I have successfully created a threading example of a thread which can update a Progressbar as it goes.However doing the same thing with multiprocessing has so far eluded me.
I am completely new to multiprocessing. I have been reading documentation about multiprocessing module. I read about Pool, Threads, Queues etc. but I am completely lost.
In short, say I have the following: import multiprocessing class Worker(multiprocessing.Process): def __init__(self):
Similar to another post I made, this answers that post and creates a new question. Recap:I need to update every record in a spatial database in which I have a data set of points that overlay data set
I have a Python program that has several processes (for now only 2) and threads (2 per process). I would like to catch every exception and especially shut down my program cleanly on Ctrl+c but I can\'
I\'m building a queueing system that passes a message from one process to another via a stack implemented in mongodb with capped_collections and tailable cursors.
I am trying to parallelize some work, which runs on my mac (Pyton 3.2.2 under Mac OS 10.7) but gives the following error on a Linux cluster I run it where I got 4 cores and access Python 3.2. The erro
I access a Linux cluster where resources are allocated using LSF, which I think is a common tool and comes from Scali (http://www.scali.com/workload-management/high-performance-computing). In an inter
I try to use Pool from the multiprocessing module to speed up reading in large csv files. For this, I adapted an example (from py2k), but it seems like the csv.dictreader object has no length. Does it
I have a class that contains a (large) number of different properties, including a few dictionaries.When I pass an instance of the class through to a new process, all of the numeric values seem to get
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