multiprocessing

问题 I'm struggling for some time to improve the execution time of this piece of code. Since the calculations are really time-consuming I think that the best solution would be to parallelize the code. The output could be also stored in memory, and written to a file afterwards. I am new to both Python and parallelism, so I find it difficult to apply the concepts explained here and here. I also found this question, but I couldn't manage to figure out how to implement the same for my situation. I am

问题 This question already has answers here : Closed 7 years ago . Possible Duplicate: Keyboard Interrupts with python's multiprocessing Pool Python's multiprocessing module has something called Pool http://docs.python.org/library/multiprocessing.html#module-multiprocessing.pool While a pool of processes is operating, I can't get the script to terminate using KeyboardInterrupt i.e Ctrl + c. The pool spawns new processes and the only way to get out is ctrl + z followed by killing them manually.

问题 Supposing I have a very big text file consisting of many lines that I would like to reverse. And I don't care of the final order. The input file contains Cyrillic symbols. I use multiprocessing to process on several cores. I wrote such program: # task.py import multiprocessing as mp POOL_NUMBER = 2 lock_read = mp.Lock() lock_write = mp.Lock() fi = open('input.txt', 'r') fo = open('output.txt', 'w') def handle(line): # In the future I want to do # some more complicated operations over the line

问题 I wrote a simple parallel python program import multiprocessing as mp import time def test_function(i): print("function starts" + str(i)) time.sleep(1) print("function ends" + str(i)) if __name__ == '__main__': pool = mp.Pool(mp.cpu_count()) pool.map(test_function, [i for i in range(4)]) pool.close() pool.join() What I expect to see in the output: function starts0 function starts2 function starts1 function starts3 function ends1 function ends3 function ends2 function ends0 What I actually see

问题 I saw a "similar" post Executing MySQL SELECT * query in parallel, buy my question is different, and this has not been answered either, so i guess its not a duplicate. I am trying to do a MySQL select request in parallel. The reason is because i need the response fast. I managed to create the request when i paralleled the connection as well, but as the connection takes more time then the actual select it would be faster to connect one time, and do the select in parallel. My approach: import

问题 I saw a "similar" post Executing MySQL SELECT * query in parallel, buy my question is different, and this has not been answered either, so i guess its not a duplicate. I am trying to do a MySQL select request in parallel. The reason is because i need the response fast. I managed to create the request when i paralleled the connection as well, but as the connection takes more time then the actual select it would be faster to connect one time, and do the select in parallel. My approach: import

问题 I went down a journey of "How much performance can I squeeze out of a Python web-server?" This lead me to AIOHTTP and uvloop. Still, I could see that AIOHTTP wasn't using my CPU to its full potential. I set out to use multiprocessing with AIOHTTP. I learned that there's a Linux kernel feature that allows multiple processes to share the same TCP port. This lead me to develop the following code (Which works wonderfully): import asyncio import os import socket import time from aiohttp import web

问题 I went down a journey of "How much performance can I squeeze out of a Python web-server?" This lead me to AIOHTTP and uvloop. Still, I could see that AIOHTTP wasn't using my CPU to its full potential. I set out to use multiprocessing with AIOHTTP. I learned that there's a Linux kernel feature that allows multiple processes to share the same TCP port. This lead me to develop the following code (Which works wonderfully): import asyncio import os import socket import time from aiohttp import web

问题 I want the user to be able to pause an execution of the multiprocessing at any given time after the was started.How to achieve it? my code is : # -*- coding: utf-8 -*- from PySide import QtCore, QtGui from Ui_MainWindow import Ui_MainWindow from queue import Queue import sys import multiprocessing, os, time def do_work(): print ('Work Started: %d' % os.getpid()) time.sleep(1) return 'Success' def manual_function(job_queue, result_queue): while not job_queue.empty(): try: job = job_queue.get

问题 I am confused on the different terms as to their actual differences. What are each of them and what do they actually mean? My IT teacher at school gives us one definition the one day, and another the next, so please can you shed some light for me. Thanks. 回答1: A thread is a sequence of program instructions that are executed by the machine. We call a program multi-threaded when a single execution of the program has more than one thread. Multi-threading can be simulated on a single-processor