Now using resolver for custom hyperopts
This commit is contained in:
Stephen Dade
Matthias
parent
e0f420983e
commit
477515c4b5
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@ -105,12 +105,12 @@ class Arguments(object):
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metavar='PATH',
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)
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self.parser.add_argument(
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'--hyperopt',
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help='specify hyperopt file (default: %(default)s)',
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'--customhyperopt',
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help='specify hyperopt class name (default: %(default)s)',
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dest='hyperopt',
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default=Constants.DEFAULT_HYPEROPT,
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type=str,
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metavar='PATH',
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metavar='NAME',
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)
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self.parser.add_argument(
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'--dynamic-whitelist',
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@ -9,7 +9,7 @@ TICKER_INTERVAL = 5 # min
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HYPEROPT_EPOCH = 100 # epochs
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RETRY_TIMEOUT = 30 # sec
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DEFAULT_STRATEGY = 'DefaultStrategy'
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DEFAULT_HYPEROPT = 'default_hyperopt'
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DEFAULT_HYPEROPT = 'DefaultHyperOpts'
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DEFAULT_DB_PROD_URL = 'sqlite:///tradesv3.sqlite'
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DEFAULT_DB_DRYRUN_URL = 'sqlite://'
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UNLIMITED_STAKE_AMOUNT = 'unlimited'
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@ -1,153 +0,0 @@
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# pragma pylint: disable=attribute-defined-outside-init
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"""
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This module load custom hyperopts
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"""
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import importlib
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import logging
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import os
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import sys
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from typing import Dict, Any, Callable
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from pandas import DataFrame
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from freqtrade.constants import Constants
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from freqtrade.optimize.interface import IHyperOpt
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sys.path.insert(0, r'../../user_data/hyperopts')
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logger = logging.getLogger(__name__)
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class CustomHyperOpt(object):
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"""
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This class contains all the logic to load custom hyperopt class
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"""
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def __init__(self, config: dict = {}) -> None:
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"""
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Load the custom class from config parameter
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:param config:
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:return:
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"""
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# Verify the hyperopt is in the configuration, otherwise fallback to the default hyperopt
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if 'hyperopt' in config:
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hyperopt = config['hyperopt']
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else:
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hyperopt = Constants.DEFAULT_HYPEROPT
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# Load the hyperopt
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self._load_hyperopt(hyperopt)
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def _load_hyperopt(self, hyperopt_name: str) -> None:
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"""
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Search and load the custom hyperopt. If no hyperopt found, fallback on the default hyperopt
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Set the object into self.custom_hyperopt
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:param hyperopt_name: name of the module to import
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:return: None
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"""
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try:
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# Start by sanitizing the file name (remove any extensions)
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hyperopt_name = self._sanitize_module_name(filename=hyperopt_name)
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# Search where can be the hyperopt file
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path = self._search_hyperopt(filename=hyperopt_name)
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# Load the hyperopt
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self.custom_hyperopt = self._load_class(path + hyperopt_name)
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# Fallback to the default hyperopt
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except (ImportError, TypeError) as error:
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logger.error(
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"Impossible to load Hyperopt 'user_data/hyperopts/%s.py'. This file does not exist"
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" or contains Python code errors",
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hyperopt_name
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)
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logger.error(
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"The error is:\n%s.",
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error
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)
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def _load_class(self, filename: str) -> IHyperOpt:
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"""
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Import a hyperopt as a module
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:param filename: path to the hyperopt (path from freqtrade/optimize/)
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:return: return the hyperopt class
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"""
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module = importlib.import_module(filename, __package__)
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custom_hyperopt = getattr(module, module.class_name)
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logger.info("Load hyperopt class: %s (%s.py)", module.class_name, filename)
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return custom_hyperopt()
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@staticmethod
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def _sanitize_module_name(filename: str) -> str:
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"""
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Remove any extension from filename
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:param filename: filename to sanatize
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:return: return the filename without extensions
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"""
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filename = os.path.basename(filename)
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filename = os.path.splitext(filename)[0]
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return filename
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@staticmethod
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def _search_hyperopt(filename: str) -> str:
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"""
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Search for the hyperopt file in different folder
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1. search into the user_data/hyperopts folder
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2. search into the freqtrade/optimize folder
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3. if nothing found, return None
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:param hyperopt_name: module name to search
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:return: module path where is the hyperopt
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"""
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pwd = os.path.dirname(os.path.realpath(__file__)) + '/'
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user_data = os.path.join(pwd, '..', '..', 'user_data', 'hyperopts', filename + '.py')
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hyperopt_folder = os.path.join(pwd, filename + '.py')
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path = None
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if os.path.isfile(user_data):
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path = 'user_data.hyperopts.'
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elif os.path.isfile(hyperopt_folder):
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path = '.'
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return path
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def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
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"""
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Populate indicators that will be used in the Buy and Sell hyperopt
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:param dataframe: Raw data from the exchange and parsed by parse_ticker_dataframe()
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:return: a Dataframe with all mandatory indicators for the strategies
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"""
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return self.custom_hyperopt.populate_indicators(dataframe)
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def buy_strategy_generator(self, params: Dict[str, Any]) -> Callable:
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"""
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Create a buy strategy generator
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"""
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return self.custom_hyperopt.buy_strategy_generator(params)
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def indicator_space(self) -> Dict[str, Any]:
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"""
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Create an indicator space
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"""
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return self.custom_hyperopt.indicator_space()
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def generate_roi_table(self, params: Dict) -> Dict[int, float]:
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"""
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Create an roi table
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"""
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return self.custom_hyperopt.generate_roi_table(params)
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def stoploss_space(self) -> Dict[str, Any]:
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"""
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Create a stoploss space
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"""
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return self.custom_hyperopt.stoploss_space()
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def roi_space(self) -> Dict[str, Any]:
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"""
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Create a roi space
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"""
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return self.custom_hyperopt.roi_space()
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@ -22,7 +22,8 @@ from freqtrade.arguments import Arguments
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from freqtrade.configuration import Configuration
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from freqtrade.optimize import load_data
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from freqtrade.optimize.backtesting import Backtesting
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from freqtrade.optimize.custom_hyperopt import CustomHyperOpt
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from freqtrade.optimize.resolver import HyperOptResolver
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logger = logging.getLogger(__name__)
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@ -40,8 +41,8 @@ class Hyperopt(Backtesting):
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"""
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def __init__(self, config: Dict[str, Any]) -> None:
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super().__init__(config)
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self.custom_hyperopt = CustomHyperOpt(self.config)
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self.config = config
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self.custom_hyperopt = HyperOptResolver(self.config).hyperopt
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# set TARGET_TRADES to suit your number concurrent trades so its realistic
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# to the number of days
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@ -0,0 +1,104 @@
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# pragma pylint: disable=attribute-defined-outside-init
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"""
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This module load custom hyperopts
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"""
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import importlib.util
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import inspect
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import logging
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import os
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from typing import Optional, Dict, Type
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from freqtrade.constants import Constants
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from freqtrade.optimize.interface import IHyperOpt
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logger = logging.getLogger(__name__)
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class HyperOptResolver(object):
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"""
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This class contains all the logic to load custom hyperopt class
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"""
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__slots__ = ['hyperopt']
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def __init__(self, config: Optional[Dict] = None) -> None:
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"""
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Load the custom class from config parameter
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:param config: configuration dictionary or None
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"""
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config = config or {}
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# Verify the hyperopt is in the configuration, otherwise fallback to the default hyperopt
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hyperopt_name = config.get('hyperopt') or Constants.DEFAULT_HYPEROPT
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self.hyperopt = self._load_hyperopt(hyperopt_name, extra_dir=config.get('hyperopt_path'))
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def _load_hyperopt(
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self, hyperopt_name: str, extra_dir: Optional[str] = None) -> Optional[IHyperOpt]:
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"""
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Search and loads the specified hyperopt.
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:param hyperopt_name: name of the module to import
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:param extra_dir: additional directory to search for the given hyperopt
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:return: HyperOpt instance or None
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"""
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current_path = os.path.dirname(os.path.realpath(__file__))
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abs_paths = [
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os.path.join(current_path, '..', '..', 'user_data', 'hyperopts'),
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current_path,
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]
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if extra_dir:
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# Add extra hyperopt directory on top of search paths
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abs_paths.insert(0, extra_dir)
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for path in abs_paths:
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hyperopt = self._search_hyperopt(path, hyperopt_name)
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if hyperopt:
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logger.info('Using resolved hyperopt %s from \'%s\'', hyperopt_name, path)
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return hyperopt
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raise ImportError(
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"Impossible to load Hyperopt '{}'. This class does not exist"
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" or contains Python code errors".format(hyperopt_name)
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)
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@staticmethod
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def _get_valid_hyperopts(module_path: str, hyperopt_name: str) -> Optional[Type[IHyperOpt]]:
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"""
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Returns a list of all possible hyperopts for the given module_path
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:param module_path: absolute path to the module
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:param hyperopt_name: Class name of the hyperopt
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:return: Tuple with (name, class) or None
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"""
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# Generate spec based on absolute path
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spec = importlib.util.spec_from_file_location('user_data.hyperopts', module_path)
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module = importlib.util.module_from_spec(spec)
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spec.loader.exec_module(module)
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valid_hyperopts_gen = (
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obj for name, obj in inspect.getmembers(module, inspect.isclass)
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if hyperopt_name == name and IHyperOpt in obj.__bases__
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)
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return next(valid_hyperopts_gen, None)
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@staticmethod
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def _search_hyperopt(directory: str, hyperopt_name: str) -> Optional[IHyperOpt]:
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"""
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Search for the hyperopt_name in the given directory
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:param directory: relative or absolute directory path
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:return: name of the hyperopt class
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"""
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logger.debug('Searching for hyperopt %s in \'%s\'', hyperopt_name, directory)
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for entry in os.listdir(directory):
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# Only consider python files
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if not entry.endswith('.py'):
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logger.debug('Ignoring %s', entry)
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continue
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hyperopt = HyperOptResolver._get_valid_hyperopts(
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os.path.abspath(os.path.join(directory, entry)), hyperopt_name
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)
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if hyperopt:
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return hyperopt()
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return None
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@ -15,10 +15,6 @@ from freqtrade.indicator_helpers import fishers_inverse
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from freqtrade.optimize.interface import IHyperOpt
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# Update this variable if you change the class name
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class_name = 'TestHyperOpt'
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# This class is a sample. Feel free to customize it.
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class TestHyperOpt(IHyperOpt):
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"""
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