def main():
cerebro = bt.Cerebro(quicknotify=True)
apikey, secret = read(
'/home/rick/PycharmProjects/Btc/huobittrade/binance.txt')
broker_config = {
'apiKey': apikey,
'secret': secret,
'nonce': lambda: str(int(time.time() * 1000)),
'enableRateLimit': True,
}
store = CCXTStore(exchange='binance',
currency='BTC',
config=broker_config,
retries=5,
debug=True)
broker_mapping = {
'order_types': {
bt.Order.Market: 'market',
bt.Order.Limit: 'limit',
bt.Order.Stop:
'stop-loss', # stop-loss for kraken, stop for bitmex
bt.Order.StopLimit: 'stop limit'
},
'mappings': {
'closed_order': {
'key': 'status',
'value': 'closed'
},
'canceled_order': {
'key': 'result',
'value': 1
}
}
}
broker = store.getbroker(broker_mapping=broker_mapping)
cerebro.setbroker(broker)
hist_start_date = dt.datetime.utcnow() - dt.timedelta(minutes=2)
data = store.getdata(dataname='BTC/USDT',
name="BTC/USDT",
timeframe=bt.TimeFrame.Minutes,
fromdate=hist_start_date,
compression=30,
ohlcv_limit=99999)
cerebro.adddata(data)
cerebro.addstrategy(CustomStrategy)
initial_value = cerebro.broker.getvalue()
print('Starting Portfolio Value: %.2f' % initial_value)
result = cerebro.run()
final_value = cerebro.broker.getvalue()
print('Final Portfolio Value: %.2f' % final_value)
def connect_broker():
apikey = 'siX-NO9IeVWstmn1zA2e904N'
secret = 'ieEjNwz9TDAzg_B2EVkpgzkchDeNmyy9_UNB03B567Gwh0A_'
cerebro = bt.Cerebro(quicknotify=True)
# Add the strategy
cerebro.addstrategy(TestStrategy)
# Create our store
config = {'apiKey': apikey, 'secret': secret, 'enableRateLimit': True}
# IMPORTANT NOTE - Kraken (and some other exchanges) will not return any values
# for get cash or value if You have never held any LTC coins in your account.
# So switch LTC to a coin you have funded previously if you get errors
store = CCXTStore(exchange='bitmex',
currency='BTC',
config=config,
retries=5,
debug=False,
testnet=True)
print("I am here")
print(store.exchange.urls)
broker = store.getbroker()
cerebro.setbroker(broker)
# Get our data
# Drop newest will prevent us from loading partial data from incomplete candles
hist_start_date = datetime.utcnow() - timedelta(minutes=50)
data = store.getdata(dataname='BTC/USD',
name="BTCUSD",
timeframe=bt.TimeFrame.Minutes,
fromdate=hist_start_date,
compression=1,
ohlcv_limit=50,
drop_newest=True) #, historical=True)
# Add the feed
cerebro.adddata(data)
# Run the strategy
cerebro.run()
def main():
cerebro = bt.Cerebro(quicknotify=True)
if ENV == PRODUCTION: # Live trading with Binance
broker_config = {
'apiKey': os.environ.get('okex_key'),
'secret': os.environ.get('okex__secret'),
'nonce': lambda: str(int(time.time() * 1000)),
'enableRateLimit': True,
}
store = CCXTStore(exchange='okex',
currency='USDT',
config=broker_config,
retries=5,
debug=DEBUG)
broker_mapping = {
'order_types': {
bt.Order.Market: 'market',
bt.Order.Limit: 'limit',
bt.Order.Stop: 'stop-loss',
bt.Order.StopLimit: 'stop limit'
},
'mappings': {
'closed_order': {
'key': 'status',
'value': 'closed'
},
'canceled_order': {
'key': 'status',
'value': 'canceled'
}
}
}
okex = store.getbroker(broker_mapping=broker_mapping)
print(okex.getcash(), okex.getvalue())
#cerebro.setbroker(okex)
broker = cerebro.getbroker()
broker.setcommission(commission=0.001, name=COIN_TARGET)
broker.setcash(100000.0)
cerebro.addsizer(FullMoney)
initial_value = cerebro.broker.getvalue()
print('Starting Portfolio Value: %.2f' % initial_value)
hist_start_date = dt.datetime.utcnow() - dt.timedelta(minutes=30000)
data = store.getdata(
dataname='%s/%s' % (COIN_TARGET, COIN_REFER),
name='%s%s' % (COIN_TARGET, COIN_REFER),
timeframe=bt.TimeFrame.Minutes,
#fromdate=hist_start_date,
fromdate=dt.datetime(2018, 1, 1),
todate=dt.datetime(2018, 12, 31),
compression=15,
ohlcv_limit=None)
# Add the feed
#cerebro.adddata(data)
cerebro.resampledata(data,
timeframe=bt.TimeFrame.Minutes,
compression=30)
else: # Backtesting with CSV file
data = OneTokenDataset(
name='btc',
dataname=
"dataset/candles_okef_btc.usd.t_2018-11-11_2018-12-12_5m.csv",
timeframe=bt.TimeFrame.Minutes,
#fromdate=dt.datetime(2018, 11, 11,11,11),
#todate=dt.datetime(2018, 11, 10,11,11),
compression=5,
nullvalue=0.0,
dtformat=1,
)
cerebro.adddata(data)
#cerebro.resampledata(data, timeframe=bt.TimeFrame.Minutes, compression=5)
broker = cerebro.getbroker()
broker.setcommission(commission=0.001, name=COIN_TARGET)
broker.setcash(10000.0)
cerebro.addsizer(FullMoney)
# Analyzers to evaluate trades and strategies
# SQN = Average( profit / risk ) / StdDev( profit / risk ) x SquareRoot( number of trades )
cerebro.addanalyzer(bt.analyzers.TradeAnalyzer, _name="ta")
cerebro.addanalyzer(bt.analyzers.SQN, _name="sqn")
# Include Strategy
cerebro.addstrategy(BasicRandom)
# Print analyzers - results
initial_value = cerebro.broker.getvalue()
print('Starting Portfolio Value: %.2f' % initial_value)
#exit()
result = cerebro.run()
final_value = cerebro.broker.getvalue()
print('Final Portfolio Value: %.2f' % final_value)
print('Profit %.3f%%' %
((final_value - initial_value) / initial_value * 100))
#exit()
print_trade_analysis(result[0].analyzers.ta.get_analysis())
print_sqn(result[0].analyzers.sqn.get_analysis())
if True: #DEBUG:
cerebro.plot()
'mappings': {
'closed_order': {
'key': 'status',
'value': 'closed'
},
'canceled_order': {
'key': 'result',
'value': 1
}
}
}
broker = store.getbroker(broker_mapping=broker_mapping)
cerebro.setbroker(broker)
# Get our data
# Drop newest will prevent us from loading partial data from incomplete candles
hist_start_date = datetime.utcnow() - timedelta(minutes=50)
data = store.getdata(dataname='BNB/USDT',
name="BNBUSDT",
timeframe=bt.TimeFrame.Minutes,
fromdate=hist_start_date,
compression=1,
ohlcv_limit=50,
drop_newest=True) #, historical=True)
# Add the feed
cerebro.adddata(data)
# Run the strategy
cerebro.run()
def main():
cerebro = bt.Cerebro(quicknotify=True)
if ENV == PRODUCTION: # Live trading with Binance
broker_config = {
'apiKey': BINANCE.get("key"),
'secret': BINANCE.get("secret"),
'nonce': lambda: str(int(time.time() * 1000)),
'enableRateLimit': True,
}
store = CCXTStore(exchange='binance',
currency=COIN_REFER,
config=broker_config,
retries=5,
debug=DEBUG)
broker_mapping = {
'order_types': {
bt.Order.Market: 'market',
bt.Order.Limit: 'limit',
bt.Order.Stop: 'stop-loss',
bt.Order.StopLimit: 'stop limit'
},
'mappings': {
'closed_order': {
'key': 'status',
'value': 'closed'
},
'canceled_order': {
'key': 'status',
'value': 'canceled'
}
}
}
broker = store.getbroker(broker_mapping=broker_mapping)
cerebro.setbroker(broker)
hist_start_date = dt.datetime.utcnow() - dt.timedelta(minutes=30000)
data = store.getdata(dataname='%s/%s' % (COIN_TARGET, COIN_REFER),
name='%s%s' % (COIN_TARGET, COIN_REFER),
timeframe=bt.TimeFrame.Minutes,
fromdate=hist_start_date,
compression=30,
ohlcv_limit=99999)
# Add the feed
cerebro.adddata(data)
else: # Backtesting with CSV file
data = CustomDataset(name=COIN_TARGET,
dataname="dataset/binance_nov_18_mar_19_btc.csv",
timeframe=bt.TimeFrame.Minutes,
fromdate=dt.datetime(2018, 9, 20),
todate=dt.datetime(2019, 3, 13),
nullvalue=0.0)
cerebro.resampledata(data,
timeframe=bt.TimeFrame.Minutes,
compression=30)
broker = cerebro.getbroker()
broker.setcommission(commission=0.001,
name=COIN_TARGET) # Simulating exchange fee
broker.setcash(100000.0)
cerebro.addsizer(FullMoney)
# Analyzers to evaluate trades and strategies
# SQN = Average( profit / risk ) / StdDev( profit / risk ) x SquareRoot( number of trades )
cerebro.addanalyzer(bt.analyzers.TradeAnalyzer, _name="ta")
cerebro.addanalyzer(bt.analyzers.SQN, _name="sqn")
# Include Strategy
cerebro.addstrategy(BasicRSI)
# Starting backtrader bot
initial_value = cerebro.broker.getvalue()
print('Starting Portfolio Value: %.2f' % initial_value)
result = cerebro.run()
# Print analyzers - results
final_value = cerebro.broker.getvalue()
print('Final Portfolio Value: %.2f' % final_value)
print('Profit %.3f%%' %
((final_value - initial_value) / initial_value * 100))
print_trade_analysis(result[0].analyzers.ta.get_analysis())
print_sqn(result[0].analyzers.sqn.get_analysis())
if DEBUG:
cerebro.plot()
}
store = CCXTStore(exchange='binance',
currency='BNB',
config=config,
retries=5,
debug=False)
# Get our data
# Drop newest will prevent us from loading partial data from incomplete candles
hist_start_date = datetime.utcnow() - timedelta(days=20)
to_date = datetime.utcnow() + timedelta(minutes=3)
data = store.getdata(dataname='BNB/USDT',
name="BNBUSDT",
timeframe=bt.TimeFrame.Minutes,
fromdate=hist_start_date,
todate=to_date,
compression=5,
ohlcv_limit=1000,
debug=False) # , historical=True)
#
broker = cerebro.getbroker()
broker.setcash(1000.0)
# Add the feed
cerebro.adddata(data)
cerebro.addanalyzer(bt.analyzers.TradeAnalyzer, _name="ta")
cerebro.addanalyzer(bt.analyzers.SQN, _name="sqn")
# Run the strategy
def main(path, name, persistence_type=PersistenceType.GOOGLE_FIRESTORE):
"""
Please provide the parameter file name with a path relative to the project root.
"""
cerebro = CTCerebro(preload=False)
try:
trade_setup_persistence = PersistenceFactory.get_persistance(
persistence_type, path, name, root_path=ROOT_PATH)
trade_setup = trade_setup_persistence.get_setup()
except:
print('Please provide the parameter file name.')
sys.exit(1) # abort
cs_persistence = get_cs_persistence(trade_setup)
cerebro.broker.setcash(trade_setup['initial_cash'])
abs_param_file = os.path.join(ROOT_PATH,
'trade_setups/backtestBNBPsarSL.json')
cerebro.addstrategy(
TrailingStopLossV3,
buy_pos_size=trade_setup['buy_pos_size'],
slippage=trade_setup['slippage'],
buy_limit=trade_setup['buy_limit'],
fallback_stop_loss=trade_setup['fallback_stop_loss'],
data_status4trading=trade_setup.get('data_status4trading'),
state_iteration_index=get_candle_state_index(cs_persistence),
cs_persistence=cs_persistence,
trade_setup_persistence=trade_setup_persistence,
# state_bucket_folder=...
abs_param_file=abs_param_file)
with open(CONFIG_PATH, 'r') as f:
runtime_config = json.load(f)
store_config = {
'apiKey': runtime_config["keys"]["binance"]["apikey"],
'secret': runtime_config["keys"]["binance"]["secret"],
'enableRateLimit': True,
'nonce': lambda: str(int(time.time() * 1000)),
}
tframes = dict(ticks=bt.TimeFrame.Ticks,
microseconds=bt.TimeFrame.MicroSeconds,
seconds=bt.TimeFrame.Seconds,
minutes=bt.TimeFrame.Minutes,
daily=bt.TimeFrame.Days,
weekly=bt.TimeFrame.Weeks,
monthly=bt.TimeFrame.Months)
store = CCXTStore(exchange=trade_setup['exchange'],
currency=trade_setup['currency'],
config=store_config,
retries=5,
debug=True)
broker = store.getbroker()
cerebro.setbroker(broker)
if trade_setup.get('fromdate'):
fromdate = dt.datetime(trade_setup['fromdate']['year'],
trade_setup['fromdate']['month'],
trade_setup['fromdate']['day'],
trade_setup['fromdate']['hour'],
trade_setup['fromdate']['minute'])
else:
fromdate = None
# Get our data
# Drop newest will prevent us from loading partial data from incomplete candles
data = store.getdata(
exchange=trade_setup['exchange'],
dataname=trade_setup['symbol'],
timeframe=tframes[trade_setup['timeframe']],
fromdate=fromdate,
compression=trade_setup['compression'],
ohlcv_limit=2, # required to make calls to binance exchange work
currency=trade_setup['currency'],
config=store_config,
retries=5,
drop_newest=False,
# historical=True,
backfill_start=False,
backfill=False
# debug=True,
)
# Add the feed
cerebro.adddata(data)
# Print out the starting conditions
print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue())
# Run the strategy
cerebro.run()
# Print out the final result
print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue())