multiprocessing

问题 Let me start with thank you for taking the time for reading this. First off I would like to start to share my code, see blow. It is around 200 lines of code but most of the lines are property definitions. Some context: I am just trying to get a beter understanding of multiprocessing so I went and made a small project to try and run multiple processes which all share a single input and output queue. It works, but sometimes it deadlocks right after calling the scheduler.start() method. I am

问题 I have a function which I want to map to a list in parallel. I achieved the task by using multiprocess module. However, when I want to run this task with multiprocessing module, it seems that the processes has spawn but none of them start working. The function and configuration of multiprocess module is as follow: import pandas as pd my_file = pd.read_csv('my_file.txt') from datetime import date, timedelta start_dates = [] for i in range(17): today = date.today() - timedelta(days = i) start

问题 I'm creating my first app, and I've found this problem with Kivy: When I use multiprocessing in a Kivy app, the processes I created are immune to ".terminate()". Same code, but outside an app, works fine. What am I doing wrong? Here I attach some code: from kivy.app import App from kivy.lang import Builder from kivy.uix.screenmanager import Screen import multiprocessing import time from plyer import tts kv = Builder.load_file("testup.kv") class TestScreen(Screen): def speech(self): for i in

问题 I'm trying to reduce a list of names, and in order to perform this I'm using the fuzzywuzzy library. I perform two for loops, both over all the names. If the two names have a fuzzy match score between the 90 and the 100, Then I rewrite the second name with the first name. Here is an example of my dataset, data . nombre 0 VICTOR MORENO MORENO 1 SERGIO HERNANDEZ GUTIERREZ 2 FRANCISCO JAVIER MUÑOZ LOPEZ 3 JUAN RAYMUNDO MORALES MARTINEZ 4 IVAN ERNESTO SANCHEZ URROZ And here is my function: def

问题 I have the following function that I would like to run using multiprocessing: def bruteForcePaths3(paths, availableNodes): results = [] #start by taking each combination 2 at a time, then 3, etc for i in range(1,len(availableNodes)+1): print "combo number: %d" % i currentCombos = combinations(availableNodes, i) for combo in currentCombos: #get a fresh copy of paths for this combiniation currentPaths = list(paths) currentRemainingPaths = [] # print combo for node in combo: #determine better

问题 #!/usr/bin/env python3.5 import multiprocessing, time def testfuncxx(num): time.sleep(num) print(num pool = multiprocessing.Pool(processes=3) ) for i in range(10): #testfuncxx(i) #print(i, '=======') pool.apply_async(testfuncxx, args=(i,)) pool.close() pool.join() 回答1: Since I can only test on Windows, the code works when I enclose the code in a if __name__ == '__main__' entry-point protection. More details here. In general, including this protection is recommended in the multiprocessing

问题 Below is my code my function receives data blocks from the server and puts them in a FIFO buffer after which two functions are called in parallel, recvData() #to keep receiving data blocks from the server and put in the FIFO buffer calculate_threshold() #to remove data blocks from the FIFO buffer and perform some calculation, give a real time display on the GUI, and write the result in the file Code import socket import turtle #import timeit import queue import multiprocessing from tkinter

问题 Below is my code my function receives data blocks from the server and puts them in a FIFO buffer after which two functions are called in parallel, recvData() #to keep receiving data blocks from the server and put in the FIFO buffer calculate_threshold() #to remove data blocks from the FIFO buffer and perform some calculation, give a real time display on the GUI, and write the result in the file Code import socket import turtle #import timeit import queue import multiprocessing from tkinter

问题 I'm trying to learn something a little new in each mini-project I do. I've made a Game of Life( https://en.wikipedia.org/wiki/Conway%27s_Game_of_Life ) program. This involves a numpy array where each point in the array (a "cell") has an integer value. To evolve the state of the game, you have to compute for each cell the sum of all its neighbour values (8 neighbours). The relevant class in my code is as follows, where evolve() takes in one of the xxx_method methods. It works fine for conv

问题 I'm struggling to use mock.patch in a multiprocessing environment while without multiprocessing mock.patch works fine. Filename: test_mp.py import multiprocessing import mock def inner(): return sub() def sub(): return "abc" def test_local(): assert inner()=="abc" def test_mp(): with multiprocessing.Pool() as pool: assert pool.apply(inner,args=[])=='abc' def test_mock(): with mock.patch('test_mp.sub', return_value='xxx') as xx: assert inner()=="xxx" xx.assert_called_once() def test_mp_mock():