ejtraderMT 3.0.8

Metatrader API

EjtraderMT Python Metatrader 5 API

Install stable version using pip

pip install ejtraderMT -U

From source code

for developers attention may contain countless bugs

git clone https://github.com/traderpedroso/ejtraderMT
cd ejtraderMT
python setup.py install

Runing Metatrader 5 on Docker or windows machine

Easy way is using docker make sure to have docker runing on your machine

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 ejtraderMT -v ejtraderMT:/data ejtrader/metatrader:5

or docker compose

version: '3.8'
services:
  app:
    container_name: metatrader
    image: ejtrader/metatrader:5
    restart: unless-stopped
    ports:
      - '5900:5900'
      - '15555:15555'
      - '15556:15556'
      - '15557:15557'
      - '15558:15558'
    volumes:
      - ejtraderMT:/data
 
      
volumes:
  ejtraderMT: {}

Dockerfile and source for Docker wine vnc github

Access Metatrader 5 via VNC

download VNC VIEWER or any other vnc client of your preference: Download

username: root
password: root

harder way installing direct to your Metatrader 5 on Windows Machine

First download MQL5 source code and install it on the Metatrader 5 github

second download and install Microsoft Visual C++ 2015 Download

import

from ejtraderMT import Metatrader

Connect Metatrader 5

make sure ejtraderMT 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 local time on the Dataframe  Metatrader(tz_local=True)
attention utc 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',tz_local=True)
'''
api = Metatrader()

Account information

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

Economic Calendar

symbol = "EURUSD"
fromDate = "20/08/2021"
toDate = "24/08/2022"

calendar = api.calendar(symbol,fromDate,toDate)
print(calendar)

	              currency	impact	event	country	actual	forecast	previous
date							
2021-08-20 06:00:00	EUR	2	PPI m/m(ppi-mm)	Germany(DE)	1.9	0.9	1.3
2021-08-20 06:00:00	EUR	1	PPI y/y(ppi-yy)	Germany(DE)	10.4	9.4	8.5
2021-08-20 17:00:00	USD	2	Baker Hughes US Oil Rig Count(baker-hughes-us-...	United States(US)	405	None	397
2021-08-20 17:00:00	USD	2	Baker Hughes US Total Rig Count(baker-hughes-u...	United States(US)	503	None	500
2021-08-20 19:30:00	EUR	1	CFTC EUR Non-Commercial Net Positions(cftc-eur...	European Union(EU)	57.6 K	None	33.9 K
...	...	...	...	...	...	...	...
2022-08-24 14:30:00	USD	1	EIA Heating Oil Stocks Change(eia-heating-oil-...	United States(US)	0.845 M	-0.013 M	0.249 M
2022-08-24 14:30:00	USD	1	EIA Gasoline Stocks Change(eia-gasoline-stocks...	United States(US)	-0.027 M	-1.829 M	-4.642 M
2022-08-24 14:30:00	USD	1	EIA Refinery Crude Oil Daily Inputs Change(eia...	United States(US)	-0.168 M	None	-0.158 M
2022-08-24 14:30:00	USD	1	EIA Refinery Utilization Rate Change(eia-refin...	United States(US)	0.3	None	-0.8
2022-08-24 17:00:00	USD	1	5-Year Note Auction(5-year-note-auction)	United States(US)	3.23	None	2.86

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.orders()

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

economic calendar
level 1 for futures only
level 2 for futures only