v0.0.13
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404c8d1e1b
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25
app.py
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25
app.py
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import logging
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import os
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from kraken_bot.KrakenBot import KrakenBot
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from kraken_bot.LinearRegression import LinearRegression
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from dotenv import load_dotenv
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load_dotenv()
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logger = logging.getLogger(__name__)
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bot = KrakenBot(
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token = os.getenv('KRAKEN_API_TOKEN'),
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secret = os.getenv('KRAKEN_API_SEC'),
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tier = 'Pro',
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investment_count = int(os.getenv('INVESTMENT_COUNT')),
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investment_volume = float(os.getenv('INVESTMENT_VOLUME'))
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)
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model = LinearRegression(
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r_value_target = float(os.getenv('R_VALUE_TARGET'))
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)
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if __name__ == '__main__':
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bot.update()
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bot.trade(model)
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@ -1,105 +0,0 @@
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import krakenex
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import pandas
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import time
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from pykrakenapi import KrakenAPI
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from scipy.stats import linregress
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class KrakenBot():
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def __init__(self, kraken_api_token, kraken_api_sec, tier, r_value_target, investment_count, investment_volume):
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self.r_value_target = r_value_target
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self.investment_count = investment_count
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self.investment_volume = investment_volume
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k = krakenex.API(kraken_api_token, kraken_api_sec)
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self.kraken = KrakenAPI(k, tier=tier)
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def filter_asset_pairs(self, tradable_asset_pairs):
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return tradable_asset_pairs[
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(tradable_asset_pairs['quote'] == 'ZUSD') &
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(tradable_asset_pairs['status'] == 'online')
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]
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def model_asset_pair(self, asset_pair):
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ohlc = self.kraken.get_ohlc_data(asset_pair)[0]
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time.sleep(self.kraken.factor)
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model = pandas.DataFrame({
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'open': linregress(ohlc['time'].astype(float), ohlc['open'].astype(float)),
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'high': linregress(ohlc['time'].astype(float), ohlc['high'].astype(float)),
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'low': linregress(ohlc['time'].astype(float), ohlc['low'].astype(float)),
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'close': linregress(ohlc['time'].astype(float), ohlc['close'].astype(float))
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}).transpose()
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model.columns = ['slope', 'intercept', 'r_value', 'p_value', 'stderr']
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return model
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def grade_models(self, models):
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model_averages = pandas.DataFrame({
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model: {
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'slope': models[model].slope.mean(),
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'intercept': models[model].intercept.mean(),
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'r_value': models[model].r_value.mean(),
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'p_value': models[model].p_value.mean(),
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'stderr': models[model].stderr.mean()
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} for model in models
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}).transpose()
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filtered_models = model_averages[
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(model_averages['r_value'] >= self.r_value_target) &
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(model_averages['slope'] > 0)
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]
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return filtered_models.sort_values(by='slope', ascending=False)
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def sell_asset(self, market, volume):
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self.kraken.add_standard_order(
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ordertype = 'market',
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type = 'sell',
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pair = market,
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volume = volume,
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validate = False
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)
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time.sleep(self.kraken.factor)
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print(f"Sold {volume} on {market}")
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def buy_asset(self, market, volume):
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self.kraken.add_standard_order(
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ordertype = 'market',
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type = 'buy',
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pair = market,
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volume = volume,
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validate = False
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)
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print(f"Purchased {volume} on {market}")
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time.sleep(self.kraken.factor)
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def update(self):
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asset_pairs = self.filter_asset_pairs(self.kraken.get_tradable_asset_pairs())
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time.sleep(self.kraken.factor)
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graded_models = self.grade_models(
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{asset_pair: self.model_asset_pair(asset_pair) for asset_pair in asset_pairs.index}
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)
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print(graded_models)
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account_balance = self.kraken.get_account_balance()
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for asset in account_balance[(account_balance.vol > 0) & (account_balance.index != 'ZUSD')].index:
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market = asset_pairs[
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(asset_pairs.base == asset) &
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(asset_pairs.quote == 'ZUSD')
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]
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if market.index[0] not in graded_models[:self.investment_count * 2].index:
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self.sell_asset(market.index[0], account_balance.loc[asset].vol)
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account_balance = self.kraken.get_account_balance()
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while ((len(account_balance[account_balance.vol > 0]) - 1 < self.investment_count) &
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(account_balance.loc['ZUSD'].vol > self.investment_volume)):
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for market in graded_models.index:
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if asset_pairs.loc[market].base not in account_balance[account_balance.vol > 0].index:
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ohlc, last = self.kraken.get_ohlc_data(market)
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volume = self.investment_volume/ohlc.iloc[-1].close
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try:
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self.buy_asset(market, volume)
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account_balance = self.kraken.get_account_balance()
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time.sleep(self.kraken.factor)
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break
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except:
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continue
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print(self.kraken.get_account_balance())
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print(self.kraken.get_trade_balance(asset='ZUSD'))
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import os
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from KrakenBot import KrakenBot
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from dotenv import load_dotenv
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load_dotenv()
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bot = KrakenBot(
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kraken_api_token = os.getenv('KRAKEN_API_TOKEN'),
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kraken_api_sec = os.getenv('KRAKEN_API_SEC'),
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tier = 'Pro',
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r_value_target = float(os.getenv('R_VALUE_TARGET')),
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investment_count = int(os.getenv('INVESTMENT_COUNT')),
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investment_volume = float(os.getenv('INVESTMENT_VOLUME'))
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)
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if __name__ == '__main__':
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bot.update()
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146
kraken_bot/KrakenBot.py
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146
kraken_bot/KrakenBot.py
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import krakenex
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import logging
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import os
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import scipy
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import time
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from pykrakenapi import KrakenAPI
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class KrakenBot(KrakenAPI):
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class KrakenOrder():
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def __init__(self, ordertype, type, pair, userref=None, volume=None, price=None, price2=None, trigger=None, leverage=None,
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oflags=None, timeinforce=None, starttm=0, expiretm=0, close_ordertype=None, close_price=None, close_price2=None,
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deadline=None, validate=True, otp=None):
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self.ordertype = ordertype
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self.type = type
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self.pair = pair
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self.userref = userref
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self.volume = volume
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self.price = price
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self.price2 = price2
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self.trigger = trigger
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self.leverage = leverage
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self.oflags = oflags
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self.timeinforce = timeinforce
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self.starttm = starttm
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self.expiretm = expiretm
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self.close_ordertype = close_ordertype
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self.close_price = close_price
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self.close_price2 = close_price2
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self.deadline = deadline
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self.validate = validate
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self.otp = otp
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def __str__(self):
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return str({
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'ordertype': self.ordertype,
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'type': self.type,
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'pair': self.pair,
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'userref': self.userref,
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'volume': self.volume,
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'price': self.price,
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'price2': self.price2,
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'trigger': self.trigger,
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'leverage': self.leverage,
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'oflags': self.oflags,
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'timeinforce': self.timeinforce,
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'starttm': self.starttm,
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'expiretm': self.expiretm,
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'close_ordertype': self.close_ordertype,
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'close_price': self.close_price,
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'close_price2': self.close_price2,
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'deadline': self.deadline,
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'validate': self.validate,
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'otp': self.otp
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})
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def __init__(self, token, secret, tier, investment_count, investment_volume):
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self.investment_count = investment_count
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self.investment_volume = investment_volume
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self.log = logging.getLogger(__name__)
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self.log.setLevel(
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getattr(logging, os.getenv('LOG_LEVEL', 'INFO'), logging.INFO)
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)
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super().__init__(krakenex.API(token, secret), tier=tier)
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self.update()
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def _delay_factor(self):
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self.log.debug(f"_delay_factor")
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time.sleep(self.factor)
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self.log.debug(f"Delayed {self.factor} seconds")
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def _update_tradable_asset_pairs(self, info=None, pair=None):
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self.log.debug(f"update_tradable_asset_pairs: info={info}, pair={pair}")
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self._delay_factor()
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self.tradable_asset_pairs = self.get_tradable_asset_pairs(info, pair)
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def _update_account_balance(self, otp=None):
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self.log.debug(f"update_account_balance: otp={otp}")
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self._delay_factor()
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self.account_balance = self.get_account_balance(otp)
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self.log.debug(self.account_balance)
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def _update_trade_balance(self, aclass='currency', asset='ZUSD', otp=None):
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self.log.debug(f"update_trade_balance: aclass={aclass}, asset={asset}, otp={otp}")
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self._delay_factor()
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self.trade_balance = self.get_trade_balance(aclass, asset, otp)
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self.log.debug(self.trade_balance)
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def _get_ohlc_data(self, pair, interval=1, since=None, ascending=False):
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self.log.debug(f"get_ohlc_data: pair={pair}, interval={interval}, since={since}, ascending={ascending}")
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self._delay_factor()
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return self.get_ohlc_data(pair, interval, since, ascending)
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def _add_standard_order(self, order):
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self.log.debug(f"add_standard_order: order={order}")
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self._delay_factor()
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order = self.add_standard_order(
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order.ordertype, order.type, order.pair, order.userref, order.volume, order.price, order.price2, order.trigger,
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order.leverage, order.oflags, order.timeinforce, order.starttm, order.expiretm, order.close_ordertype,
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order.close_price, order.close_price2, order.deadline, order.validate, order.otp)
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self.log.info(order)
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self.update()
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def update(self):
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self.log.debug(f"update")
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self._update_tradable_asset_pairs()
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self._update_account_balance()
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self._update_trade_balance()
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def trade(self, model):
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self.log.debug(f"trade")
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model.update(
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self.tradable_asset_pairs,
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{
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asset_pair: self._get_ohlc_data(
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asset_pair, model.interval, model.since(), model.ascending
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) for asset_pair in self.tradable_asset_pairs.index
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}
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)
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for asset in self.account_balance[(self.account_balance.index != 'ZUSD') & (self.account_balance.vol > 0)].index:
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market = self.tradable_asset_pairs[
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(self.tradable_asset_pairs.base == asset) &
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(self.tradable_asset_pairs.quote == 'ZUSD')
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].iloc[0]
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if market.altname not in model.analysis.index:
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self._add_standard_order(self.KrakenOrder(
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ordertype = 'market',
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type = 'sell',
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pair = market.altname,
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volume = self.account_balance.loc[asset].vol,
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validate = False
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))
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while ((len(self.account_balance[self.account_balance.vol > 0]) - 1 < self.investment_count) &
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(self.account_balance.loc['ZUSD'].vol > self.investment_volume)):
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for market in model.analysis.index:
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if self.tradable_asset_pairs.loc[market].base not in self.account_balance[self.account_balance.vol > 0].index:
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ohlc, last = self._get_ohlc_data(market)
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volume = self.investment_volume / ohlc.iloc[-1].close
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self._add_standard_order(self.KrakenOrder(
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ordertype = 'market',
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type = 'buy',
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pair = market,
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volume = volume,
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validate = False
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))
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break
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46
kraken_bot/KrakenOrder.py
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46
kraken_bot/KrakenOrder.py
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class KrakenOrder():
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def __init__(self, ordertype, type, pair, userref=None, volume=None, price=None, price2=None, trigger=None, leverage=None,
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oflags=None, timeinforce=None, starttm=0, expiretm=0, closeordertype=None, close_price=None, close_price2=None,
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deadline=None, validate=True, otp=None):
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self.ordertype = ordertype
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self.type = type
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self.pair = pair
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self.userref = userref
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self.volume = volume
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self.price = price
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self.price2 = price2
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self.trigger = trigger
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self.leverage = leverage
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self.oflags = oflags
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self.timeinforce = timeinforce
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self.starttm = starttm
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self.expiretm = expiretm
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self.closeordertype = closeordertype
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self.close_price = close_price
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self.close_price2 = clowe_price2
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self.deadline = deadline
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self.validate = validate
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self.otp = otp
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def __str__(self):
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return str({
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'ordertype': self.ordertype
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'type': self.type
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'pair': self.pair
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'userref': self.userref
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'volume': self.volume
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'price': self.price
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'price2': self.price2
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'trigger': self.trigger
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'leverage': self.leverage
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'oflags': self.oflags
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'timeinforce': self.timeinforce
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'starttm': self.starttm
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'expiretm': self.expiretm
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'closeordertype': self.closeordertype
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'close_price': self.close_price
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'close_price2': self.clowe_price2
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'deadline': self.deadline
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'validate': self.validate
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'otp': self.otp
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})
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58
kraken_bot/LinearRegression.py
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58
kraken_bot/LinearRegression.py
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import logging
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import os
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import pandas
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from kraken_bot.Model import Model
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from scipy.stats import linregress
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class LinearRegression(Model):
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def __init__(self, r_value_target):
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self.r_value_target = r_value_target
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self.log = logging.getLogger(__name__)
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self.log.setLevel(
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getattr(logging, os.getenv('LOG_LEVEL', 'INFO'), logging.INFO)
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)
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self.analysis = pandas.DataFrame({})
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super().__init__(
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interval = 1,
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ascending = False
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)
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def _linear_regression_for_ohlc_data(self, ohlc_data):
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self.log.debug(f"_linear_regression_for_ohlc_data: ohlc_data=...")
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return linregress(ohlc_data['time'].astype(float), ohlc_data['close'].astype(float))
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def _filter_asset_pairs(self, tradable_asset_pairs):
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self.log.debug(f"_filter_asset_pairs: tradable_asset_pairs=...")
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return tradable_asset_pairs[
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(tradable_asset_pairs['quote'] == 'ZUSD') &
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(tradable_asset_pairs['status'] == 'online')
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]
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def _filter_regressions(self, regressions):
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self.log.debug(f"_filter_regressions: regressions=...")
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regressions.columns = ['slope', 'intercept', 'r_value', 'p_value', 'stderr']
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return regressions[
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(regressions.r_value >= self.r_value_target) &
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(regressions.slope > 0)
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]
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def _order_regressions(self, regressions):
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self.log.debug(f"_order_regressions: regressions=...")
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return regressions.sort_values(by='slope', ascending=False)
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def since(self):
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return None
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def update(self, tradable_asset_pairs, ohlc_data):
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self.log.debug(f"update: tradable_asset_pairs=..., ohlc_data=...")
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self.analysis = self._order_regressions(
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self._filter_regressions(
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pandas.DataFrame({
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asset_pair: self._linear_regression_for_ohlc_data(
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ohlc_data[asset_pair][0]
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) for asset_pair in self._filter_asset_pairs(tradable_asset_pairs).index
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}).transpose()
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))
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self.log.info(f"Completed linear regression analysis of OHLC market data")
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self.log.info(self.analysis)
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14
kraken_bot/Model.py
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14
kraken_bot/Model.py
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from abc import ABC, abstractmethod
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class Model(ABC):
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def __init__(self, interval, ascending):
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self.interval = interval
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self.ascending = ascending
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@abstractmethod
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def since():
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pass
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@abstractmethod
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def update(self, tradable_asset_pairs, ohlc_data, account_balance, trade_balance):
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pass
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0
kraken_bot/__init__.py
Normal file
0
kraken_bot/__init__.py
Normal file
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