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Convert HyperoptResolver to static loader

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This commit is contained in:
Matthias 2019-12-23 10:06:19 +01:00
parent 560acb7cea
commit 248ef5a0ea
3 changed files with 20 additions and 17 deletions
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2
freqtrade/optimize/hyperopt.py
View File

@ -64,7 +64,7 @@ class Hyperopt:
self.backtesting = Backtesting(self.config)
self.custom_hyperopt = HyperOptResolver(self.config).hyperopt
self.custom_hyperopt = HyperOptResolver.load_hyperopt(self.config)
self.custom_hyperoptloss = HyperOptLossResolver(self.config).hyperoptloss
self.calculate_loss = self.custom_hyperoptloss.hyperopt_loss_function

25
freqtrade/resolvers/hyperopt_resolver.py
View File

@ -20,11 +20,11 @@ class HyperOptResolver(IResolver):
"""
This class contains all the logic to load custom hyperopt class
"""
__slots__ = ['hyperopt']
def __init__(self, config: Dict) -> None:
@staticmethod
def load_hyperopt(config: Dict) -> IHyperOpt:
"""
Load the custom class from config parameter
Load the custom hyperopt class from config parameter
:param config: configuration dictionary
"""
if not config.get('hyperopt'):
@ -33,21 +33,23 @@ class HyperOptResolver(IResolver):
hyperopt_name = config['hyperopt']
self.hyperopt = self._load_hyperopt(hyperopt_name, config,
hyperopt = HyperOptResolver._load_hyperopt(hyperopt_name, config,
extra_dir=config.get('hyperopt_path'))
if not hasattr(self.hyperopt, 'populate_indicators'):
if not hasattr(hyperopt, 'populate_indicators'):
logger.warning("Hyperopt class does not provide populate_indicators() method. "
"Using populate_indicators from the strategy.")
if not hasattr(self.hyperopt, 'populate_buy_trend'):
if not hasattr(hyperopt, 'populate_buy_trend'):
logger.warning("Hyperopt class does not provide populate_buy_trend() method. "
"Using populate_buy_trend from the strategy.")
if not hasattr(self.hyperopt, 'populate_sell_trend'):
if not hasattr(hyperopt, 'populate_sell_trend'):
logger.warning("Hyperopt class does not provide populate_sell_trend() method. "
"Using populate_sell_trend from the strategy.")
return hyperopt
@staticmethod
def _load_hyperopt(
self, hyperopt_name: str, config: Dict, extra_dir: Optional[str] = None) -> IHyperOpt:
hyperopt_name: str, config: Dict, extra_dir: Optional[str] = None) -> IHyperOpt:
"""
Search and loads the specified hyperopt.
:param hyperopt_name: name of the module to import
@ -57,10 +59,11 @@ class HyperOptResolver(IResolver):
"""
current_path = Path(__file__).parent.parent.joinpath('optimize').resolve()
abs_paths = self.build_search_paths(config, current_path=current_path,
user_subdir=USERPATH_HYPEROPTS, extra_dir=extra_dir)
abs_paths = IResolver.build_search_paths(config, current_path=current_path,
user_subdir=USERPATH_HYPEROPTS,
extra_dir=extra_dir)
hyperopt = self._load_object(paths=abs_paths, object_type=IHyperOpt,
hyperopt = IResolver._load_object(paths=abs_paths, object_type=IHyperOpt,
object_name=hyperopt_name, kwargs={'config': config})
if hyperopt:
return hyperopt

6
tests/optimize/test_hyperopt.py
View File

@ -163,7 +163,7 @@ def test_hyperoptresolver(mocker, default_conf, caplog) -> None:
MagicMock(return_value=hyperopt(default_conf))
)
default_conf.update({'hyperopt': 'DefaultHyperOpt'})
x = HyperOptResolver(default_conf).hyperopt
x = HyperOptResolver.load_hyperopt(default_conf)
assert not hasattr(x, 'populate_indicators')
assert not hasattr(x, 'populate_buy_trend')
assert not hasattr(x, 'populate_sell_trend')
@ -180,7 +180,7 @@ def test_hyperoptresolver_wrongname(mocker, default_conf, caplog) -> None:
default_conf.update({'hyperopt': "NonExistingHyperoptClass"})
with pytest.raises(OperationalException, match=r'Impossible to load Hyperopt.*'):
HyperOptResolver(default_conf).hyperopt
HyperOptResolver.load_hyperopt(default_conf)
def test_hyperoptresolver_noname(default_conf):
@ -188,7 +188,7 @@ def test_hyperoptresolver_noname(default_conf):
with pytest.raises(OperationalException,
match="No Hyperopt set. Please use `--hyperopt` to specify "
"the Hyperopt class to use."):
HyperOptResolver(default_conf)
HyperOptResolver.load_hyperopt(default_conf)
def test_hyperoptlossresolver(mocker, default_conf, caplog) -> None: