multiprocessing

问题 When you supply a large-enough object into multiprocessing.Queue , the program seems to hang at weird places. Consider this minimal example: import multiprocessing def dump_dict(queue, size): queue.put({x: x for x in range(size)}) print("Dump finished") if __name__ == '__main__': SIZE = int(1e5) queue = multiprocessing.Queue() process = multiprocessing.Process(target=dump_dict, args=(queue, SIZE)) print("Starting...") process.start() print("Joining...") process.join() print("Done") print(len

问题 I'm running the following code from multiprocessing import Pool def loop_f(x, num_loops): for i in range(num_loops): f(x) return def f(x): result = 0 for i in range(x): result = result*i return result x = 200000 num_times=200 for i in range(8): p = Pool(i +1) print(i+1) %time res=p.map(f, [x]*num_times) Now when I run this code I see that the performance improvement stops after the 4th process Timing when using 1 processes CPU times: user 9.08 ms, sys: 13.4 ms, total: 22.5 ms Wall time: 1.17

问题 I'm adding Flask support to a plugin-based application. On startup, the app instantiates a number of plugin classes. I thought this would be as simple as having Flask kick off when the class is initialized, but instead, the whole app hangs when it hits the Flask startup method. Consider the following example: #!/usr/bin/env python from flask import Flask class TestClass: def __init__(self): print('Initializing an instance of TestClass') self.app = Flask(__name__) self.app.run() print("Won't

问题 The idea im trying to run is this: RUN 3 Processes doing calculation ONCE one of the 3 processes finishes the task KILL others imediatly and continue with the main task, i can't let it run any second longer The things i've tried was: Putting the global variable through multiprocessing.manager, but that still lets processes finish their loops. Raising an exception OS: Windows PYTHON: 2.7 def f(name): Doing = True try: while Doing: print 'DOING',name somecodethatmarksDoingAsFalse() except

问题 Given a list() of running multiprocessing.Process -instances, how can I join on all of them and return as soon as one exits without a Process.join -timeout and looping? Example from multiprocessing import Process from random import randint from time import sleep def run(): sleep(randint(0,5)) running = [ Process(target=run) for i in range(10) ] for p in running: p.start() How can I block until at least one Process in p exits? What I don't want to do is: exit = False while not exit: for p in

问题 I am trying to create a independent process to handle my image acquire from camera. But multiprocessing seems to have difficulty pickling videocapture module from opencv. Can anyone suggest a work around ? I am using python 3.7.1 from multiprocessing import Process import multiprocessing as mp import time import logging import logging.handlers import sys import logging from enum import Enum import cv2 class Logger(): @property def logger(self): component = "{}.{}".format(type(self).__module__

问题 import time from multiprocessing import Process start = time.perf_counter() def sleep(): print('Sleeping 1 second(s)...') time.sleep(1) return 'Done Sleeping...' p1 = Process(target = sleep) p2 = Process(target = sleep) p1.start() p2.start() p1.join() p2.join() finish = time.perf_counter() print(f'Finished in {round(finish-start, 2)} second(s)') output: Finished in 0.17 second(s) I tried to use multiprocessing, but when I run the code it`s over in 0.17~ seconds and not 1 as it supposed to be,

问题 import time from multiprocessing import Process start = time.perf_counter() def sleep(): print('Sleeping 1 second(s)...') time.sleep(1) return 'Done Sleeping...' p1 = Process(target = sleep) p2 = Process(target = sleep) p1.start() p2.start() p1.join() p2.join() finish = time.perf_counter() print(f'Finished in {round(finish-start, 2)} second(s)') output: Finished in 0.17 second(s) I tried to use multiprocessing, but when I run the code it`s over in 0.17~ seconds and not 1 as it supposed to be,

问题 import time from multiprocessing import Process start = time.perf_counter() def sleep(): print('Sleeping 1 second(s)...') time.sleep(1) return 'Done Sleeping...' p1 = Process(target = sleep) p2 = Process(target = sleep) p1.start() p2.start() p1.join() p2.join() finish = time.perf_counter() print(f'Finished in {round(finish-start, 2)} second(s)') output: Finished in 0.17 second(s) I tried to use multiprocessing, but when I run the code it`s over in 0.17~ seconds and not 1 as it supposed to be,

问题 So I'm trying to use multiprocessing Manager on a dict of dicts, this was my initial try: from multiprocessing import Process, Manager def task(stat): test['z'] += 1 test['y']['Y0'] += 5 if __name__ == '__main__': test = Manager().dict({'x': {'X0': 10, 'X1': 20}, 'y': {'Y0': 0, 'Y1': 0}, 'z': 0}) p = Process(target=task, args=(test,)) p.start() p.join() print(test) of course when I run this, the output is not what I expect, z updates correctly while y is unchanged! This is the output: {'x': {