def __init__(self, start_dt, end_dt): """ 创建天勤回测类 Args: start_dt (date/datetime): 回测起始时间, 如果类型为 date 则指的是交易日, 如果为 datetime 则指的是具体时间点 end_dt (date/datetime): 回测结束时间, 如果类型为 date 则指的是交易日, 如果为 datetime 则指的是具体时间点 """ if isinstance(start_dt, datetime): self.current_dt = int(start_dt.timestamp() * 1e9) elif isinstance(start_dt, date): self.current_dt = TqApi._get_trading_day_start_time( int( datetime(start_dt.year, start_dt.month, start_dt.day).timestamp()) * 1000000000) else: raise Exception( "回测起始时间(start_dt)类型 %s 错误, 请检查 start_dt 数据类型是否填写正确" % (type(start_dt))) if isinstance(end_dt, datetime): self.end_dt = int(end_dt.timestamp() * 1e9) elif isinstance(end_dt, date): self.end_dt = TqApi._get_trading_day_end_time( int( datetime(end_dt.year, end_dt.month, end_dt.day).timestamp()) * 1000000000) else: raise Exception("回测结束时间(end_dt)类型 %s 错误, 请检查 end_dt 数据类型是否填写正确" % (type(end_dt)))
def __init__(self, start_dt, end_dt): """ 创建天勤回测类 Args: start_dt (date/datetime): 回测起始时间, 如果类型为 date 则指的是交易日, 如果为 datetime 则指的是具体时间点 end_dt (date/datetime): 回测结束时间, 如果类型为 date 则指的是交易日, 如果为 datetime 则指的是具体时间点 """ if isinstance(start_dt, datetime): self.current_dt = int(start_dt.timestamp()*1e9) else: self.current_dt = TqApi._get_trading_day_start_time(int(datetime(start_dt.year, start_dt.month, start_dt.day).timestamp())*1000000000) if isinstance(end_dt, datetime): self.end_dt = int(end_dt.timestamp()*1e9) else: self.end_dt = TqApi._get_trading_day_end_time(int(datetime(end_dt.year, end_dt.month, end_dt.day).timestamp())*1000000000)
async def _gen_serial(self, ins, dur): """k线/tick 序列的 async generator, yield 出来的行情数据带有时间戳, 因此 _send_diff 可以据此归并""" # 先定位左端点, focus_datetime 是 lower_bound ,这里需要的是 upper_bound # 因此将 view_width 和 focus_position 设置成一样,这样 focus_datetime 所对应的 k线刚好位于屏幕外 chart_info = { "aid": "set_chart", "chart_id": TqApi._generate_chart_id("backtest", ins, dur // 1000000000), "ins_list": ins, "duration": dur, "view_width": 8964, "focus_datetime": int(self.current_dt), "focus_position": 8964, } chart = TqApi._get_obj(self.data, ["charts", chart_info["chart_id"]]) current_id = None # 当前数据指针 serial = TqApi._get_obj( self.data, ["klines", ins, str(dur)] if dur != 0 else ["ticks", ins]) async with TqChan(self.api, last_only=True) as update_chan: serial["_listener"].add(update_chan) chart["_listener"].add(update_chan) await self.md_send_chan.send(chart_info.copy()) try: async for _ in update_chan: if not (chart_info.items() <= TqApi._get_obj( chart, ["state"]).items()): # 当前请求还没收齐回应, 不应继续处理 continue left_id = chart.get("left_id", -1) right_id = chart.get("right_id", -1) last_id = serial.get("last_id", -1) if (left_id == -1 and right_id == -1) or last_id == -1: # 定位信息还没收到, 或数据序列还没收到 continue if self.data.get("mdhis_more_data", True): self.data["_listener"].add(update_chan) continue else: self.data["_listener"].discard(update_chan) if current_id is None: current_id = max(left_id, 0) while True: if current_id > last_id: # 当前 id 已超过 last_id return if current_id - chart_info.get("left_kline_id", left_id) > 5000: # 当前 id 已超出订阅范围, 需重新订阅后续数据 chart_info["left_kline_id"] = current_id chart_info.pop("focus_datetime", None) chart_info.pop("focus_position", None) await self.md_send_chan.send(chart_info.copy()) if current_id > right_id: break item = serial["data"].get(str(current_id), {}).copy() del item["_path"] del item["_listener"] if dur == 0: diff = { "ticks": { ins: { "last_id": current_id, "data": { str(current_id): item, str(current_id - 8964): None, } } } } if item["datetime"] > self.end_dt: # 超过结束时间 return yield item[ "datetime"], diff, self._get_quotes_from_tick( item) else: diff = { "klines": { ins: { str(dur): { "last_id": current_id, "data": { str(current_id): { "datetime": item["datetime"], "open": item["open"], "high": item["open"], "low": item["open"], "close": item["open"], "volume": 0, "open_oi": item["open_oi"], "close_oi": item["open_oi"], }, str(current_id - 8964): None, } } } } } timestamp = item[ "datetime"] if dur < 86400000000000 else TqApi._get_trading_day_start_time( item["datetime"]) if timestamp > self.end_dt: # 超过结束时间 return yield timestamp, diff, None diff = { "klines": { ins: { str(dur): { "data": { str(current_id): item, } } } } } timestamp = item[ "datetime"] + dur - 1000 if dur < 86400000000000 else TqApi._get_trading_day_end_time( item["datetime"]) if timestamp > self.end_dt: # 超过结束时间 return yield timestamp, diff, self._get_quotes_from_kline( self.data["quotes"][ins], timestamp, item) current_id += 1 finally: # 释放chart资源 chart_info["ins_list"] = "" await self.md_send_chan.send(chart_info.copy())
def __init__(self, api, symbol_list, dur_sec, start_dt, end_dt, csv_file_name): """ 创建历史数据下载器实例 Args: api (TqApi): TqApi实例,该下载器将使用指定的api下载数据 symbol_list (str/list of str): 需要下载数据的合约代码,当指定多个合约代码时将其他合约按第一个合约的交易时间对齐 dur_sec (int): 数据周期,以秒为单位。例如: 1分钟线为60,1小时线为3600,日线为86400,Tick数据为0 start_dt (date/datetime): 起始时间, 如果类型为 date 则指的是交易日, 如果为 datetime 则指的是具体时间点 end_dt (date/datetime): 结束时间, 如果类型为 date 则指的是交易日, 如果为 datetime 则指的是具体时间点 csv_file_name (str): 输出csv的文件名 Example:: from datetime import datetime, date from contextlib import closing from tqsdk import TqApi, TqSim from tqsdk.tools import DataDownloader api = TqApi(TqSim()) download_tasks = {} # 下载从 2018-01-01 到 2018-09-01 的 SR901 日线数据 download_tasks["SR_daily"] = DataDownloader(api, symbol_list="CZCE.SR901", dur_sec=24*60*60, start_dt=date(2018, 1, 1), end_dt=date(2018, 9, 1), csv_file_name="SR901_daily.csv") # 下载从 2017-01-01 到 2018-09-01 的 rb主连 5分钟线数据 download_tasks["rb_5min"] = DataDownloader(api, symbol_list="*****@*****.**", dur_sec=5*60, start_dt=date(2017, 1, 1), end_dt=date(2018, 9, 1), csv_file_name="rb_5min.csv") # 下载从 2018-01-01凌晨6点 到 2018-06-01下午4点 的 cu1805,cu1807,IC1803 分钟线数据,所有数据按 cu1805 的时间对齐 # 例如 cu1805 夜盘交易时段, IC1803 的各项数据为 N/A # 例如 cu1805 13:00-13:30 不交易, 因此 IC1803 在 13:00-13:30 之间的K线数据会被跳过 download_tasks["cu_min"] = DataDownloader(api, symbol_list=["SHFE.cu1805", "SHFE.cu1807", "CFFEX.IC1803"], dur_sec=60, start_dt=datetime(2018, 1, 1, 6, 0 ,0), end_dt=datetime(2018, 6, 1, 16, 0, 0), csv_file_name="cu_min.csv") # 下载从 2018-05-01凌晨0点 到 2018-06-01凌晨0点 的 T1809 盘口Tick数据 download_tasks["T_tick"] = DataDownloader(api, symbol_list=["CFFEX.T1809"], dur_sec=0, start_dt=datetime(2018, 5, 1), end_dt=datetime(2018, 6, 1), csv_file_name="T1809_tick.csv") # 使用with closing机制确保下载完成后释放对应的资源 with closing(api): while not all([v.is_finished() for v in download_tasks.values()]): api.wait_update() print("progress: ", { k:("%.2f%%" % v.get_progress()) for k,v in download_tasks.items() }) """ self.api = api if isinstance(start_dt, datetime): self.start_dt_nano = int(start_dt.timestamp() * 1e9) else: self.start_dt_nano = TqApi._get_trading_day_start_time( int( datetime(start_dt.year, start_dt.month, start_dt.day).timestamp()) * 1000000000) if isinstance(end_dt, datetime): self.end_dt_nano = int(end_dt.timestamp() * 1e9) else: self.end_dt_nano = TqApi._get_trading_day_end_time( int( datetime(end_dt.year, end_dt.month, end_dt.day).timestamp()) * 1000000000) self.current_dt_nano = self.start_dt_nano self.symbol_list = symbol_list if isinstance(symbol_list, list) else [symbol_list] self.dur_nano = dur_sec * 1000000000 if self.dur_nano == 0 and len(self.symbol_list) != 1: raise Exception("Tick序列不支持多合约") self.csv_file_name = csv_file_name self.task = self.api.create_task(self._download_data())