def get_bar_list(df, frequency, date=None):
bar_list = []
end_time = df.ix[0].time
if date is None:
date = datetime.datetime.now()
slice_start_time = to_market_datetime(
datetime.datetime(date.year, date.month, date.day, 9, 30, 0))
while slice_start_time.strftime("%H:%M:%S") < end_time:
slice_end_time = slice_start_time + datetime.timedelta(
seconds=frequency)
ticks_slice = df.ix[(df.time < slice_end_time.strftime("%H:%M:%S")) &
(df.time >= slice_start_time.strftime("%H:%M:%S"))]
if not ticks_slice.empty:
open_ = ticks_slice.price.get_values()[-1]
high = max(ticks_slice.price)
low = min(ticks_slice.price)
close = ticks_slice.price.get_values()[0]
volume = sum(ticks_slice.volume)
amount = sum(ticks_slice.amount)
bar_list.append(
bar.BasicBar(slice_start_time, open_, high, low, close, volume,
0, frequency, amount))
else:
bar_list.append(None)
slice_start_time = slice_end_time
return bar_list
def dataframeToBar(bar_dataframe, frequency):
bars = []
for _, row in bar_dataframe.iterrows():
tmp_extra = {}
for key in row.keys():
if key not in [
'datetime', 'open', 'high', 'low', 'close', 'volume',
'amount'
]:
tmp_extra[key] = row[key]
bars.append(bar.BasicBar(row['datetime'], row['open'], row['high'], row['low'], row['close'], row['volume']\
, row['amount'], frequency, False, tmp_extra))
return bars
def build_bar(dateTime, ds):
prices = ds.getPriceDS()
volumes = ds.getVolumeDS()
amounts = ds.getAmountDS()
open_ = float(prices[0])
high = float(max(prices))
low = float(min(prices))
close = float(prices[-1])
volume = sum(int(v) for v in volumes)
amount = sum(float(a) for a in amounts)
return bar.BasicBar(dateTime, open_, high, low, close, volume, None,
Frequency.DAY, amount)
def _build_bar(self, identifier, start, end):
df = self._ticksDf[identifier]
ticks_slice = df.ix[(df.time < end.strftime("%H:%M:%S"))
& (df.time >= start.strftime("%H:%M:%S"))]
if not ticks_slice.empty:
open_ = ticks_slice.price.get_values()[0]
high = max(ticks_slice.price)
low = min(ticks_slice.price)
close = ticks_slice.price.get_values()[-1]
volume = sum(ticks_slice.volume)
amount = sum(ticks_slice.amount)
return bar.BasicBar(to_market_datetime(start), open_, high, low,
close, volume, amount, self.__frequency, {})
else:
return None
def get_futu_bar_list(df, frequency):
bar_list = []
for index, row in df.iterrows():
open_ = row.open
high = row.high
low = row.low
close = row.close
volume = row.volume
amount = row.turnover
slice_start_time = datetime.datetime.strptime(row.time_key,
'%Y-%m-%d %H:%M:%S')
#time formate.
slice_start_time = to_market_datetime(slice_start_time)
bar_list.append(
bar.BasicBar(slice_start_time, open_, high, low, close, volume, 0,
frequency, amount))
return bar_list
def on_recv_rsp(self, rsp_str):
#ret_code, content = super().on_recv_rsp(rsp_str)
ret_code, content = super(CurKlineTest, self).on_recv_rsp(rsp_str)
print(ret_code)
if ret_code != futu_open.RET_OK:
print("CurKlineTest: error, msg: %s" % content)
return futu_open.RET_ERROR, content
print("CurKline : ", content)
for index, row in content.iterrows():
open_ = row.open
high = row.high
low = row.low
close = row.close
volume = row.volume
amount = row.turnover
slice_start_time = datetime.datetime.strptime(
row.time_key, '%Y-%m-%d %H:%M:%S')
slice_start_time = to_market_datetime(slice_start_time)
identifier = row.code
k_type = row.k_type
if k_type != 'K_1M':
continue
if identifier not in self.__identifiers:
continue
if self.__last_kline_time[
identifier] is None or self.__last_kline_time[
identifier] < slice_start_time:
self.__last_kline_time[identifier] = slice_start_time
else:
#print "slice_start_time %s last_kline_time %s", (slice_start_time, slice_start_time)
continue
frequency = bar.Frequency.MINUTE
one_bar = bar.BasicBar(slice_start_time, open_, high, low, close,
volume, 0, frequency, amount)
bar_dict = {}
bar_dict[identifier] = one_bar
bars = bar.Bars(bar_dict)
self.__queue.put((FutuLiveFeed.ON_BARS, bars))