# coding=utf-8
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from __future__ import print_function, absolute_import, unicode_literals
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import logging
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import threading
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import time
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import constant
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# 引入掘金桥梁API
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import utils.juejin_api
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from db.redis_manager_delegate import RedisUtils
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from huaxin_client.l2_data_transform_protocol import L2DataCallBack
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from log_module.log import logger_common, logger_kpl_jingxuan_in, logger_system, logger_debug
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# 引入开盘啦API模块
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# 引入全局变量模块
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# 引入定时器模块
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# 引入历史K线方法模块
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# 引入瞬时分时行情模块
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# 引入账户管理模块【进行资金和仓位管理】
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from strategy import kpl_api, data_cache, check_timer, all_K_line, instant_time_market, account_management, \
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order_methods, local_data_management, kpl_data_manager, market_sentiment_analysis, plate_strength_analysis
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from huaxin_client import l2_market_client, l2_client
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from log_module import async_log_util
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from trade import huaxin_trade_data_update, huaxin_trade_api
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from utils import hx_qc_value_util, huaxin_util, juejin_api, tool
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# 引入行情订阅模块
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# import subscribe_market
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# 全局日志配置 如果不想用就把 logging.ERROR 如果要打就=logging.INFO
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logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
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# 计算当前线程数量
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def get_current_thread_count():
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# print(f"threading.active_count()=={threading.active_count()}")
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return threading.active_count()
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# 初始化数据 函数
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def init_data():
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# logging.info("main初始化数据开始")
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logger_common.info(f"main初始化数据开始")
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'''
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资金管理初始化
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仓位管理初始化
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都在main的初始化数据函数里面完成
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无需掘金考虑的线程或进程方式实现
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'''
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# 初始化账户仓位管理数据
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account_management.finance_management()
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# 初始化账户仓位管理数据
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account_management.position_management()
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# 初始化.实例化缓存中的全局数据
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data_cache.DataCache()
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# 读取本地K线数据 并更新到data_cache
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# 初始化A股所有目标票标的信息
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data_cache.all_stocks = utils.juejin_api.JueJinApi.get_target_codes()
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# 获取目标标的K线---初始化
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all_K_line.k_line_history.init(data_cache.DataCache().today_date, data_cache.DataCache().next_trading_day,
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data_cache.DataCache().filtered_stocks)
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# 直接调用目标标的指标K线写入本地文件
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# all_K_line.all_stocks_all_k_line_dict_write()
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local_data_management.read_local_K_line_data()
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# 读取本地个股所属板块数据 并更新到data_cache
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local_data_management.read_local_all_stocks_plate_data()
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# todo 2025-03-25 测试无误即可删除下部注释
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# # 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
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# if os.path.exists(constant.K_BARS_PATH):
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# with open(constant.K_BARS_PATH, 'r', encoding='utf-8') as f:
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# data_cache.all_stocks_all_K_line_property_dict = json.load(f)
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# print(
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# f"data_cache.all_stocks_all_K_line_property_dict的个数==={len(data_cache.all_stocks_all_K_line_property_dict)}")
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# # 获取目标标的K线---初始化
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# 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)
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# # 直接调用主要指数K线写入本地文件
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# all_K_line.main_index_k_line_dict_write()
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# 第一步：初始化context函数，并开启获取实时数据的线程
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def init():
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# 在初始化函数里面就调用全局化变量函数（即上文缩写的init_data函数）
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init_data()
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# 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】
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threading.Thread(target=lambda: check_timer.check_time(), daemon=True).start()
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# 获取实时大盘行情情绪综合强度 [分数] 线程
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threading.Thread(target=lambda: market_sentiment_analysis.set_plan_position_quantity(), daemon=True).start()
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# 实时检测是否拉取K线线程
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threading.Thread(target=lambda: all_K_line.check_time_and_data_date(), daemon=True).start()
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# print(f"all_stocks_all_K_line_property_dict== {type(data_cache.all_stocks_all_K_line_property_dict)}")
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# 获取实时大盘指数行情线程
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threading.Thread(target=lambda: instant_time_market.index_market_current(), daemon=True).start()
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# instant_time_market.index_market_trend()
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# 开盘啦的涨停概念的回调函数
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def kpl_limit_up_process(datas):
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# print(f"回调成功==={datas}")
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if datas is not None and len(datas) > 0:
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data_cache.limit_up_block_names = datas
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else:
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data_cache.limit_up_block_names = []
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# # 计算当前线程数量
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# get_current_thread_count()
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# 开启开盘啦 涨停列表 和 全盘个股概念板块 接口线程
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# 涨停概念线程
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# 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
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threading.Thread(target=plate_strength_analysis.kpl_limit_up_process, args=(kpl_limit_up_process,), daemon=True).start()
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# # 开盘啦的板块强度下的个股强度回调函数
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def get_market_sift_plate_its_stock_power_process(market_sift_plate_stock_dict):
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# print(f"回调成功===精选板块股票强度数据更新==={market_sift_plate_stock_dict}")
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# logger_kpl_jingxuan_in.info(f"{market_sift_plate_stock_dict}")
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data_cache.market_sift_plate_stock_dict = market_sift_plate_stock_dict
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# 板块强度下个股强度线程
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threading.Thread(target=plate_strength_analysis.get_market_sift_plate_its_stock_power_process,
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args=(get_market_sift_plate_its_stock_power_process,), daemon=True).start()
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# 初始化get_current_data方法函数，下单买逻辑才会运行中。。。【核心主线程，随时考虑其启动顺序】>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
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# threading.Thread(target=lambda: instant_time_market.get_current_data(), daemon=True).start()
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try:
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# 计算开盘啦昨日拉取的概念数据中为空的股票数量
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plate_strength_analysis.get_have_no_plate_num()
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except Exception as e:
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logger_system.exception(e)
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# 获取历史涨停信息数据并整理
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try:
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plate_strength_analysis.get_handling_limit_up_info()
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except Exception as e:
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logger_system.exception(e)
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try:
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# 检查K线昨日涨停是否正确
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all_K_line.check_limit_up_attribute()
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except Exception as e:
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logger_system.exception(e)
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# 持仓代码的L2数据回调
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class MyPositionsL2DataCallback(L2DataCallBack):
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__last_price_dict = {}
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__pre_close_price_dict = {} # 昨日收盘价
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def OnL2Transaction(self, code, datas):
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"""
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昨日持仓L2逐笔成交回调
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:param code:
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:param datas:
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:return:
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"""
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if datas:
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price, time_str = datas[-1][1], huaxin_util.convert_time(datas[-1][3])
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try:
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# 获取最近的成交价
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if code not in self.__pre_close_price_dict:
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# 获取收盘价格
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results = juejin_api.JueJinApi.history_n(tool.get_symbol(code), "1d", 1, 1, "close")
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if results:
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self.__pre_close_price_dict[code] = results[0]["close"]
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if self.__last_price_dict.get(code) == price:
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return
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limit_up_price = tool.get_limit_up_price(code, self.__pre_close_price_dict[code])
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if code in self.__last_price_dict:
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if abs(limit_up_price - self.__last_price_dict[code]) < 0.0001 < abs(limit_up_price - price):
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# TODO 处理炸板逻辑
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# 炸板
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logger_debug.info(f"炸板:{code}-({price},{time_str})")
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finally:
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self.__last_price_dict[code] = price
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def OnMarketData(self, code, datas):
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# logger_debug.info(f"收到L2Market数据：{datas}")
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for d in datas:
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code = d["securityID"]
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buy1 = d["buy"][0]
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# 实时L2买1成交量
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def OnRealTimeBuy1Info(self, code, buy1_info):
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# buy1_info: [买1时间,买1价格, 原始买1量, 实时买1量]
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async_log_util.info(logger_debug, f"OnRealTimeBuy1Info：{code}-{buy1_info}")
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# L1DataProcessor.excute_sell_rule(code, buy1_info[3], buy1_info[1], "l2-real")
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l2_data_callbacks = []
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def __subscript_position_l2():
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"""
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订阅持仓L2数据
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:return:
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"""
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position_result = huaxin_trade_api.get_position_list(blocking=True)
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logger_debug.info(f"获取持仓结果：{position_result}")
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if not position_result or position_result["code"] != 0 or not position_result["data"]:
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return
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positions = position_result["data"]
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subscript_codes = set()
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for p in positions:
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if p["prePosition"] > 0:
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subscript_codes.add(p["securityID"])
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if not subscript_codes:
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return
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for i in range(len(subscript_codes)):
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l2_data_callbacks.append(MyPositionsL2DataCallback())
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l2_client.run(subscript_codes, l2_data_callbacks)
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# 第三步：执行策略的初始设置
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if __name__ == '__main__':
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class MyMarketDataCallback(l2_market_client.L2MarketDataCallback):
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def on_markets(self, datas):
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"""
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L1数据回调
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:param datas:
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:return:
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"""
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data_cache.latest_code_market_info_dict = {x[0]: x for x in datas}
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if datas:
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print(datas[0])
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if constant.is_windows():
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instant_time_market.get_current_info()
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else:
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instant_time_market.set_current_info(datas)
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# 加载开盘啦板块日志数据
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kpl_data_manager.KPLStockOfMarketsPlateLogManager()
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# 启动异步日志
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threading.Thread(target=async_log_util.run_sync, daemon=True).start()
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# redis 数据同步
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threading.Thread(target=RedisUtils.run_loop, daemon=True).start()
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# 启动交易
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order_methods.run()
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# 运行华鑫增值服务进程,用于获取K线与交易日历
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threading.Thread(target=hx_qc_value_util.run, daemon=True).start()
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# 运行交易数据更新服务
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huaxin_trade_data_update.run()
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# 等待5s，等其他线程/进程启动完毕
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time.sleep(15)
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# 订阅持仓票
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threading.Thread(target=__subscript_position_l2, daemon=True).start()
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try:
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# 初始化数据
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init()
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except Exception as e:
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logger_system.exception(e)
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# 需要订阅的目标代码
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target_codes = [x["sec_id"] for x in data_cache.DataCache().all_stocks]
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# 订阅L2 market行情
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l2_market_client.run(target_codes, MyMarketDataCallback())
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