def raw_history_bars(self, instrument, frequency, start_dt=None, end_dt=None, length=None):
symbol = instrument_to_tushare(instrument)
if frequency in ["1d"]:
if start_dt and end_dt:
s_date_int = convert_date_to_int(start_dt.date())
e_date_int = convert_date_to_int(end_dt.date())
elif start_dt and length:
dates = self._dates_index(instrument)
s_date_int = convert_date_to_int(start_dt.date())
s_pos = safe_searchsorted(dates, s_date_int)
s_date_int = int(dates[s_pos])
e_date_int = int(dates[min(s_pos + length, len(dates)) - 1])
elif end_dt and length:
dates = self._dates_index(instrument)
e_date_int = convert_date_to_int(end_dt.date())
e_pos = safe_searchsorted(dates, e_date_int, side="right")
s_date_int = int(dates[max(e_pos - length, 0)])
e_date_int = int(dates[e_pos - 1])
else:
raise RuntimeError("At least two of [start_dt,end_dt,length] should be given.")
data, msg = self._api.daily(symbol, freq=frequency, adjust_mode=None,
start_date=s_date_int // 1000000,
end_date=e_date_int // 1000000)
if isinstance(data, pd.DataFrame) and data.size:
data = data[data["volume"] > 0] # TODO sikp_suspended?
return QuantOsConverter.df2np(data)
else:
if msg:
system_log.warning(msg)
return QuantOsConverter.empty()
else:
return MiniteBarDataSourceMixin.raw_history_bars(
self, instrument, frequency, start_dt=start_dt, end_dt=end_dt, length=length
)
def get_bars(self,
instrument,
frequency,
trade_date=None,
start_time=None,
end_time=None):
symbol = instrument_to_tushare(instrument)
kwargs = {}
if start_time is not None:
kwargs["start_time"] = start_time
elif end_time is not None:
kwargs["end_time"] = end_time
retry = 0
while retry < self.MAX_RETRY:
retry += 1
try:
freq = frequency[:-1] + frequency[-1].upper()
params = dict(symbol=symbol, freq=freq, trade_date=0, **kwargs)
bars, msg = self._api.bar(**params)
code = msg.split(",")[0]
if not isinstance(bars, pd.DataFrame) or code != "0":
raise QuantOsQueryError(msg)
else:
break
except QuantOsQueryError as e:
if retry <= self.MAX_RETRY:
user_system_log.warning(
"[japs] Exception occurs when call api.bar with param [%s]: %s"
% (params, e))
time.sleep(retry)
else:
raise e
return QuantOsConverter.df2np(bars)
async def _get_bars_in_day(self, instrument=None, frequency=None, trade_date=None, start_time=0, end_time=150000):
# TODO retry when net error occurs
symbol = instrument_to_tushare(instrument)
trade_date = convert_date_to_int(trade_date) // 1000000
start_time = max(start_time, 80000)
end_time = min(end_time, 160000)
return self._api.bar(symbol=symbol, freq=frequency[:-1] + frequency[-1].upper(),
trade_date=trade_date, start_time=start_time, end_time=end_time)
def get_bars(self,
instrument,
frequency,
trade_date=None,
start_time=None,
end_time=None):
symbol = instrument_to_tushare(instrument)
kwargs = {}
if start_time is not None:
kwargs["start_time"] = start_time
elif end_time is not None:
kwargs["end_time"] = end_time
bars, msg = self._api.bar(symbol=symbol,
freq=frequency[:-1] + frequency[-1].upper(),
trade_date=0,
**kwargs)
if not isinstance(bars, pd.DataFrame):
raise RuntimeError(msg)
return QuantOsConverter.df2np(bars)