def list_strategies(config=Depends(get_config)):
directory = Path(config.get(
'strategy_path', config['user_data_dir'] / USERPATH_STRATEGIES))
from freqtrade.resolvers.strategy_resolver import StrategyResolver
strategies = StrategyResolver.search_all_objects(directory, False)
strategies = sorted(strategies, key=lambda x: x['name'])
return {'strategies': [x['name'] for x in strategies]}
def _list_strategies(self):
directory = Path(
self._config.get(
'strategy_path',
self._config['user_data_dir'] / USERPATH_STRATEGIES))
from freqtrade.resolvers.strategy_resolver import StrategyResolver
strategy_objs = StrategyResolver.search_all_objects(directory, False)
strategy_objs = sorted(strategy_objs, key=lambda x: x['name'])
return jsonify({'strategies': [x['name'] for x in strategy_objs]})
def get_strategy_filename(config: Dict, strategy_name: str) -> Optional[Path]:
"""
Get Strategy-location (filename) from strategy_name
"""
from freqtrade.resolvers.strategy_resolver import StrategyResolver
directory = Path(config.get('strategy_path', config['user_data_dir'] / USERPATH_STRATEGIES))
strategy_objs = StrategyResolver.search_all_objects(directory, False)
strategies = [s for s in strategy_objs if s['name'] == strategy_name]
if strategies:
strategy = strategies[0]
return Path(strategy['location'])
return None
def get_strategy(strategy: str, config=Depends(get_config)):
config = deepcopy(config)
from freqtrade.resolvers.strategy_resolver import StrategyResolver
try:
strategy_obj = StrategyResolver._load_strategy(
strategy, config, extra_dir=config.get('strategy_path'))
except OperationalException:
raise HTTPException(status_code=404, detail='Strategy not found')
return {
'strategy': strategy_obj.get_strategy_name(),
'code': strategy_obj.__source__,
}
def _rpc_analysed_history_full(config, pair: str, timeframe: str,
timerange: str) -> Dict[str, Any]:
timerange_parsed = TimeRange.parse_timerange(timerange)
_data = load_data(
datadir=config.get("datadir"),
pairs=[pair],
timeframe=timeframe,
timerange=timerange_parsed,
data_format=config.get('dataformat_ohlcv', 'json'),
)
from freqtrade.resolvers.strategy_resolver import StrategyResolver
strategy = StrategyResolver.load_strategy(config)
df_analyzed = strategy.analyze_ticker(_data[pair], {'pair': pair})
return RPC._convert_dataframe_to_dict(strategy.get_strategy_name(), pair, timeframe,
df_analyzed, arrow.Arrow.utcnow().datetime)
def _get_strategy(self, strategy: str):
"""
Get a single strategy
get:
parameters:
- strategy: Only get this strategy
"""
config = deepcopy(self._config)
from freqtrade.resolvers.strategy_resolver import StrategyResolver
try:
strategy_obj = StrategyResolver._load_strategy(
strategy, config, extra_dir=config.get('strategy_path'))
except OperationalException:
return self.rest_error("Strategy not found.", 404)
return jsonify({
'strategy': strategy_obj.get_strategy_name(),
'code': strategy_obj.__source__,
})
def _rpc_analysed_history_full(config, pair: str, timeframe: str,
timerange: str) -> Dict[str, Any]:
timerange_parsed = TimeRange.parse_timerange(timerange)
_data = load_data(
datadir=config.get("datadir"),
pairs=[pair],
timeframe=timeframe,
timerange=timerange_parsed,
data_format=config.get('dataformat_ohlcv', 'json'),
)
if pair not in _data:
raise RPCException(f"No data for {pair}, {timeframe} in {timerange} found.")
from freqtrade.data.dataprovider import DataProvider
from freqtrade.resolvers.strategy_resolver import StrategyResolver
strategy = StrategyResolver.load_strategy(config)
strategy.dp = DataProvider(config, exchange=None, pairlists=None)
df_analyzed = strategy.analyze_ticker(_data[pair], {'pair': pair})
return RPC._convert_dataframe_to_dict(strategy.get_strategy_name(), pair, timeframe,
df_analyzed, arrow.Arrow.utcnow().datetime)
def test_generate_backtest_stats(default_conf, testdatadir):
default_conf.update({'strategy': 'DefaultStrategy'})
StrategyResolver.load_strategy(default_conf)
results = {
'DefStrat': {
'results':
pd.DataFrame({
"pair": [
"UNITTEST/BTC", "UNITTEST/BTC", "UNITTEST/BTC",
"UNITTEST/BTC"
],
"profit_ratio": [0.003312, 0.010801, 0.013803, 0.002780],
"profit_abs": [0.000003, 0.000011, 0.000014, 0.000003],
"open_date": [
Arrow(2017, 11, 14, 19, 32, 00).datetime,
Arrow(2017, 11, 14, 21, 36, 00).datetime,
Arrow(2017, 11, 14, 22, 12, 00).datetime,
Arrow(2017, 11, 14, 22, 44, 00).datetime
],
"close_date": [
Arrow(2017, 11, 14, 21, 35, 00).datetime,
Arrow(2017, 11, 14, 22, 10, 00).datetime,
Arrow(2017, 11, 14, 22, 43, 00).datetime,
Arrow(2017, 11, 14, 22, 58, 00).datetime
],
"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
"close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
"trade_duration": [123, 34, 31, 14],
"is_open": [False, False, False, True],
"sell_reason": [
SellType.ROI, SellType.STOP_LOSS, SellType.ROI,
SellType.FORCE_SELL
]
}),
'config':
default_conf,
'locks': [],
'backtest_start_time':
Arrow.utcnow().int_timestamp,
'backtest_end_time':
Arrow.utcnow().int_timestamp,
}
}
timerange = TimeRange.parse_timerange('1510688220-1510700340')
min_date = Arrow.fromtimestamp(1510688220)
max_date = Arrow.fromtimestamp(1510700340)
btdata = history.load_data(testdatadir,
'1m', ['UNITTEST/BTC'],
timerange=timerange,
fill_up_missing=True)
stats = generate_backtest_stats(btdata, results, min_date, max_date)
assert isinstance(stats, dict)
assert 'strategy' in stats
assert 'DefStrat' in stats['strategy']
assert 'strategy_comparison' in stats
strat_stats = stats['strategy']['DefStrat']
assert strat_stats['backtest_start'] == min_date.datetime
assert strat_stats['backtest_end'] == max_date.datetime
assert strat_stats['total_trades'] == len(results['DefStrat']['results'])
# Above sample had no loosing trade
assert strat_stats['max_drawdown'] == 0.0
results = {
'DefStrat': {
'results':
pd.DataFrame({
"pair": [
"UNITTEST/BTC", "UNITTEST/BTC", "UNITTEST/BTC",
"UNITTEST/BTC"
],
"profit_ratio": [0.003312, 0.010801, -0.013803, 0.002780],
"profit_abs": [0.000003, 0.000011, -0.000014, 0.000003],
"open_date": [
Arrow(2017, 11, 14, 19, 32, 00).datetime,
Arrow(2017, 11, 14, 21, 36, 00).datetime,
Arrow(2017, 11, 14, 22, 12, 00).datetime,
Arrow(2017, 11, 14, 22, 44, 00).datetime
],
"close_date": [
Arrow(2017, 11, 14, 21, 35, 00).datetime,
Arrow(2017, 11, 14, 22, 10, 00).datetime,
Arrow(2017, 11, 14, 22, 43, 00).datetime,
Arrow(2017, 11, 14, 22, 58, 00).datetime
],
"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
"close_rate": [0.002546, 0.003014, 0.0032903, 0.003217],
"trade_duration": [123, 34, 31, 14],
"open_at_end": [False, False, False, True],
"sell_reason": [
SellType.ROI, SellType.STOP_LOSS, SellType.ROI,
SellType.FORCE_SELL
]
}),
'config':
default_conf
}
}
assert strat_stats['max_drawdown'] == 0.0
assert strat_stats['drawdown_start'] == datetime(1970,
1,
1,
tzinfo=timezone.utc)
assert strat_stats['drawdown_end'] == datetime(1970,
1,
1,
tzinfo=timezone.utc)
assert strat_stats['drawdown_end_ts'] == 0
assert strat_stats['drawdown_start_ts'] == 0
assert strat_stats['pairlist'] == ['UNITTEST/BTC']
# Test storing stats
filename = Path(testdatadir / 'btresult.json')
filename_last = Path(testdatadir / LAST_BT_RESULT_FN)
_backup_file(filename_last, copy_file=True)
assert not filename.is_file()
store_backtest_stats(filename, stats)
# get real Filename (it's btresult-<date>.json)
last_fn = get_latest_backtest_filename(filename_last.parent)
assert re.match(r"btresult-.*\.json", last_fn)
filename1 = (testdatadir / last_fn)
assert filename1.is_file()
content = filename1.read_text()
assert 'max_drawdown' in content
assert 'strategy' in content
assert 'pairlist' in content
assert filename_last.is_file()
_clean_test_file(filename_last)
filename1.unlink()
def test_generate_backtest_stats(default_conf, testdatadir, tmpdir):
default_conf.update({'strategy': CURRENT_TEST_STRATEGY})
StrategyResolver.load_strategy(default_conf)
results = {
'DefStrat': {
'results':
pd.DataFrame({
"pair": [
"UNITTEST/BTC", "UNITTEST/BTC", "UNITTEST/BTC",
"UNITTEST/BTC"
],
"profit_ratio": [0.003312, 0.010801, 0.013803, 0.002780],
"profit_abs": [0.000003, 0.000011, 0.000014, 0.000003],
"open_date": [
Arrow(2017, 11, 14, 19, 32, 00).datetime,
Arrow(2017, 11, 14, 21, 36, 00).datetime,
Arrow(2017, 11, 14, 22, 12, 00).datetime,
Arrow(2017, 11, 14, 22, 44, 00).datetime
],
"close_date": [
Arrow(2017, 11, 14, 21, 35, 00).datetime,
Arrow(2017, 11, 14, 22, 10, 00).datetime,
Arrow(2017, 11, 14, 22, 43, 00).datetime,
Arrow(2017, 11, 14, 22, 58, 00).datetime
],
"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
"close_rate": [0.002546, 0.003014, 0.003103, 0.003217],
"trade_duration": [123, 34, 31, 14],
"is_open": [False, False, False, True],
"is_short": [False, False, False, False],
"stake_amount": [0.01, 0.01, 0.01, 0.01],
"exit_reason": [
ExitType.ROI, ExitType.STOP_LOSS, ExitType.ROI,
ExitType.FORCE_EXIT
]
}),
'config':
default_conf,
'locks': [],
'final_balance':
1000.02,
'rejected_signals':
20,
'timedout_entry_orders':
0,
'timedout_exit_orders':
0,
'backtest_start_time':
Arrow.utcnow().int_timestamp,
'backtest_end_time':
Arrow.utcnow().int_timestamp,
'run_id':
'123',
}
}
timerange = TimeRange.parse_timerange('1510688220-1510700340')
min_date = Arrow.fromtimestamp(1510688220)
max_date = Arrow.fromtimestamp(1510700340)
btdata = history.load_data(testdatadir,
'1m', ['UNITTEST/BTC'],
timerange=timerange,
fill_up_missing=True)
stats = generate_backtest_stats(btdata, results, min_date, max_date)
assert isinstance(stats, dict)
assert 'strategy' in stats
assert 'DefStrat' in stats['strategy']
assert 'strategy_comparison' in stats
strat_stats = stats['strategy']['DefStrat']
assert strat_stats['backtest_start'] == min_date.strftime(
DATETIME_PRINT_FORMAT)
assert strat_stats['backtest_end'] == max_date.strftime(
DATETIME_PRINT_FORMAT)
assert strat_stats['total_trades'] == len(results['DefStrat']['results'])
# Above sample had no loosing trade
assert strat_stats['max_drawdown_account'] == 0.0
# Retry with losing trade
results = {
'DefStrat': {
'results':
pd.DataFrame({
"pair": [
"UNITTEST/BTC", "UNITTEST/BTC", "UNITTEST/BTC",
"UNITTEST/BTC"
],
"profit_ratio": [0.003312, 0.010801, -0.013803, 0.002780],
"profit_abs": [0.000003, 0.000011, -0.000014, 0.000003],
"open_date": [
Arrow(2017, 11, 14, 19, 32, 00).datetime,
Arrow(2017, 11, 14, 21, 36, 00).datetime,
Arrow(2017, 11, 14, 22, 12, 00).datetime,
Arrow(2017, 11, 14, 22, 44, 00).datetime
],
"close_date": [
Arrow(2017, 11, 14, 21, 35, 00).datetime,
Arrow(2017, 11, 14, 22, 10, 00).datetime,
Arrow(2017, 11, 14, 22, 43, 00).datetime,
Arrow(2017, 11, 14, 22, 58, 00).datetime
],
"open_rate": [0.002543, 0.003003, 0.003089, 0.003214],
"close_rate": [0.002546, 0.003014, 0.0032903, 0.003217],
"trade_duration": [123, 34, 31, 14],
"is_open": [False, False, False, True],
"is_short": [False, False, False, False],
"stake_amount": [0.01, 0.01, 0.01, 0.01],
"exit_reason": [
ExitType.ROI, ExitType.ROI, ExitType.STOP_LOSS,
ExitType.FORCE_EXIT
]
}),
'config':
default_conf,
'locks': [],
'final_balance':
1000.02,
'rejected_signals':
20,
'timedout_entry_orders':
0,
'timedout_exit_orders':
0,
'backtest_start_time':
Arrow.utcnow().int_timestamp,
'backtest_end_time':
Arrow.utcnow().int_timestamp,
'run_id':
'124',
}
}
stats = generate_backtest_stats(btdata, results, min_date, max_date)
assert isinstance(stats, dict)
assert 'strategy' in stats
assert 'DefStrat' in stats['strategy']
assert 'strategy_comparison' in stats
strat_stats = stats['strategy']['DefStrat']
assert pytest.approx(strat_stats['max_drawdown_account']) == 1.399999e-08
assert strat_stats['drawdown_start'] == '2017-11-14 22:10:00'
assert strat_stats['drawdown_end'] == '2017-11-14 22:43:00'
assert strat_stats['drawdown_end_ts'] == 1510699380000
assert strat_stats['drawdown_start_ts'] == 1510697400000
assert strat_stats['pairlist'] == ['UNITTEST/BTC']
# Test storing stats
filename = Path(tmpdir / 'btresult.json')
filename_last = Path(tmpdir / LAST_BT_RESULT_FN)
_backup_file(filename_last, copy_file=True)
assert not filename.is_file()
store_backtest_stats(filename, stats)
# get real Filename (it's btresult-<date>.json)
last_fn = get_latest_backtest_filename(filename_last.parent)
assert re.match(r"btresult-.*\.json", last_fn)
filename1 = Path(tmpdir / last_fn)
assert filename1.is_file()
content = filename1.read_text()
assert 'max_drawdown_account' in content
assert 'strategy' in content
assert 'pairlist' in content
assert filename_last.is_file()
_clean_test_file(filename_last)
filename1.unlink()
def test_informative_decorator(mocker, default_conf_usdt, trading_mode):
candle_def = CandleType.get_default(trading_mode)
default_conf_usdt['candle_type_def'] = candle_def
test_data_5m = generate_test_data('5m', 40)
test_data_30m = generate_test_data('30m', 40)
test_data_1h = generate_test_data('1h', 40)
data = {
('XRP/USDT', '5m', candle_def): test_data_5m,
('XRP/USDT', '30m', candle_def): test_data_30m,
('XRP/USDT', '1h', candle_def): test_data_1h,
('LTC/USDT', '5m', candle_def): test_data_5m,
('LTC/USDT', '30m', candle_def): test_data_30m,
('LTC/USDT', '1h', candle_def): test_data_1h,
('NEO/USDT', '30m', candle_def): test_data_30m,
('NEO/USDT', '5m', CandleType.SPOT): test_data_5m, # Explicit request with '' as candletype
('NEO/USDT', '15m', candle_def): test_data_5m, # Explicit request with '' as candletype
('NEO/USDT', '1h', candle_def): test_data_1h,
('ETH/USDT', '1h', candle_def): test_data_1h,
('ETH/USDT', '30m', candle_def): test_data_30m,
('ETH/BTC', '1h', CandleType.SPOT): test_data_1h, # Explicitly selected as spot
}
default_conf_usdt['strategy'] = 'InformativeDecoratorTest'
strategy = StrategyResolver.load_strategy(default_conf_usdt)
exchange = get_patched_exchange(mocker, default_conf_usdt)
strategy.dp = DataProvider({}, exchange, None)
mocker.patch.object(strategy.dp, 'current_whitelist', return_value=[
'XRP/USDT', 'LTC/USDT', 'NEO/USDT'
])
assert len(strategy._ft_informative) == 6 # Equal to number of decorators used
informative_pairs = [
('XRP/USDT', '1h', candle_def),
('LTC/USDT', '1h', candle_def),
('XRP/USDT', '30m', candle_def),
('LTC/USDT', '30m', candle_def),
('NEO/USDT', '1h', candle_def),
('NEO/USDT', '30m', candle_def),
('NEO/USDT', '5m', candle_def),
('NEO/USDT', '15m', candle_def),
('NEO/USDT', '2h', CandleType.FUTURES),
('ETH/BTC', '1h', CandleType.SPOT), # One candle remains as spot
('ETH/USDT', '30m', candle_def)]
for inf_pair in informative_pairs:
assert inf_pair in strategy.gather_informative_pairs()
def test_historic_ohlcv(pair, timeframe, candle_type):
return data[
(pair, timeframe or strategy.timeframe, CandleType.from_string(candle_type))].copy()
mocker.patch('freqtrade.data.dataprovider.DataProvider.historic_ohlcv',
side_effect=test_historic_ohlcv)
analyzed = strategy.advise_all_indicators(
{p: data[(p, strategy.timeframe, candle_def)] for p in ('XRP/USDT', 'LTC/USDT')})
expected_columns = [
'rsi_1h', 'rsi_30m', # Stacked informative decorators
'neo_usdt_rsi_1h', # NEO 1h informative
'rsi_NEO_USDT_neo_usdt_NEO/USDT_30m', # Column formatting
'rsi_from_callable', # Custom column formatter
'eth_btc_rsi_1h', # Quote currency not matching stake currency
'rsi', 'rsi_less', # Non-informative columns
'rsi_5m', # Manual informative dataframe
]
for _, dataframe in analyzed.items():
for col in expected_columns:
assert col in dataframe.columns
