I don't know if the parallel approach would work or not, but a
possibly simpler approach would be to use the tclTaskSchedule function
from the tcltk package. You could use this to schedule your update
code to run on a regular basis, then you have access to the command
line between times that it runs.
You just need to be careful, if you are accessing a data object at the
same time that the update code runs on that same object, then there
could be problems.
On Thu, Oct 13, 2016 at 12:02 AM, K. Elo <mailli...@pp.inet.fi> wrote:
> Dear all,
>
> I am currently working a research project on social media interaction. As a
> part of this project, mostly for teaching purposes, I should develop a
> R-based approach for real-time visualisation of streamed data (from
> Twitter).
>
> My idea is simple (and working :) ): A Python-script stream Twitter for
> selected keywords/hashtags/users and redirects the output as JSON in a text
> file. My R-script reads the new entries from this text file every 5-10
> minutes, process the input and updates network and other graphical
> presentations.
>
> Thus far everything is working fine. However, I would like to have the
> possibility to work with my data when my script is sleeping. I just wonder
> whether a simple 'mcparallel({ Sys.sleep(300); TRUE})' (from 'parallel')
> would solve my problem? Or is there something I have to take into account
> when using 'parallel'?
>
> My R environment runs on Linux, so forking should work...
>
> Best regrads and thanks in advance,
> Kimmo
>
> --
> Åbo Akademi University, Finland
> Dep. for German studies
>
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--
Gregory (Greg) L. Snow Ph.D.
538...@gmail.com
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