Is Django a hard and fast requirement? If so, is it just about integrating
the routines? I think otherwise something like RStudio Server would work
for you. I've deployed it previously and it was a pretty nice setup. It's
based on Unix user accounts, so R processes run as if users were running
them on a desktop, except not. You may be able to share code in this
environment too, but I haven't played with it a ton.

http://www.rstudio.com/ide/docs/server/getting_started

-Nick

On Tue, Apr 30, 2013 at 12:06 AM, Derek <[email protected]> wrote:

> " if you write your own R  analysis routines, why have them run in a web
> system"
>
> Two issues here:
>
> 1. We are writing R routines for someone else; who needs 'analysis on
> demand'
> 2. A web system means that multiple users in multiple locations can all
> readily access the same analysis routines (but with different data sets)
>
> I agree that if you work on a desktop, with no need to access shared data
> or use the same analysis routines as anyone else, then a web interface
> makes no sense.
>
> Basically we are trying to harness two disparate systems; each of which is
> very powerful in their own sphere, to create an application that is really
> useful for better and more efficient science.
>
>
> On 29 April 2013 16:59, Javier Guerra Giraldez <[email protected]> wrote:
>
>> On Mon, Apr 29, 2013 at 2:13 AM, Derek <[email protected]> wrote:
>> > hat no one is actually using R in a production environment themselves
>> (which
>> > is a little surprising to me).
>>
>>
>> well R itself is widely used in production... but the intersection
>> with Django is very small.  (after all, if you write your own R
>> analysis routines, why have them run in a web system)
>>
>> --
>> Javier
>>
>
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