Remove unused test-strategy

This commit is contained in:
Matthias 2022-07-27 06:47:16 +02:00
parent a0b9388757
commit 2595e40e47
3 changed files with 3 additions and 179 deletions

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@ -1402,7 +1402,6 @@ def test_api_strategies(botclient):
'InformativeDecoratorTest', 'InformativeDecoratorTest',
'StrategyTestV2', 'StrategyTestV2',
'StrategyTestV3', 'StrategyTestV3',
'StrategyTestV3Analysis',
'StrategyTestV3Futures' 'StrategyTestV3Futures'
]} ]}

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@ -1,175 +0,0 @@
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
import talib.abstract as ta
from pandas import DataFrame
import freqtrade.vendor.qtpylib.indicators as qtpylib
from freqtrade.strategy import (BooleanParameter, DecimalParameter, IntParameter, IStrategy,
RealParameter)
class StrategyTestV3Analysis(IStrategy):
"""
Strategy used by tests freqtrade bot.
Please do not modify this strategy, it's intended for internal use only.
Please look at the SampleStrategy in the user_data/strategy directory
or strategy repository https://github.com/freqtrade/freqtrade-strategies
for samples and inspiration.
"""
INTERFACE_VERSION = 3
# 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 timeframe for the strategy
timeframe = '5m'
# Optional order type mapping
order_types = {
'entry': 'limit',
'exit': '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 = {
'entry': 'gtc',
'exit': 'gtc',
}
buy_params = {
'buy_rsi': 35,
# Intentionally not specified, so "default" is tested
# 'buy_plusdi': 0.4
}
sell_params = {
'sell_rsi': 74,
'sell_minusdi': 0.4
}
buy_rsi = IntParameter([0, 50], default=30, space='buy')
buy_plusdi = RealParameter(low=0, high=1, default=0.5, space='buy')
sell_rsi = IntParameter(low=50, high=100, default=70, space='sell')
sell_minusdi = DecimalParameter(low=0, high=1, default=0.5001, decimals=3, space='sell',
load=False)
protection_enabled = BooleanParameter(default=True)
protection_cooldown_lookback = IntParameter([0, 50], default=30)
# TODO: Can this work with protection tests? (replace HyperoptableStrategy implicitly ... )
# @property
# def protections(self):
# prot = []
# if self.protection_enabled.value:
# prot.append({
# "method": "CooldownPeriod",
# "stop_duration_candles": self.protection_cooldown_lookback.value
# })
# return prot
bot_started = False
def bot_start(self):
self.bot_started = True
def informative_pairs(self):
return []
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# 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_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['rsi'] < self.buy_rsi.value) &
(dataframe['fastd'] < 35) &
(dataframe['adx'] > 30) &
(dataframe['plus_di'] > self.buy_plusdi.value)
) |
(
(dataframe['adx'] > 65) &
(dataframe['plus_di'] > self.buy_plusdi.value)
),
['enter_long', 'enter_tag']] = 1, 'enter_tag_long'
dataframe.loc[
(
qtpylib.crossed_below(dataframe['rsi'], self.sell_rsi.value)
),
['enter_short', 'enter_tag']] = 1, 'enter_tag_short'
return dataframe
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(
(qtpylib.crossed_above(dataframe['rsi'], self.sell_rsi.value)) |
(qtpylib.crossed_above(dataframe['fastd'], 70))
) &
(dataframe['adx'] > 10) &
(dataframe['minus_di'] > 0)
) |
(
(dataframe['adx'] > 70) &
(dataframe['minus_di'] > self.sell_minusdi.value)
),
['exit_long', 'exit_tag']] = 1, 'exit_tag_long'
dataframe.loc[
(
qtpylib.crossed_above(dataframe['rsi'], self.buy_rsi.value)
),
['exit_long', 'exit_tag']] = 1, 'exit_tag_short'
return dataframe

View File

@ -34,7 +34,7 @@ def test_search_all_strategies_no_failed():
directory = Path(__file__).parent / "strats" directory = Path(__file__).parent / "strats"
strategies = StrategyResolver.search_all_objects(directory, enum_failed=False) strategies = StrategyResolver.search_all_objects(directory, enum_failed=False)
assert isinstance(strategies, list) assert isinstance(strategies, list)
assert len(strategies) == 7 assert len(strategies) == 6
assert isinstance(strategies[0], dict) assert isinstance(strategies[0], dict)
@ -42,10 +42,10 @@ def test_search_all_strategies_with_failed():
directory = Path(__file__).parent / "strats" directory = Path(__file__).parent / "strats"
strategies = StrategyResolver.search_all_objects(directory, enum_failed=True) strategies = StrategyResolver.search_all_objects(directory, enum_failed=True)
assert isinstance(strategies, list) assert isinstance(strategies, list)
assert len(strategies) == 8 assert len(strategies) == 7
# with enum_failed=True search_all_objects() shall find 2 good strategies # with enum_failed=True search_all_objects() shall find 2 good strategies
# and 1 which fails to load # and 1 which fails to load
assert len([x for x in strategies if x['class'] is not None]) == 7 assert len([x for x in strategies if x['class'] is not None]) == 6
assert len([x for x in strategies if x['class'] is None]) == 1 assert len([x for x in strategies if x['class'] is None]) == 1