Convert hyperoptloss resolver to static loader
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Matthias
parent
248ef5a0ea
commit
6d5aca4f32
@ -66,7 +66,7 @@ class Hyperopt:
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self.custom_hyperopt = HyperOptResolver.load_hyperopt(self.config)
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self.custom_hyperoptloss = HyperOptLossResolver(self.config).hyperoptloss
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self.custom_hyperoptloss = HyperOptLossResolver.load_hyperoptloss(self.config)
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self.calculate_loss = self.custom_hyperoptloss.hyperopt_loss_function
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self.trials_file = (self.config['user_data_dir'] /
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@ -77,9 +77,9 @@ class HyperOptLossResolver(IResolver):
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"""
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This class contains all the logic to load custom hyperopt loss class
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"""
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__slots__ = ['hyperoptloss']
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def __init__(self, config: Dict) -> None:
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@staticmethod
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def load_hyperoptloss(config: Dict) -> IHyperOptLoss:
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"""
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Load the custom class from config parameter
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:param config: configuration dictionary
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@ -89,20 +89,21 @@ class HyperOptLossResolver(IResolver):
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# default hyperopt loss
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hyperoptloss_name = config.get('hyperopt_loss') or DEFAULT_HYPEROPT_LOSS
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self.hyperoptloss = self._load_hyperoptloss(
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hyperoptloss = HyperOptLossResolver._load_hyperoptloss(
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hyperoptloss_name, config, extra_dir=config.get('hyperopt_path'))
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# Assign ticker_interval to be used in hyperopt
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self.hyperoptloss.__class__.ticker_interval = str(config['ticker_interval'])
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hyperoptloss.__class__.ticker_interval = str(config['ticker_interval'])
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if not hasattr(self.hyperoptloss, 'hyperopt_loss_function'):
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if not hasattr(hyperoptloss, 'hyperopt_loss_function'):
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raise OperationalException(
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f"Found HyperoptLoss class {hyperoptloss_name} does not "
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"implement `hyperopt_loss_function`.")
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return hyperoptloss
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def _load_hyperoptloss(
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self, hyper_loss_name: str, config: Dict,
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extra_dir: Optional[str] = None) -> IHyperOptLoss:
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@staticmethod
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def _load_hyperoptloss(hyper_loss_name: str, config: Dict,
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extra_dir: Optional[str] = None) -> IHyperOptLoss:
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"""
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Search and loads the specified hyperopt loss class.
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:param hyper_loss_name: name of the module to import
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@ -112,11 +113,12 @@ class HyperOptLossResolver(IResolver):
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"""
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current_path = Path(__file__).parent.parent.joinpath('optimize').resolve()
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abs_paths = self.build_search_paths(config, current_path=current_path,
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user_subdir=USERPATH_HYPEROPTS, extra_dir=extra_dir)
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abs_paths = IResolver.build_search_paths(config, current_path=current_path,
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user_subdir=USERPATH_HYPEROPTS,
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extra_dir=extra_dir)
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hyperoptloss = self._load_object(paths=abs_paths, object_type=IHyperOptLoss,
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object_name=hyper_loss_name)
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hyperoptloss = IResolver._load_object(paths=abs_paths, object_type=IHyperOptLoss,
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object_name=hyper_loss_name)
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if hyperoptloss:
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return hyperoptloss
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@ -198,7 +198,7 @@ def test_hyperoptlossresolver(mocker, default_conf, caplog) -> None:
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'freqtrade.resolvers.hyperopt_resolver.HyperOptLossResolver._load_hyperoptloss',
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MagicMock(return_value=hl)
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)
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x = HyperOptLossResolver(default_conf).hyperoptloss
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x = HyperOptLossResolver.load_hyperoptloss(default_conf)
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assert hasattr(x, "hyperopt_loss_function")
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@ -206,7 +206,7 @@ def test_hyperoptlossresolver_wrongname(mocker, default_conf, caplog) -> None:
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default_conf.update({'hyperopt_loss': "NonExistingLossClass"})
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with pytest.raises(OperationalException, match=r'Impossible to load HyperoptLoss.*'):
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HyperOptLossResolver(default_conf).hyperopt
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HyperOptLossResolver.load_hyperoptloss(default_conf)
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def test_start_not_installed(mocker, default_conf, caplog, import_fails) -> None:
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@ -286,7 +286,7 @@ def test_start_filelock(mocker, default_conf, caplog) -> None:
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def test_loss_calculation_prefer_correct_trade_count(default_conf, hyperopt_results) -> None:
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hl = HyperOptLossResolver(default_conf).hyperoptloss
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hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
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correct = hl.hyperopt_loss_function(hyperopt_results, 600)
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over = hl.hyperopt_loss_function(hyperopt_results, 600 + 100)
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under = hl.hyperopt_loss_function(hyperopt_results, 600 - 100)
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@ -298,7 +298,7 @@ def test_loss_calculation_prefer_shorter_trades(default_conf, hyperopt_results)
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resultsb = hyperopt_results.copy()
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resultsb.loc[1, 'trade_duration'] = 20
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hl = HyperOptLossResolver(default_conf).hyperoptloss
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hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
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longer = hl.hyperopt_loss_function(hyperopt_results, 100)
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shorter = hl.hyperopt_loss_function(resultsb, 100)
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assert shorter < longer
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@ -310,7 +310,7 @@ def test_loss_calculation_has_limited_profit(default_conf, hyperopt_results) ->
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results_under = hyperopt_results.copy()
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results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
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hl = HyperOptLossResolver(default_conf).hyperoptloss
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hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
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correct = hl.hyperopt_loss_function(hyperopt_results, 600)
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over = hl.hyperopt_loss_function(results_over, 600)
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under = hl.hyperopt_loss_function(results_under, 600)
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@ -325,7 +325,7 @@ def test_sharpe_loss_prefers_higher_profits(default_conf, hyperopt_results) -> N
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results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
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default_conf.update({'hyperopt_loss': 'SharpeHyperOptLoss'})
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hl = HyperOptLossResolver(default_conf).hyperoptloss
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hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
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correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
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datetime(2019, 1, 1), datetime(2019, 5, 1))
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over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
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@ -343,7 +343,7 @@ def test_onlyprofit_loss_prefers_higher_profits(default_conf, hyperopt_results)
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results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2
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default_conf.update({'hyperopt_loss': 'OnlyProfitHyperOptLoss'})
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hl = HyperOptLossResolver(default_conf).hyperoptloss
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hl = HyperOptLossResolver.load_hyperoptloss(default_conf)
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correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results),
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datetime(2019, 1, 1), datetime(2019, 5, 1))
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over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),
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