diff --git a/docs/strategy-advanced.md b/docs/strategy-advanced.md index 3793abacf..533402528 100644 --- a/docs/strategy-advanced.md +++ b/docs/strategy-advanced.md @@ -146,7 +146,7 @@ def version(self) -> str: The strategies can be derived from other strategies. This avoids duplication of your custom strategy code. You can use this technique to override small parts of your main strategy, leaving the rest untouched: -``` python +``` python title="user_data/strategies/myawesomestrategy.py" class MyAwesomeStrategy(IStrategy): ... stoploss = 0.13 @@ -155,6 +155,10 @@ class MyAwesomeStrategy(IStrategy): # should be in any custom strategy... ... +``` + +``` python title="user_data/strategies/MyAwesomeStrategy2.py" +from myawesomestrategy import MyAwesomeStrategy class MyAwesomeStrategy2(MyAwesomeStrategy): # Override something stoploss = 0.08 @@ -163,15 +167,13 @@ class MyAwesomeStrategy2(MyAwesomeStrategy): Both attributes and methods may be overridden, altering behavior of the original strategy in a way you need. +While keeping the subclass in the same file is technically possible, it can lead to some problems with hyperopt parameter files. + !!! Note "Parent-strategy in different files" - If you have the parent-strategy in a different file, you'll need to add the following to the top of your "child"-file to ensure proper loading, otherwise freqtrade may not be able to load the parent strategy correctly. + If you have the parent-strategy in a different file, you can still import the strategy. + Assuming `myawesomestrategy.py` is the filename, and `MyAwesomeStrategy` the strategy you need to import: ``` python - import sys - from pathlib import Path - sys.path.append(str(Path(__file__).parent)) - - from myawesomestrategy import MyAwesomeStrategy ``` ## Embedding Strategies diff --git a/freqtrade/resolvers/iresolver.py b/freqtrade/resolvers/iresolver.py index c6f97c976..3ab461041 100644 --- a/freqtrade/resolvers/iresolver.py +++ b/freqtrade/resolvers/iresolver.py @@ -6,6 +6,7 @@ This module load custom objects import importlib.util import inspect import logging +import sys from pathlib import Path from typing import Any, Dict, Iterator, List, Optional, Tuple, Type, Union @@ -15,6 +16,22 @@ from freqtrade.exceptions import OperationalException logger = logging.getLogger(__name__) +class PathModifier: + def __init__(self, path: Path): + self.path = path + + def __enter__(self): + """Inject path to allow importing with relative imports.""" + sys.path.insert(0, str(self.path)) + return self + + def __exit__(self, exc_type, exc_val, exc_tb): + """Undo insertion of local path.""" + str_path = str(self.path) + if str_path in sys.path: + sys.path.remove(str_path) + + class IResolver: """ This class contains all the logic to load custom classes @@ -57,27 +74,32 @@ class IResolver: # Generate spec based on absolute path # Pass object_name as first argument to have logging print a reasonable name. - spec = importlib.util.spec_from_file_location(object_name or "", str(module_path)) - if not spec: - return iter([None]) - - module = importlib.util.module_from_spec(spec) - try: - spec.loader.exec_module(module) # type: ignore # importlib does not use typehints - except (ModuleNotFoundError, SyntaxError, ImportError, NameError) as err: - # Catch errors in case a specific module is not installed - logger.warning(f"Could not import {module_path} due to '{err}'") - if enum_failed: + with PathModifier(module_path.parent): + module_name = module_path.stem or "" + spec = importlib.util.spec_from_file_location(module_name, str(module_path)) + if not spec: return iter([None]) - valid_objects_gen = ( - (obj, inspect.getsource(module)) for - name, obj in inspect.getmembers( - module, inspect.isclass) if ((object_name is None or object_name == name) - and issubclass(obj, cls.object_type) - and obj is not cls.object_type) - ) - return valid_objects_gen + module = importlib.util.module_from_spec(spec) + try: + spec.loader.exec_module(module) # type: ignore # importlib does not use typehints + except (ModuleNotFoundError, SyntaxError, ImportError, NameError) as err: + # Catch errors in case a specific module is not installed + logger.warning(f"Could not import {module_path} due to '{err}'") + if enum_failed: + return iter([None]) + + valid_objects_gen = ( + (obj, inspect.getsource(module)) for + name, obj in inspect.getmembers( + module, inspect.isclass) if ((object_name is None or object_name == name) + and issubclass(obj, cls.object_type) + and obj is not cls.object_type + and obj.__module__ == module_name + ) + ) + # The __module__ check ensures we only use strategies that are defined in this folder. + return valid_objects_gen @classmethod def _search_object(cls, directory: Path, *, object_name: str, add_source: bool = False diff --git a/tests/strategy/strats/hyperoptable_strategy.py b/tests/strategy/strats/hyperoptable_strategy.py index 88bdd078e..dc6b03a3e 100644 --- a/tests/strategy/strats/hyperoptable_strategy.py +++ b/tests/strategy/strats/hyperoptable_strategy.py @@ -1,14 +1,13 @@ # pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement -import talib.abstract as ta from pandas import DataFrame +from strategy_test_v2 import StrategyTestV2 import freqtrade.vendor.qtpylib.indicators as qtpylib -from freqtrade.strategy import (BooleanParameter, DecimalParameter, IntParameter, IStrategy, - RealParameter) +from freqtrade.strategy import BooleanParameter, DecimalParameter, IntParameter, RealParameter -class HyperoptableStrategy(IStrategy): +class HyperoptableStrategy(StrategyTestV2): """ Default Strategy provided by freqtrade bot. Please do not modify this strategy, it's intended for internal use only. @@ -16,38 +15,6 @@ class HyperoptableStrategy(IStrategy): or strategy repository https://github.com/freqtrade/freqtrade-strategies for samples and inspiration. """ - INTERFACE_VERSION = 2 - - # Minimal ROI designed for the strategy - minimal_roi = { - "40": 0.0, - "30": 0.01, - "20": 0.02, - "0": 0.04 - } - - # Optimal stoploss designed for the strategy - stoploss = -0.10 - - # Optimal ticker interval for the strategy - timeframe = '5m' - - # Optional order type mapping - order_types = { - 'buy': 'limit', - 'sell': 'limit', - 'stoploss': 'limit', - 'stoploss_on_exchange': False - } - - # Number of candles the strategy requires before producing valid signals - startup_candle_count: int = 20 - - # Optional time in force for orders - order_time_in_force = { - 'buy': 'gtc', - 'sell': 'gtc', - } buy_params = { 'buy_rsi': 35, @@ -91,55 +58,6 @@ class HyperoptableStrategy(IStrategy): """ return [] - def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: - """ - Adds several different TA indicators to the given DataFrame - - Performance Note: For the best performance be frugal on the number of indicators - you are using. Let uncomment only the indicator you are using in your strategies - or your hyperopt configuration, otherwise you will waste your memory and CPU usage. - :param dataframe: Dataframe with data from the exchange - :param metadata: Additional information, like the currently traded pair - :return: a Dataframe with all mandatory indicators for the strategies - """ - - # Momentum Indicator - # ------------------------------------ - - # ADX - dataframe['adx'] = ta.ADX(dataframe) - - # MACD - macd = ta.MACD(dataframe) - dataframe['macd'] = macd['macd'] - dataframe['macdsignal'] = macd['macdsignal'] - dataframe['macdhist'] = macd['macdhist'] - - # Minus Directional Indicator / Movement - dataframe['minus_di'] = ta.MINUS_DI(dataframe) - - # Plus Directional Indicator / Movement - dataframe['plus_di'] = ta.PLUS_DI(dataframe) - - # RSI - dataframe['rsi'] = ta.RSI(dataframe) - - # Stoch fast - stoch_fast = ta.STOCHF(dataframe) - dataframe['fastd'] = stoch_fast['fastd'] - dataframe['fastk'] = stoch_fast['fastk'] - - # Bollinger bands - bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2) - dataframe['bb_lowerband'] = bollinger['lower'] - dataframe['bb_middleband'] = bollinger['mid'] - dataframe['bb_upperband'] = bollinger['upper'] - - # EMA - Exponential Moving Average - dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10) - - return dataframe - def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame: """ Based on TA indicators, populates the buy signal for the given dataframe diff --git a/tests/strategy/strats/strategy_test_v2.py b/tests/strategy/strats/strategy_test_v2.py index c57becdad..59f1f569e 100644 --- a/tests/strategy/strats/strategy_test_v2.py +++ b/tests/strategy/strats/strategy_test_v2.py @@ -7,7 +7,7 @@ from pandas import DataFrame import freqtrade.vendor.qtpylib.indicators as qtpylib from freqtrade.persistence import Trade -from freqtrade.strategy.interface import IStrategy +from freqtrade.strategy import IStrategy class StrategyTestV2(IStrategy):