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'm new to working with Coq, and I'm progressing through the first volume of the Software Foundations book, but I can't for the life of me figure out how to compile the Basics.v file for the second chapter on induction.
I've seen things floating around about using the Coqc command on the command line, but I don't know how to access the terminal, or at least the windows terminal doesn't recognize the command. If anyone could walk me through this it'd be much appreciated!
In case you are using CoqIDE, there is a menu item "Compile/Compile buffer", which creates a .vo file for the currently loaded .v file. For a few files and early stages of learning, this might be the easiest way.
Then SF likely comes with a make file which you can just run with make. You didn't say what OS your are using - on Linux and Mac this should be trivial, on Windows it depends on how you did install Coq. The Windows installer doesn't come with make, but if you used the Coq Platform scripts to setup Coq on Windows, everything is there.
Otherwise it might get a bit complicated - you need to pass the right options to coqc (which CoqIDE and make do automatically for you).
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 got a large data analysis project containing dozens of R scripts that depend in complicated ways on each other and so I thought it would be a good idea to formalize all these dependencies and set the project in a build system that runs things in the correct order and re-runs anything that changes or anything that's downstream from things that change.
But even after some hours worth of googling I haven't found any build systems that are custom-made for R (though there are plenty for more genreal purposes). I've previously worked with waf to organize data analysis projects in Python and know I could use waf to run R scripts as well. But having to manage a whole Python environment just to run some R scripts seems clunky.
What are other people using to solve this problem?
There is a package called "GRANBase" that is capable of doing something similar to what you're referring to. It's an R package management & build tool, so if your scripts are put into R package(s), you could probably make use of it.
I apologize if this has already been asked a different way but I couldn't find anything getting at what I wanted.
I am really getting into R from other packages (SPSS). As I learn about what truly can be done, I realize that there are additional "tools" that I need. This gets me to my question.
What setup do you have for developing R code? I can't see myself actually developing r packages anywhere in the near future, but I do see myself wanting to manage my r projects effeciently, as well as create reports and presentations in LaTeX.
For context, I develop my R code in Eclipse for Windows, but I have had a real hard time successfully setting up Latex/Sweave and Github plugins.
Lastly, do you develop code using Windows or something else?
Many thanks in advance for any insight you can lend.
Emacs has everything I commonly need:
ESS (for R),
AucTeX (for Latex),
similarly rich 'modes' for other languages I use (C++, make, shell, ...),
plus a lot of other modes you get quite used to as e.g. dired for directory/file browsing or org-mode as planner/to-do list,
the SVN integration is very good too
and there are probably a number of tools within Emacs I am now forgetting.
Works in text mode as well as graphical mode, and works essentially the same (incl ESS and AucTeX) on several operating systems (Linux mostly and Windows when I must). On Debian/Ubuntu all this is prepackaged and tends to work out of the box as well. For both Windows and OS X, Vincent Goulet has package very handy bundles, see here.
The 'daemon mode' is outstanding too -- I keep the same main Emacs session running and just connect and re-connect to it even when accessing the machine (via ssh or directly) from different computers.
Also see the EmacsWiki for more tips around Emacs.
Back to Emacs and R in particular. The R FAQ says it pretty well:
6.1 Is there Emacs support for R?
6.2 Should I run R from within Emacs?
and I like the affirmative and resounding answer to the second question: "Yes, definitely". I fully concur.
I'll second the suggestion that Emacs compliments R nicely, but let me share what the "killer feature" is for me.
Using Org-mode with Org-babel, I can write whole reports with inline graphs produced from R in raster and vector format which compiles seamlessly into a PDF report via latex. I can also view the graphs while editing, similar to a WYSIWYG editor.
I just wrapped up a major report with over 70 inline graphs with little effort, no editing external files, no issues maintaining naming between figures in my report and external files, or forgetting to recompile the latest version of a figure. Org & Babel does it all.
Org-mode:
http://orgmode.org/
Org-Babel:
http://orgmode.org/worg/org-contrib/babel/index.php
Example of inline R with Babel and PDF output, see the first example in multiple formats:
http://orgmode.org/worg/org-contrib/babel/languages/ob-doc-R.php
Enjoy!
This is probably more relevant for package development, but it is also worth mentioning the roxygen R package that allows in-source documentation of your code. Note that even though you can't see yourself developing R packages anywhere in the near future, a package can be a very handy way of grouping related functions you develop and maintain, consistently documenting the code and keeping track of updates, even if you do not plan to distribute it.
I use a mac, and my most important tools are:
the command line, for running R
git, for keeping track of changes
github for publishing my code, bug tracking and collaboration
textmate for writing R code
Has anyone tried RStudio? It's the shiny new editor for R.
I use windows... (don't say it).
I like Notepad++ and NPPtoR. Makes it pretty easy to send things back and forth.
I use Eclipse on Windows and Linux. I compile LaTeX code (with Sweave) on Linux and I haven't bothered yet to set up the whole process in Eclipse. I need to pdflatex and bibtex files several times anyway, so I just have a terminal window with the specific string of commands handy. I tried ESS and Eclipse and they're very similar in functionality (and in my opinion the best two editors out there).
I use Eclipse / StatEt on Windows, and it Rocks !. For LaTex/Sweave I use MikTex which works well for me. For help setting things up check out this document and this post.
Other Tools you may find useful include;
If you want to build R Packages on
Windows, then get the RTools
For
Creating Documents, you may want to
check out odfWeave,
LibreOffice (was OpenOffice) and
the MSOffice ODF plugin
I have also
dabbled with Git but also didn't get
very far on Windows, but that was a
while ago.
For Presentations in LaTex
I recomend Beamer
I use Eclipse for both R and Latex while working on research papers. The plugins for both are very mature now. The nice thing is that you don't have to switch application while writing papers. I used different combination before but I found this to be the best.
I just got home from our local R User meeting (find one near you here) and of the 20 or so people there, all of us used a different program or tool to write R code in. I think that goes to show the diversity of the tools used to write and edit R code is just as diverse as the R community itself.