I recently began a project that consists of running simulations of cells. I am very new to programming and completely new to julia. I have to run this code written in julia. I downloaded the language in the juno bundle found here. I am running windows 8.1. I had previously installed the python anaconda bundle, and later installed python 3.5 because I read that it julia compiled in 3+ versions of python.
The problem is that when I attempt to use the code (use the evaluate or evaluate all commands), none of the files I run make the program do what it is supposed to. Often something is not defined, which I can sometimes fix if I run the files that define whatever wasn't defined, but I also get a bounds error (running the cell test file) and assorted other errors. I know that the code does work if run properly.
My question is: am I handling the code wrong and if so how should I run it, or is there something else going on that I am missing?
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I've created a program that runs in R that I plan on distributing among a lot of other people. Currently the R script is ran completely automatically and behind the scenes with one .sh script which is exactly how it is intended to be. I'm trying to make it so theres no need for client intervention. The R script itself loads the packages and installs them if they aren't present which takes away the task of them installing the packages themselves.
Is there a way I can provide a folder within my Application's folder that they already download that contains R-script and its dependencies so the code can use that location of Rscript to compile and run the R-program I have created. The goal is to be able to download it and run without the need of internet connection to download R and maybe even the programs required packages if possible.
Any help or ideas is appreciated.
I assume that process you want called "creating binary package". Binary is programs (like EXE files) which can run directly on target CPU without any interpreter software (like Python interpreter for python scripts, or Java VM for java applications). I'm not so familiar with packaging of R programs but I found some materials regarding this issue:
1 - Building binary package R
2 - https://seandavi.github.io/post/build-linux-r-binary-packages/
3 - https://support.rstudio.com/hc/en-us/articles/200486508-Building-Testing-and-Distributing-Packages
Second link assumes Linux as target system. Opposite to interpreted languages, binary files often OS dependent (Linux, Windows, or Mac). I, personally, don't know how compatible are packages between Linux systems with different library sets.
Please comment if you find some information misleading, I'll correct the answer.
I want to follow the advice I've read and heard to have both a main library in R_HOME/library and a user library. I'm using W10 on a desktop machine (not important, except that it gives me a name by which to refer to it), and I can't make R use the user library.
I have succeeded in doing that on a W10 laptop: C:/R/R-4.0.2/library contains some 30 recommended packages, and C:/Users/[username]/Documents/R/win-library/4.0 con contains a much larger number of packages in my user library.
As I recall, and as I wrote down when I did an upgrade on a server, all you have to do to create a site-library is to create a directory called C:/R/R-4.0.2/site-library, and R will use that the next time it starts.
To create a user library, create the directory C:/Users/[username]/Documents/R/win-library/4.0.
That seemed to work on my laptop, for I have seemingly a working R library and a user library there.
That seemed to work on the server, too: I have a library and a site-library.
In both cases, .libPaths() shows the same libraries that I see with Dired on the disk.
I tried to do the same thing on the desktop machine, and i can't make it work.
I created a directory C:/Users/[username]/Documents/R/win-library/4.0, restarted R, and ran .libPaths(); the only directory that was listed was C:/R/R-4.0.2/library.
Because I thought the Documents in that path seemed odd, I tried it again using C:/Users/[username]/R/win-library/4.0, still with no success.
https://cran.r-project.org/doc/manuals/r-release/R-admin.html#Managing-libraries seems pertinent, but I'm not sure how to interpret the output of Sys.getenv("R_LIBL_USER). I get "\\[toplevel]\[nextlevel]\Home$\[username]/R/win-library/4.0", which I presume is a long-winded way to get to /Home$/[username]/R/win-library/4.0 (aka C:/Users/[username]/R/win-library/4.0.
Suggestions? I've tried a number of other suggestions from SO, all to no avail.
I have a program that I created with pyinstaller using qt5, I converted the gui file into a py file
So I noticed the problem when I added a function and passed the program to others computers that I have, when I run the program to see that everything is good I found that in almost all the computers runs just fine while in 2 does not run, appears the message
pyinstaller failed to execute script
Just in case I always leave the previous version I created in the computer before deleting them, and I found that the previous version is not working in those computers as well
I generated the file again but now without the --noconsole parameter, and added --debug=all
And the program runs just fine, no errors, nothing so I'm at a loss of what is the problem with the computer
edit:
forgot to mention but im also using Opencv, the program is compiled in python 3.7 and the OS is windows 10 64x
I have two different versions of R installed, one which is up to date and which I use for all my regular R coding (needs to be up to date so that I can use various updated and new packages) and one which I use to access OLAP cubes (needs to be the R Client from Microsoft, because this is the only one which supports the olapR package, and which currently uses R version 3.4.3).
Since, in theory, I only have to access the OLAP cube once a month, I "outsourced" this task to a different RStudio project, in which I download and save the required data for all other projects. Hence, all other projects never require the olapR package to be installed and can and will be run in the up to date R version.
Now, ideally I would like to link my R version to my projects, so that I do not have to change my global R version and restart RStudio every time I access the OLAP cube or work on this data retrieval project (and then switch it back). However, I could not find any options in RStudio to achieve this result.
There are a few threads out there describing the same problem, but with no satisfactory answer in my opinion:
https://support.rstudio.com/hc/en-us/community/posts/200657296-Link-Project-and-R-Version
Rstudio project using different version of R
I also tried looking for a different package than olapR but with similar functionality, but could not find anything except X4R, which seems outdated and does not work for me (https://github.com/overcoil/X4R). Sadly, I am also unable to directly access the databases which the OLAP cube uses for its results, so I cannot go "around" it.
I am happy for any help or suggestions you can offer, whether it is a general workaround to link a project to a specific R version or the (less helpful for the community) solution of accessing the OLAP cube in a different way.
Thanks in advance!
Using the answer from MrGumble I created a .bat file that will execute my .R file using the desired R installation. Even though it is not the answer I thought I would get, I think it is an even better solution to the problem.
For all facing a similar issue, here is the .bat file (never created one before, so also had to google how to do it and I guess some might be in the same position):
#echo off
title Getting data for further processing in R
echo Retrieving OLAP data
echo.
"C:\Program Files\Microsoft\R Client\R_SERVER\bin\Rscript.exe" "C:\Users\me\Documents\Projects\!Data\script.R"
echo.
echo Saved data
echo.
pause
Thanks again to MrGumble for his help.
Skip RStudio.
RStudio is really just an editor (albeit powerful and useful) editor, which starts an R console for you (and the surrounding PATH variables, library locations, etc.).
If your monthly task only requires you to run the R-script (or a bit of interactive work), you can simply execute your preferred version of R from the command line and have it run your R script. E.g.
C:\Users\me>"C:\Program Files (x64)\Microsoft R\bin\Rscript" myscript.R
You might have to define some PATH variables so that the older R doesn't look for packages in the newer R's libraries, but that depends entirely on your current setup.
I've developed a .R script that works with a DB, does a bunch of processing and outputs graphs and tables. I can output that data as comma-separated values and pictures, to later import them on my software, that I have no issue.
The problem is how can I distribute my application without having to make a complete install of R on the client. I've seen things like RJava, but my app is on VB6 (yeah...) and I don't see any libraries, or ways to compile to exe. The compile package only makes compiled versions of any function you define, like what psyco used to do for Python (before Pypy).
Does anyone have some insight on compiling R to avoid having the user to install an entire additional software?
EDIT: Does an R compiler exist? This question relates deeply to mine, but I haven't seen how it can be used to make a full script an exe. You can just compile a main function and cat it to a file? Is that even possible?
The short answer is "no, that will not work".
There simply is no compiler that allows you to shrink-wrap your app. So your best best may be either
using the headless Rserve over the network, or
using the R (D)COM server used by RExcel et al