[Bioc-devel] Docker granularity: containers for individual R packages, running on a normal R installation?

[Martin Morgan]

On 04/14/2015 01:17 PM, Wolfgang Huber wrote:
> Dear Sean
> I understand the second point. As for .Call not being the right paradigm, then maybe some other method invocation mechanism? In essence, my question is whether someone already has figured out whether new virtualisation tools can help avoid some of the tradtional Makeovers/configure pain.

The part of your question that challenged me was to 'run under a “normal”, 
system-installed R', for which I don't have any meaningful help to offer. 
Probably the following is not what you were looking for...

There was no explicit mention of this in Sean's answer, so I'll point to

   http://bioconductor.org/help/docker/

A more typical use is that R is on the docker container, maybe starting the 
docker container in such a way that you have access to your non-docker file system.

I might run the devel version of R / Bioc (the devel version was a bit stale 
recently; I'm not sure if it is updated) with

   docker run -ti bioconductor/devel_sequencing R

(the first time this will be painful, but the second time instantaneous). The 
image comes with all the usual tools (e.g., compilers) and all of the packages 
with a 'Sequencing' biocViews; most additional packages can be installed w/out 
problem.

If there were complex dependencies, then one might start with one of the simpler 
containers, add the necessary dependencies, save the image, and distribute it, 
as outlined at

   http://bioconductor.org/help/docker/#modifying-the-images

I bet that many of the common complexities are already on the image. A fun 
alternative to running R is to run RStudio Server on the image, and connect to 
it via your browser

   docker run -p 8787:8787 bioconductor/devel_base

(point your browser to http://localhost:8787 and log in with username/password 
rstudio/rstudio).

I guess this also suggests a way to interact with some complicated docker-based 
package from within R on another computer, serving the package up as some kind 
of a web service.

Martin

> Wolfgang
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>> On Apr 14, 2015, at 13:52 GMT+2, Sean Davis <seandavi at gmail.com> wrote:
>>
>> Hi, Wolfgang.
>>
>> One way to think of docker is as a very efficient, self-contained virtual machine.  The operative term is "self-contained".  The docker containers resemble real machines from the inside and the outside.  These machines can expose ports and can mount file systems, but something like .Call would need to use a network protocol, basically.  So, I think the direct answer to your question is "no".
>>
>> That said, there is no reason that a docker container containing all complex system dependencies for the Bioc build system, for example, couldn't be created with a minimal R installation.  Such a system could then become the basis for further installations, perhaps even package-specific ones (though those would need to include all R package dependencies, also).  R would need to run INSIDE the container, though, to get the benefits of the installed complex dependencies.
>>
>> I imagine Dan or others might have other thoughts to contribute.
>>
>> Sean
>>
>>
>> On Tue, Apr 14, 2015 at 7:23 AM, Wolfgang Huber <whuber at embl.de> wrote:
>> Is it possible to ship individual R packages (that e.g. contain complex, tricky to compile C/C++ libraries or other system resources) as Docker containers (or analogous) so that they would still run under a “normal”, system-installed R. Or, is it possible to provide a Docker container that contains such complex system dependencies such that a normal R package can access it e.g. via .Call ?
>>
>> (This question exposes my significant ignorance on the topic, I’m still asking it for the potential benefit of a potential answer.)
>>
>> Wolfgang
>>
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>
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