def simple_backtest(config, contour, num_results):
data = load_data_test(contour)
processed = optimize.preprocess(data)
assert isinstance(processed, dict)
results = backtest(config['stake_amount'], processed, 1, True)
# results :: <class 'pandas.core.frame.DataFrame'>
assert len(results) == num_results
def simple_backtest(config, contour, num_results):
data = load_data_test(contour)
processed = optimize.preprocess(data)
assert isinstance(processed, dict)
results = backtest(config['stake_amount'], processed, 1, True)
# results :: <class 'pandas.core.frame.DataFrame'>
assert len(results) == num_results
def test_backtest(default_conf, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
exchange._API = Bittrex({'key': '', 'secret': ''})
data = optimize.load_data(None, ticker_interval=5, pairs=['BTC_ETH'])
results = backtest(default_conf['stake_amount'],
optimize.preprocess(data), 10, True)
assert not results.empty
def test_backtest(default_conf, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
exchange._API = Bittrex({'key': '', 'secret': ''})
data = optimize.load_data(None, ticker_interval=5, pairs=['BTC_ETH'])
results = backtest(default_conf['stake_amount'], optimize.preprocess(data),
10, True)
assert not results.empty
def test_backtest_1min_ticker_interval(default_conf, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
exchange._API = Bittrex({'key': '', 'secret': ''})
# Run a backtesting for an exiting 5min ticker_interval
data = optimize.load_data(None, ticker_interval=1, pairs=['BTC_UNITEST'])
results = backtest(default_conf['stake_amount'],
optimize.preprocess(data), 1, True)
assert not results.empty
def test_backtest_1min_ticker_interval(default_conf, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
exchange._API = Bittrex({'key': '', 'secret': ''})
# Run a backtesting for an exiting 5min ticker_interval
data = optimize.load_data(None, ticker_interval=1, pairs=['BTC_UNITEST'])
results = backtest(default_conf['stake_amount'], optimize.preprocess(data),
1, True)
assert not results.empty
def start(args):
# Initialize logger
logging.basicConfig(
level=args.loglevel,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
)
exchange._API = Bittrex({'key': '', 'secret': ''})
logger.info('Using config: %s ...', args.config)
config = misc.load_config(args.config)
logger.info('Using ticker_interval: %s ...', args.ticker_interval)
data = {}
pairs = config['exchange']['pair_whitelist']
if args.live:
logger.info('Downloading data for all pairs in whitelist ...')
for pair in pairs:
data[pair] = exchange.get_ticker_history(pair, args.ticker_interval)
else:
logger.info('Using local backtesting data (using whitelist in given config) ...')
data = optimize.load_data(args.datadir, pairs=pairs, ticker_interval=args.ticker_interval,
refresh_pairs=args.refresh_pairs)
logger.info('Using stake_currency: %s ...', config['stake_currency'])
logger.info('Using stake_amount: %s ...', config['stake_amount'])
max_open_trades = 0
if args.realistic_simulation:
logger.info('Using max_open_trades: %s ...', config['max_open_trades'])
max_open_trades = config['max_open_trades']
# Monkey patch config
from freqtrade import main
main._CONF = config
preprocessed = preprocess(data)
# Print timeframe
min_date, max_date = get_timeframe(preprocessed)
logger.info('Measuring data from %s up to %s ...', min_date.isoformat(), max_date.isoformat())
# Execute backtest and print results
results = backtest(
stake_amount=config['stake_amount'],
processed=preprocessed,
max_open_trades=max_open_trades,
realistic=args.realistic_simulation,
sell_profit_only=config.get('experimental', {}).get('sell_profit_only', False),
stoploss=config.get('stoploss'),
use_sell_signal=config.get('experimental', {}).get('use_sell_signal', False)
)
logger.info(
'\n==================================== BACKTESTING REPORT ====================================\n%s', # noqa
generate_text_table(data, results, config['stake_currency'], args.ticker_interval)
)
def test_processed(default_conf, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
dict_of_tickerrows = load_data_test('raise')
dataframes = optimize.preprocess(dict_of_tickerrows)
dataframe = dataframes['BTC_UNITEST']
cols = dataframe.columns
# assert the dataframe got some of the indicator columns
for col in ['close', 'high', 'low', 'open', 'date',
'ema50', 'ao', 'macd', 'plus_dm']:
assert col in cols
def test_processed(default_conf, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
dict_of_tickerrows = load_data_test('raise')
dataframes = optimize.preprocess(dict_of_tickerrows)
dataframe = dataframes['BTC_UNITEST']
cols = dataframe.columns
# assert the dataframe got some of the indicator columns
for col in [
'close', 'high', 'low', 'open', 'date', 'ema50', 'ao', 'macd',
'plus_dm'
]:
assert col in cols
def start(args):
global TOTAL_TRIES, PROCESSED, SPACE, TRIALS, _CURRENT_TRIES
TOTAL_TRIES = args.epochs
exchange._API = Bittrex({'key': '', 'secret': ''})
# Initialize logger
logging.basicConfig(
level=args.loglevel,
format='\n%(message)s',
)
logger.info('Using config: %s ...', args.config)
config = load_config(args.config)
pairs = config['exchange']['pair_whitelist']
PROCESSED = optimize.preprocess(
optimize.load_data(args.datadir,
pairs=pairs,
ticker_interval=args.ticker_interval))
if args.mongodb:
logger.info('Using mongodb ...')
logger.info(
'Start scripts/start-mongodb.sh and start-hyperopt-worker.sh manually!'
)
db_name = 'freqtrade_hyperopt'
TRIALS = MongoTrials('mongo://127.0.0.1:1234/{}/jobs'.format(db_name),
exp_key='exp1')
else:
logger.info('Preparing Trials..')
signal.signal(signal.SIGINT, signal_handler)
# read trials file if we have one
if os.path.exists(TRIALS_FILE):
TRIALS = read_trials()
_CURRENT_TRIES = len(TRIALS.results)
TOTAL_TRIES = TOTAL_TRIES + _CURRENT_TRIES
logger.info(
'Continuing with trials. Current: {}, Total: {}'.format(
_CURRENT_TRIES, TOTAL_TRIES))
try:
best_parameters = fmin(fn=optimizer,
space=SPACE,
algo=tpe.suggest,
max_evals=TOTAL_TRIES,
trials=TRIALS)
results = sorted(TRIALS.results, key=itemgetter('loss'))
best_result = results[0]['result']
except ValueError:
best_parameters = {}
best_result = 'Sorry, Hyperopt was not able to find good parameters. Please ' \
'try with more epochs (param: -e).'
# Improve best parameter logging display
if best_parameters:
best_parameters = space_eval(SPACE, best_parameters)
logger.info('Best parameters:\n%s', json.dumps(best_parameters, indent=4))
logger.info('Best Result:\n%s', best_result)
# Store trials result to file to resume next time
save_trials(TRIALS)
def test_get_timeframe():
data = preprocess(optimize.load_data(
None, ticker_interval=1, pairs=['BTC_UNITEST']))
min_date, max_date = get_timeframe(data)
assert min_date.isoformat() == '2017-11-04T23:02:00+00:00'
assert max_date.isoformat() == '2017-11-14T22:59:00+00:00'
def start(args):
# Initialize logger
logging.basicConfig(
level=args.loglevel,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
)
exchange._API = Bittrex({'key': '', 'secret': ''})
logger.info('Using config: %s ...', args.config)
config = misc.load_config(args.config)
logger.info('Using ticker_interval: %s ...', args.ticker_interval)
data = {}
pairs = config['exchange']['pair_whitelist']
if args.live:
logger.info('Downloading data for all pairs in whitelist ...')
for pair in pairs:
data[pair] = exchange.get_ticker_history(pair,
args.ticker_interval)
else:
logger.info(
'Using local backtesting data (using whitelist in given config) ...'
)
data = optimize.load_data(args.datadir,
pairs=pairs,
ticker_interval=args.ticker_interval,
refresh_pairs=args.refresh_pairs)
logger.info('Using stake_currency: %s ...', config['stake_currency'])
logger.info('Using stake_amount: %s ...', config['stake_amount'])
max_open_trades = 0
if args.realistic_simulation:
logger.info('Using max_open_trades: %s ...', config['max_open_trades'])
max_open_trades = config['max_open_trades']
# Monkey patch config
from freqtrade import main
main._CONF = config
preprocessed = preprocess(data)
# Print timeframe
min_date, max_date = get_timeframe(preprocessed)
logger.info('Measuring data from %s up to %s ...', min_date.isoformat(),
max_date.isoformat())
# Execute backtest and print results
results = backtest(
stake_amount=config['stake_amount'],
processed=preprocessed,
max_open_trades=max_open_trades,
realistic=args.realistic_simulation,
sell_profit_only=config.get('experimental',
{}).get('sell_profit_only', False),
stoploss=config.get('stoploss'),
use_sell_signal=config.get('experimental',
{}).get('use_sell_signal', False))
logger.info(
'\n==================================== BACKTESTING REPORT ====================================\n%s', # noqa
generate_text_table(data, results, config['stake_currency'],
args.ticker_interval))
def start(args):
global TOTAL_TRIES, PROCESSED, SPACE, TRIALS, _CURRENT_TRIES
TOTAL_TRIES = args.epochs
exchange._API = Bittrex({'key': '', 'secret': ''})
# Initialize logger
logging.basicConfig(
level=args.loglevel,
format='\n%(message)s',
)
logger.info('Using config: %s ...', args.config)
config = load_config(args.config)
pairs = config['exchange']['pair_whitelist']
PROCESSED = optimize.preprocess(optimize.load_data(
args.datadir, pairs=pairs, ticker_interval=args.ticker_interval))
if args.mongodb:
logger.info('Using mongodb ...')
logger.info('Start scripts/start-mongodb.sh and start-hyperopt-worker.sh manually!')
db_name = 'freqtrade_hyperopt'
TRIALS = MongoTrials('mongo://127.0.0.1:1234/{}/jobs'.format(db_name), exp_key='exp1')
else:
logger.info('Preparing Trials..')
signal.signal(signal.SIGINT, signal_handler)
# read trials file if we have one
if os.path.exists(TRIALS_FILE):
TRIALS = read_trials()
_CURRENT_TRIES = len(TRIALS.results)
TOTAL_TRIES = TOTAL_TRIES + _CURRENT_TRIES
logger.info(
'Continuing with trials. Current: {}, Total: {}'
.format(_CURRENT_TRIES, TOTAL_TRIES))
try:
best_parameters = fmin(
fn=optimizer,
space=SPACE,
algo=tpe.suggest,
max_evals=TOTAL_TRIES,
trials=TRIALS
)
results = sorted(TRIALS.results, key=itemgetter('loss'))
best_result = results[0]['result']
except ValueError:
best_parameters = {}
best_result = 'Sorry, Hyperopt was not able to find good parameters. Please ' \
'try with more epochs (param: -e).'
# Improve best parameter logging display
if best_parameters:
best_parameters = space_eval(SPACE, best_parameters)
logger.info('Best parameters:\n%s', json.dumps(best_parameters, indent=4))
logger.info('Best Result:\n%s', best_result)
# Store trials result to file to resume next time
save_trials(TRIALS)
def test_get_timeframe():
data = preprocess(
optimize.load_data(None, ticker_interval=1, pairs=['BTC_UNITEST']))
min_date, max_date = get_timeframe(data)
assert min_date.isoformat() == '2017-11-04T23:02:00+00:00'
assert max_date.isoformat() == '2017-11-14T22:59:00+00:00'