| main.py | ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史 | |
| strategy/L2_data_analysis.py | ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史 | |
| strategy/account_management.py | ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史 | |
| strategy/all_K_line.py | ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史 | |
| strategy/buying_strategy.py | ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史 | |
| strategy/index_market_trend_strategy.py | ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史 | |
| strategy/order_methods.py | ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史 |
main.py
@@ -100,7 +100,8 @@ # 开盘啦的涨停概念的回调函数 def kpl_limit_up_process(datas): # print(f"回调成功==={datas}") data_cache.limit_up_block_names = datas if datas is not None and len(datas) > 0: data_cache.limit_up_block_names = datas # # 计算当前线程数量 # get_current_thread_count() strategy/L2_data_analysis.py
@@ -65,11 +65,6 @@ # print(f"没有找到这个货：{code}") # 测试的时候可以调用一下 find_L2_big_order_of_code('002384') # # 如果你需要将解析后的日志保存到新文件中，可以使用以下代码： # output_file_path = 'path/to/your/parsed_logfile.txt' # with open(output_file_path, 'w', encoding='utf-8') as output_file: # for log in parsed_logs: # output_file.write(log + '\n') if __name__ == '__main__': # 测试的时候可以调用一下 find_L2_big_order_of_code('002384') strategy/account_management.py
@@ -92,9 +92,9 @@ else: data_cache.available_symbols_set.add(securityID) if historyPosFrozen != 0: logger.info(f"昨日持仓==={securityName}==挂单中》》挂单数量：{historyPosFrozen}") else: logger.info(f"昨日持仓==={securityName}===持仓可用：{availablePosition}") 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}") # todo 自主的计算持仓数量 管用 还是 服务端即时查询同步有用 有待验证 logger.info(f"今日可用持仓数量====================================【{len(data_cache.available_symbols_set)}】") strategy/all_K_line.py
@@ -209,8 +209,7 @@ current_count = 0 start = None # 确保不会出现除以零的报错 if current_yesterday_volume == 0: current_yesterday_volume = 1 if current_yesterday_volume != 0: if round(current_today_volume / current_yesterday_volume, 2) > 1.1: # print(f"i=={i} {it_K_line[i]['bob']} {round(current_today_volume/current_yesterday_volume,2)} 【放量】") if current_today_growth > 0: @@ -234,17 +233,19 @@ else: it_K_line[i]['today_volume_shape'] = 'decreases_balance' # print(f"i=={i} {it_K_line[i]['bob']} 【缩量平收】") else: # print(f"i=={i} {it_K_line[i]['bob']} {round(current_today_volume/current_yesterday_volume,2)} 【平量】") if current_today_growth > 0: it_K_line[i]['today_volume_shape'] = 'remained_up' # print(f"i=={i} {it_K_line[i]['bob']} 【平量上涨】") elif current_today_growth < 0: it_K_line[i]['today_volume_shape'] = 'remained_down' # print(f"i=={i} {it_K_line[i]['bob']} 【平量下跌】") else: it_K_line[i]['today_volume_shape'] = 'remained_balance' # print(f"i=={i} {it_K_line[i]['bob']} 【平量平收】") # print(f"i=={i} {it_K_line[i]['bob']} {round(current_today_volume/current_yesterday_volume,2)} 【平量】") if current_today_growth > 0: it_K_line[i]['today_volume_shape'] = 'remained_up' # print(f"i=={i} {it_K_line[i]['bob']} 【平量上涨】") elif current_today_growth < 0: it_K_line[i]['today_volume_shape'] = 'remained_down' # print(f"i=={i} {it_K_line[i]['bob']} 【平量下跌】") else: it_K_line[i]['today_volume_shape'] = 'remained_balance' # print(f"i=={i} {it_K_line[i]['bob']} 【平量平收】") else: logger.info(f"{symbol} 的 昨日成交量 为 0，报错！！") if current_open - previous_close > 0: # print(f"i=={i} {it_K_line[i]['bob']} 成交总量:{today_volume},,,成交总金额:{today_amount}") strategy/buying_strategy.py
@@ -335,12 +335,22 @@ order_methods.buy_order_by_value(symbol, data_cache.today_planned_order_amount, 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) # 查看一下该股有无大单 L2_data_analysis.find_L2_big_order_of_code(symbol_code) # 检测持仓信息中有无下单个股且有该个股的当前持仓，只有当前持仓数量不为0时，才认为交易成功 for i in data_cache.account_positions_dict: # print(i) if i['securityID'] == symbol_code: # print(i['currentPosition']) if i['currentPosition'] == 0: logger.info(f"【{i['securityName']}】交易失败~") else: # 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) logger.info(f"【{i['securityName']}】交易成功！") # 有概念无强度视界 @@ -418,12 +428,25 @@ # 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) # 查看一下该股有无大单 # # 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) # # 查看一下该股有无大单 L2_data_analysis.find_L2_big_order_of_code(symbol_code) # 检测持仓信息中有无下单个股且有该个股的当前持仓，只有当前持仓数量不为0时，才认为交易成功 for i in data_cache.account_positions_dict: # print(i) if i['securityID'] == symbol_code: # print(i['currentPosition']) if i['currentPosition'] == 0: logger.info(f"【{i['securityName']}】交易失败~") else: # 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) logger.info(f"【{i['securityName']}】交易成功！") ''' 无概念 有强度视界 @@ -505,12 +528,25 @@ data_cache.today_planned_order_amount, 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) # # 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) # 查看一下该股有无大单 L2_data_analysis.find_L2_big_order_of_code(symbol_code) # 检测持仓信息中有无下单个股且有该个股的当前持仓，只有当前持仓数量不为0时，才认为交易成功 for i in data_cache.account_positions_dict: # print(i) if i['securityID'] == symbol_code: # print(i['currentPosition']) if i['currentPosition'] == 0: logger.info(f"【{i['securityName']}】交易失败~") else: # 将有概念买入次数自加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) logger.info(f"【{i['securityName']}】交易成功！") ''' 无概念无强度 有小量换大涨幅度视界 ''' @@ -603,12 +639,25 @@ 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']) # # 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']) # 查看一下该股有无大单 L2_data_analysis.find_L2_big_order_of_code(symbol_code) # 检测持仓信息中有无下单个股且有该个股的当前持仓，只有当前持仓数量不为0时，才认为交易成功 for i in data_cache.account_positions_dict: # print(i) if i['securityID'] == symbol_code: # print(i['currentPosition']) if i['currentPosition'] == 0: logger.info(f"【{i['securityName']}】交易失败~") else: # 将有概念买入次数自加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.extend(k_line_data[0]['sec_name']) logger.info(f"【{i['securityName']}】交易成功！") ''' 昨日涨停视界,今日连板预期盯视界 ''' @@ -720,15 +769,3 @@ # 如果K线数据为空，则不进入后续判断 # print(f"代码：{symbol}，k_line_data is None，未get到该股的K线属性，或为新股、次新股第一天的时候确实没有历史K线") # 委托状态更新事件 def on_order_status(context, order): # 可在后面执行其他处理逻辑 logger.info(f"买入策略context====t————{context}") logger.info(f"买入策略order====t————{order}") # 委托执行回报事件 def on_execution_report(context, execrpt): logger.info(f"买入策略context===={context}") logger.info(f"execrpt========{execrpt}") strategy/index_market_trend_strategy.py
@@ -208,7 +208,7 @@ it_K_line[0].update(new_properties) # 计算大振幅的日期并添加到大振幅日期列表中 if not (-4 < it_K_line[i]['today_growth'] < 4): if not (-1 < it_K_line[i]['today_growth'] < 1): large_amplitude_day.append(it_K_line[i]['bob']) # 判断K线图形风险位置 及 高低时间点 @@ -282,8 +282,7 @@ current_count = 0 start = None # 确保不会出现除以零的报错 if current_yesterday_volume == 0: current_yesterday_volume = 1 if current_yesterday_volume != 0: if round(current_today_volume / current_yesterday_volume, 2) > 1.1: # print(f"i=={i} {it_K_line[i]['bob']} {round(current_today_volume/current_yesterday_volume,2)} 【放量】") if current_today_growth > 0: @@ -307,17 +306,19 @@ else: it_K_line[i]['today_volume_shape'] = 'decreases_balance' # print(f"i=={i} {it_K_line[i]['bob']} 【缩量平收】") else: # print(f"i=={i} {it_K_line[i]['bob']} {round(current_today_volume/current_yesterday_volume,2)} 【平量】") if current_today_growth > 0: it_K_line[i]['today_volume_shape'] = 'remained_up' # print(f"i=={i} {it_K_line[i]['bob']} 【平量上涨】") elif current_today_growth < 0: it_K_line[i]['today_volume_shape'] = 'remained_down' # print(f"i=={i} {it_K_line[i]['bob']} 【平量下跌】") else: it_K_line[i]['today_volume_shape'] = 'remained_balance' # print(f"i=={i} {it_K_line[i]['bob']} 【平量平收】") # print(f"i=={i} {it_K_line[i]['bob']} {round(current_today_volume/current_yesterday_volume,2)} 【平量】") if current_today_growth > 0: it_K_line[i]['today_volume_shape'] = 'remained_up' # print(f"i=={i} {it_K_line[i]['bob']} 【平量上涨】") elif current_today_growth < 0: it_K_line[i]['today_volume_shape'] = 'remained_down' # print(f"i=={i} {it_K_line[i]['bob']} 【平量下跌】") else: it_K_line[i]['today_volume_shape'] = 'remained_balance' # print(f"i=={i} {it_K_line[i]['bob']} 【平量平收】") else: logger.info(f"{symbol} 的 昨日成交量 为 0，报错！！") if current_open - previous_close > 0: # print(f"i=={i} {it_K_line[i]['bob']} 成交总量:{today_volume},,,成交总金额:{today_amount}") @@ -358,6 +359,7 @@ # 长期低幅度震荡下跌 it_K_line[0]['long_term_amplitude'] = 'low_amplitude_oscillation_and_decline' # 将加入属性值的指数K线下入到本地文件中 def all_index_k_line_dict_write(): all_index_K_line_dict = get_index_K_line() strategy/order_methods.py
@@ -51,6 +51,9 @@ # 调用资金查询函数 查看资金变化 account_management.finance_management() logger.info(f"更新的资金数据data_cache.account_finance_dict=={data_cache.account_finance_dict}") if symbol[-6:] in data_cache.account_positions_dict: pass # 因为上面的更新持仓数据函数会计算 今日新增持仓数量，所以如果再手动新增持仓数据会重复计算【考虑到持仓函数有可能会有延迟，这也可能是同时运行一段时间没有出现BUG的原因，先暂时保留以下这段代码，只是注释】 # # 买票后添加 持仓代码集合
