GekkoPy

Python library to interact with the Gekko trading bot found at https://github.com/askmike/gekko.

Installation and Requirements

1. Install Gekko
2. Start Gekko
3. Clone this repository
4. Enjoy Gekko in Python!

Accessing the Gekko Server from Python

You can access the Gekko server from Python to pull candle data or run backtests.

Pulling Candle Data

from gekkopy.gekko_client import GekkoClient

gekko = GekkoClient('http://localhost:3000')
data = gekko.pull_candles(
    'binance', 'BTC', 'USDT', 
    candlesize=60,
    date_start='2019-01-01', date_end='2019-06-01')

Backtesting a Gekko Strategy from Python code

from gekkopy.gekko_client import GekkoClient

gekko = GekkoClient('http://localhost:3000')

macd_cfg = {
    'short': 10,
    'long': 21,
    'signal': 9,
    'thresholds': {
        'down': -0.025,
        'up': 0.025,
        'persistence': 1,
    }
}
bt_config = gekko.build_backtest_config(
    exchange='binance', 
    asset='BTC', 
    currency='USDT', 
    candlesize=360, 
    strategy='MACD',
    strat_config=macd_cfg, 
    date_start='2019-01-01', 
    date_end='2019-06-01'
)

report, jdf, profits = gekko.backtest(bt_config)

print(report)
# {'startTime': '2019-02-19 23:59:00',
#  'endTime': '2019-06-01 00:01:00',
#  'timespan': '3 months',
#  'market': 118.83289531934932,
#  'balance': 5605.98664554,
#  'profit': 1598.1966455399997,
#  'relativeProfit': 39.87725518402908,
#  'yearlyProfit': 5779.418924137776,
#  'relativeYearlyProfit': 144.20463457760448,
#  'startPrice': 3699.94,
#  'endPrice': 8551.53,
#  'trades': 34,
#  'startBalance': 4007.79,
#  'exposure': 0.4925674839454903,
#  'sharpe': 13.77354874158137,
#  'downside': -2.5799428969375042,
#  'alpha': 1479.3637502206504}


# visualize backtest
gekko.plot_stats(jdf, profits, figsize=(10,10));

Open the run-backtest notebook to see the visualizations.

Running a Python Strategy in Gekko

1. In Python
   1. implement the Strategy class
   2. register your class with the StratServer
   3. start the StratServer
2. In Gekko
   1. copy the RESTAPI.js strategy into the strategies folder of your Gekko installation
   2. copy the RESTAPI.toml configuration into the config/strageies folder of your Gekko installation
   3. run the strategy from the Gekko UI. Just make sure to adjust the URL to your StratServer and make sure that the last part of the url config field matches the name under which you registered your strategy.

Example

Here's an example of a dummy strategy:

from gekkopy.serving import Strategy, StratServer
import numpy as np


class DummyStrategy(Strategy):
    """ Strategy that creates random advice, just to demo how to implement the
    interface. """

    def __init__(self):
        super().__init__()

    def window_size(self):
        return 5

    def advice(self, data):
        cond = np.ceil(np.sum(data)) % 3
        if cond == 1:
            return self.LONG
        elif cond == 2:
            return self.SHORT
        else:
            return self.HOLD


if __name__ == "__main__":
    dummy_strat = DummyStrategy()
    StratServer.register("dummy", dummy_strat)
    StratServer.start('localhost', port=2626, debug=True)

Now you're ready to give (random) advice!

After running this script, you can use the RESTAPI strategy in Gekko. Make sure to change the last part of the url to dummy.

url = "http://localhost:2626/strats/dummy"  # no trailing slash!

Author

Marius Helf

Source Code

The original sourcecode can be found at https://github.com/mariushelf/gekkopy.