MQL5 ReferencePython Integration

MetaTrader module for integration with Python

MQL5 is designed for the development of high-performance trading applications in the financial markets and is unparalleled among other specialized languages used in the algorithmic trading. The syntax and speed of MQL5 programs are very close to C++, there is support for OpenCL and integration with MS Visual Studio. Statistics, fuzzy logic and ALGLIB libraries are available as well. MetaEditor development environment features native support for .NET libraries with "smart" functions import eliminating the need to develop special wrappers. Third-party C++ DLLs can also be used. C++ source code files (CPP and H) can be edited and compiled into DLL directly from the editor. Microsoft Visual Studio installed on user's PC can be used for that.

Python is a modern high-level programming language for developing scripts and applications. It contains multiple libraries for machine learning, process automation, as well as data analysis and visualization.

MetaTrader package for Python is designed for convenient and fast obtaining of exchange data via interprocessor communication directly from the MetaTrader 5 terminal. The data received this way can be further used for statistical calculations and machine learning.

Installing the package from the command line:

pip install MetaTrader5

Updating the package from the command line:

pip install --upgrade MetaTrader5

Functions for integrating MetaTrader 5 and Python

Function	Action
initialize	Establish a connection with the MetaTrader 5 terminal
login	Connect to a trading account using specified parameters
shutdown	Close the previously established connection to the MetaTrader 5 terminal
version	Return the MetaTrader 5 terminal version
last_error	Return data on the last error
account_info	Get info on the current trading account
terminal_Info	Get status and parameters of the connected MetaTrader 5 terminal
symbols_total	Get the number of all financial instruments in the MetaTrader 5 terminal
symbols_get	Get all financial instruments from the MetaTrader 5 terminal
symbol_info	Get data on the specified financial instrument
symbol_info_tick	Get the last tick for the specified financial instrument
symbol_select	Select a symbol in the MarketWatch window or remove a symbol from the window
market_book_add	Subscribes the MetaTrader 5 terminal to the Market Depth change events for a specified symbol
market_book_get	Returns a tuple from BookInfo featuring Market Depth entries for the specified symbol
market_book_release	Cancels subscription of the MetaTrader 5 terminal to the Market Depth change events for a specified symbol
copy_rates_from	Get bars from the MetaTrader 5 terminal starting from the specified date
copy_rates_from_pos	Get bars from the MetaTrader 5 terminal starting from the specified index
copyrates_range	Get bars in the specified date range from the MetaTrader 5 terminal
copy_ticks_from	Get ticks from the MetaTrader 5 terminal starting from the specified date
copy_ticks_range	Get ticks for the specified date range from the MetaTrader 5 terminal
orders_total	Get the number of active orders.
orders_get	Get active orders with the ability to filter by symbol or ticket
order_calc_margin	Return margin in the account currency to perform a specified trading operation
order_calc_profit	Return profit in the account currency for a specified trading operation
order_check	Check funds sufficiency for performing a required trading operation
order_send	Send a request to perform a trading operation.
positions_total	Get the number of open positions
positions_get	Get open positions with the ability to filter by symbol or ticket
history_orders_total	Get the number of orders in trading history within the specified interval
history_orders_get	Get orders from trading history with the ability to filter by ticket or position
history_deals_total	Get the number of deals in trading history within the specified interval
history_deals_get	Get deals from trading history with the ability to filter by ticket or position

Example of connecting Python to MetaTrader 5

Download the latest version of Python 3.8 from https://www.python.org/downloads/windows
When installing Python, check "Add Python 3.8 to PATH%" to be able to run Python scripts from the command line.
Install the MetaTrader 5 module from the command line

pip install MetaTrader5

Add matplotlib and pandas packages

pip install matplotlib
pip install pandas

Launch the test script

from datetime import datetime
import matplotlib.pyplot as plt
import pandas as pd
from pandas.plotting import register_matplotlib_converters
register_matplotlib_converters()
import MetaTrader5 as mt5

# connect to MetaTrader 5
if not mt5.initialize():
print("initialize() failed")
mt5.shutdown()

# request connection status and parameters
print(mt5.terminal_info())
# get data on MetaTrader 5 version
print(mt5.version())

# request 1000 ticks from EURAUD
euraud_ticks = mt5.copy_ticks_from("EURAUD", datetime(2020,1,28,13), 1000, mt5.COPY_TICKS_ALL)
# request ticks from AUDUSD within 2019.04.01 13:00 - 2019.04.02 13:00
audusd_ticks = mt5.copy_ticks_range("AUDUSD", datetime(2020,1,27,13), datetime(2020,1,28,13), mt5.COPY_TICKS_ALL)

# get bars from different symbols in a number of ways
eurusd_rates = mt5.copy_rates_from("EURUSD", mt5.TIMEFRAME_M1, datetime(2020,1,28,13), 1000)
eurgbp_rates = mt5.copy_rates_from_pos("EURGBP", mt5.TIMEFRAME_M1, 0, 1000)
eurcad_rates = mt5.copy_rates_range("EURCAD", mt5.TIMEFRAME_M1, datetime(2020,1,27,13), datetime(2020,1,28,13))

# shut down connection to MetaTrader 5
mt5.shutdown()

#DATA
print('euraud_ticks(', len(euraud_ticks), ')')
for val in euraud_ticks[:10]: print(val)

print('audusd_ticks(', len(audusd_ticks), ')')
for val in audusd_ticks[:10]: print(val)

print('eurusd_rates(', len(eurusd_rates), ')')
for val in eurusd_rates[:10]: print(val)

print('eurgbp_rates(', len(eurgbp_rates), ')')
for val in eurgbp_rates[:10]: print(val)

print('eurcad_rates(', len(eurcad_rates), ')')
for val in eurcad_rates[:10]: print(val)

#PLOT
# create DataFrame out of the obtained data
ticks_frame = pd.DataFrame(euraud_ticks)
# convert time in seconds into the datetime format
ticks_frame['time']=pd.to_datetime(ticks_frame['time'], unit='s')
# display ticks on the chart
plt.plot(ticks_frame['time'], ticks_frame['ask'], 'r-', label='ask')
plt.plot(ticks_frame['time'], ticks_frame['bid'], 'b-', label='bid')

# display the legends
plt.legend(loc='upper left')

# add the header
plt.title('EURAUD ticks')

# display the chart
plt.show()

Get data and chart

[2, 'MetaQuotes-Demo', '16167573']
[500, 2325, '19 Feb 2020']

euraud_ticks( 1000 )
(1580209200, 1.63412, 1.63437, 0., 0, 1580209200067, 130, 0.)
(1580209200, 1.63416, 1.63437, 0., 0, 1580209200785, 130, 0.)
(1580209201, 1.63415, 1.63437, 0., 0, 1580209201980, 130, 0.)
(1580209202, 1.63419, 1.63445, 0., 0, 1580209202192, 134, 0.)
(1580209203, 1.6342, 1.63445, 0., 0, 1580209203004, 130, 0.)
(1580209203, 1.63419, 1.63445, 0., 0, 1580209203487, 130, 0.)
(1580209203, 1.6342, 1.63445, 0., 0, 1580209203694, 130, 0.)
(1580209203, 1.63419, 1.63445, 0., 0, 1580209203990, 130, 0.)
(1580209204, 1.63421, 1.63445, 0., 0, 1580209204194, 130, 0.)
(1580209204, 1.63425, 1.63445, 0., 0, 1580209204392, 130, 0.)
audusd_ticks( 40449 )
(1580122800, 0.67858, 0.67868, 0., 0, 1580122800244, 130, 0.)
(1580122800, 0.67858, 0.67867, 0., 0, 1580122800429, 4, 0.)
(1580122800, 0.67858, 0.67865, 0., 0, 1580122800817, 4, 0.)
(1580122801, 0.67858, 0.67866, 0., 0, 1580122801618, 4, 0.)
(1580122802, 0.67858, 0.67865, 0., 0, 1580122802928, 4, 0.)
(1580122809, 0.67855, 0.67865, 0., 0, 1580122809526, 130, 0.)
(1580122809, 0.67855, 0.67864, 0., 0, 1580122809699, 4, 0.)
(1580122813, 0.67855, 0.67863, 0., 0, 1580122813576, 4, 0.)
(1580122815, 0.67856, 0.67863, 0., 0, 1580122815190, 130, 0.)
(1580122815, 0.67855, 0.67863, 0., 0, 1580122815479, 130, 0.)
eurusd_rates( 1000 )
(1580149260, 1.10132, 1.10151, 1.10131, 1.10149, 44, 1, 0)
(1580149320, 1.10149, 1.10161, 1.10143, 1.10154, 42, 1, 0)
(1580149380, 1.10154, 1.10176, 1.10154, 1.10174, 40, 2, 0)
(1580149440, 1.10174, 1.10189, 1.10168, 1.10187, 47, 1, 0)
(1580149500, 1.10185, 1.10191, 1.1018, 1.10182, 53, 1, 0)
(1580149560, 1.10182, 1.10184, 1.10176, 1.10183, 25, 3, 0)
(1580149620, 1.10183, 1.10187, 1.10177, 1.10187, 49, 2, 0)
(1580149680, 1.10187, 1.1019, 1.1018, 1.10187, 53, 1, 0)
(1580149740, 1.10187, 1.10202, 1.10187, 1.10198, 28, 2, 0)
(1580149800, 1.10198, 1.10198, 1.10183, 1.10188, 39, 2, 0)
eurgbp_rates( 1000 )
(1582236360, 0.83767, 0.83767, 0.83764, 0.83765, 23, 9, 0)
(1582236420, 0.83765, 0.83765, 0.83764, 0.83765, 15, 8, 0)
(1582236480, 0.83765, 0.83766, 0.83762, 0.83765, 19, 7, 0)
(1582236540, 0.83765, 0.83768, 0.83758, 0.83763, 39, 6, 0)
(1582236600, 0.83763, 0.83768, 0.83763, 0.83767, 21, 6, 0)
(1582236660, 0.83767, 0.83775, 0.83765, 0.83769, 63, 5, 0)
(1582236720, 0.83769, 0.8377, 0.83758, 0.83764, 40, 7, 0)
(1582236780, 0.83766, 0.83769, 0.8376, 0.83766, 37, 6, 0)
(1582236840, 0.83766, 0.83772, 0.83763, 0.83772, 22, 6, 0)
(1582236900, 0.83772, 0.83773, 0.83768, 0.8377, 36, 5, 0)
eurcad_rates( 1441 )
(1580122800, 1.45321, 1.45329, 1.4526, 1.4528, 146, 15, 0)
(1580122860, 1.4528, 1.45315, 1.45274, 1.45301, 93, 15, 0)
(1580122920, 1.453, 1.45304, 1.45264, 1.45264, 82, 15, 0)
(1580122980, 1.45263, 1.45279, 1.45231, 1.45277, 109, 15, 0)
(1580123040, 1.45275, 1.4528, 1.45259, 1.45271, 53, 14, 0)
(1580123100, 1.45273, 1.45285, 1.45269, 1.4528, 62, 16, 0)
(1580123160, 1.4528, 1.45284, 1.45267, 1.45282, 64, 14, 0)
(1580123220, 1.45282, 1.45299, 1.45261, 1.45272, 48, 14, 0)
(1580123280, 1.45272, 1.45275, 1.45255, 1.45275, 74, 14, 0)
(1580123340, 1.45275, 1.4528, 1.4526, 1.4528, 94, 13, 0)

DXRelease

initialize