stable/freqtrade/resolvers/hyperopt_resolver.py
Matthias 378b214a56 Remove hyperopt-loss default option
Force users to make a concious choice on a hyperopt-loss function
2020-10-05 19:27:28 +02:00

90 lines
3.5 KiB
Python

# pragma pylint: disable=attribute-defined-outside-init
"""
This module load custom hyperopt
"""
import logging
from pathlib import Path
from typing import Dict
from freqtrade.constants import USERPATH_HYPEROPTS
from freqtrade.exceptions import OperationalException
from freqtrade.optimize.hyperopt_interface import IHyperOpt
from freqtrade.optimize.hyperopt_loss_interface import IHyperOptLoss
from freqtrade.resolvers import IResolver
logger = logging.getLogger(__name__)
class HyperOptResolver(IResolver):
"""
This class contains all the logic to load custom hyperopt class
"""
object_type = IHyperOpt
object_type_str = "Hyperopt"
user_subdir = USERPATH_HYPEROPTS
initial_search_path = None
@staticmethod
def load_hyperopt(config: Dict) -> IHyperOpt:
"""
Load the custom hyperopt class from config parameter
:param config: configuration dictionary
"""
if not config.get('hyperopt'):
raise OperationalException("No Hyperopt set. Please use `--hyperopt` to specify "
"the Hyperopt class to use.")
hyperopt_name = config['hyperopt']
hyperopt = HyperOptResolver.load_object(hyperopt_name, config,
kwargs={'config': config},
extra_dir=config.get('hyperopt_path'))
if not hasattr(hyperopt, 'populate_indicators'):
logger.info("Hyperopt class does not provide populate_indicators() method. "
"Using populate_indicators from the strategy.")
if not hasattr(hyperopt, 'populate_buy_trend'):
logger.info("Hyperopt class does not provide populate_buy_trend() method. "
"Using populate_buy_trend from the strategy.")
if not hasattr(hyperopt, 'populate_sell_trend'):
logger.info("Hyperopt class does not provide populate_sell_trend() method. "
"Using populate_sell_trend from the strategy.")
return hyperopt
class HyperOptLossResolver(IResolver):
"""
This class contains all the logic to load custom hyperopt loss class
"""
object_type = IHyperOptLoss
object_type_str = "HyperoptLoss"
user_subdir = USERPATH_HYPEROPTS
initial_search_path = Path(__file__).parent.parent.joinpath('optimize').resolve()
@staticmethod
def load_hyperoptloss(config: Dict) -> IHyperOptLoss:
"""
Load the custom class from config parameter
:param config: configuration dictionary
"""
hyperoptloss_name = config.get('hyperopt_loss')
if not hyperoptloss_name:
raise OperationalException("No Hyperopt loss set. Please use `--hyperopt-loss` to "
"specify the Hyperopt-Loss class to use.")
hyperoptloss = HyperOptLossResolver.load_object(hyperoptloss_name,
config, kwargs={},
extra_dir=config.get('hyperopt_path'))
# Assign timeframe to be used in hyperopt
hyperoptloss.__class__.ticker_interval = str(config['timeframe'])
hyperoptloss.__class__.timeframe = str(config['timeframe'])
if not hasattr(hyperoptloss, 'hyperopt_loss_function'):
raise OperationalException(
f"Found HyperoptLoss class {hyperoptloss_name} does not "
"implement `hyperopt_loss_function`.")
return hyperoptloss