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let TA-lib calculate macd, macdsignal and macdhistogram. remove the now unnecessary StockStats library

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Janne Sinivirta 2017-09-02 11:56:56 +03:00
parent 0643438580
commit 82b90f24e7
2 changed files with 17 additions and 12 deletions
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28
analyze.py
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@ -4,7 +4,8 @@ import logging
import arrow import arrow
import requests import requests
from pandas.io.json import json_normalize from pandas.io.json import json_normalize
from stockstats import StockDataFrame from pandas import DataFrame
# from stockstats import StockDataFrame
import talib.abstract as ta import talib.abstract as ta
logging.basicConfig(level=logging.DEBUG, logging.basicConfig(level=logging.DEBUG,
@ -12,11 +13,11 @@ logging.basicConfig(level=logging.DEBUG,
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
def get_ticker_dataframe(pair: str) -> StockDataFrame: def get_ticker_dataframe(pair: str) -> DataFrame:
""" """
Analyses the trend for the given pair Analyses the trend for the given pair
:param pair: pair as str in format BTC_ETH or BTC-ETH :param pair: pair as str in format BTC_ETH or BTC-ETH
:return: StockDataFrame :return: DataFrame
""" """
minimum_date = arrow.now() - timedelta(hours=6) minimum_date = arrow.now() - timedelta(hours=6)
url = 'https://bittrex.com/Api/v2.0/pub/market/GetTicks' url = 'https://bittrex.com/Api/v2.0/pub/market/GetTicks'
@ -40,20 +41,25 @@ def get_ticker_dataframe(pair: str) -> StockDataFrame:
'low': t['L'], 'low': t['L'],
'date': t['T'], 'date': t['T'],
} for t in sorted(data['result'], key=lambda k: k['T']) if arrow.get(t['T']) > minimum_date] } for t in sorted(data['result'], key=lambda k: k['T']) if arrow.get(t['T']) > minimum_date]
dataframe = StockDataFrame(json_normalize(data)) dataframe = DataFrame(json_normalize(data))
# calculate StochRSI # calculate StochRSI
stochrsi = ta.STOCHRSI(dataframe) stochrsi = ta.STOCHRSI(dataframe)
dataframe['stochrsi'] = stochrsi['fastd'] # values between 0-100, not 0-1 dataframe['stochrsi'] = stochrsi['fastd'] # values between 0-100, not 0-1
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
dataframe['macds'] = macd['macdsignal']
dataframe['macdh'] = macd['macdhist']
return dataframe return dataframe
def populate_trends(dataframe: StockDataFrame) -> StockDataFrame: def populate_trends(dataframe: DataFrame) -> DataFrame:
""" """
Populates the trends for the given dataframe Populates the trends for the given dataframe
:param dataframe: StockDataFrame :param dataframe: DataFrame
:return: StockDataFrame with populated trends :return: DataFrame with populated trends
""" """
""" """
dataframe.loc[ dataframe.loc[
@ -91,10 +97,10 @@ def get_buy_signal(pair: str) -> bool:
return signal return signal
def plot_dataframe(dataframe: StockDataFrame, pair: str) -> None: def plot_dataframe(dataframe: DataFrame, pair: str) -> None:
""" """
Plots the given dataframe Plots the given dataframe
:param dataframe: StockDataFrame :param dataframe: DataFrame
:param pair: pair as str :param pair: pair as str
:return: None :return: None
""" """
@ -108,8 +114,8 @@ def plot_dataframe(dataframe: StockDataFrame, pair: str) -> None:
fig, (ax1, ax2, ax3) = plt.subplots(3, sharex=True) fig, (ax1, ax2, ax3) = plt.subplots(3, sharex=True)
fig.suptitle(pair, fontsize=14, fontweight='bold') fig.suptitle(pair, fontsize=14, fontweight='bold')
ax1.plot(dataframe.index.values, dataframe['close'], label='close') ax1.plot(dataframe.index.values, dataframe['close'], label='close')
ax1.plot(dataframe.index.values, dataframe['close_30_ema'], label='EMA(60)') # ax1.plot(dataframe.index.values, dataframe['close_30_ema'], label='EMA(60)')
ax1.plot(dataframe.index.values, dataframe['close_90_ema'], label='EMA(120)') # ax1.plot(dataframe.index.values, dataframe['close_90_ema'], label='EMA(120)')
# 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'], 'bo', label='buy')
ax1.legend() ax1.legend()

1
requirements.txt
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@ -11,6 +11,5 @@ matplotlib==2.0.2
PYQT5==5.9 PYQT5==5.9
scikit-learn==0.19.0 scikit-learn==0.19.0
scipy==0.19.1 scipy==0.19.1
stockstats==0.2.0
jsonschema==2.6.0 jsonschema==2.6.0
TA-Lib==0.4.10 TA-Lib==0.4.10