| huaxin_client/l1_api_client.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/kpl_api.py | ●●●●● 补丁 | 查看 | 原始文档 | blame | 历史 |
huaxin_client/l1_api_client.py
@@ -5,7 +5,7 @@ import constant import qcvalueaddproapi from log_module.log import logger_system from log_module.log import logger_system, logger_debug from utils import tool global g_userid, g_passwd, g_address, g_port, g_seqnum @@ -157,6 +157,16 @@ except Exception as e: logging.exception(e) def __subStockIndex(self): """ 订阅股票指数行情 """ # 沪深300 self.m_api.SubscribeStockIndexData(qcvalueaddproapi.QCVD_EXD_SSE, "000300") # 沪深300 self.m_api.SubscribeStockIndexData(qcvalueaddproapi.QCVD_EXD_SSE, "000001") # 上证 self.m_api.SubscribeStockIndexData(qcvalueaddproapi.QCVD_EXD_SZSE, "399006") # 创业板指数 self.m_api.SubscribeStockIndexData(qcvalueaddproapi.QCVD_EXD_SZSE, "399001") # 深圳成指 def OnFrontConnected(self): print("OnFrontConnected") # 连接上后去登录 @@ -184,6 +194,15 @@ # threading.Thread(target=lambda: print("交易日历：", self.queryTradeCalendar("2024-03-08", "2024-12-31"))).start() # threading.Thread( # target=lambda: print("日K：", self.queryBars("601298", "2024-12-15", "2024-12-31"))).start() try: self.__subStockIndex() except: pass def OnRtnStockIndexData(self, pStockIndexData): # 指数数据 logger_debug.info(f"指数行情应答：{pStockIndexData}") pass def ReqQryGGTEODPrices(self): QryField = qcvalueaddproapi.CQCVDQryGGTEODPricesField() @@ -244,7 +263,6 @@ def __read_request(request_queue: multiprocessing.Queue, response_queue: multiprocessing.Queue): def __set_response_data(request_id, response_data): response_queue.put_nowait({"request_id": request_id, "data": response_data}) @@ -290,18 +308,16 @@ #IP（192.168.84.61）、端口（25557 # 回测交易是由历史行情来驱动撮合成交: # 因此必须同时使用traderapi和mdapi，不能单独使用traderapi，并且mdapi至少需要订阅一个以上行情。 # 用户可使用回测traderapi的RegisterFront函数来注册此地址去连接上回测服务器 print("GetApiVersion():", qcvalueaddproapi.CQCValueAddProApi_GetApiVersion()) theapi = qcvalueaddproapi.CQCValueAddProApi_CreateInfoQryApi() global thespi global thespi thespi = sampleSpi(theapi) theapi.RegisterSpi(thespi) theapi.RegisterFront(g_address, g_port) threading.Thread(target=__read_request, args=(request_queue, response_queue, ), daemon=True).start() threading.Thread(target=__read_request, args=(request_queue, response_queue,), daemon=True).start() theapi.Run()
@@ -29,10 +29,10 @@ frozenCash = data_cache.account_finance_dict[0]['frozenCash'] # 冻结的资金 fetchLimit = data_cache.account_finance_dict[0]['fetchLimit'] # 可取资金 preDeposit = data_cache.account_finance_dict[0]['preDeposit'] # 上日结存 print(f"可用资金==={data_cache.usefulMoney}") print(f"冻结的资金==={frozenCash}") print(f"可取资金==={fetchLimit}") print(f"上日结存==={preDeposit}") logger.info(f"可用资金==={data_cache.usefulMoney}") 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()
@@ -306,38 +306,33 @@ # market_strong = get_market_strong() # print(f"market_strong==={market_strong}") # 获取涨停板块名称列表并存储本地的函数 def get_limit_up_block_names(): # 获取涨停信息列表 limit_up_info = get_limit_up_info() # print(f"limit_up_info=={limit_up_info}") data_cache.limit_up_info = get_limit_up_info() # 提取涨停列表中的板块名称 limit_up_block_names = [] # 设定当前时间点 now_time = datetime.datetime.now().strftime("%H:%M:%S") # 循环添加涨停概念 for i in limit_up_info: limit_up_block_names.append(i[5]) # print(f"limit_up_block_names==={limit_up_block_names}") # return limit_up_block_names # # 使用Counter计算每个元素的出现次数 # counter = Counter(limit_up_block_names) # # 找出出现次数最多的元素及其次数 # most_common_element, most_common_count = counter.most_common(1)[0] # # 打印出现次数最多的元素 # print(f"主线概念：{most_common_element}，出现了 {most_common_count} 次") if now_time > data_cache.after_closing_time: # print(f"收盘结束，记录当前涨停板块") # 将获取到的涨停概念板块转JSON格式并存储在本地文件夹中 # 将字典转换为JSON格式的字符串 json_data = json.dumps(limit_up_block_names) # print(f"json_data=={json_data}") if len(json_data) != 0: # 写入文件 with open(constant.KPL_LIMIT_UP_BLOCK_NAMES_PATH, 'w', encoding='utf-8') as f: f.write(json_data) return limit_up_block_names # print(f"now_time===={now_time}") if data_cache.opening_time < now_time < data_cache.update_data_time: # print(f"在时间内使用--------------------------") # 获取涨停信息列表 limit_up_info = get_limit_up_info() # print(f"limit_up_info=={limit_up_info}") data_cache.limit_up_info = get_limit_up_info() # 提取涨停列表中的板块名称 limit_up_block_names = [] # 循环添加涨停概念 for i in limit_up_info: limit_up_block_names.append(i[5]) # print(f"limit_up_block_names==={limit_up_block_names}") # return limit_up_block_names # # 使用Counter计算每个元素的出现次数 # counter = Counter(limit_up_block_names) # # 找出出现次数最多的元素及其次数 # most_common_element, most_common_count = counter.most_common(1)[0] # # 打印出现次数最多的元素 # print(f"主线概念：{most_common_element}，出现了 {most_common_count} 次") return limit_up_block_names # 为开盘啦接口获取的涨停列表概念板块单独开一个进程 形参(callback)
