Re: [igraph] Re: Re: Callback for long metric calculations.

[Tamas Nepusz]

Hi Chris,

> I'm wondering what kind of issues I am going to run in to if I use  
> the processing.Process class from pyprocessing along with the  
> igraph.set_progress_handler method (process memory copy?).
You might try the following:

- spawn a new process with pyprocessing and build a shared queue  
between the parent and the child process (I think the Queue object in  
pyprocessing does exactly this, but I'm not sure, I've never used  
pyprocessing)
- set the progress handler in the child process to put the progress  
report in the queue
- make the parent process regularly poll the queue and print the  
progress report accordingly.

> These are mainly ideas I have brewing about optimizing making  
> multiple calculations. I'm also looking to slap a web interface on  
> it, which can timeout if I make it wait for calculations to finish.
If you are planning to implement a web interface, maybe you'll find  
one of my older side-projects useful; this is a simple HTTP-based  
server-client application where the server maintains a job queue and  
sends the jobs in the queue to the clients that perform the  
calculation, repeatedly report the progress and finally send back the  
result to the server. Job progress can be monitored from any web  
browser that has access to the server. I used that for calculating  
properties of graphs generated according to a given graph model with  
various parameters -- the job description included the parameters  
only, the clients generated the graphs, calculated the necessary  
properties and sent back the results. I have never released it and it  
definitely needs a lot of polishing, but anyway, if it might be useful  
for you, let me know and I'll try to find the source code.

--
Tamas