def __init__(self, start_dt: Union[date, datetime], end_dt: Union[date, datetime]) -> None:
"""
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._start_dt = int(start_dt.timestamp() * 1e9)
elif isinstance(start_dt, date):
self._start_dt = _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 = _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)))
self._current_dt = self._start_dt
# 记录当前的交易日 开始时间/结束时间
self._trading_day = _get_trading_day_from_timestamp(self._current_dt)
self._trading_day_start = _get_trading_day_start_time(self._trading_day)
self._trading_day_end = _get_trading_day_end_time(self._trading_day)
async def _send_diff(self):
"""发送数据到 api, 如果 self._diffs 不为空则发送 self._diffs, 不推进行情时间, 否则将时间推进一格, 并发送对应的行情"""
if self._pending_peek:
if not self._diffs:
quotes = await self._generator_diffs(False)
else:
quotes = await self._generator_diffs(True)
for ins, diff in quotes.items():
self._quotes[ins]["sended_init_quote"] = True
for d in diff:
self._diffs.append({
"quotes": {
ins: d
}
})
if self._diffs:
# 发送数据集中添加 backtest 字段，开始时间、结束时间、当前时间，表示当前行情推进是由 backtest 推进
if self._is_first_send:
self._diffs.append({
"_tqsdk_backtest": {
"start_dt": self._start_dt,
"current_dt": self._current_dt,
"end_dt": self._end_dt
}
})
self._is_first_send = False
else:
self._diffs.append({
"_tqsdk_backtest": {
"current_dt": self._current_dt
}
})
# 切换交易日，将历史的主连合约信息添加的 diffs
if self._current_dt > self._trading_day_end:
# 使用交易日结束时间，每个交易日切换只需要计算一次交易日结束时间
# 相比发送 diffs 前每次都用 _current_dt 计算当前交易日，计算次数更少
self._trading_day_start = _get_trading_day_start_time(_get_trading_day_from_timestamp(self._current_dt))
self._trading_day_end = _get_trading_day_end_time(_get_trading_day_from_timestamp(self._current_dt))
self._diffs.append({
"quotes": self._get_history_cont_quotes(
datetime.fromtimestamp(self._trading_day_end / 1e9).strftime("%Y%m%d")
)
})
self._diffs.append({
"quotes": {k: {'expired': v.get('expire_datetime', float('nan')) <= self._trading_day_start}
for k, v in self._data.get('quotes').items()}
})
self._sim_recv_chan_send_count += 1
if self._sim_recv_chan_send_count > 10000:
self._sim_recv_chan_send_count = 0
self._diffs.append(self._gc_data())
rtn_data = {
"aid": "rtn_data",
"data": self._diffs,
}
self._diffs = []
self._pending_peek = False
await self._sim_recv_chan.send(rtn_data)
def _get_trading_timestamp(quote, current_datetime: str):
""" 将 quote 在 current_datetime 所在交易日的所有可交易时间段转换为纳秒时间戳(tqsdk内部使用的时间戳统一为纳秒)并返回 """
# 获取当前交易日时间戳
current_trading_day_timestamp = _get_trading_day_from_timestamp(
int(datetime.datetime.strptime(current_datetime, "%Y-%m-%d %H:%M:%S.%f").timestamp() * 1e6) * 1000)
# 获取上一交易日时间戳
last_trading_day_timestamp = _get_trading_day_from_timestamp(
_get_trading_day_start_time(current_trading_day_timestamp) - 1)
trading_timestamp = {
"day": TqSim._get_period_timestamp(current_trading_day_timestamp, quote["trading_time"].get("day", [])),
"night": TqSim._get_period_timestamp(last_trading_day_timestamp, quote["trading_time"].get("night", []))
}
return trading_timestamp
def dt_func (self):
# 回测和复盘模式，用 _api._account 一定是 TqSim, 使用 TqSim _get_current_timestamp() 提供的时间
# todo: 使用 TqSim.EPOCH
if self._data["action"]["mode"] == "backtest":
return self._data['_tqsdk_backtest']['current_dt']
elif self._data["action"]["mode"] == "replay":
tqsim_current_timestamp = self._api._account._account_list[0]._get_current_timestamp()
if tqsim_current_timestamp == 631123200000000000:
# 未收到任何行情, TqSim 时间没有更新
return _get_trading_day_start_time(self._data['_tqsdk_replay']['replay_dt'])
else:
return tqsim_current_timestamp
else:
return int(datetime.now().timestamp() * 1e9)
def __init__(self, api: TqApi, symbol_list: Union[str, List[str]], dur_sec: int, start_dt: Union[date, datetime],
end_dt: Union[date, datetime], csv_file_name: str) -> None:
"""
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 = _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 = _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())
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": _generate_uuid("PYSDK_backtest"),
"ins_list": ins,
"duration": dur,
"view_width":
8964, # 设为8964原因：可满足用户所有的订阅长度，并在backtest中将所有的 相同合约及周期 的K线用同一个serial存储
"focus_datetime": int(self._current_dt),
"focus_position": 8964,
}
chart = _get_obj(self._data, ["charts", chart_info["chart_id"]])
current_id = None # 当前数据指针
serial = _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() <= _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())
# 将订阅的8964长度的窗口中的数据都遍历完后，退出循环，然后再次进入并处理下一窗口数据
# （因为在处理过5000条数据的同时向服务器订阅从当前id开始的新一窗口的数据，在当前窗口剩下的3000条数据处理完后，下一窗口数据也已经收到）
if current_id > right_id:
break
item = {
k: v
for k, v in serial["data"].get(
str(current_id), {}).items()
}
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 _get_trading_day_start_time(
item["datetime"])
if timestamp > self._end_dt: # 超过结束时间
return
yield timestamp, diff, self._get_quotes_from_kline_open(
self._data["quotes"][ins], timestamp,
item) # K线刚生成时的数据都为开盘价
diff = {
"klines": {
ins: {
str(dur): {
"data": {
str(current_id): item,
}
}
}
}
}
timestamp = item[
"datetime"] + dur - 1000 if dur < 86400000000000 else _get_trading_day_end_time(
item["datetime"]) - 999
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) # K线结束时生成quote数据
current_id += 1
finally:
# 释放chart资源
chart_info["ins_list"] = ""
await self._md_send_chan.send(chart_info.copy())
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
# 使用两个长度为 8964 的 chart，去缓存/回收下游需要的数据
chart_id_a = _generate_uuid("PYSDK_backtest")
chart_id_b = _generate_uuid("PYSDK_backtest")
chart_info = {
"aid": "set_chart",
"chart_id": chart_id_a,
"ins_list": ins,
"duration": dur,
"view_width": 8964, # 设为8964原因：可满足用户所有的订阅长度，并在backtest中将所有的 相同合约及周期 的K线用同一个serial存储
"focus_datetime": int(self._current_dt),
"focus_position": 8964,
}
chart_a = _get_obj(self._data, ["charts", chart_id_a])
chart_b = _get_obj(self._data, ["charts", chart_id_b])
symbol_list = ins.split(',')
current_id = None # 当前数据指针
if dur == 0:
serials = [_get_obj(self._data, ["ticks", symbol_list[0]])]
else:
serials = [_get_obj(self._data, ["klines", s, str(dur)]) for s in symbol_list]
async with TqChan(self._api, last_only=True) as update_chan:
for serial in serials:
serial["_listener"].add(update_chan)
chart_a["_listener"].add(update_chan)
chart_b["_listener"].add(update_chan)
await self._md_send_chan.send(chart_info.copy())
try:
async for _ in update_chan:
chart = _get_obj(self._data, ["charts", chart_info["chart_id"]])
if not (chart_info.items() <= _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)
if (left_id == -1 and right_id == -1) or chart.get("more_data", True):
continue # 定位信息还没收到, 数据没有完全收到
last_id = serials[0].get("last_id", -1)
if last_id == -1:
continue # 数据序列还没收到
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)
# 发送下一段 chart 8964 根 kline
chart_info["chart_id"] = chart_id_b if chart_info["chart_id"] == chart_id_a else chart_id_a
chart_info["left_kline_id"] = right_id
chart_info.pop("focus_datetime", None)
chart_info.pop("focus_position", None)
await self._md_send_chan.send(chart_info.copy())
while True:
if current_id > last_id:
# 当前 id 已超过 last_id
return
# 将订阅的8964长度的窗口中的数据都遍历完后，退出循环，然后再次进入并处理下一窗口数据
if current_id > right_id:
break
item = {k: v for k, v in serials[0]["data"].get(str(current_id), {}).items()}
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:
timestamp = item["datetime"] if dur < 86400000000000 else _get_trading_day_start_time(
item["datetime"])
if timestamp > self._end_dt: # 超过结束时间
return
binding = serials[0].get("binding", {})
diff = {
"klines": {
symbol_list[0]: {
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"],
}
}
}
}
}
}
for chart_id in self._serials[(ins, dur)]["chart_id_set"]:
diff["charts"] = {
chart_id: {
"right_id": current_id # api 中处理多合约 kline 需要 right_id 信息
}
}
for i, symbol in enumerate(symbol_list):
if i == 0:
diff_binding = diff["klines"][symbol_list[0]][str(dur)].setdefault("binding", {})
continue
other_id = binding.get(symbol, {}).get(str(current_id), -1)
if other_id >= 0:
diff_binding[symbol] = {str(current_id): str(other_id)}
other_item = serials[i]["data"].get(str(other_id), {})
diff["klines"][symbol] = {
str(dur): {
"last_id": other_id,
"data": {
str(other_id): {
"datetime": other_item["datetime"],
"open": other_item["open"],
"high": other_item["open"],
"low": other_item["open"],
"close": other_item["open"],
"volume": 0,
"open_oi": other_item["open_oi"],
"close_oi": other_item["open_oi"],
}
}
}
}
yield timestamp, diff, self._get_quotes_from_kline_open(
self._data["quotes"][symbol_list[0]],
timestamp,
item) # K线刚生成时的数据都为开盘价
timestamp = item["datetime"] + dur - 1000 \
if dur < 86400000000000 else _get_trading_day_start_time(item["datetime"] + dur) - 1000
if timestamp > self._end_dt: # 超过结束时间
return
diff = {
"klines": {
symbol_list[0]: {
str(dur): {
"data": {
str(current_id): item,
}
}
}
}
}
for i, symbol in enumerate(symbol_list):
if i == 0:
continue
other_id = binding.get(symbol, {}).get(str(current_id), -1)
if other_id >= 0:
diff["klines"][symbol] = {
str(dur): {
"data": {
str(other_id): {k: v for k, v in
serials[i]["data"].get(str(other_id), {}).items()}
}
}
}
yield timestamp, diff, self._get_quotes_from_kline(self._data["quotes"][symbol_list[0]],
timestamp,
item) # K线结束时生成quote数据
current_id += 1
finally:
# 释放chart资源
chart_info["ins_list"] = ""
await self._md_send_chan.send(chart_info.copy())
chart_info["chart_id"] = chart_id_b if chart_info["chart_id"] == chart_id_a else chart_id_a
await self._md_send_chan.send(chart_info.copy())
def __init__(self,
api: TqApi,
symbol_list: Union[str, List[str]],
dur_sec: int,
start_dt: Union[date, datetime],
end_dt: Union[date, datetime],
csv_file_name: str,
adj_type: Union[str, None] = None) -> None:
"""
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
adj_type (str/None): 复权计算方式，默认值为 None。"F" 为前复权；"B" 为后复权；None 表示不复权。只对股票、基金合约有效。
Example::
from datetime import datetime, date
from contextlib import closing
from tqsdk import TqApi, TqAuth, TqSim
from tqsdk.tools import DataDownloader
api = TqApi(auth=TqAuth("信易账户", "账户密码"))
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 not self._api._auth._has_feature("tq_dl"):
raise Exception(
"您的账户不支持下载历史数据功能，需要购买专业版本后使用。升级网址：https://account.shinnytech.com"
)
if isinstance(start_dt, datetime):
self._start_dt_nano = int(start_dt.timestamp() * 1e9)
else:
self._start_dt_nano = _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 = _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]
# 下载合约超时时间（默认 30s），已下市的没有交易的合约，超时时间可以设置短一点（2s），用户不希望自己的程序因为没有下载到数据而中断
self._timeout_seconds = 2 if any(
[symbol in DEAD_INS for symbol in self._symbol_list]) else 30
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")
if adj_type not in [None, "F", "B", "FORWARD", "BACK"]:
raise Exception(
"adj_type 参数只支持 None (不复权) ｜ 'F' (前复权) ｜ 'B' (后复权)")
self._adj_type = adj_type[0] if adj_type else adj_type
self._csv_file_name = csv_file_name
self._csv_header = self._get_headers()
self._dividend_cache = {} # 缓存合约对应的复权系数矩阵，每个合约只计算一次
self._data_series = None
self._task = self._api.create_task(self._run())
