def get_incoming_tick_data(self, ticker): """ Stores the midpoint of incoming price data to a pandas DataFrame `df_hist`. :param ticker: The incoming tick data as a Ticker object. """ symbol = self.get_symbol(ticker.contract) dt_obj = dt_util.convert_utc_datetime(ticker.time) bid = ticker.open ask = ticker.high
def get_incoming_tick_data(self, ticker):
"""
Stores the midpoint of incoming price data to a pandas DataFrame `df_hist`.
:param ticker: The incoming tick data as a Ticker object.
"""
symbol = self.get_symbol(ticker.contract)
dt_obj = dt_util.convert_utc_datetime(ticker.time)
bid = ticker.bid
ask = ticker.ask
mid = (bid + ask) / 2
self.df_hist.loc[dt_obj, symbol] = mid
if len(self.df_hist) > 1:
print(self.df_hist.iloc[-1])
def get_incoming_tick_data(self, ticker): """ Stores the midpoint of incoming price data to a pandas DataFrame `df_hist`. :param ticker: The incoming tick data as a Ticker object. """ symbol = self.get_symbol(ticker.contract) dt_obj = dt_util.convert_utc_datetime(ticker.time) self.lastTime = dt_obj bid = ticker.bid ask = ticker.ask mid = (bid + ask) / 2 try: self.df_hist.loc[(dt_obj, symbol)] = mid except Exception as e: print(e)
def get_historical_data_backend(self):
data = pickle.load(open(self.dataDirectory, "rb" ) )
close = data.xs('CLOSE', axis = 1, level = 1)
toTrade = [x for x in self.symbols]
if self.exchange == 'ASX':
toTrade_ = [x+ '.AX' for x in self.symbols]
elif self.exchange == 'SEHK':
toTrade_ = [x+ '.HK' for x in self.symbols]
for index, tick in enumerate(toTrade_):
if len(tick)==6:
toTrade_[index] = '0'+toTrade_[index]
else:
toTrade_ = toTrade
#Fill missing (recent) data with yahoo data
price = pdr.get_data_yahoo(toTrade_)
df = price['Adj Close'].dropna()
df.columns = [self.assetA, self.assetB]
df = df[[not x for x in df.index.duplicated()]]
missingDates = df[[dx not in close.index and dx > close.index[-1] for dx in df.index ]]
#Don't include the price for today
missingDates = missingDates[missingDates.index<pd.Timestamp.today().normalize()]
# Simply to ensure that the column order is conistent
if all([x in df.columns for x in close.columns]):
close = close[toTrade_]
close.columns = toTrade
close = pd.concat([close,missingDates], sort=True).dropna()
close = close[[self.assetA, self.assetB]]
else:
close=missingDates
close = close[[self.assetA, self.assetB]]
if close is not None:
self.df_hist = close
del data
del close
self.df_hist.index = [dt_util.convert_utc_datetime(x) for x in self.df_hist.index]
else:
print('No Histocial Data.')