algorithmic modeling for Rhino
Hello David,
Great new update and now a dedicated group!
I have been experimenting with pack unpack data. It opens great possibilities for collaboration.
the case study was 2 users working packing-unpacking from the same directory. for example first user working on landscape contours 2nd user working on the resulting mesh from these contours.
First user packing data with a button updating the data when necessary and the second user having the unpack data component with a timer, upacking data at an interval.
It works really great. As the definition of the 2nd user gets bigger, at some point timer makes things laggy. Also 2nd user gets unexpected solution triggers because of 1st user saves.
Do you see any workaround for this ?
Maybe something like needs reloading (xrefs like) in order to bypass the timer completely and inform the second user that data has changed?
Best
alex
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Hi Alex-
Thanks for testing!
Yes I can see how anytime the second user tried to load while the file was being actively saved would create an issue. I have to think about this a bit...having the timer in place is an interesting idea. The ideal would be that if the file was in use when the timer pinged, you'd keep the old output, but maybe the component would give a yellow warning and complain that the file was inaccessible at the time. I think I can do that...
Ah what you describe would be another case. it never happened to have synchronized save and load but in rare case this could happen too.
using the the timer, the two main issues are that when someone packs, the unpacker gets suddenly a new canvas recompute solution, because of the new data and the second is that timer makes definitions laggy when they are more complex.
that is why i was wondering if the timer could be completely bypassed and perhaps have the unpack component go yellow (data has changed flag, or needs reloading) when the packer saves data.
cheers
alex
I see...a flag to let the user know that new data has been loaded. I haven't worked with event listeners before, but this could be a good opportunity to have a look.
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