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Add some simple tests for hyperoptParameters

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This commit is contained in:
Matthias 2021-03-27 11:26:26 +01:00
parent 786ddc6a91
commit 71e2134694
5 changed files with 224 additions and 10 deletions
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14
freqtrade/strategy/hyper.py
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@ -67,8 +67,10 @@ class IntParameter(BaseParameter):
parameter fieldname is prefixed with 'buy_' or 'sell_'.
:param kwargs: Extra parameters to skopt.space.Integer.
"""
if high is None:
if len(low) != 2:
if high is not None and isinstance(low, Sequence):
raise OperationalException('IntParameter space invalid.')
if high is None or isinstance(low, Sequence):
if not isinstance(low, Sequence) or len(low) != 2:
raise OperationalException('IntParameter space must be [low, high]')
opt_range = low
else:
@ -101,9 +103,11 @@ class FloatParameter(BaseParameter):
parameter fieldname is prefixed with 'buy_' or 'sell_'.
:param kwargs: Extra parameters to skopt.space.Real.
"""
if high is None:
if len(low) != 2:
raise OperationalException('IntParameter space must be [low, high]')
if high is not None and isinstance(low, Sequence):
raise OperationalException('FloatParameter space invalid.')
if high is None or isinstance(low, Sequence):
if not isinstance(low, Sequence) or len(low) != 2:
raise OperationalException('FloatParameter space must be [low, high]')
opt_range = low
else:
opt_range = [low, high]

6
tests/rpc/test_rpc_apiserver.py
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@ -1149,7 +1149,11 @@ def test_api_strategies(botclient):
rc = client_get(client, f"{BASE_URI}/strategies")
assert_response(rc)
assert rc.json() == {'strategies': ['DefaultStrategy', 'TestStrategyLegacy']}
assert rc.json() == {'strategies': [
'DefaultStrategy',
'HyperoptableStrategy',
'TestStrategyLegacy'
]}
def test_api_strategy(botclient):

170
tests/strategy/strats/hyperoptable_strategy.py Normal file
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@ -0,0 +1,170 @@
# 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 FloatParameter, IntParameter, IStrategy
class HyperoptableStrategy(IStrategy):
"""
Default Strategy provided by 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 = 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,
# Intentionally not specified, so "default" is tested
# 'buy_plusdi': 0.4
}
sell_params = {
'sell_rsi': 74
}
buy_rsi = IntParameter([0, 50], default=30, space='buy')
buy_plusdi = FloatParameter(low=0, high=1, default=0.5, space='buy')
sell_rsi = IntParameter(low=50, high=100, default=70, space='sell')
def informative_pairs(self):
"""
Define additional, informative pair/interval combinations to be cached from the exchange.
These pair/interval combinations are non-tradeable, unless they are part
of the whitelist as well.
For more information, please consult the documentation
:return: List of tuples in the format (pair, interval)
Sample: return [("ETH/USDT", "5m"),
("BTC/USDT", "15m"),
]
"""
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
:param dataframe: DataFrame
:param metadata: Additional information, like the currently traded pair
:return: DataFrame with buy column
"""
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)
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Based on TA indicators, populates the sell signal for the given dataframe
:param dataframe: DataFrame
:param metadata: Additional information, like the currently traded pair
:return: DataFrame with buy column
"""
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'] > 0.5)
),
'sell'] = 1
return dataframe

38
tests/strategy/test_interface.py
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@ -1,4 +1,5 @@
# pragma pylint: disable=missing-docstring, C0103
from freqtrade.strategy.hyper import BaseParameter, FloatParameter, IntParameter
import logging
from datetime import datetime, timedelta, timezone
from unittest.mock import MagicMock
@ -10,7 +11,7 @@ from pandas import DataFrame
from freqtrade.configuration import TimeRange
from freqtrade.data.dataprovider import DataProvider
from freqtrade.data.history import load_data
from freqtrade.exceptions import StrategyError
from freqtrade.exceptions import OperationalException, StrategyError
from freqtrade.persistence import PairLocks, Trade
from freqtrade.resolvers import StrategyResolver
from freqtrade.strategy.interface import SellCheckTuple, SellType
@ -552,3 +553,38 @@ def test_strategy_safe_wrapper(value):
assert type(ret) == type(value)
assert ret == value
def test_hyperopt_parameters():
with pytest.raises(OperationalException, match=r"Name is determined.*"):
IntParameter(low=0, high=5, default=1, name='hello')
with pytest.raises(OperationalException, match=r"IntParameter space must be.*"):
IntParameter(low=0, default=5, space='buy')
with pytest.raises(OperationalException, match=r"FloatParameter space must be.*"):
FloatParameter(low=0, default=5, space='buy')
with pytest.raises(OperationalException, match=r"IntParameter space invalid\."):
IntParameter([0, 10], high=7, default=5, space='buy')
with pytest.raises(OperationalException, match=r"FloatParameter space invalid\."):
FloatParameter([0, 10], high=7, default=5, space='buy')
x = BaseParameter(opt_range=[0, 1], default=1, space='buy')
with pytest.raises(NotImplementedError):
x.get_space('space')
fltpar = IntParameter(low=0, high=5, default=1, space='buy')
assert fltpar.value == 1
def test_auto_hyperopt_interface(default_conf):
default_conf.update({'strategy': 'HyperoptableStrategy'})
PairLocks.timeframe = default_conf['timeframe']
strategy = StrategyResolver.load_strategy(default_conf)
assert strategy.buy_rsi.value == strategy.buy_params['buy_rsi']
# PlusDI is NOT in the buy-params, so default should be used
assert strategy.buy_plusdi.value == 0.5
assert strategy.sell_rsi.value == strategy.sell_params['sell_rsi']

6
tests/strategy/test_strategy_loading.py
View File

@ -35,7 +35,7 @@ def test_search_all_strategies_no_failed():
directory = Path(__file__).parent / "strats"
strategies = StrategyResolver.search_all_objects(directory, enum_failed=False)
assert isinstance(strategies, list)
assert len(strategies) == 2
assert len(strategies) == 3
assert isinstance(strategies[0], dict)
@ -43,10 +43,10 @@ def test_search_all_strategies_with_failed():
directory = Path(__file__).parent / "strats"
strategies = StrategyResolver.search_all_objects(directory, enum_failed=True)
assert isinstance(strategies, list)
assert len(strategies) == 3
assert len(strategies) == 4
# with enum_failed=True search_all_objects() shall find 2 good strategies
# and 1 which fails to load
assert len([x for x in strategies if x['class'] is not None]) == 2
assert len([x for x in strategies if x['class'] is not None]) == 3
assert len([x for x in strategies if x['class'] is None]) == 1