stable/freqtrade/strategy/strategy.py

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# pragma pylint: disable=attribute-defined-outside-init
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"""
This module load custom strategies
"""
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import os
import sys
import logging
import importlib
from pandas import DataFrame
from freqtrade.strategy.interface import IStrategy
sys.path.insert(0, r'../../user_data/strategies')
class Strategy(object):
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"""
This class contains all the logic to load custom strategy class
"""
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__instance = None
DEFAULT_STRATEGY = 'default_strategy'
def __new__(cls) -> object:
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"""
Used to create the Singleton
:return: Strategy object
"""
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if Strategy.__instance is None:
Strategy.__instance = object.__new__(cls)
return Strategy.__instance
def init(self, config: dict) -> None:
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"""
Load the custom class from config parameter
:param config:
:return:
"""
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self.logger = logging.getLogger(__name__)
# Verify the strategy is in the configuration, otherwise fallback to the default strategy
if 'strategy' in config:
strategy = config['strategy']
else:
strategy = self.DEFAULT_STRATEGY
# Load the strategy
self._load_strategy(strategy)
# Set attributes
# Check if we need to override configuration
if 'minimal_roi' in config:
self.custom_strategy.minimal_roi = config['minimal_roi']
self.logger.info("Override strategy \'minimal_roi\' with value in config file.")
if 'stoploss' in config:
self.custom_strategy.stoploss = config['stoploss']
self.logger.info(
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"Override strategy \'stoploss\' with value in config file: %s.", config['stoploss']
)
if 'ticker_interval' in config:
self.custom_strategy.ticker_interval = config['ticker_interval']
self.logger.info(
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"Override strategy \'ticker_interval\' with value in config file: %s.",
config['ticker_interval']
)
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# Minimal ROI designed for the strategy
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self.minimal_roi = self.custom_strategy.minimal_roi
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# Optimal stoploss designed for the strategy
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self.stoploss = self.custom_strategy.stoploss
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self.ticker_interval = self.custom_strategy.ticker_interval
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def _load_strategy(self, strategy_name: str) -> None:
"""
Search and load the custom strategy. If no strategy found, fallback on the default strategy
Set the object into self.custom_strategy
:param strategy_name: name of the module to import
:return: None
"""
try:
# Start by sanitizing the file name (remove any extensions)
strategy_name = self._sanitize_module_name(filename=strategy_name)
# Search where can be the strategy file
path = self._search_strategy(filename=strategy_name)
# Load the strategy
self.custom_strategy = self._load_class(path + strategy_name)
# Fallback to the default strategy
except (ImportError, TypeError):
self.custom_strategy = self._load_class('.' + self.DEFAULT_STRATEGY)
def _load_class(self, filename: str) -> IStrategy:
"""
Import a strategy as a module
:param filename: path to the strategy (path from freqtrade/strategy/)
:return: return the strategy class
"""
module = importlib.import_module(filename, __package__)
custom_strategy = getattr(module, module.class_name)
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self.logger.info("Load strategy class: %s (%s.py)", module.class_name, filename)
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return custom_strategy()
@staticmethod
def _sanitize_module_name(filename: str) -> str:
"""
Remove any extension from filename
:param filename: filename to sanatize
:return: return the filename without extensions
"""
filename = os.path.basename(filename)
filename = os.path.splitext(filename)[0]
return filename
@staticmethod
def _search_strategy(filename: str) -> str:
"""
Search for the Strategy file in different folder
1. search into the user_data/strategies folder
2. search into the freqtrade/strategy folder
3. if nothing found, return None
:param strategy_name: module name to search
:return: module path where is the strategy
"""
pwd = os.path.dirname(os.path.realpath(__file__)) + '/'
user_data = os.path.join(pwd, '..', '..', 'user_data', 'strategies', filename + '.py')
strategy_folder = os.path.join(pwd, filename + '.py')
path = None
if os.path.isfile(user_data):
path = 'user_data.strategies.'
elif os.path.isfile(strategy_folder):
path = '.'
return path
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
"""
Populate indicators that will be used in the Buy and Sell strategy
:param dataframe: Raw data from the exchange and parsed by parse_ticker_dataframe()
:return: a Dataframe with all mandatory indicators for the strategies
"""
return self.custom_strategy.populate_indicators(dataframe)
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
"""
Based on TA indicators, populates the buy signal for the given dataframe
:param dataframe: DataFrame
:return: DataFrame with buy column
:return:
"""
return self.custom_strategy.populate_buy_trend(dataframe)
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
"""
Based on TA indicators, populates the sell signal for the given dataframe
:param dataframe: DataFrame
:return: DataFrame with buy column
"""
return self.custom_strategy.populate_sell_trend(dataframe)