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Merge pull request #6560 from freqtrade/inject_path_iresolver

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Inject path to strategy loading
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Matthias 2022-03-21 19:09:14 +01:00 committed by GitHub
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4 changed files with 54 additions and 112 deletions
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16
docs/strategy-advanced.md
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@ -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

26
freqtrade/resolvers/iresolver.py
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@ -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
@ -57,7 +74,9 @@ 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))
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])
@ -75,8 +94,11 @@ class IResolver:
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 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

88
tests/strategy/strats/hyperoptable_strategy.py
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@ -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

2
tests/strategy/strats/strategy_test_v2.py
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@ -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):