Merge branch 'develop' into BASE64
This commit is contained in:
Matthias
GitHub
235
freqtrade/tests/strategy/legacy_strategy.py
Normal file
235
freqtrade/tests/strategy/legacy_strategy.py
Normal file
@@ -0,0 +1,235 @@
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# --- Do not remove these libs ---
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from freqtrade.strategy.interface import IStrategy
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from pandas import DataFrame
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# --------------------------------
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# Add your lib to import here
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import talib.abstract as ta
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import freqtrade.vendor.qtpylib.indicators as qtpylib
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import numpy # noqa
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# This class is a sample. Feel free to customize it.
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class TestStrategyLegacy(IStrategy):
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"""
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This is a test strategy using the legacy function headers, which will be
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removed in a future update.
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Please do not use this as a template, but refer to user_data/strategy/TestStrategy.py
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for a uptodate version of this template.
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"""
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# Minimal ROI designed for the strategy.
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# This attribute will be overridden if the config file contains "minimal_roi"
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minimal_roi = {
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"40": 0.0,
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"30": 0.01,
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"20": 0.02,
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"0": 0.04
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}
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# Optimal stoploss designed for the strategy
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# This attribute will be overridden if the config file contains "stoploss"
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stoploss = -0.10
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# Optimal ticker interval for the strategy
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ticker_interval = '5m'
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def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
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"""
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Adds several different TA indicators to the given DataFrame
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Performance Note: For the best performance be frugal on the number of indicators
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you are using. Let uncomment only the indicator you are using in your strategies
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or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
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"""
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# Momentum Indicator
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# ------------------------------------
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# ADX
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dataframe['adx'] = ta.ADX(dataframe)
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"""
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# Awesome oscillator
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dataframe['ao'] = qtpylib.awesome_oscillator(dataframe)
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# Commodity Channel Index: values Oversold:<-100, Overbought:>100
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dataframe['cci'] = ta.CCI(dataframe)
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# MACD
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macd = ta.MACD(dataframe)
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dataframe['macd'] = macd['macd']
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dataframe['macdsignal'] = macd['macdsignal']
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dataframe['macdhist'] = macd['macdhist']
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# MFI
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dataframe['mfi'] = ta.MFI(dataframe)
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# Minus Directional Indicator / Movement
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dataframe['minus_dm'] = ta.MINUS_DM(dataframe)
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dataframe['minus_di'] = ta.MINUS_DI(dataframe)
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# Plus Directional Indicator / Movement
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dataframe['plus_dm'] = ta.PLUS_DM(dataframe)
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dataframe['plus_di'] = ta.PLUS_DI(dataframe)
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dataframe['minus_di'] = ta.MINUS_DI(dataframe)
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# ROC
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dataframe['roc'] = ta.ROC(dataframe)
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# RSI
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dataframe['rsi'] = ta.RSI(dataframe)
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# Inverse Fisher transform on RSI, values [-1.0, 1.0] (https://goo.gl/2JGGoy)
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rsi = 0.1 * (dataframe['rsi'] - 50)
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dataframe['fisher_rsi'] = (numpy.exp(2 * rsi) - 1) / (numpy.exp(2 * rsi) + 1)
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# Inverse Fisher transform on RSI normalized, value [0.0, 100.0] (https://goo.gl/2JGGoy)
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dataframe['fisher_rsi_norma'] = 50 * (dataframe['fisher_rsi'] + 1)
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# Stoch
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stoch = ta.STOCH(dataframe)
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dataframe['slowd'] = stoch['slowd']
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dataframe['slowk'] = stoch['slowk']
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# Stoch fast
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stoch_fast = ta.STOCHF(dataframe)
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dataframe['fastd'] = stoch_fast['fastd']
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dataframe['fastk'] = stoch_fast['fastk']
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# Stoch RSI
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stoch_rsi = ta.STOCHRSI(dataframe)
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dataframe['fastd_rsi'] = stoch_rsi['fastd']
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dataframe['fastk_rsi'] = stoch_rsi['fastk']
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"""
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# Overlap Studies
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# ------------------------------------
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# Bollinger bands
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bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
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dataframe['bb_lowerband'] = bollinger['lower']
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dataframe['bb_middleband'] = bollinger['mid']
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dataframe['bb_upperband'] = bollinger['upper']
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"""
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# EMA - Exponential Moving Average
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dataframe['ema3'] = ta.EMA(dataframe, timeperiod=3)
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dataframe['ema5'] = ta.EMA(dataframe, timeperiod=5)
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dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)
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dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50)
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dataframe['ema100'] = ta.EMA(dataframe, timeperiod=100)
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# SAR Parabol
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dataframe['sar'] = ta.SAR(dataframe)
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# SMA - Simple Moving Average
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dataframe['sma'] = ta.SMA(dataframe, timeperiod=40)
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"""
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# TEMA - Triple Exponential Moving Average
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dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)
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# Cycle Indicator
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# ------------------------------------
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# Hilbert Transform Indicator - SineWave
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hilbert = ta.HT_SINE(dataframe)
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dataframe['htsine'] = hilbert['sine']
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dataframe['htleadsine'] = hilbert['leadsine']
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# Pattern Recognition - Bullish candlestick patterns
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# ------------------------------------
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"""
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# Hammer: values [0, 100]
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dataframe['CDLHAMMER'] = ta.CDLHAMMER(dataframe)
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# Inverted Hammer: values [0, 100]
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dataframe['CDLINVERTEDHAMMER'] = ta.CDLINVERTEDHAMMER(dataframe)
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# Dragonfly Doji: values [0, 100]
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dataframe['CDLDRAGONFLYDOJI'] = ta.CDLDRAGONFLYDOJI(dataframe)
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# Piercing Line: values [0, 100]
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dataframe['CDLPIERCING'] = ta.CDLPIERCING(dataframe) # values [0, 100]
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# Morningstar: values [0, 100]
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dataframe['CDLMORNINGSTAR'] = ta.CDLMORNINGSTAR(dataframe) # values [0, 100]
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# Three White Soldiers: values [0, 100]
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dataframe['CDL3WHITESOLDIERS'] = ta.CDL3WHITESOLDIERS(dataframe) # values [0, 100]
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"""
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# Pattern Recognition - Bearish candlestick patterns
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# ------------------------------------
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"""
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# Hanging Man: values [0, 100]
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dataframe['CDLHANGINGMAN'] = ta.CDLHANGINGMAN(dataframe)
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# Shooting Star: values [0, 100]
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dataframe['CDLSHOOTINGSTAR'] = ta.CDLSHOOTINGSTAR(dataframe)
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# Gravestone Doji: values [0, 100]
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dataframe['CDLGRAVESTONEDOJI'] = ta.CDLGRAVESTONEDOJI(dataframe)
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# Dark Cloud Cover: values [0, 100]
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dataframe['CDLDARKCLOUDCOVER'] = ta.CDLDARKCLOUDCOVER(dataframe)
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# Evening Doji Star: values [0, 100]
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dataframe['CDLEVENINGDOJISTAR'] = ta.CDLEVENINGDOJISTAR(dataframe)
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# Evening Star: values [0, 100]
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dataframe['CDLEVENINGSTAR'] = ta.CDLEVENINGSTAR(dataframe)
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"""
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# Pattern Recognition - Bullish/Bearish candlestick patterns
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# ------------------------------------
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"""
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# Three Line Strike: values [0, -100, 100]
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dataframe['CDL3LINESTRIKE'] = ta.CDL3LINESTRIKE(dataframe)
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# Spinning Top: values [0, -100, 100]
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dataframe['CDLSPINNINGTOP'] = ta.CDLSPINNINGTOP(dataframe) # values [0, -100, 100]
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# Engulfing: values [0, -100, 100]
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dataframe['CDLENGULFING'] = ta.CDLENGULFING(dataframe) # values [0, -100, 100]
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# Harami: values [0, -100, 100]
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dataframe['CDLHARAMI'] = ta.CDLHARAMI(dataframe) # values [0, -100, 100]
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# Three Outside Up/Down: values [0, -100, 100]
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dataframe['CDL3OUTSIDE'] = ta.CDL3OUTSIDE(dataframe) # values [0, -100, 100]
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# Three Inside Up/Down: values [0, -100, 100]
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dataframe['CDL3INSIDE'] = ta.CDL3INSIDE(dataframe) # values [0, -100, 100]
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"""
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# Chart type
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# ------------------------------------
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"""
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# Heikinashi stategy
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heikinashi = qtpylib.heikinashi(dataframe)
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dataframe['ha_open'] = heikinashi['open']
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dataframe['ha_close'] = heikinashi['close']
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dataframe['ha_high'] = heikinashi['high']
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dataframe['ha_low'] = heikinashi['low']
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"""
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return dataframe
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def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
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"""
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Based on TA indicators, populates the buy signal for the given dataframe
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:param dataframe: DataFrame
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:return: DataFrame with buy column
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"""
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dataframe.loc[
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(
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(dataframe['adx'] > 30) &
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(dataframe['tema'] <= dataframe['bb_middleband']) &
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(dataframe['tema'] > dataframe['tema'].shift(1))
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),
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'buy'] = 1
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return dataframe
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def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
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"""
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Based on TA indicators, populates the sell signal for the given dataframe
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:param dataframe: DataFrame
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:return: DataFrame with buy column
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"""
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dataframe.loc[
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(
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(dataframe['adx'] > 70) &
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(dataframe['tema'] > dataframe['bb_middleband']) &
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(dataframe['tema'] < dataframe['tema'].shift(1))
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),
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'sell'] = 1
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return dataframe
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@@ -3,14 +3,14 @@ import json
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import pytest
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from pandas import DataFrame
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from freqtrade.analyze import Analyze
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from freqtrade.exchange.exchange_helpers import parse_ticker_dataframe
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from freqtrade.strategy.default_strategy import DefaultStrategy
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@pytest.fixture
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def result():
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with open('freqtrade/tests/testdata/ETH_BTC-1m.json') as data_file:
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return Analyze.parse_ticker_dataframe(json.load(data_file))
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return parse_ticker_dataframe(json.load(data_file))
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def test_default_strategy_structure():
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@@ -23,12 +23,13 @@ def test_default_strategy_structure():
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def test_default_strategy(result):
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strategy = DefaultStrategy()
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strategy = DefaultStrategy({})
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metadata = {'pair': 'ETH/BTC'}
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assert type(strategy.minimal_roi) is dict
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assert type(strategy.stoploss) is float
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assert type(strategy.ticker_interval) is str
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indicators = strategy.populate_indicators(result)
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indicators = strategy.populate_indicators(result, metadata)
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assert type(indicators) is DataFrame
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assert type(strategy.populate_buy_trend(indicators)) is DataFrame
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assert type(strategy.populate_sell_trend(indicators)) is DataFrame
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assert type(strategy.populate_buy_trend(indicators, metadata)) is DataFrame
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assert type(strategy.populate_sell_trend(indicators, metadata)) is DataFrame
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107
freqtrade/tests/strategy/test_interface.py
Normal file
107
freqtrade/tests/strategy/test_interface.py
Normal file
@@ -0,0 +1,107 @@
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# pragma pylint: disable=missing-docstring, C0103
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import logging
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from unittest.mock import MagicMock
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|
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import arrow
|
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from pandas import DataFrame
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from freqtrade.arguments import TimeRange
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from freqtrade.optimize.__init__ import load_tickerdata_file
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from freqtrade.tests.conftest import get_patched_exchange, log_has
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from freqtrade.strategy.default_strategy import DefaultStrategy
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# Avoid to reinit the same object again and again
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_STRATEGY = DefaultStrategy(config={})
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def test_returns_latest_buy_signal(mocker, default_conf):
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mocker.patch.object(
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_STRATEGY, 'analyze_ticker',
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return_value=DataFrame([{'buy': 1, 'sell': 0, 'date': arrow.utcnow()}])
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)
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assert _STRATEGY.get_signal('ETH/BTC', '5m', MagicMock()) == (True, False)
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|
||||
mocker.patch.object(
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||||
_STRATEGY, 'analyze_ticker',
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return_value=DataFrame([{'buy': 0, 'sell': 1, 'date': arrow.utcnow()}])
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)
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assert _STRATEGY.get_signal('ETH/BTC', '5m', MagicMock()) == (False, True)
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|
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def test_returns_latest_sell_signal(mocker, default_conf):
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||||
mocker.patch.object(
|
||||
_STRATEGY, 'analyze_ticker',
|
||||
return_value=DataFrame([{'sell': 1, 'buy': 0, 'date': arrow.utcnow()}])
|
||||
)
|
||||
|
||||
assert _STRATEGY.get_signal('ETH/BTC', '5m', MagicMock()) == (False, True)
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mocker.patch.object(
|
||||
_STRATEGY, 'analyze_ticker',
|
||||
return_value=DataFrame([{'sell': 0, 'buy': 1, 'date': arrow.utcnow()}])
|
||||
)
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assert _STRATEGY.get_signal('ETH/BTC', '5m', MagicMock()) == (True, False)
|
||||
|
||||
|
||||
def test_get_signal_empty(default_conf, mocker, caplog):
|
||||
assert (False, False) == _STRATEGY.get_signal('foo', default_conf['ticker_interval'],
|
||||
None)
|
||||
assert log_has('Empty ticker history for pair foo', caplog.record_tuples)
|
||||
|
||||
|
||||
def test_get_signal_exception_valueerror(default_conf, mocker, caplog):
|
||||
caplog.set_level(logging.INFO)
|
||||
mocker.patch.object(
|
||||
_STRATEGY, 'analyze_ticker',
|
||||
side_effect=ValueError('xyz')
|
||||
)
|
||||
assert (False, False) == _STRATEGY.get_signal('foo', default_conf['ticker_interval'], 1)
|
||||
assert log_has('Unable to analyze ticker for pair foo: xyz', caplog.record_tuples)
|
||||
|
||||
|
||||
def test_get_signal_empty_dataframe(default_conf, mocker, caplog):
|
||||
caplog.set_level(logging.INFO)
|
||||
mocker.patch.object(
|
||||
_STRATEGY, 'analyze_ticker',
|
||||
return_value=DataFrame([])
|
||||
)
|
||||
assert (False, False) == _STRATEGY.get_signal('xyz', default_conf['ticker_interval'], 1)
|
||||
assert log_has('Empty dataframe for pair xyz', caplog.record_tuples)
|
||||
|
||||
|
||||
def test_get_signal_old_dataframe(default_conf, mocker, caplog):
|
||||
caplog.set_level(logging.INFO)
|
||||
# default_conf defines a 5m interval. we check interval * 2 + 5m
|
||||
# this is necessary as the last candle is removed (partial candles) by default
|
||||
oldtime = arrow.utcnow().shift(minutes=-16)
|
||||
ticks = DataFrame([{'buy': 1, 'date': oldtime}])
|
||||
mocker.patch.object(
|
||||
_STRATEGY, 'analyze_ticker',
|
||||
return_value=DataFrame(ticks)
|
||||
)
|
||||
assert (False, False) == _STRATEGY.get_signal('xyz', default_conf['ticker_interval'], 1)
|
||||
assert log_has(
|
||||
'Outdated history for pair xyz. Last tick is 16 minutes old',
|
||||
caplog.record_tuples
|
||||
)
|
||||
|
||||
|
||||
def test_get_signal_handles_exceptions(mocker, default_conf):
|
||||
mocker.patch('freqtrade.exchange.Exchange.get_ticker_history', return_value=MagicMock())
|
||||
exchange = get_patched_exchange(mocker, default_conf)
|
||||
mocker.patch.object(
|
||||
_STRATEGY, 'analyze_ticker',
|
||||
side_effect=Exception('invalid ticker history ')
|
||||
)
|
||||
assert _STRATEGY.get_signal(exchange, 'ETH/BTC', '5m') == (False, False)
|
||||
|
||||
|
||||
def test_tickerdata_to_dataframe(default_conf) -> None:
|
||||
strategy = DefaultStrategy(default_conf)
|
||||
|
||||
timerange = TimeRange(None, 'line', 0, -100)
|
||||
tick = load_tickerdata_file(None, 'UNITTEST/BTC', '1m', timerange=timerange)
|
||||
tickerlist = {'UNITTEST/BTC': tick}
|
||||
data = strategy.tickerdata_to_dataframe(tickerlist)
|
||||
assert len(data['UNITTEST/BTC']) == 99 # partial candle was removed
|
||||
@@ -1,9 +1,11 @@
|
||||
# pragma pylint: disable=missing-docstring, protected-access, C0103
|
||||
import logging
|
||||
import os
|
||||
from base64 import urlsafe_b64encode
|
||||
from os import path
|
||||
import warnings
|
||||
|
||||
import pytest
|
||||
from pandas import DataFrame
|
||||
|
||||
from freqtrade.strategy import import_strategy
|
||||
from freqtrade.strategy.default_strategy import DefaultStrategy
|
||||
@@ -13,14 +15,15 @@ from freqtrade.strategy.resolver import StrategyResolver
|
||||
|
||||
def test_import_strategy(caplog):
|
||||
caplog.set_level(logging.DEBUG)
|
||||
default_config = {}
|
||||
|
||||
strategy = DefaultStrategy()
|
||||
strategy = DefaultStrategy(default_config)
|
||||
strategy.some_method = lambda *args, **kwargs: 42
|
||||
|
||||
assert strategy.__module__ == 'freqtrade.strategy.default_strategy'
|
||||
assert strategy.some_method() == 42
|
||||
|
||||
imported_strategy = import_strategy(strategy)
|
||||
imported_strategy = import_strategy(strategy, default_config)
|
||||
|
||||
assert dir(strategy) == dir(imported_strategy)
|
||||
|
||||
@@ -36,19 +39,29 @@ def test_import_strategy(caplog):
|
||||
|
||||
|
||||
def test_search_strategy():
|
||||
default_location = os.path.join(os.path.dirname(
|
||||
os.path.realpath(__file__)), '..', '..', 'strategy'
|
||||
default_config = {}
|
||||
default_location = path.join(path.dirname(
|
||||
path.realpath(__file__)), '..', '..', 'strategy'
|
||||
)
|
||||
assert isinstance(
|
||||
StrategyResolver._search_strategy(default_location, 'DefaultStrategy'), IStrategy
|
||||
StrategyResolver._search_strategy(
|
||||
default_location,
|
||||
config=default_config,
|
||||
strategy_name='DefaultStrategy'
|
||||
),
|
||||
IStrategy
|
||||
)
|
||||
assert StrategyResolver._search_strategy(default_location, 'NotFoundStrategy') is None
|
||||
assert StrategyResolver._search_strategy(
|
||||
default_location,
|
||||
config=default_config,
|
||||
strategy_name='NotFoundStrategy'
|
||||
) is None
|
||||
|
||||
|
||||
def test_load_strategy(result):
|
||||
resolver = StrategyResolver({'strategy': 'TestStrategy'})
|
||||
assert hasattr(resolver.strategy, 'populate_indicators')
|
||||
assert 'adx' in resolver.strategy.populate_indicators(result)
|
||||
metadata = {'pair': 'ETH/BTC'}
|
||||
assert 'adx' in resolver.strategy.advise_indicators(result, metadata=metadata)
|
||||
|
||||
|
||||
def test_load_strategy_byte64(result):
|
||||
@@ -61,8 +74,8 @@ def test_load_strategy_byte64(result):
|
||||
|
||||
def test_load_strategy_invalid_directory(result, caplog):
|
||||
resolver = StrategyResolver()
|
||||
extra_dir = os.path.join('some', 'path')
|
||||
resolver._load_strategy('TestStrategy', extra_dir)
|
||||
extra_dir = path.join('some', 'path')
|
||||
resolver._load_strategy('TestStrategy', config={}, extra_dir=extra_dir)
|
||||
|
||||
assert (
|
||||
'freqtrade.strategy.resolver',
|
||||
@@ -70,8 +83,7 @@ def test_load_strategy_invalid_directory(result, caplog):
|
||||
'Path "{}" does not exist'.format(extra_dir),
|
||||
) in caplog.record_tuples
|
||||
|
||||
assert hasattr(resolver.strategy, 'populate_indicators')
|
||||
assert 'adx' in resolver.strategy.populate_indicators(result)
|
||||
assert 'adx' in resolver.strategy.advise_indicators(result, {'pair': 'ETH/BTC'})
|
||||
|
||||
|
||||
def test_load_not_found_strategy():
|
||||
@@ -79,27 +91,30 @@ def test_load_not_found_strategy():
|
||||
with pytest.raises(ImportError,
|
||||
match=r'Impossible to load Strategy \'NotFoundStrategy\'.'
|
||||
r' This class does not exist or contains Python code errors'):
|
||||
strategy._load_strategy('NotFoundStrategy')
|
||||
strategy._load_strategy(strategy_name='NotFoundStrategy', config={})
|
||||
|
||||
|
||||
def test_strategy(result):
|
||||
resolver = StrategyResolver({'strategy': 'DefaultStrategy'})
|
||||
config = {'strategy': 'DefaultStrategy'}
|
||||
|
||||
assert hasattr(resolver.strategy, 'minimal_roi')
|
||||
resolver = StrategyResolver(config)
|
||||
metadata = {'pair': 'ETH/BTC'}
|
||||
assert resolver.strategy.minimal_roi[0] == 0.04
|
||||
assert config["minimal_roi"]['0'] == 0.04
|
||||
|
||||
assert hasattr(resolver.strategy, 'stoploss')
|
||||
assert resolver.strategy.stoploss == -0.10
|
||||
assert config['stoploss'] == -0.10
|
||||
|
||||
assert hasattr(resolver.strategy, 'populate_indicators')
|
||||
assert 'adx' in resolver.strategy.populate_indicators(result)
|
||||
assert resolver.strategy.ticker_interval == '5m'
|
||||
assert config['ticker_interval'] == '5m'
|
||||
|
||||
assert hasattr(resolver.strategy, 'populate_buy_trend')
|
||||
dataframe = resolver.strategy.populate_buy_trend(resolver.strategy.populate_indicators(result))
|
||||
df_indicators = resolver.strategy.advise_indicators(result, metadata=metadata)
|
||||
assert 'adx' in df_indicators
|
||||
|
||||
dataframe = resolver.strategy.advise_buy(df_indicators, metadata=metadata)
|
||||
assert 'buy' in dataframe.columns
|
||||
|
||||
assert hasattr(resolver.strategy, 'populate_sell_trend')
|
||||
dataframe = resolver.strategy.populate_sell_trend(resolver.strategy.populate_indicators(result))
|
||||
dataframe = resolver.strategy.advise_sell(df_indicators, metadata=metadata)
|
||||
assert 'sell' in dataframe.columns
|
||||
|
||||
|
||||
@@ -113,7 +128,6 @@ def test_strategy_override_minimal_roi(caplog):
|
||||
}
|
||||
resolver = StrategyResolver(config)
|
||||
|
||||
assert hasattr(resolver.strategy, 'minimal_roi')
|
||||
assert resolver.strategy.minimal_roi[0] == 0.5
|
||||
assert ('freqtrade.strategy.resolver',
|
||||
logging.INFO,
|
||||
@@ -129,7 +143,6 @@ def test_strategy_override_stoploss(caplog):
|
||||
}
|
||||
resolver = StrategyResolver(config)
|
||||
|
||||
assert hasattr(resolver.strategy, 'stoploss')
|
||||
assert resolver.strategy.stoploss == -0.5
|
||||
assert ('freqtrade.strategy.resolver',
|
||||
logging.INFO,
|
||||
@@ -146,9 +159,64 @@ def test_strategy_override_ticker_interval(caplog):
|
||||
}
|
||||
resolver = StrategyResolver(config)
|
||||
|
||||
assert hasattr(resolver.strategy, 'ticker_interval')
|
||||
assert resolver.strategy.ticker_interval == 60
|
||||
assert ('freqtrade.strategy.resolver',
|
||||
logging.INFO,
|
||||
'Override strategy \'ticker_interval\' with value in config file: 60.'
|
||||
) in caplog.record_tuples
|
||||
|
||||
|
||||
def test_deprecate_populate_indicators(result):
|
||||
default_location = path.join(path.dirname(path.realpath(__file__)))
|
||||
resolver = StrategyResolver({'strategy': 'TestStrategyLegacy',
|
||||
'strategy_path': default_location})
|
||||
with warnings.catch_warnings(record=True) as w:
|
||||
# Cause all warnings to always be triggered.
|
||||
warnings.simplefilter("always")
|
||||
indicators = resolver.strategy.advise_indicators(result, 'ETH/BTC')
|
||||
assert len(w) == 1
|
||||
assert issubclass(w[-1].category, DeprecationWarning)
|
||||
assert "deprecated - check out the Sample strategy to see the current function headers!" \
|
||||
in str(w[-1].message)
|
||||
|
||||
with warnings.catch_warnings(record=True) as w:
|
||||
# Cause all warnings to always be triggered.
|
||||
warnings.simplefilter("always")
|
||||
resolver.strategy.advise_buy(indicators, 'ETH/BTC')
|
||||
assert len(w) == 1
|
||||
assert issubclass(w[-1].category, DeprecationWarning)
|
||||
assert "deprecated - check out the Sample strategy to see the current function headers!" \
|
||||
in str(w[-1].message)
|
||||
|
||||
with warnings.catch_warnings(record=True) as w:
|
||||
# Cause all warnings to always be triggered.
|
||||
warnings.simplefilter("always")
|
||||
resolver.strategy.advise_sell(indicators, 'ETH_BTC')
|
||||
assert len(w) == 1
|
||||
assert issubclass(w[-1].category, DeprecationWarning)
|
||||
assert "deprecated - check out the Sample strategy to see the current function headers!" \
|
||||
in str(w[-1].message)
|
||||
|
||||
|
||||
def test_call_deprecated_function(result, monkeypatch):
|
||||
default_location = path.join(path.dirname(path.realpath(__file__)))
|
||||
resolver = StrategyResolver({'strategy': 'TestStrategyLegacy',
|
||||
'strategy_path': default_location})
|
||||
metadata = {'pair': 'ETH/BTC'}
|
||||
|
||||
# Make sure we are using a legacy function
|
||||
assert resolver.strategy._populate_fun_len == 2
|
||||
assert resolver.strategy._buy_fun_len == 2
|
||||
assert resolver.strategy._sell_fun_len == 2
|
||||
|
||||
indicator_df = resolver.strategy.advise_indicators(result, metadata=metadata)
|
||||
assert type(indicator_df) is DataFrame
|
||||
assert 'adx' in indicator_df.columns
|
||||
|
||||
buydf = resolver.strategy.advise_buy(result, metadata=metadata)
|
||||
assert type(buydf) is DataFrame
|
||||
assert 'buy' in buydf.columns
|
||||
|
||||
selldf = resolver.strategy.advise_sell(result, metadata=metadata)
|
||||
assert type(selldf) is DataFrame
|
||||
assert 'sell' in selldf
|
||||
|
||||
Reference in New Issue
Block a user