def _load_datafeed(cerebro: bt.Cerebro):
"""Load all feeds into backtrader"""
# Datas are in a subfolder of the samples. Need to find where the script is located
# because it could have been called from anywhere
modpath = os.path.dirname(os.path.abspath(sys.argv[0]))
feeds = [
f for f in listdir(DATA_FEED_PATH)
if isfile(join(DATA_FEED_PATH, f)) and DATA_SUFFIX in f
]
for feed in feeds:
data_path = os.path.join(modpath, f'{DATA_FEED_PATH}{feed}')
# Data Feed
data = bt.feeds.YahooFinanceCSVData(
dataname=data_path,
# DO NOT PASS VALUES BEFORE THIS DATE
fromdate=settings.FROM_DATE,
# DO NOT PASS VALUES AFTER THIS DATE
todate=settings.TO_DATE,
reverse=False)
cerebro.adddata(data)
print(f"Added {len(feeds)} data feeds files")
def test_simple(self):
cerebro = Cerebro()
cerebro.addstrategy(TestStrategy)
# 'apiKey' and 'secret' are skipped
config = {
'enableRateLimit': True,
'nonce': lambda: str(int(time.time() * 1000))
}
feed = CCXTFeed(
exchange='binance',
dataname='BNB/USDT',
# valid values are:
# ticks, microseconds, seconds, minutes, daily, weekly, monthly
timeframe=TimeFrame.Minutes,
fromdate=dt.datetime(2019, 1, 28, 3, 30),
todate=dt.datetime(2019, 1, 28, 10, 00),
compression=15,
ohlcv_limit=2, # required to make calls to binance exchange work
currency='BNB',
config=config,
retries=5,
# drop_newest=True,
# historical=False,
debug=True,
)
# Add the feed
cerebro.adddata(feed)
# Run the strategy
cerebro.run()
def run(symbol, prices, strategy):
# initialize the Cerebro engine
cerebro = Cerebro()
cerebro.broker.setcash(100000)
# add OHLC data feed
feed = bt.feeds.PandasData(dataname=prices)
cerebro.adddata(feed)
cerebro.addstrategy(strategy=strategy, ticker=symbol)
cerebro.run()
def run_bt_multiple():
cerebro = Cerebro()
df = get_pickle('tiingo', 'SPY')
data = PandasData(dataname=df)
cerebro.adddata(data)
cerebro.addanalyzer(Returns)
cerebro.optstrategy(StrategyFetcher, idx=[0, 1])
results = cerebro.run()
strats = [x[0] for x in results]
for i, strat in enumerate(strats):
rets = strat.analyzers.returns.get_analysis()
print('Strategy {} Name {}:\n - analyzer: {}\n'.format(
i, strat.__class__.__name__, rets))
def add_symbol(cerebro: bt.Cerebro, data_path: str, start_date: str,
end_date: str):
data = DOHLCVPData(
dataname=data_path,
headers=True,
fromdate=datetime.strptime(start_date, "%Y-%m-%d"),
todate=datetime.strptime(end_date, "%Y-%m-%d"),
reverse=False,
)
data.plotinfo.plot = False
data.plotinfo.subplot = False
data_name = data_path.split("/")[-1][:-4]
cerebro.adddata(data, name=data_name)
return data
def backtesting(config):
cerebro = Cerebro()
cerebro.addstrategy(TestStrategy)
cerebro.adddata(CCXTFeed(exchange='binance',
dataname='BNB/USDT',
timeframe=TimeFrame.Minutes,
fromdate=datetime(2019, 1, 1, 0, 0),
todate=datetime(2019, 1, 1, 0, 2),
compression=1,
ohlcv_limit=2,
currency='BNB',
config=config,
retries=5))
finished_strategies = cerebro.run()
return finished_strategies
def addPandasData(codes, cerebro: bt.Cerebro, pandas_data_type=PandasDataBase):
be = get_data_backend()
start = get_start_date()
end = get_current_date()
freq = get_current_freq()
if isinstance(codes, str):
# 统一转换成list类型
codes = [codes]
dflist = []
if hasattr(be, 'get_dataFrames'):
dflist = be.get_dataFrames(codes, start, end, freq)
# else:
# todo 调用be.get_price
# for code in codes:
# data=be.get_price(codes, start, end, freq)
# df= pd.Dataframe(data)
# dflist.append(df)
for i, data in enumerate(dflist):
pdf = pandas_data_type(dataname=data)
cerebro.adddata(pdf)
def test_std_backtest_2datas(cerebro: bt.Cerebro):
datapath = getdatadir('nvda-1999-2014.txt')
data = bt.feeds.YahooFinanceCSVData(
dataname=datapath,
fromdate=datetime.datetime(1998, 1, 1),
todate=datetime.datetime(2000, 12, 31),
reverse=False,
swapcloses=True,
)
cerebro.adddata(data)
cerebro.addstrategy(bt.strategies.MA_CrossOver)
cerebro.run()
s = backtrader_plotting.schemes.Blackly()
b = Bokeh(style='bar',
scheme=s,
output_mode=_output_mode,
merge_data_hovers=True)
figs = cerebro.plot(b)
assert len(figs) == 1
assert_num_tabs(figs, 3)
assert_num_figures(figs, 5)
if __name__ == '__main__': # Точка входа при запуске этого скрипта
cerebro = Cerebro() # Инициируем "движок" BackTrader
# Несколько временнЫх интервалов: получение большего временнОго интервала из меньшего (Resample)
symbol = 'TQBR.GAZP'
store = QKStore() # Хранилище QUIK (QUIK на локальном компьютере)
# store = QKStore(Host='<Ваш IP адрес>') # Хранилище QUIK (К QUIK на удаленном компьютере обращаемся по IP или названию)
data = store.getdata(
dataname=symbol,
timeframe=TimeFrame.Minutes,
compression=1,
fromdate=datetime(
2021, 11,
19)) # Исторические данные по самому меньшему временному интервалу
cerebro.adddata(data) # Добавляем данные из QUIK для проверки исходников
cerebro.resampledata(
data, timeframe=TimeFrame.Minutes, compression=5, boundoff=1
) # Можно добавить больший временной интервал кратный меньшему (добавляется автоматом)
data1 = store.getdata(dataname=symbol,
timeframe=TimeFrame.Minutes,
compression=5,
fromdate=datetime(2021, 11, 19))
cerebro.adddata(
data1
) # Добавляем данные из QUIK для проверки правильности работы Resample
cerebro.addstrategy(ts.PrintStatusAndBars) # Добавляем торговую систему
cerebro.run() # Запуск торговой системы
# cerebro.plot() # Рисуем график. Требуется matplotlib версии 3.2.2 (pip install matplotlib==3.2.2)
from datetime import datetime
from backtrader import Cerebro, TimeFrame
from BackTraderQuik.QKStore import QKStore # Хранилище QUIK
import Strategy as ts # Торговые системы
if __name__ == '__main__': # Точка входа при запуске этого скрипта
cerebro = Cerebro() # Инициируем "движок" BackTrader
# Несколько временнЫх интервалов, прямая загрузка
symbol = 'TQBR.GAZP'
store = QKStore(Host='192.168.1.7')
data = store.getdata(
dataname=symbol,
timeframe=TimeFrame.Minutes,
compression=1,
fromdate=datetime(2020, 1, 1)
) # Исторические данные по малому временнОму интервалу (должен идти первым)
cerebro.adddata(data) # Добавляем данные
data = store.getdata(
dataname=symbol,
timeframe=TimeFrame.Days,
fromdate=datetime(
2020, 1,
1)) # Исторические данные по большому временнОму интервалу
cerebro.adddata(data) # Добавляем данные
cerebro.addstrategy(ts.PrintStatusAndBars) # Добавляем торговую систему
cerebro.run() # Запуск торговой системы
cerebro.plot(
) # Рисуем график. Требуется matplotlib версии 3.2.2 (pip install matplotlib==3.2.2)
import os, sys, argparse
import pandas
import backtrader
from backtrader import Cerebro
from strategies.BuyAndHold import BuyAndHold
from strategies.GoldenCross import GoldenCross
cerebro = backtrader.Cerebro()
pricesData = pandas.read_csv('SPY.csv', index_col='Date', parse_dates=True)
# initializing Cerebro
cerebro = Cerebro()
cerebro.broker.setcash(100000)
feed = backtrader.feeds.PandasData(dataname=pricesData) # add data feed
cerebro.adddata(feed)
strategies = {"golden_cross": GoldenCross, "buy_hold": BuyAndHold}
parser = argparse.ArgumentParser() # parse command line arguments
parser.add_argument("strategy", help="Which strategy to run", type=str)
args = parser.parse_args()
if not args.strategy in strategies:
print("Invalid strategy, must select one of {}".format(strategies.keys()))
sys.exit()
cerebro.addstrategy(strategy=strategies[args.strategy])
cerebro.run()
cerebro.plot() # plot the chart
logging.basicConfig(level=getattr(logging, args.loglevel))
# Create a cerebro entity
cerebro = Cerebro()
# Set our desired cash start
cerebro.broker.setcash(100000.0)
# Set our sizer
cerebro.addsizer(PercentSizer, percents=90)
# Load the Kraken data
pair = args.long + args.short
datafeed = KrakenData(dataname=pair,
timeframe=getattr(TimeFrame, args.timeframe),
compression=args.compression,
refresh_period=args.refresh,
historical=args.historical,
backfill_start=not args.no_backfill)
cerebro.adddata(datafeed)
# Add the strategies to run
cerebro.addstrategy(TestStrategy)
# Run the backtest
result = cerebro.run()
# Plot the result
if args.plot:
cerebro.plot()
import datetime as dt
from backtrader import Cerebro, TimeFrame
from backtrader_binance import BinanceStore
from .strategy import RSIStrategy
if __name__ == '__main___':
cerebro = Cerebro(quicknotify=True)
store = BinanceStore(
api_key='YOUR_BINANCE_KEY',
api_secret='YOUR_BINANCE_SECRET',
coin_refer='BTC',
coin_target='USDT')
broker = store.getbroker()
cerebro.setbroker(broker)
from_date = dt.datetime.utcnow() - dt.timedelta(minutes=1261)
data = store.getdata(
dataname='BTCUSDT',
fromdate=from_date,
timeframe=TimeFrame.Minutes,
compression=60)
cerebro.addstrategy(RSIStrategy)
cerebro.adddata(data)
cerebro.run()
