python - Virtual environment in R? -

python - Virtual environment in R? -

i've found several posts best practice, reproducibility , workflow in r, example:

how increment longer term reproducibility of research (particularly using r , sweave) complete substantive examples of reproducible research using r

one of major preoccupations ensuring portability of code, in sense moving new machine (possibly running different os) relatively straightforward , gives same results.

coming python background, i'm used concept of virtual environment. when coupled simple list of required packages, goes way ensuring installed packages , libraries available on machine without much fuss. sure, it's no guarantee - different oses have own foibles , peculiarities - gets 95% of way there.

does such thing exist within r? if it's not sophisticated. illustration maintaining plain text list of required packages , script install missing?

i'm start using r in earnest first time, in conjunction sweave, , ideally start in best way possible! thoughts.

i'm going utilize comment posted @cboettig in order resolve question.

packrat

packrat dependency management scheme r. gives 3 of import advantages (all of them focused in portability needs)

isolated : installing new or updated bundle 1 project won’t break other projects, , vice versa. that’s because packrat gives each project own private bundle library.

portable: transport projects 1 computer another, across different platforms. packrat makes easy install packages project depends on.

reproducible: packrat records exact bundle versions depend on, , ensures exact versions ones installed wherever go.

what's next?

walkthrough guide: http://rstudio.github.io/packrat/walkthrough.html

most mutual commands: http://rstudio.github.io/packrat/commands.html

using packrat rstudio: http://rstudio.github.io/packrat/rstudio.html

limitations , caveats: http://rstudio.github.io/packrat/limitations.html

r python