Something to Read - Python for Finance: Analyze Big Financial Data -
the blog post (the book)
more to follow ..
Forum on trading, automated trading systems and testing trading strategies
MetaTrader 5 Python User Group - how to use Python in Metatrader
Renat Fatkhullin , 2019.03.13 22:40
We are preparing a MetaTrader 5 module for Python, similar to R.
Like the package for R , we are still testing on simple functions of extracting data from a working copy of the terminal.
How can I test the work:
pip install matplotlib
pip install MetaTrader5
from datetime import datetime
from MetaTrader5 import *
ticks1 = MT5CopyTicksFrom( "EURAUD" , datetime( 2019 , 1 , 28 , 13 ), 10000 , MT5_COPY_TICKS_ALL)
ticks2 = MT5CopyTicksRange( "AUDUSD" , datetime( 2019 , 1 , 27 , 13 ), datetime( 2019 , 1 , 28 , 13 , 1 ), MT5_COPY_TICKS_ALL)
rates1 = MT5CopyRatesFrom( "EURUSD" , MT5_TIMEFRAME_M1, datetime( 2019 , 1 , 28 , 13 ), 1000 )
rates2 = MT5CopyRatesFromPos( "EURRUB" , MT5_TIMEFRAME_M1, 0 , 1000 )
rates3 = MT5CopyRatesRange( "EURPLN" , MT5_TIMEFRAME_M1, datetime( 2019 , 1 , 27 , 13 ), datetime( 2019 , 1 , 28 , 13 ))
print( 'ticks1(' , len(ticks1), ')' )
for val in ticks1[: 10 ]: print(val)
print( 'ticks2(' , len(ticks2), ')' )
for val in ticks2[: 10 ]: print(val)
print( 'rates1(' , len(rates1), ')' )
for val in rates1[: 10 ]: print(val)
print( 'rates2(' , len(rates2), ')' )
for val in rates2[: 10 ]: print(val)
print( 'rates3(' , len(rates3), ')' )
for val in rates3[: 10 ]: print(val)
x_time = [x.time for x in rates2]
y_open = [y.open for y in rates2]
y_close = [y.close for y in rates2]
import matplotlib.pyplot as plt
plt.plot(x_time, y_open, 'g-' )
plt.plot(x_time, y_close, 'r-' )
Later we will add more features and place the package in the public repository of the Python packages so that you can install properly.
Renat Fatkhullin , 2019.03.14 14:54
This is one way integration.
That is, from Python / R you can request data from the MetaTrader 5 terminal. The terminal itself does not know anything about external users and does not transmit anything to them. From the tester all the more.
Integration packages are designed to enable analysts to use market data in their environment.
First post is just the information I collected from this mql5 portal incl the thread started by MQ.And this post #1 (from MQ) should be used as the instruction.
Machine translation from Russian to the English (the discussion is going on with the participation of MQ for example)
MetaTrader 5 R User Group - how to use R in Metatrader
Vladimir Perervenko , 2019.03.15 11:35
From "R or Python" to "R and Python"
Let's look at the different aspects of these languages, what is good and what is not very good in each of them.
Since its release in 1991, Python has become extremely popular and widely used in data processing. Here are some of the reasons for its wide popularity:
The first release of the language was released in 1995 and has since become the de facto standard language for data science. Consists of packages for use in many areas of data science. I will give only a list of tasks that are solved by packages R:
This is a quick and very superficial glance at two languages. Why not use Python and R together?
Vladimir Perervenko , 2019.03.15 11:42
R in Python
PipeR - provides an easy way to access R from Python through pipes. PypeR is also included in the Python package index, which provides a more convenient installation method. PypeR is especially useful when there is no need for frequent interactive data transfers between Python and R. By running R through a pipe, Python gets the flexibility to manage subprocesses, memory management and portability on popular operating system platforms, including Windows, GNU Linux and Mac OS
pyRserve - uses Rserve as an RPC connection gateway. Through such a connection, variables can be set to R from Python, and R functions can be called remotely. R-objects are represented as instances of classes implemented in Python, with R-functions as methods associated with these objects, in some cases.
rpy2 - Performs an embedded R process in Python. It creates a platform that can convert Python objects to R objects, pass them into R functions, and convert the output R data back to Python objects. rpy2 is used more often as it is being actively developed.
Python to R
rJython - this package implements an interface to Python via Jython. It is designed for other packages to be able to embed python code along with R.
rPython is again a package that allows R to invoke Python. It allows you to run Python code, make function calls, assign and retrieve variables from it (not in the repository for R 3.5.2).
SnakeCharmR is a modern, redesigned version of rPython. This is rPython, which uses "jsonlite" and has many improvements over rPython. (not in the repository for R 3.5.2)
PythonInR - makes accessing Python from R very easy by providing functions for interacting with Python from inside R.
reticulate - The package provides a complete set of tools for interaction between Python and R. Of all the above alternatives, this one is the most widely used, especially since it is being actively developed by Rstudio. Reticulate embeds a Python session into an R session, ensuring seamless, high-performance interoperability. The package allows you to reticulate Python code in R, creating a new breed of project that combines two languages.
After finishing the data preparation started in previous posts, I will show how easy it is to use Python packages in R projects using the CatBoost package as an example.
Renat Fatkhullin , 2019.03.15 23:09
The MetaTrader5 package is already available in 32/64 libraries for Python 3.7 and is put in one line.
Renat Fatkhullin , 2019.03.16 01:27
Yes, this is the first quick presentation.
A description of working from R / Python with MetaTrader 5 will be included in the MQL5 documentation .
I am not a coder (and it is not my project).I am just collecting all the information related to this subject (this is the summary thread).Read this post #1 from MetaQuotes.