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rename populate_trends to populate_buy_trend. make it produce buy and buy_price columns

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This commit is contained in:
Janne Sinivirta 2017-09-09 16:32:53 +03:00
parent 1bcd51d6e0
commit 2f3fd1de8a
2 changed files with 20 additions and 18 deletions
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32
analyze.py
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@ -71,42 +71,40 @@ def populate_indicators(dataframe: DataFrame) -> DataFrame:
return dataframe return dataframe
def populate_trends(dataframe: DataFrame) -> DataFrame: def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
""" """
Populates the trends for the given dataframe Based on TA indicators, populates the buy trend for the given dataframe
:param dataframe: DataFrame :param dataframe: DataFrame
:return: DataFrame with populated trends :return: DataFrame with buy column
"""
"""
dataframe.loc[
(dataframe['stochrsi'] < 20)
& (dataframe['close_30_ema'] > (1 + 0.0025) * dataframe['close_60_ema']),
'underpriced'
] = 1
""" """
dataframe.loc[ dataframe.loc[
(dataframe['stochrsi'] < 20) (dataframe['stochrsi'] < 20)
& (dataframe['macd'] > dataframe['macds']) & (dataframe['macd'] > dataframe['macds'])
& (dataframe['close'] > dataframe['sar']), & (dataframe['close'] > dataframe['sar']),
'underpriced' 'buy'
] = 1 ] = 1
dataframe.loc[dataframe['underpriced'] == 1, 'buy'] = dataframe['close'] dataframe.loc[dataframe['buy'] == 1, 'buy_price'] = dataframe['close']
return dataframe return dataframe
def analyze_ticker(pair: str) -> DataFrame: def analyze_ticker(pair: str) -> DataFrame:
"""
Get ticker data for given currency pair, push it to a DataFrame and
add several TA indicators and buy signal to it
:return DataFrame with ticker data and indicator data
"""
minimum_date = arrow.now() - timedelta(hours=6) minimum_date = arrow.now() - timedelta(hours=6)
data = get_ticker(pair, minimum_date) data = get_ticker(pair, minimum_date)
dataframe = parse_ticker_dataframe(data['result'], minimum_date) dataframe = parse_ticker_dataframe(data['result'], minimum_date)
dataframe = populate_indicators(dataframe) dataframe = populate_indicators(dataframe)
dataframe = populate_trends(dataframe) dataframe = populate_buy_trend(dataframe)
return dataframe return dataframe
def get_buy_signal(pair: str) -> bool: def get_buy_signal(pair: str) -> bool:
""" """
Calculates a buy signal based on StochRSI indicator Calculates a buy signal based several technical analysis indicators
:param pair: pair in format BTC_ANT or BTC-ANT :param pair: pair in format BTC_ANT or BTC-ANT
:return: True if pair is underpriced, False otherwise :return: True if pair is good for buying, False otherwise
""" """
dataframe = analyze_ticker(pair) dataframe = analyze_ticker(pair)
latest = dataframe.iloc[-1] latest = dataframe.iloc[-1]
@ -116,7 +114,7 @@ def get_buy_signal(pair: str) -> bool:
if signal_date < arrow.now() - timedelta(minutes=10): if signal_date < arrow.now() - timedelta(minutes=10):
return False return False
signal = latest['underpriced'] == 1 signal = latest['buy'] == 1
logger.debug('buy_trigger: %s (pair=%s, signal=%s)', latest['date'], pair, signal) logger.debug('buy_trigger: %s (pair=%s, signal=%s)', latest['date'], pair, signal)
return signal return signal
@ -141,7 +139,7 @@ def plot_dataframe(dataframe: DataFrame, pair: str) -> None:
ax1.plot(dataframe.index.values, dataframe['close_30_ema'], label='EMA(30)') ax1.plot(dataframe.index.values, dataframe['close_30_ema'], label='EMA(30)')
ax1.plot(dataframe.index.values, dataframe['close_90_ema'], label='EMA(90)') ax1.plot(dataframe.index.values, dataframe['close_90_ema'], label='EMA(90)')
# ax1.plot(dataframe.index.values, dataframe['sell'], 'ro', label='sell') # ax1.plot(dataframe.index.values, dataframe['sell'], 'ro', label='sell')
ax1.plot(dataframe.index.values, dataframe['buy'], 'bo', label='buy') ax1.plot(dataframe.index.values, dataframe['buy_price'], 'bo', label='buy')
ax1.legend() ax1.legend()
ax2.plot(dataframe.index.values, dataframe['macd'], label='MACD') ax2.plot(dataframe.index.values, dataframe['macd'], label='MACD')

6
test/test_analyze.py
View File

@ -1,7 +1,7 @@
# pragma pylint: disable=missing-docstring # pragma pylint: disable=missing-docstring
import unittest import unittest
import arrow import arrow
from analyze import parse_ticker_dataframe from analyze import parse_ticker_dataframe, populate_buy_trend, populate_indicators
RESULT_BITTREX = { RESULT_BITTREX = {
'success': True, 'success': True,
@ -29,6 +29,10 @@ class TestAnalyze(unittest.TestCase):
'2017-08-30T10:40:00', '2017-08-30T10:40:00',
'2017-08-30T10:42:00']) '2017-08-30T10:42:00'])
def test_3_populates_buy_trend(self):
dataframe = populate_buy_trend(populate_indicators(self.result))
self.assertTrue('buy' in dataframe.columns)
self.assertTrue('buy_price' in dataframe.columns)
if __name__ == '__main__': if __name__ == '__main__':
unittest.main() unittest.main()