import json
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import os
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import queue
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import time
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import xlwt
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from code_attribute import gpcode_manager
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from l2.huaxin import l2_huaxin_util
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from third_data import history_k_data_manager
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from third_data.history_k_data_manager import HistoryKDataManager
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from utils import tool
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class Test:
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def print_log(self, arg):
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print(time.time(), f"arg:{arg}")
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time.sleep(2)
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def parse_big_buy_order_count(path_, limit_up_price_dict=None, max_time=None):
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"""
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统计某一天的涨停大单数量分布
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@param path_:
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@param limit_up_price_dict:
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@return:
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"""
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with open(path_, mode='r', encoding='utf-8') as f:
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lines = f.readlines()
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code_big_order_count_dict = {}
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for line in lines:
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data = line[line.find(" - ") + 3:].strip()
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data = eval(data)
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if data[1] != 0:
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continue
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if data[2][2] < 1000000:
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continue
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if max_time and l2_huaxin_util.convert_time(data[2][3]) > max_time:
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continue
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# if data[0] not in limit_up_price_dict:
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# continue
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# if abs(data[2][4] - limit_up_price_dict[data[0]]) >= 0.001:
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# continue
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if data[0] not in code_big_order_count_dict:
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code_big_order_count_dict[data[0]] = [0, 0]
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code_big_order_count_dict[data[0]][0] += 1
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code_big_order_count_dict[data[0]][1] += data[2][2]
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return code_big_order_count_dict
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def __load_limit_up_price():
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# 日期下代码的涨停价
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limit_up_price_date_code_dict = {}
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dir_path = r"D:\回测数据\K线数据"
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k_bars_files = os.listdir(dir_path)
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for k_bars_file in k_bars_files:
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code = k_bars_file.split("_")[1][:6]
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with open(f"{dir_path}\\{k_bars_file}", encoding='utf-8', mode='r') as f:
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lines = f.readlines()
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data = lines[0]
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datas = eval(data)
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# {"日期": 涨停价}
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date_limit_price = {
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d["bob"][:10]: gpcode_manager.get_limit_up_price_by_preprice(d["sec_id"], d["pre_close"]) for d in
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datas}
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for date in date_limit_price:
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if date not in limit_up_price_date_code_dict:
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limit_up_price_date_code_dict[date] = {}
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limit_up_price_date_code_dict[date][code] = round(float(date_limit_price[date]), 2)
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return limit_up_price_date_code_dict
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def export(fdatas, dates, file_name):
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wb = xlwt.Workbook(encoding="utf-8")
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ws = wb.add_sheet('sheet1')
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for i in range(len(dates)):
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ws.write(0, i + 1, dates[i])
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index = 0
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for code in fdatas:
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date_count_dict = fdatas[code]
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index += 1
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ws.write(index, 0, code)
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for i in range(len(dates)):
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d = date_count_dict.get(dates[i])
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average_big_money = d[1] // d[0] if d[0] > 0 else 0
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if d[0] > 0:
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ws.write(index, i + 1, f"{d[0]}/{round(average_big_money / 10000, 1)}万")
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else:
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ws.write(index, i + 1, f"")
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wb.save(file_name)
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if __name__ == '__main__':
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def callback_function(res):
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print("回调数据：", res)
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def exec(call_back):
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call_back({"code": 0})
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exec(callback_function)
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if __name__ == '__main__1':
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# 加载每一天的代码的涨停价
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limit_up_price_date_code_dict = __load_limit_up_price()
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print(limit_up_price_date_code_dict["2025-04-22"]["002719"])
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dir_path = r"D:\回测数据\大单数据"
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files = os.listdir(dir_path)
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dates = []
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big_order_count_date_code_dict = {}
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for file_name in files:
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path_ = f"{dir_path}\\{file_name}"
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date = file_name[-14:-4]
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dates.append(date)
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code_big_order_count_dict = parse_big_buy_order_count(path_, limit_up_price_date_code_dict[date])
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print(code_big_order_count_dict)
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big_order_count_date_code_dict[date] = code_big_order_count_dict
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# 转为：{代码:{"日期":大单数}}
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fdata = {}
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for date in big_order_count_date_code_dict:
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for code in big_order_count_date_code_dict[date]:
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if code not in fdata:
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fdata[code] = {}
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fdata[code][date] = big_order_count_date_code_dict[date][code]
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for code in fdata:
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for date in dates:
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if date not in fdata[code]:
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# 默认填充0
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fdata[code][date] = [0, 0]
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dates.sort(reverse=True)
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export(fdata, dates, "D:/test.xls")
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