class Algo(Broker):
"""Algo class initilizer (sub-class of Broker)
:Parameters:
instruments : list
List of IB contract tuples
resolution : str
Desired bar resolution (using pandas resolution: 1T, 1H, etc). Use K for tick bars.
tick_window : int
Length of tick lookback window to keep. Defaults to 1
bar_window : int
Length of bar lookback window to keep. Defaults to 100
timezone : str
Convert IB timestamps to this timezone (eg. US/Central). Defaults to UTC
preload : str
Preload history when starting algo (using pandas resolution: 1H, 1D, etc). Use K for tick bars.
continuous : bool
Tells preloader to construct continuous Futures contracts (default is True)
blotter : str
Log trades to MySQL server used by this Blotter (default is "auto detect")
force_resolution : bool
Force new bar on every ``resolution`` even if no new ticks received (default is False)
"""
__metaclass__ = ABCMeta
def __init__(self, instruments, resolution,
tick_window=1, bar_window=100, timezone="UTC", preload=None,
continuous=True, blotter=None, force_resolution=False, **kwargs):
self.name = str(self.__class__).split('.')[-1].split("'")[0]
# ----------------------------------------------------
# default args
self.args = kwargs.copy()
cli_args = self.load_cli_args()
# override kwargs args with cli args
for arg in cli_args:
if arg not in self.args or ( arg in self.args and cli_args[arg] is not None ):
self.args[arg] = cli_args[arg]
# fix flag args (no value)
for arg in ["backtest"]:
if arg in kwargs and "--"+str(arg) not in sys.argv:
self.args[arg] = kwargs["backtest"]
# ----------------------------------------------------
# assign algo params
self.bars = pd.DataFrame()
self.ticks = pd.DataFrame()
self.quotes = {}
self.books = {}
self.tick_count = 0
self.tick_bar_count = 0
self.bar_count = 0
self.bar_hash = 0
self.tick_window = tick_window if tick_window > 0 else 1
if "V" in resolution:
self.tick_window = 1000
self.bar_window = bar_window if bar_window > 0 else 100
self.resolution = resolution.replace("MIN", "T")
self.timezone = timezone
self.preload = preload
self.continuous = continuous
self.backtest = self.args["backtest"]
self.backtest_start = self.args["start"]
self.backtest_end = self.args["end"]
# -----------------------------------
self.sms_numbers = [] if self.args["sms"] is None else self.args["sms"]
self.trade_log_dir = self.args["log"]
self.blotter_name = self.args["blotter"] if self.args["blotter"] is not None else blotter
self.record_output = self.args["output"]
# -----------------------------------
# load blotter settings && initilize Blotter
self.load_blotter_args(self.args["blotter"])
self.blotter = Blotter(**self.blotter_args)
# -----------------------------------
# initiate broker/order manager
super().__init__(instruments, ibclient=int(self.args["ibclient"]),
ibport=int(self.args["ibport"]), ibserver=str(self.args["ibserver"]))
# -----------------------------------
# signal collector
self.signals = {}
for sym in self.symbols:
self.signals[sym] = pd.DataFrame()
# -----------------------------------
# initilize output file
self.record_ts = None
if self.record_output:
self.datastore = tools.DataStore(self.args["output"])
# -----------------------------------
# initiate strategy
self.on_start()
# ---------------------------------------
# add stale ticks to allow for interval-based bars
if force_resolution and self.resolution[-1] not in ("K", "V"):
self.bar_timer = tools.RecurringTask(
self.add_stale_tick, interval_sec=1, init_sec=1, daemon=True)
# ---------------------------------------
def add_stale_tick(self):
if len(self.ticks) > 0:
tick = self.ticks[-1:].to_dict(orient='records')[0]
tick['timestamp'] = datetime.utcnow()
tick = pd.DataFrame(index=[0], data=tick)
tick.set_index('timestamp', inplace=True)
tick = tools.set_timezone(tick, tz=self.timezone)
self._tick_handler(tick, stale_tick=True)
# ---------------------------------------
def load_cli_args(self):
parser = argparse.ArgumentParser(description='QTPy Algo Framework')
parser.add_argument('--ibport', default='4001', help='IB TWS/GW Port to use (default: 4001)', required=False)
parser.add_argument('--ibclient', default='998', help='IB TWS/GW Client ID (default: 998)', required=False)
parser.add_argument('--ibserver', default='localhost', help='IB TWS/GW Server hostname (default: localhost)', required=False)
parser.add_argument('--sms', nargs='+', help='Numbers to text orders', required=False)
parser.add_argument('--log', default=None, help='Path to store trade data (default: ~/qpy/trades/)', required=False)
parser.add_argument('--backtest', help='Work in Backtest mode', action='store_true', required=False)
parser.add_argument('--start', help='Backtest start date', required=False)
parser.add_argument('--end', help='Backtest end date', required=False)
parser.add_argument('--output', help='Path to save the recorded data', required=False)
parser.add_argument('--blotter', help='Log trades to the MySQL server used by this Blotter', required=False)
args, unknown = parser.parse_known_args()
return args.__dict__
# ---------------------------------------
def run(self):
"""Starts the algo
Connects to the Blotter, processes market data and passes
tick data to the ``on_tick`` function and bar data to the
``on_bar`` methods.
"""
# -----------------------------------
# backtest mode?
if self.backtest:
if self.record_output is None:
logging.error("Must provide an output file for Backtest mode")
sys.exit(0)
if self.backtest_start is None:
logging.error("Must provide start date for Backtest mode")
sys.exit(0)
if self.backtest_end is None:
self.backtest_end = datetime.now().strftime('%Y-%m-%d %H:%M:%S.%f')
# backtest history
self.blotter.drip(
symbols = self.symbols,
start = self.backtest_start,
end = self.backtest_end,
resolution = self.resolution,
tz = self.timezone,
continuous = self.continuous,
quote_handler = self._quote_handler,
tick_handler = self._tick_handler,
bar_handler = self._bar_handler,
book_handler = self._book_handler
)
# -----------------------------------
# live data mode
else:
# preload history
if self.preload is not None:
try: # dbskip may be active
self.bars = self.blotter.history(
symbols = self.symbols,
start = tools.backdate(self.preload),
resolution = self.resolution,
tz = self.timezone,
continuous = self.continuous
)
except:
pass
# print(self.bars)
# add instruments to blotter in case they do not exist
self.blotter.register(self.instruments)
# listen for RT data
self.blotter.listen(
symbols = self.symbols,
tz = self.timezone,
quote_handler = self._quote_handler,
tick_handler = self._tick_handler,
bar_handler = self._bar_handler,
book_handler = self._book_handler
)
# ---------------------------------------
@abstractmethod
def on_start(self):
"""
Invoked once when algo starts. Used for when the strategy
needs to initialize parameters upon starting.
"""
# raise NotImplementedError("Should implement on_start()")
pass
# ---------------------------------------
@abstractmethod
def on_quote(self, instrument):
"""
Invoked on every quote captured for the selected instrument.
This is where you'll write your strategy logic for quote events.
:Parameters:
symbol : string
`Instruments Object <#instrument-api>`_
"""
# raise NotImplementedError("Should implement on_quote()")
pass
# ---------------------------------------
@abstractmethod
def on_tick(self, instrument):
"""
Invoked on every tick captured for the selected instrument.
This is where you'll write your strategy logic for tick events.
:Parameters:
symbol : string
`Instruments Object <#instrument-api>`_
"""
# raise NotImplementedError("Should implement on_tick()")
pass
# ---------------------------------------
@abstractmethod
def on_bar(self, instrument):
"""
Invoked on every tick captured for the selected instrument.
This is where you'll write your strategy logic for tick events.
:Parameters:
instrument : object
`Instruments Object <#instrument-api>`_
"""
# raise NotImplementedError("Should implement on_bar()")
pass
# ---------------------------------------
@abstractmethod
def on_orderbook(self, instrument):
"""
Invoked on every change to the orderbook for the selected instrument.
This is where you'll write your strategy logic for orderbook changes events.
:Parameters:
symbol : string
`Instruments Object <#instrument-api>`_
"""
# raise NotImplementedError("Should implement on_orderbook()")
pass
# ---------------------------------------
@abstractmethod
def on_fill(self, instrument, order):
"""
Invoked on every order fill for the selected instrument.
This is where you'll write your strategy logic for fill events.
:Parameters:
instrument : object
`Instruments Object <#instrument-api>`_
order : object
Filled order data
"""
# raise NotImplementedError("Should implement on_fill()")
pass
# ---------------------------------------
def get_instrument(self, symbol):
"""
A string subclass that provides easy access to misc
symbol-related methods and information using shorthand.
Refer to the `Instruments API <#instrument-api>`_
for available methods and properties
Call from within your strategy:
``instrument = self.get_instrument("SYMBOL")``
:Parameters:
symbol : string
instrument symbol
"""
instrument = Instrument(self._getsymbol_(symbol))
instrument._set_parent(self)
return instrument
# ---------------------------------------
def get_history(self, symbols, start, end=None, resolution="1T", tz="UTC"):
"""Get historical market data.
Connects to Blotter and gets historical data from storage
:Parameters:
symbols : list
List of symbols to fetch history for
start : datetime / string
History time period start date (datetime or YYYY-MM-DD[ HH:MM[:SS]] string)
:Optional:
end : datetime / string
History time period end date (datetime or YYYY-MM-DD[ HH:MM[:SS]] string)
resolution : string
History resoluton (Pandas resample, defaults to 1T/1min)
tz : string
History timezone (defaults to UTC)
:Returns:
history : pd.DataFrame
Pandas DataFrame object with historical data for all symbols
"""
return self.blotter.history(symbols, start, end, resolution, tz)
# ---------------------------------------
# shortcuts to broker._create_order
# ---------------------------------------
def order(self, signal, symbol, quantity=0, **kwargs):
""" Send an order for the selected instrument
:Parameters:
direction : string
Order Type (BUY/SELL, EXIT/FLATTEN)
symbol : string
instrument symbol
quantity : int
Order quantiry
:Optional:
limit_price : float
In case of a LIMIT order, this is the LIMIT PRICE
expiry : int
Cancel this order if not filled after *n* seconds (default 60 seconds)
order_type : string
Type of order: Market (default), LIMIT (default when limit_price is passed), MODIFY (required passing or orderId)
orderId : int
If modifying an order, the order id of the modified order
target : float
target (exit) price
initial_stop : float
price to set hard stop
stop_limit: bool
Flag to indicate if the stop should be STOP or STOP LIMIT (default False=STOP)
trail_stop_at : float
price at which to start trailing the stop
trail_stop_by : float
% of trailing stop distance from current price
fillorkill: bool
fill entire quantiry or none at all
iceberg: bool
is this an iceberg (hidden) order
tif: str
time in force (DAY, GTC, IOC, GTD). default is ``DAY``
"""
if signal.upper() == "EXIT" or signal.upper() == "FLATTEN":
position = self.get_positions(symbol)
if position['position'] == 0:
return
kwargs['symbol'] = symbol
kwargs['quantity'] = abs(position['position'])
kwargs['direction'] = "BUY" if position['position'] < 0 else "SELL"
# print("EXIT", kwargs)
try: self.record(position=0)
except: pass
if not self.backtest:
self._create_order(**kwargs)
else:
if quantity == 0:
return
kwargs['symbol'] = symbol
kwargs['quantity'] = abs(quantity)
kwargs['direction'] = signal.upper()
# print(signal.upper(), kwargs)
# record
try:
quantity = -quantity if kwargs['direction'] == "BUY" else quantity
self.record(position=quantity)
except:
pass
if not self.backtest:
self._create_order(**kwargs)
# ---------------------------------------
def cancel_order(self, orderId):
""" Cancels a un-filled order
Parameters:
orderId : int
Order ID
"""
self._cancel_order(orderId)
# ---------------------------------------
def record(self, *args, **kwargs):
"""Records data for later analysis.
Values will be logged to the file specified via
``--output [file]`` (along with bar data) as
csv/pickle/h5 file.
Call from within your strategy:
``self.record(key=value)``
:Parameters:
** kwargs : mixed
The names and values to record
"""
if self.record_output:
try: self.datastore.record(self.record_ts, *args, **kwargs)
except: pass
# ---------------------------------------
def sms(self, text):
"""Sends an SMS message.
Relies on properly setting up an SMS provider (refer to the
SMS section of the documentation for more information about this)
Call from within your strategy:
``self.sms("message text")``
:Parameters:
text : string
The body of the SMS message to send
"""
logging.info("SMS: "+str(text))
sms.send_text(self.name +': '+ str(text), self.sms_numbers)
# ---------------------------------------
def _caller(self, caller):
stack = [x[3] for x in inspect.stack()][1:-1]
return caller in stack
# ---------------------------------------
def _book_handler(self, book):
symbol = book['symbol']
del book['symbol']
del book['kind']
self.books[symbol] = book
self.on_orderbook(self.get_instrument(symbol))
# ---------------------------------------
def _quote_handler(self, quote):
del quote['kind']
self.quotes[quote['symbol']] = quote
self.on_quote(self.get_instrument(quote))
# ---------------------------------------
def _tick_handler(self, tick, stale_tick=False):
self._cancel_expired_pending_orders()
# initial value
if self.record_ts is None:
self.record_ts = tick.index[0]
if self.resolution[-1] not in ("S", "K", "V"):
self.ticks = self._update_window(self.ticks, tick, window=self.tick_window)
else:
self.ticks = self._update_window(self.ticks, tick)
bars = tools.resample(self.ticks, self.resolution)
if len(bars.index) > self.tick_bar_count > 0 or stale_tick:
self.record_ts = tick.index[0]
self._bar_handler(bars)
periods = int("".join([s for s in self.resolution if s.isdigit()]))
self.ticks = self.ticks[-periods:]
self.tick_bar_count = len(bars)
# record tick bars
self.record(bars[-1:])
if not stale_tick:
self.on_tick(self.get_instrument(tick))
# ---------------------------------------
def _bar_handler(self, bar):
is_tick_or_volume_bar = False
handle_bar = True
if self.resolution[-1] in ("S", "K", "V"):
is_tick_or_volume_bar = True
handle_bar = self._caller("_tick_handler")
# drip is also ok
handle_bar = handle_bar or self._caller("drip")
if is_tick_or_volume_bar:
# just add a bar (used by tick bar bandler)
self.bars = self._update_window(self.bars, bar, window=self.bar_window)
else:
# add the bar and resample to resolution
self.bars = self._update_window(self.bars, bar, window=self.bar_window, resolution=self.resolution)
# new bar?
this_bar_hash = abs(hash(str(self.bars.index.values[-1]))) % (10 ** 8)
newbar = (self.bar_hash != this_bar_hash)
self.bar_hash = this_bar_hash
if newbar and handle_bar:
self.record_ts = bar.index[0]
self.on_bar(self.get_instrument(bar))
if self.resolution[-1] not in ("S", "K", "V"):
self.record(bar)
# ---------------------------------------
def _update_window(self, df, data, window=None, resolution=None):
if df is None:
df = data
else:
df = df.append(data)
if resolution is not None:
try:
tz = str(df.index.tz)
except:
tz = None
df = tools.resample(df, resolution=resolution, tz=tz)
if window is None:
return df
return df[-window:]
# ---------------------------------------
# signal logging methods
# ---------------------------------------
def _add_signal_history(self, df, symbol):
""" Initilize signal history """
if symbol not in self.signals.keys() or len(self.signals[symbol]) == 0:
self.signals[symbol] = [nan]*len(df)
else:
self.signals[symbol].append(nan)
self.signals[symbol] = self.signals[symbol][-len(df):]
df.loc[-len(self.signals[symbol]):, 'signal'] = self.signals[symbol]
return df
def _log_signal(self, symbol, signal):
""" Log signal
:Parameters:
symbol : string
instruments symbol
signal : integer
signal identifier (1, 0, -1)
"""
self.signals[symbol][-1] = signal
class Algo(Broker):
"""Algo class initilizer (sub-class of Broker)
:Parameters:
instruments : list
List of IB contract tuples
resolution : str
Desired bar resolution (using pandas resolution: 1T, 1H, etc). Use K for tick bars.
tick_window : int
Length of tick lookback window to keep. Defaults to 1
bar_window : int
Length of bar lookback window to keep. Defaults to 100
timezone : str
Convert IB timestamps to this timezone (eg. US/Central). Defaults to UTC
preload : str
Preload history when starting algo (using pandas resolution: 1H, 1D, etc). Use K for tick bars.
blotter : str
Log trades to MySQL server used by this Blotter (default is "auto detect")
"""
__metaclass__ = ABCMeta
def __init__(self, instruments, resolution, \
tick_window=1, bar_window=100, timezone="UTC", preload=None, \
blotter=None, **kwargs):
self.name = str(self.__class__).split('.')[-1].split("'")[0]
# assign algo params
self.bars = pd.DataFrame()
self.ticks = pd.DataFrame()
self.quotes = {}
self.tick_count = 0
self.tick_bar_count = 0
self.bar_count = 0
self.bar_hash = 0
self.tick_window = tick_window if tick_window > 0 else 1
self.bar_window = bar_window if bar_window > 0 else 100
self.resolution = resolution.replace("MIN", "T")
self.timezone = timezone
self.preload = preload
self.backtest = args.backtest
self.backtest_start = args.start
self.backtest_end = args.end
# -----------------------------------
self.sms_numbers = [] if args.sms is None else args.sms
self.trade_log_dir = args.log
self.blotter_name = args.blotter if args.blotter is not None else blotter
self.record_output = args.output
# -----------------------------------
# load blotter settings && initilize Blotter
self.load_blotter_args(args.blotter)
self.blotter = Blotter(**self.blotter_args)
# -----------------------------------
# initiate broker/order manager
super().__init__(instruments, ibclient=int(args.ibclient), \
ibport=int(args.ibport), ibserver=str(args.ibserver))
# -----------------------------------
# signal collector
self.signals = {}
for sym in self.symbols:
self.signals[sym] = pd.DataFrame()
# -----------------------------------
# initilize output file
self.record_ts = None
if self.record_output:
self.datastore = tools.DataStore(args.output)
# -----------------------------------
# initiate strategy
self.on_start()
# ---------------------------------------
def run(self):
"""Starts the algo
Connects to the Blotter, processes market data and passes
tick data to the ``on_tick`` function and bar data to the
``on_bar`` methods.
"""
# -----------------------------------
# backtest mode?
if self.backtest:
if self.output is None:
print(
"ERROR: Must provide an output file for backtesting mode")
sys.exit(0)
if self.backtest_start is None:
print("ERROR: Must provide start date for backtesting mode")
sys.exit(0)
if self.backtest_end is None:
self.backtest_end = datetime.now().strftime(
'%Y-%m-%d %H:%M:%S.%f')
# backtest history
self.blotter.drip(symbols=self.symbols,
start=self.backtest_start,
end=self.backtest_end,
resolution=self.resolution,
tz=self.timezone,
quote_handler=self._quote_handler,
tick_handler=self._tick_handler,
bar_handler=self._bar_handler)
# -----------------------------------
# live data mode
else:
# preload history
if self.preload is not None:
try: # dbskip may be active
self.bars = self.blotter.history(
symbols=self.symbols,
start=tools.backdate(self.preload),
resolution=self.resolution,
tz=self.timezone)
except:
pass
# print(self.bars)
# add instruments to blotter in case they do not exist
self.blotter.register(self.instruments)
# listen for RT data
self.blotter.listen(symbols=self.symbols,
tz=self.timezone,
quote_handler=self._quote_handler,
tick_handler=self._tick_handler,
bar_handler=self._bar_handler)
# ---------------------------------------
@abstractmethod
def on_start(self):
"""
Invoked once when algo starts. Used for when the strategy
needs to initialize parameters upon starting.
"""
# raise NotImplementedError("Should implement on_start()")
pass
# ---------------------------------------
@abstractmethod
def on_quote(self, instrument):
"""
Invoked on every quote captured for the selected instrument.
This is where you'll write your strategy logic for quote events.
:Parameters:
symbol : string
`Instruments Object <#instrument-api>`_
"""
# raise NotImplementedError("Should implement on_quote()")
pass
# ---------------------------------------
@abstractmethod
def on_tick(self, instrument):
"""
Invoked on every tick captured for the selected instrument.
This is where you'll write your strategy logic for tick events.
:Parameters:
symbol : string
`Instruments Object <#instrument-api>`_
"""
# raise NotImplementedError("Should implement on_tick()")
pass
# ---------------------------------------
@abstractmethod
def on_bar(self, instrument):
"""
Invoked on every tick captured for the selected instrument.
This is where you'll write your strategy logic for tick events.
:Parameters:
instrument : object
`Instruments Object <#instrument-api>`_
"""
# raise NotImplementedError("Should implement on_bar()")
pass
# ---------------------------------------
@abstractmethod
def on_fill(self, instrument, order):
"""
Invoked on every order fill for the selected instrument.
This is where you'll write your strategy logic for fill events.
:Parameters:
instrument : object
`Instruments Object <#instrument-api>`_
order : object
Filled order data
"""
# raise NotImplementedError("Should implement on_fill()")
pass
# ---------------------------------------
def get_instrument(self, symbol):
"""
A string subclass that provides easy access to misc
symbol-related methods and information using shorthand.
Refer to the `Instruments API <#instrument-api>`_
for available methods and properties
Call from within your strategy:
``instrument = self.get_instrument("SYMBOL")``
:Parameters:
symbol : string
instrument symbol
"""
instrument = Instrument(self._getsymbol_(symbol))
instrument._set_parent(self)
return instrument
# ---------------------------------------
def get_history(self, symbols, start, end=None, resolution="1T", tz="UTC"):
"""Get historical market data.
Connects to Blotter and gets historical data from storage
:Parameters:
symbols : list
List of symbols to fetch history for
start : datetime / string
History time period start date (datetime or YYYY-MM-DD[ HH:MM[:SS]] string)
:Optional:
end : datetime / string
History time period end date (datetime or YYYY-MM-DD[ HH:MM[:SS]] string)
resolution : string
History resoluton (Pandas resample, defaults to 1T/1min)
tz : string
History timezone (defaults to UTC)
:Returns:
history : pd.DataFrame
Pandas DataFrame object with historical data for all symbols
"""
return self.blotter.history(symbols, start, end, resolution, tz)
# ---------------------------------------
# shortcuts to broker._create_order
# ---------------------------------------
def order(self, signal, symbol, quantity=0, **kwargs):
""" Send an order for the selected instrument
:Parameters:
direction : string
Order Type (BUY/SELL, EXIT/FLATTEN)
symbol : string
instrument symbol
quantity : int
Order quantiry
:Optional:
limit_price : float
In case of a LIMIT order, this is the LIMIT PRICE
expiry : int
Cancel this order if not filled after *n* seconds (default 60 seconds)
order_type : string
Type of order: Market (default), LIMIT (default when limit_price is passed), MODIFY (required passing or orderId)
orderId : int
If modifying an order, the order id of the modified order
target : float
target (exit) price
initial_stop : float
price to set hard stop
trail_stop_at : float
price at which to start trailing the stop
trail_stop_by : float
% of trailing stop distance from current price
ticksize : float
If using traling stop, pass the tick size for the instruments so you won't try to buy ES at 2200.128230 :)
fillorkill: bool
fill entire quantiry or none at all
iceberg: bool
is this an iceberg (hidden) order
"""
if signal.upper() == "EXIT" or signal.upper() == "FLATTEN":
position = self.get_positions(symbol)
if position['position'] == 0:
return
kwargs['symbol'] = symbol
kwargs['quantity'] = abs(position['position'])
kwargs['direction'] = "BUY" if position['position'] < 0 else "SELL"
# print("EXIT", kwargs)
try:
self.record(position=0)
except:
pass
if not self.backtest:
self._create_order(**kwargs)
else:
if quantity == 0:
return
kwargs['symbol'] = symbol
kwargs['quantity'] = abs(quantity)
kwargs['direction'] = signal.upper()
# print(signal.upper(), kwargs)
# record
try:
quantity = -quantity if kwargs[
'direction'] == "BUY" else quantity
self.record(position=quantity)
except:
pass
if not self.backtest:
self._create_order(**kwargs)
# ---------------------------------------
def cancel_order(self, orderId):
""" Cancels a un-filled order
Parameters:
orderId : int
Order ID
"""
self._cancel_order(orderId)
# ---------------------------------------
def record(self, *args, **kwargs):
"""Records data for later analysis.
Values will be logged to the file specified via
``--output [file]`` (along with bar data) as
csv/pickle/h5 file.
Call from within your strategy:
``self.record(key=value)``
:Parameters:
** kwargs : mixed
The names and values to record
"""
if self.record_output:
self.datastore.record(self.record_ts, *args, **kwargs)
# ---------------------------------------
def sms(self, text):
"""Sends an SMS message.
Relies on properly setting up an SMS provider (refer to the
SMS section of the documentation for more information about this)
Call from within your strategy:
``self.sms("message text")``
:Parameters:
text : string
The body of the SMS message to send
"""
logging.info("SMS: " + str(text))
sms.send_text(self.name + ': ' + str(text), self.sms_numbers)
# ---------------------------------------
def _caller(self, caller):
stack = [x[3] for x in inspect.stack()][1:-1]
return caller in stack
# ---------------------------------------
def _quote_handler(self, quote):
# self._cancel_expired_pending_orders()
self.quotes[quote['symbol']] = quote
self.on_quote(self.get_instrument(quote))
# ---------------------------------------
def _tick_handler(self, tick):
self._cancel_expired_pending_orders()
if "K" not in self.resolution:
self.ticks = self._update_window(self.ticks,
tick,
window=self.tick_window)
else:
self.ticks = self._update_window(self.ticks, tick)
bar = tools.resample(self.ticks, self.resolution)
if len(bar) > self.tick_bar_count > 0:
self.record_ts = tick.index[0]
self._bar_handler(bar)
periods = int("".join(
[s for s in self.resolution if s.isdigit()]))
self.ticks = self.ticks[-periods:]
self.tick_bar_count = len(bar)
# record tick bar
self.record(bar)
self.on_tick(self.get_instrument(tick))
# ---------------------------------------
def _bar_handler(self, bar):
is_tick_bar = False
handle_bar = True
if "K" in self.resolution:
if self._caller("_tick_handler"):
is_tick_bar = True
handle_bar = True
else:
is_tick_bar = True
handle_bar = False
if is_tick_bar:
# just add a bar (used by tick bar bandler)
self.bars = self._update_window(self.bars,
bar,
window=self.bar_window)
else:
# add the bar and resample to resolution
self.bars = self._update_window(self.bars,
bar,
window=self.bar_window,
resolution=self.resolution)
# new bar?
this_bar_hash = abs(hash(str(self.bars.index.values[-1]))) % (10**8)
newbar = (self.bar_hash != this_bar_hash)
self.bar_hash = this_bar_hash
if newbar & handle_bar:
self.record_ts = bar.index[0]
self.on_bar(self.get_instrument(bar))
if "K" not in self.resolution:
self.record(bar)
# ---------------------------------------
def _update_window(self, df, data, window=None, resolution=None):
if df is None:
df = data
else:
df = df.append(data)
if resolution is not None:
try:
tz = str(df.index.tz)
except:
tz = None
df = tools.resample(df, resolution=resolution, tz=tz)
if window is None:
return df
return df[-window:]
# ---------------------------------------
# signal logging methods
# ---------------------------------------
def _add_signal_history(self, df, symbol):
""" Initilize signal history """
if symbol not in self.signals.keys() or len(self.signals[symbol]) == 0:
self.signals[symbol] = [nan] * len(df)
else:
self.signals[symbol].append(nan)
self.signals[symbol] = self.signals[symbol][-len(df):]
df.loc[-len(self.signals[symbol]):, 'signal'] = self.signals[symbol]
return df
def _log_signal(self, symbol, signal):
""" Log signal
:Parameters:
symbol : string
instruments symbol
signal : integer
signal identifier (1, 0, -1)
"""
self.signals[symbol][-1] = signal
