ejtraderMT 3.0.1

Metatrader API

Python Metatrader DataFrame API 3.0.0

Installation for docker Metatrader 5 Server API

first make sure you have docker installed on your pc

run this command on your terminal or powershell

docker volume create ejtraderMT
docker run -d --restart=always -p 5900:5900 -p 15555:15555 -p 15556:15556 -p 15557:15557 -p 15558:15558 --name ejtraderapi_server -v ejtraderMT:/data sostrader/ejtraderapi_server:stable

Access Metatrader 5 via VNC

download vnc viewer from url below or any other vnc client of your preference:

https://www.realvnc.com/connect/download/viewer/

username: root
password: root

using API withou docker direct to Metrader 5

if you dont want to use docker you can download the expert and install on your Metatrader 5 simple download the folder MQL5 from the link below and install it on the Metatrader https://github.com/traderpedroso/ejtraderMTServer

Installation for Python API module

# for last stable use pip
pip install ejtraderMT -U

or

#for developers attention may contain countless bugs
git clone https://github.com/traderpedroso/ejtraderMT
cd ejtraderMT
python setup.py install

import

from ejtraderMT import Metatrader

Connect Metatrader 5

make sure thesisAPI expert are load on the chart

'''
to change the host IP example Metatrader("192.168.1.100") ou
you can use doman example  "metatraderserverdomain.com"

for you broker time on the Dataframe  Metatrader(localtime=False)
attention local  time is the default for Dataframe index "date"


for real volume for active like WIN futures ou centralized market use Metatrader(real_volume=True)
attention tick volume is the default


to use more than one option just use , example Metatrader(host='hostIP',localtime=True)
'''
api = Metatrader()

Account information

accountInfo = api.accountInfo()
print(accountInfo)
print(accountInfo['broker'])
print(accountInfo['balance'])

History Dataframe Ready

History from Date to Date

# you can add unlimited actives to list  ["EURUSD","GBPUSD","AUDUSD"]
symbol = ["EURUSD"]
timeframe = "M1"
fromDate = "20/02/2021"
toDate = "24/02/2021"

history = api.history(symbol,timeframe,fromDate,toDate)
print(history)
                        open     high      low    close  volume  spread
date
2021-02-21 23:00:00  1.21135  1.21138  1.21131  1.21134     7.0      35
2021-02-21 23:01:00  1.21130  1.21135  1.21130  1.21135     6.0      43
2021-02-21 23:04:00  1.21150  1.21184  1.21134  1.21184    13.0      31
2021-02-21 23:05:00  1.21163  1.21207  1.21148  1.21181    39.0      42
2021-02-21 23:06:00  1.21189  1.21193  1.21182  1.21182    17.0      64
...                      ...      ...      ...      ...     ...     ...
2021-02-24 02:56:00  1.21629  1.21629  1.21590  1.21594    51.0       5
2021-02-24 02:57:00  1.21592  1.21592  1.21574  1.21574    34.0       5
2021-02-24 02:58:00  1.21574  1.21579  1.21572  1.21575    35.0       5
2021-02-24 02:59:00  1.21576  1.21588  1.21573  1.21582    55.0       5
2021-02-24 03:00:00  1.21583  1.21601  1.21578  1.21598    80.0       5

[3104 rows x 6 columns]

History by period unit like 27 candles

# you can add unlimited actives to list  ["EURUSD","GBPUSD","AUDUSD"]
symbol = ["EURUSD"]
timeframe = "M1"
fromDate = 27

history = api.history(symbol,timeframe,fromDate)
print(history)

                        open     high      low    close  volume  spread
date
2021-02-26 19:23:00  1.20846  1.20857  1.20837  1.20856    84.0       5
2021-02-26 19:24:00  1.20855  1.20858  1.20842  1.20847    71.0       5
2021-02-26 19:25:00  1.20846  1.20849  1.20832  1.20845    69.0       5
2021-02-26 19:26:00  1.20844  1.20845  1.20823  1.20833    64.0       5
2021-02-26 19:27:00  1.20833  1.20836  1.20821  1.20834    53.0       5
...                      ...      ...      ...      ...     ...     ...
2021-02-26 22:55:00  1.20721  1.20730  1.20718  1.20719    46.0      13
2021-02-26 22:56:00  1.20718  1.20738  1.20718  1.20731    39.0      12
2021-02-26 22:57:00  1.20730  1.20731  1.20716  1.20717    45.0      18
2021-02-26 22:58:00  1.20716  1.20731  1.20694  1.20704    77.0      16
2021-02-26 22:59:00  1.20702  1.20705  1.20702  1.20704    16.0      37

History for lastest period gread for predict

# you can add unlimited actives to list  ["EURUSD","GBPUSD","AUDUSD"]
symbol = ["EURUSD"]
timeframe = "M1"
fromDate = 27

history = api.history(symbol,timeframe)
print(history)

                        open     high      low    close  volume  spread
date
2021-02-26 19:23:00  1.20846  1.20857  1.20837  1.20856    84.0       5
2021-02-26 19:24:00  1.20855  1.20858  1.20842  1.20847    71.0       5
2021-02-26 19:25:00  1.20846  1.20849  1.20832  1.20845    69.0       5
2021-02-26 19:26:00  1.20844  1.20845  1.20823  1.20833    64.0       5
2021-02-26 19:27:00  1.20833  1.20836  1.20821  1.20834    53.0       5

History for multiple symbols merged dataframe

# you can add unlimited actives to list  ["EURUSD","GBPUSD","AUDUSD"] etc
symbol = ["EURUSD","GBPUSD"]
timeframe = "M1"
fromDate = "20/02/2021"
toDate = "24/02/2021"


history = api.history(symbol,timeframe,fromDate,toDate)
print(history)


                        open     high      low    close  volume  spread  gbpusd_open  gbpusd_high  gbpusd_low  gbpusd_close  gbpusd_volume  gbpusd_spread
date
2021-02-21 23:00:00  1.21135  1.21138  1.21131  1.21134     7.0      35      1.40113      1.40113     1.40110       1.40110            2.0            130
2021-02-21 23:04:00  1.21150  1.21184  1.21134  1.21184    13.0      31      1.40119      1.40119     1.40119       1.40119            1.0            102
2021-02-21 23:05:00  1.21163  1.21207  1.21148  1.21181    39.0      42      1.40174      1.40174     1.40167       1.40168           11.0             61
2021-02-21 23:06:00  1.21189  1.21193  1.21182  1.21182    17.0      64      1.40156      1.40170     1.40132       1.40155           10.0             46
2021-02-21 23:07:00  1.21181  1.21182  1.21180  1.21182     4.0      82      1.40156      1.40156     1.40156       1.40156            1.0             63
...                      ...      ...      ...      ...     ...     ...          ...          ...         ...           ...            ...            ...
2021-02-24 02:56:00  1.21629  1.21629  1.21590  1.21594    51.0       5      1.41833      1.41835     1.41786       1.41800           62.0              8
2021-02-24 02:57:00  1.21592  1.21592  1.21574  1.21574    34.0       5      1.41798      1.41801     1.41765       1.41766           54.0              8
2021-02-24 02:58:00  1.21574  1.21579  1.21572  1.21575    35.0       5      1.41767      1.41789     1.41767       1.41768           64.0              8
2021-02-24 02:59:00  1.21576  1.21588  1.21573  1.21582    55.0       5      1.41769      1.41782     1.41764       1.41769           42.0              9
2021-02-24 03:00:00  1.21583  1.21601  1.21578  1.21598    80.0       5      1.41770      1.41797     1.41746       1.41784           95.0              8

[3097 rows x 12 columns]

Live streaming Price

from ejtraderMT import Metatrader

api = Metatrader()

symbols = ["EURUSD","GBPUSD","AUDUSD"]
timeframe = "TICK"


# stream price
while True:
    price = api.price(symbols,timeframe)
    print(price)

Live streaming events

from ejtraderMT import Metatrader


api = Metatrader()

symbols = ["EURUSD","GBPUSD","AUDUSD"]
timeframe = "TICK"


# stream event
while True:
    event = api.event(symbols,timeframe)
    print(event)

Trading and Orders Manipulation

You can create market or pending order with the commands.

Market Orders

# symbol, volume, stoploss, takeprofit, deviation
api.buy("EURUSD", 0.01, 1.18, 1.19, 5)
api.sell("EURUSD", 0.01, 1.18, 1.19, 5)

Limit Orders

# symbol, volume, stoploss, takeprofit, price, deviation
api.buyLimit("EURUSD", 0.01, 1.17, 1.19, 1.18, 5)
api.sellLimit("EURUSD", 0.01, 1.20, 1.17, 1.19, 5)

Stop Orders

#symbol, volume, stoploss, takeprofit, price, deviation
api.buyStop("EURUSD", 0.01, 1.18, 1.20, 1.19, 5)
api.sellStop("EURUSD", 0.01, 1.19, 1.17, 1.18, 5)

Positions & Manipulation

positions = api.positions()


if 'positions' in positions:
    for position in positions['positions']:
        api.CloseById(position['id'])

Orders & Manipulation

orders = api.order()

if 'orders' in orders:
    for order in orders['orders']:
        api.CancelById(order['id'])

Modify possition

api.positionModify( id, stoploss, takeprofit)

Modify order

api.orderModify( id, stoploss, takeprofit, price)

close by symbol

api.CloseBySymbol("EURUSD")

close particial

# id , volume
api.ClosePartial( id, volume)

If you want to cancel all Orders

api.cancel_all()

if you want to close all positions

api.close_all()

# Project Based and reference thanks for

Ding Li @dingmaotu
https://github.com/dingmaotu/mql-zmq

Nikolai khramkov @khramkov
https://github.com/khramkov/MQL5-JSON-API

New funcion persistent history Data on SQLite Multithrering

for saving to database

from ejtraderMT import Metatrader

api = Metatrader()

symbols = ["EURUSD"] # you can also use combind dataframe = ["EURUSD","GBPUSD","AUDUSD"]
timeframe = "M1"
# saving 20 years of OHLC
fromDate = "01/01/2001"
toDate = "01/01/2021"


api.history(symbol,timeframe,fromDate,toDate,database=True)

# or you could only pass from Date you want to start


"""
you can pull the history and save using only fromDate
its will pull history fromDate till now

api.history(symbol,timeframe,fromDate,database=True)
"""

# example of saving 20 years of M1 OHLC takes around 3 minutes on a 4 core CPU

 30%|█████████████████████████████████▋                              | 2174/7305 [01:10<02:28, 34.60it/s]

Read from Database

from ejtraderMT import Metatrader

api = Metatrader()

symbol = ["EURUSD"]



data = api.history(symbol)

# example reading 20 year of M1 OHLC takes around 2 seconds read more than 7 million canldes
Elapsed run time: 2.041501855 seconds
                        date     open     high      low    close  volume  spread
0        2001-01-01 04:02:00  0.94220  0.94220  0.94220  0.94220     1.0      50
1        2001-01-01 04:03:00  0.94240  0.94240  0.94240  0.94240     1.0      50
2        2001-01-01 10:47:00  0.94250  0.94250  0.94250  0.94250     1.0      50
3        2001-01-01 11:40:00  0.94190  0.94190  0.94190  0.94190     1.0      50
4        2001-01-01 14:45:00  0.93970  0.93990  0.93970  0.93990     3.0      50
...                      ...      ...      ...      ...      ...     ...     ...
7286195  2020-12-31 17:56:00  1.22147  1.22152  1.22147  1.22152    20.0       8
7286196  2020-12-31 17:57:00  1.22152  1.22162  1.22148  1.22157    58.0       8
7286197  2020-12-31 17:58:00  1.22157  1.22167  1.22152  1.22166    77.0       9
7286198  2020-12-31 17:59:00  1.22167  1.22177  1.22154  1.22154   129.0       8
7286199  2020-12-31 18:00:00  1.22156  1.22156  1.22155  1.22155     2.0      11

[7286200 rows x 7 columns]

Future add comming soon

source code for docker server comming soon