def __init__(self,
startingBalance: float,
data: list,
strategies: list,
strategyInterval: Union[str, None] = None,
symbol: str = None,
marginEnabled: bool = True,
startDate: datetime = None,
endDate: datetime = None,
precision: int = 4,
outputTrades: bool = True):
super().__init__(symbol=symbol,
precision=precision,
startingBalance=startingBalance)
self.commissionsPaid = 0
self.marginEnabled = marginEnabled
self.outputTrades: bool = outputTrades # Boolean that'll determine whether trades are outputted to file or not.
convert_all_dates_to_datetime(data)
self.data = data
self.check_data()
self.interval = self.get_interval()
self.intervalMinutes = get_interval_minutes(self.interval)
self.profit = 0
self.startTime = None
self.endTime = None
self.inLongPosition = False
self.inShortPosition = False
self.currentPeriod = None
self.minPeriod = 0
self.pastActivity = [
] # We'll add previous data here when hovering through graph in GUI.
if len(strategyInterval.split()) == 1:
strategyInterval = convert_small_interval(strategyInterval)
self.strategyInterval = self.interval if strategyInterval is None else strategyInterval
self.strategyIntervalMinutes = get_interval_minutes(
self.strategyInterval)
self.intervalGapMinutes = self.strategyIntervalMinutes - self.intervalMinutes
self.intervalGapMultiplier = self.strategyIntervalMinutes // self.intervalMinutes
if self.intervalMinutes > self.strategyIntervalMinutes:
raise RuntimeError(
"Your strategy interval can't be smaller than the data interval."
)
self.ema_dict = {}
self.rsi_dictionary = {}
set_up_strategies(self, strategies)
self.startDateIndex = self.get_start_index(startDate)
self.endDateIndex = self.get_end_index(endDate)
def __init__(self,
startingBalance: float,
data: list,
strategies: list,
strategyInterval: Union[str, None] = None,
symbol: str = None,
marginEnabled: bool = True,
startDate: datetime = None,
endDate: datetime = None,
drawdownPercentage: int = 100,
precision: int = 4,
outputTrades: bool = True,
logger: Logger = None):
super().__init__(symbol=symbol,
precision=precision,
startingBalance=startingBalance,
marginEnabled=marginEnabled)
convert_all_dates_to_datetime(data)
self.data = data
self.check_data()
self.outputTrades: bool = outputTrades # Boolean that'll determine whether trades are outputted to file or not.
self.interval = self.get_interval()
self.intervalMinutes = get_interval_minutes(self.interval)
self.pastActivity = [
] # We'll add previous data here when hovering through graph in GUI.
self.drawdownPercentageDecimal = drawdownPercentage / 100 # Percentage of loss at which bot exits backtest.
self.optimizerRows = []
self.logger = logger
if len(strategyInterval.split()) == 1:
strategyInterval = convert_small_interval(strategyInterval)
self.allStrategies = get_strategies_dictionary(
Strategy.__subclasses__())
self.strategyInterval = self.interval if strategyInterval is None else strategyInterval
self.strategyIntervalMinutes = get_interval_minutes(
self.strategyInterval)
self.intervalGapMinutes = self.strategyIntervalMinutes - self.intervalMinutes
self.intervalGapMultiplier = self.strategyIntervalMinutes // self.intervalMinutes
if self.intervalMinutes > self.strategyIntervalMinutes:
raise RuntimeError(
f"Your strategy interval ({self.strategyIntervalMinutes} minute(s)) can't be smaller "
f"than the data interval ({self.intervalMinutes} minute(s)).")
self.ema_dict = {}
self.rsi_dictionary = {}
self.setup_strategies(strategies)
self.startDateIndex = self.get_start_index(startDate)
self.endDateIndex = self.get_end_index(endDate)
Test backtester object.
"""
import os
from datetime import datetime
import pytest
from algobot.enums import LONG, SHORT, STOP, TRAILING
from algobot.helpers import convert_all_dates_to_datetime, load_from_csv
from algobot.traders.backtester import Backtester
data_path = os.path.join(os.path.dirname(__file__), 'data',
'1INCHUSDT_data_1m.csv')
test_data = load_from_csv(path=data_path, descending=False)
convert_all_dates_to_datetime(test_data)
@pytest.fixture(scope='function', name='backtester')
def get_backtester():
"""
Sets up a backtester object and returns it as a fixture.
"""
backtester = Backtester(
startingBalance=1000,
data=test_data,
strategies=[],
strategyInterval='15m',
symbol="1INCHUSDT",
marginEnabled=True,
)
