def __init__(self, instruments, resolution, \
tick_window=1, bar_window=100, timezone="UTC", preload=None, \
continuous=True, 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
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 = 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 __init__(self, instruments=[], resolution="1T",
tick_window=1, bar_window=100, timezone="UTC", preload=None,
continuous=True, blotter=None, sms=[], log=None, backtest=False,
start=None, end=None, data=None, output=None,
ibclient=998, ibport=4001, ibserver="localhost", **kwargs):
# detect algo name
self.name = str(self.__class__).split('.')[-1].split("'")[0]
# initilize algo logger
self.log_algo = logging.getLogger(__name__)
# initilize strategy logger
tools.createLogger(self.name)
self.log = logging.getLogger(self.name)
# override args with any (non-default) command-line args
self.args = {arg: val for arg, val in locals().items(
) if arg not in ('__class__', 'self', 'kwargs')}
self.args.update(kwargs)
self.args.update(self.load_cli_args())
# 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_hashes = {}
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.upper().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.backtest_csv = self.args["data"]
# -----------------------------------
self.sms_numbers = self.args["sms"]
self.trade_log_dir = self.args["log"]
self.blotter_name = self.args["blotter"]
self.record_output = self.args["output"]
# -----------------------------------
# initiate broker/order manager
super().__init__(instruments,
**{arg: val for arg, val in self.args.items() if arg in (
'ibport', 'ibclient', 'ibhost')})
# -----------------------------------
# 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"])
# ---------------------------------------
# add stale ticks for more accurate time--based bars
if not self.backtest and self.resolution[-1] not in ("K", "V"):
self.bar_timer = asynctools.RecurringTask(
self.add_stale_tick, interval_sec=1, init_sec=1, daemon=True)
# ---------------------------------------
# sanity checks for backtesting mode
if self.backtest:
if self.record_output is None:
self.log_algo.error("Must provide an output file for Backtest mode")
sys.exit(0)
if self.backtest_start is None:
self.log_algo.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')
if self.backtest_csv is not None:
if not os.path.exists(self.backtest_csv):
self.log_algo.error("CSV directory cannot be found (%s)" % self.backtest_csv)
sys.exit(0)
elif self.backtest_csv.endswith("/"):
self.backtest_csv = self.backtest_csv[:-1]
else:
self.backtest_start = None
self.backtest_end = None
self.backtest_csv = None
# be aware of thread count
self.threads = asynctools.multitasking.getPool(__name__)['threads']
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)