Threading the same function for a different result in Python -

i need program execute function in parallel. function branches off different results depending on how user interacts program. have simple gui within module named threadgui.py has 2 options: downloading , uploading. these options create dictionaries containing variables related function. these dictionaries stored in main dictionary stored in thread_test.py module. these work fine when executing 1 after other, when try in parallel goes wrong. threading related code in threadgui.py:

def onstartclick(self):   in thread_test.dictlist.values():        #the main dictionary stored global in thread_test.py      thread = thread(target = thread_test.begin_tests, args = (i, ))      thread.start()   print "thread finished...exiting" 

the above function calls begin_test function within thread_test.py module. function looks so:

def begin_tests(arg):      print arg     print dictlist     dictitem = arg     print dictitem     if dictitem['type'] == "http_downloading":         print "download"     elif dictitem['type'] == "ftp_uploading":         print "upload"     else:         print "invalid input"         sys.exit(1) 

this simplified example of code. problem code executing 1 function out of 2 instead of both. if created dictionary called download, upload, download execute 3 downloads, instead of desired pattern.

the problem not in code posted:

from threading import thread  dictlist = {     'foo': { 'type': 'http_downloading' },     'bar': { 'type': 'ftp_uploading' },     'baz': { 'type': 'http_downloading' } }  def begin_tests(arg):     print arg     print dictlist     dictitem = arg     print dictitem     if dictitem['type'] == "http_downloading":         print "download"     elif dictitem['type'] == "ftp_uploading":         print "upload"     else:         print "invalid input"         sys.exit(1)  def onstartclick(self):   in dictlist.values():        #the main dictionary stored global in thread_test.py      thread = thread(target = begin_tests, args = (i, ))      thread.start()   print "thread finished...exiting"  onstartclick(none) 

results in:

{'type': 'http_downloading'} {'baz': {'type': 'http_downloading'}, 'foo': {'type': 'http_downloading'}, 'bar': {'type': 'ftp_uploading'}} {'type': 'http_downloading'}  {download {'type': 'ftp_uploading'} 'type': 'http_downloading'} {'baz': {'type': 'http_downloading'}, 'foo': {'type': 'http_downloading'}, 'bar': {'type': 'ftp_uploading'}} {'baz': {'type': 'http_downloading'}, 'foo': {'type': 'http_downloading'}, 'bar': {'type': 'ftp_uploading'}}  thread finished...exiting {'type': 'http_downloading'} download {'type': 'ftp_uploading'} upload 

at guess, reusing inner dict.

update:

i think case better solved using worker-pool-and-queue strategy. like:

from queue import queue threading import thread  queue = queue() # replaces dictlist  threads = [] n in range(10):     thread = thread(target = worker, args = (begin_tests, queue, ))     thread.start()     threads.append(thread)  stop = object() def worker(work, queue):     while true:         task = queue.get()         if task stop:             break         work(task)             

use so:

queue.put({ 'type': 'http_downloading' }) queue.put({ 'type': 'ftp_uploading' }) queue.put({ 'type': 'http_downloading' }) queue.put(stop) 

this not in address problem of mutating dicts; has fixed elsewhere. strategy has 2 benefits: preserve order of tasks , not risk losing tasks: dict makes limited concurrency guarantees, whereas queue() guaranteed thread-safe.