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Merge pull request #39 from hroff-1902/update-interfaces

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update interfaces for populate_* methods
This commit is contained in:
hroff-1902
2019-08-10 16:15:25 +03:00
committed by GitHub
parent f22448db6f 6f4cf17637
commit 73c2a6422c
29 changed files with 87 additions and 87 deletions
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user_data/strategies/berlinguyinca/ADXMomentum.py
+3 -3
View File
@@ -31,7 +31,7 @@ class ADXMomentum(IStrategy):
# Optimal ticker interval for the strategy
ticker_interval = '1h'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['adx'] = ta.ADX(dataframe, timeperiod=14)
dataframe['plus_di'] = ta.PLUS_DI(dataframe, timeperiod=25)
dataframe['minus_di'] = ta.MINUS_DI(dataframe, timeperiod=25)
@@ -40,7 +40,7 @@ class ADXMomentum(IStrategy):
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['adx'] > 25) &
@@ -52,7 +52,7 @@ class ADXMomentum(IStrategy):
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['adx'] > 25) &
user_data/strategies/berlinguyinca/ASDTSRockwellTrading.py
+3 -3
View File
@@ -47,7 +47,7 @@ class ASDTSRockwellTrading(IStrategy):
# Optimal ticker interval for the strategy
ticker_interval = '5m'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
@@ -56,7 +56,7 @@ class ASDTSRockwellTrading(IStrategy):
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> 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
@@ -71,7 +71,7 @@ class ASDTSRockwellTrading(IStrategy):
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> 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
user_data/strategies/berlinguyinca/AdxSmas.py
+3 -3
View File
@@ -32,14 +32,14 @@ class AdxSmas(IStrategy):
# Optimal ticker interval for the strategy
ticker_interval = '1h'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['adx'] = ta.ADX(dataframe, timeperiod=14)
dataframe['short'] = ta.SMA(dataframe, timeperiod=3)
dataframe['long'] = ta.SMA(dataframe, timeperiod=6)
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['adx'] > 25) &
@@ -49,7 +49,7 @@ class AdxSmas(IStrategy):
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['adx'] < 25) &
user_data/strategies/berlinguyinca/AverageStrategy.py
+3 -3
View File
@@ -31,7 +31,7 @@ class AverageStrategy(IStrategy):
# Optimal ticker interval for the strategy
ticker_interval = '4h'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
macd = ta.MACD(dataframe)
dataframe['maShort'] = ta.EMA(dataframe, timeperiod=8)
@@ -39,7 +39,7 @@ class AverageStrategy(IStrategy):
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> 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
@@ -53,7 +53,7 @@ class AverageStrategy(IStrategy):
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> 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
user_data/strategies/berlinguyinca/AwesomeMacd.py
+3 -3
View File
@@ -32,7 +32,7 @@ class AwesomeMacd(IStrategy):
# Optimal ticker interval for the strategy
ticker_interval = '1h'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['adx'] = ta.ADX(dataframe, timeperiod=14)
dataframe['ao'] = qtpylib.awesome_oscillator(dataframe)
@@ -43,7 +43,7 @@ class AwesomeMacd(IStrategy):
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['macd'] > 0) &
@@ -54,7 +54,7 @@ class AwesomeMacd(IStrategy):
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['macd'] < 0) &
user_data/strategies/berlinguyinca/BbandRsi.py
+3 -3
View File
@@ -32,7 +32,7 @@ class BbandRsi(IStrategy):
# Optimal ticker interval for the strategy
ticker_interval = '1h'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
# Bollinger bands
@@ -43,7 +43,7 @@ class BbandRsi(IStrategy):
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['rsi'] < 30) &
@@ -53,7 +53,7 @@ class BbandRsi(IStrategy):
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['rsi'] > 70)
user_data/strategies/berlinguyinca/BinHV27.py
+3 -3
View File
@@ -28,7 +28,7 @@ class BinHV27(IStrategy):
}
stoploss = -0.50
ticker_interval = '5m'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['rsi'] = numpy.nan_to_num(ta.RSI(dataframe, timeperiod=5))
rsiframe = DataFrame(dataframe['rsi']).rename(columns={'rsi': 'close'})
dataframe['emarsi'] = numpy.nan_to_num(ta.EMA(rsiframe, timeperiod=5))
@@ -52,7 +52,7 @@ class BinHV27(IStrategy):
dataframe['delta'] = dataframe['fastsma'] - dataframe['fastsma'].shift()
dataframe['slowingdown'] = dataframe['delta'].lt(dataframe['delta'].shift())
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
dataframe['slowsma'].gt(0) &
dataframe['close'].lt(dataframe['highsma']) &
@@ -89,7 +89,7 @@ class BinHV27(IStrategy):
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
buyframe = dataframe[dataframe['buy'] == 1].tail(1)
if len(buyframe) == 0:
dataframe.loc[[False], 'sell'] = 0
user_data/strategies/berlinguyinca/BinHV45.py
+3 -3
View File
@@ -25,7 +25,7 @@ class BinHV45(IStrategy):
stoploss = -0.05
ticker_interval = '1m'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
mid, lower = bollinger_bands(dataframe['close'], window_size=40, num_of_std=2)
dataframe['mid'] = np.nan_to_num(mid)
dataframe['lower'] = np.nan_to_num(lower)
@@ -35,7 +35,7 @@ class BinHV45(IStrategy):
dataframe['tail'] = (dataframe['close'] - dataframe['low']).abs()
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
dataframe['lower'].shift().gt(0) &
@@ -48,7 +48,7 @@ class BinHV45(IStrategy):
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
no sell signal
"""
user_data/strategies/berlinguyinca/CCIStrategy.py
+3 -3
View File
@@ -23,7 +23,7 @@ class CCIStrategy(IStrategy):
# Optimal ticker interval for the strategy
ticker_interval = '1m'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe = self.resample(dataframe, self.ticker_interval, 5)
dataframe['cci_one'] = ta.CCI(dataframe, timeperiod=170)
@@ -41,7 +41,7 @@ class CCIStrategy(IStrategy):
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> 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
@@ -63,7 +63,7 @@ class CCIStrategy(IStrategy):
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> 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
user_data/strategies/berlinguyinca/CMCWinner.py
+3 -3
View File
@@ -43,7 +43,7 @@ class CMCWinner(IStrategy):
# Optimal ticker interval for the strategy
ticker_interval = '15m'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
Adds several different TA indicators to the given DataFrame
@@ -63,7 +63,7 @@ class CMCWinner(IStrategy):
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> 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
@@ -79,7 +79,7 @@ class CMCWinner(IStrategy):
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> 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
user_data/strategies/berlinguyinca/ClucMay72018.py
+3 -3
View File
@@ -39,7 +39,7 @@ class ClucMay72018(IStrategy):
# Optimal ticker interval for the strategy
ticker_interval = '5m'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['rsi'] = ta.RSI(dataframe, timeperiod=5)
rsiframe = DataFrame(dataframe['rsi']).rename(columns={'rsi': 'close'})
dataframe['emarsi'] = ta.EMA(rsiframe, timeperiod=5)
@@ -53,7 +53,7 @@ class ClucMay72018(IStrategy):
dataframe['ema100'] = ta.EMA(dataframe, timeperiod=50)
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> 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
@@ -69,7 +69,7 @@ class ClucMay72018(IStrategy):
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> 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
user_data/strategies/berlinguyinca/CofiBitStrategy.py
+3 -3
View File
@@ -29,7 +29,7 @@ class CofiBitStrategy(IStrategy):
# Optimal ticker interval for the strategy
ticker_interval = '5m'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
stoch_fast = ta.STOCHF(dataframe, 5.0, 3.0, 0.0, 3.0, 0.0)
dataframe['fastd'] = stoch_fast['fastd']
dataframe['fastk'] = stoch_fast['fastk']
@@ -40,7 +40,7 @@ class CofiBitStrategy(IStrategy):
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> 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
@@ -59,7 +59,7 @@ class CofiBitStrategy(IStrategy):
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> 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
user_data/strategies/berlinguyinca/CombinedBinHAndCluc.py
+3 -3
View File
@@ -26,7 +26,7 @@ class CombinedBinHAndCluc(IStrategy):
stoploss = -0.15
ticker_interval = '5m'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
mid, lower = bollinger_bands(dataframe['close'], window_size=40, num_of_std=2)
dataframe['mid'] = np.nan_to_num(mid)
dataframe['lower'] = np.nan_to_num(lower)
@@ -47,7 +47,7 @@ class CombinedBinHAndCluc(IStrategy):
dataframe['ema100'] = ta.EMA(dataframe, timeperiod=50)
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
dataframe['lower'].shift().gt(0) &
@@ -67,7 +67,7 @@ class CombinedBinHAndCluc(IStrategy):
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
"""
dataframe.loc[
user_data/strategies/berlinguyinca/DoesNothingStrategy.py
+3 -3
View File
@@ -26,17 +26,17 @@ class DoesNothingStrategy(IStrategy):
# Optimal ticker interval for the strategy
ticker_interval = '5m'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
),
user_data/strategies/berlinguyinca/EMASkipPump.py
+3 -3
View File
@@ -33,7 +33,7 @@ class EMASkipPump(IStrategy):
# Optimal ticker interval for the strategy
ticker_interval = '5m'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
""" Adds several different TA indicators to the given DataFrame
"""
@@ -59,7 +59,7 @@ class EMASkipPump(IStrategy):
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(dataframe['volume'] < (dataframe['volume'].rolling(window=30).mean().shift(1) * 20)) &
@@ -72,7 +72,7 @@ class EMASkipPump(IStrategy):
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(dataframe['close'] > dataframe['ema_{}'.format(self.EMA_SHORT_TERM)]) &
user_data/strategies/berlinguyinca/Freqtrade_backtest_validation_freqtrade1.py
+3 -3
View File
@@ -26,13 +26,13 @@ class Freqtrade_backtest_validation_freqtrade1(IStrategy):
stoploss = -09.90
ticker_interval = '1h'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# SMA - Simple Moving Average
dataframe['fastMA'] = ta.SMA(dataframe, timeperiod=14)
dataframe['slowMA'] = ta.SMA(dataframe, timeperiod=28)
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['fastMA'] > dataframe['slowMA'])
@@ -41,7 +41,7 @@ class Freqtrade_backtest_validation_freqtrade1(IStrategy):
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['fastMA'] < dataframe['slowMA'])
user_data/strategies/berlinguyinca/Low_BB.py
+3 -3
View File
@@ -45,7 +45,7 @@ class Low_BB(IStrategy):
# Optimal ticker interval for the strategy
ticker_interval = '1m'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
##################################################################################
# buy and sell indicators
@@ -79,7 +79,7 @@ class Low_BB(IStrategy):
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> 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
@@ -96,7 +96,7 @@ class Low_BB(IStrategy):
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> 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
user_data/strategies/berlinguyinca/MACDStrategy.py
+3 -3
View File
@@ -42,7 +42,7 @@ class MACDStrategy(IStrategy):
# Optimal ticker interval for the strategy
ticker_interval = '5m'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
@@ -52,7 +52,7 @@ class MACDStrategy(IStrategy):
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> 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
@@ -67,7 +67,7 @@ class MACDStrategy(IStrategy):
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> 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
user_data/strategies/berlinguyinca/MACDStrategy_crossed.py
+3 -3
View File
@@ -36,7 +36,7 @@ class MACDStrategy_crossed(IStrategy):
# Optimal ticker interval for the strategy
ticker_interval = '5m'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
@@ -46,7 +46,7 @@ class MACDStrategy_crossed(IStrategy):
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> 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
@@ -61,7 +61,7 @@ class MACDStrategy_crossed(IStrategy):
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> 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
user_data/strategies/berlinguyinca/MultiRSI.py
+3 -3
View File
@@ -26,7 +26,7 @@ class MultiRSI(IStrategy):
def get_ticker_indicator(self):
return int(self.ticker_interval[:-1])
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
from technical.util import resample_to_interval
from technical.util import resampled_merge
@@ -51,7 +51,7 @@ class MultiRSI(IStrategy):
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
# must be bearish
@@ -61,7 +61,7 @@ class MultiRSI(IStrategy):
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['rsi'] > dataframe['resample_{}_rsi'.format(self.get_ticker_indicator()*2)]) &
user_data/strategies/berlinguyinca/Quickie.py
+3 -3
View File
@@ -34,7 +34,7 @@ class Quickie(IStrategy):
# Optimal ticker interval for the strategy
ticker_interval = '5m'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
dataframe['macdsignal'] = macd['macdsignal']
@@ -54,7 +54,7 @@ class Quickie(IStrategy):
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['adx'] > 30) &
@@ -66,7 +66,7 @@ class Quickie(IStrategy):
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['adx'] > 70) &
user_data/strategies/berlinguyinca/ReinforcedAverageStrategy.py
+3 -3
View File
@@ -31,7 +31,7 @@ class ReinforcedAverageStrategy(IStrategy):
# Optimal ticker interval for the strategy
ticker_interval = '4h'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['maShort'] = ta.EMA(dataframe, timeperiod=8)
dataframe['maMedium'] = ta.EMA(dataframe, timeperiod=21)
@@ -43,7 +43,7 @@ class ReinforcedAverageStrategy(IStrategy):
dataframe['bb_middleband'] = bollinger['mid']
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> 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
@@ -60,7 +60,7 @@ class ReinforcedAverageStrategy(IStrategy):
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> 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
user_data/strategies/berlinguyinca/ReinforcedQuickie.py
+3 -3
View File
@@ -47,7 +47,7 @@ class ReinforcedQuickie(IStrategy):
EMA_MEDIUM_TERM = 12
EMA_LONG_TERM = 21
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe = self.resample(dataframe, self.ticker_interval, self.resample_factor)
##################################################################################
@@ -93,7 +93,7 @@ class ReinforcedQuickie(IStrategy):
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> 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
@@ -138,7 +138,7 @@ class ReinforcedQuickie(IStrategy):
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> 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
user_data/strategies/berlinguyinca/ReinforcedSmoothScalp.py
+3 -3
View File
@@ -39,7 +39,7 @@ class ReinforcedSmoothScalp(IStrategy):
# resample factor to establish our general trend. Basically don't buy if a trend is not given
resample_factor = 5
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe = self.resample(dataframe, self.ticker_interval, self.resample_factor)
dataframe['ema_high'] = ta.EMA(dataframe, timeperiod=5, price='high')
@@ -61,7 +61,7 @@ class ReinforcedSmoothScalp(IStrategy):
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(
@@ -84,7 +84,7 @@ class ReinforcedSmoothScalp(IStrategy):
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(
user_data/strategies/berlinguyinca/Scalp.py
+3 -3
View File
@@ -39,7 +39,7 @@ class Scalp(IStrategy):
# the shorter the better
ticker_interval = '1m'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['ema_high'] = ta.EMA(dataframe, timeperiod=5, price='high')
dataframe['ema_close'] = ta.EMA(dataframe, timeperiod=5, price='close')
dataframe['ema_low'] = ta.EMA(dataframe, timeperiod=5, price='low')
@@ -56,7 +56,7 @@ class Scalp(IStrategy):
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['open'] < dataframe['ema_low']) &
@@ -69,7 +69,7 @@ class Scalp(IStrategy):
),
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(dataframe['open'] >= dataframe['ema_high'])
user_data/strategies/berlinguyinca/Simple.py
+3 -3
View File
@@ -34,7 +34,7 @@ class Simple(IStrategy):
# Optimal ticker interval for the strategy
ticker_interval = '5m'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# MACD
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
@@ -52,7 +52,7 @@ class Simple(IStrategy):
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(
@@ -65,7 +65,7 @@ class Simple(IStrategy):
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# different strategy used for sell points, due to be able to duplicate it to 100%
dataframe.loc[
(
user_data/strategies/berlinguyinca/SmoothOperator.py
+3 -3
View File
@@ -41,7 +41,7 @@ class SmoothOperator(IStrategy):
# resample factor to establish our general trend. Basically don't buy if a trend is not given
resample_factor = 12
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# resampled dataframe to establish if we are in an uptrend, downtrend or sideways trend
dataframe = StrategyHelper.resample(dataframe, self.ticker_interval, self.resample_factor)
@@ -108,7 +108,7 @@ class SmoothOperator(IStrategy):
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
@@ -178,7 +178,7 @@ class SmoothOperator(IStrategy):
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# different strategy used for sell points, due to be able to duplicate it to 100%
dataframe.loc[
(
user_data/strategies/berlinguyinca/SmoothScalp.py
+3 -3
View File
@@ -36,7 +36,7 @@ class SmoothScalp(IStrategy):
# the shorter the better
ticker_interval = '1m'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['ema_high'] = ta.EMA(dataframe, timeperiod=5, price='high')
dataframe['ema_close'] = ta.EMA(dataframe, timeperiod=5, price='close')
dataframe['ema_low'] = ta.EMA(dataframe, timeperiod=5, price='low')
@@ -62,7 +62,7 @@ class SmoothScalp(IStrategy):
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(
@@ -81,7 +81,7 @@ class SmoothScalp(IStrategy):
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(
user_data/strategies/berlinguyinca/TechnicalExampleStrategy.py
+3 -3
View File
@@ -14,12 +14,12 @@ class TechnicalExampleStrategy(IStrategy):
# Optimal ticker interval for the strategy
ticker_interval = '5m'
def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe['cmf'] = cmf(dataframe, 21)
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
dataframe.loc[
(
(
@@ -30,7 +30,7 @@ class TechnicalExampleStrategy(IStrategy):
'buy'] = 1
return dataframe
def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# different strategy used for sell points, due to be able to duplicate it to 100%
dataframe.loc[
(