Thanks Per-Olof No, it has more to do with the issue raised here: https://github.com/Sleepingwell/DjangoRpyDemo/blob/master/README.md#django-configuration
Possibly Celery could solve that (?) but I really would like to hear from someone who actually has a production configuration set up and working. Perhaps there are less people in the sciences using Django than I thought... Derek On Tuesday, 23 April 2013 21:32:12 UTC+2, Per-Olof Åstrand wrote: > > I am not sure I understand your question, but is it really related to > using specifically R? Could it be any kind of heavy number-crunching that > needs to be done in the background by a scheduler/task manager? In that > case, django-celery may be an option: > http://docs.celeryproject.org/en/latest/index.html > > Per-Olof > > On Monday, April 22, 2013 9:26:05 PM UTC+2, Derek wrote: >> >> Based on googling around this topic, it seems that using RPy2 is the most >> common way to interface with R from Python. However all the discussions on >> this seem to centre around working in a desktop (single user) environment. >> >> The one discussion I could find that deals with the issue of working with >> R "at scale" is this one - >> https://github.com/Sleepingwell/DjangoRpyDemo/blob/master/README.md#django-configuration >> >> - which indicates problems with this approach; and suggests it might be >> able to be overcome via creating distinct processes dedicated to run a WSGI >> application (although this article does not give any steps on how to do >> this, or whether it would work in practice). >> >> Another approach seems to be to use RPy2, with Twisted to enable multiple >> sessions: >> https://docs.google.com/presentation/d/11LJxej6jnbYKzJftpDudYFfVKjaB0BhOzrBSKaxJ2ME/edit#slide=id.p >> . >> >> Yet another approach might be to use Rserve ( >> http://www.rforge.net/Rserve/) and PyRserve ( >> http://pythonhosted.org/pyRserve/manual.html), but the latter seems to >> currently be in beta. >> >> Question is: does anyone have any practical experience actually using >> Django with R in a production environment (i.e dozens or hundreds of users >> doing high volume number crunching)? >> >> Thanks >> Derek >> >> PS Yes, we do need R and not one of the Python-based alternatives, as R >> offers many routines simply not available in those as yet (also, the client >> needs to re-use, and create new, R scripts themselves) >> > -- You received this message because you are subscribed to the Google Groups "Django users" group. To unsubscribe from this group and stop receiving emails from it, send an email to [email protected]. To post to this group, send email to [email protected]. Visit this group at http://groups.google.com/group/django-users?hl=en. For more options, visit https://groups.google.com/groups/opt_out.
