def emit(self, signal, signal_data=None): ''' Emits a signal and associated signal data if provided. For instance, signal data can help identifying between which states of a context a transition is happening. Parameters: signal : any pickable object signal_data : any pickable object See Also: :func:`nurse.state_machine.change_state` ''' try: async_connections = self._async_connections[signal] except KeyError: async_connections = [] async_connections += self._async_connections['__all__'] try: sync_connections = self._sync_connections[signal] except KeyError: sync_connections = [] sync_connections += self._sync_connections['__all__'] # batch active slots : # done in 2 passes to avoid domino effect if some observers # is_receiving_events status change after a first observer # receive a signal. connections = [(receiver, slot) \ for (receiver, slot) in sync_connections if receiver.is_receiving_events()] for (receiver, slot) in connections: event = SignalEvent(self, receiver, slot, signal, signal_data) event.start() connections = [(receiver, slot) \ for (receiver, slot) in async_connections if receiver.is_receiving_events()] from config import Config # FIXME : move somewhere else event_loop = Config.get_event_loop() for (receiver, slot) in connections: event = SignalEvent(self, receiver, slot, signal, signal_data) event_loop.add_event(event)
def close_all_positions(self, data):
"""Closes all open positions without any checks."""
datestamp = dt.datetime.strptime(data[0]['Time'], '%d-%m-%Y %H:%M:%S')
# close active buy
if self.active_long:
signal = SignalEvent(self.symbol, datestamp, 'EXIT', 'SELL')
self.event_queue.put(signal)
self.active_long = False
# close active sell
elif self.active_short:
signal = SignalEvent(self.symbol, datestamp, 'EXIT', 'BUY')
self.event_queue.put(signal)
self.active_short = False
def check_for_tp(self, data):
"""Checks to see if position take profit hit."""
datestamp = dt.datetime.strptime(data[0]['Time'], '%d-%m-%Y %H:%M:%S')
# active buy take profit conditions
if self.active_long & (data[0]['High'] >= self.vwap):
signal = SignalEvent(self.symbol, datestamp, 'EXIT', 'SELL')
self.event_queue.put(signal)
self.active_long = False
# active sell take profit conditions
elif self.active_short & (data[0]['Low'] <= self.vwap):
signal = SignalEvent(self.symbol, datestamp, 'EXIT', 'BUY')
self.event_queue.put(signal)
self.active_short = False
def calculate_signals(self, event):
if isinstance(event, MarketEvent):
for symbol in self.symbol_list:
data = self.data.get_latest_data(symbol)[0]
if data is not None and len(data) > 0:
signal = SignalEvent(symbol, data[1], 'LONG')
self.event_queue.put(signal)
self.bought[symbol] = True
def check_for_sl(self, position, data):
"""Checks to see if position stop loss hit."""
datestamp = dt.datetime.strptime(data[0]['Time'], '%d-%m-%Y %H:%M:%S')
buy_sl = position['Open Price'] - 0.0020 # fixed 20 pip sl
sell_sl = position['Open Price'] + 0.0020 # fixed 20 pip sl
# active buy stop loss conditions
if self.active_long & (data[0]['Low'] <= buy_sl):
signal = SignalEvent(self.symbol, datestamp, 'EXIT', 'SELL')
self.event_queue.put(signal)
self.active_long = False
# active sell stop loss conditions
elif self.active_short & (data[0]['High'] >= sell_sl):
signal = SignalEvent(self.symbol, datestamp, 'EXIT', 'BUY')
self.event_queue.put(signal)
self.active_short = False
def check_for_open(self, data):
"""Checks to see if a position should be opened."""
datestamp = dt.datetime.strptime(data[0]['Time'], '%d-%m-%Y %H:%M:%S')
lb = self.vwap - 0.00300
ub = self.vwap + 0.00300
if not self.active_long and not self.active_short:
# open buy conditions
if (self.bars_under_lb() < 1) & (data[0]['Low'] <= lb):
signal = SignalEvent(self.symbol, datestamp, 'LONG', 'BUY')
self.event_queue.put(signal)
self.active_long = True
# open sell conditions
elif (self.bars_over_ub() < 1) & (data[0]['High'] >= ub):
signal = SignalEvent(self.symbol, datestamp, 'SHORT', 'SELL')
self.event_queue.put(signal)
self.active_short = True
def calculate_signals(self, event):
#Generate a single LONG signal per symbol when the first marketevent occurs
if isinstance(event, MarketEvent):
for s in self.symbol_list:
data = self.data.get_latest_data(s)
if data is not None and len(data)>0:
if self.bought[s] == False:
signal = SignalEvent(s, data[0][1], #datetime
'LONG')
self.event_queue.put(signal)
self.bought[s] = True
def calculateSignal(self, dataHandler):
if self.mean == None:
return
XELp = dataHandler.getLatestValue(self, "XEL", "Adj Close")
CMSp = dataHandler.getLatestValue(self, "CMS", "Adj Close")
res = CMSp - self.beta * XELp
date = dataHandler.getDate()
if res > self.band1:
signal = SignalEvent("XEL", date, 1, 1)
self.event.append(signal)
signal = SignalEvent("CMS", date, -1, 1)
self.event.append(signal)
elif res < self.band2:
signal = SignalEvent("XEL", date, -1, 1)
self.event.append(signal)
signal = SignalEvent("CMS", date, 1, 1)
self.event.append(signal)
def calculate_signals(self, event: MarketEvent) -> None:
"""
For the MarketEvent, updates the event queue and sets True.
For "Buy and Hold" strategy one signal per symbol is generated.
Which means that we constantly LONG the market since the init.
Args:
event: MarketEvent object per symbol.
Todo:
Understand if other events are suitable.
"""
if event.type == "MARKET":
for s in self.symbol_list:
# Get the last bar for the symbol?
bars = self.bars.get_latest_bars(s, N=1)
if bars is not None and bars != []:
if self.bought[s] == False:
# (Symbol, Datetime, Type = LONG)
signal = SignalEvent(bars[0][0], bars[0][1], 'LONG')
self.events.put(signal)
self.bought[s] = True