multiprocessing

问题 I've done some research on this and found somewhat similar questions but none answer what I'm really looking for. I understand how to create and use processes with the multiprocessing module. But when I create a new process, I would like to spawn a new console window just for the use of that process, for printing and so on, so that the child processes don't share the parent process's console window. Is there a way of doing that with the multiprocessing module? 回答1: If you're going to spawn a

问题 I'm trying to learn how to use Python's multiprocessing package, but I don't understand the difference between map and imap . Is the difference that map returns, say, an actual array or set, while imap returns an iterator over an array or set? When would I use one over the other? Also, I don't understand what the chunksize argument is. Is this the number of values that are passed to each process? 回答1: That is the difference. One reason why you might use imap instead of map is if you wanted to

问题 I am trying to append values to a list. But, as it's multiprocessing, the list is ending up with just one value finally. Is there a way where I can append sizes of all the images to the list rather than just one? import cv2 import concurrent.futures import os length = [] def multi_proc(image): name = image[0:-4] im = cv2.imread(image) final_im = cv2.resize(im, (100,100)) cv2.imwrite(name+"rs"+".png", final_im) l = im.shape print(l) length.append(l) with concurrent.futures.ProcessPoolExecutor(

问题 Am doing web scraping with python & selenium. I used to scrape data for one location & year at a time, by creating 1800 .py files (600 places * 3 years = 1800) and batch opening 10 at a time and waiting for it to complete. which is time-consuming so I decided to use multiprocessing. I made my code to read places data from a text file and iterate with it. the text file looks like this Aandimadam Aathur_Dindugal Aathur_Salem East Abiramam Acchirapakkam Adayar Adhiramapattinam Alandur

问题 Am doing web scraping with python & selenium. I used to scrape data for one location & year at a time, by creating 1800 .py files (600 places * 3 years = 1800) and batch opening 10 at a time and waiting for it to complete. which is time-consuming so I decided to use multiprocessing. I made my code to read places data from a text file and iterate with it. the text file looks like this Aandimadam Aathur_Dindugal Aathur_Salem East Abiramam Acchirapakkam Adayar Adhiramapattinam Alandur

问题 Is there a way to share a huge dictionary to multiprocessing Subprocesses on windows without duplicating the whole memory? I only need it read-only within the sub-processes, if that helps. My programm roughly looks like this: def workerFunc(args): id, data_mp, some_more_args = args # Do some logic # Parse some files on the disk # and access some random keys from data_mp which are only known after parsing those files on disk ... some_keys = [some_random_ids...] # Do something with do_something

问题 For pool.apply_async() what is the best practice for accumulating the results coming from each process? Is it job.get() or job.wait() ? what about job.ready( ) and job.successful() ? Is it possible to accumulate each result in a global variable in each process, so that we do not end up with one process in S (sleep) mode for a long time trying to accumulate the results coming from each process? import multiprocessing import os import numpy as np def prepare_data_fill_arrays(simNum,chrLong):

问题 I have a question I wasn't really able to solve after doing a little digging, and this is also not my area of expertise so I really don't even know what I'm looking for. I'm wondering if it's possible to "link" together two python shells? This is the actual use case... I am working with a program that has it's own dedicated python shell built into the GUI. When you run commands in the internal python shell, the GUI updates in real-time reflecting the commands you ran. The problem is, the

问题 I trying to test the example at here changing it from threading to multiprocessing. Running this (the original example) in jupyter notebook, will display a progress bar that fills up in some time. import threading from IPython.display import display import ipywidgets as widgets import time progress = widgets.FloatProgress(value=0.0, min=0.0, max=1.0) def work(progress): total = 100 for i in range(total): time.sleep(0.2) progress.value = float(i+1)/total thread = threading.Thread(target=work,

问题 I trying to test the example at here changing it from threading to multiprocessing. Running this (the original example) in jupyter notebook, will display a progress bar that fills up in some time. import threading from IPython.display import display import ipywidgets as widgets import time progress = widgets.FloatProgress(value=0.0, min=0.0, max=1.0) def work(progress): total = 100 for i in range(total): time.sleep(0.2) progress.value = float(i+1)/total thread = threading.Thread(target=work,