pymt5adapter: A developer friendly wrapper for MetaTrader5

nicholish en 2020.04.17 16:57 #1

Context manager:

The main pattern for MetaTrader5 scripts in python is:

mt5.initialize()
#user code
mt5.shutdown()

The challenge is if the user code throws an exception then shutdown() won't be reached.

mt5.initialize()
err = 1 / 0
# ZeroDivisionError
# shutdown not called

pymt5adapter overcomes this challenge by implementing this login in a context manager, thus ensuring that no matter what, shutdown is always called.

import pymt5adapter as mt5

with mt5.connected(debug_logging=True):
    x = 1 / 0

# MT5 connection has been initialized.
# [shutdown()][(1, 'Success')]
# MT5 connection has been shutdown.
# Traceback (most recent call last):
#   File "C:/Users/user/AppData/Roaming/JetBrains/PyCharm2020.1/scratches/mt5.py", line 37, in <module>
#     x = 1 / 0
# ZeroDivisionError: division by zero

The context manager can also modify the behavior of the API. With one simple flag, the entire API can raise exceptions instead of the default behavior of failing silently.

import pymt5adapter as mt5

with mt5.connected(raise_on_errors=True) as conn:
    try:
        invalid = mt5.history_deals_get('sdfasdf', 'sdfadd')
    except mt5.MT5Error as e:
        print('Errors are raised globally for each function')
        print('Error code =', e.error_code)
        print('Error description =', e.description)
    conn.raise_on_errors = False
    invalid = mt5.history_deals_get('sdfasdf', 'sdfadd')
    print(invalid)
    print("Default behavior toggled at runtime. No Exceptions Raised.")

# Errors are raised globally for each function
# Error code = ERROR_CODE.INVALID_PARAMS
# Error description = Invalid arguments('sdfasdf', 'sdfadd'){}
# ()
# Default behavior toggled at runtime. No Exceptions Raised.

See builtin docs for more info on params available for the context manager.

Example script:

import pymt5adapter as mt5
import pandas as pd


def main():
    s = pd.Series(mt5.account_info()._asdict(), name='AccountInfo')
    print(s)

if __name__ == '__main__':
    with mt5.connected():
        main()

nicholish en 2020.05.31 00:18 #2

socket stream server for MT5

import argparse
import asyncio
import json

import pymt5adapter as mta

API_FUNCS = mta.get_function_dispatch()


async def handle_api(reader, writer):
    data = await reader.read(1000)
    message = data.decode()
    try:
        req = json.loads(message)
        func = API_FUNCS[req['function']]
        args = req.get('args', [])
        kwargs = req.get('kwargs', {})
        response = func(*args, **kwargs)
        res = dict(error=mta.mt5_last_error(), response=response)
    except Exception as e:
        res = dict(error=[-1, f'{type(e).__name__} {e.args[0]}'], response=None)
    res = json.dumps(res)
    writer.write(res.encode())
    await writer.drain()
    writer.close()


async def main():
    server = await asyncio.start_server(handle_api, '127.0.0.1', 8888)
    addr = server.sockets[0].getsockname()
    print('Serving on {}:{}'.format(*addr))
    async with server:
        await server.serve_forever()


if __name__ == '__main__':
    parser = argparse.ArgumentParser(description='Socket server for MT5 API')
    parser.add_argument('--path', type=str, help='Absolute path to the terminal64.exe')
    parser.add_argument('--login', type=int, help='Account number')
    parser.add_argument('--password', type=str, help='Account password')
    parser.add_argument('--server', type=str, help='Name of the trade server eg. "MetaQuotes-Demo"')
    parser.add_argument('--portable', action='store_true', default=None,
                        help='Will launch the terminal in portable mode if this flag is set')
    ns = parser.parse_args()
    kw = vars(ns)
    val_states = [v is not None for v in kw.values()]
    if any(val_states) and not all(val_states):
        print(ns)
        raise Exception('Missing commandline arguments.')
    mt5_connected = mta.connected(
        ensure_trade_enabled=True,
        native_python_objects=True,
        raise_on_errors=True,
        **kw
    )
    with mt5_connected:
        asyncio.run(main())

Example python client. (can be anything that uses sockets and JSON)

import asyncio
import json


async def socket_client(message):
    reader, writer = await asyncio.open_connection('127.0.0.1', 8888)
    print(f'Send: {message!r}')
    writer.write(message.encode())
    data = await reader.read()
    data = data.decode()
    writer.close()
    return json.loads(data)


if __name__ == '__main__':
    req = json.dumps({
        'function': 'copy_rates_from_pos',
        'kwargs'  : {
            'symbol'   : 'EURUSD',
            'timeframe': 1,
            'start_pos': 1,
            'count'    : 1000
        },
    })
    res = asyncio.run(socket_client(req))
    print(str(res)[:100])
    errno, strerr = res['error']
    if errno == 1:
        rates = res['response']
        print(len(rates))

Terrence Brannon 2020.06.19 20:27 #3

Thanks for this code. I was able to get pending orders implemented using it:

https://gist.github.com/metaperl/dc728891166963661ad6f66e80db2de5

I do have few questions/comments:

- I added a .pips() method because I think in pips not points - perhaps such a method could be added to the Symbol class?

- How should one test for successful execution of a method? Should I simply see if the retcode is 10009?

Again, thanks a lot. I was struggling with the vanilla MT5 interface. But it kicks serious butt over the old ways of doing things in MT4!

Create pending orders in Python MT5 via pymt5adapter

gist.github.com

Create pending orders in Python MT5 via pymt5adapter - mt5_pending_order.py

Trade Failed Due to My code is not How to get data

nicholish en 2020.06.21 20:00 #4

Terrence Brannon:

- I added a .pips() method because I think in pips not points - perhaps such a method could be added to the Symbol

Thanks for the kind words. I like your idea about adding a tick calculator to the Symbol class. I added an explicit function titled "tick_calc" to the Symbol class because you will always want to use Symbol.trade_tick_size for calculations, however, if you prefer you can sublclass and alias tick_calc to pips quite easily.

Declaration:

    def tick_calc(self, price: float, num_ticks: int):
        """Calculate a new price by number of ticks from the price param. The result is normalized to the
        tick-size of the instrument.

        :param price: The price to add or subtract ticks from.
        :param num_ticks: number of ticks. If subtracting ticks then this should be a negative number.
        :return: A new price adjusted by the number of ticks and normalized to tick-size.
        """
        return self.normalize_price(price + num_ticks * self.trade_tick_size)

Alias:

class MySymbol(Symbol):
    pips = Symbol.tick_calc

Usage:

    symbol = MySymbol('EURUSD')
    # alt constructor
    order = Order.as_buy_limit(
        volume=symbol.volume_min,
        expiration=mta.ORDER_TIME.DAY,
        symbol=symbol.name, )
    # call the object directly "callable object"
    order(magic=12345, comment="python")
    # set properties directly
    order.price = symbol.pips(symbol.bid, -10)
    order.sl = symbol.pips(order.price, -100)
    order.tp = symbol.pips(order.price, +100)
    res = order.send()

Make sure you update pymt5adapter

pip install -U pymt5adapter

function to return order [ARCHIVE]Any rookie question, so Discussion of article ""New

nicholish en 2020.06.21 21:09 #5

Terrence Brannon:

- How should one test for successful execution of a method? Should I simply see if the retcode is 10009?

I would recommend that you use logging and the pymt5adapter.TRADE_RETCODE enum class. The new version of pymt5adapter includes a major upgrade with regards to logging. The API logging is set by the "logger" param in the connected context manager. The logger param excepts a logging.Logger instance (you can define your own) or you can get the recommended Logger instance using the pymt5adapter.get_logger function, or you can pass in a path to the loggin file and the program will return a logging.Logger with loglevel set to logging.INFO.

Example:

import logging
from pathlib import Path

import pymt5adapter as mta
from pymt5adapter.order import Order
from pymt5adapter.symbol import Symbol


class MySymbol(Symbol):
    pips = Symbol.tick_calc


def main(conn):
    print(conn.ping())
    print(conn.terminal_info)
    symbol = MySymbol('EURUSD')
    # alt constructor
    order = Order.as_buy_limit(
        volume=symbol.volume_min,
        expiration=mta.ORDER_TIME.DAY,
        symbol=symbol.name, )
    # call the object directly "callable object"
    order(magic=12345, comment="python")
    # set properties directly
    order.price = symbol.pips(symbol.bid, -10)
    order.sl = symbol.pips(order.price, -100)
    order.tp = symbol.pips(order.price, +100)
    res = order.send()
    retcode = mta.TRADE_RETCODE(res.retcode)
    if retcode is mta.TRADE_RETCODE.DONE:
        print('done')
    else:
        print('trade error', mta.trade_retcode_description(retcode))

    try:
        print(1 / 0)
    except ZeroDivisionError as e:
        conn.logger.error(mta.LogJson(e, {
            'type'     : 'exception',
            'exception': {
                'type'   : type(e).__name__,
                'message': str(e)
            }
        }))
        raise


if __name__ == '__main__':
    print(mta.__version__)
    print(mta.__author__)
    desktop = Path.home() / 'Desktop'
    logger = mta.get_logger(loglevel=logging.DEBUG, path_to_logfile=desktop / 'example_mt5.log', time_utc=True)
    mt5_connected = mta.connected(
        path=desktop / 'terminal1/terminal64.exe',
        portable=True,
        server='MetaQuotes-Demo',
        login=18237468,
        password='kjhfdslk',
        timeout=5000,
        logger=logger,
        ensure_trade_enabled=True,
        raise_on_errors=True,
    )
    with mt5_connected as conn:
        main(conn)

Which will result in a logfile of:

2020-06-21 21:03:41,857 INFO    Terminal Initialize Success     {"type":"terminal_connection_state","state":true}
2020-06-21 21:03:41,858 INFO    Init TerminalInfo       {"type":"init_terminal_info","terminal_info":{"community_account":false,"community_connection":false,"connected":true,"dlls_allowed":false,"trade_allowed":true,"tradeapi_disabled":false,"email_enabled":false,"ftp_enabled":false,"notifications_enabled":false,"mqid":false,"build":2497,"maxbars":100000000,"codepage":0,"ping_last":147583,"community_balance":0.0,"retransmission":0.47393364928909953,"company":"MetaQuotes Software Corp.","name":"MetaTrader 5","language":"English","path":"C:\\Users\\nicho\\Desktop\\Terminal1","data_path":"C:\\Users\\nicho\\Desktop\\Terminal1","commondata_path":"C:\\Users\\nicho\\AppData\\Roaming\\MetaQuotes\\Terminal\\Common"}}
2020-06-21 21:03:41,870 INFO    Init AccountInfo        {"type":"init_account_info","account_info":{"login":7658765,"trade_mode":0,"leverage":100,"limit_orders":200,"margin_so_mode":0,"trade_allowed":true,"trade_expert":true,"margin_mode":2,"currency_digits":2,"fifo_close":false,"balance":1000000.0,"credit":0.0,"profit":0.0,"equity":1000000.0,"margin":0.0,"margin_free":1000000.0,"margin_level":0.0,"margin_so_call":50.0,"margin_so_so":30.0,"margin_initial":0.0,"margin_maintenance":0.0,"assets":0.0,"liabilities":0.0,"commission_blocked":0.0,"name":"nicholishen","server":"MetaQuotes-Demo","currency":"USD","company":"MetaQuotes Software Corp."}}
2020-06-21 21:03:41,876 DEBUG   Function Debugging: symbol_info {"type":"function_debugging","latency_ms":0.322,"last_error":[1,"Success"],"call_signature":{"function":"symbol_info","args":["EURUSD"],"kwargs":{}}}
2020-06-21 21:03:41,876 DEBUG   Function Debugging: symbol_info_tick    {"type":"function_debugging","latency_ms":0.174,"last_error":[1,"Success"],"call_signature":{"function":"symbol_info_tick","args":["EURUSD"],"kwargs":{}}}
2020-06-21 21:03:42,033 DEBUG   Function Debugging: order_send  {"type":"function_debugging","latency_ms":155.543,"last_error":[1,"Success"],"call_signature":{"function":"order_send","args":[{"action":5,"magic":12345,"volume":0.01,"price":1.11791,"sl":1.11691,"tp":1.11891,"type":2,"expiration":1,"comment":"python"}],"kwargs":{}}}
2020-06-21 21:03:42,034 INFO    Order Request: BUY_LIMIT        {"type":"order_request","request":{"action":5,"magic":12345,"order":0,"symbol":"EURUSD","volume":0.01,"price":1.11791,"stoplimit":0.0,"sl":1.11691,"tp":1.11891,"deviation":0,"type":2,"type_filling":0,"type_time":0,"expiration":1,"comment":"python","position":0,"position_by":0}}
2020-06-21 21:03:42,035 INFO    Order Response: DONE    {"type":"order_response","latency_ms":155.543,"response":{"retcode":10009,"deal":0,"order":634208352,"volume":0.01,"price":0.0,"bid":0.0,"ask":0.0,"comment":"Request executed","request_id":7,"retcode_external":0}}
2020-06-21 21:03:42,035 ERROR   division by zero        {"type":"exception","exception":{"type":"ZeroDivisionError","message":"division by zero"}}
2020-06-21 21:03:42,036 CRITICAL        UNCAUGHT EXCEPTION: division by zero    {"type":"exception","last_error":[1,"Success"],"exception":{"type":"ZeroDivisionError","message":"division by zero"}}
2020-06-21 21:03:42,036 INFO    Terminal Shutdown       {"type":"terminal_connection_state","state":false}

Which can be easily parsed using python:

import logging
from pathlib import Path

import dateutil.parser as dp
import pandas as pd

try:
    import ujson as json
except ImportError:
    import json


class LogLine:
    def __init__(self, log_line):
        time, loglevel, short_message, json_dump, *crap = log_line.split('\t')
        self.time = dp.parse(time)
        self.loglevel = self.loglevel_mapped(loglevel)
        self.short_message = short_message
        self.json_dump = json.loads(json_dump)

    def loglevel_mapped(self, loglevel):
        return getattr(logging, loglevel, None)


def iter_json(path_to_logfile):
    p = Path(path_to_logfile)
    with p.open() as f:
        for line in f:
            try:
                yield LogLine(line)
            except Exception as e:
                print(e)


if __name__ == '__main__':
    logfile = Path.home() / 'Desktop/testinglog.log'
    function_calls = []
    for line in iter_json(logfile):
        d = line.json_dump
        if d['type'] == 'function_debugging':
            function_calls.append({'latency_ms': d.get('latency_ms'), **d['call_signature']})

    df = pd.DataFrame(function_calls).groupby('function').mean()
    df = df[df['latency_ms'] >= 0.5]
    print(df)

Result dataframe

                   latency_ms
function                     
copy_rates           0.503000
history_deals_get    7.749205
order_send          51.148026
symbols_get         20.833088
terminal_info        9.934125

Send order in MetaTrader5 MetaTrader5.symbols_get() returns always NoneType Get Last Candlestick Info

nicholish en 2020.06.23 17:49 #6

pymt5adapter release 0.4.3

pip install -U pymt5adapter

fixed bug with Python 3.6 compatibility
fixed bug in Order.as_sell constructor
enhanced logging capabilities

Blessing Dumbura 2020.11.15 22:07 #7

Thanks for your python wrapper. It will help me transition from using MQL to Python.

shay ronen 2020.11.26 10:49 #8

nice going, I also developed a new drag and drop able to use python metatrader4 and metatrader5.

easy to set up, lot's of features!

Dilip Rajkumar 2022.03.29 15:38 #9

Hi, I want to know if we can call built-in MQL5 functions via python or with this pymt5adapter?

For example: I want to call this ChartScreenShot MQL5 function from python to take screenshot of the chart whenever a new position is initiated and read the saved image in the local folder of from mql5.com cloud image repository?

Documentation on MQL5: Chart Operations / ChartScreenShot

www.mql5.com

ChartScreenShot - Chart Operations - MQL5 Reference - Reference on algorithmic/automated trading language for MetaTrader 5

Roffild's Library how to get the In Python MT5, how

Fernando Carreiro 2022.03.29 16:13 #10

Dilip Rajkumar #: Hi, I want to know if we can call built-in MQL5 functions via python or with this pymt5adapter? For example: I want to call this ChartScreenShot MQL5 function from python to take screenshot of the chart whenever a new position is initiated and read the saved image in the local folder of from mql5.com cloud image repository?

No, you can only access the functions provided by the standard MetaTrader 5 Python Integration API, not the MQL5 functionality. For that you will have to write it in MQL5.