -235,7 +235,7 @@
                    # 初始化
                    # current_datas = current(symbols=[symbol], fields='symbol,high,low')
                    current_datas = utils.juejin_api.JueJinApi.get_codes_high_and_low(
                        data_cache.DataCache().filtered_stocks, fields='symbol,high,low')
                        data_cache.DataCache().min_stocks, fields='symbol,high,low')
                    current_data = current_datas[0]
                    # print(f"开始实例化对象")
                    symbol, high, low = current_data['symbol'], current_data['high'], current_data['low']

 strategy/kpl_api.py

@@ -301,7 +301,7 @@
                log_datas[b] = r[b]
        now_time = tool.get_now_time_str()
        if data_cache.L1_DATA_START_TIME < now_time < data_cache.CLOSING_TIME:
            logger.info(f"精选板块股票强度数据更新 == {market_sift_plate_stock_dict}")
            # logger.info(f"精选板块股票强度数据更新 == {market_sift_plate_stock_dict}")
            # 只在盘中时间获取
            async_log_util.info(logger_stock_of_markets_plate, f"{(market_sift_plate['list'], log_datas)}")

@@ -769,7 +769,6 @@

                    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

@@ -781,10 +780,11 @@
                        # 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
                            #  ((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 * 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 + index_trend_expectation_score) * 0.01) * (
                                                                            usefulMoney * low_emotion_mood_ratio / Unfinished_opening_plan_number)
                            # 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 + index_trend_expectation_score) * 0.01) * (
                            #                                                 usefulMoney * 0.9 * low_emotion_mood_ratio / Unfinished_opening_plan_number)
                            data_cache.today_planned_order_amount = (index_trend_expectation_score * 0.01) * (usefulMoney * 0.9 * low_emotion_mood_ratio / Unfinished_opening_plan_number)
                        else:
                            data_cache.today_planned_order_amount = data_cache.BUY_MONEY_PER_CODE