From 6d5aca4f323dd06cac94cbf598173be6fb3ed645 Mon Sep 17 00:00:00 2001 From: Matthias Date: Mon, 23 Dec 2019 10:09:08 +0100 Subject: [PATCH] Convert hyperoptloss resolver to static loader --- freqtrade/optimize/hyperopt.py | 2 +- freqtrade/resolvers/hyperopt_resolver.py | 26 +++++++++++++----------- tests/optimize/test_hyperopt.py | 14 ++++++------- 3 files changed, 22 insertions(+), 20 deletions(-) diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py index a4a8f79d1..48f883ac5 100644 --- a/freqtrade/optimize/hyperopt.py +++ b/freqtrade/optimize/hyperopt.py @@ -66,7 +66,7 @@ class Hyperopt: self.custom_hyperopt = HyperOptResolver.load_hyperopt(self.config) - self.custom_hyperoptloss = HyperOptLossResolver(self.config).hyperoptloss + self.custom_hyperoptloss = HyperOptLossResolver.load_hyperoptloss(self.config) self.calculate_loss = self.custom_hyperoptloss.hyperopt_loss_function self.trials_file = (self.config['user_data_dir'] / diff --git a/freqtrade/resolvers/hyperopt_resolver.py b/freqtrade/resolvers/hyperopt_resolver.py index a7f922c7b..0726b0627 100644 --- a/freqtrade/resolvers/hyperopt_resolver.py +++ b/freqtrade/resolvers/hyperopt_resolver.py @@ -77,9 +77,9 @@ class HyperOptLossResolver(IResolver): """ This class contains all the logic to load custom hyperopt loss class """ - __slots__ = ['hyperoptloss'] - def __init__(self, config: Dict) -> None: + @staticmethod + def load_hyperoptloss(config: Dict) -> IHyperOptLoss: """ Load the custom class from config parameter :param config: configuration dictionary @@ -89,20 +89,21 @@ class HyperOptLossResolver(IResolver): # default hyperopt loss hyperoptloss_name = config.get('hyperopt_loss') or DEFAULT_HYPEROPT_LOSS - self.hyperoptloss = self._load_hyperoptloss( + hyperoptloss = HyperOptLossResolver._load_hyperoptloss( hyperoptloss_name, config, extra_dir=config.get('hyperopt_path')) # Assign ticker_interval to be used in hyperopt - self.hyperoptloss.__class__.ticker_interval = str(config['ticker_interval']) + hyperoptloss.__class__.ticker_interval = str(config['ticker_interval']) - if not hasattr(self.hyperoptloss, 'hyperopt_loss_function'): + if not hasattr(hyperoptloss, 'hyperopt_loss_function'): raise OperationalException( f"Found HyperoptLoss class {hyperoptloss_name} does not " "implement `hyperopt_loss_function`.") + return hyperoptloss - def _load_hyperoptloss( - self, hyper_loss_name: str, config: Dict, - extra_dir: Optional[str] = None) -> IHyperOptLoss: + @staticmethod + def _load_hyperoptloss(hyper_loss_name: str, config: Dict, + extra_dir: Optional[str] = None) -> IHyperOptLoss: """ Search and loads the specified hyperopt loss class. :param hyper_loss_name: name of the module to import @@ -112,11 +113,12 @@ class HyperOptLossResolver(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) - hyperoptloss = self._load_object(paths=abs_paths, object_type=IHyperOptLoss, - object_name=hyper_loss_name) + hyperoptloss = IResolver._load_object(paths=abs_paths, object_type=IHyperOptLoss, + object_name=hyper_loss_name) if hyperoptloss: return hyperoptloss diff --git a/tests/optimize/test_hyperopt.py b/tests/optimize/test_hyperopt.py index 37de32ab0..9c6e73c53 100644 --- a/tests/optimize/test_hyperopt.py +++ b/tests/optimize/test_hyperopt.py @@ -198,7 +198,7 @@ def test_hyperoptlossresolver(mocker, default_conf, caplog) -> None: 'freqtrade.resolvers.hyperopt_resolver.HyperOptLossResolver._load_hyperoptloss', MagicMock(return_value=hl) ) - x = HyperOptLossResolver(default_conf).hyperoptloss + x = HyperOptLossResolver.load_hyperoptloss(default_conf) assert hasattr(x, "hyperopt_loss_function") @@ -206,7 +206,7 @@ def test_hyperoptlossresolver_wrongname(mocker, default_conf, caplog) -> None: default_conf.update({'hyperopt_loss': "NonExistingLossClass"}) with pytest.raises(OperationalException, match=r'Impossible to load HyperoptLoss.*'): - HyperOptLossResolver(default_conf).hyperopt + HyperOptLossResolver.load_hyperoptloss(default_conf) def test_start_not_installed(mocker, default_conf, caplog, import_fails) -> None: @@ -286,7 +286,7 @@ def test_start_filelock(mocker, default_conf, caplog) -> None: def test_loss_calculation_prefer_correct_trade_count(default_conf, hyperopt_results) -> None: - hl = HyperOptLossResolver(default_conf).hyperoptloss + hl = HyperOptLossResolver.load_hyperoptloss(default_conf) correct = hl.hyperopt_loss_function(hyperopt_results, 600) over = hl.hyperopt_loss_function(hyperopt_results, 600 + 100) under = hl.hyperopt_loss_function(hyperopt_results, 600 - 100) @@ -298,7 +298,7 @@ def test_loss_calculation_prefer_shorter_trades(default_conf, hyperopt_results) resultsb = hyperopt_results.copy() resultsb.loc[1, 'trade_duration'] = 20 - hl = HyperOptLossResolver(default_conf).hyperoptloss + hl = HyperOptLossResolver.load_hyperoptloss(default_conf) longer = hl.hyperopt_loss_function(hyperopt_results, 100) shorter = hl.hyperopt_loss_function(resultsb, 100) assert shorter < longer @@ -310,7 +310,7 @@ def test_loss_calculation_has_limited_profit(default_conf, hyperopt_results) -> results_under = hyperopt_results.copy() results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2 - hl = HyperOptLossResolver(default_conf).hyperoptloss + hl = HyperOptLossResolver.load_hyperoptloss(default_conf) correct = hl.hyperopt_loss_function(hyperopt_results, 600) over = hl.hyperopt_loss_function(results_over, 600) under = hl.hyperopt_loss_function(results_under, 600) @@ -325,7 +325,7 @@ def test_sharpe_loss_prefers_higher_profits(default_conf, hyperopt_results) -> N results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2 default_conf.update({'hyperopt_loss': 'SharpeHyperOptLoss'}) - hl = HyperOptLossResolver(default_conf).hyperoptloss + hl = HyperOptLossResolver.load_hyperoptloss(default_conf) correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results), datetime(2019, 1, 1), datetime(2019, 5, 1)) over = hl.hyperopt_loss_function(results_over, len(hyperopt_results), @@ -343,7 +343,7 @@ def test_onlyprofit_loss_prefers_higher_profits(default_conf, hyperopt_results) results_under['profit_percent'] = hyperopt_results['profit_percent'] / 2 default_conf.update({'hyperopt_loss': 'OnlyProfitHyperOptLoss'}) - hl = HyperOptLossResolver(default_conf).hyperoptloss + hl = HyperOptLossResolver.load_hyperoptloss(default_conf) correct = hl.hyperopt_loss_function(hyperopt_results, len(hyperopt_results), datetime(2019, 1, 1), datetime(2019, 5, 1)) over = hl.hyperopt_loss_function(results_over, len(hyperopt_results),