python-multithreading

I am trying to do some plotting in parallel to finish large batch jobs quicker. To this end, I start a thread for each plot I plan on making. I had hoped that each thread would finish its plotting and close itself (as I understand it, Python closes threads when they get through all the statements in run()). Below is some code that shows this behavior. If the line that creates a figure is commented out, it runs as expected. Another plausibly helpful tidbit is that it also runs as expected when you only spawn one thread. import matplotlib.pyplot as plt import time import Queue import threading

I am using the I/O non-blocking python server Tornado. I have a class of GET requests which may take a significant amount of time to complete (think in the range of 5-10 seconds). The problem is that Tornado blocks on these requests so that subsequent fast requests are held up until the slow request completes. I looked at: https://github.com/facebook/tornado/wiki/Threading-and-concurrency and came to the conclusion that I wanted some combination of #3 (other processes) and #4 (other threads). #4 on its own had issues and I was unable to get reliable control back to the ioloop when there was

I am trying to write a method that counts down to a given time and unless a restart command is given, it will execute the task. But I don't think Python threading.Timer class allows for timer to be cancelable. import threading def countdown(action): def printText(): print 'hello!' t = threading.Timer(5.0, printText) if (action == 'reset'): t.cancel() t.start() I know the above code is wrong somehow. Would appreciate some kind guidance over here. Honest Abe You would call the cancel method after you start the timer: import time import threading def hello(): print "hello, world" time.sleep(2) t

Say I have a very large list and I'm performing an operation like so: for item in items: try: api.my_operation(item) except: print 'error with item' My issue is two fold: There are a lot of items api.my_operation takes forever to return I'd like to use multi-threading to spin up a bunch of api.my_operations at once so I can process maybe 5 or 10 or even 100 items at once. If my_operation() returns an exception (because maybe I already processed that item) - that's OK. It won't break anything. The loop can continue to the next item. Note : this is for Python 2.7.3 First, in Python, if your code