Python Backtrader - Metaquotes MQL5 - API

Development state: first stable release.

Working in production on Debian 10.

About the Project
Installation
Documentation
Usage
License

About the Project

This is the Backtrader part of the project. MQL5 side of this project is located here: MQL5 - JSON - API

In development:

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Installation

pip install backtrader
pip install pyzmq
Check if the ports are free to use. (default:15555,15556, 15557,15558)

Documentation

See MQL5 - JSON - API documentation for better understanding.

You can create market or pending order with the default backtrader command.

self.buy_order = self.buy(size=0.1, price=1.11, exectype=bt.Order.Limit)

If you want to cancel it.

self.cancel(self.buy_order)

When you use bracket orders, one order with stops will be created on the MQL5 side.

self.buy_order = self.buy_bracket(limitprice=1.13, stopprice=1.10, size=0.1, exectype=bt.Order.Market)

If you want to cancel bracket orders, you shold cancel only the first one.

self.cancel(self.buy_order[0])

Usage

Live trading example

import backtrader as bt
from backtradermt5.mt5store import MTraderStore
from datetime import datetime, timedelta


class SmaCross(bt.SignalStrategy):

    def __init__(self):
        self.buy_order = None
        self.live_data = False

    def next(self):
        if self.buy_order is None:
            self.buy_order = self.buy_bracket(limitprice=1.13, stopprice=1.10, size=0.1, exectype=bt.Order.Market)

        if self.live_data:
            cash = self.broker.getcash()

		 # Cancel order
		 if self.buy_order is not None:
			  self.cancel(self.buy_order[0])

        else:
            # Avoid checking the balance during a backfill. Otherwise, it will
            # Slow things down.
            cash = 'NA'

        for data in self.datas:
            print(f'{data.datetime.datetime()} - {data._name} | Cash {cash} | O: {data.open[0]} H: {data.high[0]} L: {data.low[0]} C: {data.close[0]} V:{data.volume[0]}')

    def notify_data(self, data, status, *args, **kwargs):
        dn = data._name
        dt = datetime.now()
        msg = f'Data Status: {data._getstatusname(status)}'
        print(dt, dn, msg)
        if data._getstatusname(status) == 'LIVE':
            self.live_data = True
        else:
            self.live_data = False

cerebro = bt.Cerebro()
cerebro.addstrategy(SmaCross)

store = MTraderStore()

# comment next 2 lines to use backbroker for backtesting with MTraderStore
broker = store.getbroker(use_positions=True)
cerebro.setbroker(broker)

start_date = datetime.now() - timedelta(minutes=500)

data = store.getdata(dataname='EURUSD', timeframe=bt.TimeFrame.Ticks,
                     fromdate=start_date) #, useask=True, historical=True)
                     # the parameter "useask" will request the ask price insetad if the default bid price

cerebro.resampledata(data,
                     timeframe=bt.TimeFrame.Seconds,
                     compression=30
                     )

cerebro.run(stdstats=False)
cerebro.plot(style='candlestick', volume=False)

Download CSV data

You can instruct MT5 to download historical data as a CSV file. Files will be saved into the local Metatrader 5 Terminal installation folder:

[MT5 Terminal]/MQL/Files/Data

The example below downloads data for the past 6 months as tick data.

from datetime import datetime, timedelta
from backtradermql5.mt5store import MTraderStore
import backtrader as bt

store = MTraderStore(host='192.168.1.20') # Metatrader 5 running on a diffenet host

start_date = datetime.now() - timedelta(months=6)

cerebro = bt.Cerebro()
data2 = store.getdata(dataname='EURUSD',
                      timeframe=bt.TimeFrame.Ticks,
                      fromdate=start_date
                      )

cerebro.run(stdstats=False)

Using MT5 Indicators and drawing to MT5 charts

MT5 Inidcators

You can use any MT5 indicator directly from Backtrader via the MTraderIndicator class.

    def __init__(self, store):
        self.mt5macd = getMTraderIndicator(
            # MTraderStorestore instance
            store,
            # Data stream to run the indicator calculations on
            self.datas[0],
            # Set accessor(s) for the indicator output
            ("macd", "signal",),
            # MT5 inidicator name
            indicator="Examples/MACD",
            # Indicator parameters.
            # Any omitted values will use the defaults as defind by the indicator
            params=[12, 26, 9, "PRICE_CLOSE"],
        )()

    def next(self):
        print(f"MT5 indicator Examples/MACD: {self.mt5macd.signal[0]} {self.mt5macd.macd[0]}")

For a fully working example of a Strategy refer to example.py.

Drawing to charts

You can open and draw directly to a chart in MT5 vial the MTraderChart class.

    def __init__(self, store):
        chart = MTraderChart(data_obj=self.datas[0])
        self.bb = btind.BollingerBands(self.data)
        chart.addline(self.bb.top, style={
                      "shortname": "BT-BollingerBands", "linelabel": "Top", "color": "clrBlue"})